Protein-protein Interaction Analysis Research Articles

Transcriptome Analysis of the Striatum of Electroacupuncture-treated Naïve and Ischemic Stroke Mice.

Electroacupuncture (EA) has been demonstrated to aid stroke recovery. However, few investigations have focused on identifying the potent molecular targets of EA by comparing EA stimulation between naïve and disease models. Therefore, this study was undertaken to identify the potent molecular therapeutic mechanisms underlying EA stimulation in ischemic stroke through a comparison of mRNA sequencing data obtained from EA-treated naïve control and ischemic stroke mouse models. Using both naïve control and middle cerebral artery occlusion (MCAO) mouse models, EA stimulation was administered at two acupoints, Baihui (GV20) and Dazhui (GV14), at a frequency of 2 Hz. Comprehensive assessments were conducted, including behavioral evaluations, RNA sequencing to identify differentially expressed genes (DEGs), functional enrichment analysis, protein-protein interaction (PPI) network analysis, and quantitative real-time PCR. EA stimulation ameliorated the ischemic insult-induced motor dysfunction in mice with ischemic stroke. Comparative analysis between control vs. MCAO, control vs. control + EA, and MCAO vs. MCAO + EA revealed 4,407, 101, and 82 DEGs, respectively. Of these, 30, 7, and 1 were common across the respective groups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed upregulated DEGs associated with the regulation of inflammatory immune response in the MCAO vs. MCAO + EA comparison. Conversely, downregulated DEGs in the control vs. control + EA comparison were linked to neuronal development. PPI analysis revealed major clustering related to the regulation of cytokines, such as Cxcl9, Pcp2, Ccl11, and Cxcl13, in the common DEGs of MCAO vs. MCAO + EA, with Esp8l1 identified as the only common downregulated DEG in both EA-treated naïve and ischemic models. These findings underscore the diverse potent mechanisms of EA stimulation between naïve and ischemic stroke mice, albeit with few overlaps. However, the potent mechanisms underlying EA treatment in ischemic stroke models were associated with the regulation of inflammatory processes involving cytokines.

Genome-Wide Identification and Expression Analysis of BrBASS Genes in Brassica rapa Reveals Their Potential Roles in Abiotic Stress Tolerance.

The bile acid sodium symporter (BASS) family plays an important role in transporting substances and coordinating plants' salt tolerance. However, the function of BASS in Brassica rapa has not yet been elucidated. In this study, eight BrBASS genes distributed on five chromosomes were identified that belonged to four subfamilies. Expression profile analysis showed that BrBASS7 was highly expressed in roots, whereas BrBASS4 was highly expressed in flowers. The promoter element analysis also identified several typical homeopathic elements involved in abiotic stress tolerance and stress-related hormonal responses. Notably, under salt stress, the expression of BrBASS2 was significantly upregulated; under osmotic stress, that of BrBASS4 increased and then decreased; and under cold stress, that of BrBASS7 generally declined. The protein-protein interaction analysis revealed that the BrBASS2 homologous gene AtBASS2 interacted with Nhd1 (N-mediated heading date-1) to alleviate salt stress in plants, while the BrBASS4 homologous gene AtBASS3 interacted with BLOS1 (biogenesis of lysosome-related organelles complex 1 subunit 1) via co-regulation with SNX1 (sorting nexin 1) to mitigate an unfavorable growing environment for roots. Further, Bra-miR396 (Bra-microRNA396) targeting BrBASS4 and BrBASS7 played a role in the plant response to osmotic and cold stress conditions, respectively. This research demonstrates that BrBASS2, BrBASS4, and BrBASS7 harbor great potential for regulating abiotic stresses. The findings will help advance the study of the functions of the BrBASS gene family.

Identification of ibuprofen targeting CXCR family members to alleviate metabolic disturbance in lipodystrophy based on bioinformatics and in vivo experimental verification.

