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11 pages, 1067 KiB  
Article
Seroprevalence and Risk Factors of Crimean–Congo Hemorrhagic Fever Exposure in Wild and Domestic Animals in Benin
by Roland Eric Yessinou, Souaïbou Farougou, James Olukayode Olopade, Daniel Oladimeji Oluwayelu, Anise Happi, Christian Happi and Martin Groschup
Viruses 2025, 17(3), 387; https://doi.org/10.3390/v17030387 (registering DOI) - 8 Mar 2025
Viewed by 84
Abstract
Crimean–Congo hemorrhagic fever (CCHF) is a tick-borne zoonotic viral disease prevalent in Africa. While infection is asymptomatic in animals, it can cause severe illness with hemorrhagic manifestations and high mortality rates in humans. This study aimed to determine the seroprevalence and potential risk [...] Read more.
Crimean–Congo hemorrhagic fever (CCHF) is a tick-borne zoonotic viral disease prevalent in Africa. While infection is asymptomatic in animals, it can cause severe illness with hemorrhagic manifestations and high mortality rates in humans. This study aimed to determine the seroprevalence and potential risk factors of CCHF in wild (rodents, birds) and domestic (cattle, horses) animals in Benin. A cross-sectional study was carried out from 2022 to 2024 with the assistance of cattle breeders, hunters, farmers and bushmeat sellers in 15 districts found in three agroecological zones in the country. A total of 366 serum samples were analyzed, comprising 254 collected from wild animals and 112 from domestic animals. Among the wild animals tested, 1.18% (95% CI: 0.31–3.70; n = 3) were seropositive for antibodies against CCHF virus (CCHFV). The seroprevalence rates were 3.7% (95% CI: 0.19–20.89) in squirrels, 5.88% (95% CI: 0.31–30.76) in hares and 1.19% (95% CI: 0.06–7.38) in giant rats. In domestic animals, anti-CCHFV antibodies were detected in 38 of the 112 samples, resulting in an overall seroprevalence of 33.93% (95% CI: 25.42–43.56). Specifically, antibodies were identified in 34 out of 81 cattle (41.98%, 95% CI: 31.26–53.46) and 4 out of 24 horses (16.67%, 95% CI: 5.48–38.19). No positive samples were reported in pigeons. This study provides the first seroprevalence data on CCHF in wild and domestic animals in Benin. It highlights the risk and epidemiological dynamics of the disease and underscores the need for further investigations into tick vectors and human populations. Full article
(This article belongs to the Special Issue Viral Hemorrhagic Disease)
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<p>A map of the study sites in districts in south and north Benin. C, H and W indicates % seroprevalence of CCHFV in the study sites. The seroprevalence is 0% where no data is shown.</p>
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44 pages, 2319 KiB  
Review
Recent Progress in Developing Extracellular Vesicles as Nanovehicles to Deliver Carbohydrate-Based Therapeutics and Vaccines
by Japigorn Puagsopa, Niksa Tongviseskul, Thapakorn Jaroentomeechai and Bunyarit Meksiriporn
Vaccines 2025, 13(3), 285; https://doi.org/10.3390/vaccines13030285 - 7 Mar 2025
Viewed by 292
Abstract
Cell-derived, nanoscale extracellular vesicles (EVs) have emerged as promising tools in diagnostic, therapeutic, and vaccine applications. Their unique properties including the capability to encapsulate diverse molecular cargo as well as the versatility in surface functionalization make them ideal candidates for safe and effective [...] Read more.
Cell-derived, nanoscale extracellular vesicles (EVs) have emerged as promising tools in diagnostic, therapeutic, and vaccine applications. Their unique properties including the capability to encapsulate diverse molecular cargo as well as the versatility in surface functionalization make them ideal candidates for safe and effective vehicles to deliver a range of biomolecules including gene editing cassettes, therapeutic proteins, glycans, and glycoconjugate vaccines. In this review, we discuss recent advances in the development of EVs derived from mammalian and bacterial cells for use in a delivery of carbohydrate-based protein therapeutics and vaccines. We highlight key innovations in EVs’ molecular design, characterization, and deployment for treating diseases including Alzheimer’s disease, infectious diseases, and cancers. We discuss challenges for their clinical translation and provide perspectives for future development of EVs within biopharmaceutical research and the clinical translation landscape. Full article
(This article belongs to the Special Issue Advances in Glycoconjugate Vaccines and Nanovaccines)
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<p>Mammalian extracellular vesicles. (<b>A</b>) Three distinct biogenesis pathways are responsible for releasing EVs from cells. These EVs differ in size, as indicated, and encapsulated cargoes depending on the biogenesis pathway. Exosomes are secreted as part of the endosomal pathway via MVBs. Exocytosis releases exosomes into the extracellular space when the MVB fuses with the plasma membrane. Microvesicles/ectosomes are released directly via outward budding of the plasma membrane. Apoptotic bodies are formed during programmed cell death. Their biogenesis involves membrane blebbing, formation of apoptopodia, and frequently includes fragmented nuclear material. (<b>B</b>) Representative of surface proteins used as markers to identify EVs and their origins. (<b>C</b>) Examples of criteria used to categorize EVs from mammalian cells. Figure was created with BioRender.</p>
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<p>Bacterial EVs biogenesis. (<b>A</b>) In Gram-negative bacteria, non-lytic release due to imbalanced cell wall biosynthesis or intercalation from outside hydrophobic molecules leads to a formation of the outer membrane vesicles (OMVs). Lytic processes typically induced by bacteriophage infection generate outer–inner membrane vesicles (OIMVs) and explosive outer membrane vesicles (EOMVs). (<b>B</b>) In Gram-positive bacteria, CMV formation is triggered by the disruption of the cell wall peptidoglycan, which can result from autolysin or endolysin activity, antibiotic treatment, or phage infection, the latter being induced by phage-derived endolysin. Figure was created with BioRender.</p>
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<p>Biomedical application of EVs. (<b>A</b>) Human and bacterial cells can be used to source EVs. (<b>B</b>) EVs contains myriads of biomolecules derived from parental cells. These natural cargoes include surface-displayed N-, O-, glycosaminoglycans, glycolipids, and glycoconjugates as well as encapsulated genetic materials (DNA, mRNA, miRNA, etc.), cytosolic proteins, and metabolites. Engineering strategies including genetic, metabolic, and in vitro modifications can be deployed to load EVs with synthetic cargoes such as mAb/scFv for targeting or cancer-associated O-glycomucins domains for eliciting cancer-specific immune responses. (<b>C</b>) EVs have been proposed for use in disease treatment with illustrative examples include (i) reduction in neuritic plaques implicated for pathogenesis of Alzheimer’s disease; (ii) providing cardioprotection and/or tissue and vascular repair; and (iii) delivery of cytotoxic drugs, immune blockages, or immune adjuvants to suppress and eradicate tumors. Figure was created with BioRender.</p>
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<p>Engineering strategy for production of <span class="html-italic">E. coli</span>-derived OMV-based vaccine. (<b>A</b>) Recombinant expression of bacterial O-polysaccharide (O-PS) biosynthesis gene cluster in glycoengineered <span class="html-italic">E. coli</span> cells allows for cell-surface display of O-PS epitopes. OMVs derived from glycoengineered <span class="html-italic">E. coli</span> (GlycOMVs) retain O-PS on their surface. (<b>B</b>) <span class="html-italic">E. coli</span> cells are engineered to express and display synthetic antigen binding protein (SNAP) module on their OMVs. SNAP contains biotin binding module and thus allows for capturing of any biotinylated biomolecules, for example, biotinylated O-PS. The SNAP OMVs is a modular platform for assembling of antigen-displayed OMVs for application as vaccines. Figure was created with BioRender.</p>
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16 pages, 1186 KiB  
Article
Association Between Disease Activity of Systemic Lupus Erythematosus and Resting Electrocardiogram Abnormalities
by Lin Wu, Changlin Zhao, Jingjing Chen, Li Xu, Xianguan Yu, Xinghua Guo, Zhiming Lin, Xiaoying Xie, Bin Zhou and Yong Liu
J. Clin. Med. 2025, 14(6), 1799; https://doi.org/10.3390/jcm14061799 - 7 Mar 2025
Viewed by 41
Abstract
Objective: The association between the activity of SLE and abnormalities of ECG remains not well elucidated. We aimed to examine the relationship between the SLE Disease Activity Index 2000 (SLEDAI-2K) and abnormalities of ECG in a Chinese population. Methods: Data for this cross-sectional [...] Read more.
