[Objective] To study on the genotyping of a sample with inconsistent forward and reverse serological tests, and to conduct a pedigree investigation and molecular biological mechanism study. [Methods] The ABO blood group of the proband and his family members were identified using blood group serological method. The ABO gene exon 1-7 of samples of the proband and his family were sequenced by Sanger and single molecule real-time sequencing (SMRT). DeepTMHMM was used to predict and analyze the transmembrane region of proteins before and after mutation. [Results] The proband and his mother have the Bw phenotype, while his maternal grandfather has ABw phenotype. The blood group results of forward and reverse typing of other family members were consistent. ABO gene sequencing results showed that there was B new mutation of c.3 G>C in exon 1 of ABO gene in the proband, his mother and grandfather, leading to a shift in translation start site. DeepTMHMM analysis indicated that the shift in the translation start site altered the protein topology. [Conclusion] The c.3G>C mutation in the first exon of the ABO gene leads to a shift in the translation start site, altering the protein topology from an α-transmembrane region to a spherical signaling peptide, reducing enzyme activity and resulting in the Bw serological phenotype.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

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.

BackgroundThere exist differences in the subjective and objective cognitive functions of patients with depressive disorder， ane there are limited research on influencing factors of such phenomenon currently. ObjectiveTo explore the differences in subjective and objective cognitive function in patients with depressive disorder as well as influencing factors， and to provide references for further understanding of cognitive impairment in patients with depressive disorder. MethodsA total of 77 patients with depressive disorder who received outpatient or inpatient treatment in the Fourth People's Hospital of Chengdu from January 13， 2022 to December 11， 2023 were selected for the study. These patients also met the diagnostic criteria of Diagnostic and Statistical Manual of Mental Disorders， fifth edition（DSM-5）. Various tools were employed to assess patients in this study： Montgomery-Asberg Depression Rating Scale （MADRS） for the depressive symptoms， Perceived Deficits Questionnaire for Depression （PDQ-D） and Chinese Version of Brief Neurocognitive Test Battery （C-BCT） for the subjective and objective cognitive function， Sheehan Disability Scale （SDS） for the social function， and Clinical Global Impression-Severity of Illness（CGI-SI） for the severity of patient's condition. Pearson correlation analysis was used to examine the correlation of subjective and objective cognitive function and their differences with age， years of education， MADRS total score， SDS total score， and CGI-SI score. Multiple linear regression was used to explore the influencing factors of the differences between subjective and objective cognitive function. ResultsThere was a statistically significant difference in the total PDQ-D scores and the difference of subjective and objective cognitive function （D value） between depressive patients with and without medication （t=-4.228， -2.392， P<0.05 or 0.01）. There was no statistically significant correlation in subjective and objective cognitive function in patients with depressive disorder （r=-0.148， P>0.05）. Negative correlations can be observed between the PDQ-D total score and age or years of education （r=-0.333， -0.369， P<0.01）. The PDQ-D total score was positively correlated with MADRS total score， SDS total score and CGI-SI score （r=0.487， 0.637， 0.434， P<0.01）. D value was negatively correlated with age and years of education （r=-0.411， -0.362， P<0.01）， while positively correlated with MADRS total score， SDS total score and CGI-SI score （r=0.259， 0.468， 0.299， P<0.05 or 0.01）. Age （β=-0.328， P<0.01） and SDS total score （β=0.409， P<0.01） were two predictive factors for D value. ConclusionThe difference between subjective and objective cognitive function among patients with depressive disorder is related to several factors including age， years of education， severity of symptoms and impairment of social function. ［Funded by Surface Project of National Natural Science Foundation of China （number， 62173069）； Technological Innovation 2030-Major Project of "Brain Science and Brain-Like Research" （number， 2022ZD0211700）； Key R&D Support Program and Major Application Demonstration Project of Chengdu Science and Technology Bureau （number， 2022-YF09-00023-SN）］

