BACKGROUND: The American Heart Association (AHA) introduced the concept of cardiovascular-kidney-metabolic (CKM) health and stage, reflecting the interaction among metabolism, chronic kidney disease (CKD), and the cardiovascular system. However, the association between CKM stage and the long-term risk of cardiovascular disease (CVD) has not been validated. This study aimed to evaluate the long-term CVD risk associated with CKM health metrics and CKM stage using data from a population-based cohort study. METHODS: In total, 5293 CVD-free participants were followed up to around 13 years in the Chinese Multi-provincial Cohort Study (CMCS). Considering the pathophysiologic progression of CKM health metrics abnormalities (comprising obesity, central adiposity, prediabetes, diabetes, hypertriglyceridemia, CKD, and metabolic syndrome), participants were divided into CKM stages 0, 1, and 2. The time-dependent Cox regression models were used to estimate the cardiovascular risk associated with CKM health metrics and stage. Additionally, broader CVD outcomes were examined, with a specific assessment of the impact of stage 3 in 2581 participants from the CMCS-Beijing subcohort. RESULTS: Among participants, 91.2% (4825/5293) had at least one abnormal CKM health metric, 8.8% (468/5293), 13.3% (704/5293), and 77.9% (4121/5293) were in CKM stages 0, 1, and 2, respectively; and 710 incident CVD cases occurred during a median follow-up time of 13.3 years (interquartile range: 12.1 to 13.6 years). Participants with each poor CKM health metric exhibited significantly higher CVD risk. Compared with stage 0, the hazard ratio (HR) (95% confidence interval [CI]) for CVD incidence was 1.31 (0.84-2.04) in stage 1 and 2.27 (1.57-3.28) in stage 2. Significant interactive impacts existed between CKM stage and age or sex, with higher CVD risk related to increased CKM stages in participants aged <60 years or females. CONCLUSION These findings highlight the contribution of CKM health metrics and CKM stage to the long-term risk of CVD, suggesting the importance of multi-component recognition and management of poor CKM health in CVD prevention.
Humans ; Female ; Male ; Cardiovascular Diseases/etiology* ; Middle Aged ; Adult ; Cohort Studies ; Renal Insufficiency, Chronic/metabolism* ; Aged ; Risk Factors ; Metabolic Syndrome/metabolism* ; China ; East Asian People

Objective To investigate the expression and clinical significance of B7-H5 in patients with chro-nic hepatitis B and hepatitis B virus(HBV)-related hepatocellular carcinoma.Methods Enzyme-linked immu-nosorbent assay(ELISA)was used to detect the serum levels of B7-H5 in 104 patients with chronic hepatitis B,28 patients with HBV-related hepatocellular carcinoma and 35 healthy controls.And statistical methods were used to analyze the difference,correlation and diagnostic value of the results.Results The serum levels of B7-H5 in patients with HBV-related hepatocellular carcinoma,patients with chronic hepatitis B and healthy subjects were statistically different(P＜0.05),and the level from high to low was HBV-related liver cancer patients,chronic hepatitis B patients,healthy subjects.The serum level of B7-H5 in chronic hepatitis B pa-tients with negative HBV-DNA was significantly higher than that in healthy subjects(P＜0.01).The level of B7-H5 in patients with chronic hepatitis B was positively correlated with HBV-DNA load(P＜0.05).And the level of B7-H5 in patients with HBV-related hepatocellular carcinoma was positively correlated with HBsAg,HBeAg and AFP levels(P＜0.05).In addition,B7-H5 had diagnostic value for chronic hepatitis B and HBV-related hepatocellular carcinoma(P＜0.01),and the diagnostic value for HBV-related hepatocellular carcino-ma was higher than that for chronic hepatitis B.The level of B7-H5 in patients with HBV-related hepatocellu-lar carcinoma after surgery was significantly lower than that before surgery(P＜0.05).Conclusion Serum levels of B7-H5 is related to the progression of CHB and HBV-related hepatocellular carcinoma,and can be considered as an effective detection index for the auxiliary diagnosis and the judgment of postoperative condi-tion of CHB and HBV-related hepatocellular carcinoma.