Lipodystrophy is a rare disease that is poorly diagnosed due to its low prevalence and frequent phenotypic heterogeneity. The main therapeutic measures for patients with clinical lipodystrophy are aimed at improving general metabolic complications such as diabetes mellitus, insulin resistance, and hypertriglyceridemia. Therefore, there is an urgent need to find new biomarkers to aid in the diagnosis and targeted treatment of patients with congenital generalized lipodystrophy (CGL). Dataset GSE159337 was obtained via the Gene Expression Omnibus database. First, differentially expressed genes (DEGs) between CGL and control samples were yielded via differential expression analysis and were analyzed for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment to explore the functional pathways. Next, protein-protein interaction analysis and the MCC algorithm were implemented to yield candidate genes, which were then subjected to receiver operating characteristic (ROC) analysis to identify biomarkers with an area under the curve value exceeding 0.8. Moreover, random forest (RF), logistic regression, and support vector machine (SVM) analyses were carried out to assess the diagnostic ability of biomarkers for CGL. Finally, the small-molecule drugs targeting biomarkers were predicted, and ibuprofen was further validated in lipodystrophy mice. A total of 71 DEGs in GSE159337 were sifted out and were involved in immune receptor activity, immune response-regulating signaling pathway, and secretory granule membrane. Moreover, CXCR2, TNFSF10, NLRC4, CCR2, CEACAM3, TLR10, TNFAIP3, and JUN were considered as biomarkers by performing ROC analysis on 10 candidate genes. Meanwhile, RF, logistic regression, and SVM analyses further described that those biomarkers had an excellent diagnosis capability for CGL. Eventually, the drug-gene network included ibuprofen-CXCR1, ibuprofen-CXCR1, cenicriviroc-CCR2, fenofibrate-JUN, and other relationship pairs. Ibuprofen treatment was also validated to downregulate CXCR1 and CXCR2 in peripheral blood mononuclear cells (PBMCs) and improve glucose tolerance, hypertriglyceridemia, hepatic steatosis, and liver inflammation in lipodystrophy mice. Eight biomarkers, namely, CXCR2, TNFSF10, NLRC4, CCR2, CEACAM3, TLR10, TNFAIP3, and JUN, were identified through bioinformatic analyses, and ibuprofen targeting CXCR1 and CXCR2 in PBMCs was shown to improve metabolic disturbance in lipodystrophy, contributing to studies related to the diagnosis and treatment of lipodystrophy.

Integrating network pharmacology and experimental verification to reveal the anti-inflammatory ingredients and molecular mechanism of pycnogenol.

Introduction: Pycnogenol (PYC), a standardized extract from French maritime pine, has traditionally been used to treat inflammation. However, its primary active components and their mechanisms of action have not yet been determined. Methods: This study employed UPLC-MS/MS (Ultra-high performance liquid chromatography-tandem mass spectrometry) and network pharmacology to identify the potential active components of PYC and elucidate their anti-inflammatory mechanisms by cell experiments. Results: 768 PYC compounds were identified and 19 anti-inflammatory compounds were screened with 85 target proteins directly involved in the inflammation. PPI (protein-protein interaction) analysis identified IL6, TNF, MMP9, IL1B, AKT1, IFNG, CXCL8, NFKB1, CCL2, IL10, and PTGS2 as core targets. KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis suggested that the compound in PYC might exert anti-inflammatory effects through the IL17 and TNF signal pathways. Cell experiments determined that PYC treatment can reduce the expression of IL6 and IL1β to relieve inflammation in LPS (lipopolysaccharide)-induced BV2 cells. Conclusion: PYC could affect inflammation via multi-components, -targets, and -mechanisms.

Genome-wide association study comparison analysis based on Hanwoo full-sib family

Objective: The improvement of carcass traits is essential for the Hanwoo industry because of the Hanwoo grade determination system, and genome-wide association study (GWAS) analysis is an instrumental tool for identifying the genetic factors that impact these traits. While GWAS analysis utilizing family data offers advantages in minimizing genetic bias, research on family-based GWAS in Hanwoo is currently lacking.Methods: This study classified Group A using both parental and offspring genetic information, and Group B based solely on offspring genetic information, to compare GWAS analysis results of Hanwoo carcass traits.Results: A total of 16 significant single nucleotide polymorphism (SNP) markers were identified in Group A, comprising 7 for carcass weight (CWT), 3 for back fat thickness (BFT), and 6 for marbling score (MS). In Group B, 7 significant SNP markers were identified, including 3 for CWT, 1 for eye muscle area, 1 for BFT, and 2 for MS. Functional annotation analysis revealed only one common function related to carcass traits between the groups, while protein-protein interaction analysis indicated more gene interactions in Group A. The reliability of estimated values for common SNP markers identified between the groups was higher in Group A.Conclusion: GWAS analysis utilizing parental genetic information holds greater potential for application, owing to its higher reliability of estimated values and the ability to explore numerous candidate genes.

