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Simple Summary: Engagement of an advanced immunofluorescence technology demonstrated, for the first time, the cell cycle-dependent control of TRBP2 protein, a major component of the RNAi machinery. TRBP2 expression is lost during mitosis and restored in the cell nucleus upon interphase entry. None of the post-translational modifications, such as ubiquitination or phosphorylation, herein examined proved able to play an essential role in TRBP2 loss from the nucleus of mitotic cells. Different types of cancer cells, with diverse tissue origin, malignancy grade, metastatic potential, and mutational load, are shown to lack TRBP2 nuclear compartmentalization during mitosis, thereby opening new diagnostic and therapeutic windows for human malignancies in the clinic. Background: Transactivation Response Element RNA-binding Protein (TRBP2) is a double-stranded RNA-binding protein widely known for its critical contribution to RNA interference (RNAi), a conserved mechanism of gene-expression regulation mediated through small non-coding RNA moieties (ncRNAs). Nevertheless, TRBP2 has also proved to be involved in other molecular pathways and biological processes, such as cell growth, organism development, spermatogenesis, and stress response. Mutations or aberrant expression of TRBP2 have been previously associated with diverse human pathologies, including Alzheimer's disease, cardiomyopathy, and cancer, with TRBP2 playing an essential role(s) in proliferation, invasion, and metastasis of tumor cells. Methods: Hence, the present study aims to investigate, via employment of advanced flow cytometry, immunofluorescence, cell transgenesis and bioinformatics technologies, new, still elusive, functions and properties of TRBP2, particularly regarding its cell cycle-specific control during cancer cell division. Results: We have identified a novel, mitosis-dependent regulation of TRBP2 protein expression, as clearly evidenced by the lack of its immunofluorescence-facilitated detection during mitotic phases, in several human cancer cell lines of different tissue origin. Notably, the obtained TRBP2-downregulation patterns seem to derive from molecular mechanisms that act independently of oncogenic activities (e.g., malignancy grade), metastatic capacities (e.g., low versus high), and mutational signatures (e.g., p53−/− or p53ΔΥ126) of cancer cells. Conclusions: Taken together, we herein propose that TRBP2 serves as a novel cell cycle-dependent regulator, likely exerting mitosis-suppression functions, and, thus, its mitosis-specific downregulation can hold strong promise to be exploited for the efficient and successful prognosis, diagnosis, and (radio-/chemo-)therapy of diverse human malignancies, in the clinic. [ABSTRACT FROM AUTHOR]

Simple Summary: Precise analysis of T-cell receptor clonality is essential in lymphoma diagnostics, particularly for cutaneous T-cell lymphomas like Mycosis fungoides (MF) and Sézary Syndrome (SS). The current gold standard, based on next generation sequencing (NGS), is precise and accurate but time- and cost-intensive. This study established a workflow for the analysis of the T-cell receptor repertoire using third generation nanopore sequencing. Results are similarly accurate to NGS for cutaneous T-cell lymphoma, but less time-consuming and cost-intensive. Background: Analysis of T-cell receptor (TCR) clonality is a major diagnostic tool for lymphomas, particularly for cutaneous T-cell lymphomas (CTCL) like Mycosis fungoides and Sézary syndrome. However, a fast and cost-effective workflow is needed to enable widespread use of this method. Methods: We established a procedure for TCR rearrangement analysis via Oxford Nanopore Technology (ONT) sequencing. TCR receptor rearrangements (TCR-gamma and TCR-beta chains) were analyzed in samples from 45 patients with various diagnoses: Mycosis fungoides (37/45), Sézary Syndrome (2/45), folliculotropic CTCL (1/45), and non-CTCL diagnoses as polyclonal controls (5/45). Sample types included formalin-fixed paraffin-embedded (FFPE) samples (27/45), fresh frozen samples (9/45), and CD3-isolated cells (9/45). In addition, DNA of a Jurkat cell line was used as a monoclonal control. TCR amplicons were generated employing an optimized version of the protocol from the Euro Clonality consortium. Sequencing was conducted on the ONT GridION and Illumina MiSeq platforms, followed by similar bioinformatic analysis protocols. The tumor clone frequency (TCF), a crucial prognostic factor for CTCL patients, was used for method comparison. Results: The use of an optimized amplicon protocol and adapted bioinformatic tools demonstrated a strong correlation in TCF values between both sequencing methods across all sample types (range R: 0.992–0.996; range r2: 0.984–0.991). Conclusions: In summary, ONT sequencing was able to detect TCR clonality comparable to NGS, indicating its potential as a faster and more cost-effective option for routine diagnostic use. [ABSTRACT FROM AUTHOR]

Simple Summary: Breast cancer is the most common cancer type and the leading cause of mortality for women worldwide. The microbiome influences various cancer therapies, including radiotherapy. Thus, radiotherapy-derived metabolites and microbiome composition may affect cancer progression and treatment response, and vice versa. This review explores this bidirectional relationship as well as providing current evidence and future perspectives in this field. The gut microbiome has emerged as a crucial player in modulating cancer therapies, including radiotherapy. In the case of breast cancer, the interplay between the microbiome and radiotherapy-derived metabolites may enhance therapeutic outcomes and minimize adverse effects. In this review, we explore the bidirectional relationship between the gut microbiome and breast cancer. We explain how gut microbiome composition influences cancer progression and treatment response, and how breast cancer and its treatments influence microbiome composition. A dual role for radiotherapy-derived metabolites is explored in this article, highlighting both their therapeutic benefits and potential hazards. By integrating genomics, metabolomics, and bioinformatics tools, we present a comprehensive overview of these interactions. The study provides real-world insight through case studies and clinical trials, while therapeutic innovations such as probiotics, and dietary interventions are examined for their potential to modulate the microbiome and enhance treatment effectiveness. Moreover, ethical considerations and patient perspectives are discussed, ensuring a comprehensive understanding of the subject. Towards revolutionizing treatment strategies and improving patient outcomes, the review concludes with future research directions. It also envisions integrating microbiome and metabolite research into personalized breast cancer therapy. [ABSTRACT FROM AUTHOR]

Simple Summary: This study explores Warburg's paradox, whereby cancer cells use both glucose and oxygen to survive, even though glucose is converted to lactate instead of being oxidized. By systematically investigating cellular metabolism during each phase of cell division and comparing the metabolic profiles of lymphoma cells and non-malignant lymphocytes, we discovered that pyruvate, the end-product of glucose metabolism, is converted into alanine. This conversion directs glutamine carbon, rather than glucose, into the TCA cycle. Furthermore, using fludarabine to selectively inhibit lymphoma cell proliferation, we showed that blocking the conversion of pyruvate to alanine disrupts the TCA cycle and interferes with the supply of nucleotides and the energy necessary for cancer cell growth. Our findings suggest that with the suppression of glucose oxidation, the conversion of pyruvate to alanine is the crucial metabolic link that connects glucose and oxygen metabolism and serves as a key component of Warburg's paradox. Background/Objectives: Warburg's metabolic paradox illustrates that malignant cells require both glucose and oxygen to survive, even after converting glucose into lactate. It remains unclear whether sparing glucose from oxidation intersects with TCA cycle continuity and if this confers any metabolic advantage in proliferating cancers. This study seeks to understand the mechanistic basis of Warburg's paradox and its overall implications for lymphomagenesis. Methods: Using metabolomics, we first examined the metabolomic profiles, glucose, and glutamine carbon labeling patterns in the metabolism during the cell cycle. We then investigated proliferation-specific metabolic features of malignant and nonmalignant cells. Finally, through bioinformatics and the identification of appropriate pharmacological targets, we established malignant-specific proliferative implications for the Warburg paradox associated with metabolic features in this study. Results: Our results indicate that pyruvate, lactate, and alanine levels surge during the S phase and are correlated with nucleotide synthesis. By using 13C1,2-Glucose and 13C6, 15N2-Glutamine isotope tracers, we observed that the transamination of pyruvate to alanine is elevated in lymphoma and coincides with the entry of glutamine carbon into the TCA cycle. Finally, by using fludarabine as a strong inhibitor of lymphoma, we demonstrate that disrupting the transamination of pyruvate to alanine correlates with the simultaneous suppression of glucose-derived nucleotide biosynthesis and glutamine carbon entry into the TCA cycle. Conclusions: We conclude that the transamination of pyruvate to alanine intersects with reduced glucose oxidation and maintains the TCA cycle as a critical metabolic feature of Warburg's paradox and lymphomagenesis. [ABSTRACT FROM AUTHOR]

