Biomolecules & biomedicine最新文献

The risk factors for liver injury induced by valproic acid (VPA) are not well understood, and no predictive tool currently exists to identify patients at risk. This study aims to explore these risk factors and develop a predictive model. We collected medical data from patients treated with VPA between January 1, 2020, and October 31, 2023. Prescription sequence analysis was used to identify patients with suspected VPA-induced liver injury, and the Roussel Uclaf Causality Assessment Method was applied to confirm the diagnosis. Risk factors were analyzed using logistic regression, and a nomogram model was developed and evaluated. A total of 256 cases were included in the study: 64 in the VPA-induced liver injury group and 192 in the control group. The incidence of liver injury was 5.3%. Multivariate logistic regression analysis revealed that dysglycemia (odds ratio [OR] = 5.171; 95% confidence interval [CI]: 1.254-21.325), hyperlipidemia (OR = 4.903; 95% CI: 1.400-17.173), surgery (OR = 10.020; 95% CI: 1.737-57.805), and hypokalemia (OR = 10.407; 95% CI: 2.398-45.173) were significant independent risk factors for VPA-induced liver injury. The area under the receiver operating characteristic curve was 0.904 (95% CI: 0.860-0.947), indicating excellent model performance. The Hosmer-Lemeshow test yielded a P value of 0.2671, and the calibration plot slope was close to one, further supporting the model's accuracy. The findings suggest that patients with dysglycemia, hyperlipidemia, a history of surgery, and hypokalemia are at higher risk for VPA-induced liver injury. The nomogram model provides a reliable method for predicting the likelihood of liver injury in these patients.

Closed pelvic fractures can lead to severe complications, including hemodynamic instability (HI) and mortality. Accurate prediction of these risks is crucial for effective clinical management. This study aimed to utilize various machine learning (ML) algorithms to predict HI and death in patients with closed pelvic fractures and identify relevant risk factors. The retrospective study included 208 patients diagnosed with pelvic fractures and admitted to Suning Traditional Chinese Medicine Hospital between 2019 and 2023. Among these, 133 cases were identified as closed PFs. Patients with closed fractures were divided into a training set (n = 115) and a test set (n = 18). The training set was further stratified into two groups based on hemodynamic stability: Group A (patients with HI) and Group B (patients with hemodynamic stability). A total of 40 clinical variables were collected, and multiple machine learning algorithms were employed to develop predictive models, including logistic regression (LR), C5.0 Decision Tree (DT), Naive Bayes (NB), support vector machine (SVM), K-nearest neighbors (KNN), random Forest (RF), and artificial neural network (ANN). Additionally, factor analysis was performed to assess the interrelationships between variables. The RF and LR algorithms outperformed traditional methods-such as central venous pressure (CVP) and intra-abdominal pressure (IAP) measurements-in predicting HI. The RF model achieved an average under the ROC (AUC) of 0.92, with an accuracy of 0.86, precision of 0.81, and an F1 score of 0.87. The LR model had an average AUC of 0.82 but shared the same accuracy, precision, and F1 score as the RF model. Key risk factors identified included TILE grade, heart rate (HR), creatinine (CR), white blood cell count (WBC), fibrinogen (FIB), and lactic acid (LAC), with LAC levels >3.7 and an injury severity score (ISS) >13 as significant predictors of HI and mortality. In conclusion, the RF and LR algorithms are effective in predicting HI and mortality risk in patients with closed PFs, enhancing clinical decision-making and improving patient outcomes.

