Objective: To characterize perioperative dynamic changes in immune-cell phenotypes and inflammatory cytokines in patients undergoing CPB (cardiopulmonary bypass) cardiac surgery, and to explore their associations with postoperative outcomes. Methods: In this prospective cohort study, 120 adult patients who underwent elective cardiac surgery under CPB at West China Hospital from May 2022 to March 2023 were enrolled. Perioperative immune-cell phenotypes and concentrations of 40 inflammation-related cytokines were measured. The primary outcomes were the sequential organ failure assessment (SOFA) score at 24 h after surgery and ΔSOFA (the peak SOFA score within 48 h after surgery minus the preoperative SOFA score). Secondary outcomes included major adverse cardiovascular events (MACE), acute kidney injury (AKI), respiratory failure, severe liver injury, and infection. Results: The mean age of enrolled patients was 57±10 years. Of these, 52% (62/120) were male and 90% (108/120) underwent valve surgery. During the rewarming to the end of CPB, neutrophil counts rapidly increased (7.39×10 /L vs preoperative 3.07×10 /L, P<0.001), with significant upregulation of CD11b (7.30×10 /L vs preoperative 3.05×10 /L, P<0.001) and CD54 (7.15×10 /L vs preoperative 2.99×10 /L, P<0.001). Lymphocyte counts increased at the end of CPB (1.75×10 /L vs preoperative 1.12×10 /L, P<0.001) but decreased significantly at 24 h after surgery (0.59×10 /L vs preoperative 1.12×10 /L, P<0.001). Plasma analysis showed that multiple pro-inflammatory cytokines increased during CPB and remained elevated up to 24 h after surgery; five chemokines and the anti-inflammatory cytokine IL-10 peaked at the end of CPB. The SOFA score increased from 1 (1, 2) preoperatively to 7 (5, 10) at 24 h after surgery, with a ΔSOFA of 6 (4, 8). Within 30 days after surgery, 48 patients (40.0%) developed AKI, 17 (14.2%) developed infection, 4 (3.3%) developed severe liver injury, 3 (2.5%) developed respiratory failure, and 3 (2.5%) experienced MACE. During the 2-year follow-up, 8 patients (6.7%) experienced MACE and 5 (4.2%) died. Conclusion: Multi-organ dysfunction is common after cardiac surgery under CPB (median ΔSOFA, 6), accompanied by perioperative activation of multiple immune-cell subsets and upregulation of pro-inflammatory, anti-inflammatory, and chemotactic mediators. This study provides data-driven evidence and research clues for further investigation of the associations between CPB-related immune perturbations and postoperative organ dysfunction and clinical outcomes.

Objective To investigate the impact of dietary protein intake on the prevalence of type 2 diabetes in adult residents, and to provide a reference for formulating diabetes prevention and control measures. Methods The research was based on cross-sectional survey data from the Nutrition and Health Follow-up Study of Chinese Residents in Chongqing (2021). Energy and nutrient intake was calculated in combination with the Chinese food composition table. Multivariate logistic regression was used to analyze the association between dietary protein and diabetes, and then restricted cubic spline regression (RCS) was used to analyze the dose-response relationship between dietary protein intake and the development of diabetes. Results Among the 1 415 adult residents, dietary intake of total protein, animal protein, and plant protein was 69.69g/d, 26.26g/d, and 43.43g/d, respectively. The ratio of protein to energy supply was 14.31%, and the prevalence of diabetes was 18.02%. Comparing with the residents in the first percentile of total dietary protein intake, the multivariable-adjusted odds ratios of those in the second and third percentile were 1.754 and 2.453 respectively. Comparing the residents in the third percentile with those in the first percentile, the multivariable-adjusted odds ratios of diabetes were 1.592 for protein energy supply ratio, and 1.558 for animal protein intake. Conclusion High protein intake, high protein energy supply ratio and high animal protein intake may increase the risk of diabetes, and different types of protein may have different effects on diabetes.

