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Search Results (243)

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14 pages, 914 KiB  
Article
Quantification of Free Circulating DNA and Differential Methylation Profiling of Selected Genes as Novel Non-Invasive Biomarkers for Endometriosis Diagnosis
by Moncef Benkhalifa, Pierre Alain Menoud, David Piquemal, Jack Y. Hazout, Sami Mahjoub, Mohammed Zarquaoui, Noureddine Louanjli, Rosalie Cabry and Andre Hazout
Biomolecules 2025, 15(1), 69; https://doi.org/10.3390/biom15010069 - 6 Jan 2025
Viewed by 516
Abstract
Endometriosis is a chronic, estrogen-dependent disorder associated with the presence of endometrial cells mainly in the pelvic cavity, causing systemic immune inflammation, infertility, epigenetic dysregulation of differential DNA methylation, coelomic metaplasia, and pain. It affects approximately 10–12% of women. Despite decades of research, [...] Read more.
Endometriosis is a chronic, estrogen-dependent disorder associated with the presence of endometrial cells mainly in the pelvic cavity, causing systemic immune inflammation, infertility, epigenetic dysregulation of differential DNA methylation, coelomic metaplasia, and pain. It affects approximately 10–12% of women. Despite decades of research, full pathophysiology, a diagnostic roadmap, and clinical management strategies for endometriosis are not yet fully elucidated. Cell-free DNA (Cf-DNA) in the peripheral blood of diseased and healthy individuals was discovered in the 1950s. Quantifying peripheral Cf-DNA and the specific differential methylation of a group of genes have been proposed as potential non-invasive diagnostic biomarkers for somatic and constitutional genetics and for various other pathological disorders. In this study, we investigated the Cf-DNA levels of 78 young women, 38 of whom had endometriosis confirmed via laparoscopy and 40 of whom were healthy. We found a significant difference between the two groups when Cf-DNA was quantified, with 3.9 times more Cf-DNA in the serum of women with endometriosis. We also identified nine target genes potentially involved in the pathogenesis of endometriosis, with a different methylation profile between the two groups. Our data suggest that the combination of cell-free DNA quantification and the assessment of the epigenetic signature of differential methylation of nine genes can be proposed as a non-invasive predictive and diagnostic test for endometriosis. Full article
(This article belongs to the Special Issue Cellular and Molecular Mechanisms of Endometriosis)
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<p>A group of 151 patients was selected based on age, genital activity, pelvic pain, and quality of life. In total, 78 met the inclusion criteria and a final 38 patients were classified as patients with endometriosis while 40 were taken as a control group.</p>
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<p>The box plots represent the median, interquartile range, minimum, and maximum values of RPP30 gene expression in copy number for the cohort of 78 samples. There is a significant difference in the RPP30 copy numbers between the two groups: The statistical analysis was performed using an ANOVA test (<span class="html-italic">p</span> = 7.63 × 10<sup>−5</sup>).</p>
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<p>Average ROC curve using data from Glmnet methodology.</p>
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14 pages, 2412 KiB  
Article
Gastric Microbiota Associated with Gastric Precancerous Lesions in Helicobacter pylori-Negative Patients
by Han-Na Kim, Min-Jeong Kim, Jonathan P. Jacobs and Hyo-Joon Yang
Microorganisms 2025, 13(1), 81; https://doi.org/10.3390/microorganisms13010081 - 3 Jan 2025
Viewed by 647
Abstract
Studies on the gastric microbiota associated with gastric precancerous lesions remain limited. This study aimed to profile the gastric mucosal microbiota in patients with Helicobacter pylori-negative precancerous lesions. Gastric mucosal samples were obtained from 67 H. pylori-negative patients, including those with [...] Read more.
Studies on the gastric microbiota associated with gastric precancerous lesions remain limited. This study aimed to profile the gastric mucosal microbiota in patients with Helicobacter pylori-negative precancerous lesions. Gastric mucosal samples were obtained from 67 H. pylori-negative patients, including those with chronic gastritis (CG), intestinal metaplasia (IM), and dysplasia. The V3–V4 region of the 16S rRNA gene was sequenced and analyzed. No significant difference was observed in the alpha or beta diversity of the gastric microbiota among the groups. However, a taxonomic analysis revealed a significant enrichment of Lautropia mirabilis and the depletion of Limosilactobacillus reuteri, Solobacxterium moorei, Haemophilus haemolyticus, and Duncaniella dubosii in the IM and dysplasia groups compared to those in the CG group. Prevotella jejuni and the genus Parvimonas were enriched in the IM group. A predictive functional analysis revealed enrichment of the ornithine degradation pathway in the IM and dysplasia groups, suggesting its role in persistent gastric mucosal inflammation associated with gastric precancerous lesions. The gastric microbiota associated with H. pylori-negative gastric precancerous lesions showed an increased abundance of oral microbes linked to gastric cancer and a reduction in anti-inflammatory bacteria. These alterations might contribute to chronic gastric mucosal inflammation, promoting carcinogenesis in the absence of H. pylori infection. Full article
(This article belongs to the Special Issue Correlations Between the Gastrointestinal Microbiome and Diseases)
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<p>A flowchart of the study.</p>
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<p>Alpha diversity in the gastric microbiota did not significantly differ among the chronic gastritis (CG), intestinal metaplasia (IM), and dysplasia groups. (<b>a</b>) Observed amplicon sequence variants, (<b>b</b>) Pielou’s evenness, (<b>c</b>) Shannon index, and (<b>d</b>) Faith’s phylogenetic diversity. Horizontal lines indicate medians. No significant difference was found among the groups for any alpha diversity index after adjusting for age and sex.</p>
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<p>Overall gastric microbiota composition did not significantly differ between the chronic gastritis (CG), intestinal metaplasia (IM), and dysplasia groups in beta diversity analysis. (<b>a</b>) Bray–Curtis dissimilarity, (<b>b</b>) Jaccard distance, (<b>c</b>) unweighted UniFrac distance, and (<b>d</b>) weighted UniFrac distance. Visualization was performed using principal coordinate analysis. Effect size and significance were assessed using permutational multivariate analysis of variance with 10,000 permutations, adjusting for age and sex. Ellipses represent 95% of data points for each group.</p>
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<p>Gastric mucosal microbiota did not differ at the phylum level among the chronic gastritis (CG), intestinal metaplasia (IM), and dysplasia groups. Although a trend of decreasing relative abundance of Proteobacteria and increasing relative abundance of Firmicutes was observed from the CG to the IM and dysplasia groups, no statistically significant difference was observed among the groups by DESeq2 analysis after adjusting for age and sex.</p>
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<p>Differentially abundant taxa were identified in patients with gastric precancerous lesions compared to those without. Differentially abundant taxa are shown for (<b>a</b>) the comparison between intestinal metaplasia (IM) and chronic gastritis (CG) groups and (<b>b</b>) the comparison between dysplasia and CG groups, identified at the species level using DESeq2 analysis. The effect size represents log<sub>2</sub> fold changes between the groups with 95% confidence intervals. Dot size reflects normalized relative abundance, and colors indicate corresponding phyla. Statistical significance was determined as a false discovery rate <span class="html-italic">q</span>-value &lt; 0.1, with adjustment for age and sex.</p>
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11 pages, 1089 KiB  
Article
Gastric Intestinal Metaplasia in Children and Adolescents Is Reversible upon Reaching Adulthood—Results from a Long-Term Cohort Study
by Jan Drnovšek, Nina Zidar, Jera Jeruc, Lojze M. Šmid, Gaj Vidmar, Borut Štabuc and Matjaž Homan
Cancers 2025, 17(1), 128; https://doi.org/10.3390/cancers17010128 - 3 Jan 2025
Viewed by 531
Abstract
Background/Objectives: Gastric intestinal metaplasia (GIM) is considered an irreversible preneoplastic precursor for gastric adenocarcinoma in adults. However, its significance in children and the long-term outcome remain poorly understood. Methods: All children diagnosed with GIM between 2000 and 2020 were identified at a large [...] Read more.
Background/Objectives: Gastric intestinal metaplasia (GIM) is considered an irreversible preneoplastic precursor for gastric adenocarcinoma in adults. However, its significance in children and the long-term outcome remain poorly understood. Methods: All children diagnosed with GIM between 2000 and 2020 were identified at a large tertiary referral centre. Upon reaching adulthood (≥18 years), the patients were invited to undergo follow-up esophagogastroduodenoscopy (using narrow-band imaging additionally to high-definition white light endoscopy), with gastric biopsies obtained according to the updated Sydney protocol. Childhood and adulthood gastric biopsies were re-evaluated by two experienced gastrointestinal pathologists using Kreyberg staining. Results: Paediatric GIM was diagnosed in 178/14,409 (1.2%) esophagogastroduodenoscopies performed during the study period. Fifty adult patients with childhood GIM agreed to participate in the study. The mean age at childhood and adulthood endoscopies were 14.3 years (median 15) and 25.2 years (median 24), respectively. The mean follow-up interval was 10.5 years. All childhood GIM cases were classified as complete-type. Notably, GIM completely resolved in 41/50 of patients (82%) by the time of adulthood follow-up. No dysplasia or carcinoma was detected in any patient. Childhood Helicobacter pylori infection, similar to other evaluated host-related factors, was not significantly associated with the persistence of GIM into adulthood (11.2% vs. 29.3%, p = 0.41). Conclusions: Childhood GIM was a rare finding but demonstrated a high rate of reversibility by adulthood regardless of Helicobacter pylori status, with no cases of dysplasia or carcinoma observed during long-term follow-up. Full article
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<p>Intestinal metaplasia, complete type. (<b>Left</b>): Kreyberg staining demonstrates blue cytoplasmic mucin vacuoles in the area of intestinal metaplasia, contrasting with the absence of blue staining in the preserved gastric mucosa. (<b>Right</b>): Alcian Blue-Periodic acid Schiff staining shows blue-stained cytoplasmic mucin vacuoles in the area with intestinal metaplasia, along with strong staining of the brush border in the area of preserved gastric mucosa. Original magnification 10×.</p>
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<p>Flowchart of the patient selection process.</p>
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<p>Resolution of childhood gastric intestinal metaplasia stratified by <span class="html-italic">H. pylori</span> infection at diagnosis.</p>
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18 pages, 11501 KiB  
Article
Predictive Value of a Gastric Microbiota Dysbiosis Test for Stratifying Cancer Risk in Atrophic Gastritis Patients
by Alice Zaramella, Diletta Arcidiacono, Miriam Duci, Clara Benna, Salvatore Pucciarelli, Alberto Fantin, Antonio Rosato, Valli De Re, Renato Cannizzaro, Matteo Fassan and Stefano Realdon
Nutrients 2025, 17(1), 142; https://doi.org/10.3390/nu17010142 - 31 Dec 2024
Viewed by 528
Abstract
Background/Objectives: Gastric cancer (GC) incidence remains high worldwide, and the survival rate is poor. GC develops from atrophic gastritis (AG), associated with Helicobacter pylori (Hp) infection, passing through intestinal metaplasia and dysplasia steps. Since Hp eradication does not exclude GC development, [...] Read more.
