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Soy sauce cake (SSC) is a by-product of soy sauce production. SSC often goes underutilized due to its high salt content. To address this, halophilic bacterium was employed for SSC fermentation, aiming to release bioactive peptides in addition to the waste management advantages. Using a bioinformatics approach, in silico proteolysis of soy glycinin which was simulated with six selected proteases mined from the genomes of Virgibacillus spp. yielded 29 non-toxic antioxidant peptides, mainly two to three amino acids in size (250–360 Da). Approximately 59% of these peptides had acidic isoelectric points, negative net charges, and moderate Boman index values. Peptides HL, LW, and TY were predicted as non-allergens with positive human intestinal absorption. Furthermore, submerged fermentation of SSC by Virgibacillus sp. strain CD6 under optimal conditions (2.5% inoculum, 72-h fermentation) produced a hydrolysate with the highest peptide content (2.4 mg/g). This hydrolysate demonstrated potential ferric reducing antioxidant power (FRAP) (57%) and 1,1-diphenyl-2-picryl hydrazine (DPPH) radical scavenging activity (31%). This study pioneers the use of in silico methods and submerged fermentation with halophilic bacterium to enhance the value of high-salt SSC by releasing antioxidant peptides. It addresses waste disposal challenges and reveals new opportunities for SSC in food product development. [ABSTRACT FROM AUTHOR]

Cancer is a deadly disease that affects a cell's metabolism and surrounding tissues. Understanding the fundamental mechanisms of metabolic alterations in cancer cells would assist in developing cancer treatment targets and approaches. From this perspective, metabolomics is a great analytical tool to clarify the mechanisms of cancer therapy as well as a useful tool to investigate cancer from a distinct viewpoint. It is a powerful emerging technology that detects up to thousands of molecules in tissues and biofluids. Like other "‐omics" technologies, metabolomics involves the comprehensive investigation of micromolecule metabolites and can reveal important details about the cancer state that is otherwise not apparent. Recent developments in metabolomics technologies have made it possible to investigate cancer metabolism in greater depth and comprehend how cancer cells utilize metabolic pathways to make the amino acids, nucleotides, and lipids required for tumorigenesis. These new technologies have made it possible to learn more about cancer metabolism. Here, we review the cellular and systemic effects of cancer and cancer treatments on metabolism. The current study provides an overview of metabolomics, emphasizing the current technologies and their use in clinical and translational research settings. [ABSTRACT FROM AUTHOR]

To further understand the regulatory network and molecular mechanisms of gene expression after skin burns, we performed bioinformatics analysis of gene expression profiles of skin burn samples and identified key genes associated with skin burns. The GSE8056 and GSE139028 datasets were downloaded from the Gene Expression Omnibus database for analysis and validation. The limma package was used to screen for differentially expressed genes (DEGs). Gene ontology and pathway enrichment analyses (KEGG) were then performed. Subsequently, LASSO regression analysis was performed on DEGs and a regulatory network map of skin burn-related genes was constructed. Finally, the infiltration of immune cells was calculated and coexpression network maps of immune-related key genes and skin regeneration genes were constructed. Analysis of the GSE8056 dataset showed that 432 genes were upregulated and 351 genes were downregulated. The DEGs were mainly focused on immune response and skin regeneration. Meanwhile, these two groups of pivotal genes were significantly associated with abnormal infiltration of nine immune cells. GSE139028 validation revealed that three hub genes associated with skin burn immunity were differentially expressed, except for S100A8, while only the DPT gene was differentially expressed among the seven hub genes associated with skin regeneration. In short, the effect of skin burn on patients is to regulate the expression of immune-related genes UPP1, MMP1, MMP3, and skin regeneration-related gene DPT, which may be the key target for the treatment of skin burn. [ABSTRACT FROM AUTHOR]

Heat stroke (HS) is a severe medical condition characterized by a systemic inflammatory response that may precipitate multi-organ dysfunction, with a particular predilection for inducing profound central nervous system impairments. We aim to employ bioinformatics techniques for the retrieval and analysis of genes associated with heat stroke-induced neurological damage. We performed a comprehensive analysis of the GSE64778 dataset from the Sequence Read Archive, resulting in the identification of 1178 significantly differentially expressed genes (DEGs). We retrieved 2914 genes associated with heat stroke from the GeneCards database and 2377 genes associated with heat stroke from the Comparative Toxicogenomics Database (CTD). The intersection of the top 300 DEGs in the GSE64778 dataset intersected with the search results of GeneCards and CTD, yielding 25 final candidates for DEGs associated with heat stroke. Gene Ontology functional annotation results indicated that the target genes were mainly involved in apoptosis, stress response, and negative regulation of cellular processes and function in processes such as protein dimerization and protein binding. The Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed a predominant enrichment of candidate target genes within the PI3K-AKT signaling pathway. Subsequent protein–protein interaction network analysis highlighted HSP90aa1 as a central gene, indicating its pivotal role by possessing the highest number of edges among the genes enriched in the PI3K-AKT signaling pathway. Quantitative reverse transcription-polymerase chain reaction analysis performed on blood samples from patients validated the expression of Hsp90aa1 in individuals exhibiting early neurological damage in HS, consistent with the findings from the mRNA bioinformatics analysis. Additionally, the bioinformatics analysis of the upstream microRNAs (miRNAs) regulating HSP90aa1 and the target miRNAs associated with candidate long non-coding RNAs (lncRNAs) identified three lncRNAs, eight miRNAs, and one mRNA in the regulatory network. The DIANA Tools database and algorithms were employed for pathway enrichment and correlation analysis, revealing a significant association between LOC102547734 and MIR-206-3p, with the latter being identified as a target binding site Moreover, the analysis unveiled a correlation between MIR-206-3p and HSP90aa1, implicating the latter as a potential target binding site within the regulatory network. [ABSTRACT FROM AUTHOR]

Large language models (LLMs) offer transformative opportunities in bioinformatics education for medical students by creating interactive experiences. The integration of LLMs enhances educational outcomes through providing accessible code templates, clarifying the function of coding elements, and assisting in error troubleshooting. Here, we demonstrate the practical applications of LLMs with a case study on transcriptome sequencing data processing, a vital component of medical research. However, the reliability of the content that LLMs generate requires rigorous validation. Ensuring the accuracy and appropriateness of the LLM-generated information requires integrating innovative LLMs with traditional educational methods to prepare medical students effectively for future challenges in bioinformatics. [ABSTRACT FROM AUTHOR]

Copyright of Acta Prataculturae Sinica is the property of Acta Prataculturae Sinica Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Rising cancer-related mortality underscores the importance of biomarkers for treatment and prognosis, with Chromosome Segregation 1 Like (CSE1L) linked to various cancers yet its roles remain partially understood. This study investigates CSE1L's expression and oncogenic mechanisms in solid tumors. We analyzed multi-omics data from 31 solid tumors, measured CSE1L in 41 head and neck carcinoma patients post-chemotherapy via qRT-PCR, and evaluated the impact of CSE1L knockdown on cell proliferation in A549 and HepG2 cells. In this study, we observed significantly elevated levels of CSE1L RNA in 13 tumor tissues and protein levels in 8 tumor tissues compared to their corresponding adjacent normal tissues. Additionally, our investigation unveiled a correlation between heightened CSE1L expression in tumor tissues and worsened patient prognosis, poor response to immunotherapy, and diminished effectiveness of neoadjuvant chemotherapy. Through an analysis of CSE1L mechanisms, we discovered its potential involvement in promoting tumor cell proliferation, enhancing drug resistance, and influencing immune infiltration, thereby impacting patient prognosis and treatment outcomes. Finally, we delved into the potential mechanisms underlying upregulation of CSE1L in tumor tissues. Our findings demonstrate that CSE1L promotes tumor development in various malignancies, highlighting its potential as both a therapeutic target and prognostic indicator. [ABSTRACT FROM AUTHOR]

Fusarium oxysporum f.sp. lycopersici is a phytopathogen which causes vascular wilt disease in tomato plants. The survival tactics of both pathogens and hosts depend on intricate interactions between host plants and pathogenic microbes. Iron‐binding proteins (IBPs) and copper‐binding proteins (CBPs) play a crucial role in these interactions by participating in enzyme reactions, virulence, metabolism, and transport processes. We employed high‐throughput computational tools at the sequence and structural levels to investigate the IBPs and CBPs of F. oxysporum. A total of 124 IBPs and 37 CBPs were identified in the proteome of Fusarium. The ranking of amino acids based on their affinity for binding with iron is Glu > His> Asp > Asn > Cys, and for copper is His > Asp > Cys respectively. The functional annotation, determination of subcellular localization, and Gene Ontology analysis of these putative IBPs and CBPs have unveiled their potential involvement in a diverse array of cellular and biological processes. Three iron‐binding glycosyl hydrolase family proteins, along with four CBPs with carbohydrate‐binding domains, have been identified as potential effector candidates. These proteins are distinct from the host Solanum lycopersicum proteome. Moreover, they are known to be located extracellularly and function as enzymes that degrade the host cell wall during pathogen–host interactions. The insights gained from this report on the role of metal ions in plant–pathogen interactions can help develop a better understanding of their fundamental biology and control vascular wilt disease in tomato plants. [ABSTRACT FROM AUTHOR]

