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.

OBJECTIVE: The study aim was to investigate the effects of exposure to multiple environmental organic pollutants on cardiopulmonary health with a focus on the potential mediating role of oxidative stress. METHODS: A repeated-measures randomized crossover study involving healthy college students in Beijing was conducted. Biological samples, including morning urine and venous blood, were collected to measure concentrations of 29 typical organic pollutants, including hydroxy polycyclic aromatic hydrocarbons (OH-PAHs), bisphenol A and its substitutes, phthalates and their metabolites, parabens, and five biomarkers of oxidative stress. Health assessments included blood pressure measurements and lung function indicators. RESULTS: Urinary concentrations of 2-hydroxyphenanthrene (2-OH-PHE) ( β = 4.35% [95% confidence interval ( CI): 0.85%, 7.97%]), 3-hydroxyphenanthrene ( β = 3.44% [95% CI: 0.19%, 6.79%]), and 4-hydroxyphenanthrene (4-OH-PHE) ( β = 5.78% [95% CI: 1.27%, 10.5%]) were significantly and positively associated with systolic blood pressure. Exposures to 1-hydroxypyrene (1-OH-PYR) ( β = 3.05% [95% CI: -4.66%, -1.41%]), 2-OH-PHE ( β = 2.68% [95% CI: -4%, -1.34%]), and 4-OH-PHE ( β = 3% [95% CI: -4.68%, -1.29%]) were negatively associated with the ratio of forced expiratory volume in the first second to forced vital capacity. These findings highlight the adverse effects of exposure to multiple pollutants on cardiopulmonary health. Biomarkers of oxidative stress, including 8-hydroxy-2'-deoxyguanosine and extracellular superoxide dismutase, mediated the effects of multiple OH-PAHs on blood pressure and lung function. CONCLUSION Exposure to multiple organic pollutants can adversely affect cardiopulmonary health. Oxidative stress is a key mediator of the effects of OH-PAHs on blood pressure and lung function.
Humans ; Oxidative Stress/drug effects* ; Male ; Cross-Over Studies ; Female ; Young Adult ; Environmental Pollutants/toxicity* ; Environmental Exposure/adverse effects* ; Biomarkers/blood* ; Adult ; Blood Pressure/drug effects* ; Polycyclic Aromatic Hydrocarbons/urine* ; Beijing

Twelve pre-processing protocols for formalin-fixed paraffin-embedded(FFPE)tissue samples were developed by orthogonal experimental design,incorporating different dewaxing buffers(Triton X-100 and xylene),lysis buffers(TFE and RapiGest),and enzyme digestion methods(iST,SP3,and FASP)to explore the optimal experimental conditions.These protocols were assessed based on protein and peptide identification depth,identification stability,and quantitative levels of protein abundance.The results indicated that Triton X-100 and xylene minimally impacted proteomics identification,whereas the TFE lysis buffer and iST digestion method significantly enhanced the proteomics analysis of FFPE samples.Considering the potential toxicity of xylene,the TTI protocol based on Triton X-100,TFE,and iST was determined to be the optimal choice.This protocol exhibited the best repeatability and stability,and a higher number of proteins associated with significant biological functions were identified.In conclusion,the established TTI protocol offered an efficient and comprehensive approach for proteomic analysis of FFPE samples,significantly enhancing the repeatability and stability of protein identification.

With the continuous rise in the incidence of colorectal cancer and the trend towards younger patient population,the existing treatment options,while able to prolong survival,are difficult to avoid significant side effects.It is imperative to develop new treatment strategies.Luteolin(LUT),as a natural herbal active ingredient,has been proved to have broad-spectrum anti-tumor effects in studies of multiple cancer types.However,the mechanism of LUT action in colorectal cancer has not been systematically elucidated.In this study,for the first time,the molecular mechanism of LUT on colorectal cancer SW620 cells from the perspective of proteomics-glycoproteomics co-regulation was revealed.Proteomic analysis identified 472 differentially expressed proteins.Functional enrichment analysis showed that down-regulated proteins were mainly involved in oxidative stress response,mRNA processing,RNA splicing,and actin filament organization among key biological processes,involving oxidative phosphorylation and peroxisome pathways.Up-regulated proteins were mainly involved in DNA replication,protein folding,and rRNA metabolism,closely related to DNA replication and protein processing pathways in the endoplasmic reticulum.At the level of glycoproteomics,231 differentially expressed intact N-glycopeptides were identified.Functional enrichment analysis of corresponding glycoproteins indicateed that LUT might exert biological effects by regulating biological processes such as nuclear organization,nuclear membrane organization,and Fc receptor-mediated signaling pathways,as well as endoplasmic reticulum protein processing and N-glycan biosynthesis pathways.Analysis of key interaction networks revealed 5 core target proteins namely RPS15A,WDR43,FBL,UTP18,and UTP11.The loss of these proteins had been confirmed to inhibit the proliferation and migration of various tumor cells.Notably,altered glycosylation modifications of the lysosome-associated membrane proteins LAMP1 and LAMP2 suggested that LUT might affect tumor metastatic potential by regulating organelle dynamics.It was found that LUT could inhibit the malignant phenotype of colon cancer cells through a dual mechanism of specifically regulating protein expression networks and glycosylation modification patterns,providing new molecular targets and theoretical basis for precise treatment of colorectal cancer based on natural products.

