ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

This study analyzed the burden and trends in enteric infections in China from 1990 to 2021 from a One Health perspec-tive.Data on mortality associated with enteric infections were extracted from the 2021 Global Burden of Disease(GBD)database.The analysis focused on assessing the mortality rates of enteric infectious diseases attributed to various etiologies and risk factors,along with the age and sex distribution,from 1990 to 2021.Average annual percentage change(AAPC)was used to assess the total changes in disease burden.The age-standardized mortality rate of intestinal infections in China decreased from 9.642/100 000 in 1990 to 0.439/100 000 in 2021,with an AAPC of-57.103%(95%CI:-57.118%to-57.088%).In 2021,Rotavirus,Norovirus,and Crypto-sporidium were the top three etiologies contributing to disease burden,with mortality rates of 1.020/100 000,0.040/100 000 and 0.079/100 000,respectively.A significant variation in etiology distribution was observed across age groups:Rotavirus,Shigella,and Crypto-sporidium dominated among children under 5 years of age,whereas Cryptosporidium,Norovirus,and Clostridioides difficile were more prevalent in older populations.Risk factor analysis indicated that unsafe water sources and poor sanitation accounted for 73.394%of all enteric disease-related deaths.In conclusion,the burden of enteric infections in China markedly declined from 1990 to 2021,and sig-nificant variations in the etiological spectrum and disease burden were observed across age groups.The persistent effects of unsafe wa-ter sources and poor sanitation underscore the need for targeted interventions to further decrease the burden of these diseases.Our find-ings highlight the success of public health interventions in decreasing the burden of enteric infections in China,while emphasizing the need for targeted measures to address disparities in high-risk populations and improve environmental sanitation.

Aim To investigate the expression of or-ganic anion transporting polypeptide 4C1(Oatp4c1)-P-glycoprotein(P-gp)in the kidneys of obese mice in-duced by high-fat diet(HFD),and its impact on the pharmacokinetic changes of digoxin.Methods C57BL/6 mice were randomly divided into the Chow group and the HFD group.Body weight and blood glu-cose were recorded weekly.After successful model es-tablishment,digoxin was intraperitoneally injected,and blood was collected at different time points.Part of the blood samples was used for LC-MS/MS detection,and the other part was used for the detection of other bio-chemical indicators.After 16 weeks,the organs were removed and weighed.HE and immunohistochemical staining was used to observe the renal pathology and the expression of Villin,a marker of proximal tubules.Western blot and qPCR were combined to detect the expression of Villin,Oatp4c1 and P-gp.Results In the HFD group,body weight and blood glucose in-creased significantly.The blood concentration of digox-in rose,the area under the curve increased,and the half-life was prolonged.The proximal tubular epithelial cells shed,and the protein expression of Villin,Oatp4c1 and P-gp decreased significantly.Conclu-sions The down-regulation of Oatp4c1-P-gp expres-sion in the kidneys of HFD mice leads to an increase in the blood concentration of digoxin and a decrease in re-nal clearance.

Objective:To explore the correlation between the total cholesterol/high-density lipoprotein cholesterol (TC/HDL-C) ratio during pregnancy and the onset of gestational metabolic syndrome (GMS), as well as its association with pregnancy outcomes.Methods:Clinical data of 153 pregnant women diagnosed with GMS in the third trimester admitted to Women′s Hospital of Nanjing Medical University from January 2020 to December 2022 (observation group) were collected, and data of 153 healthy pregnant women (control group) were randomly selected for a comparative study. Indicators of the two groups were observed and compared. Multiple linear regression and restricted cubic spline analysis were used to analyze the correlation between TC/HDL-C in the first and second trimesters and metabolic indicators in the third trimester and GMS risk, respectively. According to the pregnancy outcomes of GMS pregnant women with different TC/HDL-C ratios, the association between TC/HDL-C ratio and preterm birth subtypes was analyzed.Results:There were statistically significant differences between the two groups in age, gestational week, pre-pregnancy body mass index (BMI), weight gain during pregnancy, abdominal circumference in the third trimester, whether to deliver vaginally, history of preterm birth, history of cesarean section, history of abortion, neonatal birth weight, and neonatal length (all P<0.05). There were statistically significant differences in blood pressure and BMI between the two groups in the second and third trimesters (all P<0.01). In the first trimester (gestational week <14 weeks), there were statistically significant differences in fasting plasma glucose (FPG), HDL-C, and TC/HDL-C ratio between the two groups (all P<0.05). In the second trimester (gestational weeks 14-27) and third trimester (gestational week ≥28 weeks), the levels of FPG, fasting insulin (FINS), triglyceride (TG), TC, low-density lipoprotein cholesterol (LDL-C), and TC/HDL-C ratio in the observation group were higher than those in the control group, while HDL-C was lower (all P<0.05). There were statistically significant differences between the two groups in postpartum abnormal blood pressure, abnormal BMI, abnormal glucose metabolism, and abnormal lipid metabolism (all P<0.05). After adjusting for age, gestational week, and BMI, first-trimester TC/HDL-C ratio was correlated with third-trimester FPG, systolic blood pressure, diastolic blood pressure, TG, TC, and HDL-C (all P<0.05); second-trimester TC/HDL-C ratio was correlated with third-trimester FPG, FINS, systolic blood pressure, diastolic blood pressure, TG, TC, HDL-C, and LDL-C (all P<0.05), and both were linearly related to third-trimester GMS risk ( Pfor trend<0.01). The TC/HDL-C ratio was positively correlated with the preterm birth rate ( RR>1). Conclusions:An increased TC/HDL-C ratio is closely related to the occurrence of GMS, which is prone to cause preterm birth and affect fetal growth and development.

