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Three types of highly promising small RNA therapeutics, namely, small interfering RNAs (siRNAs), microRNAs (miRNAs) and the RNA subtype of antisense oligonucleotides (ASOs), offer advantages over small‐molecule drugs. These small RNAs can target any gene product, opening up new avenues of effective and safe therapeutic approaches for a wide range of diseases. In preclinical research, synthetic small RNAs play an essential role in the investigation of physiological and pathological pathways as silencers of specific genes, facilitating discovery and validation of drug targets in different conditions. Off‐target effects of small RNAs, however, could make it difficult to interpret experimental results in the preclinical phase and may contribute to adverse events of small RNA therapeutics. Out of the two major types of off‐target effects we focused on the hybridization‐dependent, especially on the miRNA‐like off‐target effects. Our main aim was to discuss several approaches, including sequence design, chemical modifications and target prediction, to reduce hybridization‐dependent off‐target effects that should be considered even at the early development phase of small RNA therapy. Because there is no standard way of predicting hybridization‐dependent off‐target effects, this review provides an overview of all major state‐of‐the‐art computational methods and proposes new approaches, such as the possible inclusion of network theory and artificial intelligence (AI) in the prediction workflows. Case studies and a concise survey of experimental methods for validating in silico predictions are also presented. These methods could contribute to interpret experimental results, to minimize off‐target effects and hopefully to avoid off‐target‐related adverse events of small RNA therapeutics. [ABSTRACT FROM AUTHOR]

BACKGROUND: It has been shown that long non-coding RNA (lncRNA) plays an important role in the development and progression of cardiac diseases, and whether it is involved in daisy leaf gentianone antagonizing adriamycin-induced cardiac injury in mice has not been reported. OBJECTIVE: To screen differentially expressed lncRNAs in myocardial tissue of mice with adriamycin-induced myocardial injury antagonized with daisy leaf gentianone and conduct a bioinformatics analysis. METHODS: Forty-eight C57 mice were randomly divided into normal group, model group, daisy leaf gentianone group and positive drug group, with 12 mice in each group. The mice in the model group, daisy leaf gentianone group and positive drug group were injected with adriamycin intraperitoneally once every other day for 8 times in total. The daisy leaf gentianone group and positive drug group were given daisy leaf gentianone suspension and captopril solution by gavage based on adriamycin injection once a day for 21 continuous days. After medication, mice in each group underwent electrocardiogram examination and the myocardial tissue was taken for pathomorphological observation. At the same time, high-throughput sequencing analysis of mouse myocardial tissue was carried out, differentially expressed lncRNAs were screened, and target genes were predicted for differentially expressed lncRNAs. Gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes signaling pathway analyses of target genes were performed. RESULTS AND CONCLUSION: The ST segment of the electrocardiogram of mice in the model group was significantly elevated. Compared with the model group, the degree of ST-segment elevation on the electrocardiogram was reduced in the daisy leaf gentianone group. Results from hematoxylin-eosin, Masson, and Sirius red staining indicated that in the model group, the myocardial cytoplasm was unevenly colored with varying shades of color, the integrity and continuity of myocardial fibers were poor, and a large number of collagen fibers were deposited. After treatment with gentianone daisy leaves, the abnormalities in myocardial tissue of mice were improved. The results of high-throughput sequencing analysis showed that compared with the model group, a total of 270 lncRNAs were identified in the myocardial tissue of mice in the daisy leaf gentianone group, including 165 up-regulated and 105 down-regulated lncRNAs. Combining the experimental results with related literature, three lncRNAs (NONMMUT149833.1, NONMMUT003237.2, and ENSMUST00000219015) and four related mRNAs (Alas2, Igf2, Acta1, and Cilp) were finally identified. The results of target gene prediction, gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes signaling pathway analyses showed that differentially expressed lncRNAs in myocardial tissue of mice with myocardial injury could regulate the expression of their target protein-coding genes through cis- and/or trans-regulation, and participate in regulating molecular functions and biological processes. To conclude, daisy leaf gentianone significantly improves cardiac function and partial lncRNA expression in mice with adriamycin-induced myocardial injury. [ABSTRACT FROM AUTHOR]

Fermented foods are important components of the human diet. There is increasing awareness of abundant nutritional and functional properties present in fermented foods that arise from the transformation of substrates by microbial communities. Thus, it is significant to unravel the microbial communities and mechanisms of characteristic flavor formation occurring during fermentation. There has been rapid development of high-throughput and other omics technologies, such as metaproteomics and metabolomics, and as a result, there is growing recognition of the importance of integrating these approaches. The successful applications of multi-omics approaches and bioinformatics analyses have provided a solid foundation for exploring the fermentation process. Compared with single-omics, multi-omics analyses more accurately delineate microbial and molecular features, thus they are more apt to reveal the mechanisms of fermentation. This review introduces fermented foods and an overview of single-omics technologies – including metagenomics, metatranscriptomics, metaproteomics, and metabolomics. We also discuss integrated multi-omics and bioinformatic analyses and their role in recent research progress related to fermented foods, as well as summarize the main potential pathways involved in certain fermented foods. In the future, multilayered analyses of multi-omics data should be conducted to enable better understanding of flavor formation mechanisms in fermented foods. [ABSTRACT FROM AUTHOR]

Accurate knowledge of the genome, virus and bacteria that have invaded our bodies is crucial for diagnosing many human diseases. The field of bioinformatics encompasses the complex computational methods required for this purpose. Metagenomics employs next-generation sequencing (NGS) technology to study and identify microbial communities in environmental samples. This technique allows for the measurement of the relative abundance of different microbes. Various tools are available for detecting bacterial species in sequenced metagenomic samples. In this study, we focus on well-known taxonomic classification tools such as MetaPhlAn4, Centrifuge, Kraken2, and Bracken, and evaluate their performance at the species level using synthetic and real datasets. The results indicate that MetaPhlAn4 exhibited high precision in identifying species in the simulated dataset, while Kraken2 had the best area under the precision-recall curve (AUPR) performance. Centrifuge, Kraken2, and Bracken showed accurate estimation of species abundances, unlike MetaPhlAn4, which had a higher L2 distance. In the real dataset analysis with samples from an inflammatory bowel disease (IBD) research, MetaPhlAn4, and Kraken2 had faster execution times, with differences in performance at family and species levels among the tools. Enterobacteriaceae and Pasteurellaceae were highlighted as the most abundant families by Centrifuge, Kraken2, and MetaPhlAn4, with variations in abundance among ulcerative colitis (UC), Crohn’s disease (CD), and control non-IBD (CN) groups. Escherichia coli (E. coli) has the highest abundance among Enterobacteriaceae species in the CD and UC groups in comparison with the CN group. Bracken overestimated E. coli abundance, emphasizing result interpretation caution. The findings of this research can assist in selecting the appropriate short-read classifier, thereby aiding in the diagnosis of target diseases. [ABSTRACT FROM AUTHOR]

Introduction: Increasing evidence has indicated a connection between bipolar disorder (BD) and arteriosclerosis (AS), yet the specific molecular mechanisms remain unclear. This study aims to investigate the hub genes and molecular pathways for BD with AS. Methods: BD-related dataset GSE12649 were downloaded from the Gene Expression Omnibus database and differentially expressed genes (DEGs) and key module genes derived from Limma and weighted gene co-expression network analyses (WGCNA) were identified. AS-related genes were sourced from the DisGeNET database, and the overlapping genes between DEGs and AS-related genes were characterized as differentially expressed arteriosclerosis-related genes (DE-ASRGs). The functional enrichment analysis, protein-protein interaction (PPI) network and three machine learning algorithms were performed to explore the hub genes, which were validated with two external validation sets. Additionally, immune infiltration was performed in BD. Results: Overall, 67 DE-ASRGs were found to be overlapping between the DEGs and AS-related genes. Functional enrichment analysis highlighted the cancer pathways between BD and AS. We identified seven candidate hub genes (CTSD, IRF3, NPEPPS, ST6GAL1, HIF1A, SOX9 and CX3CR1). Eventually, two hub genes (CX3CR1 and ST6GAL1) were identified as BD and AS co-biomarkers by using machine learning algorithms. Immune infiltration had revealed the disorder of immunocytes. Discussion: This study identified the hub genes CX3CR1 and ST6GAL1 in BD and AS, providing new insights for further research on the bioinformatic mechanisms of BD with AS and contributing to the diagnosis and prevention of AS in psychiatric clinical practice. [ABSTRACT FROM AUTHOR]

Antarctic krill (Euphausia superba Dana) is a keystone species in the Southern Ocean ecosystem, with ecological and commercial significance. However, its vulnerability to climate change requires an urgent investigation of its adaptive potential to future environmental conditions. Historical museum collections of krill from the early 20th century represent an ideal opportunity to investigate how krill have changed over time due to predation, fishing and climate change. However, there is currently no cost‐effective method for implementing population scale collection genomics for krill given its genome size (48 Gbp). Here, we assessed the utility of two inexpensive methods for population genetics using historical krill samples, specifically low‐coverage shotgun sequencing (i.e. ‘genome‐skimming’) and exome capture. Two full‐length transcriptomes were generated and used to identify 166 putative gene targets for exome capture bait design. A total of 20 historical krill samples were sequenced using shotgun and exome capture. Mitochondrial and nuclear ribosomal sequences were assembled from both low‐coverage shotgun and off‐target of exome capture data demonstrating that endogenous DNA sequences could be assembled from historical collections. Although, mitochondrial and ribosomal sequences are variable across individuals from different populations, phylogenetic analysis does not identify any population structure. We find exome capture provides approximately 4500‐fold enrichment of sequencing targeted genes, suggesting this approach can generate the sequencing depth required to call identify a significant number of variants. Unlocking historical collections for genomic analyses using exome capture, will provide valuable insights into past and present biodiversity, resilience and adaptability of krill populations to climate change. [ABSTRACT FROM AUTHOR]