Simple Summary: There has been little improvement in Ewing sarcoma survival rates over the past several decades and new therapeutic options are desperately needed. Histone deacetylases (HDACs) are known to play a role in cancer development and progression. We show that HDAC2 is overexpressed in Ewing sarcoma cells and that an HDAC inhibitor, Panobinostat, is cytotoxic to Ewing sarcoma cells both alone and when combined with standard of care. Mechanistically, we show that Panobinostat increases the DNA damage caused by standard of care leading to the death of the Ewing sarcoma cells. We believe that HDAC inhibition combined with standard-of-care chemotherapeutics may be an effective treatment option for Ewing sarcoma patients. Background: The survival rate of patients with Ewing sarcoma (EWS) has seen very little improvement over the past several decades and remains dismal for those with recurrent or metastatic disease. HDAC2, ALK, JAK1, and CDK4 were identified as potential targets using RNA sequencing performed on EWS patient tumors with the bioinformatic analysis of gene expression. Methods/Results: The pan-HDAC inhibitor Panobinostat was cytotoxic to all the Ewing sarcoma cell lines tested. Mechanistically, Panobinostat decreases the expression of proteins involved in the cell cycle, including Cyclin D1 and phospho-Rb, and DNA damage repair, including CHK1. Further, Panobinostat induces a G1 cell cycle arrest. The combination of Panobinostat with Doxorubicin or Etoposide, both of which are used as standard of care in upfront treatment, leads to a synergistic effect in EWS cells. The combination of Panobinostat and Doxorubicin induces an accumulation of DNA damage, a decrease in the expression of DNA damage repair proteins CHK1 and CHK2, and an increase in caspase 3 cleavage. The addition of Panobinostat to standard-of-care chemotherapy combinations significantly reduces cell viability compared to that of chemotherapy alone. Conclusions: Overall, our data indicate that HDAC2 is overexpressed in many EWS tumor samples and HDAC inhibition is effective in targeting EWS cells, alone and in combination with standard-of-care chemotherapy agents. This work suggests that the addition of an HDAC inhibitor to upfront treatment may improve response. [ABSTRACT FROM AUTHOR]

Simple Summary: ATM and PALB2 are two of the main breast cancer susceptibility genes. In this research, we studied a crucial biological process called splicing that is responsible for removing introns and consecutively assembling exons, which contain the protein-coding sequence. We focused on mapping the splicing regulatory elements involved in the recognition of ATM exon 50, BRIP1 exon 1, and PALB2 exon 12, which present atypical GC-5′ splice sites. For this purpose, we used the biotechnological tool of hybrid minigenes, which mimic the splicing process of the gene of interest. Thus, we discovered one regulatory interval in ATM exon 50 and two in PALB2 exon 12 that constitute hotspots where splicing-disrupting variants can be placed. Then, 23 ATM and PALB2 candidate variants were tested. Nine ATM and three PALB2 variants impaired splicing, affecting the recognition of their corresponding exons. These variants may therefore be associated with increased breast cancer risk. Background/Objectives: The non-canonical GC-5′ splice sites (5′ss) are the most common exception (~1%) to the classical GT/AG splicing rule. They constitute weak 5′ss and can be regulated by splicing factors, so they are especially sensitive to genetic variations inducing the misrecognition of their respective exons. We aimed to investigate the GC-5′ss of the breast/ovarian cancer susceptibility genes, ATM (exon 50), BRIP1 (exon 1), and PALB2 (exon 12), and their dysregulation induced by DNA variants. Methods: Splicing assays of the minigenes, mgATM_49-52, mgBRIP1_1-2, and mgPALB2_5-12, were conducted to study the regulation of the indicated GC-5′ss. Results: A functional map of the splicing regulatory elements (SRE) formed by overlapping exonic microdeletions revealed three essential intervals, ATM c.7335_7344del, PALB2 c.3229_3258del, and c.3293_3322del, which are likely targets for spliceogenic SRE-variants. We then selected 14 ATM and 9 PALB2 variants (Hexplorer score < −40) located at these intervals that were assayed in MCF-7 cells. Nine ATM and three PALB2 variants affected splicing, impairing the recognition of exons 50 and 12, respectively. Therefore, these variants likely disrupt the active SREs involved in the inclusion of both exons in the mature mRNA. DeepCLIP predictions suggested the participation of several splicing factors in exon recognition, including SRSF1, SRSF2, and SRSF7, involved in the recognition of other GC sites. The ATM spliceogenic variants c.7336G>T (p.(Glu2446Ter)) and c.7340T>A (p.(Leu2447Ter)) produced significant amounts of full-length transcripts (55–59%), which include premature termination stop codons, so they would inactivate ATM through both splicing disruption and protein truncation mechanisms. Conclusions: ATM exon 50 and PALB2 exon 12 require specific sequences for efficient recognition by the splicing machinery. The mapping of SRE-rich intervals in minigenes is a valuable approach for the identification of spliceogenic variants that outperforms any prediction software. Indeed, 12 spliceogenic SRE-variants were identified in the critical intervals. [ABSTRACT FROM AUTHOR]

A central pursuit of cognitive neuroscience is to find neural mechanisms of cognition, with research programs favoring different strategies to look for them. But what is a neural mechanism, and how do we know we have captured them? Here I answer these questions through a framework that integrates Marr's levels with philosophical work on mechanism. From this, the following goal emerges: What needs to be explained are the computations of cognition, with explanation itself given by mechanism—composed of algorithms and parts of the brain that realize them. This reveals a delineation within cognitive neuroscience research. In the premechanism stage, the computations of cognition are linked to phenomena in the brain, narrowing down where and when mechanisms are situated in space and time. In the mechanism stage, it is established how computation emerges from organized interactions between parts—filling the premechanistic mold. I explain why a shift toward mechanistic modeling helps us meet our aims while outlining a road map for doing so. Finally, I argue that the explanatory scope of neural mechanisms can be approximated by effect sizes collected across studies, not just conceptual analysis. Together, these points synthesize a mechanistic agenda that allows subfields to connect at the level of theory. [ABSTRACT FROM AUTHOR]

Objective: 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. Methods: 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. Results: 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). Conclusion: 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]

Many herbs have been shown to safely and successfully treat hyperlipidemia. However, the molecular mechanisms underlying their treatment remain unclear. In this study, 103 prescriptions for the treatment of hyperlipidemia containing 146 herbs were screened. Cluster analyses identified a core prescription comprising five herbs, namely, Crataegus pinnatifida (Shan Zha), Cassiae semen (Jue Ming Zi), Alisma orientale (Sam.) Juz. (Ze Xie), Salvia miltiorrhiza (Dan Shen), and RadixPolygoni Multiflori (He Shou Wu), in combination for the treatment of hyperlipidemia. Next, 9, 62, 5, 132, and 34 potential targets for each of the core herbs and a total of 512 hyperlipidemia-related protein targets were detected. Finally, 40 targets shared by core herbs and hyperlipidemia were identified. IL6, AKT1, IL1B, PTGS2, VEGFA, PPARG, and NOS3 were the seven proteins that were found to be most important in the treatment of hyperlipidemia. Interestingly, the Kyoto Encyclopedia of Genes and Genomes pathway indicated that these targets were mainly enriched in the lipid and atherosclerosis pathway and the cancer pathway. In addition, core target proteins such as AKT1, PTGS2, and PPARG have been demonstrated to play critical roles in hyperlipidemia and pancreatic cancer. Significant affinity between bioactive chemicals and proteins involved in cancer pathways was found by molecular docking. Molecular docking results showed that AKT1, PTGS2, and PPARG exhibited good binding ability with three bioactive chemicals, including 3-beta-hydroxymethyllenetanshiquinone, danshexinkum d, and physciondiglucoside. The treatment of hyperlipidemia by herbs may be mediated through the modulation of proteins associated with the cancer pathway. This study helps to provide a theoretical basis for future combined therapy for hyperlipidemia and cancer. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) is a prevalent mental health condition characterized by persistent feelings of sadness and hopelessness, affecting millions globally. The precise molecular mechanisms underlying MDD remain elusive, necessitating comprehensive investigations. Our study integrates transcriptomic analysis, functional assays, and computational modeling to explore the molecular landscape of MDD, focusing on the DLPFC. We identify key genomic alterations and co-expression modules associated with MDD, highlighting potential therapeutic targets. Functional enrichment and protein–protein interaction analyses emphasize the role of astrocytes in MDD progression. Machine learning is employed to develop a predictive model for MDD risk assessment. Single-cell and spatial transcriptomic analyses provide insights into cell type–specific expression patterns, particularly regarding astrocytes. We have identified significant genomic alterations and co-expression modules associated with MDD in the DLPFC. Key genes involved in neuroactive ligand-receptor interaction pathways, notably in astrocytes, have been highlighted. Additionally, we developed a predictive model for MDD risk assessment based on selected key genes. Single-cell and spatial transcriptomic analyses underscored the role of astrocytes in MDD. Virtual screening of compounds targeting GPR37L1, KCNJ10, and PPP1R3C proteins has identified potential therapeutic candidates. In summary, our comprehensive approach enhances the understanding of MDD's molecular underpinnings and offers promising opportunities for advancing therapeutic interventions, ultimately aiming to alleviate the burden of this debilitating mental health condition. Key messages: Our investigation furnishes insightful revelations concerning the dysregulation of astrocyte-associated processes in MDD. We have pinpointed specific genes, namely KCNJ10, PPP1R3C, and GPR37L1, as potential candidates warranting further exploration and therapeutic intervention. We incorporate a virtual screening of small molecule compounds targeting KCNJ10, PPP1R3C, and GPR37L1, presenting a promising trajectory for drug discovery in MDD. [ABSTRACT FROM AUTHOR]

