Objective To analyze the main causes and risk factors of unplanned reoperation after liver transplantation. Methods The clinical data of 242 liver transplant recipients in the First Affiliated Hospital of Anhui Medical University from January 2015 to December 2024 were retrospectively analyzed. According to whether unplanned reoperation was performed during the same hospitalization after surgery, the recipients were divided into the reoperation group (n=36) and the non-reoperation group (n=206). The preoperative, intraoperative and postoperative data of the two groups, as well as donor and graft-related data, were compared to analyze the risk factors of unplanned reoperation after liver transplantation and the survival status of the two groups. Results Among the 242 liver transplant recipients, 36 underwent unplanned reoperations, with a total of 54 procedures including various laparotomies, endoscopic and interventional surgeries, among which there were 20 laparotomies, 18 endoscopic surgeries and 16 interventional surgeries. The most common cause of unplanned reoperation was biliary complications (20 times), followed by vascular complications (17 times). Compared with the non-reoperation group, the reoperation group had longer graft cold ischemia time, higher postoperative fatality rate of recipients, longer length of stay in the intensive care unit and postoperative hospital stay, and higher total hospitalization costs (all P<0.05). The incidence of unplanned reoperation was higher in recipients who underwent split liver transplantation (P<0.05). Multivariate analysis showed that intraoperative blood loss ≥1 000 mL, positive culture of graft perfusate and split liver transplantation were independent risk factors for unplanned reoperation (all P<0.05). The postoperative 7-day, 1-month, 3-month and 6-month survival rates of recipients in the reoperation group and the non-reoperation group were 100% vs. 98.1%, 88.9% vs. 94.2%, 69.4% vs. 90.8% and 66.7% vs. 90.8%, respectively, and the postoperative survival rate of recipients in the reoperation group was lower than that in the non-reoperation group (P<0.05). Conclusions The main causes of unplanned reoperation after liver transplantation are biliary complications, vascular complications, abdominal incision infection and intra-abdominal hemorrhage. Intraoperative massive blood loss, positive culture of graft perfusate and split liver transplantation are the risk factors associated with unplanned reoperation after liver transplantation.

Objective:To analyze the molecular mechanism of Huangqin Decoction in the treatment of acute lung injury (ALI) with network pharmacology; To conduct experimental validation.Methods:Active compounds and corresponding targets of Huangqin Decoction were retrieved from the TCMIP database. ALI-related targets were obtained from GeneCards, DisGeNet, TTD, and OMIM, and the intersection targets were obtained. The intersection targets were imported into the string database to build the PPI network, and the core targets were obtained through topology analysis by Cytoscape 3.10.1 software. GO and KEGG pathway enrichment analyses were conducted using clusterProfiler software. 16 SD rats were divided into two groups ( n = 8 per group) with random number table method: control and Huangqin Decoction. Rats in the Huangqin Decoction group received Huangqin Decoction by gavage at a dosage of 40 mg/kg, while the control group was administered an equal volume of distilled water. After seven consecutive treatments, drug-containing serum was collected. A549 cells were divided into four groups: control, model, Huangqin Decoction, and received relevant drugs as intervention for 24 h. Levels of SOD, MDA, GSH-Px, IL-1β, TNF-α, and IL-6 in the culture supernatant were measured by ELISA. Apoptosis was analyzed by flow cytometry. The expressions of PI3K, p-PI3K, Akt, p-Akt, mTOR, p-mTOR, LC3Ⅱ/Ⅰ, and Beclin-1 proteins were determined by Western blot. Results:A total of 137 active compounds and 178 common targets were identified in Huangqin Decoction, with TP53, AKT1, STAT3, TNF, IL6, and ESR1 as core nodes. GO enrichment indicated involvement in oxidative stress and responses to lipopolysaccharides, bacterial molecules, and hypoxia. KEGG analysis revealed enrichment in lipid and atherosclerosis, PI3K-Akt signaling pathway, hepatitis, MAPK signaling