Cosmos caudatus is a widely used traditional medicinal plant in Indonesia for cancer treatment. However, the mechanism of action of plants in treating breast neoplasms remains unclear. Thus, the active ingredients of C. caudatus and possible molecular pathways against breast neoplasms were investigated using pharmacological networks. The active compounds were screened using Lipinski and ADME parameters. Targets for the compounds were obtained using SwissTargetPrediction. Target diseases were identified using the Therapeutic Target Database, whereas disease pathways were analyzed using the Kyoto Encyclopedia of Genes and Genomes. Network pharmacology was constructed using Cytoscape. Protein-protein interactions were constructed using STRING. Gene ontology and KEGG were analyzed using DAVID. Molecular docking confirmed that the compounds and targets exhibited the best interactions. The compounds, targets, and pathways with the highest degrees in the breast neoplasm network were eriodictyol, ABCC1, and signal transduction, respectively. EGFR is the key target of PPIs. GO enrichment in BP, MF, CC, and KEGG regulated NF-KB transcription factor activity, chromatin, transcription coactivator binding, and pathways in cancer, respectively. Molecular docking with the best score on interaction 5-O-methylvisammioside-SLC2A1 (PDB ID: 6THA) (-10.3 kcal mol-1). The compound 5-O-methylvisammioside may have pharmacological activity in breast cancer through signal transduction pathways. [ABSTRACT FROM AUTHOR]

Alcohol abuse, also known as Alcohol Use Disorder (AUD), is a substance dependency psychiatric disorder. We aimed to establish a causal relationship between specific gut microbiota and alcohol abuse using Mendelian Randomisation (MR) and bioinformatics methods. We acquired summary data of genome-wide association studies (GWAS) for gut microbiota and alcohol abuse from the Mibiogen and Finngen databases, respectively. We conducted MR analyses using various methodologies and mapped the single nucleotide polymorphisms (SNPs) to genes via the FUMA GWAS platform. We further performed multiple enrichment analyses and a Multi-variable Mendelian Randomisation (MVMR) approach to examine whether gut microbiota influences alcohol abuse by modulating neurotransmitter-related amino acids. The MR analysis revealed an inverse relationship between the genus Eubacterium ventriosum group and the Porphyromonadaceae family with alcohol abuse. Gene enrichment analysis showed that these genes are expressed in brain tissue and are involved in addictive disorders, psychiatric conditions, immunological processes, neurotransmitter synthesis and synaptic regulation. MVMR analysis suggested that the Porphyromonadaceae family as well as genus Eubacterium ventriosum group may suppress alcohol abuse through the metabolism of neurotransmitter-related amino acids, especially Tryptophan. The MR analysis and bioinformatics investigations indicate that the genus Eubacterium ventriosum group and Porphyromonadaceae family confer a protective effect against alcohol abuse, potentially through the modulation of synaptic function. [ABSTRACT FROM AUTHOR]

Copyright of Turkish Journal of Obstetrics & Gynecology is the property of Galenos Yayinevi Tic. LTD. STI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Epimedium is a traditional Chinese medicine with a wide range of clinical applications; however, there have been numerous reports of adverse reactions in recent years. The most common side effect of Epimedium is liver injury. In this study, the liquid chromatography–mass spectrometry (LC–MS) method has been established to study the components of Epimedium and to identify the components absorbed into the blood of rats. Bioinformatics was used to screen out potential toxic components, and the integrating metabolomics method was used to explore the molecular mechanism of Epimedium‐induced liver injury. The chemical constituents of Epimedium were identified by LC–MS, and 62 compounds were obtained, including 57 flavonoids, four organic acids and one alkaloid. The toxicity network of "Epimedium–component–target–liver injury" was constructed using bioinformatics research methods, and then the key hepatotoxic component icaritin was identified. Integrating metabolomics was used to investigate the changes in the metabolic profile of L‐02 cells with different durations of icaritin administration compared with the control group, and 106 different metabolites were obtained. A total of 14 potential biomarkers significantly associated with cell survival were screened by Pearson correlation analysis combined with the L‐02 cell survival rate. Our study preliminarily revealed the mechanism of hepatotoxicity induced by Epimedium. [ABSTRACT FROM AUTHOR]

Transfer RNA‐derived small RNAs (tsRNAs) refer to a newly established family of non‐coding RNAs that regulate a diverse set of biological processes. However, the function of tsRNAs in skin photoaging remains unclear. This research aims to investigate the potential correlation between tsRNAs and skin photoaging. Human dermal fibroblasts (HDFs) were irradiated with UVA at 10 J/cm2 once a day lasting for 14 days, resulting in the establishment of a photoaging model induced by UVA. To identify the expression profiles and functions of tsRNAs, tsRNA sequencing and bioinformatics analysis were conducted. qPCR was employed to validate the results of differentially expressed (DE) tsRNAs. A total of 34 tsRNAs exhibited significant differential expression between the UVA and control groups (n = 3), with nine upregulated and 25 downregulated (log2 fold change >1.5, p‐value <0.05). Six tsRNAs were selected at random and validated by qRT‐PCR. The enrichment analysis of DE tsRNAs target genes indicated that the dysregulated tsRNAs appeared to be connected with cell cycle, DNA replication and the AGE‐RAGE signaling pathway. The expression of tsRNAs was found to be aberrant in UVA‐HDF. These findings provide insights into the UVA‐induced damage and potential target genes for skin photoaging. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to preliminarily investigate the association and possible mechanisms between Helicobacter. pylori (H. pylori) infection and type 2 diabetes mellitus (T2DM) through data collection, statistical analysis, and bioinformatics analysis. Methods: A retrospective cohort study, including a total of 4406 participants who attended annual health checkups at Xian GEM Flower Changqing Hospital, was conducted to explore the correlation between the incidence of T2DM and H. pylori infection. To uncover the potential mechanisms underlying the interaction between the two diseases, differentially expressed genes (DEGs) common to T2DM and H. pylori infection were identified using the GEO database and Venn diagrams. These DEGs were then analyzed through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein-protein interaction (PPI) analysis. Results: In total, 2053 participants were classified into the H. pylori-positive group and 2353 into the H. pylori-negative group. H. pylori infection was associated with a higher risk of T2DM occurrence (adjusted HR 1.59; 95% CI 1.17–2.15, P = 0.003). The average disease-free survival time was 34.81 months (95% CI 34.60-35.03 months) in the H. pylori positive group and 35.42 months (95% CI 35.28–35.56 months) in the H. pylori negative group. Multivariate analysis and subgroup analyses also showed that H. pylori infection increased the risk of developing T2DM. A total of 21 DEGs between T2DM and H. pylori infection were identified and enriched in 7 signaling pathways, indicating specific protein interactions. Conclusions: The prevalence of T2DM was associated with H. pylori infection. T2DM and H. pylori infection may interact with each other through metabolic and immune pathways. [ABSTRACT FROM AUTHOR]

Background: Asthma, a prevalent chronic inflammatory disorder, is shaped by a multifaceted interplay between genetic susceptibilities and environmental exposures. Despite strides in deciphering its pathophysiological landscape, the intricate molecular underpinnings of asthma remain elusive. The focus has increasingly shifted toward the metabolic aberrations accompanying asthma, particularly within the domain of pyrimidine metabolism (PyM)—a critical pathway in nucleotide synthesis and degradation. While the therapeutic relevance of PyM has been recognized across various diseases, its specific contributions to asthma pathology are yet underexplored. This study employs sophisticated bioinformatics approaches to delineate and confirm the involvement of PyM genes (PyMGs) in asthma, aiming to bridge this significant gap in knowledge. Methods: Employing cutting-edge bioinformatics techniques, this research aimed to elucidate the role of PyMGs in asthma. We conducted a detailed examination of 31 PyMGs to assess their differential expression. Through Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA), we explored the biological functions and pathways linked to these genes. We utilized Lasso regression and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) to pinpoint critical hub genes and to ascertain the diagnostic accuracy of eight PyMGs in distinguishing asthma, complemented by an extensive correlation study with the clinical features of the disease. Validation of the gene expressions was performed using datasets GSE76262 and GSE147878. Results: Our analyses revealed that eleven PyMGs—DHODH, UMPS, NME7, NME1, POLR2B, POLR3B, POLR1C, POLE, ENPP3, RRM2B, TK2—are significantly associated with asthma. These genes play crucial roles in essential biological processes such as RNA splicing, anatomical structure maintenance, and metabolic processes involving purine compounds. Conclusions: This investigation identifies eleven PyMGs at the core of asthma's pathogenesis, establishing them as potential biomarkers for this disease. Our findings enhance the understanding of asthma's molecular mechanisms and open new avenues for improving diagnostics, monitoring, and progression evaluation. By providing new insights into non-cancerous pathologies, our work introduces a novel perspective and sets the stage for further studies in this field. [ABSTRACT FROM AUTHOR]

Background. T cell exhaustion (TEX) is a state of T cells that is characterized by poor function of effectors and increased expression of inhibitory signals. However, the heterogeneity and prognostic values of TEX in lung adenocarcinoma (LUAD) remain not fully understood. Methods. Based on the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) transcriptomic profiles, we screened differentially expressed lncRNAs, miRNAs, and mRNAs and identified differentially expressed TEXs. Univariate cox and LASSO regression analyses were performed to construct TEX‐related prognostic signature and risk score and validated their expression using real‐time PCR assay. We then investigated the potential mechanism, immune landscape, and antitumor therapy response in LUAD. Results. A total of 315 DE‐lncRNAs, 161 DE‐miRNAs, and 2589 DEGs were screened, and then 80 DE‐TEXGs were identified in LUAD. Based on univariate cox and LASSO regression analyses, CCNA2 and SLC2A1 were identified as TEX‐related prognostic signatures, and the risk score subsequently was calculated. LUAD patients were divided into high‐ and low‐risk groups, and high‐risk groups were involved in poor survival status, immunosuppression, and more sensitive to anti‐CTLA4 therapy. Finally, a TEX‐related ceRNA network was constructed and validated based on DE‐lncRNAs, DE‐miRNAs, and TEX‐related prognostic signatures. Conclusion. We constructed the TEX‐related prognostic signature and its relevant ceRNA network and discovered the molecular mechanism and prognostic values of TEX in LUAD. [ABSTRACT FROM AUTHOR]