Background: Roux-en-Y (RYGB) and one anastomosis gastric bypass (OAGB) represent two of the most used bariatric/metabolic surgery (BMS) procedures. Gut microbiota (GM) shift after bypass surgeries, currently understated, may be a possible key driver for the short- and long-term outcomes. Methods: Prospective, multicenter study enrolling patients with severe obesity, randomized between OAGB or RYGB. Fecal and blood samples were collected, pre- (T0) and 24 months postoperatively (T1). GM was determined by V3-V4 16S rRNA regions sequencing and home-made bioinformatic pipeline based on Qiime2 plugin and R packages. Objects: To compare OAGB vs RYGB microbiota profile at T1 and its impact on metabolic and nutritional status. Results: 54 patients completed the study, 27 for each procedure. An overall significant variation was detected in anthropometric and serum nutritional parameters at T1, with a significant, similar decrease in overall microbial alpha and beta diversity observed in both groups. An increase in relative abundances of Actinobacteria and Proteobacteria and a reduction of Bacteroidetes, no significant changes in Firmicutes and Verrucomicrobia, with an increase of the Firmicutes/Bacteroidetes ratio were observed. Conclusions: BMS promotes a dramatic change in GM composition. This is the first multicenter, RCT evaluating the impact of OAGB vs Roux-en-Y bypass on GM profile. The bypass technique per se did not impact differently on GM or other examined metabolic parameters. The emergence of slightly different GM profile postoperatively may be related to clinical conditions or may influence medium or long-term outcomes and as such GM profile may represent a biomarker for bariatric surgery's outcomes. [ABSTRACT FROM AUTHOR]

Background: Long noncoding RNAs (lncRNAs) are reported that play an important role in regulating tumorigenesis. This study aims to develop a ferroptosis‐related lncRNA gene signature for predicting biochemical recurrence of prostate cancer (PCa) and prove a functional lncRNA BCRP3 as a promotor toward PCa progression. Methods: The ferroptosis‐related lncRNA were identified by interoperating the databases of The Cancer Genome Atlas (TCGA) and FerrDb. A predictive model for biochemical recurrence of PCa was established based on the LASSO Cox regression. Kaplan–Meier cures were applied in the measurement of the impact on patients' survival caused by key lncRNAs. Meanwhile, the molecular assays of CCK8, EdU, wound healing, and Transwell were conducted to evaluate the tumor‐suppressive effect of BCRP3 in vitro. Results: This study presented that 17 differentially expressed ferroptosis‐related lncRNAs were confirmed and further screened out 9 key lncRNAs for the establishment of risk model. The nomogram involved the risk model was also proved with an excellent predictive performance toward 1‐, 3‐, and 5‐year survival with the area of curves (AUC) as 0.77, 0.79, and 0.65 separately. Notably, the lncRNA BCRP3 was significantly correlated with the survival of PCa patients based on multivariate Cox regression. Additionally, downregulation of BCRP3 effectively inhibited the proliferation, migration, and invasion of PC3 cells which further proved its anti‐tumor function. Conclusion: We developed a ferroptosis‐related lncRNA risk model for predicting biochemical recurrence, which assisting in the clinical therapy of patients with PCa. [ABSTRACT FROM AUTHOR]

Background: Huashi Baidu Formula (HBF) is a clinical formula known for its efficacy against coronavirus disease 2019 (COVID-19). HBF may reduce the number of patients with abnormal serum creatinine while improving respiratory symptoms, suggesting that this formula may have potential for treating acute kidney injury (AKI). However, the protective effect of HBF on AKI has not been definitively confirmed, and the mechanism remains unclear. Therefore, the present study explored the renoprotective effects and molecular mechanisms of HBF and screened for its active ingredients to identify new potential applications of renoprotection by HBF. Methods: The present study first assessed the protective effects of HBF on AKI in a DOX-induced mouse model. Then, RNA-seq and bioinformatics analyses were used to explore the related pathological processes and potential molecular mechanisms, which were subsequently validated using qRT-PCR and Western blotting. Furthermore, candidate compounds with potential binding affinity to two pivotal targets, sphingosine kinase 1 (SphK1) and plasminogen activator inhibitor-1 (PAI-1), were screened from the 29 constituents present in the blood using Microscale Thermophoresis (MST). Finally, to identify the active ingredients, the candidate components were re-screened using the SphK1 kinase activity detection system or the uPA/PAI-1 substrate colorimetric assay system. Results: In the DOX-induced AKI mouse model, therapeutic administration of HBF significantly reduced the levels of CRE, BUN, TNF-α, IL-1β, IL-6, and UA in plasma and the levels of MDA, T-CHO, and TG in kidney tissue. Additionally, the levels of TP and Alb in plasma and SOD and CAT in the kidney tissue were significantly increased. Histopathological assessment revealed that HBF reduced tubular vacuolation, renal interstitial inflammatory cell infiltration, tubular atrophy, and positive staining of renal interstitial collagen. RNA-seq and bioinformatics analyses showed that oxidative stress, the immune-inflammatory response, and extracellular matrix (ECM) formation could be the pathological processes that HBF targets to exerts its renoprotective effects. Furthermore, HBF regulated the APJ/SPHK1/NF-κB and APJ/PAI-1/TGFβ signaling axes and reduced the phosphorylation levels of NF-κB p65 and SMAD2 and the expression of cytokines and the ECM downstream of the axis. Finally, six SphK1 inhibitors (paeoniflorin, astragalin, emodin, glycyrrhisoflavone, quercetin, and liquiritigenin) and three PAI-1 inhibitors (glycyrrhisoflavone, licochalcone B, and isoliquiritigenin) were identified as potentially active ingredients in HBF. Conclusion: In brief, our investigation underscores the renoprotective effect of HBF in a DOX-induced AKI model mice, elucidating its mechanisms through distinct pathological processes and identifying key bioactive compounds. These findings offer new insights for broadening the clinical applications of HBF and unravelling its molecular mode of action. [ABSTRACT FROM AUTHOR]

Melanoma is the most dangerous form of skin cancer. Hence, a better understanding of molecular mechanisms in melanoma pathogenesis is urgently needed, which provides a new insight into the therapy of melanoma. DTL gene is screened out in melanoma pathogenesis by integrated bioinformatics analysis, and its expression is validated in the tissue and cell samples of melanoma. Forced DTL expression facilitates the proliferation, invasion, migration and EMT of melanoma cells, while DTL knockdown suppresses the biological behavior of melanoma cells. In addition, DTL promotes the malignancy of melanoma in vivo. Mechanistically, BUB1 is the crucial downstream target of DTL. Reduced DTL expression suppresses BUB1 expression, while enhanced DTL expression induces BUB1 upregulation. Rescue experiments showed that growing and migrating of melanoma cells induced by DTL are partially impaired by BUB1 inhibition. In addition, the expression of phosphorylated ERK (p-ERK) and the downstream transcription factor E2F1 are reduced when DTL expression is blocked. Meanwhile, BUB1 levels are decreased when the expression of p-ERK or E2F1 is repressed. Notably, the growth and migration of melanoma cells by inhibition of ERK and knockdown of E2F1 was rescued by overexpressing BUB1. DTL gene may be a prognosis marker and represent a unique potential target for melanoma patients. DTL supports the biologically malignant activity of melanoma cells via the ERK/E2F1/BUB1 axis. [ABSTRACT FROM AUTHOR]

Approaches based on graph descriptors have been used in cheminformatics and bioinformatics for molecular property prediction. In this article, we apply partition technique and simple counting schemes to describe the structure of a two-dimensional (2D) kagome graphene and then derive the closed form of various degree-based topological indices (graph descriptor) of 2D kagome graphene, and its tubular and toroidal forms. [ABSTRACT FROM AUTHOR]

Cancer is highly diverse and heterogeneous. Accurate and rapid analysis of the characteristics of individual cancer cells, using a complex array of big data that includes various clinicopathological features and molecular mechanisms, is crucial for advancing precision medicine. In recent years, experts in biomedical sciences and data sciences have explored the potential of artificial intelligence (AI) to analyze such extensive data sets. The next phase of AI-based medical research on cancer should focus on the practical applications of AI tools and how they can be effectively used in actual medical research settings. Recently, translational research that leverages AI and comprehensive genetic analysis data has emerged as a significant research focus. This field represents an opportunity for groundbreaking discoveries to be shared globally. To further precision medicine in clinical practice, it is vital to develop sophisticated AI tools for cancer research. These tools should not only identify potential therapeutic targets through comprehensive genetic analysis but also predict therapeutic outcomes in clinical settings. [ABSTRACT FROM AUTHOR]

Single-cell allele-specific expression (ASE) is an effective and robust measurement to study regulatory effects. Deriving biological insights from single-cell ASE data requires an optimized bioinformatics pipeline and advanced statistical methods. Bioinformatics processing typically includes variant calling, mapping bias correction, allele-specific read counting, and count aggregation. Multiple methods are available to detect allelic imbalance and differential allelic imbalance. Most of those are based on beta-binomial regression to account for overdispersion and to model multiple influences on ASE. Specialized methods are available to address particular biological questions, including transcriptional bursting, genomic imprinting, cell classification, and construction of cancer clonal trees. Allele-specific expression (ASE) is a powerful signal that can be used to investigate multiple molecular mechanisms, such as cis -regulatory effects and imprinting. Single-cell RNA-sequencing (scRNA-seq) enables ASE characterization at the resolution of individual cells. In this review, we highlight the computational methods for processing and analyzing single-cell ASE data. We first describe a bioinformatics pipeline to obtain ASE counts from raw reads synthesized from previous literature. We then discuss statistical methods for detecting allelic imbalance and its variability across conditions using scRNA-seq data. In addition, we describe other methods that use single-cell ASE to address specific biological questions. Finally, we discuss future directions and emphasize the need for an integrated, optimized bioinformatics pipeline, and further development of statistical methods for different technologies. [ABSTRACT FROM AUTHOR]

The article explores the computational modeling approaches used by the Agency for Toxic Substances and Disease Registry (ATSDR) for toxicity assessments to evaluate the impact of environmental pollutants on public health. It describes the different approaches, including Computational Systems Biology Modeling and Benchmark Dose Modeling, and their applications, such as toxicity prediction and exposure level assessment. It explains the role of the Simulation Section within the ATSDR.