Objective To construct a machine learning prediction model for diabetic kidney disease(DKD)in type 2 diabetes mellitus(T2DM)patients in the plain-sand and loess hilly areas of Gansu Province,and analyze the interpretability of the model.Methods A multi-stage stratified random sampling method was used to collect the data of T2DM patients in the two areas.After key feature screening,eight ML prediction models were constructed for the risk of DKD in the two areas.The receiver operating characteristic(ROC)curve,accuracy and F1 index were used to evaluate the model,and Shapley additive explanation(SHAP)algorithm was used for model interpretation.Results A total of 1599 patients with T2DM were enrolled in this study.After feature screening,ten variables were selected for model construction in the plain-sand areas.Among the eight models,the gradient boosting decision tree(GBDT)model had the highest prediction efficiency.The area under the curve(AUC)of the test dataset was 0.972,the accuracy was 0.949,and the F1 index was 0.884.In the loess hilly region,12 variables were included in the model,and the best model was the random forest(RF).The AUC of the test set was 0.966,the accuracy was 0.951,and the F1 index was 0.861.SHAP analysis showed that in addition to serum creatinine,age,LDL-C,HbA1c,DM duration,serum uric acid and urinary microalbumin were also closely related to the high risk of DKD.Conclusions The GBDT and RF models have good predictive efficiency for the occurrence of DKD in the two areas,which can be used for the screening of DKD high-risk populations and the in-depth exploration of potential risk factors in the two areas.

This study analyzed the burden and trends in enteric infections in China from 1990 to 2021 from a One Health perspec-tive.Data on mortality associated with enteric infections were extracted from the 2021 Global Burden of Disease(GBD)database.The analysis focused on assessing the mortality rates of enteric infectious diseases attributed to various etiologies and risk factors,along with the age and sex distribution,from 1990 to 2021.Average annual percentage change(AAPC)was used to assess the total changes in disease burden.The age-standardized mortality rate of intestinal infections in China decreased from 9.642/100 000 in 1990 to 0.439/100 000 in 2021,with an AAPC of-57.103%(95%CI:-57.118%to-57.088%).In 2021,Rotavirus,Norovirus,and Crypto-sporidium were the top three etiologies contributing to disease burden,with mortality rates of 1.020/100 000,0.040/100 000 and 0.079/100 000,respectively.A significant variation in etiology distribution was observed across age groups:Rotavirus,Shigella,and Crypto-sporidium dominated among children under 5 years of age,whereas Cryptosporidium,Norovirus,and Clostridioides difficile were more prevalent in older populations.Risk factor analysis indicated that unsafe water sources and poor sanitation accounted for 73.394%of all enteric disease-related deaths.In conclusion,the burden of enteric infections in China markedly declined from 1990 to 2021,and sig-nificant variations in the etiological spectrum and disease burden were observed across age groups.The persistent effects of unsafe wa-ter sources and poor sanitation underscore the need for targeted interventions to further decrease the burden of these diseases.Our find-ings highlight the success of public health interventions in decreasing the burden of enteric infections in China,while emphasizing the need for targeted measures to address disparities in high-risk populations and improve environmental sanitation.

Aim To investigate the expression of or-ganic anion transporting polypeptide 4C1(Oatp4c1)-P-glycoprotein(P-gp)in the kidneys of obese mice in-duced by high-fat diet(HFD),and its impact on the pharmacokinetic changes of digoxin.Methods C57BL/6 mice were randomly divided into the Chow group and the HFD group.Body weight and blood glu-cose were recorded weekly.After successful model es-tablishment,digoxin was intraperitoneally injected,and blood was collected at different time points.Part of the blood samples was used for LC-MS/MS detection,and the other part was used for the detection of other bio-chemical indicators.After 16 weeks,the organs were removed and weighed.HE and immunohistochemical staining was used to observe the renal pathology and the expression of Villin,a marker of proximal tubules.Western blot and qPCR were combined to detect the expression of Villin,Oatp4c1 and P-gp.Results In the HFD group,body weight and blood glucose in-creased significantly.The blood concentration of digox-in rose,the area under the curve increased,and the half-life was prolonged.The proximal tubular epithelial cells shed,and the protein expression of Villin,Oatp4c1 and P-gp decreased significantly.Conclu-sions The down-regulation of Oatp4c1-P-gp expres-sion in the kidneys of HFD mice leads to an increase in the blood concentration of digoxin and a decrease in re-nal clearance.

