Objective: To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening. Methods : From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764. Conclusion The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.

Background Microparticles (MPs) are one of the main medium of inflammatory reaction with an important role in atherosclerotic progression. Studies on association of air pollution exposure and levels of peripheral blood MPs are limited among human. Objective To evaluate the effects of short-term exposure to air pollution on levels of peripheral blood MPs. Method A panel of 73 healthy adults was followed with 4 repeated follow-ups in Beijing, China, from November 2014 to January 2016. During each visit, we collected questionnaire information, fasting venous blood, urine, and exposures to fine particulate matter (PM_2.5), black carbon, nitric oxide, nitrogen dioxide, nitrogen oxide, sulfur dioxide, carbon monoxide, and ozone. We used linear mixed-effect models to analyze associations of air pollution exposure with levels of total MPs (TMPs) and MPs derived from various cells. Stratified analysis was conducted by levels of C-reactive protein (CRP) and malondialdehyde (MDA). Results The results showed significant associations between air pollution exposure and peripheral blood TMPs at 2 h-6 d prior to the follow-ups (P<0.05), while no statistical associations were found for MPs derived from different cell types. Significant increases in TMPs of 7.8% (95%CI: 0.7%, 15.3%) and 14.3% (95%CI: 2.8%, 27.2%) were observed with each interquartile range (IQR) increase in PM_2.5 (IQR=64.9 μg·m⁻³) at prior 18 h and NO (IQR=40.5 μg·m⁻³) at prior 48 h. Among participants with low levels of CRP and MDA, significantly positive associations were observed between air pollution exposure and levels of TMPs (P<0.05). Conclusion Short-term exposure to air pollution is significantly associated with increased levels of circulating MPs in healthy adults, and in people with lower systemic inflammation, peripheral blood MPs levels are more easily affected after exposure to air pollutants.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Aim To study the role and mechanism of ML210 in glioma.Methods The cell viability was detected by CCK8 assay.The percentage of dead cells was detected by SYTOXstaining.The role of ferroptosis-signaling pathway in gliomas was detected bygenomics.Cell proliferation was observed by EdU staining and clone formation assay.Cell migration ability was detec-ted by scratch healing assay.The apoptosis was detec-ted by flow cytometry.Cell mitochondrial function was assesses by JC-1 staining.The mechanism of action of ML210 was detected by molecular docking coupled with immunoblotting assay(Western blot).The levels of ROS,MDA were observed by ELISA.Results Compared with the control group,ML210 treatment dose-dependently decreased glioma cell viability,in-hibited cell proliferation,migration,and increased cell apoptosis and mitochondrial dysfunction,which were reversed by ferroptosis antagonists.Gene microarray screening showed that 688 genes of the ferroptosissig-naling pathway were aberrant and 10 signaling path-ways were altered in gliomas.Molecular docking re-sults showed that ML210 binding to GPX4 significantly inhibited the protein expression level of GPX4 and pro-moted the elevation of ROS and MDA levels.Conclu-sions ML210 produces anti-glioma cells via GPX4-mediated ferroptosis pathway.

AIM To study the chemical constituents from Dictamni Cortex.METHODS The 70％ethanol extract from Dictamni Cortex was isolated and purified by HP-20 macroporous resin,silica gel,MCI,ODS and preparative HPLC,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Thirty-three compounds were isolated and identified as rutin(1),apigenin(2),catechin(3),hesperetin(4),leonuriside A(5),androsin(6),2-methoxy-4-acetylphenol-O-α-rhamnopyranosyl-(1"-6')-β-glucopyranoside(7),vanillic acid(8),gallic acid(9),4-hydroxybenzoic acid(10),benzoic acid(11),involcranoside B(12),benzyl β-D-glucopyranoside(13),bphenylethyl-rutinoside(14),1-bromonaphthalene(15),cimifugin(16),9(S),12(S),13(S)-trihydroxyoctadeca-10(E),15(Z)-dienoic acid(17),methyl-9,12,13-trihydroxyoctadeca-10,15-dienoate(18),7,8-dihydroxy-9,12(Z,Z)-octadecadienoic acid(19),vernolic acid(20),9,10(erythro)-dihydroxy-11 E-octadecadienoic acid methyl ester(21),(7Z,9E,13Z)-11-hydroxyhexadeca-7,9,13-trienoic acid(22),(7Z,10Z,14E,16Z,19Z)-13-hydroxydocosa-7,10,14,16,19-pentaenoic acid(23),(9E)-8,11,12-trihydroxyoctadecenoic acid methyl ester(24),n-hexanol-O-rutinoside(25),hexyl β-sophoroside(26),3-pentyl 6'-(3-hydroxy-3-methylglutaryl)-β-D-glucopyranoside(27),3-methylbut-3-enyl-6-O-β-D-glucopyranosyl-β-D-glucopyranoside(28),3-methyl-but-2-en-1-yl β-D-glucopyranoside(29),3-methylbutan-1-ol-β-D-glucopyranoside(30),pregnenolone(31),2-butoxytetrahydrofuran(32),psydrin(33).CONCLUSION Compounds 2-4,8-13,15-16,25-28 and 32-33 are isolated from Rutaceae family for the first time.

