OBJECTIVE To systematically evaluate the effects of supplementation with different doses of vitamin D on maternal and infant outcomes in vitamin D-deficient pregnant women. METHODS Related literature on the effects of supplementing different doses of vitamin D on maternal and infant outcomes was searched in databases including CNKI， Wanfang Data， VIP， PubMed， Medline， the Cochrane Library， Embase from their inception to June 30， 2025. The risk of bias assessment tool from the Cochrane Handbook 5.1 was used to evaluate the quality of included literature. Meta-analysis of outcome indicators was performed by using RevMan 5.4 software. RESULTS A total of 15 studies were included， involving 4 664 patients [2 129 in the experimental group （daily dose ＞2 000 IU）， 2 058 in control group 1 （daily dose ≤1 000 IU） and 477 in control group 2 （daily dose ＞1 000-≤2 000 IU） ] . Meta-analysis results showed that the incidence of preeclampsia （PE） [OR＝0.71， 95%CI （0.53， 0.96）， P ＝0.03 ] ， gestational diabetes mellitus （GDM） [OR＝0.60， 95%CI （0.43， 0.84）， P ＝0.003 ] ， low birth weight of newborn [OR＝0.72， 95%CI （0.53， 0.97）， P ＝0.03 ] and macrosomia [OR＝0.53， 95%CI （0.29， 0.98）， P ＝0.04 ] in the experimental group were significant lower than control group 1； but there was no significant difference in the incidence of premature delivery [OR＝0.86， 95%CI （0.65， 1.13）， P ＝0.28 ] ， cesarean delivery [OR＝0.92， 95%CI （0.74， 1.15）， P ＝0.48 ] or stillbirth rate [OR＝0.77， 95%CI （0.48， 1.24）， P ＝0.29 ] . The incidence of low birth weight of ne wborn [OR＝0.64， 95%CI （0.41， 0.98）， P ＝0.04 ] in the experimental group was significant lower than control group 2； but there was no significant difference in the incidence of PE [OR＝0.61， 95%CI （0.25， 1.49）， P ＝0.28 ] ， the incidence of GDM [OR＝0.73， 95%CI （0.42， 1.24）， P ＝0.24 ] ， premature delivery rate [OR＝0.90， 95%CI （0.59， 1.39）， P ＝0.63 ] ， cesarean delivery rate [OR＝0.92， 95%CI （0.64， 1.33）， P ＝0.66 ] ， or stillbirth rate [OR＝0.68， 95%CI （0.24， 1.94）， P ＝0.48 ] . CONCLUSIONS Different doses of vitamin D supplementation in early pregnancy have a significant impact on maternal and infant pregnancy outcomes in vitamin D-deficient pregnant women； daily doses ＞2 000 IU have significant advantages in reducing the incidence of PE and GDM and improving the outcome of premature delivery.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

Objective To analyze the predictive value of different obesity indicators on acute cerebral infarction in patients with transient ischemic attack (TIA). Methods A total of 310 patients with TIA admitted to Tangdu Hospital of Air Force Medical University from March 2022 to September 2025 were selected and classified into non-event group (276 cases) and cerebral infarction group (34 cases) based on acute cerebral infarction within 90 days. The basic data and obesity-related indicators [body mass index (BMI), waist-to-hip ratio, body adiposity index (BAI), conicity index (C-index) and a body shape index (ABSI were compared. Multivariate logistic regression analysis was utilized to screen the independent influencing factors. Receiver operating characteristic (ROC) curve was drawn to analyze the predictive efficiency. Results The age, proportions of concurrent hypertension and concurrent diabetes mellitus, ABCD2 score, waist-to-hip ratio, ABSI, C-index, BMI and BAI in the cerebral infarction group were older or higher than those in the non-event group, and the symptoms duration was longer (P<0.05). The above indicators were all related factors for acute cerebral infarction in patients with TIA within 90 days (P<0.05), and ABSI and ABCD² score were independent influencing factors (P<0.05). The prediction model was manifested as Logit (P)=− 4.205 + 0.482 × ABCD² score + 1.120 × ABSI × 100. ABSI and ABCD2 score had predictive value on the occurrence of acute cerebral infarction (P<0.05), and the predictive efficiency of combined model was higher than that of single indicator (P<0.05). Conclusion Among different obesity indicators, ABSI has the highest value on predicting recent acute cerebral infarction in TIA. The prediction model based on ABSI and ABCD2 score exhibits the best predictive efficiency.