Objective: The association between the activity of SLE and abnormalities of ECG remains not well elucidated. We aimed to examine the relationship between the SLE Disease Activity Index 2000 (SLEDAI-2K) and abnormalities of ECG in a Chinese population. Methods: Data for this cross-sectional study were retrieved from an SLE database (2018–2023). According to the SLEDAI-2K, patients were categorized into inactive, mild activity, moderate activity, and severe activity groups. Weighted multivariable regression analyses and subgroup analyses were conducted to assess the independent relationship between the SLEDAI-2K and ECG abnormalities. Restricted cubic splines (RCSs) were employed to explore potential non-linear correlations. Results: A total of 317 SLE patients (282 women; mean age 30.0 [23.0; 43.0]) were included. The overall prevalence of ST segment changes and T wave abnormalities was 37.5%. Our findings indicated a linear relationship between the SLEDAI-2K and the risk of ST-T changes. We used interaction terms to assess heterogeneity among subgroups and discovered significant differences specifically related to female gender, age (≤25 years), combined autoimmune diseases, and infectious complications. This suggested that the positive association between the SLEDAI-2K and ST-T changes was influenced by participants’ gender, age, presence of combined autoimmune diseases, and infectious complications. Conclusions: Higher SLEDAI-2K scores were associated with an increased incidence of ST-T changes in SLE patients. The SLEDAI-2K is anticipated to emerge as an effective index for identifying early heart involvement in this population. Full article
(This article belongs to the Section Cardiology)
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<p>Flowchart of the sample selection from the SLE dataset.</p>
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<p>The restricted cubic spline (RCS) analyses of the SLEDAI-2K and the different types of ECG abnormalities. (<b>A</b>) The restricted cubic spline (RCS) analysis of the SLEDAI-2K and the risk of ST-T changes. (<b>B</b>) The restricted cubic spline (RCS) analysis of the SLEDAI-2K and the risk of atrial arrhythmia and ventricular arrhythmia. (<b>C</b>) The restricted cubic spline (RCS) analysis of the SLEDAI-2K and the risk of sinus arrhythmia. (<b>D</b>) The restricted cubic spline (RCS) analysis of the SLEDAI-2K and the risk of atrioventricular block. (<b>E</b>) The restricted cubic spline (RCS) analysis of the SLEDAI-2K and the risk of other types of ECG abnormalities.</p>
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<p>Subgroup analyses of the association between the SLEDAI-2K and the risk of ST-T changes, atrial arrhythmia and ventricular arrhythmia, sinus arrhythmia, atrioventricular block, and other types of ECG abnormalities. (<b>A</b>) Subgroup analysis of the association between the SLEDAI-2K and the risk of ST-T changes. (<b>B</b>) Subgroup analysis of the association between the SLEDAI-2K and the risk of atrial arrhythmia and ventricular arrhythmia. (<b>C</b>) Subgroup analysis of the association between the SLEDAI-2K and the risk of sinus arrhythmia. (<b>D</b>) Subgroup analysis of the association between the SLEDAI-2K and the risk of atrioventricular block. (<b>E</b>) Subgroup analysis of the association between the SLEDAI-2K and other types of ECG abnormalities.</p>
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12 pages, 1376 KiB  
Article
Hybrid Capture-Based Sequencing Enables Highly Sensitive Zoonotic Virus Detection Within the One Health Framework
by Weiya Mao, Jin Wang, Ting Li, Jiani Wu, Jiangrong Wang, Shubo Wen, Jicheng Huang, Yongxia Shi, Kui Zheng, Yali Zhai, Xiaokang Li, Yan Long, Jiahai Lu and Cheng Guo
Pathogens 2025, 14(3), 264; https://doi.org/10.3390/pathogens14030264 - 7 Mar 2025
Viewed by 154
Abstract
Hybrid capture-based target enrichment prior to sequencing has been shown to significantly improve the sensitivity of detection for genetic regions of interest. In the context of One Health relevant pathogen detection, we present a hybrid capture-based sequencing method that employs an optimized probe [...] Read more.
Hybrid capture-based target enrichment prior to sequencing has been shown to significantly improve the sensitivity of detection for genetic regions of interest. In the context of One Health relevant pathogen detection, we present a hybrid capture-based sequencing method that employs an optimized probe set consisting of 149,990 probes, targeting 663 viruses associated with humans and animals. The detection performance was initially assessed using viral reference materials in a background of human nucleic acids. Compared to standard metagenomic next-generation sequencing (mNGS), our method achieved substantial read enrichment, with increases ranging from 143- to 1126-fold, and enhanced detection sensitivity by lowering the limit of detection (LoD) from 103–104 copies to as few as 10 copies based on whole genomes. This method was further validated using infectious samples from both animals and humans, including bovine rectal swabs and throat swabs from SARS-CoV-2 patients across various concentration gradients. In both sample types, our hybrid capture-based sequencing method exhibited heightened sensitivity, increased viral genome coverage, and more comprehensive viral identification and characterization. Our method bridges a critical divide between diagnostic detection and genomic surveillance. These findings illustrate that our hybrid capture-based sequencing method can effectively enhance sensitivity to as few as 10 viral copies and genome coverage to >99% in medium-to-high viral loads. This dual capability is particularly impactful for emerging pathogens like SARS-CoV-2, where early detection and genomic characterization are equally vital, thereby addressing the limitations of metagenomics in the surveillance of emerging infectious diseases in complex samples. Full article
(This article belongs to the Special Issue Current Advances in Pathogen Diagnosis and Discovery Methods)
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<p>Taxonomic composition of the viral probe library.</p>
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<p>The comparison of aligned reads and genome coverage between conventional metagenomics and viral capture for different viral standards.</p>
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<p>Comparison of mNGS and capture sequencing for detecting unknown viruses in animal samples: (<b>a</b>) comparison of viral distribution at the family level; (<b>b</b>) comparison of suspected viral species at the species level; (<b>c</b>) frequency distribution of the top 25 contigs ranked by RPKM values; (<b>d</b>) genomic coverage distribution of suspected viral sequences, with color gradients indicating genomic coverage (yellow: 60–70%; blue: 70–90%; red: 90–100%).</p>
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9 pages, 1293 KiB  
Article
18-Fluorine-Fluorodeoxyglucose Positron Emission Computer Tomography Imaging in Melioidosis: Valuable but Not Essential
by Joshua Bramwell, Natalia Kovaleva, Joshua J. Morigi and Bart J. Currie
Trop. Med. Infect. Dis. 2025, 10(3), 69; https://doi.org/10.3390/tropicalmed10030069 - 6 Mar 2025
Viewed by 146
Abstract
Melioidosis is an endemic tropical disease caused by Burkholderia pseudomallei. It typically causes pulmonary disease and bacteraemia but can disseminate to cause multi-organ disease. 18-F FDG PET/CT has an evolving role in diagnosing other infectious diseases, especially where the pathogen or extent [...] Read more.
