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Biology, Volume 14, Issue 3 (March 2025) – 60 articles

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7 pages, 1510 KiB  
Brief Report
Epicardial Adipose Tissue in Arrhythmogenic Cardiomyopathy
by Davide Lapolla, Luca Canovi, Maria Letizia Berloni, Veronica Amantea, Cristina Balla, Federico Marchini, Evelina Faragasso, Matteo Bertini and Elisabetta Tonet
Biology 2025, 14(3), 278; https://doi.org/10.3390/biology14030278 (registering DOI) - 8 Mar 2025
Abstract
Arrhythmogenic cardiomyopathy (ACM) is an inherited heart disease characterized by fibrofatty replacement of the ventricular myocardium, with an estimated prevalence of 1:5000 people in the general population. Sudden cardiac death is the first manifestation of this disease in 16–23% of patients with ACM. [...] Read more.
Arrhythmogenic cardiomyopathy (ACM) is an inherited heart disease characterized by fibrofatty replacement of the ventricular myocardium, with an estimated prevalence of 1:5000 people in the general population. Sudden cardiac death is the first manifestation of this disease in 16–23% of patients with ACM. Fibrofatty infiltration can be identified with noninvasive cardiac magnetic resonance. Studies of epicardial fat deposits have suggested pathogenic roles of epicardial fats in mediating cardiac diseases and arrhythmias. Although myocardial fat infiltration has been well described in ACM, changes in epicardial fat deposits with this disease have not been well investigated. Our study shows that patients with ACM have a higher amount of EAT compared to controls. Additionally, the EAT amount seems to increase with the evolution of the disease. Full article
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<p>A patient with ACM. Black-blood T1-weighted 4-chamber image shows an example of measuring interventricular groove EAT (red line).</p>
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<p>EAT values in the two groups.</p>
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<p>First and 2-year follow-up CMR in a patient with ACM. The two upper images are SSFP 4 chamber sequences showing the EAT measure at the baseline CMR (on the left) and at the 2-year follow-up CMR (on the right). The two lower images are LGE sequences at the baseline CMR (on the left) and at the 2-year follow-up CMR (on the right). The increase in EAT at the 2-year follow-up corresponds to a greater severity of the disease, highlighted by a more extensive LGE (ring-like distribution on the LV and RV free wall involvement).</p>
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18 pages, 4244 KiB  
Article
The T-DBSCAN Algorithm for Stopover Site Identification of Migration Birds Based on Satellite Positioning Data
by Xinwu He, Xiqun Liu, Jiajia Liu, Youwen Li, Zhenggang Xu, Ping Mo and Tian Huang
Biology 2025, 14(3), 277; https://doi.org/10.3390/biology14030277 - 7 Mar 2025
Viewed by 255
Abstract
With the acceleration of social development and urbanization, birds’ natural habitats have been greatly disturbed and threatened. Satellite tracking technology can collect much bird activity data, providing important data support for habitat protection research. However, satellite data are usually characterized by discontinuity, extensive [...] Read more.
With the acceleration of social development and urbanization, birds’ natural habitats have been greatly disturbed and threatened. Satellite tracking technology can collect much bird activity data, providing important data support for habitat protection research. However, satellite data are usually characterized by discontinuity, extensive periods, and inconsistent frequency, which challenges cluster analysis. Habitat research frequently employs clustering techniques, but conventional clustering algorithms struggle to adjust to these data features, particularly when it comes to time dimension changes and irregular data sampling. T-DBSCAN, an enhanced clustering algorithm, is suggested to accommodate this intricate data need. T-DBSCAN is improved based on the traditional DBSCAN algorithm, which combines a quadtree structure to optimize the efficiency of spatial partitioning and introduces a convex hull algorithmic strategy to perform the boundary identification and clustering processing, thus improving the efficiency and accuracy of the algorithm. T-DBSCAN is made to account efficiently for the uniformity of data sampling and changes in the time dimension. Tests demonstrate that the algorithm outperforms conventional habitat identification accuracy and processing efficiency techniques. It can also manage large amounts of discontinuous satellite tracking data, making it a dependable tool for studying bird habitats. Full article
(This article belongs to the Special Issue Bird Biology and Conservation)
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<p>Conceptual explanation diagram of the T-DBSCAN algorithm.</p>
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<p>(<b>A</b>) Schematic diagram of a quadtree. (<b>B</b>) Schematic diagram of bump pack optimization.</p>
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<p>Algorithm flowchart of T-DBSCAN.</p>
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<p>Bean goose satellite positioning tracking. (<b>A</b>) Satellite tracker installation. (<b>B</b>) Satellite tracking location display map.</p>
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<p>Demonstration of habitat distribution. (<b>A</b>) Results of DBSCAN and T-DBSCAN on the map under bean goose data. (<b>B</b>) Results of the two algorithms for the same area (longitude 115.84° to 116.66°, latitude 29.01° to 30.05°).</p>
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<p>The results of the two algorithms in the bean goose data set. (<b>A</b>) Results of the T-DBSCAN. (<b>B</b>) Results of the DBSCAN.</p>
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<p>Compared with the DBSCAN algorithm, the T-DBSCAN algorithm has greater efficiency and accuracy. (<b>A</b>) Comparison of the time consumption of the two algorithms. (<b>B</b>) CH metrics for clustering effects. (<b>C</b>) Number of clusters generated by clustering.</p>
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<p>Defects in the bumper.</p>
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13 pages, 1710 KiB  
Article
A Comparison of Pollination Efficiency Between Wild Bumble Bees and Introduced Honey Bees on Polygonatum cyrtonema
by Ju Tang, Xiang-Xiang Ge, Yu-Jie Xu, Yu Zhang, Jian-Wen Shao and Xiao-Hong Li
Biology 2025, 14(3), 276; https://doi.org/10.3390/biology14030276 - 7 Mar 2025
Viewed by 172
Abstract
To clarify the pollination contributions of introduced honey bees and native wild bees, we compared their pollination efficiency on a perennial herb, Polygonatum cyrtonema Hua. The flower’s traits and bees’ body traits were measured to quantify the mechanical fit between the bee species [...] Read more.
To clarify the pollination contributions of introduced honey bees and native wild bees, we compared their pollination efficiency on a perennial herb, Polygonatum cyrtonema Hua. The flower’s traits and bees’ body traits were measured to quantify the mechanical fit between the bee species and flower. Pollen removal and deposition per visit, visit frequency, and visit duration per flower were investigated. The results show that both native bumble bees (worker bees of Bombus trifasciatus Smith) and introduced honey bees (Apis mellifera L.) are effective pollinators, but bumble bees play a more important role in pollination, due to their higher visit frequency and slightly higher pollen transfer efficiency. The bumble bees removed and deposited significantly more pollen grains per visit than the honey bees (both p < 0.001). The faster visiting speed and shorter visit duration of the bumble bees, combined with their larger body size and longer proboscises, may have contributed to their higher pollen transfer efficiency. The pollination success of P. cyrtonema depends on its pollinators. This study is the first to report on the pollination efficiency of floral visitors on P. cyrtonema. Our findings highlight the importance of conserving native bumble bee populations to ensure the reproductive success of P. cyrtonema. Future studies should focus on their management to minimize potential disruptions to native pollination contribution. Full article
(This article belongs to the Section Conservation Biology and Biodiversity)
15 pages, 1500 KiB  
Review
The Role of Th17/Treg Axis in Retinal Pathology Associated with Diabetes and Treatment Options
by Michel-Edwar Mickael, Norwin Kubick, Kreshnik Miftari, Jarosław Olav Horbańczuk, Atanas G. Atanasov, Korona Binçe, Piotr Religa, Agnieszka Kamińska, Mariusz Sacharczuk and Michał Ławiński
Biology 2025, 14(3), 275; https://doi.org/10.3390/biology14030275 - 7 Mar 2025
Viewed by 166
Abstract
Diabetic retinopathy (DR) is a major complication of diabetes, leading to vision impairment and blindness. The pathogenesis of DR involves multiple factors, including hyperglycemia-induced vascular damage, hypertension, obesity, anemia, immune dysregulation, and disruption of the blood–retinal barrier (BRB). Th17 and Treg cells, two [...] Read more.
Diabetic retinopathy (DR) is a major complication of diabetes, leading to vision impairment and blindness. The pathogenesis of DR involves multiple factors, including hyperglycemia-induced vascular damage, hypertension, obesity, anemia, immune dysregulation, and disruption of the blood–retinal barrier (BRB). Th17 and Treg cells, two types of CD4+ T cells, play opposing roles in inflammation. Th17 cells are pro-inflammatory, producing cytokines such as IL-17A, while Treg cells help suppress immune responses and promote anti-inflammatory effects. Recent studies highlight the importance of the Th17/Treg balance in retinal inflammation and disease progression in DR. Our literature review reveals an imbalance in DR, with increased Th17 activity and reduced Treg function. This shift creates a pro-inflammatory environment in the retina, worsening vascular leakage, neovascularization, and vision loss. The limited infiltration of Treg cells suggests that Th17 cells may uniquely infiltrate the retina by overwhelming or outnumbering Tregs or increasing the expression of recruiting chemokines, rather than only taking advantage of a damaged BRB. Therapeutic strategies, such as neutralizing IL-17A and enhancing Treg function with compounds like IL-35 or curcumin, may reduce inflammation and retinal damage. Restoring the balance between Th17 and Treg cells could provide new approaches for treating DR by controlling inflammation and preventing further retinal damage. Full article
(This article belongs to the Section Medical Biology)
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<p>Th17/Treg axis differentiation. The microenvironment chemokines that dominate the milieu of naïve CD4+ T cells play a crucial role in Th17/Treg differentiation. Interestingly, the presence of TGF-β1 alone promotes Treg differentiation, while TGF-β1 combined with pro-inflammatory cytokines such as IL-1β, IL-6, or IL-23 drives differentiation toward the Th17 lineage.</p>
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<p>Infiltration of Th17 Cells into the blood–retina barrier (BRB) in diabetic retinopathy (DR). In a healthy eye, the retinal layers, comprising epithelial cells, ganglion cells, bipolar cells, rods, and cones, along with the retinal pigment epithelium (RPE), Bruch’s membrane, and choroid, remain intact. We hypothesize that as diabetes mellitus progresses, Tregs (in green) lose their ability to effectively suppress Th17 cells (in gray). As a result, Th17 cells infiltrate the RPE. This is followed by increased expression of IL17 through increased acetylation of IL17 in Th17 cells and possibly in Müller cells. When IL17 binds to its receptor IL-17RC on the surface of photoreceptors and endothelial cells, the Fas mechanism is activated, leading to photoreceptor and endothelial cell apoptosis. Tofacitinib citrate appears to inhibit IL17 function and reduce its associated inflammation.</p>
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<p>Berberine (BBR) is a potential therapy for diabetic retinopathy (DR) through inflammation reduction. C57BL/6 mice were treated with streptozotocin (STZ) to induce diabetes and then fed a high-fat diet, with or without a 5-week BBR treatment. The results published by Yang et al. indicate that BBR reduced the Th17/Treg ratio in the spleen and lymph nodes, decreased inflammatory cytokine expression, and mitigated retinal damage in DR mice.</p>
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21 pages, 682 KiB  
Review
Connecting Bone Remodeling and Regeneration: Unraveling Hormones and Signaling Pathways
by Afshan Mehreen, Muhammad Faisal, Bilal Zulfiqar, Deli Hays, Kavishka Dhananjaya, Faiza Yaseen and Yujun Liang
Biology 2025, 14(3), 274; https://doi.org/10.3390/biology14030274 - 7 Mar 2025
Viewed by 91
Abstract
Recent advancements in tissue engineering and stem cell science have positioned bone disease treatment as a promising frontier in regenerative medicine. This review explores the hormonal and signaling pathways critical to bone regeneration, with a focus on their clinical relevance. Key endocrine factors, [...] Read more.
Recent advancements in tissue engineering and stem cell science have positioned bone disease treatment as a promising frontier in regenerative medicine. This review explores the hormonal and signaling pathways critical to bone regeneration, with a focus on their clinical relevance. Key endocrine factors, including thyroid hormones (T3 and T4), insulin-like growth factor 1 (IGF-1), bone morphogenetic proteins (BMPs), parathyroid hormone (PTH), calcitonin, and fibroblast growth factor 23 (FGF23), play pivotal roles in bone remodeling by regulating osteoblast activity, bone resorption, and mineralization. These factors primarily act through the Wnt/β-catenin, BMP, and FGF signaling pathways, which govern bone repair and regeneration. While animal models, such as axolotls, zebrafish, and Xenopus laevis, provide valuable findings about these mechanisms, translating these findings into human applications presents challenges. This review underscores the therapeutic potential of modulating these hormonal networks to enhance bone regeneration while cautioning against possible adverse effects, such as uncontrolled tissue proliferation or metabolic imbalances. By integrating knowledge from regenerative models, this work provides a foundation for optimizing hormone-based therapies for clinical applications in bone repair and disease treatment. Full article
(This article belongs to the Special Issue Tissue and Organ Regeneration in Fish: Evolutionary Mechanisms)
14 pages, 2607 KiB  
Article
Mandibular-Derived Monocytes from 1-Year-Old Mice Have Enhanced Osteoclast Differentiation and Differentially Regulated Gene Expression Compared to Femur-Derived Monocytes
by Emilyn D. Asinas, Rachel Clark, Jadyn Nelson, Juan E. Abrahante Llorens, Kim Mansky and Amy Tasca
Biology 2025, 14(3), 273; https://doi.org/10.3390/biology14030273 - 7 Mar 2025
Viewed by 101
Abstract
It is well established that both men and women lose bone as they age. While recent studies suggest unique molecular signatures of mineral-resorbing cells at different anatomical locations, most studies focus on long bones, and little is known about craniofacial osteoclasts, especially during [...] Read more.
It is well established that both men and women lose bone as they age. While recent studies suggest unique molecular signatures of mineral-resorbing cells at different anatomical locations, most studies focus on long bones, and little is known about craniofacial osteoclasts, especially during the aging process. To determine differences between osteoclasts at different skeletal sites, we analyzed the differentiation potential, demineralization activity, and gene expression of osteoclast precursors from 1-year-old male and female C57Bl/6J mice. In our study, we determined that mandibular-derived osteoclasts were larger in size compared to those in the femur but were significantly fewer in number. However, femur-derived osteoclasts demineralized larger and more numerous areas of a calcium phosphate surface compared to mandibular-derived osteoclasts. Bulk RNA sequencing demonstrated that the mandibular-derived monocytes were enriched for genes in the WNT signaling pathway, biomineralization, and osteogenesis pathways, while femur-derived monocytes were enriched for genes in the mitochondrial respiratory complex I. Overall, our data suggest that there are different mechanisms that regulate osteoclasts from different skeletal sites as we age. This information may help to guide the design of treatments to prevent aging-induced bone loss. Full article
(This article belongs to the Special Issue Musculoskeletal Biology: Impact of Ageing and Disease)
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<p>Diagram of study design. C57Bl/6 mice were aged to 1 year. (1) Bone marrow was isolated from mandible or femur. (2–3) Monocytes were isolated from bone marrow (4) Bulk RNA-Seq was performed for monocytes (5) Monocytes were cultured in M-CSF and RANKL to analyze osteoclast differentiation and demineralization ability.</p>
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<p>Mandibular-derived osteoclasts are larger in size compared to femur-derived osteoclasts. Monocytes were isolated from the bone marrow of the femur and mandible of 1-year-old C57Bl/6J male and female mice. Monocytes were cultured in M-CSF and RANKL to stimulate osteoclast differentiation. (<b>A</b>) Representative images of TRAP-stained osteoclasts. (<b>B</b>) The average size and (<b>C</b>) number of TRAP-positive multinuclear cells. (<b>D</b>,<b>E</b>) Monocytes were cultured on calcium phosphate-coated plates with M-CSF and RANKL for 7–10 days. (<b>D</b>) The average size of demineralized areas, and (<b>E</b>) the number of demineralized areas. The data shown are from at least three independent experiments. Samples were compared using Student’s <span class="html-italic">t</span>-test.</p>
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<p>Mandibular-derived monocytes express higher levels of osteoclast transcription factors. Monocytes were isolated from the bone marrow of the mandible and femur of 1-year-old C56Bl/6J male and female mice. RNA was isolated, and qRT-PCR was performed to measure gene expression. The relative expression of (<b>A</b>) <span class="html-italic">Jun</span>, (<b>B</b>) <span class="html-italic">c-Fos</span>, (<b>C</b>) <span class="html-italic">JunB</span>, (<b>D</b>) <span class="html-italic">Cebp-a</span>, and (<b>E</b>) <span class="html-italic">Atf3.</span> The data shown are from three independent experiments. Data are graphed relative to <span class="html-italic">Hprt.</span> Samples were compared using Student’s <span class="html-italic">t</span>-test.</p>
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<p>Analysis of bulk RNA-SEQ data from monocytes of 1-year-old mice. (<b>A</b>) Volcano plot showing number of differentially regulated genes identified by bulk RNA sequencing of femur- and mandibular-derived monocytes. Red dots represent upregulated and blue dots represent down regulated genes as identified by bulk RNA-SEQ. DAVID analysis of (<b>B</b>) number of genes in each upregulated pathway; (<b>C</b>) number of genes in each downregulated pathway in biological processes in mandibular-derived monocytes; (<b>D</b>) percentage of enrichment in genes in each upregulated pathway; and (<b>E</b>) percentage of enrichment in genes in each downregulated pathway in biological processes in mandibular-derived monocytes.</p>
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<p>Osteogenic molecules are enhanced in expression from mandibular-derived monocytes. (<b>A</b>) Heat map of osteogenic genes identified in bulk RNA-SEQ of 1-year-old mandibular-derived monocytes. (<b>B</b>–<b>G</b>) qRT-PCR of selected osteogenic genes identified by RNA-SEQ of mandibular-derived monocytes. Individual <span class="html-italic">p</span>-values are as shown. (<b>H</b>,<b>I</b>) qRT-PCR of selected osteogenic genes from mandibular- and femur-derived osteoclast precursors treated with either M-CSF only (Day 0) or M-CSF and RANKL (Day 2). Data shown are from three independent experiments. Data are graphed relative to <span class="html-italic">Hprt.</span> Samples were compared using Student’s <span class="html-italic">t</span>-test.</p>
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<p>Mitochondria complex I genes are upregulated in 1-year-old femur-derived monocytes. (<b>A</b>) Heat map of mitochondria complex I genes identified in bulk RNA-SEQ of 1-year-old mandibular- and femur-derived monocytes. (<b>B</b>–<b>F</b>) qRT-PCR of selected mitochondria complex I genes identified by RNA-SEQ. Individual <span class="html-italic">p</span>-values are as shown. (<b>G</b>–<b>K</b>) qRT-PCR of selected osteogenic genes from mandibular- and femur-derived osteoclast precursors treated with either M-CSF only (Day 0) or M-CSF and RANKL (Day 2). Data shown are from three independent experiments. Data are graphed relative to <span class="html-italic">Hprt.</span> Samples were compared using Student’s <span class="html-italic">t</span>-test.</p>
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18 pages, 706 KiB  
Review
Neural Excitatory/Inhibitory Imbalance in Motor Aging: From Genetic Mechanisms to Therapeutic Challenges
by Xuhui Chen, Ya Wang, Yongning Zhang, Xucheng Li, Le Zhang, Shangbang Gao and Cuntai Zhang
Biology 2025, 14(3), 272; https://doi.org/10.3390/biology14030272 - 7 Mar 2025
Viewed by 230
Abstract
Neural excitatory/inhibitory (E/I) imbalance plays a pivotal role in the aging process. However, despite its significant impact, the role of E/I imbalance in motor dysfunction and neurodegenerative diseases has not received sufficient attention. This review explores the mechanisms underlying motor aging through the [...] Read more.