Background/Objectives: Gastric cancer (GC) incidence remains high worldwide, and the survival rate is poor. GC develops from atrophic gastritis (AG), associated with Helicobacter pylori (Hp) infection, passing through intestinal metaplasia and dysplasia steps. Since Hp eradication does not exclude GC development, further investigations are needed. New data suggest the possible role of unexplored gastric microbiota beyond Hp in the progression from AG to GC. Aimed to develop a score that could be used in clinical practice to stratify GC progression risk, here was investigate gastric microbiota in AG Hp-negative patients with or without high-grade dysplasia (HGD) or GC. Methods: Consecutive patients undergoing upper endoscopy within an endoscopic follow-up for AG were considered. The antrum and corpus biopsies were used to assess the microbiota composition along the disease progression by sequencing the 16S ribosomal RNA gene. Statistical differences between HGD/GC and AG patients were included in a multivariate analysis. Results: HGD/GC patients had a higher percentage of Bacillus in the antrum and a low abundance of Rhizobiales, Weeksellaceae and Veillonella in the corpus. These data were used to calculate a multiparametric score (Resident Gastric Microbiota Dysbiosis Test, RGM-DT) to predict the risk of progression toward HGD/GC. The performance of RGM-DT in discriminating patients with HGD/GC showed a specificity of 88.9%. Conclusions: The microbiome-based risk prediction model for GC could clarify the role of gastric microbiota as a cancer risk biomarker to be used in clinical practice. The proposed test might be used to personalize follow-up program thanks to a better cancer risk stratification. Full article
(This article belongs to the Special Issue The Potential of Gut Microbiota in Cancer)
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<p>The schematic flow chart of the study design and the patients’ course.</p>
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<p>Quality of sequencing and alpha diversity measures. (<b>A</b>,<b>B</b>) Comparison of the number of OTUs among the patient groups in the (<b>A</b>) antrum and (<b>B</b>) corpus. (<b>C</b>,<b>D</b>) Comparison of alpha diversity measures in each group studied in the antrum (<b>C</b>) and corpus (<b>D</b>) biopsies. Statistical analyses were performed with one-way ANOVA. Post hoc analyses are annotated as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. Box plots represent the median, interquartile range, and lower and minimum values. Each dot represents an individual patient. CTRL are healthy subjects; mAG: patients with mild atrophic gastritis (i.e., OLGA stages I–II); sAG: patients with severe atrophic gastritis (i.e., OLGA stages III–IV); HGD/GC: patients with severe AG and HGD or GC.</p>
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<p>Principal coordinate analysis (PCoA) 3D plots of (<b>A</b>) weighted UniFrac in the antrum, (<b>B</b>) unweighted UniFrac in the antrum, (<b>C</b>) weighted UniFrac in the corpus, and (<b>D</b>) unweighted UniFrac in the corpus, in which samples are colored according to clinical outcome. Green dots represent CTRL patients, blue dots represent mAG patients, yellow dots represent sAG patients, and red dots represent HGD/GC patients. * PERMANOVA analysis.</p>
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<p>(<b>A</b>,<b>B</b>) Pie charts representing the relative abundance of the main phyla colonizing the gastric tissues in the antrum (<b>A</b>) and in the corpus (<b>B</b>) of all subjects and in each group of patients considered. Data are shown as the median values. Phyla with a relative abundance higher than 0.005% are plotted. (<b>C</b>) Bacteria significantly changed in gastric microbiota during GC development in the antrum and the corpus. Post hoc analyses are annotated as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. CTRL: healthy subjects; mAG: patients with mild atrophic gastritis (i.e., OLGA stages I–II); sAG: patients with severe atrophic gastritis (i.e., OLGA stages III–IV); HGD/GC: patients with severe atrophic gastric and HGD or GC. Data are shown as the median, maximum, and minimum values.</p>
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<p>(<b>A</b>,<b>B</b>) Principal coordinate analysis (PCoA) 3D plots of the unweighted UniFrac measurements in the antrum (<b>A</b>) and the corpus (<b>B</b>). Each point represents a sample and is colored according to clinical outcome. Green dots represent non-dysplastic AG patients, and red dots represent HGD/GC patients. Statistical analyses were performed with PERMANOVA. (<b>C</b>–<b>F</b>) Bar plots represent the relative abundance of the main bacterial colonizing gastric mucosa in non-dysplastic AG and dysplastic GC in both the antrum and the corpus at the phylum (<b>C</b>,<b>D</b>) and class (<b>E</b>,<b>F</b>) levels. Data are presented as median values. Only data that show a median relative abundance higher than 0.1% are plotted. Statistical analysis comparing the relative abundance of the Negativicutes class between the two groups was performed using the Mann–Whitney U test and annotated as * <span class="html-italic">p</span> &lt; 0.05. Non-dysplastic AG: patients with atrophic gastritis (mAG and sAG); HGD/GC: patients with HGD or GC.</p>
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<p>Pie charts representing the difference in the relative abundance of the main bacterial orders (<b>A</b>–<b>D</b>), families (<b>E</b>–<b>H</b>), and genera (<b>I</b>–<b>L</b>) colonizing gastric tissue in both the antrum and the corpus, comparing non-dysplastic AG patients and AG patients with high-grade dysplasia or GC. Data are presented as median values. Only data showing a median relative abundance value higher than 0.001% are reported.</p>
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<p>Relative abundance comparison of gastric bacteria significantly differed between non-dysplastic AG (non-dys AG) and patients who progressed through dysplasia and cancer (HGD/GC) both in the antrum (<b>A</b>–<b>F</b>) and in the corpus (<b>G</b>–<b>L</b>). (p, phylum; c, class; o, order; f, family; g, genus). Data are presented as the median, minimum, and maximum values. Statistical differences in the relative abundance were analyzed using the Mann–Whitney U test and annotated as * <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>(<b>A</b>) Schematic representation of points assigned to each patient to construct the proposed RGM-DT scoring system. (p, phylum; c, class; o, order; f, family; g, genus). (<b>B</b>) RGM-DT score for each patient according to the disease group. (<b>C</b>) RGM-DT score in the non-dysplastic AG group (mild and severe AG taken together) compared to the dysplastic AG group. Data are reported as mean and standard deviation. Statistical analysis was performed using the Mann–Whitney U test. (<b>D</b>) Correlation between RGM-DT and OLGA score. (<b>E</b>) The ROC curve analysis shows the performance of the RGM-DT score in discriminating between non-dysplastic AG patients and HGD/GC AG patients.</p>
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20 pages, 9893 KiB  
Review
The Influence of Gastric Microbiota and Probiotics in Helicobacter pylori Infection and Associated Diseases
by Jagriti Verma, Md Tanveer Anwar, Bodo Linz, Steffen Backert and Suneesh Kumar Pachathundikandi
Biomedicines 2025, 13(1), 61; https://doi.org/10.3390/biomedicines13010061 - 30 Dec 2024
Viewed by 593
Abstract
The role of microbiota in human health and disease is becoming increasingly clear as a result of modern microbiome studies in recent decades. The gastrointestinal tract is the major habitat for microbiota in the human body. This microbiota comprises several trillion microorganisms, which [...] Read more.
