Objective: To analyze the prevalence trends of different types of elevated blood pressure and their association with nutritional status among primary and secondary school students in Inner Mongolia from 2019 to 2024, providing references for targeted prevention strategies. Methods: From September 2019 to 2024, a stratified random cluster sampling method was used to select 12 primary and secondary schools from each league city in Inner Mongolia Autonomous Region. A total of 177 108, 137 758, 190 182, 180 084 , 188 056, 180 351 primary and secondary school students (excluding grades one to three of primary school) were included for physical examination. The correlation between their nutritional status and high blood pressure was analyzed based on the basic situation of 129 821 primary and secondary school students who completed a questionnaire survey at the same time in 2024. Statistical analysis was conducted using a Chi-square test and multiple Logistic regression model. Results: From 2019 to 2024, the detection rates of elevated blood pressure were 13.60%, 13.68%, 17.60%, 17.24%, 14.77% and 15.96%, respectively. The rates for isolated systolic hypertension were 4.24%, 5.83%, 7.26%, 7.19%, 6.24% and 6.93%; isolated diastolic hypertension rates were 6.38%, 4.99%, 6.23 %, 6.41%, 5.39% and 5.66%; and combined systolic and diastolic hypertension rates were 2.97%, 2.86%, 4.11%, 3.65%, 3.14 % and 3.36%. Multivariate Logistic regression analysis showed that girls, junior high school, senior high school, overweight, and obesity were positively associated with elevated blood pressure risk ( OR =1.27, 1.25, 1.32, 1.66, 3.07, all P <0.05); conversely, county residence, Mongolian ethnicity, and other ethnicities showed negative associations ( OR =0.90, 0.93, 0.90, all P <0.05). Conclusions Overweight and obesity among children and adolescents are closely related to various types of elevated blood pressure. Prevention strategies should prioritize effectively controlling weight issues among children and adolescents, thereby effectively reducing the incidence of elevated blood pressure.

INTRODUCTION: Lecanemab has shown promise in treating early Alzheimer's disease (AD), but its safety and efficacy in Chinese populations remain unexplored. This study aimed to evaluate the safety and 6-month clinical outcomes of lecanemab in Chinese patients with mild cognitive impairment (MCI) or mild AD. METHODS: In this single-arm, real-world study, participants with MCI due to AD or mild AD received biweekly intravenous lecanemab (10 mg/kg). The study was conducted at Hainan Branch, Ruijin Hospital Shanghai Jiao Tong University School of Medicine. Patient enrollment and baseline assessments commenced in November 2023. Safety assessments included monitoring for amyloid-related imaging abnormalities (ARIA) and other adverse events. Clinical and biomarker changes from baseline to 6 months were evaluated using cognitive scales (mini-mental state examination [MMSE], montreal cognitive assessment [MoCA], clinical dementia rating-sum of boxes [CDR-SB]), plasma biomarker analysis, and advanced neuroimaging. RESULTS: A total of 64 patients were enrolled in this ongoing real-world study. Safety analysis revealed predominantly mild adverse events, with infusion-related reactions (20.3%, 13/64) being the most common. Of these, 69.2% (9/13) occurred during the initial infusion and 84.6% (11/13) did not recur. ARIA-H (microhemorrhages/superficial siderosis) and ARIA-E (edema/effusion) were observed in 9.4% (6/64) and 3.1% (2/64) of participants, respectively, with only two symptomatic cases (one ARIA-E presenting with headache and one ARIA-H with visual disturbances). After 6 months of treatment, cognitive scores remained stable compared to baseline (MMSE: 22.33 ± 5.58 vs . 21.27 ± 4.30, P = 0.733; MoCA: 16.38 ± 6.67 vs . 15.90 ± 4.78, P = 0.785; CDR-SB: 2.30 ± 1.65 vs . 3.16 ± 1.72, P = 0.357), while significantly increasing plasma amyloid-β 42 (Aβ42) (+21.42%) and Aβ40 (+23.53%) levels compared to baseline. CONCLUSIONS: Lecanemab demonstrated a favorable safety profile in Chinese patients with early AD. Cognitive stability and biomarker changes over 6 months suggest potential efficacy, though high dropout rates and absence of a control group warrant cautious interpretation. These findings provide preliminary real-world evidence for lecanemab's use in China, supporting further investigation in larger controlled studies. REGISTRATION ClinicalTrials.gov , NCT07034222.
Humans ; Alzheimer Disease/drug therapy* ; Male ; Female ; Aged ; Middle Aged ; Cognitive Dysfunction/drug therapy* ; Aged, 80 and over ; Amyloid beta-Peptides/metabolism* ; Biomarkers ; East Asian People