Neural excitatory/inhibitory (E/I) imbalance plays a pivotal role in the aging process. However, despite its significant impact, the role of E/I imbalance in motor dysfunction and neurodegenerative diseases has not received sufficient attention. This review explores the mechanisms underlying motor aging through the lens of E/I balance, emphasizing genetic and molecular factors that contribute to this imbalance (such as SCN2A, CACNA1C, GABRB3, GRIN2A, SYT, BDNF…). Key regulatory genes, including REST, vps-34, and STXBP1, are examined for their roles in modulating synaptic activity and neuronal function during aging. With insights drawn from ALS, we discuss how disruptions in E/I balance contribute to the pathophysiology of age-related motor dysfunction. The genes discussed above exhibit a certain association with age-related motor neuron diseases (like ALS), a relationship that had not been previously recognized. Innovative genetic therapies, such as gene editing technology and optogenetic manipulation, are emerging as promising tools for restoring E/I balance, offering hope for ameliorating motor deficits in aging. This review explores the potential of these technologies to intervene in aging-related motor diseases, despite challenges in their direct application to human conditions. Full article
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<p>Various factors contribute to excitation/inhibition balance or imbalance. (<b>A</b>) Molecular mechanisms and influencing factors underlying the E/I balance: presynaptic glutamatergic and GABAergic neurons release glutamate and GABA into the synaptic cleft, respectively. This process causes postsynaptic neuron excitation or inhibition activity through the flow of ions inside and outside the cell, influenced by genetic factors, mitochondrial stress, and age. (<b>B</b>) Age-related MNDs are characterized by an abnormal increase in neuronal excitability, leading to an imbalance between excitatory and inhibitory neurotransmission. This disruption is closely linked to gene mutations, often marked by an increase in excitatory signaling, further resulting in a pathological elevation of the E/I ratio. E/I imbalance could damage axons, impair cellular communication, and disrupt motor function over time. Current gene editing technology or optogenetics may be a promising way to restore motor homeostasis and make motor neurons healthier. Upward Arrow: indicates increase/higher. Downward Arrow: indicates decrease/lower. Red font: excitability-related factors and results. Blue font: inhibition-related influencing factors and results. E: excitability; I: Inhibition.</p>
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21 pages, 3294 KiB  
Article
First Report of the Genus Quinquelaophonte Wells, Hicks and Coull, 1982 (Copepoda: Harpacticoida: Laophontidae) from China, with Description of a New Species
by Zhengcun Hou, Qi Kou and Lin Ma
Biology 2025, 14(3), 271; https://doi.org/10.3390/biology14030271 - 6 Mar 2025
Viewed by 109
Abstract
The diversity of the species-rich copepod family Laophontidae T. Scott, 1905, is rarely investigated in China. Based on the recent collections from the coasts of the Yellow Sea in Shandong, two species of the genus Quinquelaophonte Wells, Hicks and Coull, 1982 were first [...] Read more.
The diversity of the species-rich copepod family Laophontidae T. Scott, 1905, is rarely investigated in China. Based on the recent collections from the coasts of the Yellow Sea in Shandong, two species of the genus Quinquelaophonte Wells, Hicks and Coull, 1982 were first reported from China, with one identified as new. The new species, Quinquelaophonte xinzhengi sp. nov., differs from other congeners by the following characteristics: female caudal ramus about 3.2 times as long as maximum width; P1 enp-2 bearing one claw and one minute seta; female P3 exp-3 with two inner setae, male P3 exp-3 with one inner seta; P4 exp-3 with one inner seta; and female P5 exopod bearing six setae. The COI genetic divergences between the new species and three closely related congeneric species all exceed 20% (21.5–22.3%), supporting their separate species status. Our samples of Q. enormis Kim, Nam and Lee, 2020, which are first found in China, show subtle differences with the original description of the type specimens from Korea on basis of maxilliped and P2 enp-1 with cuticular bulge subapically, female P3 and P4 without conspicuous morphological variation. This is also the first report of Quinquelaophonte from the China Seas. Full article
(This article belongs to the Section Zoology)
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<p><span class="html-italic">Quinquelaophonte xinzhengi</span> sp. nov. female: (<b>A</b>) habitus, dorsal (Paratype MBM189286); (<b>B</b>) antennule (Paratype MBM189286); (<b>C</b>) antenna (Paratype MBM189287); (<b>D</b>) allobasis of antenna (Paratype MBM189286). Scale bars: A = 100 μm; B–D = 10 μm.</p>
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<p><span class="html-italic">Quinquelaophonte xinzhengi</span> sp. nov. female: (<b>A</b>) urosome, dorsal (Paratype MBM189286); (<b>B</b>) urosome, ventral (Paratype MBM189286); (<b>C</b>) urosome, lateral (Paratype MBM189286); (<b>D</b>) caudal ramus, ventral (Holotype MBM189284). Scale bar: A–D = 50 μm.</p>
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<p><span class="html-italic">Quinquelaophonte xinzhengi</span> sp. nov. female: (<b>A</b>) mandible (Paratype MBM189287). (<b>B</b>) gnathobase of mandible (Paratype MBM189286). (<b>C</b>) maxillule (Paratype MBM189287). (<b>D</b>) maxilla (Paratype MBM189285). (<b>E</b>) maxilliped (Paratype MBM189285). Scale bar: A–E = 10 μm.</p>
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<p><span class="html-italic">Quinquelaophonte xinzhengi</span> sp. nov. female: (<b>A</b>) P1, posterior (Holotype MBM189284). (<b>B</b>) P2, anterior (Holotype MBM189284). Scale bar: A–B = 50 μm.</p>
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<p><span class="html-italic">Quinquelaophonte xinzhengi</span> sp. nov. female: (<b>A</b>) P3, anterior (Holotype MBM189284); (<b>B</b>) P4, anterior (Paratype MBM189287); (<b>C</b>) P5, anterior (Holotype MBM189284). Scale bar: A–C = 50 μm.</p>
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<p><span class="html-italic">Quinquelaophonte xinzhengi</span> sp. nov. male: (<b>A</b>) habitus, dorsal (Paratype MBM189288); (<b>B</b>) antennule (Paratype MBM189288). (<b>C</b>–<b>F</b>) third to seven segment of antennule (Paratype MBM189288). Scale bars: A = 100 μm; B–F = 20 μm.</p>
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<p><span class="html-italic">Quinquelaophonte xinzhengi</span> sp. nov. male: (<b>A</b>) urosome, ventral (Paratype MBM189288); (<b>B</b>) P2, anterior (Paratype MBM189288). Scale bar: A–B = 50 μm.</p>
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<p><span class="html-italic">Quinquelaophonte xinzhengi</span> sp. nov. male: (<b>A</b>) P3, anterior (Paratype MBM189288); (<b>B</b>) P4, anterior (Paratype MBM189288); (<b>C</b>) P5, anterior (Paratype MBM189288). Scale bar: A–C = 50 μm.</p>
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<p><span class="html-italic">Quinquelaophonte enormis</span> Kim, Nam &amp; Lee, 2020. female (MBM 189290): (<b>A</b>) P1, anterior; (<b>B</b>) P2, anterior; (<b>C</b>) P3, anterior; (<b>D</b>) P4, anterior; (<b>E</b>) maxilliped, anterior. Scale bars: A–E = 10 μm.</p>
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<p>Bayesian inference tree constructed from the concatenated dataset (COI + 18S rRNA genes) partitioned by gene and codon. SH-like approximate likelihood ratio test (aLRT, upper left) values, maximum likelihood ultrafast bootstrap scores (UFBoot, upper right) and Bayesian posterior probabilities (PP, below) are indicated adjacent to each node. Node not recovered by Maximum likelihood analysis is indicated by “--/--”.</p>
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16 pages, 3332 KiB  
Article
A Preclinical Model to Assess Intestinal Barrier Integrity Using Canine Enteroids and Colonoids
by Megan P. Corbett, Vojtech Gabriel, Vanessa Livania, David Díaz-Regañón, Abigail Ralston, Christopher Zdyrski, Dongjie Liu, Sarah Minkler, Hannah Wickham, Addison Lincoln, Karel Paukner, Todd Atherly, Maria M. Merodio, Dipak Kumar Sahoo, David K. Meyerholz, Karin Allenspach and Jonathan P. Mochel
Biology 2025, 14(3), 270; https://doi.org/10.3390/biology14030270 - 6 Mar 2025
Viewed by 187
Abstract
While two-dimensional (2D) cell cultures, such as Caco-2 and Madin–Darby canine kidney (MDCK) cells are widely used in a variety of biological models, these two-dimensional in vitro systems present inherent limitations in replicating the complexities of in vivo biology. Recent progress in three-dimensional [...] Read more.
While two-dimensional (2D) cell cultures, such as Caco-2 and Madin–Darby canine kidney (MDCK) cells are widely used in a variety of biological models, these two-dimensional in vitro systems present inherent limitations in replicating the complexities of in vivo biology. Recent progress in three-dimensional organoid technology has the potential to address these limitations. In this study, the characteristics of conventional 2D cell culture systems were compared to those of canine intestinal organoids (enteroids, ENT, and colonoids, COL). Light microscopy and transmission electron microscopy were employed to evaluate the microanatomy of ENT, COL, Caco-2, and MDCK cell monolayers, while transepithelial electrical resistance (TEER) values were measured to assess monolayer integrity. The TEER values of canine ENT monolayers more closely approximated reported TEER values for human small intestines compared to Caco-2 and MDCK monolayers. Additionally, canine ENT demonstrated greater monolayer stability than Caco-2 and MDCK cells. Notably, while all systems displayed desmosomes, canine ENT and COL exclusively produced mucus. These findings highlight the potential of the canine organoid system as a more biologically relevant model for in vitro studies, addressing the limitations of conventional 2D cell culture systems. Full article
(This article belongs to the Special Issue Animal Models in Toxicology)
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<p>Ideal intestinal permeability assay monolayer. This figure illustrates the desirable properties for a cellular monolayer in a dual-chamber permeable support system, including cellular diversity (1), cell shape (2), polarization (3), the presence of microvilli (4) and tight junctions (5), the ability to imitate in vivo epithelial barrier integrity (6), with stable TEER values (8) and low between-replicates variability (7), and the reliable expression of cytochrome P450 (CYP450), P-glycoprotein (P-gp), and other important transport molecules. Created in BioRender. Corbett, M. (2025) <a href="https://BioRender.com/d25v197" target="_blank">https://BioRender.com/d25v197</a> (accessed on 7 February 2025).</p>
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<p>Organoid enterocyte height measurement guide. This figure represents the basic rules followed during the study on canine organoid measurements to ensure accurate results. (<b>A</b>) is a schematic that illustrates the structural differences between early cystic organoids and late budding organoids, with examples of correct and incorrect enterocyte height measurements in intestinal organoids (ENT). (<b>B</b>) is a representative canine colon organoid (COL) slide, composed of multiple organoids in varying states of differentiation, embedded in extracellular matrix. A black arrowhead indicates an individual COL. The pink material (asterisk) around the organoids is Matrigel, an extracellular membrane matrix: original objective 4×, H&amp;E stain. (<b>C</b>) is a representative example of an undifferentiated cystic duodenal organoid, which were excluded from analysis: original objective 20×, H&amp;E stain. (<b>D</b>) is an acceptable differentiated budding duodenal organoid. Organoids are budding structures of columnar epithelium morphologically similar to the mucosa of the tissue of origin (in this case duodenum): original objective 20×, H&amp;E stain. (<b>E</b>) shows the methods used to measure the 3D organoid cell height at the original objective of 40× (H&amp;E stain). Green lines represent acceptable measurements, while red lines represent cells that were excluded from the analysis as they were not cut along the medial axis. Images were captured using an ECHO Revolution microscope (San Diego, CA, USA). Created in BioRender. Corbett, M. (2025) <a href="https://BioRender.com/j00a064" target="_blank">https://BioRender.com/j00a064</a> (accessed on 7 February 2025).</p>
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<p>Organoid, Caco-2, and MDCK cell morphology. The morphology of canine intestinal organoids (<b>A</b>,<b>B</b>). Representative canine COL in 3D culture with mucin production, characterized by wispy, basophilic, intraluminal material ((<b>A</b>), black arrowhead). The COL lumen with sloughed cellular debris is indicated by an asterisk; original objective 20×, H&amp;E. Representative canine COL in 3D culture with intraluminal mucin highlighted in bright blue with an Alcian Blue pH 2.5 histochemical stain (<b>B</b>); original objective 20×. Comparison of 2D transwell-grown monolayers (<b>C</b>–<b>F</b>) between a representative canine duodenal ENT monolayer, a representative COL monolayer, and conventional 2D cell lines (Caco-2 and MDCK). Strictly columnar shapes can be observed in the duodenum ENT monolayer (<b>C</b>) and columnar to tall cuboidal shapes in the COL monolayer, while more cuboidal shapes are present in the Caco-2 cells (<b>E</b>), and polygonal shapes creating a flattened to piling arrangement are present in the MDCK cells (<b>F</b>); original objective 40×, H&amp;E. Images were captured using an ECHO Revolution microscope. Created in BioRender. Corbett, M. (2025) <a href="https://BioRender.com/n03j283" target="_blank">https://BioRender.com/n03j283</a> (accessed on 7 February 2025).</p>
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<p>TEER values comparison. The TEER value time-course was observed over a period of two weeks as TEER values were measured for monolayer cultures (mean TEER +/− SD) in a dual-chamber permeable system derived from canine duodenal ENTs, MDCK, and Caco-2 cells.</p>
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<p>Comparison of 3D organoids plated on a 2D transwell system with 2D cell cultures on transwell systems via TEM. These are the representative transmission electron microscopy (TEM) images. All cultures were imaged on a 2D transwell membrane. (<b>A</b>)—Duodenal organoid monolayer with small vacuoles releasing mucin-like material at the apical surface (red asterisk) near the lumen (<b>L</b>). Mitochondria are indicated by (<b>M</b>). The blue arrow indicates apical microvilli. (<b>B</b>)—Colon organoid monolayer displaying polarization; the basolateral border was defined by a permeable support membrane (<b>SM</b>) and the apical border by the organoid lumen (<b>L</b>). Microvilli (blue arrow) project from the apical membrane into the lumen. The columnar cells contain a centrally to basolaterally located nucleus (<b>N</b>). Cells are separated by paracellular spaces (yellow arrow) anchored by desmosomes (red arrow). (<b>C</b>)—Caco-2 cells. Note the nucleus (<b>N</b>), brush border microvilli (blue arrow) on the luminal surface (<b>L</b>), and desmosomes (red arrow). (<b>D</b>)—MDCK cells. The apical membrane brush border has rare microvilli (blue arrow) near the lumen (<b>L</b>). Note the wide paracellular spaces (yellow arrow) and desmosome (red arrow). Created in BioRender. Corbett, M. (2025) <a href="https://BioRender.com/e01p590" target="_blank">https://BioRender.com/e01p590</a> (accessed on 7 February 2025).</p>
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21 pages, 4825 KiB  
Article
Burn-Related Glycocalyx Derangement and the Emerging Role of MMP8 in Syndecan Shedding
by Hannes Kühtreiber, Daniel Bormann, Melanie Salek, Lisa Auer, Thomas Haider, Caterina Selina Mildner, Marie-Therese Lingitz, Clemens Aigner, Christine Radtke, Daniel Zimpfer, Hendrik Jan Ankersmit and Michael Mildner
Biology 2025, 14(3), 269; https://doi.org/10.3390/biology14030269 - 6 Mar 2025
Viewed by 157
Abstract
Burn injuries often lead to severe complications, including acute respiratory distress syndrome (ARDS), driven in part by systemic inflammation and glycocalyx disruption. In this study, we analyzed the sera of 28 patients after burn trauma and utilized single-cell RNA sequencing (scRNA-seq) along with [...] Read more.