Efforts to enhance the accuracy of protein sequence classification are of utmost importance in driving forward biological analyses and facilitating significant medical advancements. This study presents a cutting-edge model called ProtICNN-BiLSTM, which combines attention-based Improved Convolutional Neural Networks (ICNN) and Bidirectional Long Short-Term Memory (BiLSTM) units seamlessly. Our main goal is to improve the accuracy of protein sequence classification by carefully optimizing performance through Bayesian Optimisation. ProtICNN-BiLSTM combines the power of CNN and BiLSTM architectures to effectively capture local and global protein sequence dependencies. In the proposed model, the ICNN component uses convolutional operations to identify local patterns. Captures long-range associations by analyzing sequence data forward and backwards. In advanced biological studies, Bayesian Optimisation optimizes model hyperparameters for efficiency and robustness. The model was extensively confirmed with PDB-14,189 and other protein data. We found that ProtICNN-BiLSTM outperforms traditional categorization models. Bayesian Optimization's fine-tuning and seamless integration of local and global sequence information make it effective. The precision of ProtICNN-BiLSTM improves comparative protein sequence categorization. The study improves computational bioinformatics for complex biological analysis. Good results from the ProtICNN-BiLSTM model improve protein sequence categorization. This powerful tool could improve medical and biological research. The breakthrough protein sequence classification model is ProtICNN-BiLSTM. Bayesian optimization, ICNN, and BiLSTM analyze biological data accurately. [ABSTRACT FROM AUTHOR]

Background: Disulfidptosis is an emerging form of cellular death resulting from the binding of intracellular disulfide bonds to actin cytoskeleton proteins. This study aimed to investigate the expression and prognostic significance of hub disulfidptosis-related lncRNAs (DRLRs) in R0 resected hepatocellular carcinoma (HCC) as well as their impact on the malignant behaviour of HCC cells. Methods: A robust signature for R0 resected HCC was constructed using least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression and was validated in an independent internal validation cohort to predict the prognosis of R0 HCC patients. Comprehensive bioinformatics analysis was performed on the hub DRLRs (KDM4A-AS1, MKLN1-AS, and TMCC1-AS1), followed by experimental validation using quantitative real-time polymerase chain reaction (qRT‒PCR) and cellular functional assays. Results: The signature served as an independent prognostic factor applicable to R0 HCC patients across different age groups, tumour stages, and pathological characteristics. Gene Ontology (GO) and gene set enrichment analysis (GSEA) revealed hub pathways associated with this signature. The high-risk group presented an increased abundance of M0 macrophages and activated memory CD4 T cells as well as elevated macrophage and major histocompatibility complex (MHC) class I expression. High-risk R0 HCC patients also presented increased tumour immune dysfunction and exclusion scores (TIDEs), mutation frequencies, and tumour mutational burdens (TMBs). Drug sensitivity analysis revealed that high-risk patients were more responsive to drugs, including GDC0810 and osimertinib. High expression levels of the three hub DRLRs were detected in R0 HCC tissues and HCC cell lines. Functional assays revealed that the three hub DRLRs enhanced HCC cell proliferation, migration, and invasion. Conclusions: A signature was constructed on the basis of three DRLRs, providing novel insights for personalized precision therapy in R0 HCC patients. [ABSTRACT FROM AUTHOR]

In recent years, as more and more lung-cancer patients have been treated with immunotherapeutic agents, their survival has been prolonged compared to before. It is well known that BTK (Bruton's tyrosine kinase) is predominantly found in cells of the hematopoietic system. However, there is a distinct lack of literature on BTK expression in lung adenocarcinoma (LUAD) patients and its effect on the immune microenvironment. Consequently, the main goal of this investigation was to analyze how BTK expression in lung adenocarcinoma affects its progression, along with its prognostic significance, through the utilization of bioinformatics online resources and publicly available databases. Data on the sequencing results and clinical records of lung adenocarcinoma patients were gathered from The Cancer Genome Atlas (TCGA) database. Based on the expression level of BKT, TCGA categorized lung adenocarcinoma patients into BTK high-expression and low-expression groups. We investigated the effects of BKT on clinicopathologic, genomic, and immunologic characteristics of lung adenocarcinoma patients. We analyzed BTK mRNA expression in tumors and normal tissues using two key resources: Tumor Immuno Estimation Resource 2.0 (TIMER 2.0) and Gene Expression Profiling Interactive Analysis 2 (GEPIA 2). We analyzed the prognosis of the patients using GEPIA2 and validated the results using univariate and multivariate analyses. In addition, we assessed BTK protein expression by Human Protein Atlas (HPA). We sought to elucidate the clinical prognostic significance of BTK in The TCGA using the online tool GEPIA 2. Furthermore, to clarify the biologic roles and pathways linked to BTK, we conducted a genomic enrichment analysis of the information. To predict the proportion of various immune cell infiltrations in the immune microenvironment of lung adenocarcinoma patients diagnosed in the TCGA database, we performed an analysis using the TIMER online tool. Using TIMER and CIBERSORT, the correlation between genes co-expressed with BTK and the corresponding tumor-infiltrating immune cells was explored; finally, the relationship between BTK expression and immune infiltration and immune checkpoints in the TMB group and the high and low groups was analyzed by R language analysis using the TCGA database. The expression of BTK provides some hints about the prognosis of the patients. The high expression of BTK is involved in immune response regulation signaling pathways, leukocyte-mediated immunity, leukocyte intercellular adhesion, graft rejection, and complement. Analysis of the GEPIA 2 database showed that BTK was co-expressed with the genes FGD2, SASH3, NCKAP1L, CD53, ARHGAP30 and LPXN. Increased expression of the above-mentioned genes resulted in increased proportions of CD8 + T cells, memory CD4 + T cells, B cells, macrophages, and dendritic cells, and decreased proportions of Treg cells and TH2 cells. In addition, our study revealed a strong positive correlation between various key immune checkpoints (e.g., PDCD1, CD274, PDCD1LG2, CTLA4, HAVCR2, LAG3, TIGIT, and SIGLEC15) and BTK expression. In conclusion, increased BTK expression in lung adenocarcinoma is closely associated with prolonged survival of lung-cancer patients. Moreover, the genes classified under the BTK high-expression group exhibit significant enrichment in immune-related pathways, suggesting a potential impact on the tumor microenvironment. We investigated the potential of BTK as a tumor suppressor gene in predicting prolonged patient survival. In addition, we further investigated the possibility that BTK further affects the immunotherapeutic response of patients by influencing the microenvironment of tumor immune infiltration, but the relevant mechanisms remain to be further studied. [ABSTRACT FROM AUTHOR]

Background and aim: Pathological changes in the central nervous system (CNS) begin before the clinical symptoms of Alzheimer's Disease (AD) manifest, with the hippocampus being one of the first affected structures. Current treatments fail to alter AD progression. Traditional Chinese medicine (TCM) has shown potential in improving AD pathology through multi-target mechanisms. This study investigates pathological changes in AD hippocampal tissue and explores TCM active components that may alleviate these changes. Methods: GSE5281 and GSE173955 datasets were downloaded from GEO and normalized to identify differentially expressed genes (DEGs). Key functional modules and hub genes were analyzed using Cytoscape and R. Active TCM components were identified from literature and the Pharmacopoeia of the People's Republic of China. Enrichment analyses were performed on target genes overlapping with DEGs. Result: From the datasets, 76 upregulated and 363 downregulated genes were identified. Hub genes included SLAMF, CD34, ELN (upregulated) and ATP5F1B, VDAC1, VDAC2, HSPA8, ATP5F1C, PDHA1, UBB, SNCA, YWHAZ, PGK1 (downregulated). Literature review identified 33 active components from 23 herbal medicines. Target gene enrichment and analysis were performed for six components: dihydroartemisinin, berberine, naringenin, calycosin, echinacoside, and icariside II. Conclusion: Mitochondrial to synaptic vesicle dysfunction pathways were enriched in downregulated genes. Despite downregulation, UBB and SNCA proteins accumulate in AD brains. TCM studies suggest curcumin and echinacoside may improve hippocampal pathology and cognitive impairment in AD. Further investigation into their mechanisms is needed. [ABSTRACT FROM AUTHOR]

Background: Deep vein thrombosis (DVT) of lower extremity is a common complications after total knee arthroplasty (TKA). The purpose of this study was to evaluate the risk factors for DVT after TKA and analyze the expression of miR-199b-5p and nitric oxide (NO) before and after TKA, as well as their predictive value for DVT. Methods: Basic clinical information of 121 patients with TKA was analyzed retrospectively. RT-qPCR was used to detect the relative expression level of miR-199b-5p in patients before and after TKA treatment. Based on the occurrence of DVT, patients were divided into DVT and non-DVT groups. Logistic regression analysis evaluated the risk factors of DVT. The receiver operating characteristic (ROC) curve assessed the predictive value of postoperative miR-199b-5p level, preoperative NO level, and their combination in DVT. The target genes of miR-199b-5p and their functions were predicted and annotated using bioinformatics analysis. Results: The level of miR-199b-5p after TKA was upregulated compared with that before TKA (P < 0.001). DVT occurred in 20 of 121 patients after TKA, with an incidence of 16.53%. Multivariate analysis showed that age, family history of DVT, decrease of NO and increase of miR-199b-5p were risk factors for DVT after TKA (P < 0.05). The ROC curve showed that both miR-199b-5p and NO had certain diagnostic value for DVT, but the combination of miR-199b-5p and NO had the highest diagnostic accuracy (P < 0.001). Conclusion: This study showed that the expression of miR-199b-5p was up-regulated after TKA, and miR-199b-5p levels were higher in DVT patients than in non-DVT patients. miR-199b-5p combined with NO is of great value in the diagnosis of DVT after TKA. [ABSTRACT FROM AUTHOR]