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

OBJECTIVES: Multiple myeloma (MM) is a hematologic malignancy characterized by clonal proliferation of plasma cells and remains incurable. Patients with primary refractory multiple myeloma (PRMM) show poor response to initial induction therapy. This study aims to develop a machine learning-based model to predict treatment response in newly diagnosed multiple myeloma (NDMM) patients, in order to optimize therapeutic strategies. METHODS: NDMM and post-treatment MM patients hospitalized in the Department of Hematology, Third Xiangya Hospital, Central South University, between August 2022 and July 2023 were enrolled. Post-treatment MM patients were categorized into PRMM patients and treatment-responsive MM (TRMM) patients based on therapeutic efficacy. Serum metabolites were detected and analyzed via metabolomics. Based on the metabolomics analysis results and combined with transcriptomic sequencing data of NDMM patients from databases, differentially expressed amino acid metabolism-related genes (AAMGs) among post-treatment NDMM patients with varying therapeutic outcomes were screened. Using bioinformatics analyses and machine learning algorithms, a predictive model for treatment response in NDMM was constructed and used to identify patients at risk for PRMM. RESULTS: A total of 61 patients were included: 22 NDMM, 23 TRMM, and 16 PRMM patients. Significant differences in metabolite levels were observed among the 3 groups, with differential metabolites mainly enriched in amino acid metabolism pathways. Follow-up data were available for 16 of the 22 NDMM patients, including 12 treatment responders (ND_TR group) and 4 with PRMM (ND_PR group). A total of 23 differential metabolites were identified between these 2 groups: 6 metabolites (e.g., tryptophan) were upregulated and 17 (e.g., citric acid) were downregulated in the ND_TR group. Transcriptomic data from 108 TRMM and 77 PRMM patients were analyzed to identify differentially expressed AAMGs, which were then used to construct a prediction model. The area under the receiver operating characteristic curve (AUC) for the model exceeded 0.8, and AUC values in 3 external validation cohorts were all above 0.7. CONCLUSIONS This study delineated the metabolic alterations in MM patients with different treatment response, suggesting that dysregulated amino acid metabolism may be associated with poor treatment response in PRMM. By integrating metabolomics and transcriptomics, a machine learning-based predictive model was successfully established to forecast treatment response in NDMM patients.
Humans ; Multiple Myeloma/drug therapy* ; Machine Learning ; Male ; Female ; Metabolomics/methods* ; Middle Aged ; Aged ; Treatment Outcome ; Transcriptome ; Computational Biology ; Adult ; Multiomics