Melioidosis is an endemic tropical disease caused by Burkholderia pseudomallei. It typically causes pulmonary disease and bacteraemia but can disseminate to cause multi-organ disease. 18-F FDG PET/CT has an evolving role in diagnosing other infectious diseases, especially where the pathogen or extent of infection is challenging to elucidate clinically and with conventional imaging (CT, US and MRI). We present a case series of patients diagnosed with melioidosis who also underwent 18-F FDG PET/CT from December 18th 2018 to September 30th 2022. Indications for imaging were categorised and analysed as to whether 18-F FDG PET/CT changed management over conventional imaging. Twenty-one 18-F FDG PET/CT scans were performed for sixteen patients. Two scans (9.5%) performed for pyrexia of unknown origin changed management in both cases. Twelve scans (57.1%) performed to ascertain the extent of dissemination of melioidosis changed management in only three (25%) cases. Five scans (23.8%) performed to monitor the response to treatment of known foci changed management in all five cases. Five scans (23.8%) performed for suspected or known malignancy changed management in three (60%) cases. 18-F FDG PET/CT is an emerging tool which improves diagnosis and changes the management of melioidosis when applied judiciously and for well-selected indications. Full article
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<p>An illustrative case (case 8) of a patient who presented with pyrexia of unknown origin despite undergoing blood cultures and CT. (<b>a</b>) 18-F FDG PET/CT identifying an FDG avid lymph node (arrow), which was biopsied and cultured <span class="html-italic">B. pseudomallei</span>. (<b>b</b>) The result of 18-F FDG PET/CT performed after completing 4 weeks of intensive phase therapy as the patient remained febrile. This showed increased FDG avidity of splenic foci (arrow), extending the IV intensive therapy phase to 12 weeks. (<b>c</b>) The result of 18-F FDG PET/CT performed due to persistent symptoms at 30 weeks of treatment, showing complete resolution of foci, giving clinicians and the patient confidence to cease antibiotics.</p>
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15 pages, 1447 KiB  
Article
The Waxing and Waning of Fear Influence the Control of Vector-Borne Diseases
by Jing Jiao
Mathematics 2025, 13(5), 879; https://doi.org/10.3390/math13050879 - 6 Mar 2025
Viewed by 184
Abstract
One major challenge in preventing infectious diseases comes from human control behaviors. In the context of vector-borne diseases (VBDs), I explored how the waxing and waning of a human psychological emotion—fear—can generate diverse control actions, which, in turn, influence disease dynamics. Fear may [...] Read more.
One major challenge in preventing infectious diseases comes from human control behaviors. In the context of vector-borne diseases (VBDs), I explored how the waxing and waning of a human psychological emotion—fear—can generate diverse control actions, which, in turn, influence disease dynamics. Fear may diminish over time after being triggered but can also be reinforced when new triggers emerge. By integrating fear dynamics into a generic Ross–MacDonald model tailored for the Zika virus, I found that an increase in initial fear can enhance control efforts, thereby reducing the number of infected individuals and deaths. Once initial fear becomes strong enough to deplete the mosquito population, any further increase in fear no longer impacts disease dynamics. When initial fear is at an intermediate level, the increase in disease caused by greater decay in fear can be counterbalanced by increasing the frequency of fear triggers. Interestingly, when the control period is short and initial fear is at an intermediate level, increasing the frequency of fear reinforcement can lead to a “hydra effect”, which increases disease transmission. These findings help explain variations in human control efforts and provide insights for developing more effective disease control strategies that account for the fear dynamics of local communities. This work also contributes to advancing the theory at the intersection of human behavior, disease ecology, and epidemiology. Full article
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<p>The dynamics of control effort (<b>A</b>), susceptible (<b>B</b>), infected (<b>C</b>), death (<b>D</b>), total population in humans (<b>E</b>), and total mosquitoes (<b>F</b>) under the three levels of initial fear: <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math> (red dashed line), <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> (purple line), and <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>=</mo> <mn>1.5</mn> </mrow> </semantics></math> (blue line) in the absence of fear decay (<math display="inline"><semantics> <mrow> <mi>τ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>). The control lasts for 30 days (CD = 30). All other parameters are listed in <a href="#mathematics-13-00879-t002" class="html-table">Table 2</a>.</p>
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<p>The dynamics of control effort (<b>A</b>), susceptible (<b>B</b>), infected (<b>C</b>), death (<b>D</b>), total population in humans (<b>E</b>), and total mosquitoes (<b>F</b>) with and without fear decay: <math display="inline"><semantics> <mrow> <mi>τ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math> (purple line; no fear decay), 0.1 (blue line; with fear decay at rate 0.1) when initial fear is at intermediate level (<math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>) and control duration time is 30 days (CD = 30). The red dashed line shows the scenario without control (<math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>). All other parameters are listed in <a href="#mathematics-13-00879-t002" class="html-table">Table 2</a>.</p>
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<p>The relationships between initial fear (<math display="inline"><semantics> <mi>θ</mi> </semantics></math>) and total infected human (<b>A</b>), maximum infected human (<b>B</b>), total deaths (<b>C</b>), and control efficacy (<b>D</b>) under the three levels of fear decay (<math display="inline"><semantics> <mi>τ</mi> </semantics></math> = 0, 0.25, 0.5, plotted in red, purple and blue, respectively). The time window is one year and control lasts for 30 days (CD = 30). All y-axis values are log-transferred. Other parameters are listed in <a href="#mathematics-13-00879-t002" class="html-table">Table 2</a>.</p>
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<p>The dynamics of the control effort (<b>A</b>,<b>D</b>,<b>G</b>), infected human (<b>B</b>,<b>E</b>,<b>H</b>) and death cases (<b>C</b>,<b>F</b>,<b>I</b>) under the three levels of initial fear, <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math> (<b>A</b>–<b>C</b>), 1 (<b>D</b>–<b>F</b>) and 1.5 (<b>G</b>–<b>I</b>), and the three levels of control frequency (yearly in red, bimonthly in purple, and daily in blue, corresponding to three levels of fear waxing and waning periods). The control lasts for 30 days after each fear waxing (CD = 30) without decay (<math display="inline"><semantics> <mrow> <mi>τ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>). All y-axis values are log-transferred. Other parameters are listed in <a href="#mathematics-13-00879-t002" class="html-table">Table 2</a>.</p>
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<p>The dynamics of control effort (<b>A</b>), infected human (<b>B</b>) and death cases (<b>C</b>) when initial fear is at intermediate level: <math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>=</mo> </mrow> </semantics></math> 1 under the three levels of control frequency (yearly in red, bimonthly in purple, and daily in blue, corresponding to three levels of fear waxing and waning periods) in the absence of fear decay (<math display="inline"><semantics> <mrow> <mi>τ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>). The control lasts for 30 days after each fear waxing (CD = 30) without decay (<math display="inline"><semantics> <mrow> <mi>τ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>). All y-axis values are log-transferred. Other parameters are listed in <a href="#mathematics-13-00879-t002" class="html-table">Table 2</a>.</p>
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<p>The comparison between the dynamics of control effort (<b>A</b>,<b>C</b>) and infected humans (<b>B</b>,<b>D</b>) with and without fear decay (<math display="inline"><semantics> <mrow> <mi>τ</mi> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math> for (<b>A</b>,<b>B</b>); <math display="inline"><semantics> <mrow> <mi>τ</mi> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math> for (<b>C</b>,<b>D</b>)) when initial fear is at an intermediate level (<math display="inline"><semantics> <mrow> <mi>θ</mi> <mo>=</mo> </mrow> </semantics></math>1) under three levels of control frequency (yearly in red, bimonthly in purple, and daily in blue, corresponding to three levels of fear waxing and waning periods). The control duration is set up as 30 days after each fear waxing (CD = 30). All other parameters are listed in <a href="#mathematics-13-00879-t002" class="html-table">Table 2</a>.</p>
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20 pages, 944 KiB  
Review
Cornea Oculomics: A Clinical Blueprint for Extending Corneal Diagnostics and Artificial Intelligence in Systemic Health Insights
by Ryung Lee, Rahul Kumar, Alex Weaver, Ji Hyun Kim, Arriyan Raza, Joshua Ong, Ethan Waisberg and Rahul Pandit
Diagnostics 2025, 15(5), 643; https://doi.org/10.3390/diagnostics15050643 - 6 Mar 2025
Viewed by 210
Abstract
Oculomics is an emerging field that leverages ophthalmic imaging data to identify biomarkers of systemic disease, facilitating early diagnosis and risk stratification. Despite its growing recognition, gaps remain in the literature regarding the clinical applications of oculomics. Various systemic diseases—including metabolic disorders (e.g., [...] Read more.
