OBJECTIVE: To investigate the association between long-term glycemic control and cerebral infarction risk in patients with diabetes through a large-scale cohort study. METHODS: This prospective, community-based cohort study included 12,054 patients with diabetes. From 2006 to 2012, 38,272 fasting blood glucose (FBG) measurements were obtained from these participants. FBG trajectory patterns were generated using latent mixture modelling. Cox proportional hazards models were applied to assess the subsequent risk of cerebral infarction associated with different FBG trajectory patterns. RESULTS: At baseline, the mean age of the participants was 55.2 years. Four distinct FBG trajectories were identified based on FBG concentrations and their changes over the 6-year follow-up period. After a median follow-up of 6.9 years, 786 cerebral infarction events were recorded. Different trajectory patterns were associated with significantly varied outcome risks (Log-Rank P < 0.001). Compared with the low-stability group, Hazard Ratio ( HR) adjusted for potential confounders were 1.37 for the moderate-increasing group, 1.23 for the elevated-decreasing group, and 2.08 for the elevated-stable group. CONCLUSION Sustained high FBG levels were found to play a critical role in the development of ischemic stroke among patients with diabetes. Controlling FBG levels may reduce the risk of cerebral infarction.
Humans ; Cerebral Infarction/blood* ; Middle Aged ; Male ; Female ; Blood Glucose/analysis* ; Fasting/blood* ; Aged ; Prospective Studies ; Risk Factors ; Diabetes Mellitus/blood* ; Adult ; Proportional Hazards Models

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 To investigate the genetic differences among different populations based on 13 autosomal STR loci in CODIS core.Methods Data of 13 autosomal STR loci(CSF1PO,FGA,THO1,TPOX,vWA,D3S1358,D5S818,D7S820,D8S1179,D13S317,D16S539,D18S51,D21S11)were collected from 95 populations in scientific journals between 1999 and 2021,soursed from the PubMed database,which had been published.Allele frequencies of loci were sorted out and forensic genetic parameters including gene differentiation coefficient(Gst),total heterozygosity(Ht),subpopula-tion heterozygosity(Hs)values,and Nei's DA genetic distance were calculated.Principal component analysis,phylogenetic tree,and multidimensional scale analysis were conducted to assess population ge-netic structure.Results A total of 265 alleles were detected at the 13 STR loci in these 95 popula-tions.The mean values of Gst,Ht,and Hs were 0.023 247,0.797 915 and 0.779 365.Population genetic analyses reflected significant differences among populations from Asia,Africa and Europe.In Asian populations,there was a certain degree of distinction between mainland and island populations;the Han population showed a certain degree of distinction with surrounding populations in mainland;while within the Han population,there were two distinct clusters formed by the northern Han and the south-ern Han.Conclusion The 13 autosomal STR loci in CODIS core demonstrate potential value for popu-lation identification across different groups,and may be used for the differentiation of ethnic groups,among different continental populations.

Objective: The aging demographic landscape worldwide portends a heightened prevalence of neurodegenerative disorders. Foremost among these is Alzheimer’s disease (AD), the foremost cause of dementia in older adults. The shortage of efficacious therapies and early diagnostic indicators underscores the imperative to identify non-invasive biomarkers for early detection and disease monitoring. Recently, blood metabolites have emerged as promising candidates for AD biomarkers. Methods: Leveraging nuclear magnetic resonance (NMR) spectroscopy on plasma specimens, we conducted a cross-sectional study encompassing 35 AD patients and 35 age-matched healthy controls. Cognitive function was evaluated using the mini-mental state examination in all participants, followed by peripheral blood sample collection. We utilized univariate and multivariate analyses to perform targeted lipidomic profiling via NMR spectroscopy. Results: Our study revealed significant differences in the expression profiles of low-density lipoprotein-associated subfractions in females and high-density lipoprotein-associated subfractions in males between AD patients and healthy controls (all p<0.05). However, there was no significant metabolite overlap between males and females. Furthermore, receiver operating characteristic curve analysis demonstrated that the combination of lipid metabolites had good diagnostic values (all area under the curve>0.70; p<0.05). Conclusion Our findings suggest that the blood plasma samples using NMR hold promise in distinguishing between AD patients and healthy controls, with significant clinical implications for advancing AD diagnostic methodologies.