Background and purpose:In 2016 the National Cancer Institute(NCI)decided stopping to use NCI-60 cell lines for drug screening,suggesting that tumor cell lines were losing their value as a tool for drug discovery and basic research.The reason for NCI-60 cells'retirement'was that the preclinical studies based on traditional cellular and animal models did not obtain the corresponding expected efficacy in clinical trials.Since the major cancer behaviors,such as proliferation and metastasis,are fundamentally altered with long-term culture,the tumor cell lines are not representative of the characteristics of cancer in patients.Currently,scientists hope to create a new cancer model that are derived from fresh patient samples and tagged with details about their clinical past.Our purpose was to create patient-derived breast cancer primary cell lines as new cancer model for drug screening and basic research.Methods:Breast cancer tissues were collected in the Department of Breast Surgery,Affiliated Hospital of Guizhou Medical University.The collection of tumor tissue samples was approved by the Ethics Committee of the Affiliated Hospital of Guizhou Medical University(approval number:2022 ethics No.313),and the collection and use of tumor tissues complied with the Declaration of Helsinki.The primary breast cancer cell lines were isolated from the patient's breast cancer tissues and cultured in BCMI medium.After the cells proliferated,the media were replaced with DEME medium.Cell line STR genotyping was done to determine cell-specific genetic markers and identification.Clone formation assay and transplantation assay were done to analyze the ability of breast cancer primary cell lines to form tumors.Results:We created 6 primary breast cancer cell lines.The 6 primary breast cancer cell lines from the patients were tagged with the definitively clinicopathological features,clinical diagnosis,therapeutic regimens,clinical effectiveness and prognostic outcomes.The STR genotyping assays identified the genetic markers and determined the identities of the 6 primary breast cancer cell lines.Clone formation assays and transplantation assay showed that the proliferative capacities of the patient-derived primary breast cancer cell lines were significantly greater compared with the conventional breast cancer cell lines.Conclusion:We created a panel of 6 patient-derived primary breast cancer cell lines as new cancer model for drug screening and basic research in breast cancer.

A new method was developed for simultaneous detection of total 19 kinds of organophosphate esters(OPEs)and their diester metabolites(di-OPEs)in human serum(1.0 mL)and urine(1.5 mL)with low volume of samples.The target compounds were determined using ultra-high performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)after acetonitrile liquid-liquid extraction combined with purification using an ENVI-18 solid-phase extraction(SPE)column.OPEs and di-OPEs were separated using a Shim-pack GIST C18 column(100 mm×2.1 mm,2 μm)with a Shim-pack GIST-HP(G)C18 guard column.An electrospray ionization source(ESI)was employed in mass spectrometry analysis,with positive/negative ion mode using the multiple reaction monitoring(MRM).All target compounds were separated within 15 min,and exhibited good linear relationships in the concentration range of 2-100 ng/mL,with correlation coefficients(R2)above 0.994.The method detection limits(MDL)in serum ranged from 0.001 to 0.178 ng/mL and the MDL in urine ranged from 0.001 to 0.119 ng/mL.The recoveries of the analytes spiked in serum and urine matrices at two concentration levels were 30.5%-126.8%,with the relative standard deviations(RSDs)ranged from 1%to 23%.In addition,paired serum and urine samples from 11 patients were analyzed.For all samples tested,the internal standards of OPEs exhibited recoveries between 61%and 114%,whereas the internal standards for di-OPEs had recoveries ranging from 43%to 103%.OPEs and di-OPEs exhibited high detection frequencies in 22 serum and urine samples.Triethyl phosphate(TEP),tributyl phosphate(TBP),tris(2-ethylhexyl)phosphate(TEHP),tris(2-butoxyethyl)phosphate(TBEP),tris(1-chloro-2-propyl)phosphate(TCIPP),triphenyl phosphate(TPHP),tri-m-tolyl-phosphate(TMTP)and 2-ethylhexyl diphenyl phosphate(EHDPP)were universally detected in all serum samples.TCIPP was identified at the highest concentrations(median 0.548 ng/mL)in serum samples.In urine samples,the detection frequency for 12 kinds of target compounds reached 100%.Notably,TBP emerged as the predominant OPE in urine,demonstrating a median concentration of 0.506 ng/mL.Regarding di-OPEs,bis(2-chloroethyl)phosphate(BCEP)and bis(2-butoxyethyl)hydrogen phosphate(BBOEP)were the most abundant in urine,with median concentrations of 6.404 and 2.136 ng/mL,respectively.The total concentrations of OPEs and di-OPEs in serum and urine were 1.580-3.843 ng/mL and 5.149-17.537 ng/mL,respectively.These results not only confirmed the effectiveness of the method in detection of OPEs and di-OPEs in biological matrices,but also revealed the widespread presence of OPE compounds in human body and pointed to potential exposure risks.