Objective:To study the correlation of TCM syndrome elements of large artery atherosclerosis (LAA) cerebral infarction with the new four thrombotic markers and cerebrovascular disease risk factors.Methods:Retrospective analysis was conducted for the baseline data and four diagnosis of 174 patients with LAA cerebral infarction in Department of Neurology, Shanxi Provincial People's Hospital from August 2022 to September 2023. These patients were classified into six TCM syndrome elements: internal wind, qi deficiency, internal fire, blood stasis, yin deficiency, and phlegm-dampness. Thrombomodulin (TM), fibrin-α2 antifibrinolytic inhibitor complex (PIC), thrombin-antithrombinogen complex (TAT), and tissue-type plasminogen activator-plasminogen activator inhibitor complex (t-PAIC) tests were performed in 24 h. Correlation analysis was conducted between the TCM syndrome typing of LAA stroke patients and baseline data, as well as the results of four thrombotic tests.Results:Among the 174 patients with LAA cerebral infarction, 49 (28.16%) were in the internal wind type, 37 (21.26%) in the phlegm-dampness type, 37 (21.26%) in the qi deficiency type, 16 (9.20%) in the internal fire type, 18 (10.35%) in the yin deficiency type, and 17 (9.77%) in the blood stasis type. Comparison of plasma TM ( P=0.003), PIC ( P=0.022), TAT ( P<0.001) and t-PAIC ( P=0.007) levels of each TCM syndrome element showed statistically significant differences ( P<0.05). Logistic regression analysis showed that gender was an influencing factor for the internal wind syndrome element and qi deficiency syndrome element [ OR (95% CI)=0.140 (0.037-0.536)] and blood stasis syndrome element [ OR (95% CI)=0.185 (0.042-0.820)] in TCM; TM was an influencing factor for the internal wind syndrome element and yin deficiency syndrome element [ OR (95% CI)=0.617 (0.423-0.900)], and blood stasis syndrome element [ OR (95% CI)=0.693 (0.496-0.968) ]; TAT was an influencing factor for internal wind syndrome element and phlegm-dampness syndrome element [ OR (95% CI)=2.143 (1.364-3.367)], qi deficiency syndrome element [ OR (95% CI)=1.937 (1.221-3.073)], and internal fire syndrome element [ OR (95% CI)=1.937 (1.221-3.073)], internal fire evidence element [ OR (95% CI)=2.949 (1.796-4.842)], and blood stasis evidence element [ OR (95% CI)=2.118 (1.246-30 600)]; t-PAIC was an influential factor for internal wind syndrome element and qi deficiency syndrome element [ OR (95% CI)=1.140 (1.033-1.258)] ( P<0.05). The ROC curve suggested that a TM level of 8.05 TU/ml had a diagnostic performance of 71.8% for the yin deficiency syndrome; a TAT level of 2.45 ng/L had a diagnostic performance of 71.2% for the internal wind syndrome; a TAT level of 1.65 ng/L had a diagnostic performance of 72.6% for the internal fire syndrome; and a t-PAIC level of 17.55 ng/L had a diagnostic performance of 70.4% for the qi deficiency syndrome. The diagnostic performance of t-PAIC was 70.4% at a t-PAIC level of 17.55 ng/L. Conclusion:Plasma TM, TAT, and t-PAIC levels are independent risk factors for different syndrome elements in patients with LAA cerebral infarction and can be used as markers for early determination of different syndrome elements.