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]

The incidence of prostate cancer is increasing, and its poor prognosis is associated with metadherin overexpression; however, its molecular mechanisms are unclear. This study used Western blot, quantitative real-time polymerase chain reaction, immunofluorescence, and tumorigenicity assays to investigate metadherin and epithelial-mesenchymal transition in prostate cancer. We found that metadherin was highly expressed in prostate cancer tissues, especially PC-3 cells. Metadherin overexpression promoted t epithelial-mesenchymal transition and tumor growth. Bioinformatics analysis and assays revealed that lymphoid enhancer-binding factor 1 directly activates the metadherin promoter. The epithelial- mesenchymal transition and tumorigenicity were suppressed by the silencing of lymphoid enhancer-binding factor 1; however, these effects were reversed by metadherin overexpression. Vitamin D treatment downregulated metadherin and lymphoid enhancer-binding factor 1, counteracting lymphoid enhancer-binding factor 1-induced metadherin upregulation. Our findings indicate that metadherin enhances epithelial-mesenchymal transition and tumorigenicity through lymphoid enhancer-binding factor 1, with vitamin D modulating this interaction in prostate cancer. [ABSTRACT FROM AUTHOR]

Central nervous system diseases pose a significant threat to human health. Clinical observations have demonstrated that celabenzine, the primary active component of the natural plant ginseng, can potentially alleviate cognitive dysfunction in patients with central nervous system disorders. However, the specific mechanisms of its action remain unclear. The PubMed database was used to identify the targets of celabenzine. Subsequently, a Venn diagram of intersecting targets was constructed by utilizing the identified central nervous system injury targets. Additionally, Cytoscape software (version 3.7.2) was used to construct active ingredient-target and Protein-protein interaction networks. The Metascape database was used to perform Gene Ontology functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Molecular docking was performed on active ingredients and target genes. Network pharmacology analysis revealed that celabenzine shares 175 intersecting targets with central nervous system damage, manifesting its effects through PI3K-Akt and MAPK signaling pathways and proteoglycans in the cancer pathway. Celabenzine demonstrates a strong binding affinity with its target gene, RhoA, indicating stable binding. This study was accomplished using network pharmacology and bioinformatics. Our findings suggested that celabenzine shows its protective effects against central nervous system damage by modulating the RhoA gene. [ABSTRACT FROM AUTHOR]

Heart failure is a geriatric syndrome, often accompanied by a high disability rate, complex comorbidities, and a poor prognosis. This study aimed to assess the effect of Astragalus on the vitamin D- fibroblast growth factor 23/fibroblast growth factor receptor 1-KLOTHO axis in elderly heart failure patients using a bioinformatics approach. Thirteen active ingredients and 159 targets were identified based on network pharmacology, and 500 HF targets were obtained using GeneCards database. A predicted target set was established using 22 core targets, and a diagram of the active component-target network was constructed using Cytoscape software (version 3.7.2); a protein-protein interaction network was constructed for analysis, and the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment were analyzed using DAVID software. Bioinformatics analyses revealed that 22 targets were mainly involved in the Ras and PI3K-Akt signaling pathways. Molecular docking for fibroblast growth factor receptor 1 revealed that the active components HMM7 and HMM13 demonstrated better binding stability with the target gene. This study may help explain the molecular mechanism of effects on vitamin D- fibroblast growth factor 23/fibroblast growth factor receptor 1-KLOTHO axis and promote clinical application. [ABSTRACT FROM AUTHOR]

Current interventions for oral/dental diseases heavily rely on operative/surgical procedures, while the discovery of novel drug targets may enable access to noninvasive pharmacotherapy. Therefore, this study aims to leverage large-scale data and Mendelian randomization (MR) techniques, utilizing genetic variants as instruments, to identify potential therapeutic targets for oral and dental diseases supported by genetic evidence. By intersecting 4,302 druggable genes with expression quantitative trait loci from 31,684 blood samples, we identified 2,580 druggable targets as exposures. Single nucleotide polymorphisms associated with dental disease/symptom traits were collected from FinnGen R9, the Gene–Lifestyle Interactions in Dental Endpoints consortium, and the UK Biobank to serve as outcomes for both discovery and replication purposes. Through MR analysis, we identified 43 druggable targets for various dental disease/symptom traits. To evaluate the viability of these targets, we replicated the analysis using circulating protein quantitative trait loci as exposures. Additionally, we conducted sensitivity, colocalization, Gene Ontology/Kyoto Encyclopedia of Genes and Genomes annotation, protein–protein interaction analyses, and validated dental trait–associated druggable gene expression in animal models. Among these targets, IL12RB1 (odds ratio [OR], 1.01; 95% confidence interval [CI], 1.01–1.01) and TNF (OR, 0.98; 95% CI, 0.97–0.99) exhibited therapeutic promise for oral ulcers, whereas CXCL10 (OR, 0.84; 95% CI, 0.76–0.91) was for periodontitis. Through a rigorous quality control and validation pipeline, our study yields compelling evidence for these druggable targets, which may enhance the clinical prognosis by developing novel drugs or repurposing existing ones. [ABSTRACT FROM AUTHOR]

FAM136A promotes the progression and metastasis of various tumors. However, there are few studies on the role of FAM136A in esophageal cancer (ESCA). The TCGA, GTEx, and GEO databases are employed to analyze the expression of FAM136A in ESCA, and qPCR and TMA experiments are performed for validation. Enrichment analyzes are performed to investigate the association of FAM136A expression with immune features, m6A modification, alternative splicing, cuproptosis, and the ceRNA network via bioinformatics analysis. FAM136A is highly expressed in ESCA and correlated with lymph node metastasis and overall survival (OS). Bioinformatics analysis suggested that FAM136A may participate in the following processes to promote ESCA development and progression: 1) Promotion of mast cells infiltration to influence the ESCA immune microenvironment, 2) HNRNPC upregulation to regulate m6A modification, 3) ALYREF upregulation to increase the occurrence of retained intron (RI) events, 4) CDK5RAP1 upregulation to achieve inhibition of tumor cell apoptosis, and 5) promotion of ESCA progression through the lncRNA SNHG15/hsa‐miR‐29c‐3p/FAM136A ceRNA network. FAM136A is a potential biomarker for ESCA diagnosis and treatment response evaluation, and the underlying mechanisms may be associated with immune infiltration, m6A modification, alternative splicing, cuproptosis, and the ceRNA regulatory network. [ABSTRACT FROM AUTHOR]

Background: The complex and expensive processes involved in the production of current clostridial toxoid vaccines require the design of new methods. The aim of this study was to introduce single and combined nontoxic mutants of Clostridium perfringens epsilon toxin (ETX) into the vaccine production. Methods: Antigenic properties, amino acid sequence, physicochemical characteristics, stability, and protein structure of individual and combined ETX mutants were investigated with bioinformatics software. Spatial structure prediction was done by using a homologous modeling method based on the structure of wild type ETX (1UYJ1A.pdb) and the validity of the drawn spatial model was evaluated by estimating the quality and accuracy of the spatial chemistry of the modeled mutant proteins by Ramachandran plot. Results: The highest instability index was observed in H106P/N137A mutant. The results of the homology modeling did not show a clear structural change in any of the mutants compared to the wild ETX. The percentages of amino acids in the favored regions, allowed regions, and outlier regions were 92.81%, 5.03%, and 2.16%, respectively, which indicate the desirability of the proposed model for the three-dimensional structure of the H106P/N137A hybrid mutant. Conclusions: Recombinant H106P/N137A mutant of ETX can be considered a suitable candidate for the production of epsilon genetic toxoid, and this requires extensive laboratory evaluations. [ABSTRACT FROM AUTHOR]

Xiao–Jian–Zhong–Tang (XJZT) has the effect of warming the middle and tonifying the deficiency, easing the urgency and relieving pain according to the theory of traditional Chinese medicine (TCM), and is able to treat spleen deficiency type chronic atrophic gastritis (CAG). Metabolites of TCM in cecum contents are common metabolites of intestinal bacteria and hosts, which can reflect the metabolic status in disease states. The present work was performed to study the effect of XJZT against CAG coupled with the cecal metabolites analysis and bioinformatics. A total of nine prototypical components and 144 metabolites were firstly identified in the cecum metabolites of XJZT using ultra‐high performance liquid chromatography added to the quadrupole‐time of flight mass spectrometry (UHPLC‐Q‐TOF/MS), which underwent the metabolism of oxidation, reduction, methylation, and glucuronic acid reaction Furthermore, different prototypical compounds might metabolize into identical metabolites in the presence of intestinal flora. Bioinformatics was further used to correlate these metabolites with the disease and intestinal flora. Components and targets were screened by Cytoscape, and molecular docking of key targets and core components showed good binding ability. This study provided important information for exploring the mechanism of TCM formulae. [ABSTRACT FROM AUTHOR]