The role of microbiota in human health and disease is becoming increasingly clear as a result of modern microbiome studies in recent decades. The gastrointestinal tract is the major habitat for microbiota in the human body. This microbiota comprises several trillion microorganisms, which is equivalent to almost ten times the total number of cells of the human host. Helicobacter pylori is a known pathogen that colonizes the gastric mucosa of almost half of the world population. H. pylori is associated with several gastric diseases, including gastric cancer (GC) development. However, the impact of the gastric microbiota in the colonization, chronic infection, and pathogenesis is still not fully understood. Several studies have documented qualitative and quantitative changes in the microbiota’s composition in the presence or absence of this pathogen. Among the diverse microflora in the stomach, the Firmicutes represent the most notable. Bacteria such as Prevotella sp., Clostridium sp., Lactobacillus sp., and Veillonella sp. were frequently found in the healthy human stomach. In contrast, H.pylori is very dominant during chronic gastritis, increasing the proportion of Proteobacteria in the total microbiota to almost 80%, with decreasing relative proportions of Firmicutes. Likewise, H. pylori and Streptococcus are the most abundant bacteria during peptic ulcer disease. While the development of H. pylori-associated intestinal metaplasia is accompanied by an increase in Bacteroides, the stomachs of GC patients are dominated by Firmicutes such as Lactobacillus and Veillonella, constituting up to 40% of the total microbiota, and by Bacteroidetes such as Prevotella, whereas the numbers of H. pylori are decreasing. This review focuses on some of the consequences of changes in the gastric microbiota and the function of probiotics to modulate H. pylori infection and dysbiosis in general. Full article
(This article belongs to the Special Issue Inflammatory Chaos in Helicobacter pylori Infection)
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<p>Changes in the gastric microbiota following <span class="html-italic">Helicobacter pylori</span> infection. Schematic representation of the predominant phyla of the gastric microbiota in <span class="html-italic">H. pylori</span>-negative (Hp-neg.) and in <span class="html-italic">H. pylori</span>-positive individuals (Hp-pos.) and in individuals with intestinal metaplasia (IM) or with GC.</p>
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<p><span class="html-italic">Helicobacter pylori</span> infection promoting and inhibiting major microbiota groups in pathogenesis. The dynamics of microbiota composition during <span class="html-italic">H. pylori</span> infection might be involved in the associated pathologies. <span class="html-italic">H. pylori</span> is a critical factor affecting the microbiota diversity in the gastric mucosa. In the context of an <span class="html-italic">H. pylori</span> infection, gastric microbiota groups can be inhibited or promoted. As per the available evidence, these two microbiota groups are functionally different in supporting or preventing the growth of <span class="html-italic">H. pylori</span>, immune responses, and pathogenesis of the associated diseases. Thus, the survival and successful colonization of <span class="html-italic">H. pylori</span> leads to dysbiosis, which favors persistence of infection.</p>
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11 pages, 2671 KiB  
Article
Edge Artificial Intelligence Device in Real-Time Endoscopy for Classification of Gastric Neoplasms: Development and Validation Study
by Eun Jeong Gong, Chang Seok Bang and Jae Jun Lee
Biomimetics 2024, 9(12), 783; https://doi.org/10.3390/biomimetics9120783 - 22 Dec 2024
Viewed by 688
Abstract
Objective: We previously developed artificial intelligence (AI) diagnosis algorithms for predicting the six classes of stomach lesions. However, this required significant computational resources. The incorporation of AI into medical devices has evolved from centralized models to decentralized edge computing devices. In this study, [...] Read more.
Objective: We previously developed artificial intelligence (AI) diagnosis algorithms for predicting the six classes of stomach lesions. However, this required significant computational resources. The incorporation of AI into medical devices has evolved from centralized models to decentralized edge computing devices. In this study, a deep learning endoscopic image classification model was created to automatically categorize all phases of gastric carcinogenesis using an edge computing device. Design: A total of 15,910 endoscopic images were collected retrospectively and randomly assigned to train, validation, and internal-test datasets in an 8:1:1 ratio. The major outcomes were as follows: 1. lesion classification accuracy in six categories: normal/atrophy/intestinal metaplasia/dysplasia/early/advanced gastric cancer; and 2. the prospective evaluation of classification accuracy in real-world procedures. Results: The internal-test lesion-classification accuracy was 93.8% (95% confidence interval: 93.4–94.2%); precision was 88.6%, recall was 88.3%, and F1 score was 88.4%. For the prospective performance test, the established model attained an accuracy of 93.3% (91.5–95.1%). The established model’s lesion classification inference speed was 2–3 ms on GPU and 5–6 ms on CPU. The expert endoscopists reported no delays in lesion classification or any interference from the deep learning model throughout their exams. Conclusions: We established a deep learning endoscopic image classification model to automatically classify all stages of gastric carcinogenesis using an edge computing device. Full article
(This article belongs to the Special Issue Artificial Intelligence (AI) in Biomedical Engineering)
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<p>Scheme of the algorithm.</p>
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<p>Confusion matrix for the internal test.</p>
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<p>Confusion matrix for the prospective validation test.</p>
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<p>Representative images of attention map analysis.</p>
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10 pages, 1283 KiB  
Article
Endoscopic and Histological Characteristics of Gastric Cancer Detected Long After Helicobacter pylori Eradication Therapy
by Ryo Abe, Shu Uchikoshi, Yohei Horikawa, Nobuya Mimori, Yuhei Kato, Yuta Tahata, Saki Fushimi, Masahiro Saito and Satsuki Takahashi
Cancers 2024, 16(24), 4153; https://doi.org/10.3390/cancers16244153 - 13 Dec 2024
Viewed by 699
Abstract
Background/Objectives: Since 2013, eradication therapy for Helicobacter pylori gastritis (Hp-ET) has been covered by the National Health Insurance of Japan. Recently, the risk of post-eradication gastric cancer (pE-GC) has increased. pE-GC includes cancers that develop immediately and several years after Hp [...] Read more.
Background/Objectives: Since 2013, eradication therapy for Helicobacter pylori gastritis (Hp-ET) has been covered by the National Health Insurance of Japan. Recently, the risk of post-eradication gastric cancer (pE-GC) has increased. pE-GC includes cancers that develop immediately and several years after Hp-ET. Therefore, we aimed to clarify the endoscopic and histological characteristics of late types of pE-GCs. Method: One hundred patients with differentiated cancers detected after Hp-ET who underwent endoscopic submucosal dissection from 2015 to 2023 were compared. Patients were divided into two groups; the immediate group (n = 69), with cancer detected within 6 years, and the delayed group (n = 31), with cancer detected within >6 years after Hp-ET. The background mucosa and tumor mucosa were examined individually. The endoscopic findings were as follows: enlarged folds, map-like redness, intermediate zone irregularity, and the presence of a regular arrangement of collecting venules and a light blue crest (background); an irregular surface structure, an irregular vascular pattern, an irregular surface pattern, and a gastritis-like appearance (tumor). The histological findings were as follows: a low remnant rate of the fundic glands, intestinal metaplasia (IM), crypt enlargement, and neutrophil infiltration (background); mosaicism, the elongation of noncancer ducts, and an overlying non-neoplastic epithelium (tumor). Results: There was no significant difference regarding the background mucosa and tumor mucosa between the two groups. In the delayed group, the remnant rate of the fundic glands was 19.8 ± 15.6%, and IM was 87.1% (27/31). Further, 90.3% (28/31) of the patients exhibited persistent neutrophil infiltration. Conclusion: This study suggested that patients with a low remnant rate of the fundic gland and IM and persistent mucosal inflammation were at high risk for developing pE-GCs. Full article
(This article belongs to the Special Issue Developments in the Management of Gastrointestinal Malignancies)
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<p>Annual transitions of post-eradication gastric cancer treated with gastric ESD (total 100 cases).</p>
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<p>Flow diagram of patient enrollment.</p>
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<p>The remnant rate of the fundic glands. This was calculated by microscopically measuring the area of the fundic glands on the edge of the ESD specimen (1.0 mm × 2.0 mm).</p>
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<p>Annual transitions of remnant rate of fundus glands on background mucosa.</p>
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29 pages, 14685 KiB  
Article
Helicobacter pylori Inhibition, Gastritis Attenuation, and Gut Microbiota Protection in C57BL/6 Mice by Ligilactobacillus salivarius NCUH062003
by Junyi Li, Xiaoyan Xu, Shiyu Yang, Kui Liu, Min Wu, Mingyong Xie and Tao Xiong
Microorganisms 2024, 12(12), 2521; https://doi.org/10.3390/microorganisms12122521 - 7 Dec 2024
Viewed by 1032
Abstract
Helicobacter pylori (H. pylori), one of the most prevalent pathogenic bacteria worldwide, is the leading cause of gastritis, gastric intestinal metaplasia, and gastric cancer. Antibiotics, the conventional treatment for eliminating H. pylori, often lead to severe bacterial resistance, gut dysbiosis, [...] Read more.