A Network Pharmacology-based Approach to Explore Potential Targets and Mechanism of Berberis aristata Focusing on its Implications for Diabetes Mellitus

Berberis aristata, a revered medicinal shrub in traditional systems like Ayurveda, holds promise in managing diabetes mellitus, a burgeoning global health concern. Through a comprehensive analysis of its bioactive compounds and their interactions with potential targets, this study elucidates the molecular mechanisms underlying its anti-diabetic effects. Screening through databases yielded 17 bioactive compounds, including rutin, quercetin, and berberine. Protein-protein interaction analysis identified 44 potential targets, with 36 genes overlapping with disease-related genes, indicating pivotal pathways in diabetes mellitus treatment. Further, pathway analysis highlighted G-protein coupled receptor signaling, calcium signaling, and neurotransmitter receptor activity as significant, with adjusted p-values. Network analysis revealed key hub genes like DRD1 and MMP2, emphasizing their central role in Berberis aristata’s therapeutic action. The findings underscore Berberis aristata’s potential as a source of novel anti-diabetic agents and offer groundwork for potential research in this field.

SPI1-mediated macrophage polarization aggravates age-related macular degeneration.

This study revealed a core regulator and common upstream mechanisms for the multifaceted pathological processes of age-related macular degeneration (AMD) and provided proof-of-concept for this new therapeutic target. Comprehensive gene expression analysis was performed using RNA sequencing of eye cup from old mice as well as laser-induced choroidal neovascularization (CNV) mouse model. Through integrative analysis and protein-protein interaction (PPI) analysis, common pathways and key transcription factor was identified simultaneously engaged in age-related retinal degeneration and CNV, the two typical pathological process of AMD. Subsequently, the expression changes of Spi1, the key regulator, as well as the alternation of the downstream mechanisms were validated in both models through qRT-PCR, Elisa, flow cytometry and immunofluorescence. Further, we assessed the impact of Spi1 knockdown in vitro and in vivo using gene intervention vectors carried by adeno-associated virus or lentivirus to test its potential as a therapeutic target. Compared to corresponding controls, we found 1,939 and 1,319 genes differentially expressed in eye cups of old and CNV mice respectively. The integrative analysis identified a total of 275 overlapping DEGs, of which 150 genes were co-upregulated. PPI analysis verified a central transcription factor, SPI1. The significant upregulation of Spi1 expression was then validated in both models, accompanied by macrophage polarization towards the M1 phenotype. Finally, SPI1 suppression significantly inhibited M1 polarization of BMDMs and attenuated neovascularization in CNV mice. This study demonstrates that SPI1 exerts a pivotal role in AMD by regulation of macrophage polarization and innate immune response, offering promise as an innovative target for treating AMD.

What enlightenment has the development of lung cancer bone metastasis brought in the last 22 years.

Lung cancer bone metastasis (LCBM) is a disease with a poor prognosis, high risk and large patient population. Although considerable scientific output has accumulated on LCBM, problems have emerged, such as confusing research structures. To organize the research frontiers and body of knowledge of the studies on LCBM from the last 22 years according to their basic research and translation, clinical treatment, and clinical diagnosis to provide a reference for the development of new LCBM clinical and basic research. We used tools, including R, VOSviewer and CiteSpace software, to measure and visualize the keywords and other metrics of 1903 articles from the Web of Science Core Collection. We also performed enrichment and protein-protein interaction analyses of gene expression datasets from LCBM cases worldwide. Research on LCBM has received extensive attention from scholars worldwide over the last 20 years. Targeted therapies and immunotherapies have evolved into the mainstream basic and clinical research directions. The basic aspects of drug resistance mechanisms and parathyroid hormone-related protein may provide new ideas for mechanistic study and improvements in LCBM prognosis. The produced molecular map showed that ribosomes and focal adhesion are possible pathways that promote LCBM occurrence. Novel therapies for LCBM face animal testing and drug resistance issues. Future focus should centre on advancing clinical therapies and researching drug resistance mechanisms and ribosome-related pathways.