Background: The progression of tumours is related to abnormal phospholipid metabolism. This study is anticipated to present a fresh perspective for disease therapy targets of hepatocarcinoma caused by hepatitis B virus in the future by screening feature genes related to phospholipid metabolism. Methods: This study analysed GSE121248 to pinpoint differentially expressed genes (DEGs). By examining the overlap between the metabolism-related genes and DEGs, the research focused on the genes involved in phospholipid metabolism. To find feature genes, functional enrichment studies were carried out and a network diagram was proposed. These findings were validated via data base of The Cancer Genome Atlas (TCGA). Further analyses included immune infiltration studies and metabolomics. Finally, the relationships between differentially abundant metabolites and feature genes were confirmed by molecular docking, providing a thorough comprehension of the molecular mechanisms. Results: The seven genes with the highest degree of connection (PTGS2, IGF1, SPP1, BCHE, NR1I2, NAMPT, and FABP1) were identified as feature genes. In the TCGA database, the seven feature genes also had certain diagnostic efficiency. Immune infiltration analysis revealed that feature genes regulate the infiltration of various immune cells. Metabolomics successfully identified the different metabolites of the phospholipid metabolism pathway between patients and normal individuals. The docking study indicated that different metabolites may play essential roles in causing disease by targeting feature genes. Conclusions: In this study, for the first time, it reveals the possible involvement of genes linked to phospholipid metabolism-related genes using bioinformatics analysis. Identifying genes and probable therapeutic targets could provide clues for the further treatment of disease. [ABSTRACT FROM AUTHOR]

Background: Growing evidence suggests that distal regulatory elements are essential for cellular function and states. The sequences within these distal elements, especially motifs for transcription factor binding, provide critical information about the underlying regulatory programs. However, cooperativities between transcription factors that recognize these motifs are nonlinear and multiplexed, rendering traditional modeling methods insufficient to capture the underlying mechanisms. Recent development of attention mechanism, which exhibit superior performance in capturing dependencies across input sequences, makes them well-suited to uncover and decipher intricate dependencies between regulatory elements. Result: We present Transcription factors cooperativity Inference Analysis with Neural Attention (TIANA), a deep learning framework that focuses on interpretability. In this study, we demonstrated that TIANA could discover biologically relevant insights into co-occurring pairs of transcription factor motifs. Compared with existing tools, TIANA showed superior interpretability and robust performance in identifying putative transcription factor cooperativities from co-occurring motifs. Conclusion: Our results suggest that TIANA can be an effective tool to decipher transcription factor cooperativities from distal sequence data. TIANA can be accessed through: https://github.com/rzzli/TIANA. [ABSTRACT FROM AUTHOR]

The EphA family belongs to a large group of membrane receptor tyrosine kinases. Emerging evidence indicates that the EphA family participates in tumour occurrence and progression. Nonetheless, the expression patterns and prognostic values of the nine EphAs in non-small cell lung cancer (NSCLC) have rarely been studied before. In the current study, we comprehensively analysed the expression and prognostic role of EphA family members by different means. The Cancer Genome Atlas and Gene Expression Profiling Interactive Analysis databases were used to investigate the expression of EphAs in NSCLC. The cBioPortal database was applied to analyse the prognostic values and genetic mutations of EphAs.We discovered that the expression of EphA10 was significantly higher in NSCLC tissues than in adjacent noncancerous tissues, and survival analyses showed that a higher level of EphA10 predicted poor prognosis. Further exploration into the role of EphA10 by ESTIMATE, CIBERSORT, and ssGSEA analysis found that it was also related to immune infiltration and higher expression of targets of ICI targets. In conclusion, this study revealed that among the EphA family members, EphA10 played an oncogenic role and was a promising biomarker for poor prognosis and better immunotherapy response in NSCLC. [ABSTRACT FROM AUTHOR]

Background: In this study, we present a novel method for reference-based cell deconvolution using data from DNA methylation arrays. Different from existing methods like IDOL-Ext, which operate on probe-level data, our approach represents features in the principal component analysis (PCA) space for cell type deconvolution. Results: Our method's accuracy in estimating cell compositions is validated across various public datasets, including blood samples from glioma patients. It demonstrates precision comparable to IDOL-Ext, with R2 values ranging from 0.73 to 0.99 for most cell types, while offering improved discrimination between similar cell types, particularly T cell subtypes in glioma patient samples (R2 0.42–0.75 vs. 0.36–0.66 for IDOL-Ext). However, both methods showed lower accuracy for certain cell types, such as memory CD8 T cells in glioma patients (R2 0.42 vs. 0.36 for IDOL-Ext), highlighting the challenges in distinguishing closely related cell populations. We have made this method available as an R package "BloodCellDecon" on GitHub. Conclusions: Our study confirms the efficacy of cell type deconvolution in PCA space. The results indicate wide-ranging applicability and potential for adaptation to other forms of genomic data. [ABSTRACT FROM AUTHOR]

Background: Treatment of gliomas, the most prevalent primary malignant neoplasm of the central nervous system, is challenging. Arachidonate 5-lipoxygenase activating protein (ALOX5AP) is crucial for converting arachidonic acid into leukotrienes and is associated with poor prognosis in multiple cancers. Nevertheless, its relationship with the prognosis and the immune microenvironment of gliomas remains incompletely understood. Methods: The differential expression of ALOX5AP was evaluated based on public Databases. Kaplan–Meier, multivariate Cox proportional hazards regression analysis, time-dependent receiver operating characteristic, and nomogram were used to estimate the prognostic value of ALOX5AP. The relationship between ALOX5AP and immune infiltration was calculated using ESTIMATE and CIBERSORT algorithms. Relationships between ALOX5AP and human leukocyte antigen molecules, immune checkpoints, tumor mutation burden, TIDE score, and immunophenoscore were calculated to evaluate glioma immunotherapy response. Single gene GSEA and co-expression network-based GO and KEGG enrichment analysis were performed to explore the potential function of ALOX5AP. ALOX5AP expression was verified using multiplex immunofluorescence staining and its prognostic effects were confirmed using a glioma tissue microarray. Result: ALOX5AP was highly expressed in gliomas, and the expression level was related to World Health Organization (WHO) grade, age, sex, IDH mutation status, 1p19q co-deletion status, MGMTp methylation status, and poor prognosis. Single-cell RNA sequencing showed that ALOX5AP was expressed in macrophages, monocytes, and T cells but not in tumor cells. ALOX5AP expression positively correlated with M2 macrophage infiltration and poor immunotherapy response. Immunofluorescence staining demonstrated that ALOX5AP was upregulated in WHO higher-grade gliomas, localizing to M2 macrophages. Glioma tissue microarray confirmed the adverse effect of ALOX5AP in the prognosis of glioma. Conclusion: ALOX5AP is highly expressed in M2 macrophages and may act as a potential biomarker for predicting prognosis and immunotherapy response in patients with glioma. [ABSTRACT FROM AUTHOR]

Background: Breast cancer, one of the most prevalent malignancies among women worldwide, has rising incidence rates. Physical activity, particularly exercise, has emerged as a significant modifier of cancer prognosis, influencing both tumor biology and patient outcomes. Methods: In this study, we utilized a murine breast cancer model, dividing mice into a control group and an exercise group; the latter underwent 21 days of voluntary running. We conducted RNA sequencing, bioinformatics analysis, pancancer analysis, and cellular experiments to investigate the underlying mechanisms influenced by exercise. Results: Exercise led to a significant reduction in tumor size and weight. Postexercise mRNA sequencing indicated a notable upregulation of THSD7B in the exercised mice, with significant alterations observed in pathways such as MicroRNAs in cancers and the Calcium signaling pathway. In a broader cancer context, THSD7B showed considerable expression variability, being significantly downregulated in several cancers, correlating with positive prognostic outcomes in PRAD, LAML, KIRC, and GBM and highlighting its potential role as a prognostic marker and therapeutic target. THSD7B expression was also negatively associated with processes of breast cancer cell proliferation, migration, and invasion. Conclusion: This study underscores the dual role of exercise in modulating gene expression relevant to tumor growth and highlights the potential of THSD7B as a therapeutic target in cancer. Future research should further explore the specific mechanisms by which exercise and THSD7B influence cancer progression and develop immunotherapy-enhanced strategies to change patient outcomes in clinical settings. [ABSTRACT FROM AUTHOR]

Background: To investigate the effects of Isoorientin on the apoptosis, proliferation, invasion, and migration of human gastric cancer cells (HGC27 cells). Methods: We used network pharmacology to predict the targets of drugs and diseases. The CCK-8 assay was used to determine the effects of Isoorientin on the proliferation of HGC27 cells. Flow cytometry was employed to analyze the effects of Isoorientin on cell apoptosis and cell cycle distribution of HGC27 cells. Scratch test and transwell chamber test were conducted to assess the effects of Isoorientin on invasion and migration, respectively. Additionally, qPCR and western blot were performed to examine the impact of Isoorientin on apoptosis-related genes and protein expression, respectively. Results: The Isoorientin significantly inhibited the proliferation, migration, and invasion of HGC27 cells compared to the control group. Furthermore, Isoorientin induced apoptosis in HGC27 cells by upregulating the relative expression of Bax and caspase-3 while downregulating the relative expression of p-PI3K, p-AKT, and Bcl-2 proteins. Conclusion: The Isoorientin exhibits inhibitory effects on the proliferation, invasion, and migration of HGC27 cells, and induces apoptosis in gastric cancer cells. [ABSTRACT FROM AUTHOR]