OBJECTIVE: To report the blood group antigen and antibody specificity identification methods for a patient with high-frequency antibodies, and the process of finding and providing compatible blood for the patient. METHODS: A patient sent from the Blood Transfusion Department of Shanxi Provincial People's Hospital to Blood Transfusion Technology Research Laboratory of Taiyuan Blood Center in November 2022 was selected for the study. Classical serological methods were used to determine the patient's blood type, screen for unexpected antibodies, identify antibodies, and perform crossmatching. High-frequency antibody identification was carried out using red blood cells treated with various enzymes. Blood group genotyping was conducted using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF) and Sanger sequencing. Multiple strategies were employed to address the patient's blood source problem. The study was approved by the Medical Ethics Committee of Taiyuan Blood Center [Ethics No. 2024 Ethics Review No.(2)]. RESULTS: The patient's blood type was B, RhD positive. Initial screening of the patient's serum with multiple screening cells and antibody identification cells in saline medium was negative, but positive in antiglobulin medium. The patient's serum showed varying reaction intensities with red blood cells treated with different enzymes. MALDI-TOF mass spectrometry and Sanger sequencing revealed a homozygous nonsense variant c.376C>T (p.Gln126Ter) in the ABCG2 gene, resulting in the Jr(a-) phenotype. During family donor selection, the patient's son was found to have a heterozygous variant c.376C>T (p.Gln126Ter), and another heterozygous variant c.421C>A (p.Gln141Lys), which predicted a Jr(a+w) phenotype. Crossmatch tests confirmed the compatibility of blood from the patient's son, which was used to address the urgent blood requirement. Later, rare blood from a Jr(a-) donor from the Guangzhou Blood Center was used for the patient's ongoing treatment, saving the patient's life. CONCLUSION Combining classic serological testing with blood group gene typing techniques successfully identified the rare Jr(a-) blood type and high-frequency anti-Jra antibodies. Enzyme-treated red blood cell identification methods confirmed the presence of anti-Jra antibodies. By searching within the family and seeking help from other blood centers, compatible blood was found. This approach may provide insights for resolving similar complex blood matching problems in the future.
Humans ; Blood Grouping and Crossmatching/methods* ; Blood Group Antigens/immunology* ; Blood Transfusion ; Male ; Isoantibodies/blood* ; Female ; Genotype

Psychiatric comorbidity is common in symptom-based diagnoses like autism spectrum disorder (ASD), attention/deficit hyper-activity disorder (ADHD), and obsessive-compulsive disorder (OCD). However, these co-occurring symptoms mediated by shared and/or distinct neural mechanisms are difficult to profile at the individual level. Capitalizing on unsupervised machine learning with a hierarchical Bayesian framework, we derived latent disease factors from resting-state functional connectivity data in a hybrid cohort of ASD and ADHD and delineated individual associations with dimensional symptoms based on canonical correlation analysis. Models based on the same factors generalized to previously unseen individuals in a subclinical cohort and one local OCD database with a subset of patients undergoing neurosurgical intervention. Four factors, identified as variably co-expressed in each patient, were significantly correlated with distinct symptom domains (r = -0.26-0.53, P < 0.05): behavioral regulation (Factor-1), communication (Factor-2), anxiety (Factor-3), adaptive behaviors (Factor-4). Moreover, we demonstrated Factor-1 expressed in patients with OCD and Factor-3 expressed in participants with anxiety, at the degree to which factor expression was significantly predictive of individual symptom scores (r = 0.18-0.5, P < 0.01). Importantly, peri-intervention changes in Factor-1 of OCD were associated with variable treatment outcomes (r = 0.39, P < 0.05). Our results indicate that these data-derived latent disease factors quantify individual factor expression to inform dimensional symptom and treatment outcomes across cohorts, which may promote quantitative psychiatric diagnosis and personalized intervention.
Humans ; Male ; Female ; Attention Deficit Disorder with Hyperactivity ; Obsessive-Compulsive Disorder ; Adult ; Autism Spectrum Disorder ; Bayes Theorem ; Adolescent ; Young Adult ; Magnetic Resonance Imaging ; Middle Aged ; Child ; Brain/metabolism* ; Cohort Studies ; Comorbidity

