Metabolic associated fatty liver disease (MAFLD) is fundamentally driven by an imbalance in hepatic fatty-acid flux: the influx of fatty acids exceeds the liver’s capacity for disposal, resulting in excessive hepatic lipid accumulation, predominantly in the form of triglycerides (TGs). The occurrence and progression of MAFLD depend on disordered regulation across multiple metabolic steps, including fatty-acid uptake, de novo lipogenesis (DNL), fatty-acid oxidation (FAO), and very low-density lipoprotein (VLDL) export. Forkhead box protein O1 (FOXO1) is a key transcriptional regulator within the hepatic network coordinating glucose and lipid metabolism. Under metabolic stress and insulin resistance (IR), FOXO1 expression is frequently increased, whereas its inhibitory phosphorylation is reduced. These changes enhance FOXO1 nuclear localization and transcriptional activity, thereby reprogramming the expression of genes related to metabolism in the liver. Because hepatic lipid deposition is the central pathological feature of MAFLD, the functional status of FOXO1 directly influences hepatic lipid homeostasis. Growing evidence suggests that FOXO1 can exert bidirectional, environment-dependent effects on hepatic lipid accumulation; however, the molecular basis for this functional switch remains incompletely understood. This review systematically summarizes the biological functions and regulatory mechanisms of FOXO1 and its roles in hepatic lipid metabolism, with a particular focus on its crosstalk with insulin signaling. FOXO1 expression is shaped by RNA modifications and epigenetic regulation mediated by non-coding RNAs. Its transcriptional output is precisely governed by post-translational modifications—such as phosphorylation and acetylation—as well as by coordinated nucleocytoplasmic shuttling. Notably, these regulatory patterns vary markedly across nutritional states, degrees of insulin resistance, and stages of disease. In the fed state, insulin/IGF-1 signaling activates the PI3K-AKT pathway, promoting the inhibitory phosphorylation of FOXO1 and facilitating additional modifications, including acetylation, methylation, and ubiquitination. Together, these events drive FOXO1 export from the nucleus and dampen its transcriptional activity, suppressing gluconeogenesis and constraining lipogenic programs. Conversely, during fasting or when insulin signaling is weakened, FOXO1 inhibition is relieved. FOXO1 accumulates in the nucleus, binds to DNA, and regulates the transcription of downstream target genes. Mechanistically, FOXO1 can aggravate hepatic lipid accumulation by activating genes involved in TG synthesis while repressing FAO-related pathways, thereby favoring storage over oxidation. However, under specific conditions, FOXO1 may also alleviate the hepatic lipid burden by promoting TG hydrolysis and enhancing VLDL secretion, thereby reducing the net hepatic lipid load. In addition, lipotoxic signals mediated by ceramides and diacylglycerols (Cer/DAG) activate atypical protein kinase C (aPKC), further exacerbating the disruption of the AKT-FOXO1 axis. This vicious cycle ultimately produces a metabolic paradox in which increased hepatic glucose output coexists with persistent, insulin-independent lipogenesis, accelerating MAFLD progression. Importantly, FOXO1 regulation is not uniform: during early metabolic overload, insulin-mediated suppression may remain effective, whereas in advanced insulin resistance, the loss of AKT control permits sustained FOXO1 activity. Such stage-dependent dynamics may help explain why FOXO1 can either promote steatosis or, in certain contexts, support programs that facilitate lipid turnover. Accordingly, interventions should be liver-specific and tuned to the disease stage, aiming to curb maladaptive FOXO1 signaling while preserving its capacity to promote triglyceride hydrolysis and VLDL secretion when advantageous. Overall, this review offers an important perspective on MAFLD pathogenesis, emphasizing FOXO1 as a potential therapeutic target and providing a theoretical basis for developing liver-specific, disease-course-dependent precision interventions.