Introduction: Modern histocompatibility algorithms depend on the comparison and analysis of high-resolution HLA protein sequences and structures, especially when considering epitope-based algorithms, which aim to model the interactions involved in antibody or T cell binding. HLA genotype imputation can be performed in the cases where only low/intermediate-resolution HLA genotype is available or if specific loci are missing, and by providing an individuals' race/ethnicity/ancestry information, imputation results can be more accurate. This study assesses the effect of imputing high-resolution genotypes on molecular mismatch scores under a variety of ancestry assumptions. Methods: We compared molecular matching scores from "ground-truth" highresolution genotypes against scores from genotypes which are imputed from low-resolution genotypes. Analysis was focused on a simulated patient-donor dataset and confirmed using two real-world datasets, and deviations were aggregated based on various ancestry assumptions. Results: We observed that using multiple imputation generally results in lower error in molecular matching scores compared to single imputation, and that using the correct ancestry assumptions can reduce error introduced during imputation. Discussion: We conclude that for epitope analysis, imputation is a valuable and low-risk strategy, as long as care is taken regarding epitope analysis context, ancestry assumptions, and (multiple) imputation strategy. [ABSTRACT FROM AUTHOR]

Background: Prostate cancer is one of the leading causes of cancer-related deaths in men. Its molecular pathogenesis is closely linked to various genetic and epigenetic alterations, including posttranslational modifications like SUMOylation. Identifying biomarkers that predict outcomes and specific therapeutic targets depends on a comprehensive understanding of these processes. With growing interest in SUMOylation as a mechanism affecting prostate cancer-related genes, this study aimed to investigate the central role of SUMOylation in prostate cancer prognostics, focusing on the significance of NOP58. Methods: We conducted a comprehensive bioinformatics analysis, integrating differential expression analysis, survival analysis, gene set enrichment analysis (GSEA), and single-cell transcriptomic analyses using data from The Cancer Genome Atlas (TCGA). Key genes were identified through intersections of Venn diagrams, Boralta algorithm signatures, and machine learning models. These signaling mechanisms were validated through experimental studies, including immunohistochemical staining and gene ontology analyses. Results: The dual-gene molecular subtype analysis with SUMO1, SUMO2, and XPO1 genes revealed significant differences in survival outcomes across molecular subtypes, further emphasizing the potential impact of NOP58 on SUMOylation, a key post-translational modification, in prostate cancer. NOP58 overexpression was strongly associated with shorter overall survival (OS), progression-free interval (PFI), and disease-specific death in prostate cancer patients. Immunohistochemical analysis confirmed that NOP58 was significantly overexpressed in prostate cancer tissues compared to normal tissues. ROC curve analysis demonstrated that NOP58 could distinguish prostate cancer from control samples with high diagnostic accuracy. Gene Ontology analysis, along with GSVA and GSEA, suggested that NOP58 may be involved in cell cycle regulation and DNA repair pathways. Moreover, NOP58 knockdown led to increased BCL2 expression and decreased Ki67 levels, promoting apoptosis and inhibiting cell proliferation. Colony formation assays further showed that NOP58 knockdown inhibited, while its overexpression promoted, colony formation, highlighting the critical role of NOP58 in prostate cancer cell growth and survival. Additionally, NOP58 was linked to drug responses, including Methotrexate, Rapamycin, Sorafenib, and Vorinostat. Conclusion: NOP58 is a key regulator of prostate cancer progression through its mediation of the SUMOylation pathway. Its expression level serves as a reliable prognostic biomarker and an actionable therapeutic target, advancing precision medicine for prostate cancer. Targeting NOP58 may enhance therapeutic efficacy and improve outcomes in oncology. [ABSTRACT FROM AUTHOR]

The democratisation of next‐generation sequencing has vastly increased the availability of sequencing data from metabarcoding. However, to effectively prepare these metabarcoding data for subsequent analysis, researchers must consistently apply several different bioinformatic tools—including those which denoise reads, cluster sequences and assign taxonomic identities. This often creates a bioinformatics bottleneck in workflows for non‐specialists due to obstacles around: (a) integrating different tools, (b) the inability to easily modify and rerun bioinformatic pipelines involving non‐scripted ('point‐and‐click') elements and (c) the multiple outputs that may be required of a single dataset (e.g. amplicon sequence variants [ASVs] and operational taxonomic units [OTUs]), which often results in users running pipelines multiple times.Here, we introduce SimpleMetaPipeline, an open‐source bioinformatics pipeline implemented in R, which addresses these obstacles. SimpleMetaPipeline integrates the most robust and commonly used existing bioinformatic tools in a single reproducible pipeline, with a streamlined choice of parameters, to generate a sequence data table containing alternative clustering and assignment options. SimpleMetaPipeline accepts demultiplexed paired‐end and single reads from multiple sequencing runs.We describe the pipeline and demonstrate how alternative annotations enable the easy implementation of multi‐algorithm agreement tests to strengthen inferences.SimpleMetaPipeline represents a valuable addition to the existing library of pipelines, providing easy and reproducible bioinformatics, including a range of commonly desired clustering and assignment options, such as OTUs and ASVs. [ABSTRACT FROM AUTHOR]

In this study, a novel approach for the environmentally conscious extraction of titanium dioxide from ilmenite ore while limiting the environmental impact and enhancing the advantage from an economic process. Leaching conditions were tested with different acids for effective separation of the TiO2 and were optimized concerning different experimental parameters. TiO2 and TiO2NPs were characterized using with different tools. Catechol polyurethane foam immobilized with TiO2NPs was prepared and its antimicrobial action was tested against Gram-negative bacterium E. coli, Gram-positive bacterium B. cereus, and fungus A. niger. CAT-PUF /TiO2NPs showed antimicrobial effect against E. coli, B. cereus, and A. niger with inhibition zones of 27 ± 0.14, 12 ± 0.14, and 22 ± 0.06 mm, respectively. Incorporating bioinformatics, this research contributes to the burgeoning field of nanotechnology-enabled antimicrobial materials, offering insights into the potential applications of CAT-PUF/TiO2NPs in combating microbial threats. Through bio-informatics tools, the potential toxicity of the synthesized nanoparticles was assessed, providing valuable insights into their safety profile and environmental impact. Furthermore, simulating the binding affinity between the nanoparticles and target biomolecules, such as cell membrane proteins or enzyme receptors, this aspect of the research sheds light on the mechanistic underpinnings of their antimicrobial efficacy. [ABSTRACT FROM AUTHOR]

Comparing transcriptome profiling between younger and older samples reveals genes related to aging and provides insight into the biological functions affected by aging. Recent research has identified sex, tissue, and cell type-specific age-related changes in gene expression. This study reports the overall picture of the opposite aging effect, in which aging increases gene expression in one cell subset and decreases it in another cell subset. Using the Tabula Muris Senis dataset, a large public single-cell RNA sequencing dataset from mice, we compared the effects of aging in different cell subsets. As a result, the opposite aging effect was observed widely in the genes, particularly enriched in genes related to ribosomal function and translation. The opposite aging effect was observed in the known aging-related genes. Furthermore, the opposite aging effect was observed in the transcriptome diversity quantified by the number of expressed genes and the Shannon entropy. This study highlights the importance of considering the cell subset when intervening with aging-related genes. [ABSTRACT FROM AUTHOR]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an exceptionally contagious single-stranded RNA virus with a strong positive contagion. The COVID-19 pandemic refers to the swift worldwide dissemination of SARS-CoV-2 infection, which began in late 2019. The COVID-19 epidemic has disrupted many cancer treatments. A few reports indicate that the prevalence of SARS-CoV-2 has disrupted the treatment of breast cancer patients (BCs). However, the role of SARS-CoV-2 in the occurrence and prognosis of BC has not been elucidated. Here, we applied bioinformatics to construct a prognostic signature of SARS-CoV-2-related genes (SCRGs). Specifically, weighted gene co-expression network analysis (WGCNA) was utilized to extract co-expressed genes of differentially expressed genes (DEGs) in breast cancer and SCRGs. Then, we utilized the least absolute shrinkage and selection operator (LASSO) algorithm and univariate regression analysis to screen out three hub genes (DCTPP1, CLIP4 and ANO6) and constructed a risk score model. We further analyzed tumor immune invasion, HLA-related genes, immune checkpoint inhibitors (ICIs), and sensitivity to anticancer drugs in different SARS-CoV-2 related risk subgroups. In addition, we have developed a nomination map to expand clinical applicability. The results of our study indicate that BCs with a high-risk score are linked to negative outcomes, lower immune scores, and reduced responsiveness to anticancer medications. This suggests that the SARS-CoV-2 related signature could be used to guide prognosis assessment and treatment decisions for BCs. [ABSTRACT FROM AUTHOR]