Oculomics is an emerging field that leverages ophthalmic imaging data to identify biomarkers of systemic disease, facilitating early diagnosis and risk stratification. Despite its growing recognition, gaps remain in the literature regarding the clinical applications of oculomics. Various systemic diseases—including metabolic disorders (e.g., diabetes mellitus), infectious diseases (e.g., COVID-19), neurodegenerative diseases (e.g., dementia), hematologic disorders (e.g., thalassemia), autoimmune conditions (e.g., rheumatoid arthritis), and genetic syndromes (e.g., Fabry disease)—exhibit ocular manifestations detectable through in vivo confocal microscopy and anterior segment optical coherence tomography, among other imaging modalities. Increasing evidence supports the role of corneal imaging in identifying systemic disease biomarkers, a process further enhanced by artificial intelligence-driven analyses. This review synthesizes the current findings on corneal biomarkers of systemic disease, their ophthalmic imaging correlates, and the expanding role of corneal oculomics in translational medicine. Additionally, we explore future directions for integrating oculomics into clinical practice and biomedical research. Full article
(This article belongs to the Special Issue Artificial Intelligence Application in Cornea and External Diseases)
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<p>Corneal confocal microscopy showing sub-basal nerve plexus in (<b>a</b>) standard structure corneal nerve fibers and (<b>b</b>) the loss of corneal nerve fibers in type 2 diabetes. Available online: <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC4511296/" target="_blank">https://pmc.ncbi.nlm.nih.gov/articles/PMC4511296/</a> (accessed on 11 February 2025). This figure is licensed under the Creative Commons Attribution-NonCommercial License (CC BY-NC).</p>
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<p>Corneal nerve fiber morphology and measurements in healthy age-matched controls, subjects with mild cognitive impairment and dementia. Graphs comparing the corneal nerve fiber density, branch density, and length are shown for the three comparison groups (* <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> &lt; 0.0001). Available online: <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC6469344/" target="_blank">https://pmc.ncbi.nlm.nih.gov/articles/PMC6469344/</a> (accessed on 11 February 2025). This figure is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).</p>
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<p>Changes in corneal topography in systemic lupus erythematosus. Available online: <a href="https://www.mdpi.com/1422-0067/23/20/12264" target="_blank">https://www.mdpi.com/1422-0067/23/20/12264</a> (accessed on 11 February 2025). This figure is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).</p>
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13 pages, 795 KiB  
Article
Urine of Cats with Severe Fever with Thrombocytopenia Syndrome: A Potential Source of Infection Transmission
by Hirohisa Mekata, Mari Yamamoto, Yasuyuki Kaneko, Kentaro Yamada, Tamaki Okabayashi and Akatsuki Saito
Pathogens 2025, 14(3), 254; https://doi.org/10.3390/pathogens14030254 - 5 Mar 2025
Viewed by 222
Abstract
Severe fever with thrombocytopenia syndrome (SFTS), caused by infection with the SFTS virus, is an emerging fatal tick-borne zoonosis endemic to East Asia. Although SFTS is a tick-borne disease, the virus can be transmitted from animals with SFTS without a tick bite. Direct [...] Read more.
Severe fever with thrombocytopenia syndrome (SFTS), caused by infection with the SFTS virus, is an emerging fatal tick-borne zoonosis endemic to East Asia. Although SFTS is a tick-borne disease, the virus can be transmitted from animals with SFTS without a tick bite. Direct transmission of the SFTS virus from animals to humans has been reported; however, the transmission route is unclear in some cases. Therefore, this study focused on the possibility of SFTS virus transmission through urine and attempted to isolate the infectious virus from the urine of animals with SFTS. Since more efficient cell isolation is needed to determine whether the SFTS virus is present, we first expressed dendritic cell-specific ICAM-3-grabbing nonintegrin (DC-SIGN), the major receptor for the virus, in Vero cells (Vero-DC-SIGN cells) using a retroviral vector. When inoculated with equal amounts of the SFTS virus strain and SFTS-virus-infected animal serum, Vero-DC-SIGN cells had 42–136% and 20–85% more foci, respectively, than their parent Vero cells. After confirming that Vero-DC-SIGN cells were more suitable for the isolation of the SFTS virus, we investigated whether it could be isolated from the urine of eight cats and two dogs with SFTS. The virus was isolated from 25 μL of urine from two cats with SFTS. Considering that cats excrete 50–100 mL of urine per day, the transmission of the SFTS virus via the urine of cats with SFTS cannot be ruled out. Individuals examining or caring for cats suspected of having SFTS should be aware of the possibility of viral transmission via urine. Full article
(This article belongs to the Topic Zoonotic Vector-Borne Diseases of Companion Animals)
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<p>Stable expression of human DC-SIGN in Vero-DC-SIGN cells. Expression of dendritic cell-specific ICAM-3-grabbing nonintegrin (DC-SIGN) in Vero cells transfected with the human DC-SIGN genome (Vero-DC-SIGN cells) is confirmed using Western blotting. Parental Vero cells are used as negative controls. Mouse anti-DC-SIGN monoclonal antibody and mouse anti-β-actin monoclonal antibody are used as primary antibodies. A band at 44 kDa is detected for human DC-SIGN and 42 kDa for β-actin.</p>
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<p>Comparison of SFTS virus infection efficiency between Vero-DC-SIGN and Vero cells. (<b>a</b>) Vero-DC-SIGN and Vero cells are infected with the same viral titers of the SFTS virus strains A17 and SG403, and the number of foci is compared between these cells; (<b>b</b>) Vero (upper panel) and Vero-DC-SIGN (lower panel) cells 4 days after inoculation with SFTS virus strain SG403 are examined under a fluorescence microscope; (<b>c</b>) equal amounts of serum from a cat with SFTS (231127-4-CAT-SE) and a dog with SFTS (230413-3-DOG-SE) are inoculated into Vero-DC-SIGN and Vero cells. Four days after the inoculation, the number of foci in these cells is compared. Bars indicate mean values and error bars indicate the standard error of mean. * indicates <span class="html-italic">p</span>-value ≤ 0.05; ** indicates <span class="html-italic">p</span>-value ≤ 0.01.</p>
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<p>Details of 33 urine samples from which SFTS virus isolation was attempted. Days of sample collection and levels of SFTS viral RNA (Cq values) in the urine and serum of eight cats and two dogs with SFTS are depicted. The top row (syringe mark) and bottom row (spitz tube mark) indicate the Cq values of SFTS viral RNA in serum and urine, respectively. SFTS virus isolation is attempted from 33 urine samples with Cq values of 35 or less, and the infectious SFTS virus is isolated from two samples with squared Cq values (230214-1-CAT Day 2 and 240112-1-CAT Day 10). ND indicates samples for which qRT-PCR results are negative. Crosses indicate the death of the sampled animals. All animals not marked with a cross recovered from SFTS. The numbers in the boxes indicate the number of days since the onset of SFTS.</p>
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27 pages, 8826 KiB  
Article
Evaluation of Urban Infrastructure Resilience Based on Risk–Resilience Coupling: A Case Study of Zhengzhou City
by Wenli Dong, Yunhan Zhou, Dongliang Guo, Zhehui Chen and Jiwu Wang
Land 2025, 14(3), 530; https://doi.org/10.3390/land14030530 - 3 Mar 2025
Viewed by 206
Abstract
The frequent occurrence of disasters has brought significant challenges to increasingly complex urban systems. Resilient city planning and construction has emerged as a new paradigm for dealing with the growing risks. Infrastructure systems like transportation, lifelines, flood control, and drainage are essential to [...] Read more.