OBJECTIVE To explore the association between the use of oral progesterone drugs in early pregnancy and gestational diabetes mellitus （GDM）. METHODS Through real-world retrospective cohort research method， pregnant women who underwent the oral glucose tolerance test （OGTT） at the Affiliated Maternal and Child Health Hospital of Nantong University between January 2022 and January 2023 were enrolled. Based on whether oral progesterone drugs were used in early pregnancy， they were divided into treatment group and control group； propensity score matching （PSM） with a 1∶1 ratio was employed to control for confounding factors； Logistic regression and linear regression were employed to analyze the association between drug factors （whether use of oral progesterone drug， duration of medication， dosage， and drug type） and outcome indicators （occurrence of GDM， fasting blood glucose levels， and OGTT 1 and 2 h blood glucose levels in late pregnancy）. RESULTS A total of 709 pregnant women were enrolled in the two groups before PSM； after PSM， 256 cases were included in both the treatment group and the control group. The results of association analysis indicated that there was no significant association between the use of oral progesterone drugs and GDM （P＞0.05）； but a significant correlation was found with OGTT 1 h blood glucose levels [β＝0.965， 95%CI （0.007，1.922）， P＜0.05]， specifically with Dydrogesterone tablets [β＝0.977， 95%CI （0.009， 1.944）， P＜0.05] and Progesterone soft capsules [β ＝1.089， 95%CI （0.077， 2.102）， P＜0.05]. There was no significant correlation between other drug factors and outcome indicators （P＞0.05）. CONCLUSIONS The use of oral progestogen drugs in early pregnancy is not significantly associated with GDM. The blood glucose levels in late pregnancy， especially OGTT 1 h blood glucose levels， have a certain correlation with Progesterone soft capsules and Dydrogesterone tablets.

BackgroundDementia seriously affects the quality of life and lifespan of elderly people， with Alzheimer's disease （AD） being the most common type of dementia. Previous studies have suggested that gout may reduce the risk of developing AD， but the causal relationship between the two still requires further research. ObjectiveTo investigate the potential causal relationship between gout and AD through a two-sample Mendelian randomization （MR） analysis， so as to provide references for the prevention and treatment of AD. MethodsData from Genome-Wide Association Studies （GWAS） extracted in 2024 were analyzed， using pooled data on gout （6 810 cases in the case group and 477 788 cases in the control group） published by UK Biobank in 2021 as the exposure variable， and data on AD （3 899 cases in the case group and 214 893 cases in the control group） published by FinnGen in the same year as the outcome variable. The inverse-variance weighted， MR-Egger regression， weighted median estimation， simple model and weighted model were used to analyze the potential causal relationship between gout and AD. Pleiotropic effects were assessed using MR-Egger regression. Heterogeneity assessment was conducted using Cochran's Q test. The leave-one-out analysis was carried out for sensitivity analysis. And a funnel plot was drawn to detect potential publication bias. ResultsThe inverse-variance weighted analysis demonstrated a negative causal relationship between gout and AD （OR=0.004， 95% CI： 0~0.700， P<0.05）. The plot resembled a symmetrical inversed funnel， indicating the absence of publication bias. No heterogeneity was detected by Cochran's Q test. The MR-Egger regression indicated no significant horizontal pleiotropy. Concerning the reverse directions， no significant associations between AD and gout were noted. ConclusionThere is a negative causal relationship between gout and AD， with gout potentially reducing the risk of developing AD. ［Funded by The Third Batch of Social Welfare and Basic Research Projects （Medical and Health） of Zhongshan City in 2022 （number， 2022B3017）］

The use of wastewater analysis, or wastewater-based epidemiology, to assess and monitor the situation of drug abuse is now widely used at home and abroad. However, there is currently a lack of effective evaluation methods and effective ways of comparison, supervision and standardization, which is not conducive to the analysis and comparisons of data in different countries and regions. Quality control techniques can control the laboratory's analytical errors, safeguard the consistency and comparability of identification conclusions, and promote the further improvement of the level and capacity of urban drug governance, thus playing significant roles. This paper provides an overview of sample collection, sample preservation and transportation, laboratory analysis, back-calculation of drug use and external laboratory quality control in the process of wastewater analysis, with a view to exploring more comprehensive scientific and objective methods and approaches suitable for examining and evaluating qualitative and quantitative analysis of drugs in wastewater among laboratories.