BACKGROUND:Osteosarcoma has a complex pathogenesis and a poor prognosis.While advancements in medical technology have led to some improvements in the 5-year survival rate,substantial progress in its treatment has not yet been achieved. OBJECTIVE:To screen key molecular markers in osteosarcoma,analyze their relationship with osteosarcoma treatment drugs,and explore the potential disease mechanisms of osteosarcoma at the molecular level. METHODS:GSE99671 and GSE284259(miRNA)datasets were obtained from the Gene Expression Omnibus database.Differential gene expression analysis and Weighted Gene Co-expression Network Analysis(WGCNA)on GSE99671 were performed.Functional enrichment analysis was conducted using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes separately for the differentially expressed genes and the module genes with the highest positive correlation to the disease.The intersection of these module genes and differentially expressed genes was taken as key genes.A Protein-Protein Interaction network was constructed,and correlation analysis on the key genes was performed using CytoScape software,and hub genes were identified.Hub genes were externally validated using the GSE28425 dataset and text validation was conducted.The drug sensitivity of hub genes was analyzed using the CellMiner database,with a threshold of absolute value of correlation coefficient|R|>0.3 and P<0.05. RESULTS AND CONCLUSION:(1)Differential gene expression analysis identified 529 differentially expressed genes,comprising 177 upregulated and 352 downregulated genes.WGCNA analysis yielded a total of 592 genes with the highest correlation to osteosarcoma.(2)Gene Ontology enrichment results indicated that the development of osteosarcoma may be associated with extracellular matrix,bone cell differentiation and development,human immune regulation,and collagen synthesis and degradation.Kyoto Encyclopedia of Genes and Genomes enrichment results showed the involvement of pathways such as PI3K-Akt signaling pathway,focal adhesion signaling pathway,and immune response in the onset of osteosarcoma.(3)The intersection analysis revealed a total of 59 key genes.Through Protein-Protein Interaction network analysis,8 hub genes were selected,which were LUM,PLOD1,PLOD2,MMP14,COL11A1,THBS2,LEPRE1,and TGFB1,all of which were upregulated.(4)External validation revealed significantly downregulated miRNAs that regulate the hub genes,with hsa-miR-144-3p and hsa-miR-150-5p showing the most significant downregulation.Text validation results demonstrated that the expression of hub genes was consistent with previous research.(5)Drug sensitivity analysis indicated a negative correlation between the activity of methotrexate,6-mercaptopurine,and pazopanib with the mRNA expression of PLOD1,PLOD2,and MMP14.Moreover,zoledronic acid and lapatinib showed a positive correlation with the mRNA expression of PLOD1,LUM,MMP14,PLOD2,and TGFB1.This suggests that zoledronic acid and lapatinib may be potential therapeutic drugs for osteosarcoma,but further validation is required through additional basic experiments and clinical studies.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Objective:To explore the trend of influenza positive rate in Beijing by using classic autoregressive integrated moving average (ARIMA) model, autoregressive integrated moving average model with exogenous variables (ARIMAX) and vector autoregression model (VAR) to compare the performance of three models in influenza prediction and select the most suitable one for Beijing.Methods:The weekly positive rate of influenza virus nucleic acid test and meteorological data in Beijing from week 1 of 2013 to week 40 of 2024 were collected. The data were divided into four groups with expanding training sets and corresponding testing sets. The training set of the first group was from week 1 of 2013 to week 40 of 2016, and the testing set was from week 41 of 2016 to week 40 of 2017. Subsequent groups extended the training set by one year each time. Data from 2020 to 2023 were excluded due to COVID-19 pandemic. The fourth group used data from the week 1 of 2013 to week 40 of 2023 for training and from the week 41 of 2023 to week 40 of 2024 for testing.Results:The incidence of influenza had seasonality in Beijing with higher incidence in winter and spring. The positive rate of influenza virus was positively correlated with the weekly average atmospheric pressure ( r=0.482, P<0.001) and weekly average wind speed ( r=0.003, P=0.034), and negatively correlated with the weekly average temperature ( r=-0.541, P<0.001). The ARIMAX model incorporating meteorological factors had the best prediction performance, with test set's root mean square error ( RMSE) of 0.115 3 and mean absolute error ( MAE) of 0.076 7 (the RMSE and MAE values for ARIMA and VAR models were 0.117 1 and 0.163 8, and 0.078 6 and 0.122 3, respectively). The prediction results of the optimal model showed that the positive rate of influenza virus would continue to rise in Beijing after October 2024 and reach peak in the second week of 2025, but the peak positive rate would be lower than that of previous influenza season. Conclusions:Compared with the ARIMA model and the VAR model,the ARIMAX model which used meteorological parameters is more suitable for prediction of long-term influenza trend in Beijing. The influenza trend peak was predicted to occur in the second week of 2025, but lower than that in previous influenza season.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