Helicobacter pylori (H. pylori), one of the most prevalent pathogenic bacteria worldwide, is the leading cause of gastritis, gastric intestinal metaplasia, and gastric cancer. Antibiotics, the conventional treatment for eliminating H. pylori, often lead to severe bacterial resistance, gut dysbiosis, and hepatic insufficiency and fail to address the inflammatory response or gastric mucosal damage caused by H. pylori infection. In this study, based on 10-week animal experiments, two models of L. salivarius NCUH062003 for the prophylaxis and therapy of H. pylori infection in C57BL/6 mice were established; a comprehensive comparative analysis was performed to investigate the anti-H. pylori effect of probiotics, the reduction in inflammation, and repair of gastric mucosal damage. ELISA, immunohistochemistry, and pathology analyses showed that NCUH062003 decreased the expression of pro-inflammatory cytokine interleukins (IL-1β, IL-6) and myeloperoxidase (MPO) and reduced neutrophil infiltration in the gastric mucosa lamina propria. Immunofluorescence and biochemical analysis showed that NCUH062003 resisted gastric epithelial cell apoptosis, increased the level of superoxide dismutase (SOD) in gastric mucosa, and promoted the expression of tight junction protein ZO1 and Occludin. In addition, through high-throughput sequencing, in the probiotic therapy and prophylactic mode, the diversity and composition of the gut microbiota of HP-infected mice were clarified, the potential functions of the gut microbiota were analyzed, the levels of short-chain fatty acids (SCFAs) were measured, and the effects of L. salivarius NCUH062003 on the gut microbiota and its metabolites in HP-infected mice treated with amoxicillin/metronidazole were revealed. This study provides functional strain resources for the development and application of microbial agents seeking to antagonize H. pylori beyond antibiotics. Full article
(This article belongs to the Section Gut Microbiota)
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Graphical abstract
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<p>(<b>A</b>) The schematic diagram of <span class="html-italic">H. pylori</span> infection in the multiple therapy and prophylaxis processes conducted on C57BL/6 mice. (<b>B</b>) Schematic diagram showing the mechanisms of <span class="html-italic">L. salivarius</span> NCUH062003. A total of 9 groups were formed, with 8 mice in each group.</p>
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<p>(<b>A</b>,<b>B</b>) Determination of the abundance of <span class="html-italic">H. pylori</span> in the gastric tissues of mice in therapeutic and prophylactic groups. (<b>C</b>,<b>D</b>) Determination of the urease activity of the mouse gastric mucosa in therapeutic and prophylactic groups. Therapeutic groups: (1) control, (2) HP_NaCl, (3) HP_LP61, (4) HP_LS03, (5) HP_Ant, (6) and Ant_LS03 groups. Prophylactic groups: (1) control, (7) NaCl_HP, (8) LP61_HP, (9) and LS03_HP groups. LP61: <span class="html-italic">L. plantarum</span> CMCC 20261. LS03: <span class="html-italic">L. salivarius</span> NCUH062003 ANT: 0.125 μg mL<sup>−1</sup> amoxicillin and 0.5 μg mL<sup>−1</sup> metronidazole. A total of 9 groups were formed, with 8 mice in each group. Different lowercase letters in the bar graphs indicated significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>(<b>A</b>) Histopathology of gastric antrum tissue in the pyloric part of mice from different groups as determined by hematoxylin and eosin staining (200×). (<b>B</b>) Gastric mucosal lymphocyte infiltration score. (<b>C</b>) Gastric mucosal injury score. Therapeutic groups: control, HP_NaCl, HP_LP61, HP_LS03, HP_Ant, and Ant_LS03 groups. Prophylactic groups: control, NaCl_HP, LP61_HP, and LS03_HP groups. Black arrow: massive vacuole formation in lamina propria of gastric mucosa. Red arrow: neutrophil and lymphocyte infiltration in epithelial layer and lamina propria; green arrow: erythrocytes and hemorrhage in muscularis mucosa. Different lowercase letters in the bar graphs indicated significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Determination of MPO activity (<b>A</b>,<b>F</b>) and SOD levels (<b>E</b>,<b>J</b>) in gastric tissue of mice and the levels of pro-inflammatory factors IL-1β (<b>B</b>,<b>G</b>) and IL-6 (<b>C</b>,<b>H</b>) and anti-inflammatory factor IL-10 (<b>D</b>,<b>I</b>) in the serum of mice in the prophylactic and therapeutic groups, as determined by enzyme-linked immunosorbent assay (ELISA). Therapeutic groups: control, HP_NaCl, HP_LP61, HP_LS03, HP_Ant, and Ant_LS03 groups. Prophylactic groups: control, NaCl_HP, LP61_HP, and LS03_HP groups. Different lowercase letters in the bar graphs indicated significant differences (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Immunohistochemical staining of pro-inflammatory IL-1β (<b>A</b>) and anti-inflammatory TGF-β (<b>B</b>) in mice gastric tissue in the therapeutic and prophylactic groups (200×). Hematoxylin-stained nuclei were blue, and DAB (3,3′-Diaminobenzidine) showed positive expression in a brownish color. Therapeutic groups: control, HP_NaCl, HP_LP61, HP_LS03, HP_Ant, and Ant_LS03 groups. Prophylactic groups: control, NaCl_HP, LP61_HP, and LS03_HP groups.</p>
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<p>(<b>A</b>) Immunofluorescence heterologous double-labeled Ki-67 and β-catenin staining images in gastric tissues used to assess the apoptosis of gastric epithelial cells. (<b>B</b>) Immunofluorescence homologous double-labeled staining images of Occludin and ZO1 proteins involved in gastric mucosal epithelial repair (400×). DAPI channel nuclei appear blue, 488 channel positivity appears green, and CY3 channel positivity appears red. Therapeutic groups: control, HP_NaCl, HP_LP61, HP_LS03, HP_Ant, and Ant_LS03 groups. Prophylactic groups: control, NaCl_HP, LP61_HP, and LS03_HP groups.</p>
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<p>(<b>A</b>) Alpha diversity index of the mice gut microbiota samples in each therapeutic group: (<b>a</b>) ACE index, (<b>b</b>) Chao1 index, (<b>c</b>) Shannon index, and (<b>d</b>) Simpson index. (<b>B</b>) The PCoA chart of the gut microbiota of mice in each therapeutic group. (<b>C</b>) The hierarchical clustering tree diagram of the gut microbiota of mice in therapeutic groups. Therapeutic groups: control, HP_NaCl, HP_LP61, HP_LS03, HP_Ant, and Ant_LS03 groups. A total of 6 groups were formed, with 8 mice in each group.</p>
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<p>(<b>A</b>) The relative abundance of gut microbiota at the phylum level of mice in each therapeutic group. (<b>B</b>) Venn diagram of the gut microbiota of mice in each therapeutic group. (<b>C</b>) The relative abundance of gut microbiota at the genus level of mice in each therapeutic group. The taxonomic cladogram (<b>D</b>) and the histogram (<b>E</b>) from LEfSe analysis of the gut microbiota in therapeutic groups. Therapeutic groups: control, HP_NaCl, HP_LP61, HP_LS03, HP_Ant, and Ant_LS03 groups. A total of 6 groups were formed, with 8 mice in each group.</p>
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<p>(<b>A</b>) Alpha diversity index of the mice gut microbiota samples in each prophylactic group: (<b>a</b>) ACE index, (<b>b</b>) Chao1 index, (<b>c</b>) Shannon index, and (<b>d</b>) Simpson index. The beta diversity of gut microbiota of mice in prophylactic groups: (<b>B</b>) PCoA plot and (<b>C</b>) NMDS plot. Prophylactic groups: control, NaCl_HP, LP61_HP, and LS03_HP groups. A total of 4 groups were formed, with 8 mice in each group.</p>
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<p>(<b>A</b>) The relative abundance of gut microbiota at the phylum level of mice in each prophylactic group. (<b>B</b>) Venn diagram of the gut microbiota of mice in each prophylactic group. (<b>C</b>) The relative abundance of gut microbiota at the genus level of mice in each prophylactic group. The taxonomic cladogram (<b>D</b>) and the histogram (<b>E</b>) from LEfSe analysis of the gut microbiota in prophylactic groups. Prophylactic groups: control, NaCl_HP, LP61_HP, and LS03_HP groups. A total of 4 groups were formed, with 8 mice in each group.</p>
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<p>(<b>A</b>) Metabolic pathway statistical map for predicted functions of gut microbiota in each therapeutic group. (<b>B</b>) PCoA for potential functional units of the gut microbiota of mice in each therapeutic group. (<b>C</b>) Significantly different metabolic pathways between the HP_Ant and control groups in the predicted functions of gut microbiota. (<b>D</b>) Significantly different metabolic pathways between the Ant_LS03 and control groups in the predicted functions of gut microbiota. Therapeutic groups: control, HP_NaCl, HP_LP61, HP_LS03, HP_Ant, and Ant_LS03 groups. A total of 6 groups were formed, with 8 mice in each group.</p>
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14 pages, 948 KiB  
Article
Could APTIMA mRNA Assay Contribute to Predicting Cervical Bacterial Sexually Transmitted Co-Infections? A Colposcopy Population Study
by George Valasoulis, Abraham Pouliakis, Ioulia Magaliou, Dimitrios Papoutsis, Nikoletta Daponte, Chrysoula Margioula-Siarkou, Georgios Androutsopoulos, Alexandros Daponte and Georgios Michail
Int. J. Mol. Sci. 2024, 25(23), 13146; https://doi.org/10.3390/ijms252313146 - 6 Dec 2024
Viewed by 834
Abstract
In addition to chronic hrHPV anogenital infection, continuing inflammatory cervical changes are intrinsic in the development of precancerous lesions. In younger women, much of this inflammatory background parallels the progressive maturation of squamous metaplasia, often rendering treatment interventions redundant; however, patients with persistent [...] Read more.
In addition to chronic hrHPV anogenital infection, continuing inflammatory cervical changes are intrinsic in the development of precancerous lesions. In younger women, much of this inflammatory background parallels the progressive maturation of squamous metaplasia, often rendering treatment interventions redundant; however, patients with persistent cervical precancer, as well as those harboring invasive bacterial pathogens, might benefit from controlling the active inflammatory process by shortening the HPV natural cycle and avoiding subsequent cervical surgery. In a colposcopy population of 336 predominantly young asymptomatic individuals, we explored the impact of molecularly detected bacterial STIs on HPV DNA and APTIMA positivity rates using validated assays. In the multivariable analysis, several largely anticipated epidemiological factors were related to STI positivity. In this cohort, the HPV DNA test illustrated better performance for the prediction of STI positivity than the corresponding APTIMA test (sensitivity 52.94% vs. 33.82%), while inversely, the APTIMA test was more indicative of bacterial STI negativity than the HPV DNA test (specificity 77% vs. 60%). In addition, no significant differences between these two molecular assays were documented in terms of PPV, NPV, and overall accuracy. Despite the high Ureaplasma urealyticum and low Chlamydia trachomatis prevalence recorded in this study’s population, which is among the first assessing the co-variation of bacterial STI expression with established HPV biomarkers, the APTIMA assay did not predict concurrent bacterial STIs superiorly compared with an established HPV DNA assay. Full article
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<p>Odds Ratios and 95% confidence limits of parameters affecting STI positivity at univariate analysis.</p>
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<p>Characteristic curves illustrate the probability of STI positivity. (<b>Upper left</b>): parity and vaccination effect on STI positivity; (<b>Upper right</b>): parity and recent partner change effect on STI positivity; (<b>lower left</b>): number of sex partners and vaccination status on STI positivity and (<b>lower right</b>): number of sex partners and abnormal cytology role in STI positivity risk. The Vertical axis shows the probability of STI positivity.</p>
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16 pages, 1094 KiB  
Article
Prevalence of Abnormalities at Tandem Endoscopy in Patients Referred for Colorectal Cancer Screening/Surveillance Colonoscopy
by George Triadafilopoulos
Cancers 2024, 16(23), 3998; https://doi.org/10.3390/cancers16233998 - 29 Nov 2024
Viewed by 778
Abstract
Introduction: Performing a tandem endoscopy and colonoscopy in selected individuals has advantages, such as the early detection of benign and/or precancerous foregut diseases; it is efficient, and it may allow added therapies. It may also have disadvantages, such as generating anxiety from false-positive [...] Read more.