Objective:To explore the correlation between the total cholesterol/high-density lipoprotein cholesterol (TC/HDL-C) ratio during pregnancy and the onset of gestational metabolic syndrome (GMS), as well as its association with pregnancy outcomes.Methods:Clinical data of 153 pregnant women diagnosed with GMS in the third trimester admitted to Women′s Hospital of Nanjing Medical University from January 2020 to December 2022 (observation group) were collected, and data of 153 healthy pregnant women (control group) were randomly selected for a comparative study. Indicators of the two groups were observed and compared. Multiple linear regression and restricted cubic spline analysis were used to analyze the correlation between TC/HDL-C in the first and second trimesters and metabolic indicators in the third trimester and GMS risk, respectively. According to the pregnancy outcomes of GMS pregnant women with different TC/HDL-C ratios, the association between TC/HDL-C ratio and preterm birth subtypes was analyzed.Results:There were statistically significant differences between the two groups in age, gestational week, pre-pregnancy body mass index (BMI), weight gain during pregnancy, abdominal circumference in the third trimester, whether to deliver vaginally, history of preterm birth, history of cesarean section, history of abortion, neonatal birth weight, and neonatal length (all P<0.05). There were statistically significant differences in blood pressure and BMI between the two groups in the second and third trimesters (all P<0.01). In the first trimester (gestational week <14 weeks), there were statistically significant differences in fasting plasma glucose (FPG), HDL-C, and TC/HDL-C ratio between the two groups (all P<0.05). In the second trimester (gestational weeks 14-27) and third trimester (gestational week ≥28 weeks), the levels of FPG, fasting insulin (FINS), triglyceride (TG), TC, low-density lipoprotein cholesterol (LDL-C), and TC/HDL-C ratio in the observation group were higher than those in the control group, while HDL-C was lower (all P<0.05). There were statistically significant differences between the two groups in postpartum abnormal blood pressure, abnormal BMI, abnormal glucose metabolism, and abnormal lipid metabolism (all P<0.05). After adjusting for age, gestational week, and BMI, first-trimester TC/HDL-C ratio was correlated with third-trimester FPG, systolic blood pressure, diastolic blood pressure, TG, TC, and HDL-C (all P<0.05); second-trimester TC/HDL-C ratio was correlated with third-trimester FPG, FINS, systolic blood pressure, diastolic blood pressure, TG, TC, HDL-C, and LDL-C (all P<0.05), and both were linearly related to third-trimester GMS risk ( Pfor trend<0.01). The TC/HDL-C ratio was positively correlated with the preterm birth rate ( RR>1). Conclusions:An increased TC/HDL-C ratio is closely related to the occurrence of GMS, which is prone to cause preterm birth and affect fetal growth and development.

Objective To construct a machine learning prediction model for diabetic kidney disease(DKD)in type 2 diabetes mellitus(T2DM)patients in the plain-sand and loess hilly areas of Gansu Province,and analyze the interpretability of the model.Methods A multi-stage stratified random sampling method was used to collect the data of T2DM patients in the two areas.After key feature screening,eight ML prediction models were constructed for the risk of DKD in the two areas.The receiver operating characteristic(ROC)curve,accuracy and F1 index were used to evaluate the model,and Shapley additive explanation(SHAP)algorithm was used for model interpretation.Results A total of 1599 patients with T2DM were enrolled in this study.After feature screening,ten variables were selected for model construction in the plain-sand areas.Among the eight models,the gradient boosting decision tree(GBDT)model had the highest prediction efficiency.The area under the curve(AUC)of the test dataset was 0.972,the accuracy was 0.949,and the F1 index was 0.884.In the loess hilly region,12 variables were included in the model,and the best model was the random forest(RF).The AUC of the test set was 0.966,the accuracy was 0.951,and the F1 index was 0.861.SHAP analysis showed that in addition to serum creatinine,age,LDL-C,HbA1c,DM duration,serum uric acid and urinary microalbumin were also closely related to the high risk of DKD.Conclusions The GBDT and RF models have good predictive efficiency for the occurrence of DKD in the two areas,which can be used for the screening of DKD high-risk populations and the in-depth exploration of potential risk factors in the two areas.