Objective:To explore Nursing Management course design and teaching management reform under the guidance of the concept of Plan-Do-Check-Act (PDCA).Methods:The PDCA cycle was implemented in four stages and eight steps throughout the course design and teaching management of Nursing Management. With each class as a small cycle and the whole course as a big cycle, the teaching objectives, teaching content, teaching methods, teaching implementation, classroom quality, and learning effects were dynamically controlled. The implementation effects were evaluated through assessments and feedbacks.Results:The qualitative analysis showed that the teaching design was reasonable, the teaching objectives were specific, and the teaching content was clear in hierarchy and appropriate in arrangement and organization; and peers and experts rated classroom performance excellent. The quantitative analysis showed that the students' process assessment score was (88.14±1.23), written test score was (80.21±6.25), and average overall score was (82.60±4.43), all with significant improvements in horizontal and vertical comparisons; and the students had improvements in management awareness, management ability, practical application ability, and self-confidence, with a high degree of satisfaction with the course.Conclusions:PDCA-guided whole-process management can optimize the course teaching design of Nursing Management, which is conducive to developing students' management practice abilities and improving teaching quality.

Objective: The aging demographic landscape worldwide portends a heightened prevalence of neurodegenerative disorders. Foremost among these is Alzheimer’s disease (AD), the foremost cause of dementia in older adults. The shortage of efficacious therapies and early diagnostic indicators underscores the imperative to identify non-invasive biomarkers for early detection and disease monitoring. Recently, blood metabolites have emerged as promising candidates for AD biomarkers. Methods: Leveraging nuclear magnetic resonance (NMR) spectroscopy on plasma specimens, we conducted a cross-sectional study encompassing 35 AD patients and 35 age-matched healthy controls. Cognitive function was evaluated using the mini-mental state examination in all participants, followed by peripheral blood sample collection. We utilized univariate and multivariate analyses to perform targeted lipidomic profiling via NMR spectroscopy. Results: Our study revealed significant differences in the expression profiles of low-density lipoprotein-associated subfractions in females and high-density lipoprotein-associated subfractions in males between AD patients and healthy controls (all p<0.05). However, there was no significant metabolite overlap between males and females. Furthermore, receiver operating characteristic curve analysis demonstrated that the combination of lipid metabolites had good diagnostic values (all area under the curve>0.70; p<0.05). Conclusion Our findings suggest that the blood plasma samples using NMR hold promise in distinguishing between AD patients and healthy controls, with significant clinical implications for advancing AD diagnostic methodologies.

Objective: The aging demographic landscape worldwide portends a heightened prevalence of neurodegenerative disorders. Foremost among these is Alzheimer’s disease (AD), the foremost cause of dementia in older adults. The shortage of efficacious therapies and early diagnostic indicators underscores the imperative to identify non-invasive biomarkers for early detection and disease monitoring. Recently, blood metabolites have emerged as promising candidates for AD biomarkers. Methods: Leveraging nuclear magnetic resonance (NMR) spectroscopy on plasma specimens, we conducted a cross-sectional study encompassing 35 AD patients and 35 age-matched healthy controls. Cognitive function was evaluated using the mini-mental state examination in all participants, followed by peripheral blood sample collection. We utilized univariate and multivariate analyses to perform targeted lipidomic profiling via NMR spectroscopy. Results: Our study revealed significant differences in the expression profiles of low-density lipoprotein-associated subfractions in females and high-density lipoprotein-associated subfractions in males between AD patients and healthy controls (all p<0.05). However, there was no significant metabolite overlap between males and females. Furthermore, receiver operating characteristic curve analysis demonstrated that the combination of lipid metabolites had good diagnostic values (all area under the curve>0.70; p<0.05). Conclusion Our findings suggest that the blood plasma samples using NMR hold promise in distinguishing between AD patients and healthy controls, with significant clinical implications for advancing AD diagnostic methodologies.

Objective: The aging demographic landscape worldwide portends a heightened prevalence of neurodegenerative disorders. Foremost among these is Alzheimer’s disease (AD), the foremost cause of dementia in older adults. The shortage of efficacious therapies and early diagnostic indicators underscores the imperative to identify non-invasive biomarkers for early detection and disease monitoring. Recently, blood metabolites have emerged as promising candidates for AD biomarkers. Methods: Leveraging nuclear magnetic resonance (NMR) spectroscopy on plasma specimens, we conducted a cross-sectional study encompassing 35 AD patients and 35 age-matched healthy controls. Cognitive function was evaluated using the mini-mental state examination in all participants, followed by peripheral blood sample collection. We utilized univariate and multivariate analyses to perform targeted lipidomic profiling via NMR spectroscopy. Results: Our study revealed significant differences in the expression profiles of low-density lipoprotein-associated subfractions in females and high-density lipoprotein-associated subfractions in males between AD patients and healthy controls (all p<0.05). However, there was no significant metabolite overlap between males and females. Furthermore, receiver operating characteristic curve analysis demonstrated that the combination of lipid metabolites had good diagnostic values (all area under the curve>0.70; p<0.05). Conclusion Our findings suggest that the blood plasma samples using NMR hold promise in distinguishing between AD patients and healthy controls, with significant clinical implications for advancing AD diagnostic methodologies.