Introduction: Performing a tandem endoscopy and colonoscopy in selected individuals has advantages, such as the early detection of benign and/or precancerous foregut diseases; it is efficient, and it may allow added therapies. It may also have disadvantages, such as generating anxiety from false-positive screening, possible harm from further testing, and unproven cost-effectiveness. Aims: We aimed to examine the prevalence of foregut endoscopic and histologic abnormalities in subjects referred for screening/surveillance colonoscopy who also underwent a tandem endoscopy. We wanted to (1) assess implications for cancer detection, intervention, and surveillance of precancerous foregut abnormalities, (2) identify benign foregut lesions, and (3) generate data on the utilities of this tandem approach. Patients and Methods: A retrospective cohort study of consecutive subjects referred for screening or surveillance colonoscopy who also underwent an endoscopy. Based on national screening guidelines, responses to prompting questions, personal or family history, or other risk factors, subjects were assigned to tandem endoscopy with biopsies (modified Seattle and Sydney protocols), under one anesthesia. Results: Of the 1004 patients referred for colonoscopy, 317 (32%) underwent tandem endoscopy. There were 214 women and 103 men. There were 237 Whites, 16 Asians, 40 Blacks, and 24 Hispanics. Median age was 59 (range 19–85). At endoscopy, we identified actionable benign (45%) peptic, inflammatory, and H. pylori-related abnormalities, and premalignant findings (i.e., intestinal metaplasia, 27%, dysplasia, 2%, and cancer 0.9%), comparable to the premalignant (40.3%) and malignant (0.6%) colonoscopy yield. Conclusions: When implemented based on national screening guidelines, tandem EGD and colonoscopy combines Barrett’s esophagus and gastric cancer screening in one examination, and it has a high yield in a diverse US population. Full article
(This article belongs to the Collection Oncology: State-of-the-Art Research in the USA)
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<p>Study flow diagram.</p>
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<p>Need for action depending on endoscopic and histologic findings at endoscopy in the 317 subjects of the dual EGD/colonoscopy cohort.</p>
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<p>Point % prevalence of key benign and malignant endoscopic abnormalities at tandem EGD and colonoscopy in 317 subjects. PD: Peptic duodenitis; PS: Pyloric Stenosis; G: Gastritis; AN: Antral Nodule; FP: Fundic Polyp; Cancer; HH: Hiatal Hernia; SR: Schatzki’s Ring; EE: Erosive Esophagitis; BE: Barrett’s Esophagus; EoE: Eosinophilic Esophagitis; Polyps; CRC: Colorectal Cancer.</p>
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<p>Point % prevalence of key histologic abnormalities at tandem EGD and colonoscopy in 317 subjects. DL: Duodenal lymphocytosis; HP+: Active <span class="html-italic">H. pylori</span> infection; GIM: Gastric Intestinal Metaplasia; SCJ-IM: Squamocolumnar Junction–Intestinal Metaplasia; PAM: Pancreatic Acinar Metaplasia; Cancer; PE: Peptic esophagitis; EoE: Eosinophilic esophagitis; TA: Tubular Adenoma (including serrated polyps); HP: Hyperplastic polyps; CRC: Colorectal cancer.</p>
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23 pages, 18277 KiB  
Article
Novel Core Gene Signature Associated with Inflammation-to-Metaplasia Transition in Influenza A Virus-Infected Lungs
by Innokenty A. Savin, Aleksandra V. Sen’kova, Elena P. Goncharova, Marina A. Zenkova and Andrey V. Markov
Int. J. Mol. Sci. 2024, 25(22), 11958; https://doi.org/10.3390/ijms252211958 - 7 Nov 2024
Viewed by 919
Abstract
Respiratory infections caused by RNA viruses are a major contributor to respiratory disease due to their ability to cause annual epidemics with profound public health implications. Influenza A virus (IAV) infection can affect a variety of host signaling pathways that initiate tissue regeneration [...] Read more.
Respiratory infections caused by RNA viruses are a major contributor to respiratory disease due to their ability to cause annual epidemics with profound public health implications. Influenza A virus (IAV) infection can affect a variety of host signaling pathways that initiate tissue regeneration with hyperplastic and/or dysplastic changes in the lungs. Although these changes are involved in lung recovery after IAV infection, in some cases, they can lead to serious respiratory failure. Despite being ubiquitously observed, there are limited data on the regulation of long-term recovery from IAV infection leading to normal or dysplastic repair represented by inflammation-to-metaplasia transition in mice or humans. To address this knowledge gap, we used integrative bioinformatics analysis with further verification in vivo to elucidate the dynamic molecular changes in IAV-infected murine lung tissue and identified the core genes (Birc5, Cdca3, Plk1, Tpx2, Prc1. Rrm2, Nusap1, Spag5, Top2a, Mcm5) and transcription factors (E2F1, E2F4, NF-YA, NF-YB, NF-YC) involved in persistent lung injury and regeneration processes, which may serve as gene signatures reflecting the long-term effects of IAV proliferation on the lung. Further analysis of the identified core genes revealed their involvement not only in IAV infection but also in COVID-19 and lung neoplasm development, suggesting their potential role as biomarkers of severe lung disease and its complications represented by abnormal epithelial proliferation and oncotransformation. Full article
(This article belongs to the Special Issue Influenza Viruses: Infection and Genomics)
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<p>Morphological changes and viral titers in the lungs of mice during development of influenza A virus (IAV) infection. (<b>A</b>) Experimental setup. Balb/C mice were intranasally (i.n.) infected with IAV (1 LD<sub>50</sub>). At days 1, 3, 7, 10, and 14 post infection (d.p.i.), the lungs were collected for subsequent analysis. (<b>B</b>) Viral titers in the lungs of mice with IAV. (<b>C</b>) Representative histological images of IAV-infected lungs on 1, 3, 7, 10, and 14 d.p.i. Hematoxylin and eosin staining, original magnification ×200. Red and green arrows indicate inflammatory infiltration and squamous metaplasia in the lung tissue, respectively. (<b>D</b>) Dynamic inflammatory and proliferative changes in the lung tissue of IAV-challenged mice. To assess the intensity of inflammation and squamous metaplasia in the lungs, the semi-quantitative histological scoring system was used: 0—no pathological changes, 1—mild inflammation and metaplasia, 2—moderate inflammation and metaplasia, 3—severe inflammation and metaplasia.</p>
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<p>Bioinformatics analysis of key genes involved in the development of influenza virus infection. (<b>A</b>) Venn diagram of overlap between differentially expressed genes (DEGs) identified by re-analysis of datasets obtained from murine models of influenza virus infection at 7 (<b>left</b>) and at 10–12 (<b>right</b>) days after induction, and common DEGs between them (<b>middle</b>). DEGs selected for further analysis are circled in red. (<b>B</b>) PPI networks reconstructed from DEGs included in the analysis, using STRING database (confidence score ≥ 0.7, maximal number of additional interactors = 0), for batch #1 (<b>left</b>) and batch #2 (<b>right</b>). The sizes of nodes indicate roughly the centrality (degree) of each node. Additionally, clusters of the most interconnected DEGs were identified using MCODE plugin in Cytoscape software v.3.10.2. Yellow color indicates the nodes in the top-score MCODE cluster. Red gene titles indicate genes common for both gene association networks. (<b>C</b>) Detailed PPI networks, reconstructed from the DEGs in the MCODE clusters, for batch #1 (<b>left</b>) and batch #2 (<b>right</b>), and Venn diagram showing common DEGs between MCODE clusters (<b>middle</b>).</p>
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<p>Bioinformatics analysis of key genes and corresponding transcription factors involved in the development of influenza virus infection. (<b>A</b>,<b>B</b>) Graphs showing the dynamics of DEG expression levels during the course of influenza infection in the most representative GSE dataset, obtained through the STEM clusterization analysis. Only DEGs in the same profile as indicated by STEM are shown on the graphs. Different graph colors indicate different genes. (<b>C</b>,<b>D</b>) Functional analysis of the DEGs in the STEM clusterization profiles. Enrichment for Gene Ontology (biological processes), KEGG, REACTOME, and WikiPathways terms were performed using ClueGO plugin in Cytoscape. Only pathways with <span class="html-italic">p</span> &lt; 0.05 after Bonferroni step-down correction for multiple testing were included. (<b>E</b>) Venn diagram demonstrating common genes between DEGs identified at 10–12 d.p.i. (upper Venn diagram) and 7 d.p.i. (lower Venn diagram), and heatmap showing expression levels of identified DEGs in all analyzed datasets. (<b>F</b>) Identification of transcription factors regulating the expression of identified DEGs through iRegulon plugin in Cytoscape software. Only transcription factors and DEGs present in motifs with NES higher than 10 are shown. Green nodes—transcription factors, blue nodes—DEGs identified in (<b>E</b>), pink—DEGs absent in performed Venn diagram analysis. Numbers under lines near transcription factors indicate NES scores.</p>
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<p>Analysis of expression profiles of genes and transcription factors identified by bioinformatics analysis in the lung tissue of mice challenged with IAV. (<b>A</b>,<b>B</b>) The graphs show qRT-PCR data for healthy lungs (healthy control, HC) and influenza-challenged lungs at several time points after infection. Blue graph lines are DEGs, orange graph lines are TFs. Expression levels were normalized to the expression level of hypoxanthine phosphoribosyltransferase (HPRT) used as a reference gene. Three to five samples from each group were analyzed in triplicate. The data are shown as mean ± standard error mean, *—<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. (<b>C</b>) Heatmap visualizing expression level changes during influenza virus infection development. The heatmap was constructed using Morpheus web-application (<a href="https://software.broadinstitute.org/morpheus/" target="_blank">https://software.broadinstitute.org/morpheus/</a> (accessed on 17 May 2024)). (<b>D</b>) Correlation matrix visualizing correlations between expression profiles of identified DEGs and TFs throughout IAV infection development. The correlation coefficient was calculated according to the Pearson formula through ggcorrplot R package, and the matrix was visualized through ggplot2 R package. Cells with non-significant correlation coefficients are crossed out.</p>