Burn injuries often lead to severe complications, including acute respiratory distress syndrome (ARDS), driven in part by systemic inflammation and glycocalyx disruption. In this study, we analyzed the sera of 28 patients after burn trauma and utilized single-cell RNA sequencing (scRNA-seq) along with microarray transcriptomic analysis to decipher the impact of burn injury on glycocalyx derangement. We observed the significant upregulation of immune cell-derived degrading enzymes, particularly matrix metalloproteinase-8 (MMP8), which correlated with increased immune cell infiltration and glycocalyx derangement. Serum analyses of burn patients revealed significantly elevated levels of shed glycocalyx components and MMP8, both correlating with the presence of inhalation injury. Consequently, the treatment of human in vitro lung tissue models with MMP8 induced significant glycocalyx shedding in alveolar epithelial cells. Together, based on these findings, we propose that MMP8 plays a previously unrecognized role in glycocalyx disruption and subsequent lung injury post-burn, which implies that inhibiting MMP8 may represent a promising therapeutic strategy for alleviating lung injury after burn trauma. Full article
(This article belongs to the Section Biochemistry and Molecular Biology)
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<p>Transcriptomics analysis revealing response of glycocalyx and degrading enzymes post-burn trauma. (<b>A</b>) UMAP of comprehensive scRNA-seq analysis identifying 12 unique cell clusters. (<b>B</b>) Feature Plots showing a glycocalyx module score (GMS), split by condition. (<b>C</b>) Feature Plots illustrating a degrading enzyme module score (DEMS). (<b>D</b>) Dot plot of individual glycocalyx constituents used for the GMS module score. (<b>E</b>) Dot plot of individual glycocalyx-degrading enzymes used for the DEMS module score. Dot size represents the expression percentage for each gene, with color intensity reflecting average gene expression levels. (<b>F</b>) Differentially expressed genes (DEGs) between control and burn groups. Significantly (log2FC &gt; 1, adj. <span class="html-italic">p</span> &lt; 0.05) upregulated genes in the burn group show a positive fold change (red), while those downregulated show a negative fold change (blue). (<b>G</b>) The top 8 ‘GO Biological Process 2023’ terms associated with significantly upregulated and downregulated DEGs. (<b>H</b>) The top 8 terms from a combined query of ‘KEGG 2021 Human’ and ‘Reactome 2022’. Results are displayed as dot plots with their respective combined scores and gene ratios.</p>
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<p>Serum levels of glycocalyx constituents and MMP8 together with SDC1 correlation in burn patients. Systemic levels of SDC1 (<b>A</b>), SDC4 (<b>B</b>), HA (<b>C</b>), HS (<b>D</b>), and MMP8 (<b>E</b>) were quantified in healthy controls and burn patients over a 21-day follow-up. Data analysis was performed using Kruskal–Wallis tests, complemented by Dunn’s multiple comparisons. Data are presented as minimum to maximum boxplots including all data points. Time points with statistical significance (adjusted <span class="html-italic">p</span>-value &lt; 0.05) are marked in red. (<b>F</b>) Pearson’s correlation analysis between MMP8 and SDC1 serum levels in burn patients over various time points, with R<sup>2</sup> values and corresponding <span class="html-italic">p</span>-values provided.</p>
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<p>Effects of MMP8 treatment on pulmonary glycocalyx in vitro. (<b>A</b>) UMAP representation of scRNA-seq analysis from healthy human lung tissue, identifying 14 distinct cell clusters. (<b>B</b>) Feature Plot displaying the glycocalyx module score (GMS) and (<b>C</b>) degrading enzyme module score (DEMS), calculated based on the gene sets outlined in <a href="#app1-biology-14-00269" class="html-app">Supplementary Figure S2 (Figure S2B,C)</a>. (<b>D</b>) Dot plot showing syndecan gene expression, with dot size indicating the percentage of expressing cells and color intensity reflecting average expression levels. (<b>E</b>) Immunofluorescence imaging of untreated and rhMMP8-treated EpiAlveolar™ 3D lung models, incorporating alveolar epithelial cells (EpiCs), fibroblasts (FBs), and endothelial cells (ECs). The 20× magnification images display DAPI-stained nuclei (blue) and SDC1 fluorescence (red). (<b>F</b>) ELISA-based quantitative analysis of SDC1, SDC4, and HA in EpiAlveolar™ model supernatants, with significant differences (<span class="html-italic">p</span> &lt; 0.05) marked in red. (<b>G</b>) SAECs treated with APMA, rhMMP8 alone, and activated rhMMP8, with SDC1, SDC4, and HA levels in supernatants analyzed via ELISA. Statistical significance was assessed using two-tailed unpaired <span class="html-italic">t</span>-tests and the Kruskal–Wallis test followed by Dunn’s multiple comparisons, with significant results (adj. <span class="html-italic">p</span> &lt; 0.05) highlighted in red.</p>
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30 pages, 8392 KiB  
Article
The Evolution of Nutrient and Microbial Composition and Maturity During the Composting of Different Plant-Derived Wastes
by Yuxin Xie, Pengbing Wu, Ying Qu, Xingchi Guo, Junyan Zheng, Yuhe Xing, Xu Zhang and Qian Liu
Biology 2025, 14(3), 268; https://doi.org/10.3390/biology14030268 - 6 Mar 2025
Viewed by 125
Abstract
Composting is an environmentally friendly treatment technology that recycles and sanitizes organic solid waste. This study aimed to assess the evolution of nutrients, maturity, and microbial communities during the composting of different plant-derived wastes. The composting process was conducted over 49 days using [...] Read more.
Composting is an environmentally friendly treatment technology that recycles and sanitizes organic solid waste. This study aimed to assess the evolution of nutrients, maturity, and microbial communities during the composting of different plant-derived wastes. The composting process was conducted over 49 days using three types of plant-derived waste: wheat bran (WB), peanut straw (PS), and poplar leaf litter (PL). This process was examined through physical, chemical, and biological parameters. The results revealed that after 49 days of composting, the three groups experienced significant changes. They were odorless, were insect-free, exhibited a dark brown color, had an alkaline pH value, and had an electrical conductivity (EC) value of less than 4 mS/cm. These characteristics indicated that they had reached maturity. Nutrient content was the most significant factor influencing the degree of humification of the different composting materials, while changes in microbial community diversity were the key driving factors. Significantly, the compost PS, derived from peanut straw, entered the thermophilic phase first, and by the end of composting, it had the lowest organic matter (OM) loss rate (17.4%), with increases in total nitrogen (TN), total phosphorus (TP), and total potassium (TK) in the order of PS > PL > WB. The increase in humus carbon (HSC) content and the humic acid/fulvic acid (HA/FA) ratio followed the order PS > WB > PL. FTIR spectra indicated that PS had greater aromatic characteristics compared to the other samples. The abundance and diversity of bacterial and fungal communities in the compost increased significantly, accompanied by more complex community structures. Crucially, there were no phytotoxic effects in any of the three composting treatments, and the compost PS boasted a high germination index (GI) of 94.79%, with the lowest heavy metal contents. The findings indicate that the compost PS has the highest potential for resource utilization and is suitable for agricultural applications. Our results demonstrate that composting technology for plant-derived waste has the potential to enhance soil fertility and provide a reference for the composting treatment and resource utilization of other plant-derived waste. Full article
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<p>Schematic diagram of composting device.</p>
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<p>The flow-sheet of the composting treatment.</p>
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<p>Temperature changes during the three compost treatments.</p>
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<p>Changes in pH and EC values in the three compost treatments: (<b>a</b>) the change in the pH value during the three treatments of composting, (<b>b</b>) the change in the pH value at the end of the three treatments of composting, (<b>c</b>) the change in the EC value during the three treatments of composting, and (<b>d</b>) the change in the EC value at the end of composting. Different letters represent significant differences between different composting treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Changes in organic matter in the three treatments: (<b>a</b>) changes in organic matter in the composting process of the three treatments and (<b>b</b>) reductions in organic matter content in the three treatments. Different letters represent significant differences between different composting treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Changes in nutrient content in the three treatments: (<b>a</b>) changes in TN content in the three treatments, (<b>b</b>) increases in TN in the three treatments, (<b>c</b>) changes in TP content in the three treatments, (<b>d</b>) increases in TP in the three treatments, (<b>e</b>) changes in TK content in the three treatments, and (<b>f</b>) increases in TK in the three treatments. Different letters represent significant differences between different composting treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Changes in nutrient content in the three treatments: (<b>a</b>) changes in TN content in the three treatments, (<b>b</b>) increases in TN in the three treatments, (<b>c</b>) changes in TP content in the three treatments, (<b>d</b>) increases in TP in the three treatments, (<b>e</b>) changes in TK content in the three treatments, and (<b>f</b>) increases in TK in the three treatments. Different letters represent significant differences between different composting treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Three treatments for carbon changes in humus: (<b>a</b>) changes in the HSC content during the three composting treatments, (<b>b</b>) increases in the HSC content during the three composting treatments, (<b>c</b>) changes in the HAC content during the three composting treatments, (<b>d</b>) increases in the HAC content during the three composting treatments, (<b>e</b>) changes in the FAC content during the three composting treatments, (<b>f</b>) decreases in the FAC content during the three composting treatments, and (<b>c</b>) changes in the FAC content during the three composting treatments. (<b>g</b>) Changes in the HA/FA ratio during the composting process of the three treatments, and (<b>h</b>) the end value of the HA/FA ratio of the three treatments at the end of composting. Different letters represent significant differences between different composting treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Three treatments for carbon changes in humus: (<b>a</b>) changes in the HSC content during the three composting treatments, (<b>b</b>) increases in the HSC content during the three composting treatments, (<b>c</b>) changes in the HAC content during the three composting treatments, (<b>d</b>) increases in the HAC content during the three composting treatments, (<b>e</b>) changes in the FAC content during the three composting treatments, (<b>f</b>) decreases in the FAC content during the three composting treatments, and (<b>c</b>) changes in the FAC content during the three composting treatments. (<b>g</b>) Changes in the HA/FA ratio during the composting process of the three treatments, and (<b>h</b>) the end value of the HA/FA ratio of the three treatments at the end of composting. Different letters represent significant differences between different composting treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Infrared spectrum analysis of HA in the composting process of three treatments: (<b>a</b>) infrared spectrum analysis of HA in the composting process of WB treatment, (<b>b</b>) infrared spectrum analysis of HA in the composting process of PS treatment, and (<b>c</b>) infrared spectrum analysis of HA in the composting process of PL treatment.</p>
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<p>Infrared spectrum analysis of FA in the composting process of three treatments: (<b>a</b>) infrared spectrum analysis of FA in the composting process of WB treatment, (<b>b</b>) infrared spectrum analysis of FA in the composting process of PS treatment, and (<b>c</b>) infrared spectrum analysis of FA in the composting process of PL treatment.</p>
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<p>Changes in bacterial community structure: (<b>a</b>) changes in bacterial community structure at phylum level and (<b>b</b>) changes in bacterial community structure at genus level.</p>
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<p>Nonmetric multidimensional scale analysis of bacterial communities (NMDS).</p>
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<p>Functional analysis of bacterial communities.</p>
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<p>Changes in fungal community structure: (<b>a</b>) changes in fungal community structure at phylum level and (<b>b</b>) changes in fungal community structure at genus level.</p>
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<p>Nonmetric multidimensional scaling analysis of fungal communities (NMDS).</p>
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<p>Functional analysis of fungal communities.</p>
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<p>Correlation between core microbial communities and environmental factors: (<b>a</b>) WB treatment, (<b>b</b>) PS treatment, and (<b>c</b>) PL treatment. * and ** indicate significant (<span class="html-italic">p</span> &lt; 0.05) and extremely significant (<span class="html-italic">p</span> &lt; 0.01) correlation, respectively.</p>
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<p>Structural equation model of the effects of compost material, nutrient content, and microbial community structure on the humification degree of compost. * means <span class="html-italic">p</span> &lt; 0.05, ** means <span class="html-italic">p</span> &lt; 0.01, and *** means <span class="html-italic">p</span> &lt; 0.001. The red line indicates the positive path, and the blue line indicates the negative path. The width of the line indicates the degree of influence. The values next to the lines are the path coefficients, and the dashed lines indicate insignificant effects. R<sup>2</sup> represents the proportion of the explained variance. Microbial community diversity was expressed using the α-diversity index. The degree of humification was indicated by humification indicators (HSC content, HA/FA, GI value, and C/N).</p>
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16 pages, 3219 KiB  
Article
Caco2/HT-29 In Vitro Cell Co-Culture: Barrier Integrity, Permeability, and Tight Junctions’ Composition During Progressive Passages of Parental Cells
by Elena Donetti, Paola Bendinelli, Margherita Correnti, Elena Gammella, Stefania Recalcati and Anita Ferraretto
Biology 2025, 14(3), 267; https://doi.org/10.3390/biology14030267 - 6 Mar 2025
Viewed by 65
Abstract
Epithelial linings are crucial for the maintenance of physiological barriers. The intestinal epithelial barrier (IEB) consists of enterocytes through tight junctions and mucus-secreting cells and can undergo physiological modifications throughout life. To reproduce as closely as possible the IEB main features over time, [...] Read more.
Epithelial linings are crucial for the maintenance of physiological barriers. The intestinal epithelial barrier (IEB) consists of enterocytes through tight junctions and mucus-secreting cells and can undergo physiological modifications throughout life. To reproduce as closely as possible the IEB main features over time, in vitro co-cultures of Caco2/HT-29 70/30 formed by parental Caco2 and HT-29 cells sub-cultivated for more than 40 passages were set up. The measurements of the transepithelial electrical resistance (TEER) identified two populations: physiological TEER co-cultures (PC) with values > 50 Ωcm2 formed by parental cells with fewer than 40 passages, and leaky TEER co-cultures (LC) with values < 50 Ωcm2 formed by parental cells with more than 40 passages. In LC, paracellular permeability increased in parallel. By immunofluorescence and Western blot analysis, an increase in claudin 2 was observed in LC vs. PC, with no differences in occludin expression. MUC-2 immunoreactivity was stronger in PC than in LC. LC also showed an enhanced vulnerability to TNFα+IFN-γ. These results reproduce the main morpho-functional modifications reported in the human leaky/aged gut and support the usefulness of our in vitro cell model for studying the molecular processes underlying these modifications and testing drug/nutraceutical treatments to ameliorate leaky gut aging. Full article
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<p>Functional properties of Caco2/HT-29 70/30 co-culture in basal condition and after pro-inflammation cytokine treatment with the increasing passage number of the parental cells. (<b>a</b>,<b>c</b>) TEER values, expressed as Ωcm<sup>2</sup>. Each point represents the mean ± SD. (<b>b</b>,<b>d</b>) Paracellular permeability to LY, expressed as [LY] in the basolateral chamber of the transwells. Each point represents the mean ± SD. In (<b>a</b>,<b>b</b>) **** <span class="html-italic">p</span>-value &lt; 0.0001 vs. C39/H19; §§ <span class="html-italic">p</span>-value &lt; 0.01, §§§ <span class="html-italic">p</span>-value &lt; 0.001 vs. C41/H21; °° <span class="html-italic">p</span>-value &lt; 0.01 vs. C42/H22; ++ <span class="html-italic">p</span>-value &lt; 0.01 vs. C44/H24. In (<b>c</b>,<b>d</b>) * <span class="html-italic">p</span>-value &lt; 0.05, ** <span class="html-italic">p</span>-value &lt; 0.01, **** <span class="html-italic">p</span>-value &lt; 0.0001 vs. C34/H13; § <span class="html-italic">p</span>-value &lt; 0.05, §§§§ <span class="html-italic">p</span>-value &lt; 0.0001 vs. C35/H14; °°°° <span class="html-italic">p</span>-vale &lt; 0.0001 vs. C39/H18. In (<b>a</b>–<b>d</b>) Cxx/Hyy, co-culture derived from Caco2 at the xx passage of sub-cultivation and HT-29 at the yy passage of sub-cultivation. (<b>e</b>,<b>f</b>) Graphical representation of the percentage distribution of PC and LC obtained from the parental cells with different numbers of sub-cultivations. (<b>g</b>) TEER values, expressed as Ωcm<sup>2</sup>. Each bar represents the mean ± SD. (<b>h</b>) Paracellular permeability to LY expressed as [LY] in the basolateral chamber of the transwells. Each bar represents the mean ± SD. In (<b>g</b>,<b>h</b>), CTR: control; MIX: 50 ng/mL TNF-α plus 50 ng/mL IFN-γ; * <span class="html-italic">p</span>-values &lt; 0.05, ** <span class="html-italic">p</span>-value &lt; 0.01, *** <span class="html-italic">p</span>-value &lt; 0.001, **** <span class="html-italic">p</span>-value &lt; 0.0001; in (<b>e</b>–<b>h</b>), PC: physiological co-cultures with TEER &gt; 50 Ωcm<sup>2</sup>, in (<b>g</b>,<b>h</b>) Caco2 from the 34th to 37th passages and HT-29 from the 13th to 16th passages; LC: leaky co-cultures with TEER &lt; 50 Ωcm<sup>2</sup>, in (<b>g</b>,<b>h</b>) Caco2 from the 35th to 44th passages and HT-29 from the 14th to 25th passages.</p>
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<p>Analysis of the molecular composition of the tight junctions in Caco2/HT-29 70/30 co-culture showing different TEER values. (<b>a</b>,<b>b</b>) Indirect immunofluorescence for claudin 2; (<b>c</b>,<b>d</b>) immunofluorescence for occludin. (<b>e</b>) Western blot analysis for claudin 2. PC: physiological co-cultures with TEER &gt; 50 Ωcm<sup>2</sup>, Caco2 30th passage and HT-29 21st passage; LC: leaky co-cultures with TEER &lt; 50 Ωcm<sup>2</sup>, Caco2 54th passage and HT-29 41st passage. Nuclei are counterstained with DAPI. Asterisks in (<b>b</b>) indicate multinucleated cells. White arrows in (<b>c</b>,<b>d</b>) indicate the different occludin staining, respectively, in PC and LC. Labels in (<b>c</b>,<b>d</b>) indicate the nuclear dimension. Bars: 50 µm in (<b>a</b>–<b>d</b>) and 10 µm in the inset in (<b>a</b>).</p>
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<p>Mucus detection in Caco2/HT-29 70/30 co-culture showing different TEER values. (<b>a</b>,<b>b</b>): indirect immunofluorescence for MUC-2; (<b>c</b>,<b>d</b>): transmission electron analysis. PC: physiological co-cultures with TEER &gt; 50 Ωcm<sup>2</sup>, in (<b>a</b>) Caco2 30th passage and HT-29 21st passage and in (<b>c</b>) Caco2 34th passage and HT-29 12th passage; LC: leaky co-cultures with TEER &lt; 50 Ωcm<sup>2</sup>, in (<b>b</b>) Caco2 54th passage and HT-29 41st passage and in (<b>d</b>) Caco2 47th passage and HT-29 29th passage. Nuclei are counterstained with DAPI. MUC-2: mucin 2. White arrows in (<b>a</b>) and asterisks in (<b>c</b>) indicate the presence of granular mucus storage in PC. Bars: 50 µm in (<b>a</b>,<b>b</b>); 500 nm in (<b>c</b>,<b>d</b>).</p>
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<p>The sequence of events characterizing intestinal epithelial barrier damage during aging and intestinal bowel disease (IBD).</p>
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<p>Simplified chart of paracellular permeability pathways (modified from [<a href="#B21-biology-14-00267" class="html-bibr">21</a>] and created in BioRender. <a href="https://BioRender.com/n88k097" target="_blank">https://BioRender.com/n88k097</a> accessed on 26 February 2025).</p>
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15 pages, 2681 KiB  
Article
A Triple-Precursor Blend as a Topical Solution to Protect the Skin Against Environmental Damage
by Ping Gao, Xue Xiao, Zhuang Zhou, Hong Zhang, Raghupathi Subramanian, Anuchai Sinsawat and Xuelan Gu
Biology 2025, 14(3), 266; https://doi.org/10.3390/biology14030266 - 5 Mar 2025
Viewed by 359
Abstract
The epidermis acts as the body’s primary defense, relying on components like lipids, HA and GSH for skin barrier function, hydration and resistance to oxidative stress. However, limitations in the topical application of these biomolecules call for novel approaches. This study investigates the [...] Read more.