NINJ1 Facilitates Abdominal Aortic Aneurysm Formation via Blocking TLR4-ANXA2 Interaction and Enhancing Macrophage Infiltration.

Abdominal aortic aneurysm (AAA) is a common and potentially life-threatening condition. Chronic aortic inflammation is closely associated with the pathogenesis of AAA. Nerve injury-induced protein 1 (NINJ1) is increasingly acknowledged as a significant regulator of the inflammatory process. However, the precise involvement of NINJ1 in AAA formation remains largely unexplored. The present study finds that the expression level of NINJ1 is elevated, along with the specific expression level in macrophages within human and angiotensin II (Ang II)-induced murine AAA lesions. Furthermore, Ninj1flox/flox and Ninj1flox/floxLyz2-Cre mice on an ApoE-/- background are generated, and macrophage NINJ1 deficiency inhibits AAA formation and reduces macrophage infiltration in mice infused with Ang II. Consistently, in vitro suppressing the expression level of NINJ1 in macrophages significantly restricts macrophage adhesion and migration, while attenuating macrophage pro-inflammatory responses. Bulk RNA-sequencing and pathway analysis uncover that NINJ1 can modulate macrophage infiltration through the TLR4/NF-κB/CCR2 signaling pathway. Protein-protein interaction analysis indicates that NINJ1 can activate TLR4 by competitively binding with ANXA2, an inhibitory interacting protein of TLR4. These findings reveal that NINJ1 can modulate AAA formation by promoting macrophage infiltration and pro-inflammatory responses, highlighting the potential of NINJ1 as a therapeutic target for AAA.

Correlation of LLT-1 and NLRC4 inflammasome and its effect on glioblastoma prognosis.

LLT-1 is a well-known ligand for the natural killer (NK) cell inhibitory receptor NKRP1A. Here, we examined NLRC4 inflammasome components and LLT-1 expression in glioblastoma (GBM) tissues to elucidate potential associations and interactions between these factors. GBM tissues were collected for RNA sequencing (RNA-seq) and Immunofluorescent experiments. Colocalization of LLT-1 and other proteins was assessed by immunofluorescence. Computational analyses utilized RNA-seq data from 296 to 52 patients from the Chinese Glioma Genome Atlas and CHA medical records, respectively. These data were subjected to survival, non-negative matrix factorization clustering, Gene Ontology enrichment, and protein-protein interaction analyses. Receptor-ligand interactions between tumor and immune cells were confirmed by single-cell RNA-seq analysis. In GBM tissues, LLT-1 was predominantly colocalized with glial fibrillary acidic protein (GFAP)-expressing astrocytes, but not with microglial markers like Iba-1. Additionally, LLT-1 and activated NLRC4 inflammasomes were mainly co-expressed in intratumoral astrocytes, suggesting an association between LLT-1, NLRC4, and glioma malignancy. High LLT-1 expression correlates with poor prognosis, particularly in the mesenchymal subtype, and is associated with TNF and NOD-like receptor signaling pathway enrichment, indicating a potential role in tumor inflammation and progression. At the single-cell level, mesenchymal-like malignant cells showed high NF, NLR, and IL-1 signaling pathway enrichment compared to other malignant cell types. We revealed an association between NLRC4 inflammasome activity and LLT-1 expression, suggesting a novel regulatory pathway involving TNF, inflammasomes, and IL-1, potentially offering new NK-cell-mediated anti-glioma approaches.

The Applications of Artificial Intelligence (AI)-Driven Tools in Virus-Like Particles (VLPs) Research.