pathway, prostate cancer, small-cell lung cancer, and mTOR signaling pathway. In cell experiments, compared with the model group, Huangqin Decoction and inhibitor groups showed increased A549xibo ( P<0.05); levels of IL-1β, TNF-α, IL-6, and MDA in the supernatant were reduced ( P<0.05 or P<0.01), while SOD and GSH-Px levels were elevated ( P<0.05 or P<0.01); the apoptosis rate decreased ( P<0.05 or P<0.01); the expressions of LC3-Ⅱ/Ⅰ and Beclin-1 proteins decreased ( P<0.05 or P<0.01), whereas the expressions of p-mTOR/mTOR, p-Akt/Akt, and p-PI3K/PI3K increased ( P<0.05 or P<0.01). Conclusion:Huangqin Decoction exerts protective effects against ALI mainly by reducing cellular autophagy, and its mechanism may be related to the activation of the mTOR/Akt/PI3K signaling pathway.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

[Objective]To investigate the relationship between the non-fasting triglyceride and glucose(TyG)index and hyperglycemia in pregnancy during the third trimester in high altitudes.[Methods]This 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.[Results]A 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(Ftrend TC=95.61,P<0.001;Ftrend TG=1 051.91,P<0.001;Ftrend LDL-C=97.20,P<0.001;Ftrend 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).[Conclusion]Non-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.

Placenta，fetal heart and brain affect each other in the process of fetal growth. They are influenced by genetic，environmental，epigenetic and hemodynamic factors，and share several key developmental pathways. Fetal heart defect in ongenital heart disease（CHD）is associated with abnormal development of placenta and brain. One-stop-shop ‘heart-brain-placenta’ imaging is of great value in prenatal diagnosis of CHD fetuses. This review discusses the current research on the one-stop-shop ‘heart-brain-placenta’ imaging of CHD fetuses.

Objective:To investigate the correlation between serum NOD-like receptor protein 3 (NLRP3) levels and serum lipids in metabolic-associated fatty liver disease (MAFLD) before and after a single high-fat meal.Methods:A retrospective cohort study was conducted. Sixty-three MAFLD patients (MAFLD group) and fifty-four healthy subjects (CON group) recruited from February 2019 to December 2019 at Hebei Provincial People's Hospital were included. The baseline data were compared between the two groups, and a single high-fat meal trial was conducted. The levels of total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and NLRP3 were measured at 2 h, 4 h, and 6 h after fasting and a high-fat meal. Multiple linear regression analysis was used to evaluate the influencing factors of area under the operating curve (AUC NLRP3) of serum NLRP3 subjects. Logistic regression analysis was used to evaluate the correlation between serum AUC NLRP3 and the risk of MAFLD. Results:The levels of TC, TG, LDL-C, and NLRP3 were significantly higher in the fasting group than the CON group at 2 h, 4 h, and 6 h after a meal [TC (mmol/L), fasting: (5.29±1.01) vs. (4.28±0.62), 2 h: (5.24±0.98) vs. (4.25±0.62), 4 h: (5.38±1.04) vs. (4.26±0.63), 6 h: (5.54±1.07) vs. (4.41±0.65); TG (mmol/L), fasting: (2.67±0.96) vs. (0.92±0.33), 2 h: (3.91±1.35) vs. (1.69±0.59), 4 h: (5.09±1.7) vs. (1.91±0.93), 6 h: (5.36±2.27) vs. (1.75±1.03); LDL-C (mmol/L), fasting: (3.47±0.74) vs. (2.65±0.49), 2 h: (3.36±0.71) vs. (2.58±0.49), 4 h: (3.30±0.71) vs. (2.55±0.47), 6 h: (3.36±0.74) vs. (2.63±0.48); NLRP3 (ng/L), fasting: (84.63±12.96) vs. (56.71±11.37), 2 h: (106.06±17.76) vs. (69.12±14.92), 4 h: (89.78±15.98) vs. (57.74±12.34), 6 h: (80.03±13.61) vs. (54.06±10.35); P<0.001], while the HDL-C level was significantly lower than the CON group [HDL-C (mmol/L), fasting: (1.14±0.24) vs. (1.33±0.29), 2 h: (1.14±0.24) vs. (1.33±0.29), 4 h: (1.09±0.24) vs. (1.27±0.28), and 6 h: (1.05±0.26) vs. (1.29±0.30); P<0.001]. Serum AUC NLRP3 was significantly correlated with AUC TG and AUC LDL-C (AUC TG: B=7.391, 95% CI:5.662-9.12; AUC LDL-C: B=6.559, 95% CI:3.052-10.065; P<0.001) after adjusting for confounding factors, and it was identified as an independent influencing factor for MAFLD ( OR=1.039, 95% CI:1.007-1.071; P=0.015). Conclusion:The serum NLRP3 levels before and after a single high-fat meal are significantly associated with elevated TG and LDL-C levels, and may influence the progression of MAFLD.