Thrombus is a major factor leading to cardiovascular diseases such as myocardial infarction and stroke. Although fibrinolytic anti-thrombotic drugs have been widely used in clinical practice, they are still limited by narrow therapeutic windows, short half-lives, susceptibility to inactivation, and abnormal bleeding caused by non-targeting. Therefore, it is crucial to effectively deliver thrombolytic agents to the site of thrombus with minimal adverse effects. Based on the long blood circulation and excellent drug-loading properties of human serum albumin (HSA), we employed genetic engineering techniques to insert a functional peptide (P-selectin binding peptide, PBP) which can target the thrombus site to the N-terminus of HSA. The fusion protein was expressed using Pichia pastoris and purified by Ni-chelating affinity chromatography. After being loaded with gold nanoparticles (Au NPs), the fusion protein formed homogeneous and stable nanoparticles (named as PBP-HSA@Au) with a diameter of 17.7 ± 1.0 nm and a zeta potential of -11.3 ± 0.2 mV. Cytotoxicity and hemolysis tests demonstrated the superb biocompatibility of PBP-HSA@Au. Platelet-targeting experiments confirmed the thrombus-targeting ability conferred by the introduction of PBP into PBP-HSA@Au. Upon near-infrared ray (NIR) irradiation, PBP-HSA@Au rapidly converted light energy into heat, thereby disrupting fibrinogen and exhibiting outstanding thrombolytic efficacy. The designed HSA fusion protein delivery system provides a precise, rapid, and drug-free treatment strategy for thrombus therapy. This system is characterized by its simple design, high biocompatibility, and strong clinical applicability. All animal experiments involved in this study were carried out under the protocols approved by the Animal Experiment Ethics Committee of Jiangnan University [JN. No20230915S0301015(423)].

Objective To explore the relationship and internal path between activities of daily living(ADL),sleep quality and mental health of community elderly people in Shanghai.Methods A questionnaire survey was conducted among community residents aged 60 years and older seeing doctors in community health care center of five streets in Shanghai during Sept to Dec,2021 using convenience sampling.Activities of Daily Living(ADL),Pittsburgh Sleep Quality Index(PSQI)and 10-item Kessler Psychological Distress Scale(K10)were adopted in the survey.Single factor analysis,correlation analysis and multiple linear regression were used to analyze the data.The effect relationship between the variables was tested using Bootstrap's mediated effects test.Results A total of 1 864 participants were included in the study.The average score was 15.53±4.47 for ADL,5.60±3.71 for PSQI and 15.50±6.28 for K10.The rate of ADL impairment,poor sleep quality,poor and very poor mental health of the elderly were 23.6%,27.3%,11.9%and 4.9%,respectively.ADL and sleep quality were all positively correlated with mental health(r=0.321,P＜0.001;r=0.466,P＜0.001);ADL was positively correlated with sleep quality(r=0.294,P＜0.001).Multiple linear results of factors influencing mental health showed that ADL(β= 0.457,95%CI:0.341-0.573),sleep quality(β =0.667,95%CI:0.598-0.737)and mental health were positively correlated(P＜0.001).Sleep quality partially mediated the relationship between ADL and mental health(95%CI:0.078-0.124)with an effect size of 33.0%.Conclusion Sleep quality is a mediator between ADL and mental health among community elderly people.Improving ADL and sleep quality may improve mental health in the population.