Sex chromosomes have evolved in many plant species with separate sexes. Current plant research is shifting from examining the structure of sex chromosomes to exploring their functional aspects. New studies are progressively unveiling the specific genetic and epigenetic mechanisms responsible for shaping distinct sexes in plants. While the fundamental methods of molecular biology and genomics are generally employed for the analysis of sex chromosomes, it is often necessary to modify classical procedures not only to simplify and expedite analyses but sometimes to make them possible at all. In this review, we demonstrate how, at the level of structural and functional genetics, cytogenetics, and bioinformatics, it is essential to adapt established procedures for sex chromosome analysis. [ABSTRACT FROM AUTHOR]

Background: Migraine is a highly prevalent and complex neurovascular disease. However, the currently available therapeutic drugs often fall to adequately meet clinical needs due to limited effectiveness and numerous undesirable side effects. This study aims to identify putative novel targets for migraine treatment through proteome-wide Mendelian randomization (MR). Methods: We utilized MR to estimate the causal effects of plasma proteins on migraine and its two subtypes, migraine with aura (MA) and without aura (MO). This analysis integrated plasma protein quantitative trait loci (pQTL) data with genome-wide association studies (GWAS) findings for these migraine phenotypes. Moreover, we conducted a phenome-wide MR assessment, enrichment analysis, protein–protein interaction networks construction, and mediation MR analysis to further validate the pharmaceutical potential of the identified protein targets. Results: We identified 35 protein targets for migraine and its subtypes (p < 8.04 × 10–6), with prioritized targets showing minimal side effects. Phenome-wide MR identified novel protein targets—FCAR, UBE2L6, LATS1, PDCD1LG2, and MMP3—that have no major disease side effects and interacted with current acute migraine medication targets. Additionally, MMP3, PDCD1LG2, and HBQ1 interacted with current preventive migraine medication targets. The causal effects of plasma protein on migraine were partly mediated by plasma metabolites (proportion of mediation from 3.8% to 21.0%). Conclusions: A set of potential protein targets for migraine and its subtypes were identified. These proteins showed rare side effects and were responsible for biological mechanisms involved in migraine pathogenesis, indicating priority for the development of migraine treatments. [ABSTRACT FROM AUTHOR]

Non-alcoholic Fatty Liver Disease (NAFLD), noted for its widespread prevalence among adults, has become the leading chronic liver condition globally. Simultaneously, the annual disease burden, particularly liver cirrhosis caused by NAFLD, has increased significantly. Neutrophil Extracellular Traps (NETs) play a crucial role in the progression of this disease and are key to the pathogenesis of NAFLD. However, research into the specific roles of NETs-related genes in NAFLD is still a field requiring thorough investigation. Utilizing techniques like AddModuleScore, ssGSEA, and WGCNA, our team conducted gene screening to identify the genes linked to NETs in both single-cell and bulk transcriptomics. Using algorithms including Random Forest, Support Vector Machine, Least Absolute Shrinkage, and Selection Operator, we identified ZFP36L2 and PHLDA1 as key hub genes. The pivotal role of these genes in NAFLD diagnosis was confirmed using the training dataset GSE164760. This study identified 116 genes linked to NETs across single-cell and bulk transcriptomic analyses. These genes demonstrated enrichment in immune and metabolic pathways. Additionally, two NETs-related hub genes, PHLDA1 and ZFP36L2, were selected through machine learning for integration into a prognostic model. These hub genes play roles in inflammatory and metabolic processes. scRNA-seq results showed variations in cellular communication among cells with different expression patterns of these key genes. In conclusion, this study explored the molecular characteristics of NETs-associated genes in NAFLD. It identified two potential biomarkers and analyzed their roles in the hepatic microenvironment. These discoveries could aid in NAFLD diagnosis and management, with the ultimate goal of enhancing patient outcomes. [ABSTRACT FROM AUTHOR]

Background and aims: Taohong Siwu Decoction (THSWD) is a traditional Chinese herbal prescription that is effective for ischemic stroke, Whether THSWD regulates the CCL2/CCR2 axis and thus reduces the inflammatory response induced by ischemic stroke is not known. The aim of this study was to elucidate the mechanism of action of THSWD in the treatment of ischemic stroke using bioinformatics combined with in vitro and in vivo experiments. Methods: R language was used to analyze middle cerebral artery occlusion/reperfusion (MCAO/R) rat transcriptome data and to identify differential gene expression following THSWD treatment. Gene set enrichment analysis (GSEA) was used to analyze the gene set enrichment pathway of MCAO/R rats treated with THSWD. PPI networks screened key targets. The Human Brain Microvascular Endothelial Cells (HBMEC) Oxygen Glucose Deprivation/Reoxygenation (OGD/R) model and SD rat models of MCAO/R were established. FITC-dextran, immunofluorescence, flow cytometry, ELISA, immunohistochemistry, Western blotting, and RT-qPCR were performed to identify potential treatment targets. Results: A total of 515 differentially expressed genes of THSWD in MCAO/R rats were screened and 92 differentially expressed genes of THSWD potentially involved in stroke intervention were identified, including Cd68, Ccl2, and other key genes. In vitro, THSWD reversed the increase in permeability of HBMEC cells and M1/M2 polarization of macrophages induced by CCL2/CCR2 axis agonists. In vivo, THSWD improved nerve function injury and blood-brain barrier injury in MCAO/R rats. Further, THSWD inhibited the infiltration and polarization of macrophages, reduced the expression of IL-6, TNF-α, and MMP-9, and increased the expression of IL-4, while reducing the gene and protein expression of CCL2 and CCR2. Conclusion: THSWD may play a protective role in ischemic stroke by inhibiting the CCL2/CCR2 axis, reducing the infiltration of macrophages, and promoting the polarization of M2 macrophages, thereby reducing inflammatory damage, and protecting injury to the blood-brain barrier. [ABSTRACT FROM AUTHOR]

Background: Ameloblastoma and odontogenic keratocyst (OKC) are odontogenic tumors that develop from remnants of odontogenic epithelium. Both display locally invasive growth characteristics and high predilection for recurrence after surgical removal. Most ameloblastomas harbor BRAFV600E mutation while OKCs are associated with PATCH1 gene mutation but distinctive indicators of ameloblastoma growth characteristics relative to OKC are still unclear. The aim of this study was to assess hub genes that underlie ameloblastoma growth characteristics using bioinformatic analysis, ameloblastoma samples and mouse xenografts of human epithelial-derived ameloblastoma cells. Methods: RNA expression profiles were extracted from GSE186489 gene expression dataset acquired from Gene Expression Ominibus (GEO) database. Galaxy and iDEP online analysis tools were used to identify differentially expressed genes that were further characterized by gene ontology (GO) and pathway analysis using ShineyGO. The protein-protein interaction (PPI) network was constructed for significantly upregulated differentially expressed genes using online database STRING. The PPI network visualization was performed using Cytoscape and hub gene identification with cytoHubba. Top ten nodes were selected using maximum neighborhood component, degree and closeness algorithms and analysis of overlap was performed to confirm the hub genes. Epithelial-derived ameloblastoma cells from conventional ameloblastoma were transplanted into immunocompromised mice to recreate ameloblastoma in vivo based on the mouse xenograft model. The top 3 hub genes FN1, COL I and IGF-1 were validated by immunostaining and quantitative analysis of staining intensities to ameloblastoma, OKC samples and mouse ameloblastoma xenografts tissues. Results: Seven hub genes were identified among which FN1, COL1A1/COL1A2 and IGF-1 are associated with extracellular matrix organization, collagen binding, cell adhesion and cell surface interaction. These were further validated by positive immunoreactivity within the stroma of ameloblastoma samples but both ameloblastoma xenograft and OKC displayed only FN1 and IGF-1 immunoreactivity while COL 1 was unreactive. The expression levels of both FN1 and IGF-1 were much lower in OKC relative to ameloblastoma. Conclusion: This study further validates a differentially upregulated expression of matrix proteins FN1, COL I and IGF-1 in ameloblastoma relative to OKC. It suggests that differential stromal architecture and growth characteristics of ameloblastoma relative to OKC could be an interplay of differentially upregulated genes in ameloblastoma. [ABSTRACT FROM AUTHOR]

Generative artificial intelligence (AI) systems have performed well at many biomedical tasks, but few studies have assessed their performance directly compared to students in higher-education courses. We compared student knowledge-assessment scores with prompting of 6 large-language model (LLM) systems as they would be used by typical students in a large online introductory course in biomedical and health informatics that is taken by graduate, continuing education, and medical students. The state-of-the-art LLM systems were prompted to answer multiple-choice questions (MCQs) and final exam questions. We compared the scores for 139 students (30 graduate students, 85 continuing education students, and 24 medical students) to the LLM systems. All of the LLMs scored between the 50th and 75th percentiles of students for MCQ and final exam questions. The performance of LLMs raises questions about student assessment in higher education, especially in courses that are knowledge-based and online. [ABSTRACT FROM AUTHOR]

