OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

OBJECTIVE: To investigate the predictive value of the prognostic nutritional index (PNI) and systemic inflammatory response index (SIRI) for short-term efficacy and prognosis in newly treated patients with peripheral T-cell lymphoma (PTCL). METHODS: The general data, laboratory indicators, disease stage and other clinical data of 91 newly treated PTCL patients admitted to the Affiliated Hospital of Xuzhou Medical University from January 2015 to December 2023 were retrospectively analyzed. The optimal cutoff values for PNI and SIRI were determined using receiver operating characteristic (ROC) curves, and the patients were stratified into groups based on these cutoffs to compare clinical features and short-term efficacy between the different groups. Kaplan-Meier method was used to plot survival curves, and univariate and multivariate analyses were performed to identify the factors affecting overall survival (OS). RESULTS: The optimal cutoff values for PNI and SIRI were 45.30 and 1.74×10⁹/L, respectively. Patients in different PNI groups showed statistically significant differences in age, Ann Arbor stage, lactate dehydrogenase (LDH) level, international prognostic index (IPI), prognostic index for PTCL-not otherwise specified (PIT), pathological subtypes, and complete response (CR) rate (P < 0.05). PTCL patients in different SIRI groups exhibited significant differences in Ann Arbor stage, LDH level, IPI score, PIT score, and CR rate (P < 0.05). Logistic regression analysis showed that age ≥60 years old (OR =2.750), Ann Arbor stage Ⅲ-Ⅳ (OR =5.200), IPI score ≥2 (OR =7.650), low PNI (OR =3.296), and high SIRI (OR =3.130) were independent risk factors affecting treatment efficacy in PTCL patients (P < 0.05). Cox proportional hazards regression model analysis showed that low PNI and elevated β₂-microglobulin (β₂-MG) levels were independent risk factors affecting OS (P < 0.05). CONCLUSION PNI and SIRI have certain application value in evaluating short-term efficacy and prognosis in patients with PTCL. Compared with SIRI, PNI demonstrates greater predictive value for patient prognosis.
Humans ; Prognosis ; Lymphoma, T-Cell, Peripheral/therapy* ; Retrospective Studies ; Nutrition Assessment ; Male ; Female ; Middle Aged ; ROC Curve ; Inflammation

Laccase is a type of polyphenol oxidase that can catalyze the oxidation of various substances,including phenols,aromatic amines,and catecholamines.It has been widely utilized in pollutant degradation and analytical applications.However,the high cost of preparation of natural laccase and its susceptibility to environmental factors,which can lead to denaturation and inactivation,limit its practical applications.Nanozymes,which are nanomaterials that exhibit enzyme-like properties,offer advantages such as easy preparation,adjustable activity,and exceptional stability.Currently,many types of nanozymes have been developed.Inspired by the coordination of Cu2+with amino acids in the active site of natural laccase,researchers have employed coordination synthetic strategies to prepare laccase-like nanozymes.The metal nodes in these laccase-like nanozymes include copper,manganese,and cerium,while the ligands involve a variety of chemicals like nucleotides,amino acids,polypeptides,and aromatic acids.By manipulating factors such as the metal-to-ligand ratio,reducing capacity of ligands,buffer solutions,chloride ions,bromine ions,the catalytic activity of laccase-like nanozymes can be finely tuned.In this paper,laccase-like nanozymes developed through coordination strategies were categorized and summarized,along with review of their analytical applications in detection of phenolic compounds,disease biomarkers,antibiotics,pesticides,sulfur-containing pollutants,and time-temperature indicators.Furthermore,the challenges currently faced in the research of laccase-like nanozymes and future research directions were discussed.