Objective:To compare the prognostic values of different classification by using transpulmonary pressure gradient (TPG), diastolic pressure gradient (DPG) and pulmonary vascular resistance (PVR) in patients with pulmonary hypertension due to left heart disease (PH-LHD), and investigated hemodynamic and clinical factors associated with mortality in patients with PH-LHD.Methods:This was a single-center prospective cohort study. In-hospital patients diagnosed with PH-LHD via right heart catheterization at the Department of Cardiology, the First Affiliated Hospital of Nanjing Medical University, from September 2013 to December 2019 were enrolled. Patients were divided according to TPG (cutoff value 12 mmHg; 1 mmHg=0.133 kPa), DPG (cutoff value 7 mmHg), PVR (cutoff value 3 Wood Units), and the combination of TPG and PVR. Baseline characteristic was recorded. All patients were followed up until the occurrence of endpoint event, defined as all-cause death that occurred during the follow-up period, or until April 18, 2022. Receiver operating characteristic curves were used to compare the predictive value of 3 classification methods for all-cause death in PH-LHD patients. The optimal cutoff values were calculated using Jorden index. Survival analysis was performed using Kaplan-Meier analysis, and log-rank test was used to compare the predictive efficacy of classification methods based on optimal cutoff values or guidance-recommended thresholds for the survival of PH-LHD patients. Variables showing statistical significance in the univariate analysis were incorporated into multivariate Cox regression model to analyze the independent risk factors for all-cause mortality.Results:A total of 243 patients were enrolled, aged (54.9±12.7) years old, including 169 (69.5%) males. During a median follow-up of 57 months, there were 101 (41.6%) deaths occurred. Grouping results were as follows: (1) TPG: TPG≤12 mmHg group 115 patients, TPG>12 mmHg group 128 patients; (2) DPG: DPG<7 mmHg group 193 patients, DPG≥7 mmHg group 50 patients; (3) PVR: PVR≤3 Wood Units group 108 patients, PVR>3 Wood Units group 135 patients; (4) TPG and PVR: TPG≤12 mmHg and PVR≤3 Wood Units group 89 patients, TPG>12 mmHg and PVR>3 Wood Units group 109 patients. PVR ( AUC=0. 698,95% CI:0.631-0.766) had better predictive value for all-cause mortality than TPG ( AUC=0.596, 95% CI: 0.523-0.669) and DPG ( AUC=0.526, 95% CI: 0.452-0.601) (all P<0.05). The optimal cutoff values for TPG, DPG, and PVR were13.9 mmHg, 2.8 mmHg, and 3.8 Wood Units, respectively. Kaplan-Meier analysis based on the optimal cutoff values or guidance-recommended thresholds showed that PVR and TPG were the predictors of survival ( P<0.05), while DPG did not showed significance ( P>0.05). Multivariate Cox regression analysis showed that age, PVR and log 2N-terminal pro-B-type natriuretic peptide were independent risk factors for all-cause mortality in PH-LHD patients (all P<0.05). Conclusion:Classification according to PVR was most valuable in predicting all-cause death in PH-LHD patients, while TPG showed moderate predictive ability and DPG had no predictive value.

This study used kidney metabolomics to investigate the underlying mechanisms of Guilingji (GLJ) on mild cognitive impairment (MCI) rats. The rats were randomly divided into 6 groups (n = 8), i.e., control group, model group, positive drug (Ginkgo biloba tablet, donepezil) group, GLJ group (low and high dose group). The MCI rat model was replicated using subcutaneous injection of D-galactose into the back of the neck along with a semi-high-fat diet for a total of 8 weeks, and drug was administered from the 5th week for 4 weeks. The kidney function and renal pathological changes of each group of rats were tested. And LC-MS based kidney metabolomics coupled with multivariate data analysis were conducted to explore the potential biomarkers, and corresponding metabolic pathways were then determined. After administration of GLJ, the level of urea nitrogen was decreased compared with those of the model group, and the abnormalities of morphology in kidney tissues were improved. The positive drugs (ginkgo biloba tablet and donepezil) had no significant modulating effect on renal function indexes. Ginkgo biloba tablet can lessen the pathological injury of kidney tissue, and donepezil had no improvement on renal histopathology. A total of 23 MCI related differential metabolites were identified in kidney, and 17 metabolites were signifcantly restored by GLJ compared with those of the model group. Additionally, we found that the cysteine and methionine metabolism, nicotinate and nicotinamide metabolism, taurine and hypotaurine metabolism, glycerophospholipid metabolism were significantly involved in the regulatory effect of GLJ. The results illuminate the "cong shen zhi nao" mechanism of GLJ, and also provide a research basis for the clinical use of GLJ for the treatment of MCI. The animal experiment of this study was approved by the Ethics Committee of Shanxi University (approval number: 2020DW121).