Cloning and obtaining the coding region sequence of the p65 gene in the NF-κ B family from the brain tissue of Micropterus salmoides, with a total cDNA length of 1 944 bp, the ORF is 1 899 bp and can encode 632 amino acids. The theoretical molecular weight is 69.61 ku, and the theoretical isoelectric point (PI) is 5.66. The protein structure of the p65 gene was analyzed using bioinformatics analysis tools, and its protein function was predicted.The results showed that the gene does not contain a signal peptide sequence and does not have a transmembrane domain, but there is a conserved domain in the NF-κ B family. The results of multiple sequence alignment show that the similarity between Micropterus salmoides p65 and Micropterus dolomieu is the highest, at 99.30%; constructing a phylogenetic tree, it was discovered that the Micropterus salmoides p65 and Micropterus dolomieu clustered together. The results of qRT PCR indicate that the Micropterus salmoides p65 gene is expressed in all selected tissues, with the highest expression level in brain tissue, followed by the head kidney, thymus, and heart, and the lowest expression level in spleen tissue. [ABSTRACT FROM AUTHOR]

Background: Individuals with Down syndrome (DS) have intellectual disability and develop Alzheimer's disease (AD) pathology during midlife, particularly in the hippocampal component of the medial temporal lobe memory circuit. However, molecular and cellular mechanisms underlying selective vulnerability of hippocampal CA1 neurons remains a major knowledge gap during DS/AD onset. This is compounded by evidence showing spatial (e.g., deep versus superficial) localization of pyramidal neurons (PNs) has profound effects on activity and innervation within the CA1 region. Objective: We investigated whether there is a spatial profiling difference in CA1 PNs in an aged female DS/AD mouse model. We posit dysfunction may be dependent on spatial localization and innervation patterns within discrete CA1 subfields. Methods: Laser capture microdissection was performed on trisomic CA1 PNs in an established mouse model of DS/AD compared to disomic controls, isolating the entire CA1 pyramidal neuron layer and sublayer microisolations of deep and superficial PNs from the distal CA1 (CA1a) region. Results: RNA sequencing and bioinformatic inquiry revealed dysregulation of CA1 PNs based on spatial location and innervation patterns. The entire CA1 region displayed the most differentially expressed genes (DEGs) in trisomic mice reflecting innate DS vulnerability, while trisomic CA1a deep PNs exhibited fewer but more physiologically relevant DEGs, as evidenced by bioinformatic inquiry. Conclusions: CA1a deep neurons displayed numerous DEGs linked to cognitive functions whereas CA1a superficial neurons, with approximately equal numbers of DEGs, were not linked to pathways of dysregulation, suggesting the spatial location of vulnerable CA1 PNs plays an important role in circuit dissolution. [ABSTRACT FROM AUTHOR]

Background: Osteosarcoma (OS) is a malignant bone tumor that commonly occurs in children and adolescents under the age of 20. Dysregulation of microRNAs (miRNAs) is an important factor in the occurrence and progression of OS. MicroRNA miR-744-5p is aberrantly expressed in various tumors. However, its roles and molecular targets in OS remain unclear. Methods: Differentially expressed miRNAs in OS were analyzed using the Gene Expression Omnibus dataset GSE65071, and the potential hub miRNA was identified through weighted gene co-expression network analysis. Quantitative real-time PCR (qRT-PCR) was used to detect the expression of miR-744-5p in OS cell lines. In vitro experiments, including CCK-8 assays, colony formation assays, flow cytometry apoptosis assays, and tube formation assays, were performed to explore the effects of miR-744-5p on OS cell biological behaviors. The downstream target genes of miR-744-5p were predicted through bioinformatics, and the binding sites were validated by a dual-luciferase reporter assay. Results: The lowly expressed miRNA, miR-744-5p, was identified as a hub miRNA involved in OS progression through bioinformatic analysis. Nuclear factor I X (NFIX) was confirmed as a direct target for miR-744-5p in OS. In vitro studies revealed that overexpression of miR-744-5p could restrain the growth of OS cells, whereas miR-744-5p inhibition showed the opposite effect. It was also observed that treatment with the conditioned medium from miR-744-5p-overexpressed OS cells led to poorer proliferation and angiogenesis in human umbilical vein endothelial cells (HUVECs). Furthermore, NFIX overexpression restored the suppression effects of miR-744-5p overexpression on OS cell growth and HUVECs angiogenesis. Conclusion: Our results indicated that miR-744-5p is a potential tumor-suppressive miRNA in OS progression by targeting NFIX to restrain the growth of OS cells and angiogenesis in HUVECs. [ABSTRACT FROM AUTHOR]

Background: Wild food plants (WFPs) play an important role in the traditional dietary habits of various indigenous communities worldwide, particularly in mountainous regions. To understand the dynamics of food preferences, cross-cultural studies on food plants should be conducted across diverse ethnic groups in a given area. In this context, the current study investigated the use of WFPs by seven different cultural groups in the Kashmir Himalayan Region. In this area, people gather wild plants and their parts for direct consumption, traditional foods, or sale in local markets. Despite this reliance, documentation of the food system, especially concerning WFPs, is notably lacking. Hence, our research aimed to document WFPs, along with associated traditional ecological knowledge, and identify major threats to their long-term sustainability in Division Muzaffarabad. Methods: Through a comprehensive approach involving questionnaires, interviews, focus groups, and market surveys, we gathered data from 321 respondents. PCA was performed to analyze threats and plant use using "factoextra" in R software. Origin Pro was used to create a chord diagram, while R software was used to generate a Polar heat map. Additionally, a Venn diagram was created using Bioinformatics software. Results: The study included 321 informants, of whom 75.38% were men and 24.61% were women. In total, 113 plant taxa from 74 genera and 41 botanical families were reported. Polygonaceae and Rosaceae accounted for the majority (17 species each), followed by Lamiaceae (7 species). Leaves were the most used part as food sources (41.04%), followed by fruits (33.33%). Most of the species are consumed as cooked (46.46%) and as raw snacks (37.80%). A total of 47 plant species were collected and cooked as wild vegetables, followed by 40 species used as fruits. This study is the first to describe the market potential and ecological distribution of WFPs in the study area. Cross-comparison showed that utilization of WFPs varies significantly across the region and communities, including their edible parts and mode of consumption. Jaccard index (JI) value ranged from 5.81 to 25. Furthermore, the current study describes 29 WFPs and 10 traditional food dishes that have rarely been documented in Pakistan's ethnobotanical literature. Climate change, invasive species, expansion of agriculture, and plant diseases are some of the most significant threats to WFPs in the study area. Conclusions: The older age group has more knowledge about WFPs compared to the younger generation, who are not interested in learning about the utilization of WFPs. This lack of interest in information about WFPs among the younger generation can be attributed to their limited access to markets and availability of food plants in the study area. Traditional gathering of food plants has been reduced in younger generations during recent years; therefore, it is crucial to develop effective conservation strategies. These efforts not only safeguard indigenous flora, food knowledge, and cultural heritage, but they also contribute to food security and public health by utilizing local wild foods in the examined area. [ABSTRACT FROM AUTHOR]

Aims: Exploring key genes and potential molecular pathways of ferroptosis in immunoglobulin A nephropathy (IgAN). Methods: The IgAN datasets and ferroptosis‐related genes (FRGs) were obtained in the Gene Expression Omnibus (GEO) and FerrDb database. Differentially expressed genes (DEGs) were identified using R software and intersected with FRGs to obtain differentially expressed FRGs (DE‐FRGs). After that, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis (PEA) and Gene Ontology (GO) functional annotation were performed on DE‐FRGs. In the Search Tool for the Retrieval of Interacting Genes (STRING) website, we construct a protein–protein interaction (PPI) network. The PPI network was further investigated with screening hub genes with Cytoscape software. The core genes were then subjected to gene set enrichment analysis (GSEA). Finally, the samples were analyzed for immune infiltration in R, and the correlation between hub genes and immune cells was analyzed. Results: A total of 347 DEGs were identified. CD44, CDO1, CYBB, IL1B, RRM2, AKR1C1, activated transcription factor‐3 (ATF3), CDKN1A, GDF15, JUN, MGST1, MIOX, MT1G, NR4A1, PDK4, TNFAIP3, and ZFP36 were determined as DE‐FRGs. JUN, IL1B, and ATF3 were then screened as hub genes. GSEA and immune infiltration analysis revealed that the hub genes were closely associated with immune inflammatory responses such as NOD‐like receptor signaling, IL‐17 signaling, and TNF signaling. Conclusions: Our results show that JUN and ATF3 are possibly critical genes in the process of IgAN ferroptosis and may be related with immune cell infiltration. [ABSTRACT FROM AUTHOR]

Objective To develop a hypoxia-based gene model to assess prognosis and immune microenvironment of skin cutaneous melanoma (SKCM). Methods Public database (TCGA, GEO, GTEx) was used to search SKCM cases. Cox regression analysis was used to screen genes for hypoxia-related traits. A risk model containing seven hypoxia genes was constructed. GSEA was used to compare enrichment differences between the two groups, using the CIBERSORT tool to investigate potential correlations between immune cells and genetic signatures. Results Seven genes (FBP1, GPI, BGN, SERPINE1, SDC4, PGM1, EGFR) contained in the SKCM hypoxia model were found to have a lower survival rate in the high-risk group than in the low-risk group. In addition, we found significant differences in the infiltration of nine immune cells in the tissues of patients in the high-and low-risk groups. Conclusion Hypoxia is associated with the prognosis and the incidence of immune cell infiltration in SKCM patients, which provides an immunological perspective for the development of personalized therapy [ABSTRACT FROM AUTHOR]