Background: Circadian rhythm disruption is typical in Parkinson’s disease (PD) early stage, and it plays an important role in the prognosis of the treatment effect in the advanced stage of PD. There is growing evidence that circadian rhythm genes can influence development of PD. Therefore, this study explored specific regulatory mechanism of circadian genes (C-genes) in PD through bioinformatic approaches. Methods: Differentially expressed genes (DEGs) between PD and control samples were identified from GSE22491 using differential expression analysis. The key model showing the highest correlation with PD was derived through WGCNA analysis. Then, DEGs, 1,288 C-genes and genes in key module were overlapped for yielding differentially expressed C-genes (DECGs), and they were analyzed for LASSO and SVM-RFE for yielding critical genes. Meanwhile, from GSE22491 and GSE100054, receiver operating characteristic (ROC) was implemented on critical genes to identify biomarkers, and Gene Set Enrichment Analysis (GSEA) was applied for the purpose of exploring pathways involved in biomarkers. Eventually, immune infiltrative analysis was applied for understanding effect of biomarkers on immune microenvironment, and therapeutic drugs which could affect biomarkers expressions were also predicted. Finally, we verified the expression of the genes by q-PCR. Results: Totally 634 DEGs were yielded between PD and control samples, and MEgreen module had the highest correlation with PD, thus it was defined as key model. Four critical genes (AK3, RTN3, CYP4F2, and LEPR) were identified after performing LASSO and SVM-RFE on 18 DECGs. Through ROC analysis, AK3, RTN3, and LEPR were identified as biomarkers due to their excellent ability to distinguish PD from control samples. Besides, biomarkers were associated with Parkinson’s disease and other functional pathways. Conclusion: Through bioinformatic analysis, the circadian rhythm related biomarkers were identified (AK3, RTN3 and LEPR) in PD, contributing to studies related to PD treatment. [ABSTRACT FROM AUTHOR]

Phytochrome-interacting factors (PIFs) are a subgroup of transcription factors within the basic helix-loop-helix (bHLH) family, playing a crucial role in integrating various environmental signals to regulate plant growth and development. Despite the significance of PIFs in these processes, a comprehensive genome-wide analysis of PIFs in conifers has yet to be conducted. In this investigation, three PtPIF genes were identified in Chinese pine, categorized into three subgroups, with conserved motifs indicating the presence of the APA/APB motif and bHLH domain in the PtPIF1 and PtPIF3 proteins. Phylogenetic analysis revealed that the PtPIF1 and PtPIF3 proteins belong to the PIF7/8 and PIF3 groups, respectively, and were relatively conserved among gymnosperms. Additionally, a class of PIF lacking APA/APB motif was identified in conifers, suggesting its function may differ from that of traditional PIFs. The cis-elements of the PtPIF genes were systematically examined, and analysis of PtPIF gene expression across various tissues and under different light, temperature, and plant hormone conditions demonstrated similar expression profiles for PtPIF1 and PtPIF3. Investigations into protein-protein interactions and co-expression networks speculated the involvement of PtPIFs and PtPHYA/Bs in circadian rhythms and hormone signal transduction. Further analysis of transcriptome data and experimental validation indicated an interaction between PtPIF3 and PtPHYB1, potentially linked to diurnal rhythms. Notably, the study revealed that PtPIF3 may be involved in gibberellic acid (GA) signaling through its interaction with PtDELLAs, suggesting a potential role for PtPIF3 in mediating both light and GA responses. Overall, this research provides a foundation for future studies investigating the functions of PIFs in conifer growth and development. [ABSTRACT FROM AUTHOR]

Objective: This study employs integrated bioinformatics analysis and in vitro cellular experiments to elucidate the role of Synaptotagmin-12 (SYT12) in the progression of gastric cancer. Methods: We utilized databases and platforms such as Xiantao Academic Tools, UALCAN, Kaplan-Meier plotter analysis, and The Cancer Genome Atlas (TCGA) to extract datasets on SYT12 in gastric cancer. We analyzed the relationship between SYT12 expression and the clinicopathological features, prognosis, diagnosis, and immune infiltration of stomach adenocarcinoma (STAD) patients. Verification was conducted using samples from 31 gastric cancer patients. Additionally, in vitro cellular experiments were performed to determine the role and potential mechanisms of SYT12 in the malignant behavior of gastric cancer cells. Results: Comprehensive bioinformatics analysis indicated that SYT12 is highly expressed in most cancers and is associated with promoter DeoxyriboNucleic Acid (DNA) methylation levels. SYT12 expression correlated with clinicopathological features, immune cell infiltration, immune checkpoint gene expression, and poor prognosis in STAD patients. In vitro experiments suggest that SYT12 may promote the proliferation and migration of gastric cancer cells by inducing epithelial-mesenchymal transition (EMT). Conclusions: This study highlights the significant role of SYT12 in gastric cancer, suggesting its potential as a new target for early diagnosis, treatment, immunological, and prognostic evaluation in gastric cancer, offering new insights for precision medicine in this disease. [ABSTRACT FROM AUTHOR]

Background: Triple‐negative breast cancer, a subtype of breast cancer, is characterized by a poor prognosis. Recent studies have shown that miRNA30b acts as an oncogene and is vital for the proliferation of malignancies across various systems. This study aimed to elucidate the impact of miRNA30b on the proliferation, migration, and invasion capabilities of breast cancer cells in vitro. Methods: Triple‐negative breast cancer cell lines MDA‐MB‐231 were transiently transfected with miRNA30b inhibitor, mimic, or the negative control by Lipofectamine 2000. Successful transfection was confirmed by quantitative real‐time polymerase chain reaction (qRT‐PCR). Functional assays, including CCK8, clone formation, scratch, and transwell assays, were conducted to evaluate the proliferation, invasion, and migration ability of MDA‐MB‐231 cells in each group. The target protein of miRNA30b was determined using an online prediction data website, and the dual‐luciferase assay confirmed whether there was a binding site between miRNA30b and ADAM12. The effect was further verified by Western blot analysis. Results: MDA‐MB‐231 cells were transfected with miRNA30b inhibitor, mimic, and negative control. miRNA30b expression was downregulated in the cells. Relative to the negative control group, miRNA30b expression significantly increased in the mimic group and decreased in the miRNA30b inhibitor group, with the differences being statistically significant. The miRNA30b mimic group exhibited a significant increase in miRNA30b expression and a corresponding promotion of cell proliferation, colony formation, and migration. Conversely, the miRNA30b inhibitor group displayed significantly reduced miRNA30b expression and suppressed cell proliferation, colony formation, and migration abilities compared to the negative control cells. Bioinformatics software predicted ADAM12 as a potential target of miRNA30b. Dual‐luciferase assays confirmed the presence of a binding site between miRNA30b and ADAM12. Western blot analysis revealed that overexpression of miRNA30b downregulated ADAM12 expression in MDA‐MB‐231 cells. Conclusions: miRNA30b could promote proliferation, migration, and invasion of TNBC cell lines MDA‐MB‐231. The effect of miRNA30b on triple‐negative breast cancer would be achieved partly at least through inhibiting the expression of ADAM12. [ABSTRACT FROM AUTHOR]

Objective To analyze the gene expression profiles of gefitinib-sensitive and drug-resistant non-small cell lung cancer (NSCLC) cells in GEO database by bioinformatics, to study the potential key genes leading to acquired drug resistance of NSCLC, and to provide new ideas for the prognosis evaluation of patients with drug-resistant NSCLC. Methods The GEO2R network tool was used to analyze the GSE123066 and GSE83666 data sets to identify differentially expressed genes (DEGs). The key candidate genes were identified by comparing the DEGs between the two groups of data through the Wayne diagram, and then GO analysis. KEGG analysis and protein-protein interaction (PPI) analysis were performed on the candidate genes. The clinical prognosis analysis and expression level analysis of tumor tissues and different stages were performed on the obtained genes. Results A total of 46 core DEGs were significantly associated with drug-resistant NSCLC. Cytoscape identified eight key genes that play an important role in the progression of gefitinib resistance in NSCLC cells, namely SOD2, GADD45A, NCF2, LOX, CYR61, SOX2, JUP and MUC1, respectively. Among them, SOD2 was highly correlated with gefitinib resistance in NSCLC. Conclusion SOD2 may be the key genes leading to acquired drug resistance of NSCLC cells to gefitinib, and their high expression is associated with poor prognosis of NSCLC, indicating that SOD2 may be potential therapeutic targets with clinical application value in the future. [ABSTRACT FROM AUTHOR]

Neurotropic pathogens, notably, herpesviruses, have been associated with significant neuropsychiatric effects. As a group, these pathogens can exploit molecular mimicry mechanisms to manipulate the host central nervous system to their advantage. Here, we present a systematic computational approach that may ultimately be used to unravel protein–protein interactions and molecular mimicry processes that have not yet been solved experimentally. Toward this end, we validate this approach by replicating a set of pre-existing experimental findings that document the structural and functional similarities shared by the human cytomegalovirus-encoded UL144 glycoprotein and human tumor necrosis factor receptor superfamily member 14 (TNFRSF14). We began with a thorough exploration of the Homo sapiens protein database using the Basic Local Alignment Search Tool (BLASTx) to identify proteins sharing sequence homology with UL144. Subsequently, we used AlphaFold2 to predict the independent three-dimensional structures of UL144 and TNFRSF14. This was followed by a comprehensive structural comparison facilitated by Distance-Matrix Alignment and Foldseek. Finally, we used AlphaFold-multimer and PPIscreenML to elucidate potential protein complexes and confirm the predicted binding activities of both UL144 and TNFRSF14. We then used our in silico approach to replicate the experimental finding that revealed TNFRSF14 binding to both B- and T-lymphocyte attenuator (BTLA) and glycoprotein domain and UL144 binding to BTLA alone. This computational framework offers promise in identifying structural similarities and interactions between pathogen-encoded proteins and their host counterparts. This information will provide valuable insights into the cognitive mechanisms underlying the neuropsychiatric effects of viral infections. [ABSTRACT FROM AUTHOR]