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<p>Expression profiles of genes identified in the lung tissue of IAV-infected mice and in the peripheral blood of influenza and COVID-19 human patients. (<b>A</b>) Heatmap showing expression of identified DEGs in public datasets, obtained from human patients with IAV and COVID-19 infections. Heatmap was constructed using Morpheus web-tool of the Broad Institute (<a href="https://software.broadinstitute.org/morpheus/" target="_blank">https://software.broadinstitute.org/morpheus/</a> (accessed on 10 August 2024)). (<b>B</b>) Expression level of DEGs of interest in peripheral blood of COVID-19 patients according to bulk-RNA seq analysis. Graph was constructed using COMBATdb comparing blood from healthy volunteers (H) with blood from mild (mC), severe (sC), and critical (cC) COVID-19 patients. Sample inclusion strategy was one priority sample at maximum severity per individual. FDR ≤ 0.05.</p>
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<p>Association between identified DEGs of interest and human neoplasms. (<b>A</b>) Network, including connections between identified DEGs and human diseases. Disease nodes include neoplasm (red) and non-neoplasm diseases (green) with additional classification based on organ specificity: organ-specific (circle), non-organ-specific (square), lung disorders (triangle) and hematological disorders (rhombus). Search was performed in DisGeNET curated database, all sources included. (<b>B</b>) Correlation between high and low expression of identified DEGs of interest and survival rate of patients with lung adenocarcinoma (LUAD). Comparison was performed between patients in 25th percentile of high and low expression levels using TCGA database and OncoLnc web-server [<a href="#B91-ijms-25-11958" class="html-bibr">91</a>].</p>
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7 pages, 5943 KiB  
Case Report
The First Case of Schaumann Bodies in Pediatric Very Early Onset Crohn’s Disease: Case Report and Literature Review
by Jovan Jevtić, Miloš Đuknić, Nevena Popovac, Nina Ristić, Ivan Milovanovich, Milica Radusinović, Irena Đordjić, Ljubica Simić, Gorana Nikolić, Maja Životić, Ana Mioljević, Nikola Bogosavljević and Radmila Janković
Children 2024, 11(10), 1216; https://doi.org/10.3390/children11101216 - 6 Oct 2024
Viewed by 806
Abstract
Crohn’s disease (CD) is a chronic inflammatory bowel condition with increasing global incidence. Diagnosing CD is challenging and requires close collaboration between clinicians and pathologists due to the lack of specific diagnostic criteria. Histologically, CD is characterized by transmural inflammation, crypt distortion, metaplasia, [...] Read more.
Crohn’s disease (CD) is a chronic inflammatory bowel condition with increasing global incidence. Diagnosing CD is challenging and requires close collaboration between clinicians and pathologists due to the lack of specific diagnostic criteria. Histologically, CD is characterized by transmural inflammation, crypt distortion, metaplasia, and granulomas, although granulomas are not always present. Schaumann bodies (SB), initially described in sarcoidosis, are rare in CD but have been reported in about 10% of cases. This case report presents a 4-year-old female with chronic hemorrhagic diarrhea, severe anemia, and elevated inflammatory markers. Endoscopic and histological evaluations suggested CD, with the presence of SB in the gastric mucosa. Further investigations ruled out sarcoidosis, confirming a diagnosis of multi-segmental, very early onset CD with atypical histological features. SB are inclusions composed of calcium carbonate crystals and conchoid bodies, typically found within giant cells. The presence of SB in the mucosa is rare, limiting their diagnostic significance in endoscopic biopsies. Differential diagnosis should exclude other granulomatous diseases such as intestinal tuberculosis and sarcoidosis. This case highlights the importance of considering SB in the diagnosis of CD, particularly in pediatric patients. Full article
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<p>Endoscopic findings: (<b>A</b>)—Normal stomach; (<b>B</b>)—Ulceration in the terminal ileum (arrow); (<b>C</b>,<b>D</b>)—Numerous aphthae in the left and right halves of the colon (arrows).</p>
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<p>Histological findings of upper endoscopy: (<b>A</b>)—Macrophage aggregate (arrow), hyperplasia of the basal layer of the epithelium, dilation of intercellular spaces, and infiltration by numerous lymphocytes (asterisk); (<b>B</b>–<b>D</b>)—Granulomas with Langhans-type giant cells containing mixed-type SB in antrum (arrows).</p>
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<p>Histological finding in a biopsy of the corpus: (<b>A</b>)—Langhans-type giant cells containing mixed-type SB (arrow); (<b>B</b>)—SB within the cytoplasm of the giant cell exhibited birefringence after exposure to polarized light (arrow).</p>
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<p>Histological findings of lower endoscopy: (<b>A</b>)—Granuloma in lamina propria of ileum (asterisk); (<b>B</b>)—Granuloma in submucosa of cecum (arrow); (<b>C</b>)—Cryptitis (black arrow) and crypt abscess (red arrow); (<b>D</b>)—Paneth cell metaplasia in distal parts of colon (arrow).</p>
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13 pages, 12170 KiB  
Article
Development of a New Swine Model Resembling Human Empty Nose Syndrome
by Dan Bi Park, David W. Jang, Do Hyun Kim and Sung Won Kim
Medicina 2024, 60(10), 1559; https://doi.org/10.3390/medicina60101559 - 24 Sep 2024
Viewed by 1417
Abstract
Background and Objectives: Empty nose syndrome (ENS) is a debilitating condition that often results from traumatic or iatrogenic causes, such as nasal surgery. There are various conservative and surgical treatments for ENS, but their effectiveness remains uncertain. Therefore, the development of animal models [...] Read more.
Background and Objectives: Empty nose syndrome (ENS) is a debilitating condition that often results from traumatic or iatrogenic causes, such as nasal surgery. There are various conservative and surgical treatments for ENS, but their effectiveness remains uncertain. Therefore, the development of animal models that accurately mimic human ENS is essential for advancing effective treatment strategies. Materials and Methods: To investigate ENS development, turbinoplasty was performed in the nasal cavity of swine, entailing partial removal of the ventral turbinate using turbinectomy scissors followed by electrocauterization. After 56 days, samples were obtained for histological and morphological analyses. Results: A significant reduction in the volume of the ventral turbinate in the ENS model led to an expansion of the nasal cavity. Histological analysis revealed mucosal epithelial changes similar to those observed in ENS patients, including squamous cell metaplasia, goblet cell metaplasia, submucosal fibrosis, and glandular atrophy. Biomarkers related to these histopathological features were identified, and signals potentially contributing to squamous cell metaplasia were elucidated. Conclusions: The swine ENS model is anticipated to be instrumental in unraveling the pathogenesis of ENS and may also be useful for evaluating the effectiveness of various treatments for ENS. Full article
(This article belongs to the Special Issue Update on Otorhinolaryngologic Diseases (2nd Edition))
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<p>Morphology of the nasal cavity following turbinectomy on the swine snout. (<b>a</b>) Overview of the surgical procedure. (<b>b</b>) Endoscopic image of the swine ventral turbinate. (<b>c</b>) Cross-sectional view of the ventral turbinate: control (blue) and ENS after turbinoplasty (red). (<b>d</b>) Lateral view and cross-section of the swine snout. (<b>e</b>) Nasal cavity cross-sections at various locations. (<b>f</b>) Ventral turbinate volume and morphometric index; data are means ± standard deviation (SD) (** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Surface changes in the ventral turbinate in the ENS model. (<b>a</b>,<b>b</b>) Surface images of the ventral turbinate captured by scanning electron microscopy at magnifications of 1000× and 7000×.</p>
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<p>Histological alterations in the epithelium in the ENS model. (<b>a</b>) Cross-sectional images of tissue samples with H and E and MT staining. (<b>b</b>) Tissues were examined at 200× magnification following H and E staining to compare histological features between the control and ENS groups. Arrow indicates squamous cell metaplasia. (<b>c</b>) IHC staining for KRT5 and ΔNp63, examined at 400× magnification. (<b>d</b>) IHC images were compared quantitatively; data are means ± SD (** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>The difference in protein expression in ENS squamous epithelium. (<b>a</b>) Comparison of ΔNp63 and KRT13 co-expression between the two groups using IF staining. (<b>b</b>) IHC images of β-catenin and SOX2. (<b>c</b>) Percentages of stained cells in the epithelium; data are means ± SD (*** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Goblet cell metaplasia was observed in the ENS epithelium. (<b>a</b>) Goblet cell metaplasia (arrows) was observed at 200× magnification following H and E staining. (<b>b</b>,<b>c</b>) Mucin were visualized following Alcian blue staining and plotted as percentages. (<b>d</b>,<b>e</b>) Goblet cell metaplasia was visualized using IHC with MUC5AC at 400× magnification and plotted as numbers of stained cells; data are means ± SD (* <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Histological changes were observed in ENS submucosa. (<b>a</b>) Histological changes in the submucosa were observed at 200× magnification following H and E staining. Arrows and arrowheads indicate submucosal fibrosis and glandular atrophy, respectively. (<b>b</b>,<b>c</b>) Collagen distributions in the submucosa were visualized using MT staining and plotted as means ± SD. (<b>d</b>,<b>e</b>) Submucosal glands (yellow lines) were visualized at 200× magnification following H and E staining, and their sizes were plotted as means ± SD (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
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23 pages, 12352 KiB  
Article
Predicting Regression of Barrett’s Esophagus—Can All the King’s Men Put It Together Again?
by Martin Tobi, Nabiha Khoury, Omar Al-Subee, Seema Sethi, Harvinder Talwar, Michael Kam, James Hatfield, Edi Levi, Jason Hallman, Mary Pat Moyer, Laura Kresty, Michael J. Lawson and Benita McVicker
Biomolecules 2024, 14(9), 1182; https://doi.org/10.3390/biom14091182 - 20 Sep 2024
Cited by 1 | Viewed by 1049
Abstract
The primary pre-neoplastic lesion of the lower esophagus in the vicinity of the gastroesophageal junction (GEJ) is any Barrett’s esophageal lesions (BE), and esophageal neoplasia has increased in the US population with predispositions (Caucasian males, truncal obesity, age, and GERD). The responses to [...] Read more.