The frequent occurrence of disasters has brought significant challenges to increasingly complex urban systems. Resilient city planning and construction has emerged as a new paradigm for dealing with the growing risks. Infrastructure systems like transportation, lifelines, flood control, and drainage are essential to the operation of a city during disasters. It is necessary to measure how risks affect these systems’ resilience at different spatial scales. This paper develops an infrastructure risk and resilience evaluation index system in city and urban areas based on resilience characteristics. Then, a comprehensive infrastructure resilience evaluation is established based on the risk–resilience coupling mechanism. The overall characteristics of comprehensive infrastructure resilience are then identified. The resilience transmission level and the causes of resilience effects are analyzed based on the principle of resilience scale. Additionally, infrastructure resilience enhancement strategies under different risk scenarios are proposed. In the empirical study of Zhengzhou City, comprehensive infrastructure resilience shows significant clustering in the city area. It is high in the central city and low in the periphery. Specifically, it is relatively high in the southern and northwestern parts of the airport economy zone (AEZ) and low in the center. The leading driving factors in urban areas are risk factors like flood and drought, hazardous materials, infectious diseases, and epidemics, while resilience factors include transportation networks, sponge city construction, municipal pipe networks, and fire protection. This study proposes a “risk-resilience” coupling framework to evaluate and analyze multi-hazard risks and the multi-system resilience of urban infrastructure across multi-level spatial scales. It provides an empirical resilience evaluation framework and enhancement strategies, complementing existing individual dimensional risk or resilience studies. The findings could offer visualized spatial results to support the decision-making in Zhengzhou’s resilient city planning outline and infrastructure special planning and provide references for resilience assessment and planning in similar cities. Full article
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<p>Research design.</p>
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<p>(<b>a</b>) Result matrix of risk–resilience coupling. (<b>b</b>) Corresponding color legends on the map [<a href="#B2-land-14-00530" class="html-bibr">2</a>].</p>
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<p>Initial indicator system for infrastructure risk evaluation in Zhengzhou City.</p>
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<p>Initial indicator system for infrastructure resilience evaluation in Zhengzhou City.</p>
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<p>Evaluation results of infrastructure resilience, risk, and comprehensive resilience in the Zhengzhou city area.</p>
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<p>Evaluation results of resilience, risk, and comprehensive resilience of infrastructure subsystems in the Zhengzhou city area (transportation, flood control and drainage, and lifelines).</p>
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<p>Evaluation results of infrastructure resilience, risk, and comprehensive resilience in the Zhengzhou urban area.</p>
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<p>Evaluation results of resilience, risk, and comprehensive resilience of infrastructure subsystems in the Zhengzhou urban area (transportation, flood control and drainage, and lifelines).</p>
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<p>Spatial autocorrelation analysis of comprehensive infrastructure resilience in the Zhengzhou urban area ((<b>a</b>) Getis-Ord G*, (<b>b</b>) Anselin Local Moran’s I).</p>
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<p>Heat map of the interaction of factors affecting comprehensive infrastructure resilience in the Zhengzhou urban area.</p>
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<p>Examples of risks faced in Huiji District.</p>
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<p>Resilience enhancement strategies for each system.</p>
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<p>Resilience enhancement strategies in flooding risk scenarios.</p>
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<p>Resilience enhancement strategies in geologic disaster risk scenarios.</p>
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<p>Resilience enhancement strategies in fire accident risk scenarios.</p>
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<p>Resilience enhancement strategies in infectious diseases and epidemic risk scenarios.</p>
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24 pages, 4491 KiB  
Article
Emergency Dyspnea in 258 Cats: Insights from the French RAPID CAT Study
by Nour Abboud, Jack-Yves Deschamps, Marie Joubert and Françoise A. Roux
Vet. Sci. 2025, 12(3), 242; https://doi.org/10.3390/vetsci12030242 - 3 Mar 2025
Viewed by 260
Abstract
Dyspnea is common in feline emergency medicine. Dyspneic cats are often unable to tolerate additional diagnostic tests upon admission. The aim of this study was to determine the relative frequency of the causes of severe dyspnea in cats and to identify clinical indicators [...] Read more.
Dyspnea is common in feline emergency medicine. Dyspneic cats are often unable to tolerate additional diagnostic tests upon admission. The aim of this study was to determine the relative frequency of the causes of severe dyspnea in cats and to identify clinical indicators that could guide immediate management. Records of 312 severely dyspneic cats admitted over a 5-year period to our institution’s emergency and critical care unit were retrospectively reviewed. The cause of dyspnea was identified for 258 cats, representing 83% of the cases. This study focused solely on these 258 cats. Respiratory causes accounted for 33% of cases, followed by cardiac causes (25%) and both traumatic and neoplastic causes (21% each). Pleural effusion was present in 39% of the cats, with various origins: cardiac (38%), respiratory (pyothorax, feline infectious peritonitis, 30%), neoplastic (23%), and traumatic (9%). Male cats were significantly overrepresented in the cardiac and respiratory groups. The median age differed according to the cause (2 years for traumatic causes, 6 years for respiratory causes, and approximately 11 years for cardiac and neoplastic causes). Cats with cardiac disease were significantly more often hypothermic. Hyperthermia was not systematically indicative of an infectious process. No clinical element (temperature, heart rate, cardiac auscultation, etc.) allowed for predicting the cause of dyspnea. In-hospital mortality was 44%, varying according to the cause (78% for neoplastic causes, 40% for traumatic causes, 37% for cardiac causes, and 30% for respiratory causes). In conclusion, the four main categories of causes were represented in approximately equal proportions, which contrasts with the results of the British RAPID CAT study, where cardiac causes accounted for nearly two-thirds of dyspnea cases. In the dyspneic cats in this series, the clinical presentation did not allow clinicians to identify a particular cause. This highlights the importance of non-invasive examinations such as POCUS (point-of-care ultrasound), which has become a routine test in emergency medicine. However, this importance should not lead to underestimating the continued value of radiography when the cat’s clinical condition allows for image acquisition. Full article
(This article belongs to the Special Issue Advancements in Small Animal Internal Medicine)
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<p>Thoracentesis of a pleural effusion, here a pyothorax, in an awake cat. In this series, 39% of the 258 dyspneic cats with an etiologic diagnosis had pleural effusion. Detecting pleural effusion is a priority, as thoracentesis provides significant relief.</p>
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<p>Atrial dilation confirmed by a left atrium-to-aorta ratio of 4.3 in a dyspneic cat. A cardiac POCUS, minimally stressful for the patient, allows for the detection of atrial dilation and thus confirms the cardiac origin of dyspnea.</p>
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<p>Frontal radiographic image of a cat with suspected feline asthma. The diagnosis of feline asthma was one of exclusion. A relatively young age, reported episodic coughing or dyspnea, expiratory effort, subtle radiographic lesions compared to the severity of symptoms, suggestive radiographic findings (donut-shaped opacities, pulmonary hyperinflation, atelectasis of the right (D) middle lobe), and a favorable response to treatment all supported this diagnosis.</p>
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<p>Pulmonary edema, pleural effusion, and cardiomegaly in a dyspneic cat. The cats in this series with congestive heart failure presented with pulmonary edema in 67% of cases, pleural effusion in 62% of cases, and both lesions simultaneously in 30% of cases.</p>
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<p>Neoplasia accounted for 21% of the causes of dyspnea in this series. The median age of the affected cats was 11 years. The lesions responsible for dyspnea varied: effusion (<b>on the left</b>), diffuse parenchymal involvement (<b>in the center</b>), and pneumothorax (<b>on the right</b>).</p>
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<p>Diaphragmatic hernia with stomach displacement into the thoracic cavity. About a quarter of cats that were dyspneic due to trauma had a diaphragmatic hernia. The prognosis was good after surgery (90% survival), but 30% of owners declined the surgical procedure.</p>
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<p>Traumatic pneumothorax in two cats. The assessment of dyspneic cats with pneumothorax, for whom an accident had been observed (case in <b>the left image</b>) or broken ribs were detected (case in <b>the right image</b>), led to the conclusion of a traumatic cause. Although traumatic pneumothorax is relatively easy to manage, it was associated with a high in-hospital mortality rate in this series (42%) due to associated injuries, which sometimes resulted in requests for euthanasia.</p>
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17 pages, 2448 KiB  
Article
Genetic Diversity and Molecular Evolution of Hepatitis E Virus Within the Genus Chirohepevirus in Bats
by Bo Wang, Peter Cronin, Marcus G. Mah, Xing-Lou Yang and Yvonne C. F. Su
Viruses 2025, 17(3), 339; https://doi.org/10.3390/v17030339 - 28 Feb 2025
Viewed by 134
Abstract
Hepatitis E virus (HEV) is a major zoonotic pathogen causing hepatitis E, with strains identified in various animal species, including pigs, wild boar, rabbits, deer, camels, and rats. These variants are capable of crossing species barriers and infecting humans. HEV belongs to the [...] Read more.
