Pyrethroid insecticides are widely used globally, but their potential nephrotoxicity has gained increasing attention. Although previous studies suggest pyrethroids may induce acute kidney injury (AKI), the underlying mechanisms remain unclear. This study employed a network toxicology approach to elucidate the molecular mechanisms of pyrethroid-induced AKI. Eight commonly used pyrethroids were analyzed individually. A total of 3203 AKI-related genes were retrieved from public databases, and intersection analysis identified 157-196 common targets for each pyrethroid. Protein-protein interaction (PPI) network integration further identified 18 shared hub targets across the eight pyrethroids, among which 15 were further supported by GEO validation in AKI samples. Notably, 7 targets - SRC, CASP3, ESR1, CCND1, MMP9, BCL2, and HSP90AA1-were consistently shared across all compounds and were therefore considered as core targets. Enrichment analyses indicated that these targets were mainly involved in oxidative stress-, inflammation- and apoptosis-related processes. GEO validation further suggested that these alterations were particularly prominent in renal tubular cells and endothelial cells. Molecular docking supported potential interactions between pyrethroids and the core targets. The findings suggested that pyrethroid-induced AKI may involve processes related to oxidative stress, inflammation, and apoptosis, accompanied by impaired repair responses, ultimately disrupting the balance between injury and regeneration in renal tubular epithelial cells.

Rationale: Immune checkpoint inhibitors, particularly programmed cell death protein 1 (PD-1) blockers, have transformed cancer therapy but can induce immune-related endocrine toxicities. Severe involvement of multiple endocrine axes, including dual pituitary dysfunction, is rare and challenging to diagnose due to nonspecific clinical features. Highlighting such cases can improve early recognition and management. Patient concerns: A 56-year-old man with esophageal cancer developed fatigue, polyuria, polydipsia, dizziness, and severe hyponatremia after treatment with tislelizumab, a PD-1 inhibitor. Diagnoses: Laboratory evaluation revealed new-onset autoimmune diabetes, hypothyroidism, and secondary adrenal insufficiency. The constellation of biochemical abnormalities and clinical features, in the absence of alternative etiologies, indicated immune-related hypophysitis and pancreatic islet injury. Two additional cases of severe, recurrent hyponatremia after PD-1 therapy were also reviewed. Interventions: The patient received targeted hormone replacement therapy, including glucocorticoids and levothyroxine, along with insulin for glycemic control. Outcomes: Symptoms improved significantly, and biochemical parameters normalized following treatment, demonstrating effective management of multi-glandular endocrine failure induced by PD-1 blockade. Lessons: PD-1 inhibitors can cause severe, concurrent dysfunction of multiple endocrine organs. Clinicians should maintain high vigilance, implement proactive screening for pituitary and metabolic abnormalities during and after immune checkpoint inhibitor therapy, and adopt a multidisciplinary approach to ensure timely diagnosis and treatment.

Type 2 diabetes mellitus (T2DM) is a highly heterogeneous disease with a varying risk of complications. The recent novel subgroup classification using cluster analysis contributed to the risk evaluation of diabetic complications. However, whether the subgroup classification strategy could be adopted to predict the risk of onset and progression of diabetic kidney disease (DKD) in Chinese individuals with T2DM remains to be elucidated. In this retrospective study, 612 Chinese patients with T2DM were enrolled, and the median follow-up time was 3.5 years. The T2DM subgroups were categorized by a two-step cluster analysis based on five parameters, including age at onset of diabetes, body mass index (BMI), glycosylated hemoglobin (HbA1c), homeostasis model assessment 2 of insulin resistance (HOMA2-IR), and homeostasis model assessment 2 of β-cell function (HOMA2-β). Clinical characteristics across subgroups were compared using t-tests and chi-square tests. Furthermore, multivariate logistic regression models were adopted to assess the risk of albuminuria progression and renal function decline among different subgroups. The cohort was categorized into four groups: severe insulin-deficient diabetes (SIDD), with 146 patients (23.9

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.

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: Radiation-induced oral mucositis (RIOM) is an intractable inflammatory disease whose pathogenesis needs to be clarified. “Kouchuangling” (KCL), a traditional Chinese medicine formula, is composed of Lonicerae Japonicae Flos, Radix Paeoniae Rubra, and Radix Sanguisorbae. Although all of them are Chinese folk medicines which have long been utilized for ameliorating inflammation, the mechanism of KCL to RIOM remains unclear. Purpose: To predict the active ingredients of KCL and identify the mechanism of KCL on RIOM. Material and Methods: We identified the chemical ingredients in KCL using TCM Systems Pharmacology (TCMSP), TCM@Taiwan, PubChem, and SuperPred databases and used the oral bioavailability (OB), drug-like properties (DL) and Degree of compounds for screening. Targets for oral mucositis were obtained from the Online Mendelian Inheritance in Man (OMIM), Therapeutic Target Database (TTD), PharmGKB, and DrugBank databases. Cytoscape 3.7.0 was used to visualize the compound-target-disease network for KCL and RIOM. The biological processes of target gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were analyzed using DAVID. Results: Based on OB≥30%, DL≥0.18 and Degree≥3, 24 active ingredients and 960 targets on which the active components acted were identified. A total of 1387 targets for oral mucositis were screened. GO enrichment and KEGG pathway analyses resulted in 43 biological processes (BPs), 3 cell components (CCs), 5 molecular functions (MFs), and 32 KEGG pathways, including leishmaniasis, Toll-like receptor signaling, TNF signaling, and Influenza A pathways. Conclusion: This experiment preliminarily verified that the active ingredients of KCL play a role in the treatment of RIOM through multiple targets and pathways, providing a reference for further study of the pharmacological mechanism of Chinese herbal medicine.

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.