Background: Proliferative diabetic retinopathy (PDR) is a severe complication of diabetes, and understanding its molecular mechanisms is crucial. Endoplasmic reticulum (ER) stress has been implicated in various diseases, including diabetic complications. This study aims to elucidate ER stress-related biomarkers in PDR, providing insights into the underlying molecular pathways. Methods: We analyzed two independent PDR datasets, GSE102485 and GSE60436. The GSE102485 dataset (22 PDR and 3 normal samples) was the primary dataset for comprehensive analyses, including differential expression, functional enrichment, PPI network construction, immune cell infiltration, and drug prediction. The GSE60436 dataset (6 PDR and 3 normal samples) was used for validation. In vitro experiments using human umbilical vein endothelial cells (HUVECs) in a high-glucose environment were conducted to validate key bioinformatics outcomes. Western blotting assessed protein levels of ER stress markers (TRAM1 and TXNIP). Results: Differential expression analysis identified 2451 genes, including 328 ER stress-related genes. Functional analysis revealed enrichment in ER stressrelated processes and pathways. Hub genes (BCL2, CCL2, IL-1b, TLR4, TNF, TP53) were identified, and immune infiltration analysis showed altered immune cell proportions. Validation in GSE60436 and in vitro confirmed ER stress gene dysregulation. Drug prediction suggested potential small molecules targeting ER stress markers. Conclusion: This study provides a comprehensive molecular characterization of ER stress in PDR, highlighting altered biological processes, immune changes, and potential therapeutic targets. The identified hub genes and small molecules offer avenues for further investigation and therapy development, enhancing understanding of PDR pathogenesis and aiding targeted intervention creation. [ABSTRACT FROM AUTHOR]

Background and objectives: Periodontitis (PD), a chronic inflammatory disease, is a serious threat to oral health and is one of the risk factors for Alzheimer's disease (AD). A growing body of evidence suggests that the two diseases are closely related. However, current studies have not provided a comprehensive understanding of the common genes and common mechanisms between PD and AD. This study aimed to screen the crosstalk genes of PD and AD and the potential relationship between cross-talk and PANoptosis-related genes. The relationship between core genes and immune cells will be analyzed to provide new targets for clinical treatment. Materials and methods: The PD and AD datasets were downloaded from the GEO database and differential expression analysis was performed to obtain DEGs. Overlapping DEGs had cross-talk genes linking PD and OP, and PANoptosis-related genes were obtained from a literature review. Pearson coefficients were used to compute cross-talk and PANoptosis-related gene correlations in the PD and AD datasets. Cross-talk genes were obtained from the intersection of PD and AD-related genes, protein-protein interaction (PPI) networks were constructed and cross-talk genes were identified using the STRING database. The intersection of cross-talk and PANoptosis-related genes was defined as cross-talk-PANoptosis genes. Core genes were screened using ROC analysis and XGBoost. PPI subnetwork, gene-biological process, and gene-pathway networks were constructed based on the core genes. In addition, immune infiltration on the PD and AD datasets was analyzed using the CIBERSORT algorithm. Results: 366 cross-talk genes were overlapping between PD DEGs and AD DEGs. The intersection of cross-talk genes with 109 PANoptosis-related genes was defined as cross-talk-PANoptosis genes. ROC and XGBoost showed that MLKL, DCN, IL1B, and IL18 were more accurate than the other cross-talk-PANoptosis genes in predicting the disease, as well as better in overall characterization. GO and KEGG analyses showed that the four core genes were involved in immunity and inflammation in the organism. Immune infiltration analysis showed that B cells naive, Plasma cells, and T cells gamma delta were significantly differentially expressed in patients with PD and AD compared with the normal group. Finally, 10 drugs associated with core genes were retrieved from the DGIDB database. Conclusion: This study reveals the joint mechanism between PD and AD associated with PANoptosis. Analyzing the four core genes and immune cells may provide new therapeutic directions for the pathogenesis of PD combined with AD. [ABSTRACT FROM AUTHOR]

Background: Lysophosphatidic acid receptor 1 (LPAR1) has been identified as a biomarker in various cancer types. However, its biological function in papillary thyroid carcinoma (PTC) remains unknown. Methods: LPAR1 was identified as a key regulator of epithelial-mesenchymal transition (EMT) in PTC cells through bioinformatics analysis of TCGA and GEO datasets. PPI analysis and correlation with immune infiltrates were also conducted. LPAR1 expression was evaluated using Gepia2 and GTEx, and miRNA target gene prediction was done with multiMiR. To assess the expression of LPAR1, we extracted total RNA from both the BCPAP cell line and the normal human thyroid epithelial cell line Nthy-ori 3-1. The levels of LPAR1 expression were then measured using quantitative real-time polymerase chain reaction (qRT-PCR) in the BCPAP cell line, with a comparison to the Nthy-ori 3-1 cell line. Results: 1081 genes were upregulated, and 544 were downregulated compared to normal tissue. LPAR1 was identified as a key candidate by analyzing the TCGA and GEO datasets. PPI data analysis showed interactions with metastasis-related proteins. Functional enrichment analysis indicated involvement in signaling pathways like phospholipase D and actin cytoskeleton regulation. LPAR1 expression correlated positively with immune infiltrates such as CD4+ T cells, macrophages, neutrophils, and myeloid dendritic cells but negatively with B cells. Additionally, miR-221-5p was predicted to target LPAR1 in PTC. Furthermore, our experimental data demonstrated that LPAR1 was under-expressed in the PTC cell line compared to the nonmalignant one (P <.01). Conclusion: LPAR1 suppresses metastasis and is linked to EMT, as evidenced by the decreased LPAR1 expression and increased miR-221-5p in PTC. This suggests its potential as a biomarker for diagnosis and prognosis and as a therapeutic target for EMT. [ABSTRACT FROM AUTHOR]

Melanoma is known to be the most hazardous and life‐threatening type of skin cancer. Although numerous treatments have been authorized in recent years, they often result in severe side effects and may not fully cure the disease. To combat this issue, immunotherapy has emerged as a promising approach for the prevention and treatment of melanoma. Specifically, the use of epitope melanoma vaccine, a subset of immunotherapy, has recently gained attention. The aim of this study was to create a multi‐epitope melanoma vaccine using immunoinformatic methods. Two well‐known antigens, NYESO‐1 and MAGE‐C2, were selected due to their strong immunogenicity and high expression in melanoma. To enhance the immunogenicity of the peptide vaccine, Brucella cell‐surface protein 31 (BCSP31), the G5 domain of resuscitation‐promoting factor B (RpfB) adjuvants, and the helper epitope of pan HLADR‐binding epitope (PADRE) were incorporated to vaccine construct. These different segments were connected with suitable linkers and the resulting vaccine structure was evaluated for its physicochemical, structural, and immunological properties using computational tools. The designed vaccine was found to have satisfactory allergenicity, antigenicity, and physicochemical parameters. Additionally, a high‐quality tertiary structure of the vaccine was achieved through modeling, refinement, and validation. Docking and molecular dynamics studies showed that the vaccine had a stable and appropriate interaction with the cognate TLR2 and TLR4 receptors during the simulation period. Finally, in silico immune simulation analysis revealed a significant increase in the levels of helper and cytotoxic T cells, as well as the cytokines interferon‐gamma and interleukin‐2, after repeated exposure to the melanoma vaccine. These results suggest that the designed vaccine has the potential to be an effective therapeutic option for melanoma. However, additional in vitro and in vivo validations are crucial to assess real‐world efficacy and safety. [ABSTRACT FROM AUTHOR]

Recent advances in single‐cell (sc) transcriptomics have revolutionized our understanding of dendritic cells (DCs), pivotal players of the immune system. ScRNA‐sequencing (scRNA‐seq) has unraveled a previously unrecognized complexity and heterogeneity of DC subsets, shedding light on their ontogeny and specialized roles. However, navigating the rapid technological progress and computational methods can be daunting for researchers unfamiliar with the field. This review aims to provide immunologists with a comprehensive introduction to sc transcriptomic analysis, offering insights into recent developments in DC biology. Addressing common analytical queries, we guide readers through popular tools and methodologies, supplemented with references to benchmarks and tutorials for in‐depth understanding. By examining findings from pioneering studies, we illustrate how computational techniques have expanded our knowledge of DC biology. Through this synthesis, we aim to equip researchers with the necessary tools and knowledge to navigate and leverage scRNA‐seq for unraveling the intricacies of DC biology and advancing immunological research. [ABSTRACT FROM AUTHOR]

BACKGROUND: In recent years, research on the interaction mechanism between the immune system and the skeleton in postmenopausal osteoporosis has become a hot topic. However, the impact of changes in key immune-related cytokine expression on postmenopausal osteoporosis remains unclear and requires further exploration. OBJECTIVE: To investigate the differential expression of immune-related cytokines in bone marrow mesenchymal stem cells of mice with postmenopausal osteoporosis by bioinformatics methods. METHODS: Postmenopausal osteoporosis mouse model was established through ovariectomy. Bone marrow mesenchymal stem cells were obtained by the whole bone marrow adherence method and passaged to passage 2. RayBio L-Series Mouse Antibody Array 308 Glass Slide Kit immune-related factor antibody chip was used to detect the differentially expressed proteins in bone marrow mesenchymal stem cells from ovariectomy and sham-operation mice. Gene ontology, Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and protein-protein interaction network analysis were performed to screen common Hub genes by MCC, EPC, and MNC algorithms. RESULTS AND CONCLUSION: This study identified a total of 68 differentially expressed genes. Gene ontology analysis revealed that the differentially expressed genes were enriched in terms including “immune system processes”, “extracellular regions”, and “signal receptor binding”. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the differentially expressed genes were mainly enriched in “cytokine-cytokine receptor interactions”, “tumor necrosis factor signaling pathways”, and “chemokine signaling pathways”. Further screening was performed by constructing a protein-protein interaction network analysis of these 68 differentially expressed genes to identify 8 Hub genes. The violin plot and correlation matrix showed that the expression levels of these 8 Hub genes were significantly down-regulated in the ovariectomy group compared to the sham-operation group. These results demonstrated that there was differential expression of immune-related factors in bone marrow mesenchymal stem cells of postmenopausal osteoporosis mice, and key genes involved in cytokine-cytokine receptor interactions, immune system-related processes, and potential targeted signaling pathways and cellular biological processes were identified, providing new promising targets for the diagnosis, treatment, and prevention of postmenopausal osteoporosis. [ABSTRACT FROM AUTHOR]