Hepatitis E virus (HEV) is a major zoonotic pathogen causing hepatitis E, with strains identified in various animal species, including pigs, wild boar, rabbits, deer, camels, and rats. These variants are capable of crossing species barriers and infecting humans. HEV belongs to the family Hepeviridae, which has recently divided into two subfamilies: Orthohepevirinae and Parahepevirinae, and five genera: Paslahepevirus, Avihepevirus, Rocahepevirus, Chirohepevirus, and Piscihepevirus. Recent advances in high-throughput sequencing, particularly of bat viromes, have revealed numerous HEV-related viruses, raising concerns about their zoonotic potential. Bat-derived HEVs have been classified into the genus Chirohepevirus, which includes three distinct species. In this study, we analyzed 64 chirohepevirus sequences from 22 bat species across six bat families collected from nine countries. Twelve sequences represent complete or nearly complete viral genomes (>6410 nucleotides) containing the characteristic three HEV open reading frames (ORFs). These strains exhibited high sequence divergence (>25%) within their respective host genera or species. Phylogenetic analyses with maximum likelihood methods identified at least seven distinct subclades within Chirohepevirus, each potentially representing an independent species. Additionally, the close phylogenetic relationship between chirohepevirus strains and their bat hosts indicates a pattern of virus–host co-speciation. Our findings expand the known diversity within the family Hepeviridae and provide new insights into the evolution of bat-associated HEV. Continued surveillance of chirohepevirus will be essential for understanding its potential for zoonotic transmission and public health risks. Full article
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<p>Worldwide distribution of chirohepeviruses in bats. Countries where chirohepevirus genomic sequences have been detected are marked in red. Bat families that are positive for chirohepeviruses are highlighted in bold. The number of chirohepevirus sequences detected in each bat species is shown in brackets. The world map was created using a free and open-source quantum geographic information system (QGIS) version 3.38, with raster map data from Natural Earth.</p>
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<p>Genome organization comparisons of chirohepeviruses and related genera. The typical three HEV open reading frames (ORFs) and putative functional domains within the ORF1 of <span class="html-italic">Paslahepevirus</span> are depicted, including methyltransferase (Met), Y domain, papain-like cysteine protease (PCP), hypervariable region (HVR), X domain, helicase (Hel), and RNA-dependent RNA polymerase (RdRp). The genome scale in nucleotides is shown at the top. GenBank accession numbers for the virus strains presented: M73218 (<span class="html-italic">Paslahepevirus</span>), AY535004 (<span class="html-italic">Avihepevirus</span>), GU345042 (<span class="html-italic">Rocahepevirus</span>), KJ562187 (Rf-HEV/Shanxi2013), MT210622 (GD2019), OR951173 (LQB_Rsin), MW249011 (API17_F_DrHEV), MW249012 (AYA11_F_DrHEV), MW249013 (AYA14_F_DrHEV), MW249014 (LR3_F_DrHEV), KX513953 (BtHEVMd2350), OQ715534 (JM_My.ricketti.hev), JQ001749 (BS7/GE/2009), MT815970 (BtHEV-Ps1/CH/2019), OQ715533 (JM_Mi.magnater.hev), and HQ731075 (<span class="html-italic">Piscihepevirus</span>).</p>
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<p>Genetic diversity of chirohepeviruses and other HEV genera. (<b>A</b>) Phylogenetic tree based on complete genomes of representative members of the family <span class="html-italic">Hepeviridae</span>. Virus classification follows the ICTV Virus Taxonomy Profile: <span class="html-italic">Hepeviridae</span> 2022. Virus strains within the genus <span class="html-italic">Chirohepevirus</span> are highlighted in red. Major host tropisms for each virus genus are indicated using animal icons. The tree is rooted using the divergent cutthroat trout <span class="html-italic">Piscihepevirus</span>. Bootstrap support values are indicated at relevant nodes. The scale bar corresponds to number of nucleotide substitutions per site. (<b>B</b>) Pairwise nucleotide sequence distances between <span class="html-italic">Chirohepevirus</span> and four other HEV genera. (<b>C</b>) Comparison of nucleotide sequence distances based on partial HEV genomes (at least &gt;4400 nucleotides) identified in known bat genera or within the Order Chiroptera.</p>
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<p>Maximum likelihood phylogeny of partial ORF1 of chirohepeviruses. The tree is based on approximately 1600-nucleotide region of ORF1 and is rooted using an avian HEV strain (GenBank accession no. AY535004) from the genus <span class="html-italic">Avihepevirus</span>. Bootstrap support values are indicated at relevant nodes. The scale bar represents the number of nucleotide substitutions per site. Viruses from distinct subclades are color-coded, with designations including GenBank accession number, host species, and sampling location and year.</p>
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<p>Maximum likelihood phylogeny of nearly complete genomes of chirohepeviruses. The nearly complete genomes consist of approximately 5600 nucleotides. The tree is rooted using an avian HEV strain (GenBank accession no. AY535004) from the related genus <span class="html-italic">Avihepevirus</span>. Bootstrap support values are indicated at relevant nodes. The scale bar corresponds to number of nucleotide substitutions per site. Viruses from distinct subclades are highlighted in various colors. Virus designations include GenBank accession number, host species, sampling location, and collection year. Seven potentially designated bat <span class="html-italic">Chirohepevirus</span> species are shown on the right.</p>
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<p>Co-evolution of chirohepeviruses and bat species. (<b>A</b>) Maximum likelihood trees generated based on approximately 4400 nucleotide sequences of chirohepeviruses in various bat species (left) and nucleotide sequences of the cytochrome B (CYTB) gene of corresponding hosts (right). Host taxonomy (family) is specified on the phylogenetic tree. Lines between chirohepeviruses and their corresponding host species are color-coded according to the four bat families. The scale bar corresponds to the number of nucleotide substitutions per site. (<b>B</b>) Comparison of the numbers of bat species testing positive for chirohepevirus versus the total number of extant bat species in each family or within the Order Chiroptera. The numbers of taxonomically described chiropteran species in each family are derived from the Bat Species of the World databases.</p>
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20 pages, 1626 KiB  
Review
Adaptive Changes and Genetic Mechanisms in Organisms Under Controlled Conditions: A Review
by Yu-Wei Guo, Yang Liu, Peng-Cheng Huang, Mei Rong, Wei Wei, Yan-Hong Xu and Jian-He Wei
Int. J. Mol. Sci. 2025, 26(5), 2130; https://doi.org/10.3390/ijms26052130 - 27 Feb 2025
Viewed by 166
Abstract
Adaptive changes encompass physiological, morphological, or behavioral modifications occurring in organisms in response to specific environmental conditions. These modifications may become established within a population through natural selection. While adaptive changes can influence individuals or populations over short timeframes, evolution involves the inheritance [...] Read more.
