Background Platelet parameters are important indicators of cardiovascular risk, and environmental pollutants such as polychlorinated biphenyls (PCBs) may impair platelet function through oxidative stress. Objective To investigate the differential effects of single and mixed exposure to PCBs on platelet parameters among individuals with normal glucose tolerance (NGT), impaired fasting glucose (IFG), and type 2 diabetes mellitus (T2DM), and to evaluate the potential modifying role of a healthy lifestyle. Methods This study included 2249 participants (including 707 with NGT, 759 with IFG, and 783 with T2DM). Plasma PCB concentrations were measured using triple quadrupole gaschromatography-tandem mass spectrometry. Generalized linear regression was used to assess the associations between individual PCB congeners and platelet parameters. Quantile g-computation (QGC) and Bayesian kernel machine regression (BKMR) models were used to evaluate the overall effects of PCBs mixture exposure on platelet parameters across different glycemic states, as well as its interaction with healthy lifestyle score (HLS). Results Generalized linear regression analyses showed significant differences in the effects of PCBs on platelet parameters across different glycemic states (P<0.05). After adjusting for confounders, PCBs mixture exposure was significantly associated with lower platelet counts (PLT) in individuals with NGT (b=−10.60, 95%CI: −16.48, −4.71) and IFG (b=−12.91, 95%CI: −18.90, −6.92), whereas no significant association was observed in individuals with T2DM (P=0.051). Mean platelet volume (MPV) and platelet-large cell ratio (P-LCR) increased significantly with higher PCBs exposure levels across all three groups (P<0.05). BKMR analysis showed a positive association between PCBs mixture exposure and P-LCR, with the strongest association observed in the NGT group. Furthermore, a significant interaction was observed between HLS and PCBs mixture exposure, and a higher HLS attenuated the effects of PCBs on P-LCR. Conclusion Glycemic glycemic states may modify the effects of PCBs on platelets. Individuals with NGT appear more sensitive to PCBs exposure, whereas the T2DM state may attenuate this effect. Moreover, healthy lifestyles, including not smoking, moderate alcohol consumption, maintaining moderate-to-high physical activity, a healthy diet, and an appropriate body mass index (BMI), may mitigate the adverse effects of most PCBs on platelet parameters.

Background Platelet parameters are important indicators of cardiovascular risk, and environmental pollutants such as polychlorinated biphenyls (PCBs) may impair platelet function through oxidative stress. Objective To investigate the differential effects of single and mixed exposure to PCBs on platelet parameters among individuals with normal glucose tolerance (NGT), impaired fasting glucose (IFG), and type 2 diabetes mellitus (T2DM), and to evaluate the potential modifying role of a healthy lifestyle. Methods This study included 2249 participants (including 707 with NGT, 759 with IFG, and 783 with T2DM). Plasma PCB concentrations were measured using triple quadrupole gaschromatography-tandem mass spectrometry. Generalized linear regression was used to assess the associations between individual PCB congeners and platelet parameters. Quantile g-computation (QGC) and Bayesian kernel machine regression (BKMR) models were used to evaluate the overall effects of PCBs mixture exposure on platelet parameters across different glycemic states, as well as its interaction with healthy lifestyle score (HLS). Results Generalized linear regression analyses showed significant differences in the effects of PCBs on platelet parameters across different glycemic states (P<0.05). After adjusting for confounders, PCBs mixture exposure was significantly associated with lower platelet counts (PLT) in individuals with NGT (b=−10.60, 95%CI: −16.48, −4.71) and IFG (b=−12.91, 95%CI: −18.90, −6.92), whereas no significant association was observed in individuals with T2DM (P=0.051). Mean platelet volume (MPV) and platelet-large cell ratio (P-LCR) increased significantly with higher PCBs exposure levels across all three groups (P<0.05). BKMR analysis showed a positive association between PCBs mixture exposure and P-LCR, with the strongest association observed in the NGT group. Furthermore, a significant interaction was observed between HLS and PCBs mixture exposure, and a higher HLS attenuated the effects of PCBs on P-LCR. Conclusion Glycemic glycemic states may modify the effects of PCBs on platelets. Individuals with NGT appear more sensitive to PCBs exposure, whereas the T2DM state may attenuate this effect. Moreover, healthy lifestyles, including not smoking, moderate alcohol consumption, maintaining moderate-to-high physical activity, a healthy diet, and an appropriate body mass index (BMI), may mitigate the adverse effects of most PCBs on platelet parameters.

Cognitive decline is one of the most common adverse symptoms following acute high-altitude exposure(AHAE).MRI can reveal the structural and functional changes in brain caused by AHAE,thereby deeply understanding the specific mechanism of its cognitive decline,which is of great significance for early prevention and intervention.Research progresses on MRI assessment of cognitive function after AHAE and related intervention methods were reviewed in this article.