Simple Summary: Combining drugs is crucial for enhancing anti-cancer responses. However, the potential of pre-clinical data in identifying suitable combinations and dosage is often underutilized. In this study, we leverage pre-clinical in vitro cell line drug response data and computational modeling of signal transduction and of pharmacokinetics to elucidate distinct dose requirements for the combination of pan-RAF and MEK inhibitors in melanoma. Our findings reveal a more synergistic but narrower dosing landscape in NRAS vs. BRAF mutant melanoma, which we link to a mechanism of adaptive resistance through negative feedback. Further, our analysis suggests the importance of drug dosing strategies to optimize synergy based on mutational context yet highlights the real-world challenges of maintaining a narrow dose range. This approach establishes a framework for translational investigation of drug responses in the refinement of combination therapy, balancing the potential for synergy and practical feasibility in cancer treatment planning. Purpose: This study explores the potential of pre-clinical in vitro cell line response data and computational modeling in identifying the optimal dosage requirements of pan-RAF (Belvarafenib) and MEK (Cobimetinib) inhibitors in melanoma treatment. Our research is motivated by the critical role of drug combinations in enhancing anti-cancer responses and the need to close the knowledge gap around selecting effective dosing strategies to maximize their potential. Results: In a drug combination screen of 43 melanoma cell lines, we identified specific dosage landscapes of panRAF and MEK inhibitors for NRAS vs. BRAF mutant melanomas. Both experienced benefits, but with a notably more synergistic and narrow dosage range for NRAS mutant melanoma (mean Bliss score of 0.27 in NRAS vs. 0.1 in BRAF mutants). Computational modeling and follow-up molecular experiments attributed the difference to a mechanism of adaptive resistance by negative feedback. We validated the in vivo translatability of in vitro dose–response maps by predicting tumor growth in xenografts with high accuracy in capturing cytostatic and cytotoxic responses. We analyzed the pharmacokinetic and tumor growth data from Phase 1 clinical trials of Belvarafenib with Cobimetinib to show that the synergy requirement imposes stricter precision dose constraints in NRAS mutant melanoma patients. Conclusion: Leveraging pre-clinical data and computational modeling, our approach proposes dosage strategies that can optimize synergy in drug combinations, while also bringing forth the real-world challenges of staying within a precise dose range. Overall, this work presents a framework to aid dose selection in drug combinations. [ABSTRACT FROM AUTHOR]

Simple Summary: Building on the idea of a germline oligogenic origin of lung cancer, we performed WES of DNA from patients' peripheral blood and their unaffected sibs. Filtering for rare variants and potentially damaging effects, we identified 40 deleterious variants mapping in genes previously associated with cancer exclusively identified in patients. Transcriptome profiling on both tumor and normal lung tissues revealed that, among the selected mutated genes, 16 variants mapping in 16 genes were either down- or upregulated in cancer specimens. Among the downregulated genes, 9 variants in 9 genes carried the mutated allele suggesting a loss of heterozygosity. Notably, the group of mutated genes was unique for each patient, pinpointing to a "private" oligogenic germline signature. In the era of precision medicine, this report emphasizes the importance of an "omic" approach to uncover an oligogenic germline signature underlying cancer development and identify suitable therapeutic targets. Lung cancer (LC) continues to be an important public health problem, being the most common form of cancer and a major cause of cancer deaths worldwide. Despite the great bulk of research to identify genetic susceptibility genes by genome-wide association studies, only few loci associated to nicotine dependence have been consistently replicated. Our previously published study in few phenotypically discordant sib-pairs identified a combination of germline truncating mutations in known cancer susceptibility genes in never-smoker early-onset LC patients, which does not present in their healthy sib. These results firstly demonstrated the presence of an oligogenic combination of disrupted cancer-predisposing genes in non-smokers patients, giving experimental support to a model of a "private genetic epidemiology". Here, we used a combination of whole-exome and RNA sequencing coupled with a discordant sib's model in a novel cohort of pairs of never-smokers early-onset LC patients and in their healthy sibs used as controls. We selected rare germline variants predicted as deleterious by CADD and SVM bioinformatics tools and absent in the healthy sib. Overall, we identified an average of 200 variants per patient, about 10 of which in cancer-predisposing genes. In most of them, RNA sequencing data reinforced the pathogenic role of the identified variants showing: (i) downregulation in LC tissue (indicating a "second hit" in tumor suppressor genes); (ii) upregulation in cancer tissue (likely oncogene); and (iii) downregulation in both normal and cancer tissue (indicating transcript instability). The combination of the two techniques demonstrates that each patient has an average of six (with a range from four to eight) private mutations with a functional effect in tumor-predisposing genes. The presence of a unique combination of disrupting events in the affected subjects may explain the absence of the familial clustering of non-small-cell lung cancer. In conclusion, these findings indicate that each patient has his/her own "predisposing signature" to cancer development and suggest the use of personalized therapeutic strategies in lung cancer. [ABSTRACT FROM AUTHOR]

Simple Summary: Adenoid cystic carcinoma is a rare but devastating disease. Currently, treatment options are very poor, and ACC does not respond well to conventional chemotherapy or radiation therapy and has a high rate of recurrence or metastasis. The molecular drivers that govern disease pathology are currently poorly understood. We conducted a molecular analysis of adenoid cystic carcinoma of the salivary and lacrimal glands in order to better understand these mechanisms and pave the way for the development of future therapeutics. Adenoid cystic carcinoma (ACC) of head and neck origin is associated with slow but relentless progression and systemic metastasis, resulting in poor long-term survival rates. ACC does not respond to conventional chemotherapy. Determination of molecular drivers may provide a rational basis for personalized therapy. Herein, we investigate the clinical and detailed molecular genomic features of a cohort of patients treated in Ireland and correlate the site of origin, molecular features, and outcomes. Clinical and genomic landscapes of all patients diagnosed with ACC over a twenty-year period (2002–2022) in a single unit in Ireland were examined and analyzed using fluorescence in situ hybridization, DNA sequencing, and bioinformatic analysis. Fourteen patients were included for analysis. Eleven patients had primary salivary gland ACC and three primary lacrimal gland ACC; 76.9% of the analyzed tumors displayed evidence of NFIB-MYB rearrangement at the 6q23.3 locus; 35% had mutations in NOTCH pathway genes; 7% of patients had a NOTCH1 mutation, 14.3% NOTCH2 mutation, and 14.3% NOTCH3 mutation. The presence of epigenetic modifications in ACC patients significantly correlated with worse overall survival. Our study identifies genetic mutations and signaling pathways that drive ACC pathogenesis, representing potential molecular and therapeutic targets. [ABSTRACT FROM AUTHOR]

Simple Summary: As global meat production is rapidly increasing, it is important to find sustainable sources of meat. Horsemeat is a viable alternative due to its lower environmental impact and high nutritional value. In this study, bioinformatics was used to determine genetic markers (SNPs) that could improve horsemeat production by focusing on orthologous genes related to meat yield in cattle and in QTLs for body weight and body size. Out of 268 markers, 27 SNPs in key genes such as LCORL, LASP1, IGF1R, and MSTN were prioritized. These findings can help small-scale farmers to breed horses with better meat yield. In addition, this information will be valuable for large-scale genetic studies to further evaluate these markers and improve breeding programs. This work lays the foundation for a better understanding of horse genetics and the advancement of horse breeding. In view of the predicted significant increase in global meat production, alternative sources such as horsemeat are becoming increasingly important due to their lower environmental impact and high nutritional value. This study aimed to identify SNP markers on the GeneSeek® Genomic Profiler™ Equine (Neogen, Lansing, MI, USA) that are important for horsemeat production traits. First, orthologous genes related to meat yield in cattle and common genes between horses and cattle within QTLs for body size and weight were identified. Markers for these genes were then evaluated based on predicted variant consequences, GERP scores, and positions within constrained elements and orthologous regulatory regions in pigs. A total of 268 markers in 57 genes related to meat production were analyzed. This resulted in 27 prioritized SNP markers in 22 genes, including notable markers in LCORL, LASP1, IGF1R, and MSTN. These results will benefit smallholder farmers by providing genetic insights for selective breeding that could improve meat yield. This study also supports future large-scale genetic analyses such as GWAS and Genomic Best Linear Unbiased Prediction (GBLUP). The results of this study may be helpful in improving the accuracy of genomic breeding values. However, limitations include reliance on bioinformatics without experimental validation. Future research can validate these markers and consider a wider range of traits to ensure accuracy in equine breeding. [ABSTRACT FROM AUTHOR]

Simple Summary: Capacitation confers competency to spermatozoa to fertilize the oocyte, yet its regulatory mechanisms are not fully understood. Thus, we aimed to investigate the comparative proteomic profiling in ram spermatozoa under non-capacitating (NC) and capacitating (CAP) conditions in vitro using a liquid chromatography–tandem mass spectrometry (LCMS/MS) combined with tandem mass tag (TMT) labeling strategy. Functional enrichment analysis indicated that the differentially abundant proteins Prune Exopolyphosphatase 1, Galactose-1-Phosphate Uridylyltransferase, and ATP Citrate Lyase were strictly related to energy production and conversion, and Phosphoglycolate phosphatase, Glucosamine-6-Phosphate Deaminase 1 and 2 were related to metabolism, RNA processing, and vesicular transport pathways. Furthermore, the networks of protein–protein interaction indicated a strong interaction among these differential proteins in annotated pathways such as ubiquitin and transport metabolism. Together, our results provided the database for studying the differentially expressed proteins during ram sperm capacitation. Ram sperm undergo a sequence of physiological and biochemical changes collectively termed as capacitation to perform oocyte fertilization. However, the protein changes induced by capacitation remain in need of further exploration. Thus, the present study investigated the comparative proteomic profiling in ram spermatozoa under non-capacitating (NC) and capacitating (CAP) conditions in vitro using a liquid chromatography–tandem mass spectrometry combined with tandem mass tag labeling strategy. As a results, 2050 proteins were identified and quantified; 348 of them were differentially abundant, with 280 of the proteins upregulated and 68 of the proteins downregulated between the CAP and NC spermatozoa, respectively. Functional enrichment analysis indicated that the differentially abundant proteins Prune Exopolyphosphatase 1, Galactose-1-Phosphate Uridylyltransferase, and ATP Citrate Lyase were strictly related to energy production and conversion, and Phosphoglycolate phosphatase, Glucosamine-6-Phosphate Deaminase 1 and 2 were related to metabolism, RNA processing, and vesicular transport pathways. Furthermore, the networks of protein–protein interaction indicated a strong interaction among these differential proteins in annotated pathways such as ubiquitin and transport metabolism. Our findings indicate that capacitation progress might be regulated through different pathways, providing insights into mechanisms involved in ram sperm capacitation and fertility. [ABSTRACT FROM AUTHOR]