The epidermis acts as the body’s primary defense, relying on components like lipids, HA and GSH for skin barrier function, hydration and resistance to oxidative stress. However, limitations in the topical application of these biomolecules call for novel approaches. This study investigates the efficacy of Pro-GHL, a blend of free fatty acids, acetylglucosamine and GSH amino acid precursors (GAPs), designed to replenish skin lipids, HA and GSH through de novo biosynthesis. Using primary human keratinocytes, Pro-GHL demonstrated superior antioxidant and anti-inflammatory capacities compared to each individual component under the challenge of UVB or blue light. In 3D skin equivalent models (EpiKutis®), Pro-GHL enhanced skin barrier function. In addition, Pro-GHL prevented the development of pigmentation in pigmented 3D skin equivalent models (MelaKutis®) subjected to UVB irradiation or Benzo[a]pyrene exposure. Together, these results highlight Pro-GHL’s potential as a novel, effective and comprehensive skincare approach to fortify the skin’s defense system from within and prevent the accumulation of tissue damage in response to extrinsic stressors. Full article
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<p>Topical precursor approach for skin protection.</p>
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<p>Pro-GHL suppressed ROS and IL-8 levels in UVB-exposed keratinocytes. (<b>a</b>) Cell viability of UVB-exposed NHEKs treated with Pro-GHL and individual components. (<b>b</b>) ROS level in UVB-exposed NHEKs treated with Pro-GHL and individual components. (<b>c</b>) Relative normalized level of IL-8 in UVB-exposed NHEKs. All values are the mean ± SD (n = 3). ## <span class="html-italic">p</span> &lt; 0.01 versus the NT group; * <span class="html-italic">p</span> &lt; 0.05 versus the UVB group; ** <span class="html-italic">p</span> &lt; 0.01 versus the UVB group; ^^ <span class="html-italic">p</span> &lt; 0.01 versus the Pro-GHL group.</p>
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<p>Dosage–responsiveness of ROS inhibition by Pro-GHL in NHEKs. NHEKs treated with or without Pro-GHL were exposed to blue light. Levels of ROS in NHEKs were quantified using the DCFH-DA probe. All values are the mean ± SD (n = 3). ## <span class="html-italic">p</span> &lt; 0.01 versus the NT group; * <span class="html-italic">p</span> &lt; 0.05 versus the blue light group; ** <span class="html-italic">p</span> &lt; 0.01 versus the blue light group; *** <span class="html-italic">p</span> &lt; 0.001 versus the blue light group.</p>
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<p>Pro-GHL restored gene expression changes induced by blue light and regulated multiple pathways linked to the skin barrier. (<b>a</b>) Principal component analysis of gene expression in the Pro-GHL, blue light and control groups (BL: blue light group; NT: control group). (<b>b</b>) Correlation between gene expression changes in the Pro-GHL and blue light groups. (<b>c</b>) Venn diagram of DEGs (BL_up: upregulated DEGs in the blue light group versus the control group. BL_down: downregulated DEGs in the blue light group versus the control group. Pro-GHL_up: upregulated DEGs in the Pro-GHL group versus the blue light group. Pro-GHL_down: downregulated DEGs in the Pro-GHL group versus the blue light group). (<b>d</b>) Highlighted functions of Pro-GHL-regulated genes predicted via IPA (Green: downregulation. Red: upregulation. Orange: predicted activation of genes based on Pro-GHL-regulated DEGs). (<b>e</b>) Top enriched biological processes of DEGs in the Pro-GHL group based on GO enrichment analysis. (<b>f</b>) Comparison of IPA-predicted pathway activity between the Pro-GHL and blue light groups. The number indicates the Z-score of the pathway from the IPA where a positive number indicates activation of the pathway and a negative number indicates inhibition of the pathway.</p>
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<p>The effects of Pro-GHL on the skin barrier. (<b>a</b>) H&amp;E, IHC of HABP and loricrin staining of the 3D skin equivalent model. The scale bar equals 50 μm. Arrows indicate IHC labeling of HABP (brown) or loricrin (brown). (<b>b</b>–<b>d</b>) Quantification of epidermal living cell thickness, HABP and loricrin levels. All values are the mean ± SD (n = 3). * <span class="html-italic">p</span> &lt; 0.05 versus the NT group; ** <span class="html-italic">p</span> &lt; 0.01 versus the NT group.</p>
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<p>Protective effects of Pro-GHL against UV and BaP. (<b>a</b>) Dermoscopy and melanin distribution of the pigmented 3D skin equivalent model. The scale bar equals 50 μm. Arrows indicate the melanin pigment. (<b>b</b>,<b>c</b>): L* value and total melanin content of the pigmented 3D skin equivalent model after application. (<b>d</b>–<b>f</b>) Gene expression of <span class="html-italic">HMOX1, ELOVL1</span> and <span class="html-italic">CD44</span> in the pigmented 3D skin equivalent model under UVB with or without Pro-GHL application. All values are the mean ± SD (n = 3). * <span class="html-italic">p</span> &lt; 0.05 between groups; ** <span class="html-italic">p</span> &lt; 0.01 between groups.</p>
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12 pages, 2989 KiB  
Article
Assessing the Use of 3D-Model Prostheses in White Storks: A Promising Method in Rehabilitation of Injured Wildlife
by Rusko Petrov, Catarina Quinteira and Stefka Dimitrova
Biology 2025, 14(3), 265; https://doi.org/10.3390/biology14030265 - 5 Mar 2025
Viewed by 198
Abstract
Wildlife Rehabilitation Centres emerged with the purpose of recovering individuals, as a tool for environmental education and monitoring the balance of ecosystems. The White Stork (Ciconia ciconia) is one of the many species that are admitted to rehabilitation centres all around [...] Read more.
Wildlife Rehabilitation Centres emerged with the purpose of recovering individuals, as a tool for environmental education and monitoring the balance of ecosystems. The White Stork (Ciconia ciconia) is one of the many species that are admitted to rehabilitation centres all around the world, due to traumatic amputations. This work presents the development of 3D-printed orthopedic prostheses aimed at partially restoring biomechanical function and enabling the reintegration of amputated birds into their natural habitat. Conducted at the Green Balkans Wildlife Rehabilitation and Breeding Center in Bulgaria, three prosthetic prototypes were created using epoxy resin, polylactic acid (PLA), and polyamide, based on detailed anatomical measurements. The process involved 3D Computer-Aided Design (CAD), biomechanical analysis, and performance evaluation, focusing on locomotion, feeding, and flight. Results showed improved prosthetic efficacy, with birds adapting within 1–5 days, resuming normal behaviours, and regaining flight. Of the 12 birds analyzed, 3 were released into the wild, with 1 tracked via GPS, marking the first documented case of an amputated bird with a prosthesis monitored post-release, covering over 470 km in 15 days. This study highlights the potential of 3D printing in conservation medicine, offering alternatives to euthanasia and open new perspectives in the global context of biodiversity preservation. Full article
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<p>Prototypes of legs and beaks prosthetics developed by the team of veterinarians and 3D AMS.</p>
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<p>(<b>a1</b>,<b>a2</b>) P1—Prosthetic leg made of epoxy resin and a syringe; (<b>b1</b>–<b>b5</b>) P2—Different angles of the second model made with PLA, the red and white version; (<b>c1</b>–<b>c3</b>) P3—The biggest prosthetic model made with polyamide.</p>
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<p>Multi-phase process to develop the prosthesis.</p>
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<p>Three-dimensional renderings of the design of the prosthesis.</p>
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<p>Measurements of the healthy limb.</p>
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<p>Methodology for the placement of the second and third prototype prostheses. (<b>A</b>) Self-adhesive rubber insulation tape. (<b>B</b>) Placement of the fitting piece and tightening of the screws using a hex key.</p>
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<p>(<b>A</b>) Radiograph of the partial limb with the prosthetic device; (<b>B</b>) Functionality evaluation and analysis of animal behaviour.</p>
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<p>(<b>A</b>) Release in the wild of the stork CR97, with the GPS device and a variation of the prototype 2 (<b>B</b>) Total of 1060 GPS points recorded (<b>C</b>) Initial five days post-release movements.</p>
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14 pages, 3729 KiB  
Article
Highly Sensitive Duplex Quantitative PCR Assay for Simultaneous Detection of Two Japanese Eel Viruses, Anguillid Herpesvirus 1 and Japanese Eel Endothelial Cells-Infecting Virus
by Jun-Young Song, Keun-Yong Kim and Ahran Kim
Biology 2025, 14(3), 264; https://doi.org/10.3390/biology14030264 - 5 Mar 2025
Viewed by 184
Abstract
Japanese eel endothelial cells-infecting virus (JEECV) and Anguillid herpesvirus 1 (AnHV) are major pathogens in farmed eels. JEECV causes eel viral endothelial cell necrosis (VECNE), while AnHV leads to symptoms such as head erythema and gill necrosis. Both viruses cause severe mortality alone [...] Read more.
Japanese eel endothelial cells-infecting virus (JEECV) and Anguillid herpesvirus 1 (AnHV) are major pathogens in farmed eels. JEECV causes eel viral endothelial cell necrosis (VECNE), while AnHV leads to symptoms such as head erythema and gill necrosis. Both viruses cause severe mortality alone or in combination, necessitating rapid and early detection of their presences. In this study, we developed a highly efficient duplex quantitative PCR method (r2 = 0.999) using hydrolysis probes for the rapid and simultaneous detections of AnHV and JEECV. This new diagnostic method demonstrated a 1.7-fold higher detection rate for AnHV and a 2.5-fold higher detection rate for JEECV than conventional PCR. Quantitative analysis of water and eel tissue samples from aquaculture facilities revealed that the two viruses could be detected in water 1–3 months prior to mortality, enabling their early identification of infections through water testing alone. Notably, the method reliably detected low viral loads (< 1 copy) in both water and tissue samples, facilitating preclinical detection and proactive disease management. This approach reduces the risk of mass mortality and economic losses in eel farming. This study underscores the critical role of advanced molecular diagnostic technologies in enhancing health management in aquaculture. Full article
(This article belongs to the Section Microbiology)
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<p>Phylogenetic tree constructed by neighbor-joining method based on the <span class="html-italic">Pol</span> sequences of AnHV. The sequences analyzed in this study were in the bold.</p>
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<p>Phylogenetic tree constructed by neighbor-joining method based on the <span class="html-italic">Ltlg</span> sequences of JEECV. The sequence analyzed in this study were bold.</p>
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<p>Duplex qPCR amplification curves of AnHV and JEECV (<b>A</b>) and standard curves for AnHV (<b>B</b>) and JEECV (<b>C</b>) at internal standard concentrations (100,000 copies/rxn, 10,000 copies/rxn, 1000 copies/rxn, 100 copies/rxn, 10 copies/rxn, 1 copy/rxn), with an <span class="html-italic">r</span><sup>2</sup> value of 0.999.</p>
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21 pages, 5495 KiB  
Article
Repurposing ProTAME for Bladder Cancer: A Combined Therapeutic Approach Targeting Cell Migration and MMP Regulation
by Ihsan Nalkiran and Hatice Sevim Nalkiran
Biology 2025, 14(3), 263; https://doi.org/10.3390/biology14030263 - 5 Mar 2025
Viewed by 189
Abstract
Bladder cancer, the fourth most common cancer type among men, remains a therapeutic challenge due to its heterogeneity and frequent development of chemoresistance. Cisplatin-based chemotherapy, often combined with gemcitabine, is the standard treatment, yet resistance and off-target effects in non-cancerous tissues limit its [...] Read more.
Bladder cancer, the fourth most common cancer type among men, remains a therapeutic challenge due to its heterogeneity and frequent development of chemoresistance. Cisplatin-based chemotherapy, often combined with gemcitabine, is the standard treatment, yet resistance and off-target effects in non-cancerous tissues limit its efficacy. This study evaluated the effects of cisplatin, gemcitabine, and the APC/C inhibitor proTAME, both individually and in combination, on cell migration and MMP2/MMP9 expression in RT4 bladder cancer and ARPE-19 normal epithelial cells. Molecular docking analyses were conducted to investigate the interactions of these compounds with MMP2 and MMP9. IC20 values for gemcitabine, cisplatin, and proTAME were applied in scratch-wound healing and quantitative real-time PCR (qRT-PCR) assays. Docking results predicted that proTAME may interact favorably with MMP2 (−9.2 kcal/mol) and MMP9 (−8.7 kcal/mol), showing high computational binding affinities and potential key hydrogen bonds; however, these interactions require further experimental validation. Scratch-wound healing and qRT-PCR assays demonstrated that proTAME-containing combinations were associated with reduced cell migration and decreased MMP2 and MMP9 expression in RT4 cells. Cisplatin combined with proTAME showed the most pronounced reduction in MMP expression and cell migration, with proTAME alone also exhibiting notable inhibitory effects. In ARPE-19 cells, gemcitabine and cisplatin upregulated MMP2 and MMP9 expression, suggesting a potential stress response, whereas proTAME mitigated this effect. These differential effects show the importance of tumor-specific responses in RT4 cells, where proTAME shows promise in enhancing the efficacy of chemotherapy by modulating MMP-related pathways involved in tumor migration and invasion. In conclusion, this study highlights the potential of proTAME as a repurposed agent in bladder cancer treatment due to its association with reduced cell migration and MMP downregulation. While these in vitro and in silico findings suggest a promising role for proTAME in combination therapies, further validation in advanced preclinical models is necessary to assess its therapeutic applicability and safety. Full article
(This article belongs to the Special Issue Cancer and Signalling: Targeting Cellular Pathways)
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<p>The structures of the therapeutic agents and ligands used in the molecular docking study are shown. (<b>a</b>) represents the 2D structure of proTAME. (<b>b</b>) illustrates gemcitabine, while (<b>c</b>) shows cisplatin. (<b>d</b>) presents the small-molecule ligand I52, and (<b>e</b>) depicts the 2D structure of the small-molecule ligand NFH. The chemical structures used in this figure were downloaded and modified from the PubChem database, <a href="https://pubchem.ncbi.nlm.nih.gov" target="_blank">https://pubchem.ncbi.nlm.nih.gov</a> (accessed on 9 October 2024).</p>
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<p>Molecular docking interactions of proTAME, gemcitabine, cisplatin, and I52 with MMP2. (<b>a</b>,<b>b</b>) ProTAME–MMP2: 3D visualization (<b>a</b>) demonstrates stable positioning of proTAME within the active site of MMP2, supported by interactions with key residues, as detailed in the 2D interaction map (<b>b</b>). (<b>c</b>,<b>d</b>) Gemcitabine–MMP2: 3D visualization (<b>c</b>) shows gemcitabine effectively bound to active site of MMP2, with the 2D interaction map (<b>d</b>) outlining residue-specific interactions. (<b>e</b>,<b>f</b>) Cisplatin–MMP2: 3D visualization (<b>e</b>) illustrates the positioning of cisplatin within the active site of MMP2, with the 2D interaction map (<b>f</b>) displaying key stabilizing interactions. (<b>g</b>,<b>h</b>) I52–MMP2: 3D visualization (<b>g</b>) highlights strong binding of I52 to the active site of MMP2, with the 2D interaction map (<b>h</b>) summarizing its stabilizing interactions. This figure highlights the varying binding affinities and interaction networks of these ligands within the active site of MMP2.</p>
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<p>Molecular docking interactions of proTAME, gemcitabine, cisplatin, and NFH with MMP9. (<b>a</b>,<b>b</b>) ProTAME–MMP9: 3D visualization (<b>a</b>) demonstrates the stable binding of proTAME within the active site of MMP9, supported by interactions with surrounding residues. The 2D interaction map (<b>b</b>) highlights key stabilizing interactions, including hydrogen bonds and other forces. (<b>c</b>,<b>d</b>) Gemcitabine–MMP9: 3D visualization (<b>c</b>) shows the effective positioning of gemcitabine within the active site of MMP9, with the 2D interaction map (<b>d</b>) displaying residue-specific interactions contributing to binding. (<b>e</b>,<b>f</b>) Cisplatin–MMP9: 3D visualization (<b>e</b>) illustrates binding of cisplatin to the active site of MMP9, stabilized by multiple interactions as shown in the 2D interaction map (<b>f</b>). (<b>g</b>,<b>h</b>) NFH–MMP9: 3D visualization (<b>g</b>) highlights the positioning of NFH and interactions within the active site of MMP9, with the 2D interaction map (<b>h</b>) summarizing key hydrogen bonds and stabilizing forces. This figure emphasizes the varying binding affinities and interaction networks of these ligands with MMP9.</p>
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<p>Inhibition of cell migration in ARPE-19 and RT4 cells by cisplatin, gemcitabine, and proTAME treatments in scratch-wound healing assay. (<b>a</b>,<b>d</b>) The images of scratch-wound healing assays performed on ARPE-19 (<b>a</b>) and RT4 (<b>d</b>) cells at 0, 24, and 48 h post-treatment. The cells were treated with DMSO control, cisplatin, gemcitabine, proTAME, or combinations of cisplatin+proTAME, gemcitabine+proTAME, gemcitabine+cisplatin, and gemcitabine+cisplatin+proTAME. Images represent one of three independent replicates (<span class="html-italic">n</span> = 3), with three technical replicates per condition. Images were captured using an inverted microscope at 4× magnification. (<b>b</b>,<b>e</b>) Quantification of the scratch-wound area (µm<sup>2</sup>) over time for ARPE-19 (<b>b</b>) and RT4 (<b>e</b>) cells, with measurements taken at 0, 24, and 48 h. The data show the reduction in scratch area across different treatment groups, indicating varying degrees of cell migration inhibition. (<b>c</b>,<b>f</b>) The percentage of the scratch-wound area remaining at 48 h relative to the initial wound size (0 h) for ARPE-19 (<b>c</b>) and RT4 (<b>f</b>) cells.</p>
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<p>Effects of cisplatin, gemcitabine, and proTAME on MMP2 and MMP9 gene expression in ARPE-19 and RT4 cells. (<b>a</b>) MMP2 gene expression fold change in ARPE-19 and RT4 cells following treatment with cisplatin, gemcitabine, proTAME, and their combinations. (<b>b</b>) MMP2 gene expression heat map visualization. (<b>c</b>) MMP9 gene expression fold change in ARPE-19 and RT4 cells under the same treatment conditions as (<b>a</b>). (<b>d</b>) MMP9 gene expression heat map visualization. Gene expression levels were normalized to GAPDH, and fold changes were calculated using the 2<sup>−ΔΔCt</sup> method. The data are presented as fold change relative to the ARPE-19 untreated control, with statistical comparisons conducted against the untreated control for cisplatin-, gemcitabine-, and cisplatin+gemcitabine-treated groups. Statistical significance is indicated as follows: ns: non-significant, *: <span class="html-italic">p</span> &lt; 0.05, **: <span class="html-italic">p</span> &lt; 0.01, ***: <span class="html-italic">p</span> &lt; 0.001. Statistical analyses were performed for proTAME, cisplatin+proTAME, gemcitabine+proTAME, and gemcitabine+cisplatin+proTAME groups compared to DMSO control. The statistical significance is indicated as follows: ns (bold): non-significant, §: <span class="html-italic">p</span> &lt; 0.05, §§: <span class="html-italic">p</span> &lt; 0.01, §§§: <span class="html-italic">p</span> &lt; 0.001. The statistical significance of RT4 untreated control was compared to ARPE-19 untreated control. All experiments were performed with three independent biological replicates, each consisting of three technical replicates, and data are presented as mean ± standard deviation (SD) from three independent experiments.</p>
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6 pages, 7163 KiB  
Correction
Correction: Sarria-Sarria et al. A New Genus of Andean Katydid with Unusual Pronotal Structure for Enhancing Resonances. Biology 2024, 13, 1071
by Fabio A. Sarria-Sarria, Glenn K. Morris and Fernando Montealegre-Z
Biology 2025, 14(3), 262; https://doi.org/10.3390/biology14030262 - 5 Mar 2025
Viewed by 94
Abstract
In the original publication [...] Full article
(This article belongs to the Special Issue Adaptation of Living Species to Environmental Stress)
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<p>Morphological characters of <span class="html-italic">Tectucantus</span> spp. (<b>A</b>–<b>C</b>) Habitus of male of <span class="html-italic">T. planatus</span>, <span class="html-italic">T. vargasi</span>, and <span class="html-italic">T. tinnulus</span>. (<b>D</b>–<b>F</b>) Dorsal view and size comparison of pronotum. (<b>G</b>–<b>I</b>) <span class="html-italic">Tectucantus</span> spp. tympanal slits design.</p>
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<p><span class="html-italic">Tectucantus</span> spp. wing morphology, dorsal and ventral view. (<b>A</b>–<b>D</b>) <span class="html-italic">T. planatus</span> (<b>E</b>–<b>H</b>) <span class="html-italic">T. vargasi</span> (<b>I</b>–<b>L</b>) <span class="html-italic">T. tinnulus</span>.</p>
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<p><span class="html-italic">Tectucantus</span> spp. abdominal morphological features. (<b>A</b>–<b>C</b>) Ventral view of male subgenital plate. (<b>D</b>–<b>F</b>) Dorsal view of male epiproct. (<b>G</b>–<b>I</b>) Male right cercus. (<b>J</b>–<b>L</b>) Dorsal view of female subgenital plate. (<b>M</b>–<b>O</b>) Side view of female ovipositor.</p>
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<p>The stridulatory file of <span class="html-italic">Tectucantus</span> spp. Graph panels on the left show the measurements of inter-tooth distances in the direction of scraper motion during stridulation (anal to basal), and the panels on the right show SEM pictures of the files of each species, except for <span class="html-italic">T. tinnulus</span>. (<b>A</b>) <span class="html-italic">T. planatus</span>, (<b>B</b>) <span class="html-italic">T. vargasi</span>, and (<b>C</b>) <span class="html-italic">T. tinnulus</span>.</p>
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<p>Acoustic analysis of <span class="html-italic">Tectucantus</span> spp. (<b>A</b>–<b>C</b>) Calling song of a recorded section. (<b>D</b>–<b>F</b>) Close-up view of an echeme. (<b>G</b>–<b>I</b>) Close-up view of a syllable (<b>J</b>–<b>L</b>) Frequency spectrum of a single syllable, red dashed line indicates peak frequency.</p>
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<p>Three-dimensional segmentation and volumetric features. (<b>A</b>–<b>C</b>) Side view of head and thorax. (<b>D</b>–<b>L</b>) Pronotum 3D reconstruction, side view and pronotal cavity volume. (<b>J</b>–<b>L</b>) Pronotal volume represented by the shaded area.</p>
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<p>Relationships between <span class="html-italic">Tectucantus</span> spp. pronotal cavity and calling songs. (<b>A</b>) Correlation between pronotal volume and carrier frequency. (<b>B</b>) Correlation between carrier frequency and predicted carrier frequency.</p>
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22 pages, 9146 KiB  
Article
Exploring the Role of BCL2 Interactome in Cancer: A Protein/Residue Interaction Network Analysis
by Sidra Ilyas and Donghun Lee
Biology 2025, 14(3), 261; https://doi.org/10.3390/biology14030261 - 5 Mar 2025
Viewed by 163
Abstract
BCL2 is a critical regulator of intrinsic and extrinsic pathways of apoptosis that have been implicated in cancer progression and therapeutic resistance. In this study, the protein–protein interactions (PPIs) of BCL2 with potential binding partners and their role in cancer was investigated. A [...] Read more.