ObjectiveTo introduce the basic design， development plan and objectives of a population-based birth cohort in Shanghai， and further present the main data and baseline characteristics of enrolled participants in the cohort， and to provide key information for reproductive health-related studies. MethodsThe Shanghai population-based birth cohort initiated on January 1， 2005， included newborns born in Shanghai every year and their parents， and collected information on reproductive health， reproductive treatment， birth characteristics， growth and development status， as well as the incidence， treatment and death of diseases by employing data linkage technology and investigations. This formed a birth cohort spanning the entire life cycle. ResultsAs of October 2022， a total of 2 978 538 newborns and their parents were included in the cohort. Among them， 2 905 135 （97.54%） were naturally conceived （NC）， and 73 403 （2.46%） were born through assisted reproductive technologies （ART）. The average age of parents was （32.56±4.12） years old for females and （34.62±5.34） years old for males in the ART group， which was higher than （28.02±4.71） years and （30.07±5.54） years for parents in the NC group. Among parents， females and males aged 30 and above accounted for 77.12% and 85.08%， respectively， which were higher than that of parents （35.28% for females and 49.66% for males） in the NC group. Furthermore， the percentage of parents with a college degree or above in the ART group was 73.23% for females and 73.66% for males， which were higher than those in the NC group （49.98% and 50.91%， respectively）. The multiple births rate in the ART group was 33.81%， which was higher than that in the NC group （1.88%）. The incidence of premature birth and low birth weight in the ART group were 24.47% and 19.08%， respectively， which was higher than that in the NC group （5.47% and 3.73%）. ConclusionThe comprehensive collection of reproductive health-related information in the birth cohort in Shanghai can provide essential resources to determine the influence of genetics， environment， reproductive treatment and other related factors on the health of offspring after birth.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.

Objective:To explore the association between occupational noise perception and cardiovascular disease (CVD), depression symptoms, as well as their comorbidity in occupational population and provide evidence for the prevention and control of physical and mental illnesses.Methods:A cross-sectional survey design was adopted, based on baseline data in population in 28 prefectures in Sichuan Province and Guizhou Province, and 33 districts (counties) in Chongqing municipality from Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd. during October to December 2021. A questionnaire survey was conducted to collect information about noise perception, depressive symptoms, and the history of CVD. Latent profile analysis model was used to determine identify noise perception type, and multinomial logistic regression analysis was conducted to explore the relationship between different occupational noise perception types and CVD, depression symptoms and their comorbidity.Results:A total of 30 509 participants were included, the mean age was (36.6±10.5) years, and men accounted for 82.0%. The direct perception of occupational noise, psychological effects and hearing/sleep impact of occupational noise increased the risk for CVD, depressive symptoms, and their comorbidity. By using latent profile analysis, occupational noise perception was classified into four levels: low, medium, high, and very high. As the level of noise perception increased, the association with CVD, depressive symptoms, and their comorbidity increased. In fact, very high level occupational noise perception were found to increase the risk for CVD, depressive symptoms, and their comorbidity by 2.14 (95% CI: 1.73-2.65) times, 8.80 (95% CI: 7.91-9.78) times, and 17.02 (95% CI: 12.78-22.66) times respectively compared with low-level occupational noise perception. Conclusions:Different types of occupational noise perception are associated with CVD and depression symptom, especially in the form of CVD complicated with depression symptom. Furthermore, the intensity of occupational noise in the work environment should be reduced to lower the risk for physical and mental health.

Background::Breast cancer (BC) risk-stratification tools for Asian women that are highly accurate and can provide improved interpretation ability are lacking. We aimed to develop risk-stratification models to predict long- and short-term BC risk among Chinese women and to simultaneously rank potential non-experimental risk factors.Methods::The Breast Cancer Cohort Study in Chinese Women, a large ongoing prospective dynamic cohort study, includes 122,058 women aged 25-70 years old from the eastern part of China. We developed multiple machine-learning risk prediction models using parametric models (penalized logistic regression, bootstrap, and ensemble learning), which were the short-term ensemble penalized logistic regression (EPLR) risk prediction model and the ensemble penalized long-term (EPLT) risk prediction model to estimate BC risk. The models were assessed based on calibration and discrimination, and following this assessment, they were externally validated in new study participants from 2017 to 2020.Results::The AUC values of the short-term EPLR risk prediction model were 0.800 for the internal validation and 0.751 for the external validation set. For the long-term EPLT risk prediction model, the area under the receiver operating characteristic curve was 0.692 and 0.760 in internal and external validations, respectively. The net reclassification improvement index of the EPLT relative to the Gail and the Han Chinese Breast Cancer Prediction Model (HCBCP) models for external validation was 0.193 and 0.233, respectively, indicating that the EPLT model has higher classification accuracy.Conclusions::We developed the EPLR and EPLT models to screen populations with a high risk of developing BC. These can serve as useful tools to aid in risk-stratified screening and BC prevention.