The primary pre-neoplastic lesion of the lower esophagus in the vicinity of the gastroesophageal junction (GEJ) is any Barrett’s esophageal lesions (BE), and esophageal neoplasia has increased in the US population with predispositions (Caucasian males, truncal obesity, age, and GERD). The responses to BE are endoscopic and screening cytologic programs with endoscopic ablation of various forms. The former have not been proven to be cost-effective and there are mixed results for eradication. A fresh approach is sorely needed. We prospectively followed 2229 mostly male veterans at high risk for colorectal cancer in a 27-year longitudinal long-term study, collecting data on colorectal neoplasia development and other preneoplastic lesions, including BE and spontaneous regression (SR). Another cross-sectional BE study at a similar time period investigated antigenic changes at the GEJ in both BE glandular and squamous mucosa immunohistochemistry and the role of inflammation. Ten of the prospective cohort (21.7%) experienced SR out of a total of forty-six BE patients. Significant differences between SR and stable BE were younger age (p < 0.007); lower platelet levels (p < 0.02); rectal p87 elevation in SR (p < 0.049); a reduced innate immune system (InImS) FEREFF ratio (ferritin: p87 colonic washings) (p < 0.04). Ancillary testing showed a broad range of neoplasia biomarkers. InImS markers may be susceptible to intervention using commonplace and safe medical interventions and encourage SR. Full article
(This article belongs to the Special Issue Insights of Innate Immunology into Inflammation and Infections)
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Figure 1

Figure 1
<p>(<b>a</b>) Bar diagram of percentages of staining with various antibodies in glandular versus squamous epithelium in Barrett’s esophagus. (<b>b</b>) Bar diagram of percentages of staining with various antibodies in glandular versus squamous epithelium in non-Barrett’s esophagus.</p>
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<p>(<b>a</b>) Percentage staining of squamous nuclei in a Barrett’s esophagus patient with p53 nuclear staining as evidenced by the brown nuclei. Magnification 360×. (<b>b</b>) VEGF staining in a glandular section of a specimen taken from a patient with Barrett’s esophagus. (<b>b</b>) shows moderate brown VEGF staining in the glandular epithelium more localized in the cytoplasm (arrows indicate glands and staining). Magnification 50×. (<b>c</b>) Cox2 staining is seen from a section taken through the GEJ in a section taken from a patient with Barrett’s esophagus. Magnification 50×. (<b>d</b>) COX-2 staining in the squamous epithelium is moderate diffuse and cytoplasmic. Magnification 130×. The intensity of stain was 3+ in the areas on the left and 1–2+ on the right. (<b>e</b>) Adnab-9 staining of a section taken from the GEJ of a patient with confirmed Barrett’s esophagus. Esophagus. Magnification 50×. (<b>f</b>) shows Adnab-9 labeling of squamous cells in a patient with Barrett’s esophagus focally with reticulated cytoplasmic staining at a higher power. Magnification 360×. (<b>g</b>) Tn staining of glandular mucosa in a patient with Barrett’s esophagus. Magnification 50×. (<b>h</b>) Intense nuclear CDX2 staining is seen in this section of Barrett’s epithelium and involves most of the glandular epithelium in this section. Magnification 125×.</p>
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<p>(<b>a</b>) Percentage staining of squamous nuclei in a Barrett’s esophagus patient with p53 nuclear staining as evidenced by the brown nuclei. Magnification 360×. (<b>b</b>) VEGF staining in a glandular section of a specimen taken from a patient with Barrett’s esophagus. (<b>b</b>) shows moderate brown VEGF staining in the glandular epithelium more localized in the cytoplasm (arrows indicate glands and staining). Magnification 50×. (<b>c</b>) Cox2 staining is seen from a section taken through the GEJ in a section taken from a patient with Barrett’s esophagus. Magnification 50×. (<b>d</b>) COX-2 staining in the squamous epithelium is moderate diffuse and cytoplasmic. Magnification 130×. The intensity of stain was 3+ in the areas on the left and 1–2+ on the right. (<b>e</b>) Adnab-9 staining of a section taken from the GEJ of a patient with confirmed Barrett’s esophagus. Esophagus. Magnification 50×. (<b>f</b>) shows Adnab-9 labeling of squamous cells in a patient with Barrett’s esophagus focally with reticulated cytoplasmic staining at a higher power. Magnification 360×. (<b>g</b>) Tn staining of glandular mucosa in a patient with Barrett’s esophagus. Magnification 50×. (<b>h</b>) Intense nuclear CDX2 staining is seen in this section of Barrett’s epithelium and involves most of the glandular epithelium in this section. Magnification 125×.</p>
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<p>(<b>a</b>) Percentage staining of squamous nuclei in a Barrett’s esophagus patient with p53 nuclear staining as evidenced by the brown nuclei. Magnification 360×. (<b>b</b>) VEGF staining in a glandular section of a specimen taken from a patient with Barrett’s esophagus. (<b>b</b>) shows moderate brown VEGF staining in the glandular epithelium more localized in the cytoplasm (arrows indicate glands and staining). Magnification 50×. (<b>c</b>) Cox2 staining is seen from a section taken through the GEJ in a section taken from a patient with Barrett’s esophagus. Magnification 50×. (<b>d</b>) COX-2 staining in the squamous epithelium is moderate diffuse and cytoplasmic. Magnification 130×. The intensity of stain was 3+ in the areas on the left and 1–2+ on the right. (<b>e</b>) Adnab-9 staining of a section taken from the GEJ of a patient with confirmed Barrett’s esophagus. Esophagus. Magnification 50×. (<b>f</b>) shows Adnab-9 labeling of squamous cells in a patient with Barrett’s esophagus focally with reticulated cytoplasmic staining at a higher power. Magnification 360×. (<b>g</b>) Tn staining of glandular mucosa in a patient with Barrett’s esophagus. Magnification 50×. (<b>h</b>) Intense nuclear CDX2 staining is seen in this section of Barrett’s epithelium and involves most of the glandular epithelium in this section. Magnification 125×.</p>
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<p>(<b>a</b>) Percentage staining of squamous nuclei in a Barrett’s esophagus patient with p53 nuclear staining as evidenced by the brown nuclei. Magnification 360×. (<b>b</b>) VEGF staining in a glandular section of a specimen taken from a patient with Barrett’s esophagus. (<b>b</b>) shows moderate brown VEGF staining in the glandular epithelium more localized in the cytoplasm (arrows indicate glands and staining). Magnification 50×. (<b>c</b>) Cox2 staining is seen from a section taken through the GEJ in a section taken from a patient with Barrett’s esophagus. Magnification 50×. (<b>d</b>) COX-2 staining in the squamous epithelium is moderate diffuse and cytoplasmic. Magnification 130×. The intensity of stain was 3+ in the areas on the left and 1–2+ on the right. (<b>e</b>) Adnab-9 staining of a section taken from the GEJ of a patient with confirmed Barrett’s esophagus. Esophagus. Magnification 50×. (<b>f</b>) shows Adnab-9 labeling of squamous cells in a patient with Barrett’s esophagus focally with reticulated cytoplasmic staining at a higher power. Magnification 360×. (<b>g</b>) Tn staining of glandular mucosa in a patient with Barrett’s esophagus. Magnification 50×. (<b>h</b>) Intense nuclear CDX2 staining is seen in this section of Barrett’s epithelium and involves most of the glandular epithelium in this section. Magnification 125×.</p>
Full article ">Figure 2 Cont.