Background Environmental metal exposure is closely associated with the onset and progression of mild cognitive impairment (MCI) in the elderly. Effectively identifying hazardous metal exposure and assessing their interaction effects have significant public health implications. Objective To explore the relationship between urinary single metal and metal mixture exposure and MCI in elderly compound residents. Methods This study included 391 elderly individuals aged 60 and above from residential compounds in Zhongshan City, Guangdong Province. Concentrations of iron (Fe), copper (Cu), selenium (Se), arsenic (As), cadmium (Cd), manganese (Mn), chromium (Cr), nickel (Ni), vanadium (V), cobalt (Co), antimony (Sb), thallium (Tl), zinc (Zn), calcium (Ca), and magnesium (Mg) in urine were measured using inductively coupled plasma mass spectrometry. Cognitive function in the elderly was assessed using the Chinese version of the Mini-Mental State Examination (MMSE). Logistic regression was used to explore the relationship between single metal exposure level and MCI. LASSO regression and multi-metal logistic regression models were used to identify key metal ions associated with MCI. Bayesian kernel machine regression (BKMR) was employed to analyze the relationship between key metal ion mixtures and MCI, as well as the interactions between metals. Age, gender, education level, occupation, and body mass index were adjusted as covariates. Results A total of 78 among the 391 elderly individuals surveyed (19.94%) were diagnosed with MCI (MCI group), and the other 313 individuals were controls. The levels of Se, Cd, Mn, and As in the urine of the MCI group were significantly higher than those in the control group (P < 0.05). In the single-metal model, after adjusting for covariates and using the first quartile (Q₁) of each metal concentration as the reference, the OR for MCI in the elderly in the Q₄ group of Se was 2.190 (95%CI: 1.017, 4.716); for Cd, the OR was 2.345 (95%CI: 1.041, 5.283) in the Q₃ group and 2.371 (95%CI: 1.043, 5.393) in the Q₄ group; for Mn, the OR was 2.355 (95%CI: 1.038, 5.344) in the Q₂ group; for As, the OR was 3.377 (95%CI: 1.442, 7.908) in the Q₃ group and 2.886 (95%CI: 1.227, 6.788) in the Q₄ group; for Sb, the OR was 2.779 (95%CI: 1.234, 6.257) in the Q₂ group. When urinary metal concentrations were ln-transformed and included as continuous variables in the single-metal model, Cd concentration was positively correlated with MCI (OR=1.377; 95%CI: 1.008, 1.882; P=0.044). Cd, Se, Mg, Ca, Mn, As, Cr, Co, Tl, and Sb were selected by the LASSO regression model and included in the multi-metal model. In the multi-metal model, compared with Q₁, the OR for MCI in the elderly was 0.395 (95%CI: 0.164, 0.953) in the Q₂ group of Co and 0.390(95%CI: 0.167，0.911) in the Q₃ group of Co; for Mn, the OR in the Q₂ group was 2.636 (95%CI: 1.053, 6.596); for Sb, the OR in the Q₂ group was 2.640 (95%CI: 1.047, 6.658). As continuous variables, Mg (OR=0.472; 95%CI: 0.248, 0.899; P=0.022) and Co (OR=0.857; 95%CI: 0.737, 0.996; P=0.044) concentrations were negatively correlated with MCI. The BKMR mixture analysis suggested that Mg and Co exhibited a synergistic negative correlation with MCI, while Mn and Sb exhibited a synergistic positive correlation with MCI. Mg and Co attenuated the positive correlation of Mn and Sb with MCI, whereas Mn weakened the protective effects of Mg and Co. Conclusion Elevated levels of Se, Cd, As, Mn, and Sb in urine may increase the risk of MCI in the elderly, while Mg and Co have protective effects. Potential synergistic or antagonistic interactions may be found among Mn, Sb, Mg, and Co, which should not be overlooked in terms of their impact on the cognitive function of the elderly.