Humans ; Asthma/drug therapy* ; Biological Therapy

Background: Serum C-peptide results from various routine methods used in China are highly variable, warranting well-performing methods to serve as an accuracy base to improve the harmonization of C-peptide measurements in China. We developed an accurate isotope dilution liquid chromatography-tandem mass spectrometry (ID-LC–MS/MS) method for serum C-peptide measurement and explored its use in harmonization. Methods: After protein precipitation with ZnSO4 solution, C-peptide was extracted from serum samples by anion-exchange solid-phase extraction and quantified by ID-LC–MS/MS in positive ion mode. The precision and analytical recovery of the ID-LC–MS/MS method were assessed. Seventy-six serum samples were analyzed using the ID-LC–MS/MS method and six routine immunoassays. Ordinary linear regression (OLR) and Bland-Altman (BA) analyses were conducted to evaluate the relationship between the ID-LC–MS/MS method and routine immunoassays. Five serum pool samples assigned using the ID-LC–MS/MS method were used to recalibrate the routine assays. OLR and BA analyses were re-conducted after recalibration. Results: The within-run, between-run, and total precision for the ID-LC–MS/MS method at four concentrations were 1.0%–2.1%, 0.6%–1.2%, and 1.3%–2.2%, respectively. The analytical recoveries for the ID-LC–MS/MS method at three concentrations were 100.3%–100.7%, 100.4%–101.0%, and 99.6%–100.7%. The developed method and the immunoassays were strongly correlated, with all R2 >0.98. The comparability among the immunoassays was substantially improved after recalibration. Conclusions The performance of the ID-LC–MS/MS method was carefully validated, and this method can be used to improve the harmonization of serum C-peptide measurements in China.

Machine learning approaches are increasingly being applied to neuroimaging data from patients with psychiatric disorders to extract brain-based features for diagnosis and prognosis. The goal of this review is to discuss recent practices for evaluating machine learning applications to obsessive-compulsive and related disorders and to advance a novel strategy of building machine learning models based on a set of core brain regions for better performance, interpretability, and generalizability. Specifically, we argue that a core set of co-altered brain regions (namely 'core regions') comprising areas central to the underlying psychopathology enables the efficient construction of a predictive model to identify distinct symptom dimensions/clusters in individual patients. Hypothesis-driven and data-driven approaches are further introduced showing how core regions are identified from the entire brain. We demonstrate a broadly applicable roadmap for leveraging this core set-based strategy to accelerate the pursuit of neuroimaging-based markers for diagnosis and prognosis in a variety of psychiatric disorders.
Humans ; Obsessive-Compulsive Disorder/epidemiology* ; Brain/pathology* ; Neuroimaging/methods* ; Machine Learning ; Comorbidity ; Magnetic Resonance Imaging/methods*

Objective To investigate the correlation between the expression of coagulation markers thrombomodulin(TM) and tissue plasminogen activator-plasminogen activator inhibitor-1 complex(t-PAIC) and white matter lesions(WMLs). Methods A total of 69 patients with WMLs who were hospitalized in the Department of Neurology of Shanxi Provincial People's Hospital from July 2020 to October 2022 were selected. After admission,novel coagulation markers were tested,and cranial magnetic resonance examination was completed. WMLs were graded according to the Fazekas visual rating scale,and the correlation between novel coagulation markers and WML severity in patients with WMLs was analyzed by the Kendall stau-b method. Multivariate logistic regression was used to analyze the influencing factors for WML severity. Results There were significant differences in serum TM and t-PAIC levels between the mild,moderate,and severe WML groups,and the levels of serum TM and t-PAIC in the moderate and severe WML groups were significantly increased compared with the mild WML group(P<0.05). There was a correlation between serum TM and t-PAIC levels and the severity of WMLs in the three groups(P<0.05). The high level of t-PAIC and age were risk factors for the aggravation of WMLs,with odds ratios(95% confidence interval) of 1.274(1.052-1.544) and 1.063(1.015-1.114),respectively(P<0.05). Conclusion The expression of serum TM and t-PAIC in patients with WMLs is positively correlated with the degree of white matter lesions,and t-PAIC is a risk factor for the exacerbation of white matter lesions, which may be used as a serum marker to indicate the development of WML patients.