Viral-like particles (VLPs) represent versatile nanoscale structures mimicking the morphology and antigenic characteristics of viruses, devoid of genetic material, making them promising candidates for various biomedical applications. The integration of artificial intelligence (AI) into VLP research has catalyzed significant advancements in understanding, production, and therapeutic applications of these nanostructures. This comprehensive review explores the collaborative utilization of AI tools, computational methodologies, and state-of-the-art technologies within the VLP domain. AI's involvement in bioinformatics facilitates sequencing and structure prediction, unraveling genetic intricacies and three-dimensional configurations of VLPs. Furthermore, AI-enabled drug discovery enables virtual screening, demonstrating promise in identifying compounds to inhibit VLP activity. In VLP production, AI optimizes processes by providing strategies for culture conditions, nutrient concentrations, and growth kinetics. AI's utilization in image analysis and electron microscopy expedites VLP recognition and quantification. Moreover, network analysis of protein-protein interactions through AI tools offers an understanding of VLP interactions. The integration of multi-omics data via AI analytics provides a comprehensive view of VLP behavior. Predictive modeling utilizing machine learning algorithms aids in forecasting VLP stability, guiding optimization efforts. Literature mining facilitated by text mining algorithms assists in summarizing information from the VLP knowledge corpus. Additionally, AI's role in laboratory automation enhances experimental efficiency. Addressing data security concerns, AI ensures the protection of sensitive information in the digital era of VLP research. This review serves as a roadmap, providing insights into AI's current and future applications in VLP research, thereby guiding innovative directions in medicine and beyond.

In silico analysis of the protein-protein interaction of the SARS-CoV-2 spike protein

The pandemic caused by the SARS-CoV-2 virus has represented a global challenge with a significant impact on public health since its emergence in 2019. Understanding the interactions between this virus and the human immune system is essential for the development of new strategies more effective therapies and diagnoses. This study aimed to predict epitopes for SARS-CoV-2 T and B cells, as well as evaluate the interaction of the spike protein with other viral proteins, using bioinformatics methods. SARS-CoV-2 protein sequences were collected from UniProt. Epitopes for T cells were predicted in silico using specific HLA alleles from the Bahia population. Epitopes for B cells were predicted using the IEDB server with multiple methods based on amino acid features. Protein-protein interaction was analyzed using the STRING database. The result is 10,671 peptides related to various SARS-CoV-2 viral proteins, including the spike, essential for the infection and pathogenesis of COVID-19. In addition to spike, proteins such as ORF3a, ORF7a, and ORF8 showed significant immunogenic potential. Protein-protein interaction analysis revealed that proteases such as TMPRSS2 and TMPRSS11D are crucial for viral entry and are potential therapeutic targets. This study expands the understanding of the molecular interactions of SARS-CoV-2, highlighting new therapeutic targets and clinical complications associated with COVID-19. The results provide valuable insights for the development of targeted therapeutic strategies and improved diagnostics, contributing to the mitigation of the global pandemic.

Extracellular matrix (ECM) pathway involved in skin immune response of Cynoglossus semilaevis upon Vibrio vulnificus infection

Half-smooth tongue sole (Cynoglossus semilaevis) is regarded as a significant commercial marine fish species in China, and frequent outbreaks of vibriosis has led to substantial economic losses. In this study, we investigated the molecular mechanisms underlying the involvement of the extracellular matrix (ECM) signaling pathway in the skin immune response of C. semilaevis infected with Vibrio vulnificus. The results showed that most differentially expressed proteins (DEPs) were identified through iTRAQ proteome analysis, and ten ECM-related proteins were screened at 12 and 36 ​h post-infection (hpi). Notably, several DEPs associated with ECM including HSPG, FN, COCH, LAMB1, LAMC1, TSPN, COL6A1, AMBP, HX and ITGA6 were tested for their expression at the transcriptional level during V. vulnificus infection using qRT-PCR assay. The analysis of protein-protein interaction (PPI) showed that the integrin ITGA6 exhibited obvious interactions among ECM-related DEPs. Furthermore, the spatio-temporal expression of the Csitga6 gene was highest in the skin, gill, muscle, and spleen, but lower in the liver, kidney and intestine. To our knowledge, this is the first report on the involvement of ECM pathway in the skin immune response to V. vulnificus infection, and provides a reference for further study of the ECM mechanism in the mucosal immune response of marine fish.

