Background: Type 2 diabetes-associated cognitive dysfunction (DCD) is a chronic complication of diabetes that has gained international attention. The medicinal compound Banxia Xiexin Decoction (BXXXD) from traditional Chinese medicine (TCM) has shown potential in improving insulin resistance, regulating endoplasmic reticulum stress (ERS), and inhibiting cell apoptosis through various pathways. However, the specific mechanism of action and medical value of BXXXD remain unclear. Methods: We utilized TCMSP databases to screen the chemical constituents of BXXXD and identified DCD disease targets through relevant databases. By using Stitch and String databases, we imported the data into Cytoscape 3.8.0 software to construct a protein-protein interaction (PPI) network and subsequently identified core targets through network topology analysis. The core targets were subjected to Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The results were further validated through in vitro experiments. Results: Network pharmacology analysis revealed the screening of 1490 DCD-related targets and 190 agents present in BXXXD. The topological analysis and enrichment analysis conducted using Cytoscape software identified 34 core targets. Additionally, GO and KEGG pathway analyses yielded 104 biological targets and 97 pathways, respectively. BXXXD exhibited its potential in treating DCD by controlling synaptic plasticity and conduction, suppressing apoptosis, reducing inflammation, and acting as an antioxidant. In a high glucose (HG) environment, the expression of JNK, Foxo3a, SIRT1, ATG7, Lamp2, and LC3 was downregulated. BXXXD intervention on HT22 cells potentially involved inhibiting excessive oxidative stress, promoting neuronal autophagy, and increasing the expression levels of JNK, SIRT1, Foxo3a, ATG7, Lamp2, and LC3. Furthermore, the neuroprotective effect of BXXXD was partially blocked by SP600125, while quercetin enhanced the favorable role of BXXXD in the HG environment. Conclusion: BXXXD exerts its effects on DCD through multiple components, targets, levels, and pathways. It modulates the JNK/SIRT1/Foxo3a signaling pathway to mitigate autophagy inhibition and apoptotic damage in HT22 cells induced by HG. These findings provide valuable perspectives and concepts for future clinical trials and fundamental research.

This study aims to elucidate the potential genetic commonalities between metabolic syndrome (MetS) and rheumatic diseases through a disease interactome network, according to publicly available large‐scale genome‐wide association studies (GWAS). The analysis included linkage disequilibrium score regression analysis, cross trait meta‐analysis and colocalisation analysis to identify common genetic overlap. Using modular partitioning, the network‐based association between the two disease proteins in the protein–protein interaction set was divided and quantified. Clinical samples from public databases were used to confirm the mapped genes. Mendelian randomisation analyses were conducted using genetic instrumental variables for causal inference. MetS and rheumatoid arthritis (RA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), Sjogren's syndrome (SS) and their primary module networks shared topological overlap and genetic correlation. Functional analysis highlighted the significance of these shared targets in processes such as a diverse array of metabolic pathways involving glucose, lipids, energy, protein transport, inflammatory response, autophagy and cytokine regulation, elucidating the pathways through which MetS intersects with rheumatic diseases. Causal associations were determined between MetS phenotypes and rheumatic diseases. The persistence of MetS effects on rheumatic diseases remained evident even after adjusting for alcohol consumption and smoking. We have highlighted specific genetic associations between MetS and rheumatic diseases. Several genes (e.g., PRRC2A, PSMB8, BAG6, GPSM3, PBX2, etc.) have been identified with molecular commonalities in MetS and RA, AS, SLE and SS, which may serve as potential targets for shared treatments.

Objective: To estimate the survival and prognosis of patients with thyroid carcinoma (THCA) based on the Long non-coding RNA (lncRNA) traits linked to cuproptosis and to investigate the connection between the immunological spectrum of THCA and medication sensitivity.Methods: RNA-Seq data and clinical information for THCA were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We built a risk prognosis model by identifying and excluding lncRNAs associated with cuproptosis using Cox regression and LASSO methods. Both possible biological and immune infiltration functions were investigated using Principal Component Analysis (PCA), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and immunoassays. The sensitivity of the immune response to possible THCA medicines was assessed using ratings for tumor immune dysfunction and exclusion (TIDE) and tumor mutational burden (TMB).Results: Seven cuproptosis-related lncRNAs were used to construct our prognostic prediction model: AC108704.1, DIO3OS, AL157388.1, AL138767.3, STARD13-AS, AC008532.1, and PLBD1-AS1. Using data from TCGA’s training, testing, and all groups, Kaplan-Meier and ROC curves demonstrated this feature’s adequate predictive validity. Different clinical characteristics have varying effects on cuproptosis-related lncRNA risk models. Further analysis of immune cell infiltration and single sample Gene Set Enrichment Analysis (ssGSEA) supported the possibility that cuproptosis-associated lncRNAs and THCA tumor immunity were closely connected. Significantly, individuals with THCA showed a considerable decline in survival owing to the superposition effect of patients in the high-risk category and high TMB. Additionally, the low-risk group had a higher TIDE score compared with the high-risk group, indicating that these patients had suboptimal immune checkpoint blocking responses. To ensure the accuracy and reliability of our results, we further verified them using several GEO databases.Conclusion: The clinical and risk aspects of cuproptosis-related lncRNAs may aid in determining the prognosis of patients with THCA and improving therapeutic choices.