The accuracy of medical imaging diagnosis will directly impact the clinical forensic evaluation's scientific validity and objectivity.This study systematically analyzed the primary causes of misdiagnosis and missed diagnosis in imaging examinations,focusing on representative cases,including rib fractures,traumatic subarachnoid hemorrhage,joint injuries with ligament damage,nasal fractures,congenital skeletal variations,and epiphyseal injuries.Key contributing factors encompassed limitation of imaging technologies,the insufficient interpretive experience of examiners,the complexity of injury mechanisms,and inadequate post-traumatic dynamic imaging follow-up.To address these issues,improvement strategies are proposed,which were establishing standardized imaging review protocols,implementing multimodal imaging approaches,rigorous evaluation of original imaging data,and enhancing professional knowledge regarding anatomical variations and injury differentiation.These measures aim to elevate the quality of forensic imaging diagnosis,providing more precise and reliable strategies for forensic clinical identifications.

Aim To investigate the role of corylin in angiotensin Ⅱ(Ang Ⅱ)-induced cardiomyocyte hy-pertrophy and its underlying mechanisms.Methods An Ang Ⅱ-induced cardiomyocyte hypertrophy model was established and treated with corylin.Real-time PCR was employed to assess hypertrophic gene mRNA expression,and immunofluorescence was used to meas-ure cardiomyocyte surface area.Western blot and en-zyme activity assay kits were used to evaluate SIRT1 expression and activity.Results Corylin markedly mitigated Ang Ⅱ-induced hypertrophic gene expression and cardiomyocyte surface area enlargement.Moreo-ver,it prevented the Ang Ⅱ-mediated decline in SIRT1 protein levels and deacetylase activity.Further investi-gation indicated that corylin inhibited Ang Ⅱ-driven NF-κB transcriptional activity and the expression of its downstream target genes,such as TNF-α,IL-6,and IL-1β.Notably,SIRT1 silencing abolished the protective effects of corylin against cardiomyocyte hypertrophy,as well as its regulation of the SIRT1/NF-κB signaling pathway.Conclusion Corylin suppresses cardiomyo-cyte hypertrophy by modulating the SIRT1-dependent NF-κB signaling pathway.

Objective To investigate the coagulation effect of a cold atmospheric plasma(CAP)jet device with helium as the working gas and to study its coagulation mechanism preliminarily.Methods A CAP jet device treatment group,a helium airflow treatment group,a hot air treatment group(60℃)and a natural coagulation group were formed according to the treatment modes of the blood samples,with 10 μL of blood samples involved in each group,in order to validate the coagulation effect of the CAP jet device in vitro;the coagulation mechanism of the CAP jet device was explored by its application to the treatment of anticoagulated whole blood,platelet-rich plasma and platelet-depleted plasma;the coagulation effect of the CAP jet device in vivo was verified with a mouse liver punctate hemorrhage model and a rabbit mesenteric hemorrhage model.Results The CAP jet device can significantly accelerate the coagulation of anticoagulated blood droplets,and the coagulation time of anticoagulated blood droplets in the CAP jet device-treated group was shortened from 28 min in the natural coagulation group to(23±1.56)s,with the difference statistically significant(P<0.05),and the CAP jet device treatment group gained advantages significantly over the helium airflow treatment group(P<0.05)and the hot air(60℃)treatment group(P<0.05)in coagulation-promoting effect;the procoagulant effect of the CAP jet device rose with the increase of platelet content in blood droplets,and the coagulation effect of platelet-rich blood droplets was significantly better than that of whole blood(P<0.05),while no coagulation was observed in platelet-poor droplets.The CAP jet device could rapidly stop hemostasis of punctate hemorrhage in mouse liver and mesenteric hemorrhage in rabbits without delayed hemorrhage occurring within 10 min,and no obvious structural abnormality of the liver and thermal damage of the tissue were found microscopically.Conclusion The CAP jet device plays procoagulant and hemostatic effects in vivo and in vitro,and its effect is not dependent on temperature and airflow evaporation effects and is considered to be related to platelet activation,with low thermal damage to living tissue.[Chinese Medical Equipment Journal,2025,46(6):20-27]

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.