Semen cryopreservation results in the differential remodeling of the molecules presented in sperm, and these alterations related to reductions in sperm quality and its physiological function have not been fully understood. Given this, this study aimed to investigate the cryoinjury mechanism of goat sperm by analyzing changes of the metabolic characteristics in sperm during the cryopreservation process. The ultra-high-performance liquid chromatography–quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) technique was performed to explore metabolite profiles of fresh sperm (C group), equilibrated sperm (E group), and frozen–thawed sperm (F group). In total, 2570 metabolites in positive mode and 2306 metabolites in negative mode were identified, respectively. After comparative analyses among these three groups, 374 differentially abundant metabolites (DAMs) in C vs. E, 291 DAMs in C vs. F, and 189 DAMs in E vs. F were obtained in the positive mode; concurrently, 530 DAMs in C vs. E, 405 DAMs in C vs. F, and 193 DAMs in E vs. F were obtained in the negative mode, respectively. The DAMs were significantly enriched in various metabolic pathways, including 31 pathways in C vs. E, 25 pathways in C vs. F, and 28 pathways in E vs. F, respectively. Among them, 65 DAMs and 25 significantly enriched pathways across the three comparisons were discovered, which may be tightly associated with sperm characteristics and function. Particularly, the functional terms such as TCA cycle, biosynthesis of unsaturated fatty acids, sphingolipid metabolism, glycine, serine and threonine metabolism, alpha-linolenic acid metabolism, and pyruvate metabolism, as well as associated pivotal metabolites like ceramide, betaine, choline, fumaric acid, L-malic acid and L-lactic acid, were focused on. In conclusion, our research characterizes the composition of metabolites in goat sperm and their alterations induced by the cryopreservation process, offering a critical foundation for further exploring the molecular mechanisms of metabolism influencing the quality and freezing tolerance of goat sperm. Additionally, the impacts of equilibration at low temperature on sperm quality may need more attentions as compared to the freezing and thawing process. [ABSTRACT FROM AUTHOR]

Androgenetic alopecia (AGA) is characterized by microinflammation and abnormal immune responses, particularly in the upper segment of hair follicles (HFs). However, the precise patterns of immune dysregulation remain unclear, partly due to limitations in current analysis techniques to preserve tissue architecture. The infundibulum, a major part of the upper segment of HFs, is associated with significant clusters of immune cells. In this study, we investigated immune cells around the infundibulum, referred to as peri-infundibular immune infiltration (PII). We employed spatial transcriptome profiling, a high-throughput analysis technology, to investigate the immunological disruptions within the PII region. Our comprehensive analysis included an evaluation of overall immune infiltrates, gene set enrichment analysis (GSEA), cellular deconvolution, differential expression analysis, over-representation analysis, protein-protein interaction (PPI) networks, and upstream regulator analysis to identify cell types and molecular dysregulation in immune cells. Our results demonstrated significant differences in immune signatures between the PII of AGA patients (PII-A) and the PII of control donors (PII-C). Specifically, PII-A exhibited an enrichment of CD4+ helper T cells, distinct immune response patterns, and a bias toward a T helper (Th) 2 response. Immunohistochemistry revealed disruptions in T cell subpopulations, with more CD4+ T cells displaying an elevated Th2 response and a reduced Th1-cytotoxic response compared to PII-C. These findings reveal the unique immune landscapes of PII-A and PII-C, suggesting potential for the development of innovative treatment approaches. [ABSTRACT FROM AUTHOR]

Objective To analyze the structure and function of Rv1772 protein in Mycobacterium tuberculosis(MTB). Methods Gene information for Rv1772 was obtained from the National Center for Biotechnology Information (NCBI). Bioinformatics tools were utilized to analyze the structure and function of Rv1772 protein. Results The Rv1772 protein had a relative molecular mass of 10 896. 28 Da and consists of 103 amino acids. It exhibited a gravy index of 77. 96 and an instability coefficient of 43.98(40), indicating it was an unstable protein. The average hydrophilicity of Rv1772 was 0. 105, with a solubility index of 0. 49. The protein comprised only intracellular and extracellular domains, lacked transmembrane regions, suggesting it was a non-transmembrane protein. Rv1772 lacked a signal peptide [D value=0.112(<0.45)], confirming its solubility and cytoplasmic localization. Rv1772 contained six serine phosphorylation sites and five threonine phosphorylation sites, potentially involved in regulating signal transduction during MTB infection. The secondary structure of Rv1772 consisted of a-helix (52.43%), β-sheet (9.71%), β-turn (4.85%), and random coil (33.01%). It predominantly featured a helical structures, suggesting multiple B-cell antigenic epitopes. Rv1772 harbored three IFN-y-induced HTL antigenic epitopes, two dominant CTL antigenic epitopes.and one prominent linear B-cell antigenic epitope. It exhibited high homology with MTB proteins containing the ANTAR domain. Rv1772 interacted with Rv1592c, Rv0340, efpA, kasA, fbpC, oxyR, Rv2242, iniB, ndh, and fadE24 proteins. Conclusion Rv1772 protein contains multiple potential dominant T-cell and B-cell antigenic epitopes, interacts with other proteins, and thus may serve as a promising antigen for tuberculosis vaccine development. [ABSTRACT FROM AUTHOR]

Neuroblastoma, the deadliest solid tumor in children, exhibits alarming mortality rates, particularly among high-risk cases. To enhance survival rates, a more precise risk stratification for patients is imperative. Utilizing proteomic data from 34 cases with or without N-Myc amplification, we identified 28 differentially expressed ubiquitination-related proteins (URGs). From these, a prognostic signature comprising 6 URGs was constructed. A nomogram incorporating clinical-pathological parameters yielded impressive AUC values of 0.88, 0.93, and 0.95 at 1, 3, and 5 years, respectively. Functional experiments targeting the E3 ubiquitin ligase FBXO42, a component of the prognostic signature, revealed its TP53-dependent promotion of neuroblastoma cell proliferation. In conclusion, our ubiquitination-related prognostic model robustly predicts patient outcomes, guiding clinical decisions. Additionally, the newfound pro-proliferative role of FBXO42 offers a novel foundation for understanding the molecular mechanisms of neuroblastoma. [ABSTRACT FROM AUTHOR]

Background: Inflammatory cytokines such as Interleukin 1β(IL1β), IL6,Tumor Necrosis Factor-α (TNF-α) can inhibit osteoblast differentiation and induce osteoblast apoptosis. PANoptosis, a newly identified type of programmed cell death (PCD), may be influenced by long noncoding RNA (lncRNAs) which play important roles in regulating inflammation. However, the potential role of lncRNAs in inflammation and PANoptosis during osteogenic differentiation remains unclear. This study aimed to investigate the regulatory functions of lncRNAs in inflammation and apoptosis during osteogenic differentiation. Methods and results: High-throughput sequencing was used to identify differentially expressed genes involved in osteoblast differentiation under inflammatory conditions. Two lncRNAs associated with inflammation and PANoptosis during osteogenic differentiation were identified from sequencing data and Gene Expression Omnibus (GEO) databases. Their functionalities were analyzed using diverse bioinformatics methodologies, resulting in the construction of the lncRNA-miRNA-mRNA network. Among these, lncRNA (MIR17HG) showed a high correlation with PANoptosis. Bibliometric methods were employed to collect literature data on PANoptosis, and its components were inferred. PCR and Western Blotting experiments confirmed that lncRNA MIR17HG is related to PANoptosis in osteoblasts during inflammation. Conclusions: Our data suggest that TNF-α-induced inhibition of osteogenic differentiation and PANoptosis in MC3T3-E1 osteoblasts is associated with MIR17HG. These findings highlight the critical role of MIR17HG in the interplay between inflammation, PANoptosis, and osteogenic differentiation, suggesting potential therapeutic targets for conditions involving impaired bone formation and inflammatory responses. [ABSTRACT FROM AUTHOR]

Crohn's disease (CD) presents with diverse clinical phenotypes due to persistent inflammation of the gastrointestinal tract. Its global incidence is on the rise. Neutrophil extracellular traps (NETs) are networks released by neutrophils that capture microbicidal proteins and oxidases targeting pathogens. Research has shown that NETs are implicated in the pathogenesis of several immune‐mediated diseases such as rheumatoid arthritis, systemic lupus erythematosus and inflammatory bowel disease. The goal of this study was to identify a panel of NET‐related genes to construct a diagnostic and therapeutic model for CD. Through analysis of the GEO database, we identified 1950 differentially expressed genes (DEGs) associated with CD. Gene enrichment and immune cell infiltration analyses indicate that neutrophil infiltrates and chemokine‐related pathways are predominantly involved in CD, with other immune cells such as CD4 and M1 macrophages also playing a role in disease progression. Utilizing weighted gene co‐expression network analysis (WGCNA) and protein–protein interaction (PPI) networks, we identified six hub genes (SPP1, SOCS3, TIMP1, IRF1, CXCL2 and CD274). To validate the accuracy of our model, we performed external validation with statistical differences(p < 0.05). Additionally, immunohistochemical experiments demonstrated higher protein expression of the hub genes in colonic tissues from CD patients compared to healthy subjects (p < 0.05). In summary, we identified six effective hub genes associated with NETs as potential diagnostic markers for CD. These markers not only offer targets for future research but also hold promise for the development of novel therapeutic interventions for CD. [ABSTRACT FROM AUTHOR]