Drug prediction and treatment using bioinformatics and large-scale modeling have emerged as pivotal research areas. This study proposes a novel multi-level collaboration framework named Syn-COM for feature extraction and data integration of diseases and drugs. The framework aims to explore optimal drug combinations and interactions by integrating molecular virtuality, similarity clustering, overlap area, and network distance. It uniquely combines the characteristics of Chinese herbal medicine with clinical experience and innovatively assesses drug interaction and correlation through a synergy matrix. Gouty arthritis (GA) was used as a case study to validate the framework’s reliability, leading to the identification of an effective drug combination for GA treatment, comprising Tamaricis Cacumen (S_i = 0.73), Cuscutae Semen (S_i = 0.68), Artemisiae Annuae Herba (S_i = 0.62), Schizonepetae Herba (S_i = 0.73), Gleditsiae Spina (S_i = 0.89), Prunellae Spica (S_i = 0.75), and Achyranthis Bidentatae Radix (S_i = 0.62). The efficacy of the identified drug combination was confirmed through animal experiments and traditional Chinese medicine (TCM) component analysis. Results demonstrated significant reductions in the blood inflammatory factors IL1A, IL6, and uric acid, as well as downregulation of TGFB1, PTGS2, and MMP3 expression (p < 0.05), along with improvements in ankle joint swelling in GA mice. This drug combination notably enhances therapeutic outcomes in GA by targeting key genes, underscoring the potential of integrating traditional medicine with modern bioinformatics for effective disease treatment.

Background: Diabetic cognitive dysfunction (DCD) is emerging as a chronic complication of diabetes that is gaining increasing international recognition. The traditional Chinese medicine (TCM) formulation, Tangzhiqing decoction (TZQ), has shown the capacity to modulate the memory function of mice with DCD by ameliorating insulin resistance. Nevertheless, the precise mechanism underlying the effects of TZQ remains elusive. Methods: The chemical constituents of TZQ were screened using TCMSP databases, and DCDassociated disease targets were retrieved from various databases. Subsequently, core targets were identified through network topology analysis. The core targets underwent analysis using Gene Ontology (GO) functional annotations and enrichment in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Models were established through high-fat and high-glucose diet feeding along with intraperitoneal injection of streptozotocin (STZ). TZQ and metformin were administered at varying doses over 8 weeks. The Morris water maze was employed to evaluate the cognitive capabilities of each rat group, while indicators of oxidative stress and insulin were assessed in mice. Neuronal apoptosis in distinct groups of mice's hippocampi was detected using TdT-mediated dUTP Nick-End Labeling (TUNEL), and western blot (WB) analysis was conducted to assess the expression of apoptosis- and autophagy-related proteins, including Bax, Bcl2, Caspase3, Caspase8, Beclin1, ATG7, LC3, p62, and Lamp2, within the hippocampus. Results:: TZQ exhibited the capacity to modulate neuronal autophagy, ameliorate endoplasmic reticulum stress, apoptosis, inflammation, and oxidative stress, as well as to regulate synaptic plasticity and conduction. TZQ mitigated cognitive dysfunction in mice, while also regulating hippocampal inflammation and apoptosis. Additionally, it influenced the protein expression of autophagy-related factors such as Bax, Bcl2, Caspase3, Caspase8, Beclin1, ATG7, and LC3. Notably, this modulation significantly reduced neuronal apoptosis in the hippocampus and curbed excessive autophagy. Conclusion: TZQ demonstrated a substantial reduction in neuronal apoptosis within the hippocampus and effectively suppressed excessive autophagy.

Background: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder. Riluzole, Edaravone, and Tofersen, three promising treatments, have distinct profiles that merit comparative analysis to guide clinical decision-making. Methods: This study utilizes a pharmacovigilance analysis of adverse events reported in the FDA Adverse Event Reporting System database from Q1 2004 to Q2 2024. Employing disproportionality, we assessed and compared the AE signals associated with Riluzole, Edaravone, and Tofersen to elucidate their safety profiles in ALS treatment. Finally, applying the Random Walk with Restart (RWR) algorithm to the protein-protein interaction (PPI) network for selecting drug target genes that have a strong correlation genes associated with severe adverse reactions. Finally, their interactions with the target were assessed through molecular docking and transcriptome analysis. Results: The analysis included 2106 AE reports for Riluzole, 2466 AE reports for Edaravone, and 136 for Tofersen. Highlights the higher incidence of adverse reactions associated with Riluzole, including abdominal discomfort, hypoaesthesia oral, and hepatic enzyme increased, as well as a significant correlation between Edaravone and falls, gait disturbance, and aphasia. Tofersen exhibits different adverse reactions compared to Riluzole and Edaravone, such as headaches, csf red blood cell count positive. Comparative analysis revealed that the three drugs shared a serious adverse reaction, which is thrombosis. RWR analysis identified seven targets related to thrombosis caused by the three drugs, including F10 and MMP9. Subsequently, molecular docking and transcriptome analysis indicate a favorable binding interaction between the drug candidate and the F10 molecule. Conclusion: This comprehensive evaluation underscores the importance of understanding the distinct AE profiles of Riluzole, Edaravone, and Tofersen in clinical practice, providing valuable insights for personalized ALS management. Future research with rigorous prospective designs is recommended to validate these findings and explore the mechanisms underlying the reported adverse events.