OBJECTIVE To investigate the clinical characteristics of euglycemic diabetic ketoacidosis （euDKA） induced by empagliflozin， and provide references for safe medication. METHODS Case reports of euDKA induced by empagliflozin were retrieved and analyzed from PubMed， Web of Science， CNKI， and Wanfang Data. The Naranjo’s scale was adopted to assess the causal relationship between empagliflozin and euDKA. RESULTS A total of 29 patients were enrolled， including 16 males and 13 females，with a median age of 58 years. All patients were diagnosed with type 2 diabetes mellitus； 22 patients had at least one comorbidity. The median time to euDKA onset was 60 days after administration， and 7 cases occurred within 2 weeks of treatment. Perioperative periods，fasting，and low-carbohydrate or ketogenic diets were the main predisposing factors. Common presentations included nausea，vomiting， fatigue， tachypnea，and tachycardia. The causal relationship between empagliflozin and euDKA was assessed as “probable” in all cases. According to adverse reaction severity grading， 13 cases were grade 3 （severe） and 16 cases were grade 4 （life-threatening）. All patients discontinued empagliflozin and recovered after corresponding treatment. CONCLUSIONS euDKA is a serious adverse reaction to empagliflozin， which mostly occurs early in treatment. Perioperative periods， fasting， and ketogenic diets are prone to induce euDKA. Elderly patients and those with comorbidities are at higher risk. Risk assessment should be conducted before clinical administration； blood ketones and acid-base monitoring should be strengthened in the early medication period； withhold the drug before elective surgery， avoid prolonged fasting；upon diagnosis， discontinue empagliflozin and initiate intravenous insulin， provide fluid resuscitation promptly， and use other treatments to improve patient prognosis.

ObjectiveTo investigate the protective effect of magnolol ester derivative YW against cisplatin （Cis）-induced acute kidney injury （AKI） and to explore its effect and preliminary mechanisms on Cis-induced AKI. MethodsThe research group designed and synthesized the magnolol ester derivative YW using magnolol as the parent core. Molecular docking was employed to predict the binding interaction between YW and lysine acetyltransferase 7 （KAT7）. A Cis-induced AKI model was established in C57BL/6J mice. Mice were divided into the normal control group， model group， YW low/medium/high dose groups （17.5， 35， 70 mg/kg）， and the positive control amifostine group. Renal function was assessed by measuring serum creatinine （Scr） and blood urea nitrogen （BUN） levels. Pathological changes were evaluated via HE staining and scoring of kidney tissues. Protein expression levels of kidney injury molecule 1 （KIM-1）， lysine acetyltransferase 7 （KAT7）， and cyclin-dependent kinase inhibitor 1A （p21） in kidney tissues were detected by Western blot （WB）. HK-2 cells were treated with different concentrations of YW； cell viability was measured by CCK-8 assay. WB was used to detect the expression levels of the renal injury marker KIM-1， KAT7， and its downstream protein p21. Cellular senescence was assessed by senescence-associated β-galactosidase （SA-β-Gal） staining. ResultsYW could stably bind to KAT7. In vivo experiments showed that， compared with the model group， all YW dose groups， especially the medium and high doses， significantly reduced the elevated levels of Scr and BUN in AKI mice （P<0.001） and effectively ameliorated renal histopathological damage. YW significantly downregulated the protein expression levels of KIM-1， KAT7， and p21 in kidney tissues （P<0.05）. Concentrations of YW≤10 μmol/L had no significant effect on HK-2 cell viability. YW inhibited the Cis-induced decline in HK-2 cell viability （P<0.05）， suppressed the Cis-induced upregulation of KIM-1， KAT7， and p21 proteins （P<0.05）， and significantly decreased the percentage of SA-β-Gal-positive cells （P<0.01）. ConclusionYW suppresses the expression of KAT7 and p21 proteins and inhibits the decline in HK-2 cell viability in cisplatin-induced AKI， significantly mitigates HK-2 cell senescence， and improves renal function， providing preliminary experimental evidence for developing AKI treatment strategies based on structural optimization of natural products.