Adaptive changes encompass physiological, morphological, or behavioral modifications occurring in organisms in response to specific environmental conditions. These modifications may become established within a population through natural selection. While adaptive changes can influence individuals or populations over short timeframes, evolution involves the inheritance and accumulation of these changes over extended periods under environmental pressures through natural selection. At present, addressing climate change, emerging infectious diseases, and food security are the main challenges faced by scientists. A comprehensive and profound understanding of the mechanisms of adaptive evolution is of great significance for solving these problems. The genetic basis of these adaptations can be examined through classical genetics, which includes stochastic gene mutations and chromosomal instability, as well as epigenetics, which involves DNA methylation and histone modifications. These mechanisms not only govern the rate and magnitude of adaptive changes but also affect the transmission of adaptive traits to subsequent generations. In the study of adaptive changes under controlled conditions, short-term controlled experiments are commonly utilized in microbial and animal research to investigate long-term evolutionary trends. However, the application of this approach in plant research remains limited. This review systematically compiles the findings on adaptive changes and their genetic foundations in organisms within controlled environments. It aims to provide valuable insights into fundamental evolutionary processes, offering novel theoretical frameworks and research methodologies for future experimental designs, particularly in the field of plant studies. Full article
(This article belongs to the Section Molecular Genetics and Genomics)
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<p>Trends in the adaptive changes in microbial traits under controlled conditions. (<b>a</b>) Multigenerational cultivation gradually increases reactive oxygen species (ROS) levels in microorganisms. (<b>b</b>) Multigenerational cultivation leads to a progressive decline in microbial colony size and biomass.</p>
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<p>Trends in plant trait adaptation under controlled conditions. (<b>a</b>) Multigenerational cultivation initially increases stamen length, followed by a subsequent decrease in plants. (<b>b</b>) Multigenerational cultivation causes an initial rise in pistil length, followed by a gradual decline in plants.</p>
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<p>Schematic representation of genetic mechanisms driving adaptive changes in organisms under controlled conditions. (<b>a</b>) Genetic mechanisms: This panel illustrates the key genetic processes involved in adaptive changes, including gene mutations, which introduce new genetic variations; chromosomal instability, which involves structural alterations of chromosomes, such as inversions or translocations; and enzyme activity differences, which influence metabolic pathways and can drive phenotypic changes. (<b>b</b>) Epigenetic mechanisms: This panel depicts various epigenetic processes that regulate gene expression without altering the underlying DNA sequence. These include DNA methylation, which typically suppresses gene expression; histone modifications, such as acetylation or methylation, which alter chromatin structure and affect gene accessibility; and non-coding RNA regulation, which involves RNA molecules that can modulate gene expression post-transcriptionally. (<b>c</b>) Multigenerational cultivation across different organisms (microorganisms, animals and plants): This panel represents the application of controlled multigenerational cultivation to study adaptive changes in different organisms. At the top are animals, represented by <span class="html-italic">Drosophila melanogaster</span> (fruit flies), known for their genetic tractability and rapid generation time; in the middle are microorganisms, represented by fungi, particularly species like <span class="html-italic">Saccharomyces cerevisiae</span>, which are commonly used in evolutionary studies due to their short life cycle and high mutation rates; at the bottom are plants, represented by <span class="html-italic">Arabidopsis thaliana</span>, a model organism in plant biology due to its well-characterized genetics and significance in plant research. The figure highlights how different organisms are used to explore the genetic and epigenetic mechanisms that drive adaptation under controlled experimental conditions.</p>
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<p>Types of adaptive traits exhibited by different organisms under controlled conditions. In animals, adaptive changes include reproductive, physiological, morphological, and behavioral traits. In microorganisms, variations occur in morphological, physiological, reproductive, and biochemical traits. In plants, adaptations involve morphological and biochemical traits.</p>
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16 pages, 2976 KiB  
Article
The Gut Microbiota of the Greater Horseshoe Bat Confers Rapidly Corresponding Immune Cells in Mice
by Shan Luo, Xinlei Huang, Siyu Chen, Junyi Li, Hui Wu, Yuhua He, Lei Zhou, Boyu Liu and Jiang Feng
Animals 2025, 15(5), 685; https://doi.org/10.3390/ani15050685 - 26 Feb 2025
Viewed by 228
Abstract
Background: Emerging infectious diseases threaten human and animal health, with most pathogens originating from wildlife. Bats are natural hosts for many infectious agents. Previous studies have demonstrated that changes in some specific genes in bats may contribute to resistance to viral infections, but [...] Read more.
Background: Emerging infectious diseases threaten human and animal health, with most pathogens originating from wildlife. Bats are natural hosts for many infectious agents. Previous studies have demonstrated that changes in some specific genes in bats may contribute to resistance to viral infections, but they have mostly overlooked the immune function of the bat gut microbiota. Aims: In this study, we used fecal transplants to transfer the gut microbiota from the Greater Horseshoe Bat (Rhinolophus ferrumequinum) into mice treated with antibiotics. The gut microbiota changes in mice were detected using 16S rRNA high-throughput sequencing technology. Flow cytometry was used to detect changes in associated immune cells in the spleen and mesenteric lymph nodes of the mice. Results: The results showed that the gut microbiota of mice showed characteristics of some bat gut microbiota. The Greater Horseshoe Bat’s gut microbiota changed some immune cells’ composition in the spleen and mesenteric lymph nodes of mice and also conferred a faster and higher proportion of natural killer cell activation. Conclusion: This result provides new evidence for the regulatory immune function of bat gut microbiota and contributes to a deeper insight into the unique immune system of bats. Full article
(This article belongs to the Section Wildlife)
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<p>Study design sketch.</p>
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<p>Changes in the distribution of gut microbiota in mice. Community bar plot analysis of phylum (<b>a</b>) and genus (<b>b</b>). (<b>c</b>) NMDS based on unweighted UniFrac distance matrices. (<b>d</b>) Relative abundance distributions of the phylum. MF: Feces from mouse donors; RF: Feces from bat donors; AbxM7: Feces on day 7 in mice receiving fecal transplants from mouse donors; AbxR7: Feces on day 7 in mice receiving fecal transplants from bat donors; AbxM14: Feces on day 14 in mice receiving fecal transplants from mouse donors; AbxR14: Feces on day 14 in mice receiving fecal transplants from bat donors.*, <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>Changes in LEfSe analysis of gut microbiota after FMT. (<b>a</b>) LEfSe bar graphs of microorganisms from the MF and RF groups. (<b>b</b>) LEfSe bar graphs of microorganisms from the AbxM7 and AbxR7 groups. (<b>c</b>) LEfSe bar graphs of microorganisms from the AbxM14 and AbxR14 groups. Box: Representative flora with LDA over 3.5 in RF and AbxR14 groups. MF: Feces from mouse donors; RF: Feces from bat donors; AbxM7: Feces on day 7 in mice receiving fecal transplants from mouse donors; AbxR7: Feces on day 7 in mice receiving fecal transplants from bat donors; AbxM14: Feces on day 14 in mice receiving fecal transplants from mouse donors; AbxR14: Feces on day 14 in mice receiving fecal transplants from bat donors.</p>
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<p>PICRUSt2 analysis of gut microbiota after FMT. (<b>a</b>) KO heatmap for PICRUSt2 analysis. (<b>b</b>) MetaCyc pathway heatmap for PICRUSt2 analysis. MF: Feces from mouse donors; RF: Feces from bat donors; AbxM7: Feces on day 7 in mice receiving fecal transplants from mouse donors; AbxR7: Feces on day 7 in mice receiving fecal transplants from bat donors; AbxM14: Feces on day 14 in mice receiving fecal transplants from mouse donors; AbxR14: Feces on day 14 in mice receiving fecal transplants from bat donors.</p>