Objective To investigate the biocompatibility of new gadolinium-doped hydroxyapatite(Gd-HA)composite scaffolds and to explore their feasibility as cell culture materials and bone tissue engineering scaffolds.Methods The Gd-HA composite scaffolds were chemically synthesized and placed under the electron microscope for observation.The experiment was divided into three groups,the HA group,the Gd-HA group,and the control group.Rabbit adipose-derived mesenchymal stem cells(ADSCs)were isolated,cultured and characterized,and the Gd-HA composite scaffold extract was added to the ADSCs in vitro culture system.Cell survival and cytotoxicity were assessed by live-dead cell staining,cell proliferation ability within the scaffolds was assessed by CCK-8 assay,and the scaffolds were assessed by alizarin red staining for cell osteogenic differentiation.The toxic reactions of the scaffold materials were observed by skin irritation test,systemic acute toxicity test and muscle tissue and liver and kidney pathology at the site of intramuscular implantation of the scaffolds.Results The Gd-HA composite scaffold showed irregular void structure under electron microscope.Cell morphology observation showed that ADSCs grew adherently to the wall and were long shuttle-shaped.The positivity rate of CD29 was 96.94％,CD44 was 97.90％,CD45 was 0.10％,and CD34 was 0.46％,which was obtained using flow cytometry.Live-dead cell staining showed that the amount of live cells in the Gd-HA group was significantly better than that in the hydroxyapatite(HA)group after 5 days of co-culture.CCK-8 assay showed no significant difference in cell proliferation within 0-3 days.After 3 days,the Gd-HA group was significantly better than the HA group and the control group(P＜0.05).Calcium nodule deposition after alizarin red staining was significantly better in the Gd-HA group than in the HA and control groups,showing a deeper red color.No skin irritation was observed in gross and skin tissue HE observations after the contact of the extract with the skin.The general condition of the experimental groups was good after the infusion of the extract into the abdominal cavity,and the body mass tended to increase steadily(P＞0.05).HE staining showed that inflammatory reaction at the interface between the material and muscle tissue of the stent intramuscular implantation site in Gd-HA group was significantly higher than that of the control group,and the inflammatory cell infiltration was gradually reduced with the prolongation of implantation time.At the 8th weeks the morphology of the tissue around the material was close to normal muscle tissue,and no pathological changes were observed in the HE staining of liver and kidney at the 12th week.Conclusion Gd-HA composite scaffolds exhibit good biocompatibility and facilitate cell proliferation and osteogenic differentiation,and they are expected to serve as good carriers for stem cell transplantation in tissue engineering.

Objective To investigate the characteristics of epitope distribution on HLA class Ⅰ antigen in the regular platelet donors from Nanjing area and establish the HLA epitope database for regular platelet donors.Methods High-resolution HLA typing was per-formed using Sanger method for the blood samples from 649 regular platelet donors in Nanjing area.The polymorphism of HLA antigen epitopes corresponding to the high-resolution HLA typing results was analyzed using the HLA Eplet Registry website.The frequencies of allele frequencies,HLA haplotype,and HLA antigen epitope were calculated by using the direct counting method.Results Among the 649 regular platelet donors,38 HLA-A alleles were detected,corresponding to 36 HLA-A epitopes,and the higher frequencies were 79GT,144K and 138MI.Seventy-three HLA-B alleles were detected corresponding to 35 HLA-B epitopes,and the higher frequencies were 131S,69TNT,and 80N.Sixty-four HLA class Ⅰ antigen epitopes were detected,in which the higher frequencies were 79GT,131S,and 144K.Conclusions The distribution of HLA antigen epitopes in the regular platelet donors of Nanjing area exhibited u-nique polymorphic characteristics.The epitope matching strategies should be established based on the distribution characteristics of HLA antigen epitopes,which may expand the range of available donors and reduce the incidence of platelet transfusion refractoriness.