ObjectiveTo explore the effect of oral sodium butyrate on skeletal muscle atrophy in CT26 tumor mice through the gut microbiota-skeletal muscle axis and its potential mechanism. MethodsSixty SPF BALB/c male mice aged 8 weeks were randomly divided into a normal control group (NC, n=18) and a ABX-depleted group (ABX, n=42). The ABX mice were pretreated with a quadruple antibiotic cocktail via oral gavage (0.2 ml per administration, once daily, 6 d per week, for 2 weeks), whereas NC received an equal volume of sterile water. The quadruple antibiotic cocktail consisted of metronidazole (1 g/L), vancomycin (0.5 g/L), ampicillin (1 g/L), and gentamicin (1 g/L). Following successful pretreatment, six mice from each group were randomly selected for gut microbiota sequencing analysis and designated as the Abx group and the NC0 group, respectively. Theremaining mice in ABX were subcutaneously inoculated in the dorsum with 0.2 ml of CT26 cell suspension (at a cell density of 1×10⁷/ml). Then these mice were randomly allocated into three subgroups: a control tumor bearing model group (0_NaB, n=12), a tumor-bearing model group receiving low-dose oral sodium butyrate (L_NaB, n=12), a tumor-bearing model group receiving high-dose oral sodium butyrate (H_NaB, n=12). And mice in NC were inoculated at the same site with 0.2 ml of normal saline. The administration dose for L_NaB was 0.3 g/(kg·d), that for H_NaB was 0.5 g/(kg·d), while NC and 0_NaB were given the same volume of normal saline (0.2ml per time, once daily, 6 d per week, for 4 weeks). The general condition of mice was monitored, and forelimb grip strength gastrocnemius muscle mass and its muscle fiber cross-sectional area were measured for each group. The structural changes in gut microbiota were assessed by 16S rRNA sequencing of cecal contents. Pathological alterations in the intestinal wall were examined via HE staining. Serum and gastrocnemius muscle levels of TNF‑α, IL-6, IL-1β, and LPS were quantified using ELISA. The protein expression of ZO-1 and occludin in the small intestine, as well as proteins associated with the TLR4/MyD88/NF-κB signaling pathway in the gastrocnemius muscle, were detected by Western blot analysis. Results(1) The alpha-diversity in Abx was significantly lower than that in NC0 (P<0.01), a significant decrease of the mass and muscle fiber cross-sectional area of the gastrocnemius (P<0.01), with the majority of gut microbiota being effectively depleted. (2) Compared with NC, the subcutaneous tumors of mice in 0_NaB were prominent, a significant increase of the mass and muscle fiber cross-sectional area of the gastrocnemius, accompanied by a significant decrease in body weight at the end of the 3th and 4th week (P<0.05), and a significant weakening of the forelimb grasping strength at the 5th and 6th week (P<0.01). Compared with 0_NaB, the tumor mass of mice in L_NaB and H_NaB showed a significant decreasing trend, and the grip strength of the forelimbs significantly increased at the 5th and 6th week (P<0.05, P<0.01). (3) Compared with 0_NaB, the Shannon and Observed species indices in α diversity of L_NaB and H_NaB were significantly increased (P<0.05). At the genus level, compared with 0_NaB, L_NaB exhibited a significant decrease in the relative abundance of Parasutterella (P< 0.01), while H_NaB showed significant reductions in the relative abundances of both Escherichia-Shigella and Parasutterella (P < 0.01). (4) Compared with 0_NaB, the small intestinal tissue structure in L_NaB and H_NaB was more intact, the infiltration of inflammatory cells was significantly reduced, and the capillaries were slightly dilated. The expression levels of ZO-1 and occludin proteins in L_NaB were significantly increased (P<0.01). (5) The LPS concentration in the gastrocnemius muscle and the protein expression levels of TLR4, MyD88, p-IκBα, and p-NF‑κB p65 in L_NaB and H_NaB were significantly lower than those in 0_NaB (P<0.05). The serum TNF‑α concentration in H_NaB and TNF-α concentration in the gastrocnemius muscle of the L_NaB and H_NaB were significantly lower than those in 0_NaB (P<0.05, P<0.01, P<0.01). ConclusionOral administration of NaB can improve gut microbiota α diversity, adjusting its composition, improving intestinal mucosal barrier function, reducing the LPS-induced pro-inflammatory response, and delaying skeletal muscle atrophy. The underlying mechanism may involve down regulation of TLR4/MyD88/NF-κB signaling in skeletal muscle.

BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

ObjectiveTo develop a full-process data platform of renal rehabilitation, diagnosis and quality control information. MethodsA hierarchical architectural design was proposed, adhering to clinical pathway models and standardized data protocols. The platform comprehensively covered assessment, intervention, follow-up and quality control for maintenance hemodialysis (MHD) patients. By integrating multidisciplinary resources and standardizing rehabilitation workflows, it delivered standardized and intelligent rehabilitation services. ResultsThe platform achieved standardized and intelligent management of rehabilitation services, effectively improved the physiological function, psychological state and quality of life convenience for MHD patients, while significantly reduced the economic and care burden on patients' families and society. ConclusionThe rehabilitation service model based on a full-process data platform may provide scientific and systematic support for MHD patients.

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.

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.

BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

The recombinant human thyroid-stimulating hormone (rhTSH) can be used for differentiated thyroid cancer (DTC) preparation before ¹³¹I therapy, and follow-up. Since its approval by the American Food and Drug Administration (FDA) in 1998, rhTSH has been clinically used in European countries, the United States, and other countries for nearly 30 years. In April 2024, China’s first independently developed rhTSH agent was approved. Based on clinical experience and evidence from domestic and international studies, an expert consensus on the application of rhTSH has been developed following thorough consultations among experts. The consensus offers evidence-based recommendations to guide the appropriate use of rhTSH in clinical practice.

Objective: To analyze the characteristics of influenza-like illness (ILI) and etiological monitoring results among children aged 0 to 14 years in Heilongjiang Province, so as to provide a basis for formulating prevention and control measures against influenza in children. Methods: Data on ILI among children aged 0 to 14 years and pathogen surveillance results were collected from 18 influenza sentinel hospitals in Heilongjiang Province from 2020 to 2024 through the Chinese Influenza Surveillance Information System. The characteristics of ILI and the distribution of influenza viruses were descriptively analysed. Results: From 2020 to 2024, 215 782 cases of ILI in children aged 0 to 14 were reported in Heilongjiang Province, accounting for 1.18% of all outpatient and emergency cases. The proportion of ILI among outpatient and emergency cases from 2020 to 2024 were 0.56%, 0.52%, 0.78%, 1.63% and 1.87%, respectively, showing an upward trend (P<0.05). The higher number of ILI was reported between November and March of the following year, with 32 784 cases, accounting for 15.19%. A total of 29 300 throat swab samples were collected, of which 2 595 were positive for influenza virus, with an overall detection rate of 8.86%. More positive specimens were detected in winter and spring, with 1 994 cases, accounting for 76.84%. The positive detection rate of influenza virus was higher in boys than in girls (9.23% vs. 8.46%, P<0.05). The positive detection rate was higher among students, at 13.64%. The influenza virus subtypes detected were influenza A (H1N1), influenza A (H3N2) and influenza B (Victoria lineage), accounting for 30.17%, 31.33% and 38.50%, respectively. No influenza B (Yamagata lineage) was detected. Influenza A(H3N2) was the predominant subtype in 2020, only influenza B (Victoria lineage) was detected in 2021, influenza A (H3N2) and influenza A (H1N1) were the predominant subtypes in 2023, and influenza B (Victoria lineage) was the predominant subtype in 2022 and 2024. Conclusions From 2020 to 2024, the proportion of ILI among children aged 0 to 14 years in Heilongjiang Province showed an upward trend, with peak incidence occurring in winter and spring. Boys and students were the key target population for prevention and control, and as dominant strains alternate in circulation, targeted monitoring and prevention measures need to be strengthened.