Objective: To determine the expression of melanoma-associated antigens D4(MAGED4) and SIRT7 in human glioma, and to analyze the potential effects of MAGED4 and SIRT7 on glioma cell proliferation. Methods: The MAGED4 and SIRT7 expression levels and their correlation were compared by the China glioma genome atlas(CGGA), human protein atlas(HPA), and UALCAN databases. Survival analysis, ROC curve analysis, and Cox regression analysis were used to predict the outcome of MAGED4 and SIRT 7 in glioma patients. Gene ontology(GO) and Kyoto encyclopedia of genes and genomes(KEGG) signaling pathway enrichment analysis were used to explore the biological functions of MAGED4 and SIRT7 in glioma. Western blot experiment was used to investigate whether MAGED4 protein exerted its regulatory effects on the activity of the PI3K/AKT signaling pathway via SIRT7. The effect of MAGED4 on cell proliferation in glioma through SIRT7 was explored by CCK-8. Results: The analysis results of CGGA, UALCAN, and HPA databases showed that the expression levels of MAGED4 and SIRT7 in glioma tissues were higher than those in normal brain tissue, and the expression were positively correlated. Results of survival, ROC, and Cox analysis showed that high expression of MAGED4 and SIRT7 mRNA were risk factors for poor prognosis in glioma. Results of KEGG enrichment analysis showed that MAGED4 and SIRT7 were associated with the PI3K/AKT signaling in glioma, and Western blot results showed that MAGED4 activated the PI3K/AKT signaling pathway by regulating SIRT7. The CCK-8 results showed that MAGED4 promotes the proliferation of glioma cells through SIRT7. Conclusion MAGED4 and SIRT7 are highly expressed in glioma and associated with poor prognosis, and MAGED4 promotes glioma cell proliferation through activation of the PI3K/AKT signaling pathway by SIRT7.

Gene editing technology has become an important tool for biomedical research because of its high efficiency and precision in target gene localization and cleavage.The technology not only facilitates basic research on gene function,but also provides new strategies for gene therapy of hereditary diseases and genetic improvement of crops.With the integration of artificial intelligence(AI)technology,espe-cially the application of machine learning algorithms,the design and execution of gene editing have be-come more intelligent.AI technology optimizes the design of sgRNAs through predictive analysis and pat-tern recognition,improving the specificity and efficiency of editing while reducing the risk of off-target effects.In addition,AI plays a key role in the parsing of large-scale genomic data,providing new per-spectives for understanding complex biological processes and disease mechanisms.This paper reviews the research progress of data-driven gene editing technology in target precision,safety enhancement and per-sonalized therapy,aiming to provide reference and inspiration for researchers in the field of gene editing technology and to promote the application and development of AI in gene editing technology.

Aim To explore the mechanism of ligustil-ide(LIG)improving demyelination by inhibiting in-flammatory response in mice with distal middle cerebral artery occlusion(dMCAO)through AIM2/caspase-1 signal pathway.Methods Thirty C57BL/6N male mice were randomly divided into three groups:sham operation group(Sham group,n=10),model group(dMCAO group,n=10)and treatment group(LIG group,n=10).The dMCAO mouse model was estab-lished by electrocoagulation in dMCAO group and LIG group.The mice were scored by Longa after waking up,and the changes of cerebral blood flow were moni-tored by laser speckle blood flow imaging system after dMCAO.One hour after modeling,LIG(30 mg·kg-1·d-1)was injected intraperitoneally in LIG group,and the same amount of normal saline was injected in sham group and dMCAO group for one week until the end of the experiment.The mice in each group were stained with TTC,and the brain injury was observed pathologically.Fatigue turning bar test and open field test were used to evaluate the motor function and anxie-ty degree of mice,and then the brain tissues of mice were taken for black gold staining to compare the chan-ges of myelin sheath in each group.Immunofluores-cence staining was used to detect the average fluores-cence intensity of MBP,IBA1 and GFAP in CC,CPU and CX regions of mouse brains.ELISAwas used to de-tect the contents of TNF-α,IL-6,IL-1 β,IL-17A and BDNF in brain tissue proteins of mice.Western blot-ting was used to detect the protein expressions of AIM2,caspase-1 and ASC-in each group.Results Compared with the dMCAO group,the infarct area was reduced,the behavior was significantly improved and the demyelination was reduced in the LIG group.The expression of MBP protein in CC,CPU and CX regions increased(P＜0.05),the expression of IBA1 in CX decreased(P＜0.01),and the expression of GFAP in-creased in CC,CPU and CX regions(P＜0.01).The results of ELISA showed that the levels ofTNF-α(P＜0.01),IL-6(P＜0.01),IL-1β(P＜0.05)and IL-17A(P＜0.01)significantly decreased,while the ex-pression of BDNF increased(P＜0.05).The protein expression levels of AIM2,caspase-1 and ASC in mouse brain decreased after treatment(P＜0.01).Conclusion LIG has a protective effect on demyelina-tion in dMCAO mice,which may be related to the inhi-bition of AIM2/caspase-1 signaling pathway and in-flammation and to the promotion of BDNF secretion.