BCL2 is a critical regulator of intrinsic and extrinsic pathways of apoptosis that have been implicated in cancer progression and therapeutic resistance. In this study, the protein–protein interactions (PPIs) of BCL2 with potential binding partners and their role in cancer was investigated. A comprehensive PPI network for BCL2 has been generated by using the Protein Interactions Network Analysis (PINA) platform to identify key interactors. To further investigate the network, Molecular Operating Environment (MOE), Search Tool for the Retrieval of Interacting Genes (STRING), Residue Interaction Network Generation (RING), and the gProfiler server were used. Docking and Molecular Dynamics (MD) simulations were performed by using HDOCK and Gromacs to analyze the binding dynamics and stability of protein complexes. The BCL2 interactome revealed that three key interactors (p53, RAF1, and MAPK1) are involved in cancer-related processes. Docking studies highlighted BCL2 residues such as ASP111, ASP140, ARG107, and ARG146 that were predominantly involved in multiple hydrogen bonds, ionic interactions, and van der Waals contacts, highlighting conserved binding sites that play critical roles in the stability and specificity of protein–protein interactions. MD simulations (200 ns) of the BCL2-p53 complex showed that the RMSD was increased, suggesting the suppression of BCL2’s anti-apoptotic activity by p53. The RMSD for BCL2-RAF1 was also increased, showing protein domain structural rearrangements that enhance BCL2 anti-apoptotic activity. The BCL2-MAPK1 complex revealed structural, distinct flexibility patterns and dynamic hydrogen bonding interactions. These findings provide valuable insights into the molecular dynamics by which BCL2 modulates apoptosis and its potential as a promising therapeutic in cancer and apoptosis-related diseases. Full article
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<p>The workflow used in the study.</p>
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<p>Venn diagram showing common interactors (11) of BCL2, p53, RAF1, and MAPK1.</p>
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<p>Protein–protein interaction analysis using (<b>A</b>) STRING and (<b>B</b>) cytoHubba. The STRING network was supported by multiple lines of evidence, including experimentally validated interactions and associations, further strengthening the reliability of the identified protein–protein relationships. The top 10 PPI interactions identified by cytoHubba based on degree centrality and shortest path were also identified.</p>
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<p>Key biological processes, molecular functions, cellular components, and KEGG pathways identified in functional enrichment analysis by gProfiler.</p>
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<p>The BCL2-p53 complex generated using HDOCK server was visualized using PyMOL, highlighting key connections including hydrogen bonds and hydrophobic interactions where green shows BCL2 protein and magenta color indicates p53.</p>
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<p>Protein–protein interaction analysis of BCL2-p53 using HDOCK and RING server. The chord diagram illustrates the connectivity and distribution of interacting residues between BCL2 and p53. The first amino acid (SER99 with ASP111) showed p53, while the second residue displayed BCL2. The HBOND indicates hydrogen bonds and VDW specifies van der Waals forces.</p>
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<p>The BCL2-RAF1 complex generated using HDOCK server was visualized using PyMOL, highlighting key connections including hydrogen bonds and hydrophobic interactions where green shows BCL2 protein and salmon indicates RAF1.</p>
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<p>Protein–protein interaction analysis of BCL2-RAF1 using HDOCK and RING server. The chord diagram illustrates the connectivity and distribution of interacting residues between RAF1 and BCL2 where first amino acid (LYS470 with ASP103) showed RAF1 and second residue exhibited BCL2. The HBOND indicates hydrogen bonds and VDW specifies van der Waals forces.</p>
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<p>The BCL2-MAPK1 complex generated using HDOCK server was visualized using PyMOL, highlighting key connections including hydrogen bonds and hydrophobic interactions, where green shows BCL2 protein and cyan color indicates MAPK1.</p>
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<p>Protein–protein interaction analysis of BCL2-MAPK1 using HDOCK and RING server. The chord diagram demonstrates the connectivity and distribution of interacting residues between the proteins where first amino acid (ARG107 with ARG13) showed BCL2 and second residue displayed MAPK1. The HBOND indicates hydrogen bonds and VDW specifies van der Waals forces.</p>
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<p>Protein–protein interaction analysis of BCL2 with associated partners. The chord diagram highlights the key amino acid residues involved in both hydrogen as well as ionic bonding.</p>
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<p>MD simulations (200 ns) of BCL2, p53, and BCL2-p53 complex. (<b>a</b>) The RMSD plot showed the stability of the complex during the simulation, with fluctuations indicating conformational changes. (<b>b</b>) The RMSF analysis highlights the flexibility of individual residues within the complex. (<b>c</b>) The radius of gyration (Rg) indicates a stable overall conformation, whereas the (<b>d</b>) hydrogen bonding analysis reveals the average of 6–8 hydrogen bonds formed at the interface between the proteins during the simulation. The black and red color indicates original time series and average hydrogen bonds over (200 ns).</p>
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<p>MD simulations (200 ns) of BCL2, RAF1, and BCL2-RAF1 complex using Gromacs. (<b>a</b>) The RMSD plot of the complex showed conformational changes at the beginning of simulation, with a plateau phase indicating stability over time. (<b>b</b>) The RMSF analysis highlighted the flexibility of individual residues within the complex. (<b>c</b>) The radius of gyration (Rg) indicates a stable overall conformation, whereas the (<b>d</b>) hydrogen bonding reveals the protein–protein stability and increased interactions. The black and red color indicates original time series and average hydrogen bonds over (200 ns).</p>
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<p>MD simulations (200 ns) of BCL2-MAPK1 complex using Gromacs. (<b>a</b>) The RMSD plot of the complex shows greater conformational changes. (<b>b</b>) The RMSF analysis highlights the flexibility of individual residues within the complex. (<b>c</b>) The radius of gyration (Rg), indicates a stable conformation, whereas the (<b>d</b>) hydrogen bonding reveals the protein–protein stability, and increased interactions. The black and red color indicates original time series and average hydrogen bonds over (200 ns).</p>
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19 pages, 9350 KiB  
Article
Physiological Adaptation to Different Heavy Metal Stress in Seedlings of Halophyte Suaeda liaotungensis
by Jieqiong Song, Xiaoqi Cao, Ruixuan An, Haoran Ding, Wen Wang, Yahan Zhou, Chunyan Wu, Yizihan Cao, Hongfei Wang, Changping Li and Qiuli Li
Biology 2025, 14(3), 260; https://doi.org/10.3390/biology14030260 - 5 Mar 2025
Viewed by 144
Abstract
Soil contamination with heavy metals is a worldwide environmental issue that impacts plant growth and human health. This study is the first to investigate the tolerance and physiological response mechanism of Suaeda liaotungensis seedlings to heavy metal stress. The results exhibited that the [...] Read more.
Soil contamination with heavy metals is a worldwide environmental issue that impacts plant growth and human health. This study is the first to investigate the tolerance and physiological response mechanism of Suaeda liaotungensis seedlings to heavy metal stress. The results exhibited that the toxicity degree of Pb, Cd, Cu, and Zn to Suaeda liaotungensis seedlings was highest for Cd and lowest for Pb. Heavy metal stress increased H2O2 levels in seedlings, thereby aggravating lipid peroxidation of the cell membrane and consequently increasing MDA content. Meanwhile, the SOD and CAT activities in seedlings increased under heavy metal stress, whereas POD activity decreased consistently under Cd and Zn stress. The soluble sugars and proline content in seedlings also showed an increasing trend under heavy metal stress. Furthermore, the tolerance in the seedlings from black seeds to Pb and Cd stress was improved by enhancing SOD and CAT activities and accumulating proline. However, the tolerance in the seedlings from brown seeds to Cu stress was improved by increasing CAT activity as well as accumulating soluble sugar and proline content. The results reveal the response mechanism of Suaeda liaotungensis seedlings to heavy metal stress and provide the basis for utilizing Suaeda liaotungensis to improve heavy metal-contaminated saline soil. Full article
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<p>Phenotypes of seedlings from dimorphic seeds under heavy metal stress. Seedling growth of dimorphic seeds under Pb stress (<b>A</b>), Cd stress (<b>B</b>), Cu stress (<b>C</b>), and Zn stress (<b>D</b>). Bars = 5 mm.</p>
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<p>Effect of heavy metal stress on ROS content of seedlings of <span class="html-italic">S. liaotungensis</span>. O<sub>2</sub><sup>−.</sup> and H<sub>2</sub>O<sub>2</sub> content in seedlings from dimorphic seeds under Pb stress (<b>A</b>,<b>B</b>), Cd stress (<b>C</b>,<b>D</b>), Cu stress (<b>E</b>,<b>F</b>), and Zn stress (<b>G</b>,<b>H</b>). Under the same heavy metal concentration, significant difference between brown and black seeds is represented by distinct uppercase letters (<span class="html-italic">p</span> &lt; 0.05). Significant differences in O<sub>2</sub><sup>−.</sup> and H<sub>2</sub>O<sub>2</sub> content among different concentrations of heavy metals for the same seed type are represented by distinct lowercase letters (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of heavy metal stress on MDA content of seedlings of <span class="html-italic">S. liaotungensis</span>. MDA content in seedlings from dimorphic seeds under Pb stress (<b>A</b>), Cd stress (<b>B</b>), Cu stress (<b>C</b>), and Zn stress (<b>D</b>). Under the same heavy metal concentration, significant difference between brown and black seeds is represented by distinct uppercase letters (<span class="html-italic">p</span> &lt; 0.05). Significant difference in MDA content among varying heavy metal concentrations for the same seed type is represented by distinct lowercase letters (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of heavy metal stress on antioxidant enzyme activity of seedlings of <span class="html-italic">S. liaotungensis</span>. SOD, POD, and CAT activities in seedlings under Pb stress (<b>A</b>–<b>C</b>), Cd stress (<b>D</b>–<b>F</b>), Cu stress (<b>G</b>–<b>I</b>), and Zn stress (<b>J</b>–<b>L</b>). Under the same heavy metal concentration, significant difference between brown and black seeds is represented by distinct uppercase letters (<span class="html-italic">p</span> &lt; 0.05). Significant differences in SOD, POD, and CAT activities among varying heavy metal concentrations for the same seed type are represented by distinct lowercase letters (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of heavy metal stress on osmotic adjustment substances in seedlings from dimorphic seeds of <span class="html-italic">S. liaotungensis</span>. Soluble sugar and proline content of seedlings from dimorphic seeds under Pb stress (<b>A</b>,<b>B</b>), Cd stress (<b>C</b>,<b>D</b>), Cu stress (<b>E</b>,<b>F</b>), and Zn stress (<b>G</b>,<b>H</b>). Under the same heavy metal concentration, significant difference between brown and black seeds is represented by distinct uppercase letters (<span class="html-italic">p</span> &lt; 0.05). Significant difference among varying heavy metal concentrations for the same seed type is represented by distinct lowercase letters (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Principle component analysis (PCA) of physiological and biochemical traits of seedlings under heavy metal (Pb, Cd, Cu, and Zn) stress. Abbreviation: Br, brown seeds; Bl, black seeds; RL, root length; SL, shoot length; O<sub>2</sub><sup>−.</sup>, superoxide anion radical; H<sub>2</sub>O<sub>2</sub>, hydrogen peroxide; MDA, malondialdehyde; SOD, superoxide dismutase; POD, peroxidase; CAT, catalase; SS, soluble sugar; Pro, proline.</p>
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<p>The correlation analysis of the physiological and biochemical traits of seedlings under heavy metal (Pb, Cd, Cu, and Zn) stress. Red and blue represent positive and negative correlations, respectively. Correlation values are significant at * <span class="html-italic">p</span>&lt; 0.05, ** <span class="html-italic">p</span>&lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001, respectively. The red dot represents 0.05 &lt; <span class="html-italic">p</span> &lt; 0.1. Abbreviation: Br, brown seeds; Bl, black seeds; RL, root length; SL, shoot length; O<sub>2</sub><sup>−.</sup>, superoxide anion radical; H<sub>2</sub>O<sub>2</sub>, hydrogen peroxide; MDA, malondialdehyde; SOD, superoxide dismutase; POD, peroxidase; CAT, catalase; SS, soluble sugar; Pro, proline.</p>
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11 pages, 3295 KiB  
Article
Leontodon albanicus subsp. acroceraunicus (Asteraceae, Cichorieae): A New Subspecies from Southern Albania
by Fabio Conti, Luca Bracchetti, Marco Dorfner, Nadine Benda and Christoph Oberprieler
Biology 2025, 14(3), 259; https://doi.org/10.3390/biology14030259 - 4 Mar 2025
Viewed by 210
Abstract
Some plants belonging to the Leontodon sect. Asterothrix were collected from southern Albania. They were compared with the closest taxon (L. albanicus s.str.) from morphological and molecular (AFLPseq fingerprinting) points of view. Uni- and multivariate statistical analyses of morphological data revealed distinctive [...] Read more.