The incidence of atrial fibrillation (AF) increases with age and is particularly high in individuals with diabetes. Sodium-glucose cotransporter-2 inhibitors (SGLT2i), such as dapagliflozin, show promise in treating heart failure (HF) and reducing the risk of AF. Sirtuin 1 (SIRT1), a key enzyme in metabolic regulation, may be influenced by SGLT2i and play a role in the development of AF. This study investigates the relationship between dapagliflozin therapy and atrial tachyarrhythmia in diabetic cardiomyopathy, with a focus on the role of SIRT1. A streptozotocin (STZ)-induced diabetes mellitus (DM) rat model was used to assess AF across four groups: sham, STZ, STZ with dapagliflozin, and STZ with dapagliflozin + sirtinol (a SIRT1 inhibitor). Additionally, HL-1 cardiomyocytes were cultured under high glucose (HG) conditions and treated with dapagliflozin, with or without sirtinol. In the rat model, dapagliflozin improved atrial fibrosis and reduced AF inducibility and duration-effects that were partially reversed by sirtinol. These findings suggest that dapagliflozin may alleviate cardiac fibrosis and atrial arrhythmia by modulating SIRT1. In HL-1 cells under HG conditions, dapagliflozin reduced apoptosis, restored autophagy and mitophagy, and improved calcium channel activity. However, sirtinol negated these protective effects. Dapagliflozin helped normalize autophagy, mitophagy, and calcium handling, while sirtinol diminished its protective effects, highlighting the key role of SIRT1 in regulating calcium handling under HG conditions. Overall, SIRT1 plays a protective role in diabetic cardiomyopathy by reducing apoptosis, regulating autophagy and mitophagy, and modulating calcium channel activity. Dapagliflozin reduces AF duration and inducibility in the STZ model, likely through SIRT1 upregulation and calcium channel modulation.

Immune checkpoint inhibitors produce durable antitumor effects in various cancers, but not all patients respond. High tumor mutational burden (TMB) is a known predictor of clinical benefit. In this study, we focused on the MHC-I-dependent neoantigen presentation pathway to enhance predictive capabilities beyond TMB. Using pan-cancer immunogenomic analyses of somatic mutation data from The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC), we analyzed 33 cancer types. Objective response rates (ORRs) to PD-1/PD-L1 inhibitors were evaluated in relation to immune characteristics, including TMB, neoantigen load, MHC-I gene expression, and CD8+ T cell fraction. Spearman’s rank correlation was used to assess these relationships. TMB showed the strongest correlation with ORR (r = 0.783, P = 2.17 × 10⁻⁵). However, integrating TMB, HLA-A expression, and CD8+ T cell fraction significantly improved predictive accuracy (r = 0.865, P = 1.80 × 10⁻⁶). Validation in external cohorts confirmed these findings, revealing notable differences in MHC-I pathway activity between responders and non-responders to immunotherapy. Our results demonstrate that the MHC-I antigen presentation pathway is strongly associated with response to PD-1/PD-L1 inhibitors. Importantly, combining antigen expression, processing, presentation, and recognition features provides superior predictive power compared to TMB alone. This integrated approach could improve treatment outcome predictions and advance personalized immunotherapy strategies.

Inhibiting ferroptosis represents a promising strategy for managing neuronal injury caused by intracerebral hemorrhage (ICH). Platelet factor 4 (PF4), a chemokine with diverse biological functions, has an unclear role in ICH and its impact on neuronal ferroptosis. To investigate this, a hemin-induced injury model was established in PC12 cells in vitro, and an ICH model was created in vivo using IV collagenase injection. Hemin-treated PC12 cells were co-cultured with recombinant mouse PF4 (Rm-PF4) protein to examine the effects of PF4 on ferroptosis. Additionally, Rm-PF4 was administered intraperitoneally to ICH mice, and its influence on neurological dysfunction, brain edema, and neuronal ferroptosis was evaluated. Western blot analysis was employed to assess PF4 levels, CXCR3/phosphatidylinositol 3-kinase (PI3K)/AKT/nuclear factor erythroid-2-related factor 2 (Nrf2) pathway activation, and ferroptosis-related protein expression. PF4 levels were found to be reduced in both perihematomal brain tissues of ICH mice and hemin-treated PC12 cells. Treatment with Rm-PF4 decreased ferrous ion, malondialdehyde (MDA), and reactive oxygen species (ROS) levels, effectively inhibiting ferroptosis in PC12 cells. Furthermore, Rm-PF4 administration alleviated neurological dysfunction, neuronal damage, and brain edema while suppressing neuronal ferroptosis in ICH mice. Mechanistically, Rm-PF4 activated the CXCR3/PI3K/AKT/Nrf2 pathway, and this protective effect was diminished by a CXCR3 antagonist in both ICH mice and hemin-treated PC12 cells. In conclusion, PF4 mitigates ICH-induced neuronal ferroptosis in mouse models and PC12 cells by activating the CXCR3/PI3K/AKT/Nrf2 pathway.