Objective Methods Results Conclusion Osteoporosis is a severe bone disease with a complex pathogenesis involving various immune processes. With the in‐depth understanding of bone immune mechanisms, discovering new therapeutic targets is crucial for the prevention and treatment of osteoporosis. This study aims to explore novel bone immune markers related to osteoporosis based on single‐cell and transcriptome data, utilizing bioinformatics and machine learning methods, in order to provide novel strategies for the diagnosis and treatment of the disease.Single cell and transcriptome data sets were acquired from Gene Expression Omnibus (GEO). The data was then subjected to cell communication analysis, pseudotime analysis, and high dimensional WGCNA (hdWGCNA) analysis to identify key immune cell subpopulations and module genes. Subsequently, ConsensusClusterPlus analysis was performed on the key module genes to identify different diseased subgroups in the osteoporosis (OP) training set samples. The immune characteristics between subgroups were evaluated using Cibersort, EPIC, and MCP counter algorithms. OP's hub genes were screened using 10 machine learning algorithms and 113 algorithm combinations. The relationship between hub genes and immunity and pathways was established by evaluating the immune and pathway scores of the training set samples through the ESTIMATE, MCP‐counter, and ssGSEA algorithms. Real‐time fluorescence quantitative PCR (RT‐qPCR) testing was conducted on serum samples collected from osteoporosis patients and healthy adults.In OP samples, the proportions of bone marrow‐derived mesenchymal stem cells (BM‐MSCs) and neutrophils increased significantly by 6.73% (from 24.01% to 30.74%) and 6.36% (from 26.82% to 33.18%), respectively. We found 16 intersection genes and four hub genes (DND1, HIRA, SH3GLB2, and F7). RT‐qPCR results showed reduced expression levels of DND1, HIRA, and SH3GLB2 in clinical blood samples of OP patients. Moreover, the four hub genes showed positive correlations with neutrophils (0.65–0.90), immature B cells (0.76–0.92), and endothelial cells (0.79–0.87), while showing negative correlations with myeloid‐derived suppressor cells (negative 0.54–0.73), T follicular helper cells (negative 0.71–0.86), and natural killer T cells (negative 0.75–0.85).Neutrophils play a crucial role in the occurrence and development of osteoporosis. The four hub genes potentially inhibit metabolic activities and trigger inflammation by interacting with other immune cells, thereby significantly contributing to the onset and diagnosis of OP. [ABSTRACT FROM AUTHOR]

Granulosa cells (GCs) play crucial roles in oocyte maturation. Through gap junctions and extracellular vesicles, they mediate the exchange of molecules such as microRNAs and messenger RNAs. Different ovarian cell types exhibit unique gene expression profiles, reflecting their specialized functions and stages. By combining RNA-seq data from various cell types forming the follicle, we aimed at capturing a wide range of expression patterns, offering insights into the functional diversity and complexity of the transcriptome regulation across GCs. Herein, we performed an integrated bioinformatics analysis of RNA sequencing datasets present in public databases, with a unique and standardized workflow., By combining the data from different studies, we successfully increased the robustness and reliability of our findings and discovered novel genes, miRNAs, and signaling pathways associated with GCs function and oocyte maturation. Moreover, our results provide a valuable resource for further wet-lab research on GCs biology and their impact on oocyte development and competence. [ABSTRACT FROM AUTHOR]

Understanding the evolving nature of coronary hemodynamics is crucial for early disease detection and monitoring progression. We require digital twins that mimic a patient's circulatory system by integrating continuous physiological data and computing hemodynamic patterns over months. Current models match clinical flow measurements but are limited to single heartbeats. To this end, we introduced the longitudinal hemodynamic mapping framework (LHMF), designed to tackle critical challenges: (1) computational intractability of explicit methods; (2) boundary conditions reflecting varying activity states; and (3) accessible computing resources for clinical translation. We show negligible error (0.0002–0.004%) between LHMF and explicit data of 750 heartbeats. We deployed LHMF across traditional and cloud-based platforms, demonstrating high-throughput simulations on heterogeneous systems. Additionally, we established LHMFC, where hemodynamically similar heartbeats are clustered to avoid redundant simulations, accurately reconstructing longitudinal hemodynamic maps (LHMs). This study captured 3D hemodynamics over 4.5 million heartbeats, paving the way for cardiovascular digital twins. [ABSTRACT FROM AUTHOR]

Pangenomics is a relatively new scientific field which investigates the union of all the genomes of a clade. The word pan means everything in ancient Greek; the term pangenomics originally regarded genomes of bacteria and was later intended to refer to human genomes as well. Modern bioinformatics offers several tools to analyze pangenomics data, paving the way to an emerging field that we can call computational pangenomics. Current computational power available for the bioinformatics community has made computational pangenomic analyses easy to perform, but this higher accessibility to pangenomics analysis also increases the chances to make mistakes and to produce misleading or inflated results, especially by beginners. To handle this problem, we present here a few quick tips for efficient and correct computational pangenomic analyses with a focus on bacterial pangenomics, by describing common mistakes to avoid and experienced best practices to follow in this field. We believe our recommendations can help the readers perform more robust and sound pangenomic analyses and to generate more reliable results. [ABSTRACT FROM AUTHOR]

Eukaryotic elongation factors (eEFs) are protein factors that mediate the extension of peptide chain, among which eukaryotic elongation factor 1 alpha (eEF1A) is one of the most abundant protein synthesis factors. Previously we showed that the P3 protein of Soybean mosaic virus (SMV), one of the most destructive and successful viral pathogens of soybean, targets a component of the soybean translation elongation complex to facilitate its pathogenesis. Here, we conducted a systematic analyses of the soybean eEF (GmeEF) gene family in soybean and examinedits role in virus resistance. In this study, GmeEF family members were identified and characterized based on sequence analysis. The 42 members, which were unevenly distributed across the 15 chromosomes, were renamed according to their chromosomal locations. The GmeEF members were further divided into 12 subgroups based on conserved motif, gene structure, and phylogenetic analyses. Analysis of the promoter regions showed conspicuous presence of myelocytomatosis (MYC) and ethylene-responsive (ERE) cis-acting elements, which are typically involved in drought and phytohormone response, respectively, and thereby in plant stress response signaling. Transcriptome data showed that the expression of 15 GmeEF gene family members changed significantly in response to SMV infection. To further examine EF1A function in pathogen response, three different Arabidopsis mutants carrying T-DNA insertions in orthologous genes were analyzed for their response to Turnip crinkle virus (TCV) and Cucumber mosaic virus (CMV). Results showed that there was no difference in viral response between the mutants and the wild type plants. This study provides a systematic analysis of the GmeEF gene family through analysis of expression patterns and predicted protein features. Our results lay a foundation for understanding the role of eEF gene in soybean anti-viral response. [ABSTRACT FROM AUTHOR]

Background: Bladder cancer, a highly fatal disease, poses a significant threat to patients. Positioned at 19q13.2-13.3, LIG1, one of the four DNA ligases in mammalian cells, is frequently deleted in tumour cells of diverse origins. Despite this, the precise involvement of LIG1 in BLCA remains elusive. This pioneering investigation delves into the uncharted territory of LIG1's impact on BLCA. Our primary objective is to elucidate the intricate interplay between LIG1 and BLCA, alongside exploring its correlation with various clinicopathological factors. Methods: We retrieved gene expression data of para-carcinoma tissues and bladder cancer (BLCA) from the GEO repository. Single-cell sequencing data were processed using the "Seurat" package. Differential expression analysis was then performed with the "Limma" package. The construction of scale-free gene co-expression networks was achieved using the "WGCNA" package. Subsequently, a Venn diagram was utilized to extract genes from the positively correlated modules identified by WGCNA and intersect them with differentially expressed genes (DEGs), isolating the overlapping genes. The "STRINGdb" package was employed to establish the protein-protein interaction (PPI) network.Hub genes were identified through the PPI network using the Betweenness Centrality (BC) algorithm. We conducted KEGG and GO enrichment analyses to uncover the regulatory mechanisms and biological functions associated with the hub genes. A machine-learning diagnostic model was established using the R package "mlr3verse." Mutation profiles between the LIG1^high and LIG1^low groups were visualized using the BEST website. Survival analyses within the LIG1^high and LIG1^low groups were performed using the BEST website and the GENT2 website. Finally, a series of functional experiments were executed to validate the functional role of LIG1 in BLCA. Results: Our investigation revealed an upregulation of LIG1 in BLCA specimens, with heightened LIG1 levels correlating with unfavorable overall survival outcomes. Functional enrichment analysis of hub genes, as evidenced by GO and KEGG enrichment analyses, highlighted LIG1's involvement in critical function such as the DNA replication, cellular senescence, cell cycle and the p53 signalling pathway. Notably, the mutational landscape of BLCA varied significantly between LIG1high and LIG1low groups. Immune infiltrating analyses suggested a pivotal role for LIG1 in immune cell recruitment and immune regulation within the BLCA microenvironment, thereby impacting prognosis. Subsequent experimental validations further underscored the significance of LIG1 in BLCA pathogenesis, consolidating its functional relevance in BLCA samples. Conclusions: Our research demonstrates that LIG1 plays a crucial role in promoting bladder cancer malignant progression by heightening proliferation, invasion, EMT, and other key functions, thereby serving as a potential risk biomarker. [ABSTRACT FROM AUTHOR]