OBJECTIVE: Peritoneal fibrosis (PF) is an adverse event that occurs during long-term peritoneal dialysis, significantly impairing treatment efficiency and adversely affecting patient outcomes. Astragaloside IV (AS-IV), a principal active component derived from Astragalus membranaceus (Fisch.) Bunge, has exhibited anti-inflammatory and antifibrotic effects in various settings. This study aims to investigate the potential therapeutic efficacy and mechanism of AS-IV in the treatment of PF. METHODS: The PF mouse model was established by intraperitoneal injection of 4.25% peritoneal dialysis fluid (100 mL/kg). The epithelial-mesenchymal transition (EMT) of HMrSV5 cells was induced by the addition of 10 ng/mL transforming growth factor β (TGF-β). The differentially expressed genes in HMrSV5 cells treated with AS-IV were screened using transcriptome sequencing analysis. The potential targets of AS-IV were screened using network pharmacology and analyzed using molecular docking and molecular dynamics simulations. RESULTS: Administration of AS-IV at doses of 20, 40, or 80 mg/kg effectively mitigated the increase in peritoneal thickness and the development of fibrosis in mice with PF. The expression of the fibrosis marker α-smooth muscle actin in the peritoneum was significantly decreased in AS-IV-treated mice. The treatment of AS-IV (10, 20, and 40 μmol/L) significantly delayed the EMT of HMrSV5 cells induced by TGF-β, as demonstrated by the decreased number of 5-ethynyl-2'-deoxyuridine-positive cells, reduced migrated area, and decreased expression of fibrosis markers. A total of 460 differentially expressed genes were detected in AS-IV-treated HMrSV5 cells through transcriptome sequencing, with notable enrichment in the phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)-AKT serine/threonine kinase 1 (AKT) signaling pathway. The reduced levels of phosphorylated PI3K (p-PI3K) and p-AKT were detected in HMrSV5 cells with AS-IV treatment. Epidermal growth factor receptor (EGFR) was predicted as a direct target of AS-IV, exhibiting strong hydrogen bond interactions. The activation of the PI3K-AKT pathway by the compound 740Y-P, and the activation of the EGFR pathway by NSC 228155 each partially counteracted the inhibitory effect of AS-IV on the EMT of HMrSV5 cells. CONCLUSION AS-IV delayed the EMT process in peritoneal mesothelial cells and slowed the progression of PF, potentially serving as a therapeutic agent for the early prevention and treatment of PF. Please cite this article as: Huang Y, Chu CL, Qiu WH, Chen JY, Cao LX, Ji SY, Zhu B, Wang GK, Shen QQ. Astragaloside IV delayed the epithelial-mesenchymal transition in peritoneal fibrosis by inhibiting the activation of EGFR and PI3K-AKT pathways. J Integr Med. 2025; 23(6):694-705.
Epithelial-Mesenchymal Transition/drug effects* ; Animals ; Saponins/pharmacology* ; Triterpenes/pharmacology* ; Mice ; Peritoneal Fibrosis/pathology* ; Proto-Oncogene Proteins c-akt/metabolism* ; ErbB Receptors/metabolism* ; Phosphatidylinositol 3-Kinases/metabolism* ; Signal Transduction/drug effects* ; Male ; Humans ; Molecular Docking Simulation ; Cell Line ; Mice, Inbred C57BL

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

This article summarized the current status and challenges of manipulation therapy for musculoskeletal pain and its placebo effect in clinical trials, analyzing the impact of the placebo effect on the evaluation of therapeutic efficacy. The efficacy of different manual manipulation techniques remains uncertain, and the degree of blinding and patient expectations play a crucial role in efficacy assessment. The article suggested improving trial design through standardized placebo intervention design, comprehensive investigation of patient expectations and psychological states, rigorous training of practitioners, and optimized diagnostic and treatment scenarios and doctor-patient relationship, to ensure consistency between intervention and placebo groups. Specific measures include the application of the DITTO (Deconstruct, Identify, Take out, Think, Optimize) framework, the use of standardized questionnaire tools, and multi-center, large-sample randomized controlled trials to enhance the external validity and statistical power of research results, thereby providing more scientifically reliable evidence for clinical practice.