The Wnt signaling pathway is one of the most important and critical signaling pathways for maintaining cellular functions, such as cell proliferation and differentiation. Increasing evidence substantiates that the Wnt signaling pathway also plays a significant role in the regulation of bone formation in osteoporosis. Accordingly, inhibitors of this pathway, such as sclerostin, Dickkopf-1 (DKK1), WNT inhibitory factor 1 (WIF1), and secreted frizzled-related proteins (SFRPs), have a negative regulatory role in bone formation and may serve as effective therapeutic targets for osteoporosis. This review examines the mechanisms of action of Wnt signaling pathway inhibitors in osteoporosis, the relationship between the Wnt pathway and its inhibitors, and new molecular targets for osteoporosis treatment. Overall, the regulatory mechanisms of Wnt pathway inhibitors are summarized to provide scientific and theoretical guidance for the treatment and prevention of osteoporosis.

Vulvovaginal candidiasis (VVC) is a common fungal infection caused primarily by Candida albicans, characterized by inflammation and discomfort, often requiring effective therapeutic strategies to reduce fungal load and inflammation. This study aimed to explore the therapeutic effects and underlying mechanisms of combining aspirin (ASP) and itraconazole (ITR) in treating vulvovaginal candidiasis (VVC) through activation of the NF-κB signaling pathway. Clinical isolates of Candida albicans were selected, and the M27-A4 microbroth dilution method was used for in vitro drug sensitivity testing. A VVC model was established, and after three days of continuous administration, fungal load, inflammatory factors, and pathway protein expression were analyzed using Gram staining, plate counting, glycogen (PAS) staining, ELISA, and qPCR. The results of the in vitro drug sensitivity tests revealed that the MIC50 values of ASP and ITR were significantly reduced when the two drugs were combined. In animal experiments, the VVC model group exhibited a substantial vaginal fungal load compared to the blank control group. This was accompanied by elevated levels of inflammatory factors (IL-1β, IL-6, and TNF-α) in serum and vaginal lavage fluid, increased phosphorylation of p65 and IκBα, and upregulation of p65 and IκBα mRNA expression in vaginal tissue. Treatment with the ASP and ITR combination significantly reduced vaginal fungal load, decreased levels of IL-1β, IL-6, and TNF-α, and suppressed the phosphorylation of p65 and IκBα in serum and vaginal lavage fluid. Additionally, the mRNA expression of p65 and IκBα in vaginal tissue was downregulated. These findings suggest that the combination of ASP and ITR is effective in treating VVC. The therapeutic effect may be attributed to the inhibition of IL-1β, IL-6, and TNF-α production by downregulating NF-κB signaling pathway proteins.