ObjectiveTo construct and validate a risk assessment model for post-transplant diabetes mellitus （PTDM） using multiple machine learning algorithms， and to realize the early identification of PTDM. MethodsA retrospective analysis was performed for the clinical data of the patients who underwent allogeneic liver transplantation in The First Hospital of Shanxi Medical University from April 1， 2020 to December 31， 2024， and they were randomly divided into a training set and a validation set at a ratio of 7∶3. The LASSO regression analysis combined with 5-fold cross-validation was used for feature selection. Seven machine learning models were developed in the training set， i.e.， logistic regression （LR）， decision tree （DT）， Naive Bayes （NB）， random forest （RF）， K-nearest neighbor （KNN）， extreme gradient boosting （XGBoost）， and adaptive boosting （AdaBoost）. In the validation set， various methods were used to assess the predictive performance of each model， such as accuracy， precision， recall rate， specificity， F1 score， area under the receiver operating characteristic curve （AUROC）， and area under the precision-recall curve （AUPRC）. The Brier score and decision curve analysis were used to assess the calibration and clinical practicability of the models， and the SHAP method was used to analyze feature importance. The independent-samples t test or the Wilcoxon rank-sum test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. ResultsA total of 135 liver transplant recipients were enrolled， among whom 26 developed PTDM， and there were 94 patients in the training set and 41 in the validation set. Feature extraction and screening identified 7 key features of sex， overweight or obesity， anhepatic phase， time of operation， length of hospital stay， early postoperative hypomagnesemia， and impaired fasting glucose （IFG）. In the validation set， the XGBoost model showed the best predictive performance， with an AUROC of 0.907 （95% confidence interval ［CI］： 0.807 — 0.989）， an AUPRC of 0.649 （95%CI： 0.339 — 0.955）， an accuracy of 0.878， a precision of 0.667， a recall rate of 0.750， an F1-score of 0.706， a specificity of 0.909， and a Brier score of 0.104. The decision curve analysis showed that when the threshold probability was below 0.667， application of the XGBoost model in clinical decision-making provided relatively high net benefit. The SHAP analysis showed that the length of hospital stay ranked first in terms of feature importance， followed by time of operation， overweight or obesity， sex， IFG， anhepatic phase， and early postoperative hypomagnesemia. ConclusionThe risk assessment model for PTDM in liver transplant recipients based on XGBoost algorithm has excellent performance and can effectively identify high-risk individuals； however， multicenter large-sample data are needed for further validation.

