Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

OBJECTIVE: Serological and molecular biological analysis of a B(A) subtype family was carried out to explore the underlying mechanism of B(A) subtype and clinical safe blood transfusion strategies. METHODS: The ABO blood type of the proband and her four family members were identified by serological methods, and serological experiments such as anti-H, anti-A1 and absorption-elution tests was added. In addition, the exons 6 and 7 of the ABO gene were sequenced by PCR-SSP (polymerase chain reaction - sequence specific primer). RESULTS: The serological results showed that the agglutination intensity of the proband, her mother and her maternal grandmother was imbalanced during forward typing, showing weak A and strong B antigens, and there were strong H antigens and their intensity were higher than that of normal B type. The results of reverse typing indicated the presence of weak anti-A1 antibodies, and human anti-A was positive in the absorption-elution test. Genetic sequencing revealed a characteristic mutation of c.700 C>G in all three individuals. The sequencing results showed that the proband was B(A)02/B01, her mother was B(A)02/O02, and her maternal grandmother was B(A)02/O01 . According to the compatibility principle, 1.5 units of type O washed red blood cells were transfused intraoperatively, resulting in no adverse reactions. CONCLUSION The c.700 C > G mutation on exon 7 is the molecular basis for the formation of B(A)02, and pedigree analysis shows that the B(A)02 allele was inherited from the proband's maternal grandmother to the proband's mother and then to the proband, showing a stable cis-inheritance pattern rather than a spontaneous mutation. For patients with B(A)02 subtype, type O washed red blood cells and type AB plasma can be transfused according to the principle of compatibility.
Humans ; ABO Blood-Group System/genetics* ; Female ; Blood Transfusion ; Blood Grouping and Crossmatching ; Pedigree ; Male ; Mutation ; Adult ; Exons

BACKGROUND: Medical informatics accumulated vast amounts of data for clinical diagnosis and treatment. However, limited access to follow-up data and the difficulty in integrating data across diverse platforms continue to pose significant barriers to clinical research progress. In response, our research team has embarked on the development of a specialized clinical research database for cardiology, thereby establishing a comprehensive digital platform that facilitates both clinical decision-making and research endeavors. METHODS: The database incorporated actual clinical data from patients who received treatment at the Cardiovascular Medicine Department of Chinese PLA General Hospital from 2012 to 2021. It included comprehensive data on patients' basic information, medical history, non-invasive imaging studies, laboratory test results, as well as peri-procedural information related to interventional surgeries, extracted from the Hospital Information System. Additionally, an innovative artificial intelligence (AI)-powered interactive follow-up system had been developed, ensuring that nearly all myocardial infarction patients received at least one post-discharge follow-up, thereby achieving comprehensive data management throughout the entire care continuum for high-risk patients. RESULTS: This database integrates extensive cross-sectional and longitudinal patient data, with a focus on higher-risk acute coronary syndrome patients. It achieves the integration of structured and unstructured clinical data, while innovatively incorporating AI and automatic speech recognition technologies to enhance data integration and workflow efficiency. It creates a comprehensive patient view, thereby improving diagnostic and follow-up quality, and provides high-quality data to support clinical research. Despite limitations in unstructured data standardization and biological sample integrity, the database's development is accompanied by ongoing optimization efforts. CONCLUSION The cardiovascular specialty clinical database is a comprehensive digital archive integrating clinical treatment and research, which facilitates the digital and intelligent transformation of clinical diagnosis and treatment processes. It supports clinical decision-making and offers data support and potential research directions for the specialized management of cardiovascular diseases.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Heart failure （HF）， as the terminal stage of most cardiovascular diseases， manifests with primary symptoms including dyspnea， fatigue， edema， and palpitations. With recurrent episodes and a protracted clinical course， HF imposes a substantial global disease burden. PANoptosis represents a distinctive form of programmed cell death （PCD） that integrates features of pyroptosis， apoptosis， and necroptosis， yet cannot be fully attributed to any single pathway among these three PCD modalities. Recent studies demonstrate significant dysregulation of PANoptosis-related genes during HF progression， positioning PANoptosis as both an emerging mechanism mediating HF pathogenesis and a novel therapeutic target. In recent years， traditional Chinese medicine （TCM） has gained substantial recognition for its therapeutic potential in HF management， offering advantages such as flexible compatibility， multi-target effects， and minimal adverse reactions. Astragali Radix， a representative Qi-invigorating and blood-activating herbal medicine， has demonstrated remarkable clinical efficacy in the treatment for various HF subtypes. Research reveals that its major bioactive components—including astragaloside Ⅳ， polysaccharide， quercetin， and calycosin—exhibit significant associations with the regulation of apoptosis， pyroptosis， and necroptosis pathways. This review systematically explores the therapeutic feasibility of Astragali Radix in the prevention and treatment of HF through the lens of PANoptosis mechanisms. By synthesizing recent advances in the mechanisms of Astragali Radix-derived bioactive compounds and Astragali Radix-containing compound prescriptions in modulating PANoptosis， this paper aim to provide critical insights for advancing the diagnosis and therapeutic strategies of HF.