The role of the C15orf48 gene in lung cancer is not well understood. This study aimed to investigate the effect of C15orf48 in non-small cell lung cancer (NSCLC). Bioinformatics analyses were performed using Oncomine, The Cancer Genome Atlas (TCGA), Protein-Protein Interaction (PPI) networks, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). Immunohistochemical staining was used to detect C15orf48 expression in tissue microarrays. Cellular assays, including CCK8, colony formation, wound healing, transwell migration, flow cytometry, and cell adhesion, were conducted to assess cell viability, proliferation, invasion, and apoptosis. A xenograft tumor model was used to examine tumor growth, and Western blotting was used to detect protein expression. C15orf48 expression was significantly upregulated in tumor tissues compared to normal tissues and was associated with poor prognosis. Knockdown of C15orf48 in A549 and H1299 cells reduced proliferation, invasion, and adhesion while increasing apoptosis. C15orf48 knockdown also inhibited tumor growth in vivo and was associated with immune cell infiltration. Although C15orf48 expression correlated with the epithelial-mesenchymal transition (EMT) score, no significant differences were observed. GSEA identified the NF-κB signaling pathway as a key pathway involved. Proteins PLAUR, IKBα, IL-1RN, ICAM1, and TMPRSS4 showed decreased expression in the shC15orf48 group compared to the shCtrl group. We concluded that C15orf48 promotes NSCLC progression, potentially through immune cell infiltration and the NF-κB signaling pathway.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by the selective death of motor neurons in the spinal cord, brainstem, and motor cortex. This study investigates the effects of simvastatin on the G93A-copper/zinc superoxide dismutase (G93ASOD1) transgenic mouse model of ALS. The experiment included three groups: C57BL/6 wild-type (WT) mice, C57BL/6J SOD1G93A mice treated with PBS (SOD1G93A + PBS), and C57BL/6J SOD1G93A mice treated with simvastatin (SOD1G93A + simvastatin). The primary endpoints were survival rates, body weight changes, performance in pole climbing and suspension tests, and neurological deficit scores. Pathological changes were assessed using H&E staining, transmission electron microscopy, Nissl staining, and Masson staining. Proteomic and metabolomic analyses were performed to identify differentially expressed proteins (DEPs) and metabolites. Quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting were used to measure gene expression. Although there were no significant differences in survival rates, body weight, pole climbing, and suspension test performance, or neurological deficit scores between the SOD1G93A + simvastatin and SOD1G93A + PBS groups, simvastatin treatment improved axonal organization within the spinal cord, increased the number of neurons, and reduced cytoplasmic swelling and gastrocnemius fibrosis. A total of 47 DEPs and 13 differential metabolites were identified between the SOD1G93A + PBS and SOD1G93A + simvastatin groups. Notably, the expression levels of Apoa4 and Alb were elevated in the SOD1G93A + simvastatin group compared to the SOD1G93A + PBS group. Our results suggest that simvastatin may have potential therapeutic effects in ALS, likely involving the modulation of Apoa4 and Alb expression.

Cardiac arrest (CA) remains a critical global health issue with high rates of mortality and morbidity. Accurate prediction of neurological outcomes in post-CA patients is essential for optimizing management strategies. Optic nerve sheath diameter (ONSD) and near-infrared spectroscopy (NIRS) are emerging as promising tools for evaluating brain oxygenation and intracranial pressure. However, the potential benefits of combining these methods for improved prognostic accuracy have not been thoroughly explored. This study investigates whether the combined use of ultrasonographic ONSD and NIRS measurements enhances the prediction of neurological outcomes after CA. In this prospective study, ONSD measurements were obtained three times at 24-hour intervals, while regional hemoglobin oxygen saturation (rSO2) using NIRS was recorded twice. Neurological outcomes were assessed using the Full Outline of Unresponsiveness (FOUR) and Cerebral Performance Categories (CPC) scores for both early and late evaluations. Results indicated that 47.5% of patients had poor outcomes and 52.5% had good outcomes based on the FOUR score, while 65% had poor outcomes and 35% had good outcomes according to the CPC score. The combination of ONSD and NIRS measurements showed superior prognostic performance compared to either method alone. While standalone NIRS measurements taken after 24 hours exhibited limited predictive value, combining ONSD and NIRS provided a more reliable approach for neurological assessment in the short-term following CA. This integrated method may improve prognostic accuracy and support better clinical decision-making.