Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

OBJECTIVE To analyze the metabolites of Zhideke granules and speculate its metabolic pathway in rats in vivo. METHODS Male SD rats were randomly divided into blank group and administration group （Zhideke granules， 9.45 g/kg）； they were given ultrapure water or relevant medicine， twice a day， every 6-8 h， for 3 consecutive days. Serum， urine and feces samples of rats were collected， and their metabolites were identified by UPLC-Q-Exactive-MS technique after intragastric administration of Zhideke granules； their metabolic pathways were speculated. RESULTS After intragastric administration of Zhideke granules， 16 prototype components （i.g. irisflorentin， baicalin， chlorogenic acid） and 11 metabolites （i.g. hydration products of kaempferol or luteolin， methylation products of chlorogenic acid， and hydroxylation products of baicalin） were identified in serum， urine and feces of rats. Among them， 8 prototype components and 4 metabolites were identified in serum samples； 10 prototype components and 7 metabolites were identified in urine samples； 8 prototype components and 5 metabolites were identified in the fecal samples. CONCLUSIONS The metabolites of Zhideke granules in rats mainly include baicalin， irisflorentin，chlorogenic acid， and the main metabolic pathways included methylation， hydroxylation， glucuronidation.

Objective    To explore the safety and feasibility of uni-portal video-assisted thoracic surgery (VATS) for the treatment of bronchopulmonary sequestration (BPS). Methods    The clinical data of BPS patients with surgical resection in Shanghai Pulmonary Hospital from February 2010 to June 2021 were reviewed. The patients were divided into a VATS group and a thoracotomy group according to the operation method. The operation time, intraoperative blood loss, hospital stay and postoperative complication rate were compared between the two groups. The VATS group was subdivided into a uni-portal VATS group and a multi-portal VATS group for subgroup analysis. Results    Finally 131 patients were enrolled, including 62 males and 69 females with an average age of 39.3±13.2 years. There were 103 patients in the VATS group and 28 patients in the thoracotomy group. A total of 104 patients were diagnosed with left lower BPS, 26 with right lower BPS and 1 with bilateral lower BPS. The main symptom was cough (88 patients, 67.2%). There were 119 patients diagnosed by thoracic enhanced CT before operation. Compared with the thoracotomy group, the operation time was not statistically different (P=0.717), but the blood loss was less, the rate of postoperative complication was lower and hospital stay was shorter in the VATS group (P<0.05). The rate of conversion to open surgery in the uni-portal VATS group and multi-portal VATS group was 11.8% and 13.5%, respectively. Meanwhile, patients in the uni-portal VATS group had shorter operation time and postoperative hospital stay, less blood loss and lower postoperative complication rate than those in the multi-portal VATS group (P<0.05). Conclusion     In order to improve the rate of diagnosis, the lung enhanced CT scan should be selected as an optimal noninvasive method in adult suspected patients (especially those with solid cystic and solid lesions in the lower lobe). Uni-portal VATS is a safe and feasible method for BPS which can be widely promoted.

Objective To explore the mechanism underlying the protective effect of Lonicerae japonicae flos(LJF)extract against doxorubicin(DOX)-induced liver injury in mice.Methods Network pharmacology methods were used to obtain the intersection genes between LJF targets and disease targets,based on which the protein-protein interaction(PPI)network was constructed using STRING database for screening the core targets using Cytoscape software.DAVID database was used for bioinformatics analysis,and the core components and core targets were verified using molecular docking study.In a mouse model of DOX-induced liver injury,the effect of LJF extract on liver pathologies,serum levels of ALT and AST,and hepatic expressions of HYP,ROS,TNF-α,IL-6,COL-IV and P53 proteins were evaluated using HE and Masson staining,ELISA,and Western blotting.Results We identified 12 core targets from 43 intersection genes involving cancer pathway,IL-17 signaling pathway,and TNF signaling pathways.Molecular docking study suggested that 10 core components of LJF could bind to different core targets.The mice with DOX-induced liver injury showed elevated serum AST and ALT levels with obvious liver injury and fibrosis,increased ROS content,and enhanced expressions of TNF-α,IL-6,HYP,COL-IV and P53 proteins in the liver tissue.All these changes in the mouse models were significantly alleviated by treatment with LJF extract,suggesting obviously lowered levels of oxidative stress,inflammation and fibrosis in the liver tissues.Conclusion LJF extract is capable of alleviating DOX-induced liver injury in mice by downregulating Trp53,TNF and IL-6 to reduce liver oxidative stress,inflammation and fibrosis.