In the elderly population, coronary heart disease (CHD) often coexists with hypertension. However, excessive blood pressure reduction can paradoxically increase the incidence of adverse events. Understanding the molecular mechanisms underlying hypertension and CHD in aged populations is crucial for developing targeted therapies and improving clinical outcomes. In this study, we constructed myocardial infarction (MI) and transverse aortic constriction (TAC) modelsY in aged mice to simulate the disease states of CHD and hypertension, respectively. Using integrated proteomic and phosphoproteomic analyses, we investigated the molecular signatures associated with MI and TAC in these models. Our aim was to identify key molecules involved in these conditions and to understand their unique and shared characteristics. Through our comprehensive proteomic and phosphoproteomic analysis, we identified a total of 1583 proteins and 232 phosphorylated proteins. We observed significant upregulation of heart disease markers such as Myh7, Xirp2, and Acta1, indicating the successful establishment of the MI and TAC models. The overlapped differentially expressed proteins (DEPs) and differentially phosphorylated proteins (DPPs) in MI and TAC were involved in heart failure‐related processes including cardiac muscle contraction and hypertrophic cardiomyopathy, further supporting the validity of the models. Among the DEPs, Ppme1 was upregulated in the TAC model but downregulated in the MI model, while Sec31a and Gm56451 displayed the opposite expression patterns. Among the DPPs, Ablim1 and Atp2a2 were found to be significantly upregulated in the TAC model, whereas their expression was markedly reduced in the MI model. In addition, five other DPPs, including REV_Q3TAY5, Cbx3, PITPNB, Eif4b, and A0A1Y7VP73, were elevated in the MI model but decreased in the TAC model. In conclusion, these findings suggest that MI and TAC not only share certain molecular features but also retain their unique characteristics, providing potential biomarkers and therapeutic targets. [ABSTRACT FROM AUTHOR]

ABSTRACT Low coverage ‘genome‐skims’ are often used to assemble organelle genomes and ribosomal gene sequences for cost‐effective phylogenetic and barcoding studies. Natural history collections hold invaluable biological information, yet poor preservation resulting in degraded DNA often hinders polymerase chain reaction‐based analyses. However, it is possible to generate libraries and sequence the short fragments typical of degraded DNA to generate genome‐skims from museum collections. Here we introduce a snakemake toolkit comprised of three pipelines skim2mito, skim2rrna and gene2phylo, designed to unlock the genomic potential of historical museum specimens using genome skimming. Specifically, skim2mito and skim2rrna perform the batch assembly, annotation and phylogenetic analysis of mitochondrial genomes and nuclear ribosomal genes, respectively, from low‐coverage genome skims. The third pipeline gene2phylo takes a set of gene alignments and performs phylogenetic analysis of individual genes, partitioned analysis of concatenated alignments and a phylogenetic analysis based on gene trees. We benchmark our pipelines with simulated data, followed by testing with a novel genome skimming dataset from both recent and historical solariellid gastropod samples. We show that the toolkit can recover mitochondrial and ribosomal genes from poorly preserved museum specimens of the gastropod family Solariellidae, and the phylogenetic analysis is consistent with our current understanding of taxonomic relationships. The generation of bioinformatic pipelines that facilitate processing large quantities of sequence data from the vast repository of specimens held in natural history museum collections will greatly aid species discovery and exploration of biodiversity over time, ultimately aiding conservation efforts in the face of a changing planet. [ABSTRACT FROM AUTHOR]

AbstractBackgroundMethodsResultsConclusionsTalin-1 (TLN1) is crucial in cell migration, metastasis, and cancer development. This study evaluated Talin-1 expression and its clinical significance in gastric cancer (GC), along with human epidermal growth factor receptor-2 (HER-2) expression and its correlation with Talin-1.Bioinformatics analysis assessed the potential prognostic value of Talin-1 and HER-2 in GC patients. The study included 223 GC patients (Signet Ring Cells and Intestinal subtypes) and 29 non-malignant tissue samples. Immunohistochemistry (IHC) on tissue microarray slides evaluated Talin-1 and HER-2 expression and clinical significance. Receiver operating characteristic (ROC) curves assessed their diagnostic value.Bioinformatics identified Talin-1 as a potential prognostic factor and HER-2 as an oncogene in GC. Talin-1 and HER-2 expression increased in SRC-type GC samples compared to non-malignant tissues. High cytoplasmic Talin-1 expression inversely correlated with tumor expansion and invasion in SRC-type GC. Increased HER-2 expression positively correlated with metastasis. ROC curves showed significant diagnostic values for both proteins.Higher cytoplasmic Talin-1 expression is associated with less invasive tumor behavior, while increased membranous HER-2 expression is associated with metastasis in SRC-type GC. These findings suggest potential use in assessing diagnosis and screening high-risk cancer patients, particularly those with SRC-type GC. [ABSTRACT FROM AUTHOR]

Background: Type 2 diabetes mellitus (T2DM) has emerged as a global epidemic issue, with high rates of disability and fatality. Traditional diagnostic biomarkers are typically detected once a metabolic imbalance has already occurred, thus the development of early diagnostic biomarkers is crucial for T2DM. Metabolomics studies have identified several predictive biomarkers for T2DM, including miR‐320. Our previous research found that miR‐320b was significantly downregulated in T2DM patients, but the underlying mechanism remains unclear. Therefore, this study was designed to investigate the significance of miR‐320b for T2DM diagnosis and to explore the involved molecular mechanism. Methods: A total of 50 patients with T2DM and 80 sex‐ and age‐matched healthy subjects were selected. The plasma miR‐320b of all participations was detected by qRT‐PCR and its correlations with other biomarkers of T2DM were analyzed. Besides, the expression of miR‐320b in HepG2 cells was suppressed by miRNA inhibitors. Then the glucose consumption of HepG2 cells was measured. The target gene of miR‐320b was predicted by four bioinformatics tools and intersected these prediction results by Venny method. The T2DM relevant target genes were identified by the GeneCards database. To ensure disease relevance, these T2DM relevant target genes were subsequently intersected with the target genes of miR‐320b. Protein–protein analysis (PPI) was used to screening the gene with the most connections in these target genes. Finally, the target gene of miR‐320b specific to T2DM was confirmed directly by luciferase reporter assay. The expression of target gene in HepG2 cell culture supernatant and plasma of all participations was detected. Results: Our results showed that the expression level of miR‐320b was significantly lower in T2DM patients compared to the healthy controls. It was negatively correlated with fasting plasma glucose (FPG), glycated hemoglobin (HbA1C), and homeostasis model assessment of insulin resistance (HOMA‐IR), but positively with HOMA‐β. The glucose consumption of HepG2 cells in the miR‐320b inhibitor group was significantly lower compared to inhibitor‐NC and blank control group. We predicted and confirmed that phosphatase and tensin homolog (PTEN) was the direct target gene of miR‐320b using Bioinformation tools and luciferase reporter assay. Moreover, the concentration of PTEN was significantly higher in the HepG2 cell culture supernatant and plasma of T2DM patients. Conclusions: Our research demonstrated a negative correlation between miR‐320b and FPG, HbA1C, and HOMA‐IR, while exhibiting a positive correlation with HOMA‐β. Suppressing miR‐320b expression would impair glucose consumption of HepG2 cells through PI3K pathway by targeting PTEN. These results suggest that miR‐320b may be a potential biomarker for diagnosing T2DM and a promising target for therapeutic intervention. [ABSTRACT FROM AUTHOR]

Background: Dirigent (DIR) genes play a key role in the development of organic products in plants. They confer conformational influence on processes that lack stereoselectivity and regioselectivity through processes that are mostly understood. They are required to produce lignans, which are a unique and widely distributed family of plant secondary metabolites with intriguing pharmacological characteristics and potential role in plant development. DIR genes are implicated in the process of lignification and protect plants from environmental stresses, including biotic and abiotic stresses. Nevertheless, no research has been performed on the DIR gene family in Solanum lycopersicum. This study provides detailed information on the DIR gene family in S. lycopersicum. Methods and results: The conserved domain analysis, phylogenetic analysis, evolutionary adaptation, cis-acting elements, proteomic analysis, signal peptide detection, transmembrane potential analysis, sequence identity and similarity analysis, gene assembly, genomic localization, duplication of gene analysis, and evolutionary linkage of 31 potential DIR genes were studied. All these analyses provide a deep understanding of DIR genes in the S. lycopersicum genome that will provide a useful reference for further functional analysis of the DIR genes in S. lycopersicum. Conclusion: This research provides an in-depth and comprehensive explanation of the detailed process and structural characterization of DIR genes in the genome of S. lycopersicum, laying the groundwork for future plant genetic engineering and crop development exploration. This work will provide valuable information for identifying DIR genes in higher plants and support future research on the DIR gene family. [ABSTRACT FROM AUTHOR]