Objective:To establish 30-day of age transcutaneous bilirubin (TcB) reference curves for healthy neonates, and to investigate regional variations in bilirubin dynamics.Methods:A multicenter retrospective cohort study was conducted. A total of 220 950 healthy neonates born at a gestational age of 35-<42 weeks, with a birth weight ≥2 000 g, who did not receive phototherapy within 60 h after birth were recruited. All of them underwent remote TcB monitoring using the Bilibaby remote jaundice monitoring system between August 1 st, 2020 and December 31 st, 2024 in 426 hospitals. TcB data were collected within the period from birth to 30-day of age. The P40, P75, and P95 of TcB values were calculated, and dynamic TcB curves for 30-day of age were constructed. Patterns of bilirubin change, rates of change, and transition outcomes were described. Regional comparisons between South and North were conducted using linear mixed-effects models for TcB trajectories and Pearson′s chi-square test for outcome differences. Results:A total of 220 950 neonates were included, of whom 101 711 (46.03%) were female. Gestational age at birth was (38.75±1.12) weeks, and birth weight was (3 272±417) g. TcB levels increased rapidly within 3-day of age, peaked at 4-6-day of age, with peak values at P40, P75, and P95 of 200.6, 239.7 and 275.4 μmol/L (11.8, 14.1 and 16.2 mg/dl), respectively. TcB levels gradually declined thereafter and stabilized after 13-day of age, with values at P40, P75, and P95 fluctuating between 147.9-159.8, 190.4-200.6, and 231.2-239.7 μmol/L (8.7-9.4, 11.2-11.8, 13.6-14.1 mg/dl), respectively. Notably, among neonates categorized as low-or low-intermediate-risk within 3-day of age, 6 700 (12.76%) progressed to intermediate-high or high risk between 4 and 30 days of age. Before 13-day of age, TcB levels in the southern regions were consistently higher than those in the northern regions ( P=0.039); from 14 to 30 days of age, the overall TcB levels had no statistically difference, but the temporal changes in TcB still showed regional differences (degrees of freedom=3, all interaction P<0.05). Among neonates classified as low-or low-intermediate risk within 3-day of age, 25 326 were from southern regions, of whom 4 254 (16.80%) progressed to intermediate-high or high risk between 4 and 30 days of age. In northern regions, 27 193 neonates were classified as low-or low-intermediate risk within 3-day of age, among whom 2 446 (8.99%) progressed to intermediate-high or high risk. The risk progression between the 2 regions had statistically difference ( χ2=716.49, P<0.001). Conclusions:A TcB percentile curve for neonates within 30-day of age was established, revealing that both the overall TcB level and its temporal trend were higher in southern than in northern newborns. These findings provide baseline data to support continuous management of neonatal jaundice.

Objective:To explore the impact of plant and animal dietary behaviors on type 2 diabetes mellitus (T2DM) in older adults aged ≥65 in 18 longevity areas of China.Methods:The subjects were 5 223 older adults over 65 years old from the Healthy Ageing and Biomarkers Cohort Study (HABCS) in 18 longevity areas in China. Through a questionnaire survey and physical examination, information about their demographic characteristics, lifestyles, daily activities, self-health status, current diseases, and fasting venous blood were collected. Food Frequency and Questionnaire (FFQ) was used to collect data on food intake frequency. Based on the prior method, the plant-based diet index (PDI) and animal-based diet index (ADI) of 5 223 older adults were calculated. Subjects were divided into three groups (low-level group: PDI<39 or ADI<31, middle-level group: 39≤PDI≤42 or 31≤ADI≤34, high-level group: PDI>42 or ADI>34) by tertiles of PDI and ADI. Multivariate logistic regression was used to analyze the association between PDI and ADI and the risk of T2DM.Results:The average age of 5 223 subjects was (84.8±11.5) years, with the median ( Q1, Q3) of PDI about 41(38, 43) and the median ( Q1, Q3) of ADI about 33 (30, 35). The prevalence rate of T2DM was 16.41% (857/5 223). After adjusting for covariates, multivariate logistic regression showed that PDI was negatively associated with T2DM. Compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 0.83 (0.69-0.99). ADI was positively associated with T2DM, and compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 1.28 (1.06-1.55). For every one-point increase in PDI and ADI, the risk of T2DM decreased by 2% and increased by 3%, respectively, with the OR (95% CI) of 0.98 (0.96-1.00) and 1.03 (1.01-1.06), respectively. Conclusion:In Chinese older adults ≥65 years in 18 longevity areas, higher adherence to the plant-based behavior may be negatively associated with the risk of T2DM, while higher adherence to the animal-based behavior may be positively associated with the risk of T2DM.