Cervical cancer is a kind of tumor related to chronic HPV infection. Currently, the treatment of cervical cancer is guided mainly by clinicopathological factors. The role of tumor microenvironment in the prognosis and treatment of cervical cancer has been ignored. We aimed to use bioinformatics to identify the molecular subtypes in cervical cancer and construct a predictive nomogram combining a matrix-immune signature (MIS) and clinicopathological factors to support treatment decisions. Two cervical cancer subtypes with different prognoses were identified based on matrix- and immune-genes in TCGA-CESC. The MIS was developed using Cox regression and Lasso algorithm and verified in the Cancer Genome Characterization Initiative (CGCI) using time-dependent receiver operating characteristic (ROC) curve analysis. Multivariable analysis identified lymph node metastases, lymphovascular space invasion, and the MIS as independent prognostic factors, which were used to construct the predictive nomogram. The areas under the ROC curve of the model were 0.872, 0.879, and 0.803 for the 1-, 3-, and 5-year periods, respectively. The C-index was 0.845. Calibration curves confirmed the excellent prognosis prediction of the nomogram. The nomogram indicted a 3-year survival rate of > 90% in patients with a total score > 110.1. The constructed predictive nomogram has significant implications for prognostic assessment and treatment selection in cervical cancer. [ABSTRACT FROM AUTHOR]

Backgrounds: Homeobox C6 (HOXC6) is a gene that encodes for a transcription factor involved in various cellular processes, including development and differentiation, and regulates cancer progression. However, the carcinogenesis and effect of HOXC6 in lung adenocarcinoma (LUAD) still need further investigation. Methods: The differential HOXC6 expression levels at the mRNA and protein level were explored in multiple public datasets, including The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) dataset. Gene Expression Omnibus (GSE31210), International Cancer Genome Consortium (ICGC) datasets and the LUAD sample from Affiliated Hospital of Guangxi Medical University. We also investigated the relation between HOXC6 expression and clinicopathologic indexes. Furthermore, the correlation of immune infiltration, drug responsiveness and HOXC6 were explored. Results: The upregulated HOXC6 expressions at mRNA and protein levels were found in LUAD tissues compared to the normal lung tissues. Besides, the relatively shorter overall survival time, worse T and N stages, and lower immune scores were found in the high-expression HOXC6 subgroup. Notably, T cells regulatory (Tregs), Macrophages M0, and Plasma cells had the higher infiltration levels in the high-HOXC6 expression subgroup, while NK cells activated, Monocytes, Dendritic cells resting, and Mast cells resting had the lower infiltration levels. In drug sensitivity analysis, we revealed that LUAD patients with high-HOXC6 expression may be more susceptible to Camptothecin, Cytarabine, Docetaxel, Elesclomol, Rapamycin, Sorafinib, Temsirolimus, and Vorinostat. Conclusions: Taken together, there is a great potential for HOXC6 to become a prognosis biomarker and contribute to develop treatment strategies for LUAD patients. Further mechanism exploration and drug development for HOXC6 are needed. [ABSTRACT FROM AUTHOR]

Background: Spontaneous preterm birth (sPTB) is a global disease that is a leading cause of death in neonates and children younger than 5 years of age. However, the etiology of sPTB remains poorly understood. Recent evidence has shown a strong association between metabolic disorders and sPTB. To determine the metabolic alterations in sPTB patients, we used various bioinformatics methods to analyze the abnormal changes in metabolic pathways in the preterm placenta via existing datasets. Methods: In this study, we integrated two datasets (GSE203507 and GSE174415) from the NCBI GEO database for the following analysis. We utilized the "Deseq2" R package and WGCNA for differentially expressed genes (DEGs) analysis; the identified DEGs were subsequently compared with metabolism-related genes. To identify the altered metabolism-related pathways and hub genes in sPTB patients, we performed multiple functional enrichment analysis and applied three machine learning algorithms, LASSO, SVM-RFE, and RF, with the hub genes that were verified by immunohistochemistry. Additionally, we conducted singlesample gene set enrichment analysis to assess immune infiltration in the placenta. Results: We identified 228 sPTB-related DEGs that were enriched in pathways such as arachidonic acid and glutathione metabolism. A total of 3 metabolismrelated hub genes, namely, ANPEP, CKMT1B, and PLA2G4A, were identified and validated in external datasets and experiments. A nomogram model was developed and evaluated with 3 hub genes; the model could reliably distinguish sPTB patients and term labor patients with an area under the curve (AUC) > 0.75 for both the training and validation sets. Immune infiltration analysis revealed immune dysregulation in sPTB patients. Conclusion: Three potential hub genes that influence the occurrence of sPTB through shadow participation in placental metabolism were identified; these results provide a new perspective for the development and targeting of treatments for sPTB. [ABSTRACT FROM AUTHOR]

Inflammatory Bowel Diseases (IBD), which encompass ulcerative colitis (UC) and Crohn's disease (CD), are characterized by chronic inflammation and tissue damage of the gastrointestinal tract. This study aimed to uncover novel disease-gene signatures, dysregulated pathways, and the immune cell infiltration landscape of inflamed tissues. Eight publicly available transcriptomic datasets, including inflamed and non-inflamed tissues from CD and UC patients were analyzed. Common differentially expressed genes (DEGs) were identified through meta-analysis, revealing 180 DEGs. DEGs were implicated in leukocyte transendothelial migration, PI3K-Akt, chemokine, NOD-like receptors, TNF signaling pathways, and pathways in cancer. Protein–protein interaction network and cluster analysis identified 14 central IBD players, which were validated using eight external datasets. Disease module construction using the NeDRex platform identified nine out of 14 disease-associated genes (CYBB, RAC2, GNAI2, ITGA4, CYBA, NCF4, CPT1A, NCF2, and PCK1). Immune infiltration profile assessment revealed a significantly higher degree of infiltration of neutrophils, activated dendritic cells, plasma cells, mast cells (resting/activated), B cells (memory/naïve), regulatory T cells, and M0 and M1 macrophages in inflamed IBD tissue. Collectively, this study identified the immune infiltration profile and nine disease-associated genes as potential modulators of IBD pathogenesis, offering insights into disease molecular mechanisms, and highlighting potential disease modulators and immune cell dynamics. [ABSTRACT FROM AUTHOR]

Gibberellic acid-stimulated Arabidopsis sequences (GASAs) are a subset of the gibberellin (GA)-regulated gene family and play crucial roles in various physiological processes. However, the GASA genes in Brassica rapa have not yet been documented. In this study, we identified and characterized 16 GASA genes in Chinese cabbage (Brassica rapa L. ssp. pekinensis). Analysis of the conserved motifs revealed significant conservation within the activation segment of BraGASA genes. This gene family contains numerous promoter elements associated with abiotic stress tolerance, including those for abscisic acid (ABA) and methyl jasmonate (MeJA). Expression profiling revealed the presence of these genes in various tissues, including roots, stems, leaves, flowers, siliques, and callus tissues. When plants were exposed to drought stress, the expression of BraGASA3 decreased notably in drought-sensitive genotypes compared to their wild-type counterparts, highlighting the potentially crucial role of BraGASA3 in drought stress. Additionally, BraGASAs exhibited various functions in sexual reproduction dynamics. The findings contribute to the understanding of the function of BraGASAs and provide valuable insights for further exploration of the GASA gene function of the BraGASA gene in Chinese cabbage. [ABSTRACT FROM AUTHOR]

Background: Osteosarcoma (OS) is undeniably a formidable bone malignancy characterized by a scarcity of effective treatment options. Reprogramming of amino acid (AA) metabolism has been associated with OS development. The present study was designed to identify metabolism-associated genes (MAGs) that are differentially expressed in OS and to construct a MAG-based prognostic risk signature for this disease. Methods: Expression profiles and clinicopathological data were downloaded from Gene Expression Omnibus (GEO) and UCSC Xena databases. A set of AA MAGs was obtained from the MSigDB database. Differentially expressed genes (DEGs) in GEO dataset were identified using "limma." Prognostic MAGs from UCSC Xena database were determined through univariate Cox regression and used in the prognostic signature development. This signature was validated using another dataset from GEO database. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, single sample gene set enrichment analysis, and GDSC2 analyses were performed to explore the biological functions of the MAGs. A MAG-based nomogram was established to predict 1-, 3-, and 5-year survival. Real-time quantitative polymerase chain reaction, Western blot, and immunohistochemical staining confirmed the expression of MAGs in primary OS and paired adjacent normal tissues. Results: A total of 790 DEGs and 62 prognostic MAGs were identified. A MAG-based signature was constructed based on four MAGs: PIPOX, PSMC2, SMOX, and PSAT1. The prognostic value of this signature was successfully validated, with areas under the receiver operating characteristic curves for 1-, 3-, and 5-year survival of 0.714, 0.719, and 0.715, respectively. This MAG-based signature was correlated with the infiltration of CD56dim natural killer cells and resistance to several antiangiogenic agents. The nomogram was accurate in predictions, with a C-index of 0.77. The expression of MAGs verified by experiment was consistent with the trends observed in GEO database. Conclusion: Four AA MAGs were prognostic of survival in OS patients. This MAG-based signature has the potential to offer valuable insights into the development of treatments for OS. [ABSTRACT FROM AUTHOR]