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<p>Changes in adaptive immunity (T and B cells) and natural killer cells in the spleen. Control: PBS group; AbxM: a group receiving mouse fecal transplants; AbxR: a group receiving bat fecal transplants. (<b>a</b>–<b>h</b>) Changes in the proportion of lymphocytes in the spleen after FMT. (<b>i</b>–<b>l</b>) Changes in the proportion of NK cells in the spleen after FMT. Five mice per group, with each point representing a sample from one mouse. A significance level of <span class="html-italic">p</span> &lt; 0.05 was considered significantly different from each group. Data were tested for statistical significance using one-way ANOVA and a subsequent Tukey test. PBS: the control group without FMT and with equal amounts of PBS instilled throughout; AbxM: the group of mice receiving fecal transplants from mouse donors; AbxR: the group of mice receiving fecal transplants from bat donors.</p>
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<p>Changes in adaptive immunity (T and B cells) and natural killer cells in the MLN. (<b>a</b>–<b>h</b>) Changes in the proportion of lymphocytes in the MLN after FMT. (<b>i</b>–<b>l</b>) Changes in the proportion of NK cells in the MLN after FMT. The experimental groups were the same as the spleen (see <a href="#animals-15-00685-f003" class="html-fig">Figure 3</a>). Five mice per group, with each point representing a sample from one mouse. A significance level of <span class="html-italic">p</span> &lt; 0.05 was considered significantly different from each group. Data (<b>a</b>–<b>f</b>,<b>i</b>–<b>l</b>) were tested for statistical significance using one-way ANOVA, which was followed by Tukey’s test, and (<b>g</b>,<b>h</b>) were tested using the Kruskal–Wallis test and, subsequently, Dunn’s test. PBS: the control group without FMT and with equal amounts of PBS instilled throughout; AbxM: the group of mice receiving fecal transplants from mouse donors; AbxR: the group of mice receiving fecal transplants from bat donors.</p>
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12 pages, 1040 KiB  
Article
Prospective Audit and Feedback of Targeted Antimicrobials Use at a Tertiary Care Hospital in the United Arab Emirates
by Shabaz Mohiuddin Gulam, Dixon Thomas, Fiaz Ahamed and Danial E. Baker
Antibiotics 2025, 14(3), 237; https://doi.org/10.3390/antibiotics14030237 - 26 Feb 2025
Viewed by 264
Abstract
Background/Objectives: Antimicrobial stewardship programs improve antimicrobial use and help combat antimicrobial resistance. The Infectious Disease Society of America’s (IDSA) recommended core interventions include prospective audit and feedback along with formulary restriction and preauthorization. IDSA recommends any one of these interventions be implemented in [...] Read more.
Background/Objectives: Antimicrobial stewardship programs improve antimicrobial use and help combat antimicrobial resistance. The Infectious Disease Society of America’s (IDSA) recommended core interventions include prospective audit and feedback along with formulary restriction and preauthorization. IDSA recommends any one of these interventions be implemented in acute care hospitals to improve antimicrobial stewardship. The objective of this project was to implement a prospective audit and feedback system using selected antimicrobials at a tertiary care hospital in the United Arab Emirates as the foundation to build an antimicrobial stewardship program. Results: A total of 497 patients met the inclusion and exclusion criteria during the study period; the post-intervention group had 260 patients, and the control group had 237 patients. After the implementation of the program, a total of 186 interventions were recommended, and 76% were accepted. The length of stay, length of therapy, and days of therapy were lower in the intervention group compared to the control group (p < 0.05). There was no statistically significant difference in clinical outcome measures (e.g., 30-day readmission, 30-day all-cause mortality, 30-day emergency visit with the same infection, and 60-day readmission). Methods: This single-center quasi-experimental research was conducted from August 2023 to July 2024. A pharmacist-led prospective audit and feedback system was initiated in February 2024 after review and approval of the medical staff, in addition to formulary restrictions. Data from patients receiving the selected antimicrobial before February 2024 were collected from their charts and related medical records without any intervention; this was used by our control group. After implementation, the hospital pharmacy’s records were evaluated during the night shift to determine whether they met the inclusion criteria. The records of the eligible patients were then evaluated by the clinical pharmacist. In case of antimicrobial inappropriateness, feedback was provided to the prescriber. If the recommendation was not accepted, succeeding reviews and feedback were provided on subsequent days. The effectiveness of the intervention was measured using clinical and antibiotic use measures. Conclusions: Implementation of a pilot pharmacist-led antimicrobial stewardship program resulted in modification in antimicrobial use measures (i.e., defined daily doses of targeted antimicrobials and days of antimicrobial therapy) without an increase in length of stay or readmissions or mortality. Full article
(This article belongs to the Section Antibiotics Use and Antimicrobial Stewardship)
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<p>Average defined daily doses of targeted antibiotics.</p>
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<p>Prospective audit and feedback process adopted.</p>
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14 pages, 1444 KiB  
Article
Imported Typhoid Fever in Romania Between 2010 and 2024
by Dragos Stefan Lazar, George Sebastian Gherlan, Simin Aysel Florescu, Corneliu Petru Popescu and Maria Nica
Infect. Dis. Rep. 2025, 17(2), 16; https://doi.org/10.3390/idr17020016 - 25 Feb 2025
Viewed by 138
Abstract
Background/Objectives: Although a “forgotten” disease in developed countries, typhoid fever remains a significant global health problem, especially in regions with inadequate sanitation and overcrowding. Despite medical advances, this systemic bacterial infection, caused by Salmonella Typhi, continues to affect millions worldwide. Accurate diagnosis and [...] Read more.
Background/Objectives: Although a “forgotten” disease in developed countries, typhoid fever remains a significant global health problem, especially in regions with inadequate sanitation and overcrowding. Despite medical advances, this systemic bacterial infection, caused by Salmonella Typhi, continues to affect millions worldwide. Accurate diagnosis and timely treatment are crucial to prevent severe complications and mortality. Even though antibiotic therapy is effective, the emergence of drug-resistant strains is a growing challenge. Methods: We present a series of cases encountered in a tertiary infectious disease hospital in Romania over 15 years. Results: The hospitalised patients were mainly from Sub-Saharan Africa and the Indian subcontinent; the median time between the onset of the first symptoms and hospital admission was 15 days. The symptoms encountered along with fever were headache, chills, cough, diarrhoea and tachycardia, an unusual feature in the clinical picture of this disease. Aneosinophilia (the absence of peripheral eosinophilic granulocytes) was the most frequently encountered laboratory finding, followed by increased serum transaminases and inflammatory syndrome. Conclusions: S. Typhi was generally identified from blood culture, demonstrating, except in one case, resistance to ciprofloxacin and, in several cases, multi-drug resistance (MDR). In this series of cases, all strains were sensitive to ceftriaxone. Full article
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<p>Number of cases/year according to the two reports (European Centre for Disease Prevention and Control, Dr. Victor Babes Hospital for Infectious and Tropical Diseases).</p>
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<p>Origin and trajectory of typhoid fever cases admitted to Dr. Victor Babes Hospital for Infectious and Tropical Diseases during 2013–2024. Each color represents a different case.</p>
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<p>Comparison (in days) between the repatriation and onset hospitalisation periods.</p>
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<p>EPI curve of typhoid fever cases admitted to VBH.</p>
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