Gene Reports最新文献

{"title":"Profiling of biomarker gene expression pattern in upper GI cancer in southern India","authors":"Laxmi R. Patil ,&nbsp;Naveen Shankarappa Gowda ,&nbsp;Rohit N. Maidur ,&nbsp;Palaksha Kanive Javaregowda ,&nbsp;Mallikarjun Goni ,&nbsp;Murigendra.B. Hiremath ,&nbsp;Renukaradhya K. Math","doi":"10.1016/j.genrep.2025.102305","DOIUrl":"10.1016/j.genrep.2025.102305","url":null,"abstract":"<div><div>Upper gastrointestinal (GI) cancers, including esophageal (EC) and gastric (GC), are highly lethal due to late diagnosis and limited biomarker-driven treatments. This study aimed to assess the expression profiles of selected cancer-associated genes E-cadherin, EGFR, HER2, Ki67, KIF2C, TP53, and PD-L1 in south Indian upper GI cancer patients using qRT-PCR. Gene expression patterns were analysed alongside clinical data and bacterial profiling. The study revealed the upper GI cancer subtype-specific variation in the gene expression pattern. In EC, E-cadherin was variably altered (−4.2 ± 2.3), while EGFR and HER2 showed overall downregulation with interpatient variability. Ki67 (3.4 ± 2.7), KIF2C (3.9 ± 2.9), TP53 (2.7 ± 2.4), and PD-L1 (2.7 ± 2.4) were generally upregulated, indicating enhanced proliferation, genomic instability, and immune modulation. Conversely, GC showed consistent downregulation of all seven genes, suggesting widespread transcriptional suppression and potential immune evasion. Correlation analysis revealed, Ki67-KIF2C and HER2-TP53-E-cadherin emerged as strongly co-expressed gene pairs, hinting coordinated tumor regulation mechanisms. ROC analysis highlighted KIF2C and TP53 as potential diagnostic markers, particularly in EC. Fecal bacterial analysis revealed increased diplococci, notably in GC patients. Clinicopathological correlations showed gene expression variations linked to age, diet, tumor site, and bowel habits. EC reflects active proliferation and immune interaction, whereas GC shows generalized gene suppression. KIF2C and TP53 could be potential diagnostic markers. Findings emphasize the value of integrated molecular and clinical profiling in advancing precision diagnostics for upper GI cancers. Further validation in larger, independent cohorts of multiple sites along with protein-level and functional studies is warranted to confirm the diagnostic utility and biological relevance of the identified biomarkers.</div></div>","PeriodicalId":12673,"journal":{"name":"Gene Reports","volume":"40 ","pages":"Article 102305"},"PeriodicalIF":1.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144696618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differences in gastrointestinal metabolites in different breeds of yak revealed by combined multi-omics analysis","authors":"Yang Gao ,&nbsp;Xueyi Jing ,&nbsp;Wangdui Basang ,&nbsp;Xuelong Yu ,&nbsp;Nan Jiang ,&nbsp;Liang Hong","doi":"10.1016/j.genrep.2025.102301","DOIUrl":"10.1016/j.genrep.2025.102301","url":null,"abstract":"<div><div>In this study, we systematically analyzed the microbial composition of the gastrointestinal tract and its metabolite differences between Niangya yaks and Sibu yaks by non-targeted metabolomics technology combined with 16S rDNA sequencing, aiming at providing theoretical references for yak breed selection, precision breeding, and healthy breeding. The results showed that the abundance of <em>Solibacillus</em> was higher in the gastrointestinal tract of the Sibu yak, while the abundance of <em>Christensenellaceae</em>_R-7_group, <em>Prevotella</em>, <em>Candidatus_Saccharimonas</em> and <em>Lysinibacillus</em> was higher in the Niangya yak. Metabolomics results showed that metabolites such as <em>N</em>-methyl-d-aspartic acid and L-homoserine were up-regulated in the rumen of Niangya yaks, and metabolites such as Val-Ala-lys and 2,4-dihydroxybenzophenone were up-regulated in the Sibu yaks. Metabolites such as Proscillaridin_a, 2-cis-4-trans-abscisic acid, and <em>N</em>-acetyl-d-galactosaminitol were up-regulated in the intestines of the Niangya yak group compared to the intestines of the Sibu yak group. Correlation analysis showed that L-homoserine was significantly and positively correlated with <em>Christensenellaceae</em>_R-7_group, <em>Candidatus_Saccharimonas</em>, <em>Prevotella</em> and <em>Solibacillus</em> (<em>P &lt; 0.05</em>). N-methyl-d-aspartic acid was significantly positively correlated with <em>Solibacillus</em>, <em>Christensenellaceae</em>_R-7_group, <em>Candidatus_ Saccharimonas</em> were significantly positively correlated (<em>P &lt; 0.05</em>). <em>Lysinibacillus</em> was significantly positively correlated with Proscillaridin_a, 2-cis-4-trans-abscisic _acid were significantly positively correlated (<em>P &lt; 0.05</em>). These results suggest that different yak breeds may influence host growth performance, nutrient utilization efficiency and health status through their unique microbial-metabolite interaction networks.</div></div>","PeriodicalId":12673,"journal":{"name":"Gene Reports","volume":"40 ","pages":"Article 102301"},"PeriodicalIF":1.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144702657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of fish diversity using DNA barcoding from the Beas River in Himachal Pradesh for conservation and sustainable management","authors":"Kushal Thakur ,&nbsp;Amit Kumar Sharma ,&nbsp;Dixit Sharma ,&nbsp;Chander Mohan Singh Bist ,&nbsp;Danish Mahajan ,&nbsp;Sunil Kumar ,&nbsp;Rajinder Jindal ,&nbsp;Rakesh Kumar","doi":"10.1016/j.genrep.2025.102300","DOIUrl":"10.1016/j.genrep.2025.102300","url":null,"abstract":"<div><div>Beas River is one of the major rivers in Himachal Pradesh, frequently impacted by flash floods in the upper reaches, causing biodiversity loss. DNA barcoding using the cytochrome <em>c</em> oxidase I (COI) gene is widely used in assessing biodiversity and species identification. The current study represents the identification of fish fauna using the COI gene sequences in the Beas River basin in Himachal Pradesh. A total of 69 barcodes were generated, and molecular-based identification approaches such as Barcode Index Number, Automatic Barcode Gap Discovery were also employed. Along with molecular identification, biometric characters, including total length and meristic characters, were also measured for the observed species. In the present study, 35 fish species belonging to 27 genera, 10 orders, and 14 families were identified through DNA Barcoding using the 69 partial sequences of the mitochondrial COI gene. Out of 35 fish species, 3 species were Vulnerable, 1 species was Near Threatened, and 1 Endangered species was reported. Barcode sequence similarity of approximately all sequences was found to be 98–100 % identical with NCBI GenBank and BOLD system. The mean K2P genetic divergence from within species, within genera, within families and within orders were 0.50 %, 1.30 %, 5.80 %, and 8.20 %. A Maximum likelihood (ML) tree was also constructed, and all species revealed a distinct separation among the ten orders and fourteen families. The results of current study will aid other researchers in species identification and policymakers in formulating strategies for sustainable biodiversity management and conservation in Himachal Pradesh, Northern India.</div></div>","PeriodicalId":12673,"journal":{"name":"Gene Reports","volume":"40 ","pages":"Article 102300"},"PeriodicalIF":1.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144702658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Anoxia-responsive microRNA profile of freshwater turtle red skeletal muscle","authors":"Tighe Bloskie,&nbsp;Kenneth B. Storey","doi":"10.1016/j.genrep.2025.102302","DOIUrl":"10.1016/j.genrep.2025.102302","url":null,"abstract":"<div><div>The red-eared slider (<em>Trachemys scripta elegans</em>) is a uniquely impressive vertebrate facultative anaerobe, capable of 18 weeks without oxygen at 3 °C. Metabolic rate depression (∼85 %) is the core feature of anaerobiosis and is characterized by the suppression of costly processes like protein synthesis/decay and the cell cycle. The elucidation of microRNA (miRNA) action in support of animal extreme stress adaptation is increasing, but is currently lacking in <em>T.s. elegans</em> anoxia tolerance. Here, we use small RNA sequencing and subsequent bioinformatic analyses to identify differentially expressed miRNA