Simple Summary: This review provides a comprehensive overview of the current knowledge on mutational signatures in colorectal cancer (CRC), highlighting their potential clinical applications. It discusses the challenges and limitations in translating these analyses into clinical practice and proposes strategies to overcome these obstacles. Additionally, it provides insights into future directions and emerging proof-of-concept studies that highlight the translational potential of mutational signature analysis in improving patient care and outcomes in CRC. A multitude of exogenous and endogenous processes have the potential to result in DNA damage. While the repair mechanisms are typically capable of correcting this damage, errors in the repair process can result in mutations. The findings of research conducted in 2012 indicate that mutations do not occur randomly but rather follow specific patterns that can be attributed to known or inferred mutational processes. The process of mutational signature analysis allows for the inference of the predominant mutational process for a given cancer sample, with significant potential for clinical applications. A deeper comprehension of these mutational signatures in CRC could facilitate enhanced prevention strategies, facilitate the comprehension of genotoxic drug activity, predict responses to personalized treatments, and, in the future, inform the development of targeted therapies in the context of precision oncology. The efforts of numerous researchers have led to the identification of several mutational signatures, which can be categorized into different mutational signature references. In CRC, distinct mutational signatures are identified as correlating with mismatch repair deficiency, polymerase mutations, and chemotherapy treatment. In this context, a mutational signature analysis offers considerable potential for enhancing minimal residual disease (MRD) tests in stage II (high-risk) and stage III CRC post-surgery, stratifying CRC based on the impacts of genetic and epigenetic alterations for precision oncology, identifying potential therapeutic vulnerabilities, and evaluating drug efficacy and guiding therapy, as illustrated in a proof-of-concept clinical trial. [ABSTRACT FROM AUTHOR]

Simple Summary: The inactivation of apoptotic signaling by inhibitors of apoptosis proteins (IAPs) is one of the important hallmarks of cancer cells. Survivin, a 16.5 kDa member of the IAP family, is commonly enriched in many cancers and is a potential therapeutic target. We investigated the Survivin-targeting potential of Withaferin-A (Wi-A) and Withanone (Wi-N), two major withanolides from Withania somnifera (Ashwagandha), using computational assays. The results were validated in various in vitro experimental assays using Wi-A-rich extracts from Ashwagandha leaves, suggesting their use as an important bioresource for cancer drug development. Survivin, a member of the IAP family, functions as a homodimer and inhibits caspases, the key enzymes involved in apoptosis. Several Survivin inhibitors, including YM-155, Debio1143, EM1421, LQZ-7I, and TL32711, have emerged as potential anticancer drugs awaiting validation in clinical trials. Due to the high cost and adverse side effects of synthetic drugs, natural compounds with similar activity have also been in demand. In this study, we conducted molecular docking assays to evaluate the ability of Wi-A and Wi-N to block Survivin dimerization. We found that Wi-A, but not Wi-N, can bind to and prevent the homodimerization of Survivin, similar to YM-155. Therefore, we prepared a Wi-A-rich extract from Ashwagandha leaves (Wi-AREAL). Experimental analyses of human cervical carcinoma cells (HeLa and ME-180) treated with Wi-AREAL (0.05–0.1%) included assessments of viability, apoptosis, cell cycle, migration, invasion, and the expression levels (mRNA and protein) of molecular markers associated with these phenotypes. We found that Wi-AREAL led to growth arrest mediated by the upregulation of p21WAF1 and the downregulation of several proteins (CDK1, Cyclin B, pRb) involved in cell cycle progression. Furthermore, Wi-AREAL treatment activated apoptosis signaling, as evidenced by reduced PARP-1 and Bcl-2 levels, increased procaspase-3, and elevated Cytochrome C. Additionally, treating cells with a nontoxic low concentration (0.01%) of Wi-AREAL inhibited migration and invasion, as well as EMT (epithelial–mesenchymal transition) signaling. By combining computational and experimental approaches, we demonstrate the potential of Wi-A and Wi-AREAL as natural inhibitors of Survivin, which may be helpful in cancer treatment. [ABSTRACT FROM AUTHOR]

Simple Summary: Breast cancer significantly affects women globally, but physical activity (PA) has been shown to improve the quality of life, aid recovery, and enhance survival rates in patients. Studies reveal that PA influences DNA methylation, both globally and at gene-specific levels, potentially reversing abnormal methylation linked to cancer. This review compiles research on PA's impact on DNA methylation in breast cancer patients. The findings suggest that PA increases global DNA methylation in tumour tissues and alters gene-specific promoter methylation across various genes. Bioinformatic analysis indicates that these genes are primarily involved in metabolic pathways, cell cycle regulation, mitosis, cellular stress responses, and diverse binding processes. The Human Protein Atlas supports these findings, showing gene functionality in 266 tissues, including various breast tissues. Overall, PA's ability to modify DNA methylation patterns in breast cancer patients may aid in the restoration of normal cellular functions and enhance recovery and survival outcomes. Breast cancer (BC) continues to significantly impact women worldwide. Numerous studies show that physical activity (PA) significantly enhances the quality of life, aids recovery, and improves survival rates in BC patients. PA's influence extends to altering DNA methylation patterns on both a global and gene-specific scale, potentially reverting abnormal DNA methylation, associated with carcinogenesis and various pathologies. This review consolidates the findings of the current literature, highlighting PA's impact on DNA methylation in BC patients. Our systematic analysis indicates that PA may elevate global DNA methylation within tumour tissues. Furthermore, it appears to modify gene-specific promoter methylation across a wide spectrum of genes in various tissues. Through bioinformatic analysis, to investigate the functional enrichment of these affected genes, we identified a predominant enrichment in metabolic pathways, cell cycle regulation, cell cycle checkpoints, mitosis, cellular stress responses, and molecular functions governing diverse binding processes. The Human Protein Atlas corroborates this enrichment, indicating gene functionality across 266 tissues, notably within various breast tissues. This systematic review unveils PA's capacity to systematically alter DNA methylation patterns across multiple tissues, particularly in BC patients. Emphasising its influence on crucial biological processes and functions, this alteration holds potential for restoring normal cellular functionality and the cell cycle. This reversal of cancer-associated patterns could potentially enhance recovery and improve survival outcomes. [ABSTRACT FROM AUTHOR]

N6-methyladenosine (m6A) RNA modification is a conserved mechanism that regulates the fate of RNA across eukaryotic organisms. Despite its significance, a comprehensive analysis of m6A-related genes in non-model plants, such as kiwifruit, is lacking. Here, we identified 36 m6Arelated genes in the kiwifruit genome according to homology and phylogenetic inference. We performed bioinformatics and evolutionary analyses of the writer, eraser, and reader families of m6A modification. Reanalysis of public RNA-seq data collected from samples under various biotic and abiotic stresses indicated that most m6A-related genes were remarkably expressed under different conditions. Through construction of gene co-expression networks, we found significant correlations between several m6A-related genes and transcription factors (TFs) as well as receptor-like genes during the development and ripening of kiwifruit. Furthermore, we performed ATAC-seq assays on diverse kiwifruit tissues to investigate the regulatory mechanisms of m6A-related genes. We identified 10 common open chromatin regions that were present in at least two tissues, and these regions might serve as potential binding sites for MADS protein, C2H2 protein, and other predicted TFs. Our study offers comprehensive insights into the gene family of m6A-related components in kiwifruit, which will lay foundation for exploring mechanisms of post-transcriptional regulation involved in development and adaptation of kiwifruit. [ABSTRACT FROM AUTHOR]

Objective: The present study was performed to identify key biomarkers associated with immune cell infiltration in peri‐implantitis through bioinformatic analyses. Methods: Six peri‐implantitis soft tissue samples and six healthy gingiva samples were obtained from GSE106090, and were used to identify immune‐associated differentially expressed genes (DEGs) in peri‐implantitis. The candidate biomarkers associated with immune cell infiltration were examined by immunohistochemical staining. Results: We identified 2089 upregulated and 2173 downregulated genes. Upregulated DEGs were significantly associated with immune response. Ten key candidate biomarkers were identified in the PPI network, including IL1B, TLR2, TLR4, CCL4, CXCL8, IL10, IL6, CD4, CCL3, and PTPRC. The expression level of the 10 genes increased in peri‐implantitis soft tissue samples compared with healthy gingiva samples. The proportion of CD4+ T cells, iTreg, and Tfh in infiltration immune cells increased in peri‐implantitis soft tissue samples and were positively correlated with the expression level of candidate biomarkers TLR4, CCL3, CXCL8, and IL1B. Immunohistochemistry showed that there were more lymphocytes in peri‐implantitis soft tissue samples, with an increased expression level of TLR4, CCL3, CXCL8, and IL1B. Conclusion: Identification of four novel diagnostic biomarkers was helpful for revealing the molecular mechanisms and could serve as a risk predictor for the immune microenvironment in peri‐implantitis. [ABSTRACT FROM AUTHOR]

Human papillomavirus (HPV) L1 major capsid protein generates a highly immunogenic virus like particles (VLPs), which have been used as the main component of its prophylactic vaccine. However, the neutralizing antibodies against L1 VLPs are mostly type specific and may not be effective to prevent infection from different strains of HPV. On the other hand, HPV L2 minor capsid protein has low antigenic variation, thus can induce cross-neutralization. This study aims to obtain HPV 52 L1/L2 chimeric protein, which is designed based on HPV type 52 as one of the most circulated high-risk types in Indonesia, to develop a broad-spectrum HPV vaccine. Substitution of HPV 52 H4 helix L1 region with an HPV 52 L2 epitope was carried out using overlap extension PCR. HPV 52 L1/L2 chimeric gene was constructed into pET-SUMO expression vector and expressed in Escherichia coli BL21 (DE3). Bioinformatics modeling suggested that L2 epitope was located inside of the loop region in monomer form, and on the contrary, it was located outside of the pentamer surface. Furthermore, B cell and T cell epitopes predictions were conducted using Immune Epitope Database (IEDB) analysis. The B cell epitopes prediction revealed eleven potential epitopes, whereas the T cell epitopes prediction showed seven potential epitopes for each MHC class I and MHC class II. This study showed that HPV 52 L1/L2 chimeric protein has the potential to induce cross-neutralizing antibodies and can be developed as a promising candidate for a new HPV vaccine. [ABSTRACT FROM AUTHOR]