With the increasing prevalence of overweight and obesity among children and adolescents in China, pediatric metabolic syndrome has emerged as a significant public health challenge. The Developmental Origins of Health and Disease (DOHaD) theory underscores the critical influence of early environmental factors on lifelong metabolic health. Consequently, maternal nutritional status and physical activity during pregnancy have become key modifiable factors that have attracted considerable attention in recent years. Research indicates exposure to a maternal high-fat diet (HFD) during pregnancy has long-term effects on offspring health, which may be transmitted through placental transit disorder, inflammation, and oxidative stress. Similarly, a high-protein diet (HPD) during pregnancy exhibits a dose- and time-dependent biphasic effect: excessive intake may lead to fetal growth restriction and an increased risk of preterm birth, whereas moderate supplementation may instead reduce the susceptibility of offspring to obesity. Interestingly, caloric restriction (CR) during pregnancy presents a double-edged sword: while it may impair the development of metabolic organs in offspring, moderate CR in metabolically compromised mothers can ameliorate maternal metabolic dysfunction and reprogram oocyte DNA methylation, significantly lowering the risk of metabolic disorders in offspring. Notably, metabolic abnormalities induced by a low-protein diet (LPD) during pregnancy demonstrate lifecycle-accumulative effects and transgenerational inheritance, with offspring exhibiting obesity phenotypes during weaning, insulin resistance in adulthood, and hepatic decompensation in old age, mediated through oocyte epigenetic reprogramming. Additionally, maintaining an optimal micronutrient balance is crucial for the metabolic homeostasis of offspring, as both deficiency and excess can lead to detrimental outcomes. Maternal exercise has been established as a safe and effective non-pharmacological intervention that confers multigenerational metabolic benefits through diverse biological pathways. Maternal metabolic dysregulation represents a critical determinant of offspring metabolic disorders. Regular exercise during gestation exerts protective effects by attenuating maternal systemic inflammation and reducing the incidence of pregnancy-related complications, thereby effectively mitigating fetal overgrowth and metabolic dysfunction. This dual benefit for both mother and offspring underscores the pivotal role of gestational physical activity in promoting long-term metabolic health. The placenta, serving as the exclusive interface for maternal-fetal communication, mediates exercise-induced metabolic programming through enhanced secretion of key regulatory factors (including SOD3, Apelin, ADPN, and Irisin) and promotes the development of vascular networks, collectively optimizing nutrient transport efficiency. The intrauterine period represents a crucial window for epigenetic reprogramming, during which maternal exercise modulates DNA methylation patterns of critical metabolic genes (e.g., Ppargc-1α, Prdm16, Klf4, and Slc23a2) in offspring, thereby enhancing their capacity to resist metabolic disorders. Notably, the regulatory effects of maternal exercise extend beyond the gestational period. Postnatally, exercise-induced modifications in the bioactive components of breast milk and gut microbiota composition contribute to the sustained maintenance of metabolic homeostasis in offspring, establishing a continuum of metabolic protection from prenatal to postnatal stages. This review explores the potential of maternal combined nutrition-exercise interventions, suggesting that such strategies may synergistically enhance transgenerational health benefits through interactions within the metabolic-epigenetic network, thereby outperforming single interventions. Additionally, it examines current research limitations, including controversies surrounding transgenerational mechanisms, sex-specific responses, and undefined dynamic thresholds, while providing directions for future investigations. These findings pave the way for a theoretical foundation for early-life health interventions, potentially offering a more effective strategy for combatting intergenerational metabolic disorders.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