and predicted target pathways in 20 h anoxic red skeletal muscle of red-eared slider turtles. Of the 52 mapped miRNA species, we identify two that were upregulated (miR-2114-5p, let-7f-5p) and two that were downregulated (miR-1260b, miR-5100) under 20 h anoxic conditions (|FC| &gt; 1.5; <em>p</em> &lt; 0.05). KEGG and GO analysis predict miRNA contribute to the aerobic to anaerobic respiration shift and outline miRNA-mediated inhibition of numerous gene sets in (1) protein turnover, (2) RNA turnover and (3) the cell cycle. Conversely, alleviated miRNA interference in branched amino acid biosynthesis, arachidonic acid and linolenic acid metabolism suggest a role in atrophy resistance of skeletal muscles.</div></div>","PeriodicalId":12673,"journal":{"name":"Gene Reports","volume":"40 ","pages":"Article 102302"},"PeriodicalIF":1.0,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification and characterization of heat shock protein 90 in Cyclina sinensis and its function under thermal and Vibrio parahaemolyticus infection","authors":"Dehui Sun ,&nbsp;Lisha Wei ,&nbsp;Ruyan Yi ,&nbsp;Yujuan Hong ,&nbsp;Yuwei Wang ,&nbsp;Wenwen Dong ,&nbsp;Fengjuan Jiang ,&nbsp;Qing Nie ,&nbsp;Xiuke Ouyang","doi":"10.1016/j.genrep.2025.102303","DOIUrl":"10.1016/j.genrep.2025.102303","url":null,"abstract":"<div><div>HSP90 is a member of heat shock protein superfamily and plays an important role in response to various stressors. In this study, we identified the CsHSP90 from genomic databases of <em>Cyclina sinensis</em>. The full length of the <em>CsHSP90</em> coding sequence (CDS) was 2184 bp and coding 727 amino acids with an estimated molecular mass of 83.67 kDa and isoelectric point of 4.85. The analysis result showed that CsHSP90 was a predicted hydrophilic protein and mainly localized in the cytoplasm. The results of motif analysis, three-dimensional structural modeling and amino acid sequence alignment suggested that HSP90 were highly conserved. Phylogenetic analysis indicated that CsHSP90 was clustered with HSP90s of Bivalve. The qRT-PCR analysis results showed that <em>CsHSP90</em> was detected in all the tissue and primarily expressed in the adductor. The expression was increased under high temperature stress and <em>Vibrio parahaemolyticus</em> infection. These results accumulate basic data for revealing the molecular function of <em>CsHsp90</em> in stress response.</div></div>","PeriodicalId":12673,"journal":{"name":"Gene Reports","volume":"40 ","pages":"Article 102303"},"PeriodicalIF":1.0,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring changes in metabolites and fecal microbiota of I, II, and III thyroid cancer patients based on metabolomics and 16S rDNA sequencing","authors":"Xiang Ao","doi":"10.1016/j.genrep.2025.102304","DOIUrl":"10.1016/j.genrep.2025.102304","url":null,"abstract":"<div><h3>Background</h3><div>Understanding the alterations in fecal microbiota and metabolites across different stages of thyroid cancer may provide valuable insights into the disease progression and potential biomarkers for clinical application.</div></div><div><h3>Objective</h3><div>This study aims to investigate the alterations in fecal microbiota and metabolites in stage I, II, and III thyroid cancer patients using metabolomics and 16S rDNA sequencing techniques.</div></div><div><h3>Methods</h3><div>We conducted a comprehensive study to investigate the alterations in fecal microbiota and metabolites in stage I, II, and III thyroid cancer patients using metabolomics and 16S rDNA sequencing techniques.</div></div><div><h3>Results</h3><div>Our results revealed notable shifts in the microbial community structure. Specifically, the abundance of agathobacter was significantly higher in stage I patients compared to those in stages II and III. Furthermore, our comprehensive metabolomic analysis identified 219 differentially expressed metabolites (DEMs) between stage I and II thyroid cancer patients, with four metabolites up-regulated and 215 down-regulated in stage II. Through ROC curve analysis, we identified two potential biomarkers: 5-Aminoimidazole (AUC: 0.815) and (<em>R</em>)-5-Diphosphomevalonic acid (AUC: 0.759), which have the potential