Objective: The aging demographic landscape worldwide portends a heightened prevalence of neurodegenerative disorders. Foremost among these is Alzheimer’s disease (AD), the foremost cause of dementia in older adults. The shortage of efficacious therapies and early diagnostic indicators underscores the imperative to identify non-invasive biomarkers for early detection and disease monitoring. Recently, blood metabolites have emerged as promising candidates for AD biomarkers. Methods: Leveraging nuclear magnetic resonance (NMR) spectroscopy on plasma specimens, we conducted a cross-sectional study encompassing 35 AD patients and 35 age-matched healthy controls. Cognitive function was evaluated using the mini-mental state examination in all participants, followed by peripheral blood sample collection. We utilized univariate and multivariate analyses to perform targeted lipidomic profiling via NMR spectroscopy. Results: Our study revealed significant differences in the expression profiles of low-density lipoprotein-associated subfractions in females and high-density lipoprotein-associated subfractions in males between AD patients and healthy controls (all p<0.05). However, there was no significant metabolite overlap between males and females. Furthermore, receiver operating characteristic curve analysis demonstrated that the combination of lipid metabolites had good diagnostic values (all area under the curve>0.70; p<0.05). Conclusion Our findings suggest that the blood plasma samples using NMR hold promise in distinguishing between AD patients and healthy controls, with significant clinical implications for advancing AD diagnostic methodologies.

Objective:To explore the application effect of 6S and PDCA cycle lean management in nursing management of orthopaedic trauma surgery.Methods:A retrospective cohort study was conducted to analyze the clinical data of 80 patients with orthopedic trauma admitted to University-Town Hospital of Chongqing Medical University from January 2020 to November 2021, including 51 males and 29 females; aged 23-68 years [(44.5±9.2)years]. According to the order of operation date, 40 patients from January 2021 to November 2021 received routine management plus 6S and PDCA cycle lean management (lean management group), and 40 patients from January 2020 to December 2020 received routine surgical nursing management (routine management group). The nursing quality score in operating room (instrument and equipment management, surgical instrument preparation, surgical coordination, disinfection and isolation), qualified rate of infection monitoring in operating room (air in operating room, hand hygiene of medical staffs and sterile articles in operating room), surgeons′ satisfaction with operating nurses (circulating nurses and scrub nurses), self- rating anxiety scale (SAS) of patients before operation, incidence of complications at postoperative 12 days and patients′ satisfaction with nurses in operating room at postoperative 2-3 days.Results:The four dimensions of the nursing quality score in operating room in lean management group were (27.8±1.5)points, (18.1±1.1)points, (26.6±1.5)points and (18.1±0.8)points, significantly higher than (23.7±2.3)points, (14.6±1.1)points, (22.4±1.8)points and (13.7±1.1)points in routine management group (all P<0.01). The three dimensions of qualified rate of infection monitoring in operating room in lean management group were all 100%, showing no significant differences in routine management group (75%, 100%, 100%) (all P>0.05). Surgeons′ satisfaction with circulating nurses and scrub nurses in lean management group was 90% and 85%, higher than 73% and 65% in routine management group (all P<0.05). Preoperative SAS in lean management group was (32.5±8.2)points, significantly lower than (54.6±10.7)points in routine management group ( P<0.01). The incidence of postoperative complications in lean management group was 0, significantly lower than 15%(6/40) in routine management group ( P<0.05). Patients′ satisfaction with nurses in operating room in lean management group was 95% (38/40), significantly higher than 78%(31/40) in routine management group ( P<0.05). Conclusion:6S and PDCA cycle lean management can effectively improve the nursing quality of orthopedic trauma surgery, reduce patients′ anxiety and postoperative complications, and improve surgeons′ and patients′ satisfaction, which is worthy of further clinical application.