Special environments have significant impacts on the structure and function of multiple organs in human body,thereby causing a series of physiological or pathological adaptive changes.Imaging represents a pivotal technological approach for visualizing the structural damage and functional changes in organs.The research progresses of multi-organ imaging in special environments were reviewed in this article.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Background: and Purpose This study aimed to investigate the association between residual inflammatory risk (RIR) and vulnerable plaques using high-resolution magnetic resonance imaging (HRMRI) in symptomatic intracranial atherosclerotic stenosis (ICAS). Methods: This retrospective study included 70%–99% symptomatic ICAS patients hospitalized from January 2016 to December 2022. Patients were classified into four groups based on high-sensitivity C-reactive protein (hs-CRP) and low-density lipoprotein cholesterol (LDL-C): residual cholesterol inflammatory risk (RCIR, hs-CRP ≥3 mg/L and LDL-C ≥2.6 mmol/L), RIR (hs-CRP ≥3 mg/L and LDL-C <2.6 mmol/L), residual cholesterol risk (RCR, hs-CRP <3 mg/L and LDL-C ≥2.6 mmol/L), and no residual risk (NRR, hs-CRP <3 mg/L and LDL-C <2.6 mmol/L). Vulnerable plaque features on HRMRI included positive remodeling, diffuse distribution, intraplaque hemorrhage, and strong enhancement. Results: Among 336 included patients, 21, 60, 58, and 197 were assigned to the RCIR, RIR, RCR, and NRR groups, respectively. Patients with RCIR (adjusted odds ratio [aOR], 3.606; 95% confidence interval [CI], 1.346–9.662; P=0.011) and RIR (aOR, 3.361; 95% CI, 1.774–6.368, P<0.001) had higher risks of strong enhancement than those with NRR. Additionally, patients with RCIR (aOR, 2.965; 95% CI, 1.060–8.297; P=0.038) were more likely to have intraplaque hemorrhage compared with those with NRR. In the sensitivity analysis, RCR (aOR, 2.595; 95% CI, 1.201–5.608; P=0.015) exhibited an additional correlation with an increased risk of intraplaque hemorrhage. Conclusion In patients with symptomatic ICAS, RIR is associated with a higher risk of intraplaque hemorrhage and strong enhancement, indicating an increased vulnerability to atherosclerotic plaques.

Cerebral small vessel disease represents a group of common vascular disorders involving pathological changes in arterioles,capillaries and venules,with microvascular investigation remaining a key challenge in stroke.With high signal-to-noise ratio and high contrast enabled by enhanced field strength,7T MRI can surpass the resolution limits of 3T MRI,revealing structural and functional abnormalities in cerebral small vessels below 400 μm,as well as detecting subtle lesions in brain tissue.This paper reviews the research progress of multimodal high-resolution imaging techniques based on 7T MRI,such as time-of-flight angiography,phase contrast imaging and susceptibility imaging,in the study of cerebral small vessel disease.Utilizing these technologies,7T MRI can clearly display the structure of cerebral small vessels,such as the lenticulostriate arteries and deep medullary veins,and measure functional parameters like flow velocity and susceptibility.Additionally,it can sensitively detect cerebral microbleeds and cortical cerebral microinfarct.These imaging data provide valuable information for detecting early features of cerebral small vessel disease and assessing its progression,offering new insights into its pathogenesis.Combined with artificial intelligence-based image analysis methods,7T MRI holds great promise for early diagnosis and progression evaluation in cerebral small vessel disease.

As a pivotal advancement in ultra-high field MRI,7T MRI has transitioned from research-oriented applications to clinical implementation.Leveraging its ultra-high spatial resolution and superior signal-to-noise ratio,this technology enables a revolutionary shift in multi-dimensional imaging spanning macro-anatomical visualization to molecular metabolic characterization.Particularly in neurodegenerative disorders,cerebrovascular diseases,brain tumors and osteoarticular diseases,7T MRI emerges as an indispensable tool for precise diagnosis and ultrastructural imaging investigations.It presents a new perspective in early diagnosis of disease,monitoring of curative effect,evaluation of prognosis and even exploration of pathogenesis.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Investigated the mechanisms by which baicalein regulates nuclear factor E2-related factor 2(Nrf2)/heme oxygenase-1(HO-1)to ameliorate lipopolysaccharide(LPS)-induced sepsis-asso-ciated acute kidney injury(AKI)in mice.Sixty male C57BL/6 mice were randomly divided into six groups:control,model,low-dose baicalein(50 mg/kg),medium-dose baicalein(100 mg/kg),high-dose baicalein(200 mg/kg),and high-dose baicalein+brusatol(4 mg/kg).Baicalein was adminis-tered orally for 7 days as a preventative measure.Sepsis was induced via intraperitoneal injection of LPS.Murine sepsis score(MSS)was assessed within 12 hours post-induction.Serum creatinine(Scr),blood urea nitrogen(BUN),tumor necrosis factor-α(TNF-α),interleukin-1β(IL-1β),and interleukin-6(IL-6)were measured using an automatic biochemical analyzer and enzyme-linked immunosorbent assays(ELISA),respectively.Histopathological changes in kidney tissues were ob-served via hematoxylin-eosin(HE)staining.Western blot analysis was employed to determine the protein expression levels of Nrf2,HO-1,caspase-8,TNF-α,IL-1β,and IL-6 in kidney tissues.Additionally,total superoxide dismutase(SOD)activity in kidney tissues was assessed using com-mercially available kits.Compared to the model group,baicalein treatment significantly improved renal histopathological changes,alleviated cellular damage,and reduced the levels of inflammatory cytokines(TNF-α,IL-1βand IL-6)(P＜0.01)and kidney injury markers(Scr and BUN)(P＜0.01).Moreover,baicalein treatment significantly increased the protein expression levels of Nrf2 and HO-1(P＜0.01)and enhanced antioxidant enzyme activity.In conclusion,baicalein may pro-tect against LPS-induced sepsis-associated AK1 in mice by modulating the Nrf2/HO-1 signaling pathway,thereby attenuating oxidative stress,reducing inflammation,and disrupting the vicious cycle between inflammation and oxidative stress.