Objective:To investigate the correlation between serum NOD-like receptor protein 3 (NLRP3) levels and serum lipids in metabolic-associated fatty liver disease (MAFLD) before and after a single high-fat meal.Methods:A retrospective cohort study was conducted. Sixty-three MAFLD patients (MAFLD group) and fifty-four healthy subjects (CON group) recruited from February 2019 to December 2019 at Hebei Provincial People's Hospital were included. The baseline data were compared between the two groups, and a single high-fat meal trial was conducted. The levels of total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and NLRP3 were measured at 2 h, 4 h, and 6 h after fasting and a high-fat meal. Multiple linear regression analysis was used to evaluate the influencing factors of area under the operating curve (AUC NLRP3) of serum NLRP3 subjects. Logistic regression analysis was used to evaluate the correlation between serum AUC NLRP3 and the risk of MAFLD. Results:The levels of TC, TG, LDL-C, and NLRP3 were significantly higher in the fasting group than the CON group at 2 h, 4 h, and 6 h after a meal [TC (mmol/L), fasting: (5.29±1.01) vs. (4.28±0.62), 2 h: (5.24±0.98) vs. (4.25±0.62), 4 h: (5.38±1.04) vs. (4.26±0.63), 6 h: (5.54±1.07) vs. (4.41±0.65); TG (mmol/L), fasting: (2.67±0.96) vs. (0.92±0.33), 2 h: (3.91±1.35) vs. (1.69±0.59), 4 h: (5.09±1.7) vs. (1.91±0.93), 6 h: (5.36±2.27) vs. (1.75±1.03); LDL-C (mmol/L), fasting: (3.47±0.74) vs. (2.65±0.49), 2 h: (3.36±0.71) vs. (2.58±0.49), 4 h: (3.30±0.71) vs. (2.55±0.47), 6 h: (3.36±0.74) vs. (2.63±0.48); NLRP3 (ng/L), fasting: (84.63±12.96) vs. (56.71±11.37), 2 h: (106.06±17.76) vs. (69.12±14.92), 4 h: (89.78±15.98) vs. (57.74±12.34), 6 h: (80.03±13.61) vs. (54.06±10.35); P<0.001], while the HDL-C level was significantly lower than the CON group [HDL-C (mmol/L), fasting: (1.14±0.24) vs. (1.33±0.29), 2 h: (1.14±0.24) vs. (1.33±0.29), 4 h: (1.09±0.24) vs. (1.27±0.28), and 6 h: (1.05±0.26) vs. (1.29±0.30); P<0.001]. Serum AUC NLRP3 was significantly correlated with AUC TG and AUC LDL-C (AUC TG: B=7.391, 95% CI:5.662-9.12; AUC LDL-C: B=6.559, 95% CI:3.052-10.065; P<0.001) after adjusting for confounding factors, and it was identified as an independent influencing factor for MAFLD ( OR=1.039, 95% CI:1.007-1.071; P=0.015). Conclusion:The serum NLRP3 levels before and after a single high-fat meal are significantly associated with elevated TG and LDL-C levels, and may influence the progression of MAFLD.