Some plants belonging to the Leontodon sect. Asterothrix were collected from southern Albania. They were compared with the closest taxon (L. albanicus s.str.) from morphological and molecular (AFLPseq fingerprinting) points of view. Uni- and multivariate statistical analyses of morphological data revealed distinctive discontinuities—especially in terms of the characteristics of the indumentum–that are paralleled by separation into two genetic clusters in AFLPseq fingerprinting. Following an integrated taxonomic approach based on morphological, genetic, and geographical sources of evidence, we show that the newly discovered population should be regarded as a new subspecies named Leontodon albanicus subsp. acroceraunicus. The new taxon is described and illustrated, and its relationship with L. albanicus subsp. albanicus is also discussed. We have no data to assess conservation status according to IUCN categories and criteria; however, considering that it is probably limited to the Acroceraunian Mountains, it deserves particular conservation interest. Full article
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<p>Scatter plot of Principal Component Analysis; accessions of the Ҫika population are on the left side (green triangles); accessions of the Nëmerçkë population of <span class="html-italic">L. albanicus</span> are on the right side (blue squares).</p>
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<p>Ordination of nine accessions of <span class="html-italic">Leontodon albanicus</span> on the first two axes of Principal Co-ordinate Analysis (PCoA) based on 9260 parsimony informative SNPs from AFLPseq fingerprinting with Jukes-Cantor distances as a measure of genetic similarity among accessions. Ҫika population is on the left (green triangles); Nëmerçkë population of <span class="html-italic">L. albanicus</span> is on the right (blue squares).</p>
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<p>Leaf hairs from a specimen of <span class="html-italic">L. albanicus</span> subsp. <span class="html-italic">albanicus</span> collected on Mt. Nëmerçkë.</p>
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<p>Leaf hairs from a specimen of <span class="html-italic">L. albanicus</span> subsp. acroceraunicus collected on Mt. Ҫika.</p>
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<p>Holotypus of <span class="html-italic">Leontodon albanicus</span> subsp. <span class="html-italic">acroceraunicus</span>.</p>
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<p>Distribution map of <span class="html-italic">Leontodon albanicus</span> according to the herbarium materials studied: subsp. <span class="html-italic">albanicus</span> (blue squares); subsp. <span class="html-italic">acroceraunicus</span> (green triangles).</p>
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16 pages, 24261 KiB  
Article
The Mutations in RcMYB114 Affect Anthocyanin Glycoside Accumulation in Rose
by Maofu Li, Yuan Yang, Hua Wang, Pei Sun, Shuting Zhou, Yanhui Kang, Xiangyi Sun, Min Jin and Wanmei Jin
Biology 2025, 14(3), 258; https://doi.org/10.3390/biology14030258 - 4 Mar 2025
Viewed by 300
Abstract
In plants, the R2R3-MYB transcription factors are one of the largest MYB gene families. These MYB transcription factors are very important for regulating plant growth and development. RcMYB114, RcbHLH, and RcWD40 promote anthocyanin accumulation by forming the MBW (MYB-bHLH-WD40) complex and determine the [...] Read more.
In plants, the R2R3-MYB transcription factors are one of the largest MYB gene families. These MYB transcription factors are very important for regulating plant growth and development. RcMYB114, RcbHLH, and RcWD40 promote anthocyanin accumulation by forming the MBW (MYB-bHLH-WD40) complex and determine the rose flower’s color. RcMYB114 genomic sequences differ between the red petal and white varieties. Two non-synonymous substitutions were found in the open reading frame. It leads to a change in amino acids. Here, the anthocyanin content showed that there was no anthocyanin in white petals, while the anthocyanin content in red petals increased firstly at stage 2, decreased slightly at stage 4, and then increased again at stage 5. The spatiotemporal expression pattern analysis showed that RcMYB114 was not expressed in all petals and tissues of white petals at different flower development stages. In red petal varieties, RcMYB114 was highly expressed in petals, followed by styles, and not expressed in stems, young leaves, and stage 1 of flower development. However, RcMYB114 has the highest expression level at the blooming stage. The RcMYB114 sequence contains 9 SNPs in the coding region, 7 of which were synonymous substitutions that had no effect on the translation product and 2 of which were non-synonymous substitutions that resulted in amino acid alteration at positions 116 and 195, respectively. The RcMYB114 gene in red rose was named RcMYB114a, and in white rose was RcMYB114b. RcMYB114c was mutated into leucine via artificial mutation; it was valine at position 116 of RcMYB114a, and Glycine mutated into Arginine at position 195 of RcMYB114a was RcMYB114d. RcMYB114b was the double mutation at positions 116 and 195 of RcMYB114a. The results of yeast two-hybrid experiments showed that RcMYB114a and its missense mutations RcMYB114b, RcMYB114c, and RcMYB114d could both interact with RcbHLH and RcWD40 to form the MYB-bHLH-WD40 complex. A transient transformation experiment in tobacco confirmed that RcMYB114a and its missense mutations RcMYB114b, RcMYB114c, and RcMYB114d could significantly promote the high expression of related structural genes in tobacco, together with the RcbHLH gene, which led to the accumulation of anthocyanins and produced the red color of the leaves. The RcMYB114a gene and its missense mutations RcMYB114b, RcMYB114c, and RcMYB114d interacted with the RcbHLH gene and significantly regulated the accumulation of anthocyanins. The two non-synonymous mutations of RcMYB114 do not affect the function of the gene itself, but the content of the anthocyanins accumulated was different. This study should provide clues and references for further research on the molecular mechanism underlying the determination of rose petal color. Full article
(This article belongs to the Special Issue Recent Advances in Biosynthesis and Degradation of Plant Anthocyanin)
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<p>Morphology and anthocyanin content in ‘Slater’s Crimson China’ flowers at different developmental stages. Slater’s Crimson China’ flowers at five different development stages. S1: small bud stage; S2: large bud stage; S3: initial opening period; S4: blooming period; S5: withering period; Anthocyanin content in ‘Slater’s Crimson China’ flowers at the five developmental stages. Asterisks (*) represent that the values of total anthocyanin content (n = 3, ±SE) are significantly different at <span class="html-italic">p</span> &lt; 0.05 as determined using independent <span class="html-italic">t</span>-test.</p>
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<p>The expression pattern of <span class="html-italic">RcMYB114</span> in ‘Slater’s Crimson China’. (<b>a</b>,<b>b</b>): Semiquantitative RT-PCR analysis of <span class="html-italic">RcMYB114</span> expression in different tissues and petals at different developmental stages of ‘Slater’s Crimson China’; (<b>c</b>,<b>d</b>): <span class="html-italic">RcMYB114</span> expression in ‘Slater’s Crimson China’ different tissues and petals at different developmental stages determined by quantitative RT-PCR. <span class="html-italic">Actin</span> gene was used as the internal reference gene. Asterisks (*) represent that the values of the corresponding transcription levels (n = 3, ±SE) are significantly different at <span class="html-italic">p</span> &lt; 0.05 as determined using independent <span class="html-italic">t</span>-test.</p>
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<p>Expression of structural genes of anthocyanin biosynthesis in ‘Slater’s Crimson China’ petals at different developmental stages. <span class="html-italic">PAL</span>: phenylalanine ammonia-lyase, <span class="html-italic">C4H</span>: cinnamate 4-hydroxylase, <span class="html-italic">CHI</span>: chalcone isomerase, <span class="html-italic">CHS</span>: chalcone synthase, <span class="html-italic">F3H</span>: flavanone 3-hydroxylase, <span class="html-italic">DFR</span>: dihydroflavonol-4-reductase/flavanone-4-reductase, <span class="html-italic">ANS</span>: anthocyanidin synthase, <span class="html-italic">UFGT</span>: flavonol-O-glucosyltransferases. Asterisks (*) represent that the values of the corresponding transcription levels (n = 3, ±SE) are significantly different at <span class="html-italic">p</span> &lt; 0.05 as determined using independent <span class="html-italic">t</span>-test.</p>
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<p>Cloning of <span class="html-italic">RcMYB114</span> in ‘Slater’s Crimson China’ and alignment of the deduced proteins. (<b>a</b>). Cloning of <span class="html-italic">RcMYB114</span> in ‘Slater’s Crimson China’ using genomic DNA (1) and cDNA (2) as templates; (<b>b</b>). Alignment of RcMYB114 proteins from ‘Slater’s Crimson China’. The red arrow indicates the difference in amino acids caused by two non-synonymous. The protein sequence RcMYB114a was cloned from red petal cDNA, and RcMYB114b was calculated from the genomic sequence <span class="html-italic">RcMYB114</span> in white petal variety.</p>
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<p>Comparison of the RcMYB114a and its mutant’s structures. (<b>a</b>,<b>b</b>). Predicted secondary structures of RcMYB114a, RcMYB114b, RcMYB114c, and RcMYB114d, in (<b>a</b>), the c: Random coil; e: Extended strand; h: α-helix; t: Beta turn; in (<b>b</b>), the pink module: Random coil; red module: Extended strand; blue module: α-helix; green module: Beta turn.</p>
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<p>Interaction of different RcMYB114 variants with RcWD40 and RcbHLH assessed by yeast two-hybrid (Y2H). (<b>a</b>). Schematic diagram of different vectors used for the Y2H experiment; (<b>b</b>). The co-transformants were incubated on SD/-Leu/-Trp plate; (<b>c</b>). The co-transformants were incubated on SD/-Trp/-Leu/-His/-Ade plate; (<b>d</b>). β-galactosidase tests were performed on the same SD/-Trp/-Leu/-His/-Ade plate, and positive clones were dyed by using 3–5 µL 4 mg/mL X-α-gal, and false-positive activation was excluded using the P53 plus SV40 vector.</p>
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<p>Morphologyand anthocyanin content of tobacco leaves transformed with different <span class="html-italic">RcMYB114</span> alleles. (<b>a</b>): Phenotype of tobacco leaves after injection of plasmids containing different <span class="html-italic">RcMYB114</span> alleles; (<b>b</b>): Assays of the anthocyanin contents of tobacco leaves that overexpressed different <span class="html-italic">RcMYB114</span> alleles. Assays were carried out with three biological replicates, with at least three plants injected for each replicate. Asterisks (*) represent that the values of total anthocyanin content (n = 3, ±SE) are significantly different at <span class="html-italic">p</span> &lt; 0.05 as determined using independent <span class="html-italic">t</span>-test.</p>
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20 pages, 10682 KiB  
Article
Temporal Profiling of Cellular and Molecular Processes in Osteodifferentiation of Dental Pulp Stem Cells
by Bibiána Baďurová, Kristina Nystøl, Terézia Okajček Michalič, Veronika Kucháriková, Dagmar Statelová, Slavomíra Nováková, Ján Strnádel, Erika Halašová and Henrieta Škovierová
Biology 2025, 14(3), 257; https://doi.org/10.3390/biology14030257 - 4 Mar 2025
Viewed by 101
Abstract
Based on the potential of DPSCs as the most promising candidates for bone tissue engineering, we comprehensively investigated the time-dependent cellular and molecular changes that occur during their osteodifferentiation. To analyze this area in-depth, we used both cellular and molecular approaches. Morphological changes [...] Read more.
Based on the potential of DPSCs as the most promising candidates for bone tissue engineering, we comprehensively investigated the time-dependent cellular and molecular changes that occur during their osteodifferentiation. To analyze this area in-depth, we used both cellular and molecular approaches. Morphological changes were monitored using bright-field microscopy, while the production of mineral deposits was quantified spectrophotometrically. The expression of a key mesenchymal stem cell marker, CD90, was assessed via flow cytometry. Finally, protein-level changes in whole cells were examined by fluorescence microscopy. Our results show successful long-term osteodifferentiation of the patient’s DPSCs within 25 days. In differentiated cells, mineralized extracellular matrix production gradually increased; in contrast, the expression of the specific stem cell marker CD90 significantly decreased. We observed dynamic changes in intracellular and extracellular proteins when collagen1 A1 and osteopontin appeared as earlier markers of osteogenesis, while apolipoprotein A2, bone morphogenetic protein 9, dentin sialophosphoprotein, and matrix metalloproteinase 8 were produced mainly in the late stages of this process. A decrease in actin microfilament expression indicated a reduction in cell proliferation, which could be used as another marker of osteogenic initiation. Our results suggest a coordinated process in vitro in which cells synthesize the necessary proteins and matrix components to regulate the growth of hydroxyapatite crystals and form the bone matrix. Full article
(This article belongs to the Special Issue Bone Cell Biology)
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<p>Cell morphology changes and cell density monitored by light microscopy before and during osteodifferentiation of DPSCs over 25 days. Control cells were cultivated in standard basal medium and differentiated cells in osteodifferentiation medium, which induced calcium deposit production in cells.</p>
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<p>Alizarin Red staining of calcium deposits of both control (DPSCs) and osteodifferentiated (Osteo) cells in a time-dependent manner over 25 days from the beginning of osteodifferentiation. (<b>a</b>) The stained mineral deposits were visualized by light microscopy; (<b>b</b>) Mineral deposit quantification was measured by a spectrophotometer. The graph shows an increase in calcium deposit production over 25 days. Gradual increase in calcium compounds in osteodifferentiated cells confirms bone matrix production. Control cells have a value of 100% at all time points. The values are the mean ± SD control and osteodifferentiated cells (<span class="html-italic">n</span> = 6). The statistical significance of the change between control and differentiated cells on each day is represented by the <span class="html-italic">p</span>-values <span class="html-italic">p</span> ≤ 0.05 (**) and <span class="html-italic">p</span> ≤ 0.005 (***).</p>
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<p>Flow cytometry analysis of control (DPSCs) and osteodifferentiated cells (Osteo) over 25 days. (<b>a</b>) Histograms show expression of CD90, a surface-specific marker of stem cell phenotype, in both types of cells; (<b>b</b>) The graph shows a decrease in CD90 expression in osteodifferentiated cells over a period of 25 days. Control cells have a value of 1 at all time points. The values are the mean ± SD control and osteodifferentiated cells (<span class="html-italic">n</span> = 6). The statistical significance of the change between control and differentiated cells on each day is represented by the <span class="html-italic">p</span>-values <span class="html-italic">p</span> ≤ 0.05 (**) and <span class="html-italic">p</span> ≤ 0.005 (***).</p>
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<p>Immunocytochemical staining of osteogenesis markers was performed using fluorescent antibodies over 25 days following the initiation of osteodifferentiation in dental pulp stem cells (DPSCs). Both control and osteodifferentiated cells were stained on the 5th, 10th, 15th, 20th, and 25th days with specific fluorescent antibodies against apolipoprotein A2 (APOA2), bone morphogenetic protein 9 (BMP9), collagen1 A1 (COL1A1), dentin sialophosphoprotein (DSPP), matrix metalloproteinase 8 (MMP8), and osteopontin (OPN). Actin filaments of the cytoskeleton were labeled with an antibody against phalloidin (PHALL). This figure represents the osteodifferentiated cells, while images of the control cells are shown in <a href="#app1-biology-14-00257" class="html-app">Figure S2</a>. Fluorescent signals were captured and analyzed using fluorescence microscopy.</p>
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<p>The graphs provide a graphical representation of the abundance of specific proteins, apolipoprotein A2 (APOA2), bone morphogenetic protein 9 (BMP9), collagen1 A1 (COL1A1), dentin sialophosphoprotein (DSPP), matrix metalloproteinase 8 (MMP8), osteopontin (OPN), and phalloidin (PHALL), which binds to actin filaments. The graphs represent the quantification of results from immunocytochemical analysis conducted over 25 days following the initiation of osteodifferentiation in DPSCs. The data are presented as a relative ratio to control cells, with control cells assigned a value of 1 (red line). The values are the mean ± SD osteodifferentiated vs. control cells (<span class="html-italic">n</span> = 6). The statistical significance of the change between control and differentiated cells on each day is represented by the <span class="html-italic">p</span>-values <span class="html-italic">p</span> ≤ 0.5 (*), <span class="html-italic">p</span> ≤ 0.05 (**), and <span class="html-italic">p</span> ≤ 0.005 (***).</p>
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23 pages, 5785 KiB  
Article
Uncovering New Biomarkers for Prostate Cancer Through Proteomic and Network Analysis
by Rossana Rossi, Elena Monica Borroni, Ishak Yusuf, Andrea Lomagno, Mohamed A. A. A. Hegazi, Pietro Luigi Mauri, Fabio Grizzi, Gianluigi Taverna and Dario Di Silvestre
Biology 2025, 14(3), 256; https://doi.org/10.3390/biology14030256 - 4 Mar 2025
Viewed by 138
Abstract
Background: Prostate cancer (PCa), is the second most prevalent solid tumor among men worldwide (7.3%), and the leading non-skin cancer in USA where it represents 14.9% of all new cancer cases diagnosed in 2024. This multifactorial disease exhibits substantial variation in incidence and [...] Read more.