Ischemia-reperfusion (IR) injury contributes to primary graft dysfunction, a major cause of early mortality after lung transplantation. Transcriptomics uses high-throughput techniques to profile the RNA transcripts within a sample and provides a unique view of the mechanisms underlying various biological processes. This review aims to highlight the applications of transcriptomics in lung IR injury studies, which have thus far revealed inflammatory responses to be the major event activated by IR, identified potential biomarkers and therapeutic targets, and investigated the mechanisms of therapeutic interventions. Ex vivo lung perfusion, together with advanced bioinformatic and transcriptomic techniques, including single-cell RNA-sequencing, microRNA profiling, and multi-omics, continue to expand the capabilities of transcriptomics. In the future, the construction of biospecimen banks and the promotion of international collaborations among clinicians and researchers have the potential to advance our understanding of IR injury and improve the management of lung transplant recipients. [ABSTRACT FROM AUTHOR]

Background: Febrile urinary tract infections (UTIs) are among the most severe bacterial infections in infants, in which a subset of patients develops complications. Identifying infants at risk of recurrent infections or kidney damage based on clinical signs is challenging. Previous observations suggest that genetic factors influence UTI outcomes and could serve as predictors of disease severity. In this study, we conducted a nationwide survey of infant genotypes to develop a strategy for infection management based on individual genetic risk. Our aims were to identify genetic susceptibility variants for renal scarring (RS) and genetic host factors predisposing to dilating vesicoureteral reflux (VUR) and recurrent UTIs. Methods: To assess genetic susceptibility, we collected and analyzed DNA from blood using exome genotyping. Disease-associated genetic variants were identified through bioinformatics analysis, including allelic frequency tests and odds ratio calculations. Kidney involvement was defined using dimercaptosuccinic acid (DMSA) scintigraphy. Results: In this investigation, a cohort comprising 1087 infants presenting with their first episode of febrile UTI was included. Among this cohort, a subset of 137 infants who underwent DMSA scanning was subjected to gene association analysis. Remarkable genetic distinctions were observed between patients with RS and those exhibiting resolved kidney involvement. Notably, the genetic signature indicative of renal scarring prominently featured mitochondrial genes. Conclusions: In this nationwide study of genetic susceptibility to RS after febrile UTIs in infancy, we identified a profile dominated by mitochondrial polymorphisms. This profile can serve as a predictor of future complications, including RS and recurrent UTIs. [ABSTRACT FROM AUTHOR]

Background: Congenital anomalies of the kidney and urinary tract (CAKUT) represent a frequent cause of pediatric kidney failure. CNVs, as a major class of genomic variations, can also affect miRNA regions. Common CNV corresponding miRNAs (cCNV-miRNAs) are functional variants regulating crucial processes which could affect urinary system development. Thus, we hypothesize that cCNV-miRNAs are associated with CAKUT occurrence and its expressivity. Methods: The extraction and filtering of common CNVs, identified in control samples deposited in publicly available databases gnomAD v2.1 and dbVar, were coupled with mapping of miRNA sequences using UCSC Genome Browser. After verification of the mapped miRNAs using referent miRBase V22.1, prioritization of cCNV-miRNA candidates has been performed using bioinformatic annotation and literature research. Genotyping of miRNA gene copy numbers for MIR9-3, MIR511, and MIR1299, was conducted on 221 CAKUT patients and 192 controls using TaqMan™ technology. Results: We observed significantly different MIR9-3 and MIR1299 gene copy number distribution between CAKUT patients and controls (Chi-square, P = 0.006 and P = 0.0002, respectively), while difference of MIR511 copy number distribution showed nominal significance (Chi-square, P = 0.027). The counts of less and more than two of MIR1299 copy numbers were more frequent within CAKUT patients compared to controls (P = 0.01 and P = 0.008, respectively) and also in cohort of patients with anomalies of the urinary tract compared to controls (P = 0.016 and P = 0.003, respectively). Conclusions: Copy number variations of miRNA genes represent a novel avenue in clarification of the inheritance complexity in CAKUT and provide potential evidence about the association of common genetic variation with CAKUT phenotypes. [ABSTRACT FROM AUTHOR]

Commercial short tandem repeat (STR) kits exclusively contain human-specific primers; however, various non-human organisms with high homology to the STR kit's primer sequences can cause cross-reactivity. Owing to the proprietary nature of the primers in STR kits, the origins and sequences of most non-specific peaks (NSPs) remain unclear. Such NSPs can complicate data interpretation between the casework and reference samples; thus, we developed "NSPlex", an efficient method to discover the biological origins of NSPs. We used leftover STR kit amplicons after capillary electrophoresis and performed advanced bioinformatics analyses using next-generation sequencing followed by BLAST nucleotide searches. Using our method, we could successfully identify NSP generated from PCR amplicons of a sample mixture of human DNA and DNA extracted from matcha powder (finely ground powder of green tea leaves and previously known as a potential source of NSP). Our results showed our method is efficient for NSP analysis without the need for the primer information as in commercial STR kits. [ABSTRACT FROM AUTHOR]

Background: Type-2 diabetes mellitus is a metabolic disorder characterised by hyperglycemia and insulin resistance. This study aims to explore the role and mechanism of DIRAS family GTPase 3 (DIRAS3) in mediating pancreatic β-cell death and insulin secretion. Materials and Methods: A bioinformatic analysis of the GSE118230 and GSE150281 datasets was performed to screen differentially expressed genes. The pancreatic β-cell lines, INS-1 and MIN6, were treated with palmitic acid (PA) to mimic the cell models of type-2 diabetes mellitus. CCK-8 assay, 5-ethynyl-2'-deoxyuridine staining, flow cytometry, enzyme-linked immunoassay, immunofluorescence, qRT-PCR, and western immunoblotting were conducted to illustrate the role of DIRAS3 in the cell models. Results: Unlike in normal controls, DIRAS3 was highly expressed in PA-treated pancreatic β-cells in a dose- and time-dependent manner. Moreover, the silencing of DIRAS3 in the INS-1 cells attenuated PA-induced cell loss by improving cell proliferation and inhibiting apoptosis and prevented the PA-induced impairment of insulin secretion. Consistently, the overexpression of DIRAS3 in the MIN6 cells accelerated PA-induced cell loss and impaired insulin secretion. A Gene Set Enrichment Analysis predicted that phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) was a downstream signalling pathway of DIRAS3, as the inhibitory effects of DIRAS3 on the activation of the PI3K/AKT signalling pathway were confirmed in the INS-1 and MIN6 cells. Moreover, the PI3K inhibitor, LY294002, effectively reversed the protective effects of DIRAS3 silencing on the INS-1 cells. Conclusion: DIRAS3 was highly expressed in the cell models of type-2 diabetes mellitus, contributing to PA-induced cell death and impaired insulin secretion in pancreatic β-cells through the inhibition of the PI3K/AKT signalling pathway. [ABSTRACT FROM AUTHOR]

Endometrial carcinoma is one of most common malignant tumors in women, and ferroptosis is closely related to the development and treatment of endometrial carcinoma. The aim of this study was to screen ferroptosis-related genes associated with endometrial carcinoma and predict targeted drugs through bioinformatics. 761 differentially expressed genes were obtained by the dataset GSE63678 from the GEO database, and most of the genes were enriched in the KEGG_CELL_CYCLE and KEGG_OOCYTE_MEIOSIS signaling pathways. 22 ferroptosis-differentially expressed genes were obtained by intersection with the FerrDb database. These genes were involved in biological processes including macromolecular complex assembly and others, and involved in signal pathways including glutathione metabolism, p53 signaling pathway and others. CDKN2A, IDH1, NRAS, TFRC and GOT1 were obtained as hub genes by PPI network analysis. GEPIA showed that CDKN2A, IDH1, NRAS and TFRC were significantly expressed in endometrial carcinoma. Immunohistochemical results showed that CDKN2A, NRAS and TFRC were significantly expressed in endometrial carcinoma clinical tissue samples. The ROC constructed by TCGA database showed that CDKN2A, NRAS and TFRC had significant value in the diagnosis of endometrial carcinoma, and all had prognostic efficacy. 136,572-09-3 BOSS and others were identified as potential targeted drugs for endometrial carcinoma targeting ferroptosis. Our study has shown that ferroptosis-related genes CDKN2A, NRAS and TFRC are diagnostic markers of endometrial carcinoma, and 136,572-09-3 BOSS, methyprylon BOSS, daunorubicin CTD 00005752, nitroglycerin BOSS and dUTP BOSS, IRON BOSS, Imatinib mesylate BOSS, 2-Butanone BOSS, water BOSS, and L-thyroxine BOSS may be potential therapeutic drugs. [ABSTRACT FROM AUTHOR]