Objective:To investigate the predictive role of intrapartum ultrasound indicators on the difficulty of vacuum-assisted delivery.Methods:A prospective cohort study was conducted. The study subjects were singleton pregnant women hospitalized for delivery at the Third Affiliated Hospital of Sun Yat-sen University from February 2021 to December 2022, who had indications for vacuum-assisted delivery, and completed intrapartum ultrasound examination within 10 minutes before the procedure. Intrapartum ultrasound indicators included fetal position, angle of progression (AOP), and head-perineum distance (HPD). Based on the difficulty of vacuum-assisted delivery, the subjects were divided into easy and difficult groups. The fetal position, AOP, and HPD before vacuum-assisted delivery and delivery outcomes were compared between the two groups to explore the correlation and predictive value of intrapartum ultrasound indicators on the difficulty of vacuum-assisted delivery. Statistical and predictive value analyses were performed using independent-sample t-test, U-test, Chi-square (or Fisher's exact) test, logistic regression analysis, and receiver operating characteristic (ROC) curve. Results:A total of 162 cases were included in the study, with 120 in the easy and 42 in the difficult groups. The age of the 162 pregnant women ranged from 20 to 44 years, with an average of (30.6±3.9) years; 107 cases (66.0%) were first pregnancies, and 139 cases (85.8%) were primipara. (1) The fetal head stations in the difficult and easy groups were 2.3 (2.0-2.5) cm and 2.0 (2.0-2.5) cm, respectively, with no statistically significant difference ( P>0.05). The AOP during the interval and contraction periods and the ΔAOP in the difficult group were smaller than those in the easy group [ (138.1±8.8) vs. (143.8±7.9), t=3.89; (148.7±9.3) vs. (157.9±8.9), t=5.67; and (10.6±6.4) vs. (14.1±6.3), t=3.08; all P<0.01], while the HPD during the interval and contraction periods and ΔHPD in the difficult group were greater than those in the easy group [(3.4±0.5) cm vs. (3.2±0.4) cm, t=－2.69; (2.8±0.5) cm vs. (2.4±0.5) cm, t=－4.70; (－0.5±0.4) cm vs. (－0.8±0.5) cm, t=－2.83; all P<0.01]. (2) In the difficult group, seven cases required forceps delivery after 2-3 vacuum cup detachments; in the easy group, all cases were successfully delivered after 1-2 vacuum tractions. The duration of vacuum extraction was longer in the difficult group [7.0 (6.0-10.0) min vs. 3.0 (2.0-3.0) min, Z=9.65] (all P<0.001). (3) In the difficult group, four cases had severe maternal and neonatal delivery complications, including two cases of shoulder dystocia, one case of vesicovaginal fistula after failed vacuum extraction converted to forceps delivery, and one case of third-degree perineal tear after failed vacuum extraction converted to forceps delivery. In the easy group, one case had shoulder dystocia with mild neonatal asphyxia. The rate of vaginal tears in the difficult group was higher than in the easy group [47.6% (20/42) vs. 29.2% (35/120)] ( χ2=4.72, P=0.030). The incidence of postpartum hemorrhage in the difficult and easy groups was 11.9% (5/42) and 8.3% (10/120), respectively, with no statistically significant difference (Fisher's exact test, P=0.539). No cases required cesarean section after failed vacuum extraction. The incidence of scalp hematoma was higher in the difficult group than in the easy group [28.6% (12/42) vs. 11.7% (14/120), χ2=6.60, P=0.010]. The two groups had no statistically significant differences in the incidence of other neonatal complications. (4) Multivariate logistic regression analysis identified three independent variables associated with difficult vacuum extraction: maternal age, AOP and HPD during contraction. The ROC curve was used to test the predictive value of the multivariate model for difficult vacuum extraction, with an area under the curve of 0.808 (95% CI: 0.734-0.882) ( P<0.001). When the maximum Youden index (0.487) was taken, the sensitivity and specificity of the model in predicting difficult vacuum extraction were 0.762 (95% CI: 0.696-0.828) and 0.725 (95% CI: 0.656-0.794), respectively. Conclusions:AOP and HPD are related to the difficulty of vacuum extraction. The risk of difficult vacuum extraction increases with advanced maternal age, smaller AOP and larger HPD during the contraction phase.