Background: Prostate cancer (PCa), is the second most prevalent solid tumor among men worldwide (7.3%), and the leading non-skin cancer in USA where it represents 14.9% of all new cancer cases diagnosed in 2024. This multifactorial disease exhibits substantial variation in incidence and mortality across different ethnic groups and geographic regions. Although prostate-specific antigen (PSA) remains widely used as a biomarker for PCa, its limitations reduce its effectiveness for accurate detection. Consequently, finding molecules that can either complement PSA and other biomarkers is a major goal in PCa research. Methods: Urine samples were collected from healthy donors (n = 5) and patients with low- and high-risk PCa (4 and 7 subjects, respectively) and were analyzed using proteomic data-derived systems and biology approaches. The most promising proteins were further investigated by means of The Cancer Genome Atlas (TCGA) database to assess their associations with clinical and histopathological characteristics in a larger in silico patient population. Results: By evaluating the variations in the urinary proteome as a mirror of the changes occurring in prostate tumor tissue, components of complement and coagulation cascades and glutathione metabolism emerged as hallmarks of low- and high-risk PCa patients, respectively. Moreover, our integrated approach highlighted new potential biomarkers, including CPM, KRT8, ITIH2, and RCN1. Conclusions: The good overlap of our results with what is already reported in the literature supports the new findings in the perspective of improving the knowledge on PCa. Furthermore, they increase the panel of biomarkers that could enhance PCa management. Of course, further investigations on larger patient cohorts are required. Full article
(This article belongs to the Special Issue Computational Discovery Tools in Genomics and Precision Medicine)
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<p>Proteomic analysis was performed on urine samples from HD and PCa patients categorized as low- (LRPCa) and high-risk (HRPCa). (<b>A</b>) Spearman’s correlation was used to compare the global protein profiles of HD, LRPCa, and HRPCa groups. (<b>B</b>) A Venn diagram shows proteins uniquely identified in HD, LRPCa, and HRPCa groups. Red, green, and blue rectangles show proteins found in at least 40% of subjects per group. (<b>C</b>) Hierarchical clustering and (<b>D</b>) Principal Component Analysis (PCA) were conducted using peptide spectrum matches (PSMs) of differentially abundant proteins (DAPs) extracted via Linear Discriminant Analysis (LDA); both show a good grouping based on the health status of the subjects considered. Principal Component1 (PC1) and Principal Component2 (PC2) accounted for 65.4% and 8.7% of the variance, respectively. Hierarchical clustering employed <span class="html-italic">Euclidean</span> distance metrics and <span class="html-italic">Ward</span>’s method.</p>
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<p>Functional enrichment analysis. (<b>A</b>) GO biological process, (<b>B</b>) pathways, (<b>C</b>) GO molecular function, (<b>D</b>) COMPARTMENT, (<b>E</b>) and GO cellular component differentially enriched by comparing HD (red), LRPCa (green) and HRPCa (blue) groups. The functional modules were enriched starting from the whole protein profile characterized per subject (FDR ≤ 0.05), while the enrichment profiles were compared by linear discriminant analysis (LDA, <span class="html-italic">p</span> ≤ 0.05).</p>
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<p>Protein–protein interaction (PPI) network and functional modules differentially abundant in (<b>A</b>) HD, (<b>B</b>) LRPCa and (<b>C</b>) HRPCa. The PPI network was reconstructed starting from proteins selected as differentially abundant (DAPs, <span class="html-italic">n</span> = 141); only database (score ≥ 0.3) and experiment (score ≥ 0.15) annotated interactions were considered. The functional modules were defined through STRING and BINGO Cytoscape’s APPs (<span class="html-italic">p</span> ≤ 0.05). The color code, from blue to red, is based on the normalized PSM values (range 0–100) and indicates low (blue) and high (red) abundant proteins.</p>
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<p>Network topology. (<b>A</b>) Media netw (<b>A</b>) Average network centralities calculated for the HD, LRPCa and HRPCa PPI network models. (<b>B</b>) Violin plots of betweenness from HD, LRPCa and HRPCa PPI random network models; the average value of betweenness in real models (<b>A</b>) differs from that of random networks validating the selection of hubs/bottlenecks. (<b>C</b>) Hubs and bottlenecks from HD, (<b>D</b>) LRPCa and (<b>E</b>) HRPCa; specifically, blue gene names indicate hubs selected by betweenness and centroid, red gene names indicate bottlenecks selected by betweenness and bridging, while black bold gene names indicate hubs/bottlenecks selected by betweenness, centroid and bridging centralities. Hubs and bottlenecks were related to their main functions, and the GO chord plots show that in PCa patients, they mainly fall in cell cycle, complement and coagulation cascade, immune response and proteolysis.</p>
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<p>TCGA bioinformatic analysis. (<b>A</b>) Heatmap illustrating the frequency of protein expression in urine samples from healthy donors (HD) and prostate cancer-affected (PCa) patients. (<b>B</b>) TCGA expression data for Carboxypeptidase M (CPM) across a pan-cancer dataset, comparing expression levels in tumor tissues (red) versus their normal counterparts (blue). (<b>C</b>) CPM expression in normal vs. primary tumor. (<b>D</b>) CPM expression in normal versus PCa tissues with different Gleason score (GS). (<b>E</b>) TIMER analysis correlating CPM expression with immune cell infiltration. (<b>F</b>) TCGA expression data for Keratin, type II cytoskeletal 8 (KRT8) across a pan-cancer dataset, comparing expression levels in tumor tissues (red) versus their normal counterparts (blue); Wilcoxon test <span class="html-italic">p</span> ≤ 0.05. (<b>G</b>) KRT8 expression in normal vs. primary tumor. (<b>H</b>) KRT8 expression in normal versus PCa tissues with different Gleason score (GS); Wilcoxon test <span class="html-italic">p</span> ≤ 0.05. (<b>I</b>) TIMER analysis correlating KRT8 expression with immune cell infiltration.</p>
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<p>TCGA bioinformatic analysis. (<b>A</b>) Heatmap illustrating the frequency of protein expression in urine samples from prostate cancer-affected patients classified LRPCa and HRPCa. (<b>B</b>) TCGA expression data for Inter-alpha-trypsin inhibitor heavy chain H2 (ITIH2) across a pan-cancer dataset, comparing expression levels in tumor tissues (red) versus their normal counterparts (blue). (<b>C</b>) ITIH2 expression in normal vs. primary tumor. (<b>D</b>) ITIH2 expression in normal versus PCa tissues with different Gleason scores (GS). (<b>E</b>) TIMER analysis correlating ITIH2 expression with immune cell infiltration. (<b>F</b>) TCGA expression data for Reticulocalbin-1 (RCN1) across a pan-cancer dataset, comparing expression levels in tumor tissues (red) versus their normal counterparts (blue); Wilcoxon test <span class="html-italic">p</span> ≤ 0.05. (<b>G</b>) RCN1 expression in normal vs. primary tumor. (<b>H</b>) RCN1 expression in normal versus PCa tissues with different Gleason score (GS); Wilcoxon test <span class="html-italic">p</span> ≤ 0.05. (<b>I</b>) TIMER analysis correlating RCN1 expression with immune cell infiltration.</p>
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10 pages, 535 KiB  
Article
Investigating the Temporal Effects of Thermal Stress on Corticosterone Release and Growth in Toad Tadpoles
by Saeid Panahi Hassan Barough, Dillon J. Monroe, Thomas C. Clark and Caitlin R. Gabor
Biology 2025, 14(3), 255; https://doi.org/10.3390/biology14030255 - 3 Mar 2025
Viewed by 285
Abstract
Corticosterone (CORT) is a key glucocorticoid hormone that regulates energy balance and physiological responses to environmental stressors, making it a valuable biomarker for assessing how organisms cope with changing conditions. Understanding how amphibians respond to chronic thermal stress is critical in the context [...] Read more.
Corticosterone (CORT) is a key glucocorticoid hormone that regulates energy balance and physiological responses to environmental stressors, making it a valuable biomarker for assessing how organisms cope with changing conditions. Understanding how amphibians respond to chronic thermal stress is critical in the context of climate change and urbanization. We investigated the effects of a week-long exposure to elevated water temperatures on CORT release rates and growth in Gulf Coast toad (Incilius nebulifer) tadpoles, a species adapted to variable thermal environments. Using a non-invasive water-borne hormone method, we measured CORT at multiple time points (1 h, 2 h, 6 h, 24 h, 48 h, and 5 days) post-treatment to assess how CORT varied with time after exposure to elevated heat vs. the control temperature. We found a significant time-by-treatment response in tadpoles after a week of exposure to 32 °C versus 23 °C (control) temperatures. Both control and treatment individuals showed a marked decrease in CORT release rates 6 h post-return to room temperature, but by 24 h post-experiment, CORT release rates were higher in the tadpoles exposed to 32 °C. Heat-exposed tadpoles also showed significantly faster growth during and after treatment, but a lower survival to 12 days, indicating a potential trade-off between survival and accelerated growth. Overall, our study highlights a trade-off for populations of I. nebulifer when exposed to thermal stress and suggests that amphibian responses to chronic environmental stressors are shaped by adaptive physiological strategies, with implications for understanding and conserving amphibian populations in a rapidly changing world. Full article
(This article belongs to the Section Conservation Biology and Biodiversity)
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<p>Corticosterone release rates (pg/g/h) over time from Day 1 (baseline 23 °C) before exposure, at which point <span class="html-italic">Incilius nebulifer</span> tadpoles were exposed to higher (H) water temperature (32 °C) or lower (L) water temperature (23 °C) for 7 days. On Day 8, the tadpoles were returned to the same water temperature (23 °C). The boxplot at each time point explains the distribution of data, while the points represent individual observations. Different letters indicate significant differences.</p>
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<p>Mass (g) of <span class="html-italic">Incilius nebulifer</span> tadpoles over time starting from before exposure, to 32 °C water, to the end of 7 days of exposure, and after 5 more days when both treatments were maintained at 23 °C. Different letters indicate significant differences.</p>
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24 pages, 4398 KiB  
Article
Seasonal Occurrence and Biodiversity of Insects in an Arid Ecosystem: An Ecological Study of the King Abdulaziz Royal Reserve, Saudi Arabia
by Abdulrahaman S. Alzahrani, Moutaman Ali Kehail, Sara A. Almannaa, Areej H. Alkhalifa, Abdulaziz M. Alqahtani, Mohammed H. Altalhi, Hussein H. Alkhamis, Abdullah M. Alowaifeer and Abdulwahed Fahad Alrefaei
Biology 2025, 14(3), 254; https://doi.org/10.3390/biology14030254 - 2 Mar 2025
Viewed by 301
Abstract
Each living organism thrives best in a habitat that provides optimal conditions for flourishing, reproduction, and distribution within a certain area. This study aims to investigate the seasonal variation in insect biodiversity across different sites of the King Abdulaziz Royal Reserve (KARR), located [...] Read more.
Each living organism thrives best in a habitat that provides optimal conditions for flourishing, reproduction, and distribution within a certain area. This study aims to investigate the seasonal variation in insect biodiversity across different sites of the King Abdulaziz Royal Reserve (KARR), located between E 45.19–46.57 and N 25.15–27.41, with a focus on assessing biodiversity, density and seasonal variation using active and passive methods, over the period from January to November 2023. A total of 68 sites within the study area were randomly selected for trap placement. The trapped specimens were labeled and transferred to plastic bottles half filled with 70% ethanol and then taken to the laboratory for counting and identification. Identification was based on morphological characteristics and appropriate identification keys, with the assistance of entomological expertise, and a list of local species. Simpson’s diversity index (D) was also calculated. The results revealed that, out of 6320 trapped insects, species were identified across six orders: Blattodea (termites), represented by 2 families and 2 species; Coleoptera, comprising 12 families and 38 species, of which 11 belonged to the family Tenebrionidae; Hemiptera, comprising 7 families and 9 species, 3 of which belonged to the family Lygaeidae; Hymenoptera, comprising 5 families and 15 species, 9 of which were from Formicidae; Lepidoptera, comprising 2 families and 3 species; and Orthoptera, comprising 3 families and 7 species, 4 of which were from family Acrididae. Insect biodiversity and abundance were observed to be relatively low during the winter (January–March) and autumn (October–November) seasons, while relatively higher densities were recorded during spring (May) and summer (August–September). Full article
(This article belongs to the Section Zoology)
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<p>Map of the study area showing locations of different sites within KARR.</p>
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<p>Biodiversity of insects within KARR according to No. of species within each family.</p>
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<p>Relative abundance of insects within KARR according to No. of individual insects within each order (Lepidoptera represented less than 1%).</p>
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<p>Relative abundance of insects trapped during winter season (January–March 2023). Lepidoptera represented less than 1%.</p>
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<p>Relative abundance of insect orders trapped during spring season (May 2023).</p>
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<p>Relative abundance of insect order trapped during summer (August–September 2023).</p>
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<p>Relative abundance of insect orders trapped during autumn (October–November 2023).</p>
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34 pages, 2242 KiB  
Review
Druggable Molecular Networks in BRCA1/BRCA2-Mutated Breast Cancer
by Francesca Pia Carbone, Pietro Ancona, Stefano Volinia, Anna Terrazzan and Nicoletta Bianchi
Biology 2025, 14(3), 253; https://doi.org/10.3390/biology14030253 - 2 Mar 2025
Viewed by 356
Abstract
Mutations in the tumor suppressor genes BRCA1 and BRCA2 are associated with the triple-negative breast cancer phenotype, particularly aggressive and hard-to-treat tumors lacking estrogen, progesterone, and human epidermal growth factor receptor 2. This research aimed to understand the metabolic and genetic links behind [...] Read more.
Mutations in the tumor suppressor genes BRCA1 and BRCA2 are associated with the triple-negative breast cancer phenotype, particularly aggressive and hard-to-treat tumors lacking estrogen, progesterone, and human epidermal growth factor receptor 2. This research aimed to understand the metabolic and genetic links behind BRCA1 and BRCA2 mutations and investigate their relationship with effective therapies. Using the Cytoscape software, two networks were generated through a bibliographic analysis of articles retrieved from the PubMed-NCBI database. We identified 98 genes deregulated by BRCA mutations, and 24 were modulated by therapies. In particular, BIRC5, SIRT1, MYC, EZH2, and CSN2 are influenced by BRCA1, while BCL2, BAX, and BRIP1 are influenced by BRCA2 mutation. Moreover, the study evaluated the efficacy of several promising therapies, targeting only BRCA1/BRCA2-mutated cells. In this context, CDDO-Imidazolide was shown to increase ROS levels and induce DNA damage. Similarly, resveratrol decreased the expression of the anti-apoptotic gene BIRC5 while it increased SIRT1 both in vitro and in vivo. Other specific drugs were found to induce apoptosis selectively in BRCA-mutated cells or block cell growth when the mutation occurs, i.e., 3-deazaneplanocin A, genistein or daidzein, and PARP inhibitors. Finally, over-representation analysis on the genes highlights ferroptosis and proteoglycan pathways as potential drug targets for more effective treatments. Full article
(This article belongs to the Special Issue Advances in Biological Breast Cancer Research)
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<p>Scheme of progressive steps for the selection of articles including all criteria: <span class="html-italic">BRCA</span> mutations, modulated genes and drug treatments for network creation.</p>
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<p>Link between apoptosis and genomic instability in BC cells. For <span class="html-italic">BRCA2</span>, we analyzed studies and evaluated the most impacted genes. In this case, <span class="html-italic">BRCA2</span> was represented as the “node” in the blue octagon, whilst the other genes were the “edges” in purple rectangles. Flat-tipped lines represent downregulation, whereas pointed arrows represent upregulation, and the brown lines are representative for phytoestrogen treatment.</p>
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<p>Network of correlation between altered genes by <span class="html-italic">BRCA1</span> mutation and treatments. (<b>A</b>) We used colors to graphically highlight <span class="html-italic">BRCA1</span> (light blue octagon) and the deregulated genes (white rectangles). <span class="html-italic">BRCA1</span> was represented as the “node”, whereas the other genes were named “edges”. Flat-tipped lines represent the downregulation of gene expression, while the pointed arrows represent upregulation. The colored lines represent the different treatments used on <span class="html-italic">BRCA1</span>-mutated cell lines and their effect on gene expression. Dashed lines are used to depict secondary interactions whereas the continuous lines portray primary and direct interactions. (<b>B</b>) Highlighting of the genes modulated by therapies.</p>
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<p>Bar chart of the top 20 KEGG pathways. The image was created with Python v.3.13.1 (matplotlib).</p>
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13 pages, 1203 KiB  
Article
Small Extracellular Vesicles with a High Sphingomyelin Content Isolated from Hypertensive Diabetic db/db Mice Inhibits Calcium Mobilization and Augments Amiloride-Sensitive Epithelial Sodium Channel Activity
by Hunter Ramsay, Ling Yu, Faisal F. Alousi and Abdel A. Alli
Biology 2025, 14(3), 252; https://doi.org/10.3390/biology14030252 - 1 Mar 2025
Viewed by 226
Abstract
Extracellular vesicles (EVs) contain bioactive lipids that play a key role in pathophysiology. We hypothesized that EVs released from salt-loaded hypertensive diabetic db/db mice have increased bioactive lipid content that inhibits intracellular calcium mobilization and increases the activity of renal epithelial sodium channels [...] Read more.
Extracellular vesicles (EVs) contain bioactive lipids that play a key role in pathophysiology. We hypothesized that EVs released from salt-loaded hypertensive diabetic db/db mice have increased bioactive lipid content that inhibits intracellular calcium mobilization and increases the activity of renal epithelial sodium channels (ENaC). An enrichment of sphingomyelins (SMs) was found in small urinary EVs (uEVs) isolated from salt-loaded hypertensive diabetic db/db mice (n = 4) compared to non-salt loaded db/db mice with diabetes alone (n = 4). Both groups of mice were included in the same cohort to control for variability. Cultured mouse cortical collecting duct (mpkCCD) cells loaded with a calcium reporter dye and challenged with small uEVs from hypertensive diabetic db/db mice showed a decrease in calcium mobilization when compared to cells treated with small uEVs from diabetic db/db mice. The amiloride-sensitive transepithelial current was increased in mpkCCD cells treated with small uEVs with abundant sphingomyelin content from hypertensive diabetic db/db mice in a dose- and time-dependent manner. Similar results were observed in mpkCCD cells and Xenopus 2F3 cells treated with exogenous sphingomyelin in a time-dependent manner. Single-channel patch clamp studies showed a decrease in ENaC activity in cells transiently transfected with sphingomyelin synthase 1/2 specific siRNA compared to non-targeting siRNA. These data suggest EVs with high sphingomyelin content positively regulate renal ENaC activity in a mechanism involving an inhibition of calcium mobilization. Full article
(This article belongs to the Special Issue Physiology and Pathophysiology of the Kidney)
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<p>Quantification of sphingomyelin concentration in small urinary extracellular vesicles isolated from the urine of diabetic db/db mice and salt-loaded hypertensive diabetic db/db mice. EVs were isolated from separate collections of urine (30 mLs each) from diabetic db/db mice (N = 4) and salt-loaded hypertensive diabetic db/db mice (N = 4). The concentration of each uEV preparation was normalized after performing NanoSight analysis. The small uEVs were lysed in RIPA buffer and the number of sphingomyelins present in the samples was determined by performing an in vitro sphinomyelin fluorescent-based assay. N = 4 per group. A Student <span class="html-italic">t</span> test was performed to compare the two groups. * represents a <span class="html-italic">p</span>-value &lt; 0.05.</p>
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<p>Small urinary EVs from salt-loaded hypertensive diabetic db/db mice compared to diabetic db/db mice inhibit calcium influx in mpkCCD cells. (<b>A</b>) Summary analysis showing a transient influx in intracellular calcium mediated by ionomycin (Ion) after pretreating mpkCCD cells with small uEVs from each group; (<b>B</b>) Representative immunofluorescence images before (left panel) and after (right panel) calcium influx; (<b>C</b>) Summary graph of the relative fluorescent intensity in (<b>B</b>). N = 4 per group. A Student <span class="html-italic">t</span> test was performed to compare the two groups. uEVs refer to urinary extracellular vesicles. NS refers to normal salt (non-salt loaded diabetic db/db mice). HS refers to high salt (salt-loaded hypertensive diabetic db/db mice). * represents a <span class="html-italic">p</span>-value &lt; 0.05.</p>
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<p>Exogenous sphingomyelins (SM-6) (1 μM) augment amiloride-sensitive transepithelial current in mpkCCD cells and in <span class="html-italic">Xenopus</span> 2f3 cells. (<b>A</b>) transepithelial current in mpkCCD cells treated with SM-6 or VEH. (<b>B</b>) transepithelial current in 2f3 cells treated with SM-6 or VEH. At the end of the experiment for each cell type, 1 μM amiloride was administered on the apical side as a measure of amiloride-sensitive transepithelial current. Closed squares represent cells treated with vehicle and open circles represent cells treated with SM-6. N = 4 per group. A Student <span class="html-italic">t</span> test was performed to make comparisons between the two groups. VEH represents vehicle. SM-6 represents sphingomyelin-6. * represents a <span class="html-italic">p</span>-value &lt; 0.05.</p>
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<p>Patch clamp analysis of a highly selective cation channel in mouse mpkCCD cells transiently transfected with sphingomyelin synthase 1 and 2 specific siRNA or non-targeting control siRNA. mpkCCD cells transfected with sphingomyelin synthase 1 and 2 siRNA or non-targeting control siRNA were patched for ENaC single channel activity. (<b>A</b>) NPo as a measure of ENaC activity, (<b>B</b>) N, as a measure of the number of channels in a patch, (<b>C</b>) Po, as a measure of the open probability of the channel. The numbers at the top of the plots indicate the number of patches per group. (<b>D</b>) representative traces where C represents the closed state and O represents the open state. (<b>E</b>) Current voltage curve. (<b>F</b>) Representative Western blot for smgs1 (top blot) to assess siRNA mediated knockdown of Smgs1 and transfection efficiency in mpkCCD cells. The Western blot for actin (bottom blot) was used to assess lane loading. Densitometric analysis and plot of the Smgs1 protein band normalized to actin (right). siRNA sgms refers to sphingomyelin synthase 1/2 specific siRNA. siRNA ctrl refers to non-targeting control siRNA. NS refers to no significant difference between the groups. The number of experiments for each group is given at the top of panels A–C. For NPo and N, N = 24 in each group. A Student <span class="html-italic">t</span> test was performed to compare the two groups. * represents a <span class="html-italic">p</span>-value &lt; 0.05.</p>
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24 pages, 2530 KiB  
Review
The Gut Microbiota and Colorectal Cancer: Understanding the Link and Exploring Therapeutic Interventions
by Imen Zalila-Kolsi, Dhoha Dhieb, Hussam A. Osman and Hadjer Mekideche
Biology 2025, 14(3), 251; https://doi.org/10.3390/biology14030251 - 28 Feb 2025
Viewed by 348
Abstract
CRC remains a significant public health challenge due to its high prevalence and mortality rates. Emerging evidence highlights the critical role of the gut microbiota in both the pathogenesis of CRC and the efficacy of treatment strategies, including chemotherapy and immunotherapy. Dysbiosis, characterized [...] Read more.