<p>(<b>a</b>) Percentage staining of squamous nuclei in a Barrett’s esophagus patient with p53 nuclear staining as evidenced by the brown nuclei. Magnification 360×. (<b>b</b>) VEGF staining in a glandular section of a specimen taken from a patient with Barrett’s esophagus. (<b>b</b>) shows moderate brown VEGF staining in the glandular epithelium more localized in the cytoplasm (arrows indicate glands and staining). Magnification 50×. (<b>c</b>) Cox2 staining is seen from a section taken through the GEJ in a section taken from a patient with Barrett’s esophagus. Magnification 50×. (<b>d</b>) COX-2 staining in the squamous epithelium is moderate diffuse and cytoplasmic. Magnification 130×. The intensity of stain was 3+ in the areas on the left and 1–2+ on the right. (<b>e</b>) Adnab-9 staining of a section taken from the GEJ of a patient with confirmed Barrett’s esophagus. Esophagus. Magnification 50×. (<b>f</b>) shows Adnab-9 labeling of squamous cells in a patient with Barrett’s esophagus focally with reticulated cytoplasmic staining at a higher power. Magnification 360×. (<b>g</b>) Tn staining of glandular mucosa in a patient with Barrett’s esophagus. Magnification 50×. (<b>h</b>) Intense nuclear CDX2 staining is seen in this section of Barrett’s epithelium and involves most of the glandular epithelium in this section. Magnification 125×.</p>
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<p>(<b>a</b>) Percentage staining of squamous nuclei in a Barrett’s esophagus patient with p53 nuclear staining as evidenced by the brown nuclei. Magnification 360×. (<b>b</b>) VEGF staining in a glandular section of a specimen taken from a patient with Barrett’s esophagus. (<b>b</b>) shows moderate brown VEGF staining in the glandular epithelium more localized in the cytoplasm (arrows indicate glands and staining). Magnification 50×. (<b>c</b>) Cox2 staining is seen from a section taken through the GEJ in a section taken from a patient with Barrett’s esophagus. Magnification 50×. (<b>d</b>) COX-2 staining in the squamous epithelium is moderate diffuse and cytoplasmic. Magnification 130×. The intensity of stain was 3+ in the areas on the left and 1–2+ on the right. (<b>e</b>) Adnab-9 staining of a section taken from the GEJ of a patient with confirmed Barrett’s esophagus. Esophagus. Magnification 50×. (<b>f</b>) shows Adnab-9 labeling of squamous cells in a patient with Barrett’s esophagus focally with reticulated cytoplasmic staining at a higher power. Magnification 360×. (<b>g</b>) Tn staining of glandular mucosa in a patient with Barrett’s esophagus. Magnification 50×. (<b>h</b>) Intense nuclear CDX2 staining is seen in this section of Barrett’s epithelium and involves most of the glandular epithelium in this section. Magnification 125×.</p>
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<p>Linear correlation diagram shows an expected positive relationship between mild and significant dysplasia in BE Patients with diabetes mellitus.</p>
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<p>A bar diagram showing no significant differences of Hp in BE.</p>
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<p>A bar diagram showing the proportional effects of the FERAD ratio in those with and without BE.</p>
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<p>A bar diagram showing higher mean p87 in the colonic effluent of regressed Barrett’s epithelium patients as opposed to stable patients.</p>
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<p>A bar diagram showing the higher level of native p87 in the ascending colon of patients with regressed BE as compared to those with lower levels.</p>
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<p>A bar diagram showing a significantly lower platelet count in the patients with BE regression.</p>
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<p>Effect of turmeric ingestion, followed by influenza vaccination, on fecal p87.</p>
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<p>A bar diagram shows that a daily dose of 5 mg folate significantly reduces stool p87.</p>
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<p>Adnab-9 is pH Indifferent (<b>A</b>). Early Response of pp38ɣ (<b>B</b>). 30 min pp38 Mab response (<b>C</b>). Anti-ppERK Response (<b>D</b>). Western blot of NCM460 cell lines exposed to different pH levels for 1 h, stained for BGP using the CEACAM1 monoclonal (<b>E</b>).</p>
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<p>A bar diagram with percentage staining of antibodies used.</p>
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<p>Stylized putative pathway leading to EAC in BE and regression.</p>
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17 pages, 6852 KiB  
Article
Predictive Neuromarker Patterns for Calcification Metaplasia in Early Tendon Healing
by Melisa Faydaver, Valeria Festinese, Oriana Di Giacinto, Mohammad El Khatib, Marcello Raspa, Ferdinando Scavizzi, Fabrizio Bonaventura, Valentina Mastrorilli, Paolo Berardinelli, Barbara Barboni and Valentina Russo
Vet. Sci. 2024, 11(9), 441; https://doi.org/10.3390/vetsci11090441 - 19 Sep 2024
Viewed by 1084
Abstract
Unsuccessful tendon healing leads to fibrosis and occasionally calcification. In these metaplastic drifts, the mouse AT preclinical injury model represents a robust experimental setting for studying tendon calcifications. Previously, calcium deposits were found in about 30% of tendons after 28 days post-injury. Although [...] Read more.
Unsuccessful tendon healing leads to fibrosis and occasionally calcification. In these metaplastic drifts, the mouse AT preclinical injury model represents a robust experimental setting for studying tendon calcifications. Previously, calcium deposits were found in about 30% of tendons after 28 days post-injury. Although a neuromediated healing process has previously been documented, the expression patterns of NF200, NGF, NPY, GAL, and CGRP in mouse AT and their roles in metaplastic calcific repair remain to be explored. This study included a spatiotemporal analysis of these neuromarkers during the inflammatory phase (7 days p.i.) and the proliferative/early-remodelling phase (28 days p.i.). While the inflammatory phase is characterised by NF200 and CGRP upregulation, in the 28 days p.i., the non-calcified tendons (n = 16/24) showed overall NGF, NPY, GAL, and CGRP upregulation (compared to 7 days post-injury) and a return of NF200 expression to values similar to pre-injury. Presenting a different picture, in calcified tendons (n = 8), NF200 persisted at high levels, while NGF and NPY significantly increased, resulting in a higher NPY/CGRP ratio. Therefore, high levels of NF200 and imbalance between vasoconstrictive (NPY) and vasodilatory (CGRP) neuromarkers may be indicative of calcification. Tendon cells contributed to the synthesis of neuromarkers, suggesting that their neuro-autocrine/paracrine role is exerted by coordinating growth factors, cytokines, and neuropeptides. These findings offer insights into the neurobiological mechanisms of early tendon healing and identify new neuromarker profiles predictive of tendon healing outcomes. Full article
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Figure 1
<p>Illustrative images of the tendon injury in the mouse AT model. (<b>1.</b>) The tendon was identified, exposed, and isolated from adjacent tissues. (<b>2.</b>) A controlled lesion, not exceeding 50% of the total tendon diameter, was created at the mid-length of the tendon using a scalpel blade. The images were obtained using a stereomicroscope during the surgical procedure.</p>
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<p>Example of a detailed large-format image representing an injured tendon tissue in high resolution. The quantification analysis was conducted in a defined area of 1.8 mm<sup>2</sup> (length × width: 3 mm × 0.6 mm), and the myotendinous junction (Mj) and the enthesis (Ee) were not considered. Large images (LIs) were acquired using the Timelapse Nikon fluorescent microscope at 4× magnification, and then 12 detailed images within the considered area were taken of each tendon in the analysed area at 40× magnification. Scale bar = 500 µm.</p>
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<p>Representative large images (LIs) of the entire mouse ATs stained with H-E for histological analysis. (<b>A</b>) Healthy tendons and (<b>B</b>) samples after 7 days post-surgery and (<b>C</b>) 28 days post-surgery. The squares in each sample represent the position of the detailed image with magnification (right). The detailed images show the cellularity and fibre disposition in that area. LI scale bar = 500 µm. Magnified image scale bar = 50 µm.</p>
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<p>Representative images of Alcian Blue staining obtained from tendons at 28 days p.i. The staining in image (<b>A</b>) (scale bar = 500 μm—10×) shows the positivity to Alcian Blue in the tendon, and (<b>B</b>) shows a detailed 20× image of the chondrocyte-like cells within spontaneously healed tendons (scale bar = 50 μm). The positivity is visible as a bright blue staining surrounding the chondrocyte-like cells in the ECM, where proteoglycans are released.</p>
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<p>Representative images of Alizarin Red staining showing (<b>A</b>) calcium deposits within the tendon tissue at 28 days p.i. and surrounding the nuclei (arrow). Scale bar = 250 µm. (<b>B</b>) The presence of calcium deposits arranged around the chondrocyte-like cells. Scale bar = 100 µm.</p>
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<p>Exemplary LI images of samples showing the neuromarker distribution in healthy, 7-day and 28-day tendons. For the 28-day time point, only calcified samples are shown as an example. In the healthy tendon (left), positivity can be observed concentrated in the paratenon and endotenon, whereas, in the rest of the images, fluorescence expression can be observed in the tendon proper. Scale bar = 200 µm. Green channel (AlexaFluor 488) represents the each analysed neuromarker, whereas the nuclei are stained with DAPI (blue).</p>
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<p>Neuromarker double IF co-staining TNMD in healthy tendons and the various stages of tendon healing (7 days, 28 days non-calcified and 28 days calcified samples). Tenocyte positivity using double staining with TNMD (red channel—CY3) together with the individual neuromarkers’ staining (green channel—AlexaFluor 488) can be observed. When the markers proved to be co-localised, orange fluorescence was evident. Scale bar = 25 µm. The green channel (Alexa Fluor 488) represents each analysed neuromarker, and the red channel (Cy3) was used for TNMD, whereas the nuclei were stained with DAPI (blue fluorescence).</p>
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<p>Double IF staining of each analysed neuromarker together with TNMD in chondrocyte-like cells. These images show a high positivity level in chondrocyte-like cells for both TNMD and each neuromarker. Moreover, there is a high intra-cellular positivity, as well as ECM positivity. Scale bar = 50 µm. The green channel (AlexaFluor 488) represents each analysed neuromarker, and red (cy3) is for TNMD, whereas the nuclei are stained with DAPI (blue).</p>
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<p>Graphical representation of the average fluorescence intensity (aFI) of each analysed sample. (<b>A</b>) aFI from healthy vs. 7 days vs. 28 days non-calcified p.i.; (<b>B</b>) 28 days p.i. non-calcified vs. calcified tissues normalised to the healthy tendon sample. In the statistical analysis, significance was expressed in * (<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), **** (<span class="html-italic">p</span> &lt; 0.0001). Each sample was compared with the others.</p>
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