SUMMARY: The plant hormone abscisic acid (ABA) regulates essential processes in plant development and responsiveness to abiotic and biotic stresses. ABA perception triggers a post‐translational signaling cascade that elicits the ABA gene regulatory network (GRN), encompassing hundreds of transcription factors (TFs) and thousands of transcribed genes. To further our knowledge of this GRN, we performed an RNA‐seq time series experiment consisting of 14 time points in the 16 h following a one‐time ABA treatment of 5‐week‐old Arabidopsis rosettes. During this time course, ABA rapidly changed transcription levels of 7151 genes, which were partitioned into 44 coexpressed modules that carry out diverse biological functions. We integrated our time‐series data with publicly available TF‐binding site data, motif data, and RNA‐seq data of plants inhibited in translation, and predicted (i) which TFs regulate the different coexpression clusters, (ii) which TFs contribute the most to target gene amplitude, (iii) timing of engagement of different TFs in the ABA GRN, and (iv) hierarchical position of TFs and their targets in the multi‐tiered ABA GRN. The ABA GRN was found to be highly interconnected and regulated at different amplitudes and timing by a wide variety of TFs, of which the bZIP family was most prominent, and upregulation of genes encompassed more TFs than downregulation. We validated our network models in silico with additional public TF‐binding site data and transcription data of selected TF mutants. Finally, using a drought assay we found that the Trihelix TF GT3a is likely an ABA‐induced positive regulator of drought tolerance. Significance Statement: The hormone abscisic acid (ABA) regulates many plant stress responses and plant development by activating a complex gene regulatory network. We unveiled key players and their hierarchy in the ABA network. For this, we generated high‐density RNA‐seq time series data of mature ABA‐treated Arabidopsis thaliana leaves and used existing and newly developed methods to integrate the transcriptional dynamics with publicly available TF‐binding data and RNA‐seq data of ABA‐treated plants inhibited in translation. [ABSTRACT FROM AUTHOR]

Background: Lichen striatus (LS) is an acquired skin disorder with a linear pattern along Blaschko's lines. It commonly occurs in childhood, and the lesions spontaneously regress within several months. Objectives: Although up to 50% of LS cases exhibit hypopigmentation that can persist for several months to years, it is unknown why LS is associated with such a high incidence of hypopigmentation compared to other inflammatory skin diseases. Therefore, this study aimed to analyse the differences in the skin microbiome between LS patients with and without hypopigmentation. Methods: Differences in skin microbiome were analysed using whole genome sequencing of skin biopsies and subsequent bioinformatics analyses. Results: Some microbes commonly found in hypopigmented skin disorders, including Cutibacterium acnes, were more abundant in patients with LS showing hypopigmentation than in those not showing hypopigmentation. Conclusions: The skin microbiota may be involved in the development of hypopigmentation in LS and may be considered a treatment target to reduce LS duration and hypopigmentation. [ABSTRACT FROM AUTHOR]

Fructans are commonly used as dietary fibre supplements for their ability to promote the growth of beneficial gut microbes. However, fructan consumption has been associated with various dosage-dependent side effects. We characterised side effects in an exploratory analysis of a randomised trial in healthy adults (n = 40) who consumed 18 g/day inulin or placebo. We found that individuals weighing more or habitually consuming higher fibre exhibited the best tolerance. Furthermore, we identified associations between gut microbiome composition and host tolerance. Specifically, higher levels of Christensenellaceae R-7 group were associated with gastrointestinal discomfort, and a machine-learning-based approach successfully predicted high levels of flatulence, with [Ruminococcus] torques group and (Oscillospiraceae) UCG-002 sp. identified as key predictive taxa. These data reveal trends that can help guide personalised recommendations for initial inulin dosage. Our results support prior ecological findings indicating that fibre supplementation has the greatest impact on individuals whose baseline fibre intake is lowest. [ABSTRACT FROM AUTHOR]

Context.--There have been exceedingly few reports of epidermodysplasia verruciformis (EV) or EV-like lesions in the vulva. We describe the first observation of vulvar lesions displaying synchronous EV-like histology and conventional high-grade squamous intraepithelial lesion (HSIL), a finding hitherto unreported in medical literature. Objectives.--To describe this novel vulvar lesion with hybrid features of HSIL and EV, attempt to confirm the hypothesis of coinfection with a and b human papillomavirus (a-HPV and b-HPV) genotypes, and describe relevant underlying genetic mutations. Design.--Cases were retrospectively selected from our institutional archive. Detailed review of clinical information, histologic examination, and whole genome sequencing (WGS) were performed. Results.--Five samples from 4 different patients were included. Three of 4 patients had a history of either iatrogenic immune suppression or prior immune deficiency, and all 3 featured classic HSIL and EV changes within the same lesion. One patient had no history of immune disorders, presented with EV-like changes and multinucleated atypia of the vulva, and was the sole patient without conventional HSIL. By WGS, several uniquely mappable reads pointed toward infection with multiple HPV genotypes, including both a-HPVs and b-HPVs. Mutations in genes implicated in cell-mediated immunity, such as DOCK8, CARMIL2, MST1, and others, were also found. Conclusions.--We provide the first description of vulvar lesions harboring simultaneous HSIL and EV features in the English-language literature, a phenomenon explained by coinfection with a-HPV and b-HPV genotypes. The finding of EV-like changes in a vulvar specimen should prompt assessment of the patient's immune status. [ABSTRACT FROM AUTHOR]

• LGB-IPs is a new LGB-based optimal feature fusion model for the accurate prediction of STY phosphorylation sites. • LGB-IPs explores ten different feature descriptors and assesses its discriminative capability using five different classifiers. • Extensive cross-validation and independent assessment shows that LGB-IPs outperformed the single feature models consistently. SARS-CoV-2′s global spread has instigated a critical health and economic emergency, impacting countless individuals. Understanding the virus's phosphorylation sites is vital to unravel the molecular intricacies of the infection and subsequent changes in host cellular processes. Several computational methods have been proposed to identify phosphorylation sites, typically focusing on specific residue (S/T) or Y phosphorylation sites. Unfortunately, current predictive tools perform best on these specific residues and may not extend their efficacy to other residues, emphasizing the urgent need for enhanced methodologies. In this study, we developed a novel predictor that integrated all the residues (STY) phosphorylation sites information. We extracted ten different feature descriptors, primarily derived from composition, evolutionary, and position-specific information, and assessed their discriminative power through five classifiers. Our results indicated that Light Gradient Boosting (LGB) showed superior performance, and five descriptors displayed excellent discriminative capabilities. Subsequently, we identified the top two integrated features have high discriminative capability and trained with LGB to develop the final prediction model, LGB-IPs. The proposed approach shows an excellent performance on 10-fold cross-validation with an ACC, MCC, and AUC values of 0.831, 0.662, 0.907, respectively. Notably, these performances are replicated in the independent evaluation. Consequently, our approach may provide valuable insights into the phosphorylation mechanisms in SARS-CoV-2 infection for biomedical researchers. [ABSTRACT FROM AUTHOR]

Enzymes are biological catalysts that accelerate chemical reactions by reducing their activation energy. Enzymes specific environmental conditions to function optimally. Additive molecules and compounds, such as organic solvents, ionic liquids, and deep eutectic solvents, have crucial effects on enzyme behavior by changing activity and stability. However, finding and testing different additives is an expensive process that requires specialists, laboratory equipment, and chemical compounds. Machine learning, which has been present in all fields of science and technology in recent years, is one of the ways to find a suitable additive for our desired enzyme without doing a time-consuming experimental process. In this manuscript, we introduce ADDZYME, a machine learning-based software, to predict the effect of additives on enzyme activity. ADDZYME utilizes an ensemble of extremely randomized trees models alongside physicochemical descriptors to make a prediction. To ease usage, ADDZYME is accompanied by a graphical user interface. ADDZYME is freely available on www.github.com/miladrayka/addzyme for further experiments. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to explore the expression, clinical significance, and functional mechanism of FYN in lower-grade gliomas (LGG). Methods: The mRNA and protein expression of FYN in LGG tissues were detected using databases including OncoLnc, GEPIA, and Human protein atlas (HPA). The UCSC Xena browser, TIMER, STRING and Metascape databases were used to investigate Kaplan–Meier survival curves, correlations between FYN expression and various types of immune cell infiltration, protein interaction network and possible functional mechanism. Results: FYN expression in LGG, IDH mutation or 1p19q co-deletion subgroup was significantly higher than in corresponding control groups (p < 0.05). Patients with higher FYN expression had longer overall survival (p < 0.05). Male or no 1p19q co-deletion groups with higher FYN expression also had longer overall survival (p < 0.05). FYN expression had close correlation with infiltrating levels of cell purity, CD4+T cells, macrophages, and CD8+T cells (p < 0.05). Protein interaction network result showed correlation among FYN, SH2D1A, LCK, CAV1, SRC, CBL and PTK2. Functional enrichment analysis revealed that FYN and its related genes mainly participated in bacterial invasion of epithelial cells and natural killer cell mediated cytotoxicity. Peptidyl-tyrosine phosphorylation, negative regulation of anoikis, immune effector process, transmembrane receptor protein tyrosine kinase signaling pathway, epidermal growth factor receptor signaling pathway, and negative regulation of protein modification process may be the critical biological process. Conclusions: FYN is up-expressed in LGG and related to its good prognosis. It participated in tumor pathophysiological processes and may be a therapeutic target for LGG. [ABSTRACT FROM AUTHOR]

Endoplasmic reticulum stress (ERS) plays an essential role in the development of traumatic brain injury (TBI). We aimed to identify and validate the potential ERS-related genes of TBI through bioinformatics analysis and in vitro cell experiment. A total of 19 TBI and ERS-related genes were obtained from the GeneCards database and Comparative Toxicogenomics Database (CTD). Enrichment analysis primarily enriched in apoptosis. NFE2L2 was identified as a hub gene based on the protein–protein interactions (PPI) network that combined seven ranked methods included in cytoHubba. To further explore the effect of Nrf2, the protein encoded by NFE2L2, on ERS-induced apoptosis, we conducted cell experiments with tert-butylhydroquinone (tBHQ), the classical inducer of Nrf2. Western blot suggested tBHQ pretreatment could diminish ERS and reduce the protein expressions of apoptosis in the primary cultured neuron injury model. These data may establish some theoretical basis for the treatment of TBI and provide inspiration and innovative ideas for clinicians and pathologists to understand TBI comprehensively. [ABSTRACT FROM AUTHOR]