CRC remains a significant public health challenge due to its high prevalence and mortality rates. Emerging evidence highlights the critical role of the gut microbiota in both the pathogenesis of CRC and the efficacy of treatment strategies, including chemotherapy and immunotherapy. Dysbiosis, characterized by imbalances in microbial communities, has been implicated in CRC progression and therapeutic outcomes. This review examines the intricate relationship between gut microbiota composition and CRC, emphasizing the potential for microbial profiles to serve as biomarkers for early detection and prognosis. Various interventions, such as prebiotics, probiotics, postbiotics, fecal microbiota transplantation, and dietary modifications, aim to restore microbiota balance and shift dysbiosis toward eubiosis, thereby improving health outcomes. Additionally, the integration of microbial profiling into clinical practice could enhance diagnostic capabilities and personalize treatment strategies, advancing the field of oncology. The study of intratumoral microbiota offers new diagnostic and prognostic tools that, combined with artificial intelligence algorithms, could predict treatment responses and assess the risk of adverse effects. Given the growing understanding of the gut microbiome–cancer axis, developing microbiota-oriented strategies for CRC prevention and treatment holds promise for improving patient care and clinical outcomes. Full article
(This article belongs to the Special Issue Probiotics and Gut Microbiome-Prospects and Challenges)
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<p>Dysbiosis of the gut microbiota and its connection to CRC. Three mechanisms, comprising the dysregulation of immune responses, virulence factors/toxins, and metabolic products, could be used to induce chronic inflammation and, consequently, the beginning and progression of cancer via dysbiosis of the gut microbiota and an increase in the quantity of pathogenic bacteria.</p>
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<p>Relationship between gut microbiota dysbiosis, colorectal cancer, immune system, and chemoresistance. Numerous factors impact dysbiosis of the gut microbiota, which in turn affects a number of processes, including immune system activation, cancer progression, and the emergence of chemoresistance.</p>
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<p>The gut microbiome’s impact on colon epithelial cells’ (CECs) genome and epigenome. (<b>a</b>). Specific microbes cause DNA damage in CECs through their toxins. Other microbes affect macrophages, leading to chromosomal instability and mutations in cancer-related genes. (<b>b</b>). Gut microbes, shown using antibiotics and germ-free mice, trigger gene hypermethylation and hypomethylation in CRC pathways. (<b>c</b>). Gut microbes, demonstrated with antibiotics and germ-free mice, do not typically affect global chromatin structure in CECs but alter promoter and enhancer regions in CRC pathways. (<b>d</b>). Gut microbes, shown using antibiotics and germ-free mice, influence the expression of oncomiRNAs and anti-oncomiRNAs in CECs. Abbreviations: pks (Polyketide Synthase), ETBF (Enterotoxigenic <span class="html-italic">Bacteroides Fragilis</span>), IRF (Interferon Regulatory Factor), STAT (Signal Transducer and Activator of Transcription), ETS (E26 Transformation-Specific), CRC (Colorectal Cancer), TGF (Transforming Growth Factor), TGF-β (Transforming Growth Factor Beta), and GPCR (G Protein-Coupled Receptor). Symbols: The “<span class="html-italic">*</span>” indicates the passenger strand of the miRNA duplex. A circle symbol represents spherical cocci bacteria, while an ellipse symbol represents rod-shaped bacilli bacteria.</p>
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<p>Potential of microbiome analysis-derived data to advance novel diagnostic capabilities in cancer.</p>
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16 pages, 1748 KiB  
Article
IL-1 Receptor Antagonist Anakinra Inhibits the Effect of IL-1β- Mediated Osteoclast Formation by Periodontal Ligament Fibroblasts
by Elizabeth Steemers, Wael M. I. Talbi, Jolanda M. A. Hogervorst, Ton Schoenmaker and Teun J. de Vries
Biology 2025, 14(3), 250; https://doi.org/10.3390/biology14030250 - 28 Feb 2025
Viewed by 252
Abstract
Rheumatoid arthritis and periodontitis are comorbidities that share mutual pathways. IL-1β is a pro-inflammatory cytokine that plays a crucial role in both diseases. One of the treatment options for rheumatoid arthritis is the use of an IL-1 receptor antagonist (IL-1RA) such as anakinra. [...] Read more.
Rheumatoid arthritis and periodontitis are comorbidities that share mutual pathways. IL-1β is a pro-inflammatory cytokine that plays a crucial role in both diseases. One of the treatment options for rheumatoid arthritis is the use of an IL-1 receptor antagonist (IL-1RA) such as anakinra. Anakinra tempers the disease by decreasing bone resorption and it could possibly stimulate bone formation. Here, we investigate the effect of anakinra in a periodontal disease setting on osteoclastogenesis by co-culturing periodontal ligament fibroblasts (PDLFs) and peripheral blood mononuclear cells (PBMCs) that contain monocytes, a source of osteoclast precursors, as well as by culturing PBMCs alone. The effect of anakinra on PDLF-mediated osteogenesis was studied under mineralization conditions. To mimic a chronic infection such as that prevalent in periodontitis, 10 ng/mL of IL-1β was added either alone or with 10 µg/mL of anakinra. Osteoclastogenesis experiments were performed using co-cultures of PDLF and PBMCs and PBMCs only. Osteoclastogenesis was determined through the formation of multinucleated cells in co-cultures of PDLF and PBMCs, as well as PBMCs alone, at day 21, and gene expression through qPCR at day 14. Osteogenesis was determined by measuring alkaline phosphatase activity (ALP) per cell at day 14. Anakinra is effective in downregulating IL-1β mediated leukocyte clustering and osteoclastogenesis in the co-cultures of both PDLF and PMBCs and PBMCs alone. Gene expression analysis shows that IL-1β increases the expression of the osteoclastogenic marker RANKL and its own expression. This higher expression of IL-1β at the RNA level is reduced by anakinra. Moreover, IL-1β downregulates OPG expression, which is upregulated by anakinra. No effects of anakinra on osteogenesis were seen. Clinically, these findings suggest that anakinra could have a beneficial systemic effect on periodontal breakdown in rheumatoid arthritis patients taking anakinra. Full article
(This article belongs to the Special Issue Bone Cell Biology)
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<p>Outline of experiments. Timeline in days. The periodontal ligament fibroblasts (PDLFs) were seeded 1 day before the start of the experiment. Anakinra was added to the osteogenesis (<b>A</b>) and osteoclastogenesis (<b>B</b>) experiments. (<b>C</b>) A graphical explanation of the co-culture osteoclastogenesis experiments, with the PDLFs in pink and the osteoclast precursor that differentiates into a multinucleated osteoclast in green.</p>
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<p>(<b>A</b>–<b>C</b>): Titration experiments with anakinra on osteoclast formation (<b>A</b>,<b>B</b>) and alkaline phosphatase activity in osteogenesis experiments (<b>C</b>). (<b>A</b>) Number of osteoclasts in co-culture of PDLF and PBMCs. (<b>B</b>) Number of osteoclasts in PBMC-only culture. For these experiments, 3 PDLF donors were used in (<b>A</b>). PBMCs only, in (<b>B</b>), were seeded in quadruplicate. *: <span class="html-italic">p</span> &lt; 0.05. (<b>C</b>) Increased concentration of anakinra does not affect alkaline phosphatase activity. ALP/DNA (nMol/ng DNA): alkaline phosphatase enzyme activity per cell at days 0 (<b>C</b>) and 14 (C—normal medium without anakinra, 0.01, 0.1, 1, 10 μg/mL anakinra in mineralization medium). Activity was measured at day 0 (t = 0) and at day 14 for all subsequent measures. C = control without mineralization medium, M = with mineralization medium. Results from 3 PDLF donors.</p>
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<p>(<b>A</b>–<b>D</b>): IL-1Β induces large osteoclasts and this is reduced with anakinra in cultures containing only PBMC at high density. PBMCs were cultured and osteoclast formation was assessed at 21 days after TRAcP staining. (<b>A</b>) Yellow arrow: osteoclast with more than 6 nuclei. (<b>B</b>) Number of osteoclasts with 3–5 nuclei in PBMC culture. (<b>C</b>) Osteoclast count with ≥6 nuclei in PBMC culture. (<b>D</b>) Total osteoclast nuclei (≥3 nuclei). *: <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt;0.01. Results are from quadruplicate plating of PBMCs.</p>
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<p>(<b>A</b>-<b>C</b>): IL-1Β induces cluster formation and subsequent osteoclast formation in co-cultures of PDLF and PBMCs. (<b>A</b>) Cluster formation (white arrows) in the presence of IL-1Β at 14 days. (<b>B</b>) Absence of clusters in the case of IL-1Β and anakinra (Ana). (<b>C</b>) Number of leukocyte cell clusters under the four conditions (control, IL-1Β, IL-1Β with anakinra, anakinra). (<b>D</b>–<b>G</b>): IL-1Β induces more osteoclasts with a higher number of nuclei in PDLF-PBMC co-cultures at day 21. Anakinra decreases the total osteoclast count at day 21. (<b>D</b>) Yellow arrows: osteoclasts with more than 6 nuclei; white arrows: osteoclast with less than 6 nuclei. (<b>E</b>) Number of osteoclasts with 3-5 nuclei in PDLF-PBMC co-culture. (<b>F</b>) Number of osteoclasts with ≥6 nuclei in PDLF-PBMC co-culture. (<b>G</b>) Total osteoclasts ≥3 nuclei in PDLF-PBMC co-culture. *: <span class="html-italic">p</span> &lt; 0.05. Experiments from 7 PDLF donors are shown.</p>
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<p>(<b>A</b>–<b>H</b>): Gene expression at 0 days or 14 days (PDLF-PBMC co-cultures without addition (<b>C</b>) or with IL-1Β, IL-1Β with anakinra and anakinra) of RANKL (<b>A</b>), OPG (<b>B</b>), ratio RANKL/OPG (<b>C</b>), IL-1Ββ (<b>D</b>), IL-1ΒRa (<b>E</b>), TNF-α (<b>F</b>), DC-STAMP (<b>G</b>), TRAcP (<b>H</b>). All data are from 7 PDLF donors. RANKL was increased by IL-1Β. Anakinra increased the expression of OPG. The ratio RANKL/OPG reduced in the anakinra group. *: <span class="html-italic">p</span> &lt; 0.05, **: <span class="html-italic">p</span> &lt; 0.01, ***: <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>IL-1β or anakinra does not affect alkaline phosphatase activity. ALP/DNA in nMol/ngDNA: alkaline phosphatase enzyme activity per cell at day 0 (C) and 14 (C—normal medium without anakinra, last 4 columns, 0, IL-1β, IL-1β+Ana and Ana display the result where mineralization medium was added. Results from 7 PDLF donors are shown.</p>
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17 pages, 2683 KiB  
Article
Soil Moisture Is the Key Factor Facilitating Giant Ragweed Invasions in Grasslands of the Yili Vally, China
by Xinyi Chen, Zhanli Song, Baoxiong Chen, Wanli Yu and Hegan Dong
Biology 2025, 14(3), 249; https://doi.org/10.3390/biology14030249 - 28 Feb 2025
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Abstract
Giant ragweed (GR; Ambrosia trifida L.), an invasive alien species, causes significant harm to grassland ecosystems and farmlands in some areas but is challenging to control. GR has invaded the hilly grasslands of Yili Valley, China, since 2013, and preliminary observations have shown [...] Read more.
Giant ragweed (GR; Ambrosia trifida L.), an invasive alien species, causes significant harm to grassland ecosystems and farmlands in some areas but is challenging to control. GR has invaded the hilly grasslands of Yili Valley, China, since 2013, and preliminary observations have shown that GR populations on the lower slopes of hills are more successful than those on the middle or upper slopes. To clarify the factors determining GR’s invasion success, we compared GR population distributions among slope positions and the relationship between non-biotic factors and the invasion of GR. Of the soil physicochemical properties, only soil moisture differed significantly among slope positions, with the wettest soils found on the lower slopes. GR biomass increased with the soil water content, irrespective of native plant diversity. In our experiment, when the annual average soil volume moisture content exceeded 20.3% and 25.3%, GR could reduce the biomass of native herbs by more than 50% and 80%. Therefore, water is the determining factor of a successful GR invasion in the grasslands of the Yili Valley. On a global scale, it was discovered for the first time that GR can invade temperate grasslands, but also has risks of invading other grasslands that share similar conditions. So, GR invasions of temperate grasslands must be closely monitored, particularly in low-lying areas or those with increasing precipitation. Full article
(This article belongs to the Special Issue Biology, Ecology and Management of Invasive Alien Plants)
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Figure 1

Figure 1
<p>Population growth of giant ragweed (<span class="html-italic">Ambrosia trifida</span> L.) at the seedling period, growing period, and mature period. (<b>A</b>–<b>E</b>) are taken in the same place as the grassland of Yili Vally, respectively, showing the population growth of giant ragweed during these periods. (<b>A</b>–<b>D</b>) Population growth can be seen at the bottom of the slope, with the green part showing the giant ragweed population. The dark gray in the red box of the bottom slope in (<b>E</b>) is the giant ragweed population, and there is no obvious giant ragweed population in the middle and top slope. The above photos were taken in 2019.</p>
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<p>Location of the Yili Valley and sample plot within the Xinjiang Autonomous Region.</p>
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<p>The population density, plant height, and population coverage of giant ragweed (<span class="html-italic">Ambrosia trifida</span> L.) and native herbs during the seedling period, the growing period, and at maturity at different positions on slopes in Yili Valley, China. Different capital letters indicate significant differences among slope positions (<span class="html-italic">p</span> &lt; 0.05, least significant difference test). Different lowercase letters indicate significant differences between giant ragweed and native herbs (<span class="html-italic">p</span> &lt; 0.05, least significant difference test). (<b>A</b>,<b>D</b>,<b>G</b>) A comparative analysis of the density, plant height, and coverage of native species at different slope positions as well as giant ragweed during the seedling stage. (<b>B</b>,<b>E</b>,<b>H</b>) A comparative analysis of the density, plant height, and coverage of native species at different slope positions as well as giant ragweed during the seedling stage. (<b>C</b>,<b>F</b>,<b>I</b>) A comparative analysis of the density, plant height, and coverage of native species at different slope positions as well as giant ragweed during the seedling stage.</p>
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<p>Soil temperature and moisture during the seedling period, growing period, mature period, and winter season at different positions on slopes in the Yili Valley, China. Different letters indicate significant differences among the slope positions (<span class="html-italic">p</span> &lt; 0.05, least significant difference test). (<b>A</b>) Soil temperature at different slope positions in different growth stages of GR. (<b>B</b>) Soil humidity at different slope positions in different growth stages of GR. (<b>C</b>) The relative frequency of GR in relation to soil temperature variations at different slope positions. (<b>D</b>) The relative frequency of GR in relation to soil humidity variations at different slope positions. The role of red frame is to show that GR occurs more frequently when the water content is greater than 35%.</p>
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<p>(<b>A</b>) PCA of biomass and habitat soil factors of <span class="html-italic">Ambrosia trifida</span> L. (<b>B</b>) A heat map. AN, available nitrogen (g/kg); AK, available potassium (g/kg); AP, available phosphorus (g/kg); TN, total nitrogen(g/kg); TK, total potassium (g/kg); TP, total phosphorus (g/kg); pH, acidity; EC, electrical conductivity (us/cm); SOM, soil organic matter; SQ, seed quantity per m<sup>2</sup>; Bio, biomass per m<sup>2</sup>; T, the top of the mountain; M, the middle of the mountain; B, the bottom of the mountain. “*”, <span class="html-italic">p</span> &lt; 0.05; “***”, <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Native herb density, coverage, height, and biomass per unit area at different positions on the slopes in Yili Valley, China, for sites with and without giant ragweed (<span class="html-italic">Ambrosia trifida</span> L.). Different letters indicate significant differences between native herb populations growing with and without giant ragweed (<span class="html-italic">Ambrosia trifida</span> L.; <span class="html-italic">p</span> &lt; 0.05, least significant difference test). (<b>A</b>) Comparison of native herb density between plots with and without GR invasion. (<b>B</b>) Comparison of native herb height between plots with and without GR invasion. (<b>C</b>) Comparison of native herb coverage between plots with and without GR invasion.</p>
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<p>The linear relationship between annual average soil moisture content and reduction in native plant biomass yield per unit area in areas of Yili Valley, China, colonized by giant ragweed (<span class="html-italic">Ambrosia trifida</span> L.). The green dotted line represents the annual average soil moisture content corresponding to a 20% reduction in native herb biomass (similar to soil moisture levels at the top slope of plots 1–6), the blue dotted line represents the annual average soil moisture content corresponding to a 50% reduction in native herb biomass (similar to the soil moisture levels at the middle slope of plots 1–6), and the red dotted line represents the annual average soil moisture content corresponding to an 80% reduction in native herb biomass (similar to the soil moisture level at the bottom slope of plots 1–6).</p>
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