to distinguish between patients with stage I and stage II thyroid cancer. In the comparison between stages I and III patients, the majority of DEMs were significantly down-regulated in stage III, with 12 metabolites up-regulated and 217 down-regulated. Potential biomarkers between stage I and stage III patients included Gaboxadol, Oxiracetam, N-Nitroso-3-hydroxypyrrolidine, N6-(L-1,3-Dicarboxypropyl)-<span>l</span>-lysine, and 3-Ethyl-4-methylphenol, with AUC values significantly greater than 0.85. In the comparison between stage II and III patients, a total of 86 DEMs were identified, with the majority downregulated in stage III. Key biomarkers distinguishing stage II and stage III patients were Glutathionylaminopropylcadaverine, lle-Ala-Arg, Tridecanal, and Pregnenolone, identified through ROC analysis with AUC values greater than 0.85.</div></div><div><h3>Conclusion</h3><div>These findings underscore the complex interplay between the gut microbiota, metabolites, and thyroid cancer progression and pave the way for a new era of personalized medicine in thyroid cancer management, offering hope for more effective and targeted treatment approaches.</div></div>","PeriodicalId":12673,"journal":{"name":"Gene Reports","volume":"40 ","pages":"Article 102304"},"PeriodicalIF":1.0,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144686621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Threat of multidrug resistant bacteria: The role of genomic solutions and a call to action","authors":"Subhasmita Mallik ,&nbsp;Sagarbala Dash ,&nbsp;Snigdha Mishra ,&nbsp;Rushi Brata Mohanty ,&nbsp;Swagatika Sahoo ,&nbsp;Archita Patra ,&nbsp;Swayamprabha Sahoo ,&nbsp;Rukmini Mishra ,&nbsp;Jatindra Nath Mohanty","doi":"10.1016/j.genrep.2025.102298","DOIUrl":"10.1016/j.genrep.2025.102298","url":null,"abstract":"<div><div>The global rise of multidrug-resistant (MDR) bacteria presents a critical threat to public health and the environment, demanding urgent and coordinated international action. The spread of superbugs resistant to multiple antibiotics has severely compromised traditional treatments, resulting in increased mortality, prolonged illness, and escalating healthcare costs. Genomic technologies have emerged as powerful tools to uncover the molecular mechanisms behind antimicrobial resistance (AMR). They enable the identification of resistance genes, detection of novel mutations, and in-depth mapping of bacterial genomes, paving the way for targeted therapies and personalized treatment strategies. However, the implementation of these technologies remains challenging due to high costs, limited infrastructure in low-resource settings, and the need for specialized expertise. This review comprehensively explores the current status of MDR bacteria, examining their health impacts, restricted treatment options, and the global interconnectedness of the AMR crisis. It also emphasizes the importance of the one health approach in addressing MDR from a holistic perspective. Furthermore, cutting-edge genomic innovations, including CRISPR-Cas genome editing, third-generation sequencing and other omics strategies, are discussed as promising avenues for combating MDR pathogens. While these technologies offer transformative potential, global collaboration, regulatory oversight, and equitable access are essential to fully realize their benefits. By harnessing genomic data, researchers and healthcare providers can move towards more precise diagnostics, new antimicrobial agents, and sustainable solutions to antibiotic resistance.</div></div>","PeriodicalId":12673,"journal":{"name":"Gene Reports","volume":"41 ","pages":"Article 102298"},"PeriodicalIF":1.0,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144713625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decoding the tumor-suppressive mechanisms of NDRG family genes in colon cancer","authors":"Xia Weng ,&nbsp;Jiyun Zhu ,&nbsp;Xiaoshuai Zhou","doi":"10.1016/j.genrep.2025.102295","DOIUrl":"10.1016/j.genrep.2025.102295","url":null,"abstract":"<div><h3>Background</h3><div>The NDRG family regulates biological processes in various cancers, but its mechanistic role in colon adenocarcinoma (COAD) remains unclear.