Metabolic syndrome, which affects approximately one-quarter of the world’s population, is a combination of multiple traits and is associated with high all-cause mortality, increased cancer risk, and other hazards. It has been shown that the epigenetic functions of miRNAs are closely related to metabolic syndrome, but epigenetic studies have not yet fully elucidated the regulatory network and key genes associated with metabolic syndrome. To perform data analysis and screening of potential differentially expressed target miRNAs, mRNAs and genes based on a bioinformatics approach using a metabolic syndrome mRNA and miRNA gene microarray, leading to further analysis and identification of metabolic syndrome-related miRNA–mRNA regulatory networks and key genes. The miRNA gene set (GSE98896) and mRNA gene set (GSE98895) of peripheral blood samples from patients with metabolic syndrome from the GEO database were screened, and set|logFC|> 1 and adjusted P < 0.05 were used to identify the differentially expressed miRNAs and mRNAs. Differentially expressed miRNA transcription factors were predicted using FunRich software and subjected to GO and KEGG enrichment analysis. Next, biological process enrichment analysis of differentially expressed mRNAs was performed with Metascape. Differentially expressed miRNAs and mRNAs were identified and visualized as miRNA–mRNA regulatory networks based on the complementary pairing principle. Data analysis of genome-wide metabolic syndrome-related mRNAs was performed using the gene set enrichment analysis (GSEA) database. Finally, further WGCNA of the set of genes most closely associated with metabolic syndrome was performed to validate the findings. A total of 217 differentially expressed mRNAs and 158 differentially expressed miRNAs were identified by screening the metabolic syndrome miRNA and mRNA gene sets, and these molecules mainly included transcription factors, such as SP1, SP4, and EGR1, that function in the IL-17 signalling pathway; cytokine–cytokine receptor interaction; proteoglycan syndecan-mediated signalling events; and the glypican pathway, which is involved in the inflammatory response and glucose and lipid metabolism. miR-34C-5P, which was identified by constructing a miRNA–mRNA regulatory network, could regulate DPYSL4 expression to influence insulin β-cells, the inflammatory response and glucose oxidative catabolism. Based on GSEA, metabolic syndrome is known to be closely related to oxidative phosphorylation, DNA repair, neuronal damage, and glycolysis. Finally, RStudio and DAVID were used to perform WGCNA of the gene sets most closely associated with metabolic syndrome, and the results further validated the conclusions. Metabolic syndrome is a common metabolic disease worldwide, and its mechanism of action is closely related to the inflammatory response, glycolipid metabolism, and impaired mitochondrial function. miR-34C-5P can regulate DPYSL4 expression and can be a potential research target. In addition, UQCRQ and NDUFA8 are core genes of oxidative phosphorylation and have also been identified as potential targets for the future treatment of metabolic syndrome.

目的:系统评价温胆汤治疗糖尿病胃轻瘫的临床有效性、安全性及复发率等.方法:通过计算机及手工检索Pub Med、The Cochrane Library、Web of Science、中国知网、万方、维普及生物医学文献数据库,纳入2000年1月-2020年10月使用温胆汤治疗糖尿病胃轻瘫的随机对照试验(randomized controlled trial,RCT).采用Rev man 5.4软件进行Meta分析.结果:研究共纳入8篇文献,总计688例患者,Meta分析结果显示温胆汤治疗有效率(RR=1.32,95％CI[1.23,1.42],P＜0.00001)优于对照组,温胆汤治疗复发率(RR=0.31,95％CI[0.18,0.53],P＜0.0001)、不良反应发生率(RR=0.27,95％CI[0.11,0.67],P=0.005)低于对照组,空腹血糖(MD=-0.22,95％C1[-0.55,0.11],P=0.18＞0.05)差异无统计学意义.结论:温胆汤能提高糖尿病胃轻瘫临床有效率,且复发率跟不良反应发生率较低,安全性较高.但部分纳入文献质量偏低,临床病例相对有限,仍需大样本、高质量的随机对照试验验证.

本文旨在通过探讨中医药治疗糖尿病认知功能障碍的用药特点与规律,为临床用药提供新的参考.运用中国知网(CNKI)、万方数据(WF)、维普期刊全文数据库(VIP)、生物医学文献数据库(CBM)、及中国科学引文数据库(CSCD)检索自1999年1月至2020年10月收载的中医药治疗糖尿病认知功能障碍文献,经筛选后建立数据库,运用Microsoft Excel 2019、SPSS Modeler 18.0、SPSS Statistics 25.0软件进行数据挖掘,分析用药规律.通过检索TCM-SP、OMIM、TTD、Pharm Gkb和Drugbank数据库获得核心药物组合和疾病的有效活性成分,利用Cytoscape 3.8.0软件构建"化合物-靶点"作用网络图,运用Stitch和String构建蛋白质-蛋白质相互作用(PPI)网络,并通过Cytoscape进行网络拓扑分析获得药物和疾病交互的核心靶点.筛选DAVID数据库对核心靶点进行GO和KEGG富集分析.结果 共纳入文献33篇,中药处方123首,获得高频中药20味,桃仁-红花、当归-桃仁-川芎、熟地黄-菟丝子-枸杞子等26对核心药物组合,通过因子分析提取8个公因子,聚类分析得到6类,得到核心组方的有效活性成分109个,药物潜在基因靶点1620个,疾病潜在基因靶点1490个,核心组方治疗疾病的核心靶点76个,涉及237条GO富集功能和96条KEGG通路.发现中医治疗糖尿病认知功能障碍以活血化瘀、化痰开窍、滋益固肾为原则,其核心药物治疗糖尿病认知功能障碍的作用机制可能与胰岛素抵抗、细胞凋亡、炎症反应、内质网应激等密切相关.