Objective: To investigate the prognostic significance of CXCL8 in cervical cancer and its effect on immune response based on bioinformatics method. Methods: This study employs the HPA database to investigate CXCL8 expression in normal human tissues.The TIMER2.0 database is utilized to analyze CXCL8 expression across various types of cancer.Utilizing the TCGA database, we analyze the correlation between CXCL8 and the overall survival (OS) and progression-free interval (PFI) of patients with various tumors using R 4.3.2.Additionally, its association with immune checkpoint-related genes across various types of cancer is examined.We further analyze the association between CXCL8 expression and the expression of LAG3, CTLA4, PDCD1, and CD274 in cervical cancer.The TIMER database is used to study the association between CXCL8 and the extent of Tumor-Infiltrating Immune Cells (TIICs) infiltration.Enrichment analysis of genes related to CXCL8 is conducted using the LinkedOmics database. Result: CXCL8 is found in a wide range of normal human tissues.In the majority of tumor tissues, CXCL8 expression is elevated compared to their normal counterparts.There is a significant correlation between CXCL8 expression and the overall survival (OS) and progression-free interval (PFI) of patients with various tumors.CXCL8 expression is associated with the expression of diverse immune checkpoint-related genes and the extent of Tumor-Infiltrating Immune Cells (TIICs) infiltration.Genes related to CXCL8 participate in diverse immune-related processes in cervical cancer. Conclusion: CXCL8 plays a role in modulating immune infiltration, thereby influencing the prognosis of patients with various tumors, particularly those with cervical cancer.CXCL8 could potentially act as a biomarker for forecasting the prognosis and immune response of patients with tumors. [ABSTRACT FROM AUTHOR]

Plastics are ubiquitous in our ecosystems, and microplastic accumulation in the environment is an emerging global health concern. Since available recycling technologies are not economically competitive with primary plastic production, global use is expected to reach 1231 megatons by 2060, with 493 megatons leeching into the environment each year. To identify new nylon‐recycling biotechnologies, targeted genome mining was used to identify thermostable enzymes capable of degrading polyamides. Here, we describe the characterization of a novel protein sourced from Thermovenabulum gondwanense: TvgC. TvgC is extremely stable, exhibiting a melting temperature of 93 °C and no detectable losses in hydrolytic activity after one week at 60 °C. While nylonases primarily process nylon‐6, TvgC catalysed the degradation of both nylon‐6 and nylon‐6,6 films, which are considerably more difficult to degrade. Finally, conversion experiments demonstrate that TvgC achieves a 1.2 wt % conversion of nylon‐6 film, comparable to that of the most highly engineered nylonases. This novel hyperthermostable protein represents an excellent starting point for future engineering of increasingly efficient nylonases. [ABSTRACT FROM AUTHOR]

Background: Acute compartment syndrome(ACS) is a perilous consequence of trauma. Acute compartment syndrome's precise cause is yet unknown. We performed studies to confirm that acute compartment syndrome can be relieved by suppressing ferroptosis and activating the Nrf2/Hmox1 pathway. Methods: We generated an ACS rat model and we conducted next-generation sequencing(NGS) of skeletal muscle tissue and identified differentially expressed target genes. Ultimately, we performed in vivo experiments to validate the presence of ferroptosis and the Nrf2/Hmox1 pathway in ACS rats. After the minocycline intervention, the drug was evaluated for its effects on ACS by examining changes associated with ferroptosis. Results: The bioinformatics analysis identified that the genetic changes in the disease were mostly focused on ferroptosis, with noticeable modifications in Nrf2/Hmox1. Based on the in vivo results, it was observed that ACS rats exhibited significantly elevated levels of ferroptosis compared to the control rats. The suppression of the Nrf2/Hmox1 pathway mediated by minocycline improves outcomes in ACS and reduces tissue damage after intervention. Conclusion: Minocycline hinders ferroptosis via stimulating the Nrf2/Hmox1 pathway, which slows down the advancement of acute compartment syndrome. [ABSTRACT FROM AUTHOR]

Background: Esophageal squamous cell carcinoma (ESCC) is one of the most common malignant tumors, with high incidence and poor prognosis. Revealing mechanisms of ESCC progression and developing new therapeutic targets remains crucial. The aim of this study was to elucidate the molecular mechanism of miR‐30c‐5p in regulating the malignant progression of ESCC. Methods: TCGA, GEO, and other datasets were used to analyze the differential expression of miR‐30c‐5p in ESCC and adjacent tissues, and its impact on prognosis. Then the effects of miR‐30c‐5p on the proliferation, migration, and invasion of TE‐1 and Eca9706 cells were investigated through proliferation experiments, transwell and wounding healing assays. The regulatory mechanism of miR‐30c‐5p on the PI3K/AKT signaling pathway and its interaction in cancer progression were investigated through Western blots, dual‐luciferase reporter assay, and rescue experiments. Results: miR‐30c‐5p was significantly downregulated in ESCC tissue and represented a poor prognosis. miR‐30c‐5p mimic significantly inhibited the proliferation, migration, and invasion ability of ESCC, while miR‐30c‐5p inhibitor significantly promoted tumor cell progression. Through bioinformatic analysis and experimental results, miR‐30c‐5p interacted directly with PIK3CA mRNA and inhibited subsequent signaling pathway activation. PIK3CA activator could eliminate the inhibitory effects of miR‐30c‐5p mimic on the progression of ESCC, while PIK3CA inhibitors could rescue the promoting effect of miR‐30c‐5p inhibitor group cells. Conclusions: In summary, we found that miR‐30c‐5p inhibited the proliferation, invasion and migration of ESCC by inhibiting PI3K/AKT signaling pathway for the first time, and this study is expected to provide a novel insight and potential therapeutic target for managing ESCC. [ABSTRACT FROM AUTHOR]

Introduction: Lung adenocarcinoma, a disease with complex pathogenesis, high mortality and poor prognosis, is one of the subtypes of lung cancer. Hence, it is very crucial to find novel biomarkers as diagnostic and therapeutic targets for LUAD. Methods: GSE10072 was used for DEGs and WGCNA, and the intersection genes were subjected to enrichment analysis through Metascape and GSEA. Key genes were screened by three machine learning methods. Further, the reliability of key genes was identified by ROC, COX regression analysis and qRT-PCR. CIBERSORT and Spearman analysis were used for understanding the relationships of LUAD, immunity and key genes. In addition, ceRNA networks and potential drugs of key genes were constructed and predicted. Results: After overlapping 631 DEGs and key module genes, 623 intersection genes were obtained. Subsequently, DUOX1, CD36, AGTR1, FHL5 and SSR4 were further selected using three machine learning methods. Reliability analysis demonstrated that AGTR1 possesses important predictive value for the occurrence and prognosis of LUAD. The enrichment analysis showed that AGTR1 was significantly enriched in the GPCR-related pathways. Immune infiltration analysis showed that the development of LUAD was related to the changes of immune cells such as M2 macrophages and neutrophils, which were regulated by AGTR1. Further, AGTR1 is also involved in regulating immune chemokines, checkpoints and immune regulatory factors such as PECAM1, ADARB1, SPP1 and ENO1, all of them playing important roles in immune cell regulation, tumor cell proliferation and migration. Further, the drug-gene interaction network screened out 13 potential drugs such as Benazepril, Valsartan, Eprosartan, and so on. Discussion: AGTR1 is a potential biomarker for the occurrence and progression of LUAD, closely related to tumor immunity, proliferation and migration. It can serve as a new target for the diagnosis and treatment of LUAD. [ABSTRACT FROM AUTHOR]

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Background: Insomnia (ISM) is one of the non-traditional drivers of atherosclerosis (AS) and an important risk factor for AS-related cardiovascular disease. Our study aimed to explore the shared pathways and diagnostic biomarkers of ISM-related AS using integrated bioinformatics analysis. Methods: We download the datasets from the Gene Expression Omnibus database and the GeneCards database. Weighted gene co-expression network analysis and gene differential expression analysis were applied to screen the ASrelated gene set. The shared genes of ISM and AS were obtained by intersecting with ISM-related genes. Subsequently, candidate diagnostic biomarkers were identified by constructing protein-protein interaction networks and machine learning algorithms, and a nomogram was constructed. Moreover, to explore potential mechanisms, a comprehensive analysis of shared genes was carried out, including enrichment analysis, protein interactions, immune cell infiltration, and single-cell sequencing analysis. Results: We successfully screened 61 genes shared by ISM and AS, of which 3 genes (IL10RA, CCR1, and SPI1) were identified as diagnostic biomarkers. A nomogram with excellent predictive value was constructed (the area under curve of the model constructed by the biomarkers was 0.931, and the validation set was 0.745). In addition, the shared genes were mainly enriched in immune and inflammatory response regulation pathways. The biomarkers were associated with a variety of immune cells, especially myeloid immune cells. Conclusion: We constructed a diagnostic nomogram based on IL10RA, CCR1, and SPI1 and explored the inflammatory-immune mechanisms, which indicated new insights for early diagnosis and treatment of ISM-related AS. [ABSTRACT FROM AUTHOR]