Aim To explore the mechanism of ligustil-ide(LIG)improving demyelination by inhibiting in-flammatory response in mice with distal middle cerebral artery occlusion(dMCAO)through AIM2/caspase-1 signal pathway.Methods Thirty C57BL/6N male mice were randomly divided into three groups:sham operation group(Sham group,n=10),model group(dMCAO group,n=10)and treatment group(LIG group,n=10).The dMCAO mouse model was estab-lished by electrocoagulation in dMCAO group and LIG group.The mice were scored by Longa after waking up,and the changes of cerebral blood flow were moni-tored by laser speckle blood flow imaging system after dMCAO.One hour after modeling,LIG(30 mg·kg-1·d-1)was injected intraperitoneally in LIG group,and the same amount of normal saline was injected in sham group and dMCAO group for one week until the end of the experiment.The mice in each group were stained with TTC,and the brain injury was observed pathologically.Fatigue turning bar test and open field test were used to evaluate the motor function and anxie-ty degree of mice,and then the brain tissues of mice were taken for black gold staining to compare the chan-ges of myelin sheath in each group.Immunofluores-cence staining was used to detect the average fluores-cence intensity of MBP,IBA1 and GFAP in CC,CPU and CX regions of mouse brains.ELISAwas used to de-tect the contents of TNF-α,IL-6,IL-1 β,IL-17A and BDNF in brain tissue proteins of mice.Western blot-ting was used to detect the protein expressions of AIM2,caspase-1 and ASC-in each group.Results Compared with the dMCAO group,the infarct area was reduced,the behavior was significantly improved and the demyelination was reduced in the LIG group.The expression of MBP protein in CC,CPU and CX regions increased(P＜0.05),the expression of IBA1 in CX decreased(P＜0.01),and the expression of GFAP in-creased in CC,CPU and CX regions(P＜0.01).The results of ELISA showed that the levels ofTNF-α(P＜0.01),IL-6(P＜0.01),IL-1β(P＜0.05)and IL-17A(P＜0.01)significantly decreased,while the ex-pression of BDNF increased(P＜0.05).The protein expression levels of AIM2,caspase-1 and ASC in mouse brain decreased after treatment(P＜0.01).Conclusion LIG has a protective effect on demyelina-tion in dMCAO mice,which may be related to the inhi-bition of AIM2/caspase-1 signaling pathway and in-flammation and to the promotion of BDNF secretion.

Objective To investigate the perioperative management of antithrombotic drugs in patients undergoing non-cardiac surgery.Methods Patients on long-term antithrombotic drugs who underwent non-cardiac surgery in our hospital were included.Through interviews with patients and physicians,perioperative antithrombotic medication regimens were reviewed and compared with the"Multidisciplinary Expert Consensus on Perioperative Management of Antithrombotic Therapy"to evaluate compliance with consensus and analyze influencing factors.Results A total of 372 patients were included in the analysis.Among them,355 patients were on long-term antiplatelet therapy alone,and 17 were on long-term oral anticoagulantion.364(97.8％)discontinued antithrombotic medications prior to surgery.109 patients(29.3％)received low molecular weight heparin(LMWH)bridging therapy.Among the 355 patients on antiplatelet therapy,108(30.4％)had discontinuation durations consistent with the consensus recommendations,while 186(52.4％)discontinued medications for longer periods.Postoperatively,the average hospital stay for antiplatelet therapy patients was 6.64 days,with only 37(10.4％)resuming therapy during hospitalization.The average hospital stay for patients on anticoagulants was 9.94 days,with only 2(11.8％)resuming therapy during hospitalization.Regarding perioperative risk assessment,only 40(10.8％)of patients underwent additional internal medical evaluation for thromboembolic risk after medication discontinuation,with the remainder assessed soly by surgeons.Coronary heart disease was an independent risk factor associated with internal medical evaluation(OR 2.851,95％CI 1.160-7.011,P=0.022).For bleeding risk assessment,surgeons evaluations aligned with the consensus in 68.0％of cases,but surgeons tended to underestimate risk compared to the consensus.Conclusions In this single-center study,perioperative antithrombotic management showed low compliance with expert consensus,characterized by prolonged preoperative medication discontinuation,high rates of LMWH bridging,and low postoperative in-hospital resumption of therapy.A robust multidisciplinary collaboration system should be established to enhance comprehensive patient assessment.