Mitochondrial Impact of Organophosphate Pesticide-Induced Cardiotoxicity: An In Silico and In Vitro Study.

Organophosphate pesticides are widely used; however, their use is limited due to neurotoxicity and, to a lesser extent, cardiotoxicity in humans. Given the high energy demands of cardiac muscle, which is characterized by a dense population of mitochondria, any damage to these organelles can exacerbate cardiotoxicity. This study aims to elucidate whether the cardiotoxic effects of organophosphate pesticides originate from mitochondrial dysfunction. To investigate this, in silico toxicogenomic analyses were performed using various tools, such as the Comparative Toxicogenomic Database, GeneMANIA, STRING, and Cytoscape. Results revealed that 11 out of the 13 WHO-recommended Class Ia organophosphate pesticides target genes associated with cardiotoxicity. Notably, three of these genes were mitochondrial, with catalase (CAT) being the common differentially expressed gene among parathion, methyl parathion, and phorate. Furthermore, protein-protein interaction analysis indicated a strong association between CAT and superoxide dismutase 2, mitochondrial (SOD2). Subsequently, isolated heart mitochondria were utilized to assess CAT and superoxide dismutase (SOD) activities in vitro. The findings demonstrated that at a concentration of 7.5ng/µL, both methyl parathion and phorate significantly decreased CAT activity by approximately 35%. Moreover, phorate reduced total SOD and SOD2 activities by 17% and 19%, respectively, at the same concentration. In contrast, none of the three organophosphate pesticides induced the opening of the mitochondrial permeability transition pore. These results suggest that the reduction in CAT and SOD2 activities, critical antioxidant enzymes, leads to the accumulation of reactive oxygen species within mitochondria, ultimately resulting in mitochondrial damage. This mechanism likely underlies the observed cardiotoxicity induced by these organophosphate pesticides.

Novel insights into STIM1's role in store-operated calcium entry and its implications for T-cell mediated inflammation in trigeminal neuralgia.

This investigation aims to elucidate the novel role of Stromal Interaction Molecule 1 (STIM1) in modulating store-operated calcium entry (SOCE) and its subsequent impact on inflammatory cytokine release in T lymphocytes, thereby advancing our understanding of trigeminal neuralgia (TN) pathogenesis. Employing the Gene Expression Omnibus (GEO) database, we extracted microarray data pertinent to TN to identify differentially expressed genes (DEGs). A subsequent comparison with SOCE-related genes from the Genecards database helped pinpoint potential target genes. The STRING database facilitated protein-protein interaction (PPI) analysis to spotlight STIM1 as a gene of interest in TN. Through histological staining, transmission electron microscopy (TEM), and behavioral assessments, we probed STIM1's pathological effects on TN in rat models. Additionally, we examined STIM1's influence on the SOCE pathway in trigeminal ganglion cells using techniques like calcium content measurement, patch clamp electrophysiology, and STIM1- ORAI1 co-localization studies. Changes in the expression of inflammatory markers (TNF-α, IL-1β, IL-6) in T cells were quantified using Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) in vitro, while immunohistochemistry and flow cytometry were applied in vivo to assess these cytokines and T cell count alterations. Our bioinformatic approach highlighted STIM1's significant overexpression in TN patients, underscoring its pivotal role in TN's etiology and progression. Experimental findings from both in vitro and in vivo studies corroborated STIM1's regulatory influence on the SOCE pathway. Furthermore, STIM1 was shown to mediate SOCE-induced inflammatory cytokine release in T lymphocytes, a critical factor in TN development. Supportive evidence from histological, ultrastructural, and behavioral analyses reinforced the link between STIM1-mediated SOCE and T lymphocyte-driven inflammation in TN pathogenesis. This study presents novel evidence that STIM1 is a key regulator of SOCE and inflammatory cytokine release in T lymphocytes, contributing significantly to the pathogenesis of trigeminal neuralgia. Our findings not only deepen the understanding of TN's molecular underpinnings but also potentially open new avenues for targeted therapeutic strategies.