Heart failure （HF）， as the terminal stage of most cardiovascular diseases， manifests with primary symptoms including dyspnea， fatigue， edema， and palpitations. With recurrent episodes and a protracted clinical course， HF imposes a substantial global disease burden. PANoptosis represents a distinctive form of programmed cell death （PCD） that integrates features of pyroptosis， apoptosis， and necroptosis， yet cannot be fully attributed to any single pathway among these three PCD modalities. Recent studies demonstrate significant dysregulation of PANoptosis-related genes during HF progression， positioning PANoptosis as both an emerging mechanism mediating HF pathogenesis and a novel therapeutic target. In recent years， traditional Chinese medicine （TCM） has gained substantial recognition for its therapeutic potential in HF management， offering advantages such as flexible compatibility， multi-target effects， and minimal adverse reactions. Astragali Radix， a representative Qi-invigorating and blood-activating herbal medicine， has demonstrated remarkable clinical efficacy in the treatment for various HF subtypes. Research reveals that its major bioactive components—including astragaloside Ⅳ， polysaccharide， quercetin， and calycosin—exhibit significant associations with the regulation of apoptosis， pyroptosis， and necroptosis pathways. This review systematically explores the therapeutic feasibility of Astragali Radix in the prevention and treatment of HF through the lens of PANoptosis mechanisms. By synthesizing recent advances in the mechanisms of Astragali Radix-derived bioactive compounds and Astragali Radix-containing compound prescriptions in modulating PANoptosis， this paper aim to provide critical insights for advancing the diagnosis and therapeutic strategies of HF.

Objective: To investigate the prevalence of human T-lymphotropic virus (HTLV) infection among blood donors in Hunan Province from 2022 to 2024. Methods: A total of 1 830 342 blood donors from 14 prefecture-level blood centers in Hunan Province over the past three years were screened for anti-HTLV-Ⅰ/Ⅱ using enzyme-linked immunosorbent assay (ELISA). Initially reactive samples were further tested with Line Immunoassay (LIA )/MP-Western blot and RT-PCR nucleic acid test for confirmation. Blood donors confirmed positive for HTLV were tracked and followed up. Results: From 2022 to 2024, the initial ELISA reactive rate for anti-HTLV-I/II among blood donors in Hunan Province was 1.36 per 10 000 (249/1 830 342). The confirmed positive rate was 0.20 per 10 000 (37/1 830 342), accounting for 14.86% of the initially reactive donors. The follow-up success rate for confirmed HTLV-positive blood donors was only 18.92%, while that for HTLV-indeterminate donors was 54.17%. Conclusion: The confirmed HTLV infection rates in Yueyang, Loudi, Shaoyang, Yiyang, and Zhuzhou cities were higher than the provincial (0.20 per 10 000). Chenzhou, Yongzhou, Zhangjiajie, and Xiangxi were identified as low prevalence areas, with an infection rate of 0. The overall follow-up success rate was low, indicating significant difficulties and bottlenecks in follow-up work. The comprehensive screening for HTLV and follow-up studies in Hunan provide valuable data to further improve blood safety testing strategies and risk warning mechanisms.