</div></div><div><h3>Methods</h3><div>Through multi-omics analysis, we evaluated the expression profiles of NDRG family members across pan-cancer and COAD contexts, including genomic correlations (TMB, MSI), clinical prognosis, protein interactions, and immune infiltration. Key tumor-suppressive functions and downstream pathways were validated via in vitro experiments.</div></div><div><h3>Results</h3><div>NDRG family genes were generally downregulated in tumors, showing negative correlations with TMB and MSI (<em>P</em> &lt; 0.05), indicative of tumor-suppressive roles. Notably, NDRG4 was significantly downregulated in COAD and positively correlated with T/B cell subtypes and dendritic cell infiltration (<em>r</em> = 0.32–0.45). Functional experiments demonstrated that NDRG4 overexpression suppressed tumor growth and metastasis by inhibiting nitrogen metabolism pathways (KEGG enrichment <em>P</em> = 1.2 × 10⁻⁵). Synergistic inhibition of PBK enhanced antitumor efficacy (68 % reduction in proliferation).</div></div><div><h3>Conclusion</h3><div>This study provides the first comprehensive elucidation of the tumor-suppressive and immune-modulatory roles of the NDRG family (particularly NDRG4) in COAD, identifying NDRG4 as a potential therapeutic target and prognostic biomarker.</div></div>","PeriodicalId":12673,"journal":{"name":"Gene Reports","volume":"40 ","pages":"Article 102295"},"PeriodicalIF":1.0,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144702656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic susceptibility to severe COVID-19 in men: The impact of androgen receptor CAG repeat length","authors":"Arsalan Eskandarinezhad ,&nbsp;Asra Moradkhani ,&nbsp;Mobin Azami ,&nbsp;Efat Shafiei ,&nbsp;Sabah Hasani ,&nbsp;Abbas Aghaei ,&nbsp;Nariman Moradi ,&nbsp;Shahnaz Ghafouri ,&nbsp;Naseh Sigari ,&nbsp;Asaad Azarnezhad","doi":"10.1016/j.genrep.2025.102299","DOIUrl":"10.1016/j.genrep.2025.102299","url":null,"abstract":"","PeriodicalId":12673,"journal":{"name":"Gene Reports","volume":"41 ","pages":"Article 102299"},"PeriodicalIF":0.9,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144750837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"scCAM: An explainable method to annotate scRNA-seq data and identify annotation-related genes based on residual network and layer class activation maps","authors":"Ya Zhang ,&nbsp;Yongzhao Du ,&nbsp;Yuqing Fu","doi":"10.1016/j.genrep.2025.102297","DOIUrl":"10.1016/j.genrep.2025.102297","url":null,"abstract":"<div><div>Single-cell RNA sequencing (scRNA-seq) has been widely used to explore gene expression and cellular heterogeneity. Cell type annotation is a crucial step in the scRNA-seq data analysis. Recently, several deep learning methods have been developed for cell annotation. However, most existing methods lack biological explainability and fail to discover key genes related to annotation. Therefore, we propose an explainable automatic cell annotation method: scCAM. Our method combines residual networks and layer class activation maps, constructs grayscale images to represent gene expression, and utilizes backward class-specific gradients and the spatial location importance to explore the cell annotation decision-making processes and discover annotation-related genes. We performed experiments on benchmark datasets in multiple situations, the experimental results show that scCAM outperforms other state-of-the-art methods, especially on the large-scale dataset, exceeds other methods by 6.4 %, 18 %, 39.2 %, 16.5 % and 9.8 % on the accuracy, respectively. Explainable analysis on the Segerstolpe pancreas dataset successfully identifies annotation-related genes including marker genes and differentially expressed genes, provides reference and support for the discovery of new marker genes. The source code of scCAM is available at <span><span>https://github.com/zhangya10956/scCAM-cell-anno</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":12673,"journal":{"name":"Gene Reports","volume":"41 ","pages":"Article 102297"},"PeriodicalIF":0.9,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144771754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}