Bioinformatics and systems biology approaches to identify potential common pathogeneses for sarcopenia and osteoarthritis.

Sarcopenia, a geriatric syndrome characterized by progressive loss of muscle mass and strength, and osteoarthritis, a common degenerative joint disease, are both prevalent in elderly individuals. However, the relationship and molecular mechanisms underlying these two diseases have not been fully elucidated. In this study, we screened microarray data from the Gene Expression Omnibus to identify associations between sarcopenia and osteoarthritis. We employed multiple statistical methods and bioinformatics tools to analyze the shared DEGs (differentially expressed genes). Additionally, we identified 8 hub genes through functional enrichment analysis, protein-protein interaction analysis, transcription factor-gene interaction network analysis, and TF-miRNA coregulatory network analysis. We also discovered potential shared pathways between the two diseases, such as transcriptional misregulation in cancer, the FOXO signalling pathway, and endometrial cancer. Furthermore, based on common DEGs, we found that strophanthidin may be an optimal drug for treating sarcopenia and osteoarthritis, as indicated by the Drug Signatures database. Immune infiltration analysis was also performed on the sarcopenia and osteoarthritis datasets. Finally, receiver operating characteristic (ROC) curves were plotted to verify the reliability of our results. Our findings provide a theoretical foundation for future research on the potential common pathogenesis and molecular mechanisms of sarcopenia and osteoarthritis.

Precision Drug Repurposing: A Deep Learning Toolkit for Identifying 34 Hyperpigmentation-Associated Genes and Optimizing Treatment Selection.

Hyperpigmentation is a skin disorder characterized by a localized darkening of the skin due to increased melanin production. When patients fail first line topical treatments, secondary treatments such as chemical peels and lasers are offered. However, these interventions are not devoid of risks and are associated with postinflammatory hyperpigmentation. In the quest for novel therapeutic potentials, this study aims to investigate computational methods in the identification of new targeted therapies in the treatment of hyperpigmentation. We used a comprehensive approach, which integrated text mining, interpreting gene lists through enrichment analysis and integration of diverse biological information (GeneCodis), protein-protein association networks and functional enrichment analyses (STRING), and plug-in network centrality parameters (Cytoscape) to pinpoint genes closely associated with hyperpigmentation. Subsequently, analysis of drug-gene interactions to identify potential drugs (Cortellis) was utilized to select drugs targeting these identified genes. Lastly, we used Deep Learning Based Drug Repurposing Toolkit (DeepPurpose) to conduct drug-target interaction predictions to ultimately identify candidate drugs with the most promising binding affinities. Thirty-four hyperpigmentation-related genes were identified by text mining. Eight key genes were highlighted by utilizing GeneCodis, STRING, Cytoscape, gene enrichment, and protein-protein interaction analysis. Thirty-five drugs targeting hyperpigmentation-associated genes were identified by Cortellis, and 29 drugs, including 16 M2PK1 inhibitors, 11 KRAS inhibitors, and 2 BRAF inhibitors were recommended by DeepPurpose. The study highlights the promise of advanced computational methodology for identifying potential treatments for hyperpigmentation.

Network pharmacology study on fermented soybeans for the prevention of Alzheimer's disease in older individuals.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by the disruption of synaptic communication among millions of neurons. Recent research has highlighted the potential therapeutic effectiveness of natural polyphenolic compounds in addressing AD. Soybeans are abundant in polyphenols, and their polyphenolic composition undergoes significant alteration through fermentation by Eurotium cristatum. Through comprehensive database searches, we identified active components within fermented soybean polyphenols and genes associated with AD. Subsequently, we utilized Venn diagrams to analyze the overlap between AD-related genes and these components. Furthermore, we visualized the network between intersecting targets and proteins using Cytoscape software. The anti-AD effects of soybeans were further explored through comprehensive analysis, including protein-protein interaction analysis, pathway enrichment analysis, and molecular docking studies. Our investigation unveiled 6-hydroxydaidzein as a major component of fermented soybean polyphenols, shedding light on its potential therapeutic significance in combating AD. The intersection between target proteins of fermented soybeans and disease-related targets in AD comprised 34 genes. Protein-protein interaction analysis highlighted key potential targets, including glyceraldehyde-3-phosphate dehydrogenase (GAPDH), glycogen synthase kinase 3 beta (GSK3B), amyloid precursor protein (APP), cyclin-dependent kinase 5 (CDK5), and beta-site APP cleaving enzyme 1 (BACE1). Molecular docking results demonstrated a robust binding effect between major components from fermented soybeans and the aforesaid key targets implicated in AD treatment. These findings suggest that fermented soybeans demonstrate a degree of efficacy and present promising prospects in the prevention of AD.