ObjectiveTo investigate the relationship between the non-fasting triglyceride and glucose （TyG） index and hyperglycemia in pregnancy during the third trimester in high altitudes. MethodsThis study selected clinical and laboratory data of 774 Tibetan singleton pregnant women who delivered at Chaya People's Hospital of Qamdo city in Xizang autonomous region， from January 2023 to April 2025. The non-fasting TyG index was calculated from non-fasting triglyceride （TG） and random plasma glucose （PG）. Based on the tertiles of the non-fasting TyG index values， the individuals were split into three groups （corresponding to non-fasting TyG index of 8.89 and 9.21， respectively）. The baseline clinical characteristics， lipid levels and the occurrence of developing hyperglycemia in pregnancy were compared among the three groups. Statistical analyses were performed using ANOVA， Kruskal-Wallis H test， Chi-square test， or Fisher exact test and the relationship between the non-fasting TyG index and hyperglycemia in pregnancy were examined using multivariate logistic regression models and curve fitting. ResultsA total of 774 Tibetan singleton pregnant women were included， with a average age of 27.3 ± 6.1 years， a pre-delivery body mass index （Pre-BMI） of （25.2±2.3）kg/m² ， a proportion of 26.7% （207/774） primigravid women， the mean non-fasting TyG index was 9.1 ± 0.4。Thirty pregnant women were diagnosed with hyperglycemia in pregnancy， with a detection rate of 3.9% （30/774）. Statistically significant differences in serum total cholesterol （TC）， TG， low-density lipoprotein cholesterol （LDL-C） and high-density lipoprotein cholesterol （HDL-C） levels were identified when comparing different non-fasting TyG groups （all P values <0.05）. Subsequent trend test analysis indicated that the levels of TC， TG， LDL-C， and PG gradually increased with elevated the non-fasting TyG index （ F_{trend TC}=95.61， P<0.001； F_{trend TG}=1 051.91， P<0.001； F_{trend LDL-C} = 97.20， P < 0.001； F_{trend TG}=195.20； P<0.001）. After adjustment for maternal age， pre-delivery BMI， altitude， TC， LDL-C， and HDL-C， multivariate Logistic regression models revealed independent positive associations between non-fasting TyG index and hyperglycemia in pregnancy （Model 1： OR=2.72， 95% CI： 1.13-6.53， P=0.026； Model 2： OR=2.56， 95% CI： 1.01-6.50， P=0.048； Model 3： OR=2.72， 95% CI： 1.06-6.97， P=0.037； Model 4： OR=4.02， 95% CI： 1.42-11.40， P=0.009） and the incident of hyperglycemia in pregnancy showed an increasing tendency as increasing with the non-fasting TyG index， however， this association did not statistical significance （P _trend >0.05）. Curve fitting by restricted cubic splines （RCS） were used to assess linearity between non-fasting TyG and hyperglycemia in pregnancy， and there was a linear dose-response relationship between non-fasting TyG and hyperglycemia in pregnancy （P _{for non-linear} = 0.515）. ConclusionNon-fasting TyG index in the third trimester is a risk factor for hyperglycemia in pregnancy among the Tibetan singleton pregnant women at high altitudes and there was a possible linear dose-response relationship between the non-fasting TyG index and hyperglycemia in pregnancy.

OBJECTIVE To construct ensemble learning models for predicting high-use days of budesonide based on meteorological factors， thereby providing reference for hospital pharmacy management. METHODS Meteorological data for 2024 and outpatient budesonide usage data from the jurisdiction of Sanming Hospital of Integrated Traditional Chinese and Western Medicine were collected. High-use days were defined as the 75th percentile of outpatient budesonide usage， and a corresponding dataset was established. The prediction task was formulated as a classification problem， and three ensemble learning models were developed： Random Forest， Extreme Gradient Boosting （XGBoost）， and Histogram-based Gradient Boosting Classifier. Model performance was evaluated using accuracy， precision， recall， F1-score， and log-loss. Model interpretability was analyzed using Shapley Additive Explanations （SHAP）. RESULTS The Histogram-based Gradient Boosting Classifier achieved the best performance （accuracy＝0.75， F1-score＝0.48）， followed by XGBoost （accuracy＝0.74， F1-score＝0.43） and Random Forest （accuracy＝0.72， F1-score＝0.22）. SHAP results suggested that the prediction results of the last two models have the highest correction. CONCLUSIONS Ensemble learning models can effectively predict high-use days of budesonide， with the Histogram- based Gradient Boosting Classifier demonstrating the best predictive performance. Low temperature， high humidity， and low atmospheric pressure show significant positive impacts on the prediction of daily budesonide usage.