Integrated metabolomic and lipidomic profiling,utilizing liquid chromatography coupled with high-resolution mass spectrometry(LC-HRMS),has emerged as a pivotal strategy for biomarker discovery.However,the inherent polarity disparity between metabolites and lipids complicates simultaneous analysis.To address this,a dual-stationary phase polarity-extended liquid chromatography(PELC)system was developed,which surpassed conventional one-dimensional LC(1D-LC)by enabling comprehensive coverage of both polar and non-polar compounds within a single injection.This system enhanced chromatographic resolution,peak capacity,and throughput while minimizing analytical variability.Extracellular vesicles(EVs),lipid bilayer-enclosed nanoparticles ubiquitously present in biofluids,had gained prominence as reservoirs of cancer biomarkers due to their cargo stability and pathophysiological relevance.Herein,the application of PELC-HRMS for concurrent metabolome-lipidome profiling in EVs was pioneered.A total of 193 metabolites were identified using this technique coupled with MS-DIAL software and Human Metabolome Database.Subsequently,this technique was employed to explore potential biomarkers for prostate cancer(PCa).Multivariate analysis identified 17 differentially abundant metabolites in PCa,implicating dysregulated pathways including purine metabolism,starch and sucrose metabolism,galactose metabolism,cysteine and methionine metabolism,and biosynthesis of unsaturated fatty acids.Notably,creatine(AUC=0.92)and DG 42:5(AUC=0.80)demonstrated robust diagnostic efficacy,attributable to their broad polarity ranges and EV-specific enrichment.This study established PELC as a high-fidelity platform for multi-omics integration in complex biospecimens,advancing mechanistic insights into metabolic rewiring and disease pathophysiology.

Objective:To explore the clinical characteristics and identification of the independent risk factors for disease progression in patients with anti-gp210 antibody-positive primary biliary cholangitis (PBC).Methods:A retrospective cohort study was performed. A total of 323 cases with PBC diagnosed in Tianjin Medical University General Hospital from January 2013 to June 2023 (125 patients with anti-gp210 antibody-positive and 198 patients with anti-gp210 antibody-negative) were included. Baseline and follow-up data were collected. The independent sample t-test and Mann-Whitney U rank sum test were used for comparison between groups of continuous data. The χ2 test was used to compare the data between groups for the count data. The Pearson test was used for correlation analysis between continuous variables. The Kaplan-Meier method was used to analyze the disease progression-free survival rate. The Cox regression model was used to analyze the risk factors for disease progression. Results:The male proportion (11.2% vs. 5.1%, P=0.040) and IgM level [3.29(1.88, 4.80) g/L vs. 2.56(1.44, 3.87) g/L, P=0.019] were significantly higher in patients with PBC with positive anti-gp210 antibodies than those of the negative group. Histopathological analysis showed that the Scheuer score [1(0,3) vs. 0(0,2)], bile duct inflammation [(2(1,3) vs. 1(1,2)] and bile duct reaction score [(2(1,3) vs. 1(1,2)] were higher in the positive group than those of the negative group ( P<0.05), and the maturity of the tertiary lymphoid structure was higher ( P=0.011). Kaplan-Meier analysis showed that the 5-year disease-free survival rate was significantly lower in patients with positive anti-gp210 antibodies than that of the negative group (55.8% vs. 79.7%, P=0.006) at a median follow-up of 3(2,6) years. Multivariate Cox regression analysis showed that γ-glutamyl transferase [ HR=1.002 (95% CI: 1.000～1.003)] and platelet count [ HR=0.993 (95% CI: 0.988～0.999)] were the independent influencing factors for disease progression in patients with anti-gp210 antibody-positive PBC ( P=0.002, 0.017). Conclusion:Patients with anti-gp210 antibody-positive PBC have more severe clinical pathological manifestations and a higher risk of disease progression. Higher levels of γ-glutamyl transferase and lower platelet counts during the first visit are independent risk factors for disease progression in patients with anti-gp210 antibody-positive PBC, which can be used as dynamic monitoring indicators for this population, suggesting the need for early intensive intervention.

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.

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 systematically evaluate studies validating the performance of the Global Leadership Initiative on Malnutrition (GLIM) in diagnosing malnutrition.Methods:Seven Chinese and English databases including Embase, Web of Science (WOS), PubMed, CINAHL, Cochrane Library, SinoMed, CNKI, Wanfang Data, and VIP Database were searched for articles on the validation of GLIM criteria published between September 2018 and September 2024. Two researchers independently performed literature screening and data extraction. The concurrent and predictive validity of the criteria was analyzed.Results:A total of 136 papers were included for analysis. The GLIM criteria for diagnosing malnutrition had a sensitivity of 77%, a specificity of 87%, and an area under the curve (AUC) of 0.90. Malnutrition diagnosed by the GLIM criteria predicted prolonged hospital and intensive care unit (ICU) stays, increased readmission and complication rates (both overall and infectious), reduced survivals (median, overall, and disease-free), and increased in-hospital and follow-up mortalities. Both moderate and severe malnutrition predicted decreased overall survival. However, only three studies analyzed the impact of nutritional therapy on the clinical outcomes of malnourished patients.Conclusions:The GLIM criteria accurately differentiate malnutrition and are a valid predictive tool of clinical outcomes. However, the validity criteria in these validation studies were questionable, along with high methodological heterogeneity. Furthermore, there is a lack of studies validating the role of nutritional therapy in improving the clinical outcomes of malnourished patients.