Bidirectional effects of the tryptophan metabolite indole-3-acetaldehyde on colorectal cancer.

Colorectal cancer (CRC) has a high incidence and mortality. Recent studies have shown that indole derivatives involved in gut microbiota metabolism can impact the tumorigenesis, progression, and metastasis of CRC. To investigate the effect of indole-3-acetaldehyde (IAAD) on CRC. The effect of IAAD was evaluated in a syngeneic mouse model of CRC and CRC cell lines (HCT116 and DLD-1). Cell proliferation was assessed by Ki-67 fluorescence staining and cytotoxicity tests. Cell apoptosis was analysed by flow cytometry after staining with Annexin V-fluorescein isothiocyanate and propidium iodide. Invasiveness was investigated using the transwell assay. Western blotting and real-time fluorescence quantitative polymerase chain reaction were performed to evaluate the expression of epithelial-mesenchymal transition related genes and aryl hydrocarbon receptor (AhR) downstream genes. The PharmMapper, SEA, and SWISS databases were used to screen for potential target proteins of IAAD, and the core proteins were identified through the String database. IAAD reduced tumorigenesis in a syngeneic mouse model. In CRC cell lines HCT116 and DLD1, IAAD exhibited cytotoxicity starting at 24 h of treatment, while it reduced Ki67 expression in the nucleus. The results of flow cytometry showed that IAAD induced apoptosis in HCT116 cells but had no effect on DLD1 cells, which may be related to the activation of AhR. IAAD can also increase the invasiveness and epithelial-mesenchymal transition of HCT116 and DLD1 cells. At low concentrations (< 12.5 μmol/L), IAAD only exhibited cytotoxic effects without promoting cell invasion. In addition, predictions based on online databases, protein-protein interaction analysis, and molecular docking showed that IAAD can bind to matrix metalloproteinase-9 (MMP9), angiotensin converting enzyme (ACE), poly(ADP-ribose) polymerase-1 (PARP1), matrix metalloproteinase-2 (MMP2), and myeloperoxidase (MPO). Indole-3-aldehyde can induce cell apoptosis and inhibit cell proliferation to prevent the occurrence of CRC; however, at high concentrations (≥ 25 μmol/L), it can also promote epithelial-mesenchymal transition and invasion in CRC cells. IAAD activates AhR and directly binds MMP9, ACE, PARP1, MMP2, and MPO, which partly reveals why it has a bidirectional effect.

Kinesin binding as a shared pathway underlying the genetic basis of male factor infertility and insomnia

To study whether male factor infertility and insomnia share genetic risk variants and identify any molecular, cellular, and biologic interactions between these traits. The in silico study was performed. Two lists of genetic variants were manually curated through a literature review, one of those associated with male factor infertility and the other with insomnia. Genes were assigned to these variants to compose male factor infertility-associated (454 genes) and insomnia-associated (921 genes) gene lists. Not applicable. Not applicable. Not applicable. Enrichment of biologic pathways and protein-protein interaction analysis. Twenty-eight genes were common to both lists, representing a greater overlap than would be expected by chance. In the 28 genes contained in the intersection list, there was a significant enrichment of pathways related to kinesin binding. A protein-protein interaction analysis using the intersection list as input retrieved 25 nodes and indicated that two of them were kinesin-related proteins (PLEKHM2 and KCL1). The shared male factor infertility and insomnia genes, and the biologic pathways highlighted in this study, suggest that further functional investigations into the interplay between fertility and sleep are warranted.