Background: Breast cancer ranks as one of the most prevalent malignancies among women globally, with increasing incidence rates. Physical activity, particularly exercise, has emerged as a potentially significant modifier of cancer prognosis, influencing tumor biology and patient outcomes. Methods: Using a murine breast cancer model, we established a control and an exercise group, where the latter was subjected to 21 days of voluntary running. RNA Sequencing, bioinformatics analysis, pan-cancer analysis, and cell experiments were performed to validate the underlying mechanisms. Results: We observed that exercise significantly reduced tumor size and weight, without notable changes in body weight, suggesting that physical activity can modulate tumor dynamics. mRNA sequencing post-exercise revealed substantial downregulation of CD300E in the exercise group, accompanied by alterations in critical pathways such as MicroRNAs in cancers and the Calcium signaling pathway. Expanding our analysis to a broader cancer spectrum, CD300E demonstrated significant expression variability across multiple cancer types, with pronounced upregulation in myeloma, ovarian, lung, and colorectal cancers. This upregulation was correlated with poorer prognostic outcomes, emphasizing CD300E's potential role as a prognostic marker and therapeutic target. Moreover, CD300E expression was associated with cancer cell proliferation and apoptosis. Conclusion: The study highlights the dual role of exercise in modulating gene expression relevant to tumor growth and the potential of CD300E as a target in cancer therapeutics. Further research is encouraged to explore the mechanisms by which exercise and CD300E influence cancer progression and to develop targeted strategies that could enhance patient outcomes in clinical settings. [ABSTRACT FROM AUTHOR]

Background: Lung adenocarcinoma (LUAD), a predominant subtype of non-small cell lung cancers, continues to challenge treatment outcomes due to its heterogeneity and complex tumor microenvironment (TME). Dysregulation in nucleotide metabolism has been identified as a significant factor in tumorigenesis, suggesting its potential as a therapeutic target. Methods: This study analyzed LUAD samples from The Cancer Genome Atlas (TCGA) using Non-negative Matrix Factorization (NMF) clustering, Weighted Correlation Network Analysis (WGCNA), and various machine learning techniques. We investigated the role of nucleotide metabolism in relation to clinical features and immune microenvironment through large-scale data analysis and single-cell sequencing. Using in vivo and in vitro experiments such as RT-qPCR, Western Blot, immunohistochemistry, and subcutaneous tumor formation in mice, we further validated the functions of key nucleotide metabolism genes in cell lines and animals. Results: Nucleotide metabolism genes classified LUAD patients into two distinct subtypes with significant prognostic differences. The 'C1' subtype associated with active nucleotide metabolism pathways showed poorer prognosis and a more aggressive tumor phenotype. Furthermore, a nucleotide metabolism-related score (NMRS) calculated from the expression of 28 key genes effectively differentiated between patient outcomes and predicted associations with oncogenic pathways and immune responses. By integrating various immune infiltration algorithms, we delineated the associations between nucleotide metabolism signature genes and the tumor microenvironment, and characterized their distribution differences at the cellular level by analyzing single-cell sequencing dataset related to immunochemotherapy. Finally, we demonstrated the differential expression of the key nucleotide metabolism gene AUNIP acts as an oncogene to promote LUAD cell proliferation and is associated with tumor immune infiltration. Conclusion: The study underscores the pivotal role of nucleotide metabolism in LUAD progression and prognosis, highlighting the NMRS as a valuable biomarker for clinical outcomes and therapeutic responses. Specifically, AUNIP functions as a critical oncogene, offering a promising target for novel treatment strategies in LUAD. [ABSTRACT FROM AUTHOR]

Introduction: Type 2 diabetes mellitus (T2DM) is a major cause of atherosclerosis (AS). However, definitive evidence regarding the common molecular mechanisms underlying these two diseases are lacking. This study aimed to investigate the mechanisms underlying the association between T2DM and AS. Methods: The gene expression profiles of T2DM(GSE159984) and AS (GSE100927) were obtained from the Gene Expression Omnibus, after which overlapping differentially expressed gene identification, bioinformatics enrichment analyses, protein-protein interaction network construction, and core genes identification were performed. We confirmed the discriminatory capacity of core genes using receiver operating curve analysis. We further identified transcription factors using TRRUST database to build a transcription factor-mRNA regulatory network. Finally, the immune infiltration and the correlation between core genes and differential infiltrating immune cells were analyzed. Results: A total of 27 overlapping differentially expressed genes were identified under the two-stress conditions. Functional analyses revealed that immune responses and transcriptional regulation may be involved in the potential pathogenesis. After protein-protein interaction network deconstruction, external datasets, and qRT-PCR experimental validation, four core genes (IL1B, C1QA, CCR5, and MSR1) were identified. ROC analysis further showed the reliable value of these core genes. Four common differential infiltrating immune cells (B cells, CD4+ T cells, regulatory T cells, and M2 macrophages) between T2DM and AS datasets were selected based on immune cell infiltration. A significant correlation between core genes and common differential immune cells. Additionally, five transcription factors (RELA, NFkB1, JUN, YY1, and SPI1) regulating the transcription of core genes were mined using upstream gene regulator analysis. Discussion: In this study, common target genes and co-immune infiltration landscapes were identified between T2DM and AS. The relationship among five transcription factors, four core genes, and four immune cells profiles may be crucial to understanding T2DM complicated with AS pathogenesis and therapeutic direction. [ABSTRACT FROM AUTHOR]

Background: Endometriosis (EM) is a prevalent gynecological disorder frequently associated with irregular menstruation and infertility. Programmed cell death (PCD) is pivotal in the pathophysiological mechanisms underlying EM. Despite this, the precise pathogenesis of EM remains poorly understood, leading to diagnostic delays. Consequently, identifying biomarkers associated with PCD is critical for advancing the diagnosis and treatment of EM. Methods: This study used datasets from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs) following preprocessing. By crossreferencing these DEGs with genes associated with PCD, differentially expressed PCD-related genes (DPGs) were identified. Enrichment analyses for KEGG and GO pathways were conducted on these DPGs. Additionally, Mendelian randomization and machine learning techniques were applied to identify biomarkers strongly associated with EM. Results: The study identified three pivotal biomarkers: TNFSF12, AP3M1, and PDK2, and established a diagnostic model for EM based on these genes. The results revealed a marked upregulation of TNFSF12 and PDK2 in EM samples, coupled with a significant downregulation of AP3M1. Single-cell analysis further underscored the potential of TNFSF12, AP3M1, and PDK2 as biomarkers for EM. Additionally, molecular docking studies demonstrated that these genes exhibit significant binding affinities with drugs currently utilized in clinical practice. Conclusion: This study systematically elucidated the molecular characteristics of PCD in EM and identified TNFSF12, AP3M1, and PDK2 as key biomarkers. These findings provide new directions for the early diagnosis and personalized treatment of EM. [ABSTRACT FROM AUTHOR]

Background: Interactions between the immune and metabolic systems may play a crucial role in the pathogenesis of metabolic syndrome-associated rheumatoid arthritis (MetS-RA). The purpose of this study was to discover candidate biomarkers for the diagnosis of RA patients who also had MetS. Methods: Three RA datasets and one MetS dataset were obtained from the Gene Expression Omnibus (GEO) database. Differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms including Least Absolute Shrinkage and Selection Operator (LASSO) regression and Random Forest (RF) were employed to identify hub genes in MetS-RA. Enrichment analysis was used to explore underlying common pathways between MetS and RA. Receiver operating characteristic curves were applied to assess the diagnostic performance of nomogram constructed based on hub genes. Protein-protein interaction, Connectivity Map (CMap) analyses, and molecular docking were utilized to predict the potential small molecule compounds for MetS-RA treatment. qRT-PCR was used to verify the expression of hub genes in fibroblast-like synoviocytes (FLS) of MetS-RA. The effects of small molecule compounds on the function of RA-FLS were evaluated by wound-healing assays and angiogenesis experiments. The CIBERSORT algorithm was used to explore immune cell infiltration in MetS and RA. Results: MetS-RA key genes were mainly enriched in immune cell-related signaling pathways and immune-related processes. Two hub genes (TYK2 and TRAF2) were selected as candidate biomarkers for developing nomogram with ideal diagnostic performance through machine learning and proved to have a high diagnostic value (area under the curve, TYK2, 0.92; TRAF2, 0.90). qRT-PCR results showed that the expression of TYK2 and TRAF2 in MetS-RA-FLS was significantly higher than that in non-MetS-RA-FLS (nMetS-RA-FLS). The combination of CMap analysis and molecular docking predicted camptothecin (CPT) as a potential drug for MetS-RA treatment. In vitro validation, CPT was observed to suppress the cell migration capacity and angiogenesis capacity of MetS-RA-FLS. Immune cell infiltration results revealed immune dysregulation in MetS and RA. Conclusion: Two hub genes were identified in MetS-RA, a nomogram for the diagnosis of RA and MetS was established based on them, and a potential therapeutic small molecule compound for MetS-RA was predicted, which offered a novel research perspective for future serum-based diagnosis and therapeutic intervention of MetS-RA. [ABSTRACT FROM AUTHOR]