Objective : To investigate the protective effect of total glucosides of paeony ( TGP) on dexamethasone(DEX) ⁃induced liver injury in rats. Methods: Thirty SD rats were randomly divided into normal ( N) , DEX ,DEX + TGP (50 mg/kg) , DEX + TGP ( 100 mg/kg) , and DEX + TGP (200 mg/kg) groups , with 6 rats in each group. A rat model of liver injury was established by intraperitoneal injection of DEX ( 17. 5 mg/kg) . Serum levels of alanine aminotransferase ( ALT) , aspartate aminotransferase ( AST) , and alkaline phosphatase ( ALP) were measured , and the liver⁃to⁃body weight ratio was calculated. HE staining was performed to observe histopathological changes in the liver. The contents of malondialdehyde ( MDA) , superoxide dismutase ( SOD) , and glutathione (GSH) in liver tissues were determined. Western blot analysis was conducted to detect the expression levels of NADPH oxidase 4 ( NOX4 ) and endoplasmic reticulum stress⁃related proteins : glucose regulatory protein 94 homologous protein (CHOP) expression level in liver tissues. Results: Compared with the normal group , the DEX group exhibited significantly elevated serum levels of ALT , AST , ALP and liver⁃to⁃body weight ratio ( t = 14. 96 ,ing, degeneration , and necrosis ( t = 15. 49 , P < 0. 01) . Compared with the DEX group , there was no significant change in liver function biochemical indexes and liver histopathology in the TGP (50 mg/kg) treatment group. TGP treatment at 100 mg/kg and 200 mg/kg significantly attenuated these effects : both doses reduced ALT , AST , ALP and liver⁃to⁃body weight ratio( t = 3. 30 , 4. 13 , 7. 45 , 2. 97 , P < 0. 05 ; t = 8. 92 , 6. 45 , 8. 65 , 7. 47 , P < 0. 01) ,vealed that DEX administration significantly increased hepatic MDA levels ( t = 7. 06 , P < 0. 01) and NOX4 ex⁃pression ( t = 4. 23 , P < 0. 01) , whereas SOD activity ( t = 7. 78 , P < 0. 01) and GSH content ( t = 7. 92 , P <0. 01) were markedly suppressed. There was no significant change in the TGP (50 mg/kg) treatment group , TGP intervention at 100 mg/kg and 200 mg/kg effectively reversed these changes , lowering MDA and NOX4 levels( t = 3. 35 , 4. 30 , P < 0. 05 ; t = 5. 44 , 7. 44 , P < 0. 01) , while restoring SOD ( t200 mg/kg = 4. 04 , P < 0. 05) and GSH ( t = 4. 70 , P < 0. 05 ; t = 5. 50 , P < 0. 01) . Endoplasmic reticulum stress markers , including GRP94、GRP78、p- elF2α、CHOP ( t = 3. 31 , 6. 53 , 5. 18 , 3. 09 ; P < 0. 05 , 0. 01 , 0. 01 , 0. 05 ) , were significantly upregulated in the DEX group compared to the normal group. However, TGP treatment at 100 mg/kg and 200 mg/kg dose-dependent- ly suppressed the expression of GRP94、GRP78、p-elF2α、CHOP ( t = 3. 14 ,4. 95 , 3. 13 ,4. 25 , P < 0. 05 ; t = 4. 03 , 7. 48 ,4. 68 ,5. 10 ,P < 0. 01) expression levels were significantly reduced compared to the DEX group , and there was no significant change in the TGP (50 mg/kg) treatment group. Conclusion TGP exerts protective effects a- gainst DEX-induced liver injury , and its mechanism is likely mediated by suppressing hepatic oxidative stress and endoplasmic reticulum stress triggered by DEX in rats.

Gastrointestinal (GI) cancers are a leading cause of cancer morbidity and mortality worldwide. Despite advances in treatment, cancer relapse remains a significant challenge, necessitating novel therapeutic strategies. In this study, we engineered nanobody-based chimeric antigen receptor (CAR) natural killer (NK) cells targeting cadherin 17 (CDH17) for the treatment of GI tumors. In addition, to enhance the efficacy of CAR-NK cells, we also incorporated CV1, a CD47-SIRPα axis inhibitor, to evaluate the anti-tumor effect of this combination. We found that CDH17-CAR-NK cells effectively eliminated GI cancers cells in a CDH17-dependent manner. CDH17-CAR-NK cells also exhibit potent in vivo anti-tumor effects in cancer cell-derived xenograft and patient-derived xenograft mouse models. Additionally, the anti-tumor activity of CDH17-CAR-NK cells is synergistically enhanced by CD47-signal regulatory protein α (SIRPα) axis inhibitor CV1, likely through augmented macrophages activation and an increase in M1-phenotype macrophages in the tumor microenvironment. Collectively, our findings suggest that CDH17-targeting CAR-NK cells are a promising strategy for GI cancers. The combination of CDH17-CAR-NK cells with CV1 emerges as a potential combinatorial approach to overcome the limitations of CAR-NK therapy. Further investigations are warranted to speed up the clinical translation of these findings.