OBJECTIVE To provide reference for basic analysis of the pharmacodynamic substance in Stahlianthus involucratus. METHODS Overall 24 SD male rats were randomly divided into blank group （purified water）， and administration group （ethanol extract of S. involucratus， 15.75 g/kg， calculated by crude drug）， with 12 rats in each group. They were given drug liquid/purified water intragastrically， twice a day， every 6-8 h， for consecutive 3 days. After medication， the blood， urine and fecal samples were collected from two groups of rats. UPLC-Q-Exactive-MS technology was used to identify the chemical constituents in the ethanol extract of S. involucratus， and metabolites in the blood， urine and fecal of rats after intragastrical administration of the ethanol extract of S. involucratus. Multivariate statistical analysis was employed to screen various serum metabolites. Metabolic pathways were analyzed by MetaboAnalyst 5.0 platform. RESULTS A total of 38 chemical constituents were identified from the ethanol extract of S. involucratus， including fourteen prototype components and three metabolites identified from 5 urine samples， nine prototype components identified from fecal samples， and ten prototype components and one metabolite identified from serum samples. A total of 71 differential metabolites were screened from two groups of rat serum samples， of which 44 differential metabolites， such as ferulic acid， glycyrrhizin， were up-regulated and 27 differential metabolites， such as arachidonic acid， phenylacetylglutamine， were down-regulated. The 71 differential metabolites were mainly enriched in 11 metabolic pathways， including phenylalanine metabolism， linoleic acid metabolism， arachidonic acid metabolism， and tryptophan metabolism. CONCLUSIONS Ferulic acid， liquiritigenin， isofraxidin and formononetin may be the material basis that directly exert pharmacological effects of S. involucratus. S. involucratus may exert anti-inflammatory effects by affecting metabolic pathways， including arachidonic acid metabolism and tryptophan metabolism.

Objective To explore the mechanism underlying the protective effect of Lonicerae japonicae flos(LJF)extract against doxorubicin(DOX)-induced liver injury in mice.Methods Network pharmacology methods were used to obtain the intersection genes between LJF targets and disease targets,based on which the protein-protein interaction(PPI)network was constructed using STRING database for screening the core targets using Cytoscape software.DAVID database was used for bioinformatics analysis,and the core components and core targets were verified using molecular docking study.In a mouse model of DOX-induced liver injury,the effect of LJF extract on liver pathologies,serum levels of ALT and AST,and hepatic expressions of HYP,ROS,TNF-α,IL-6,COL-IV and P53 proteins were evaluated using HE and Masson staining,ELISA,and Western blotting.Results We identified 12 core targets from 43 intersection genes involving cancer pathway,IL-17 signaling pathway,and TNF signaling pathways.Molecular docking study suggested that 10 core components of LJF could bind to different core targets.The mice with DOX-induced liver injury showed elevated serum AST and ALT levels with obvious liver injury and fibrosis,increased ROS content,and enhanced expressions of TNF-α,IL-6,HYP,COL-IV and P53 proteins in the liver tissue.All these changes in the mouse models were significantly alleviated by treatment with LJF extract,suggesting obviously lowered levels of oxidative stress,inflammation and fibrosis in the liver tissues.Conclusion LJF extract is capable of alleviating DOX-induced liver injury in mice by downregulating Trp53,TNF and IL-6 to reduce liver oxidative stress,inflammation and fibrosis.

Objective:To investigate the distribution characteristics of skeletal muscle mass and strength in the older adults over 65 years old in 18 longevity areas in China.Methods:The subjects were selected from the Healthy Aging and Biomarkers Cohort Study conducted in 18 longevity areas of China. A total of 4 662 older adults over 65 years old from a cross- sectional survey in 2021 were included in the study. The information about their sociodemographic characteristics, lifestyle, nutrient intake and other factors were collected through questionnaire surveys and physical examinations. Grip strength was measured by using professional electronic grip dynamometer. Total skeletal muscle mass (TSM) was measured using bioelectrical impedance analysis, and TSM was adjusted by height squared and BMI to obtain TSM Ht2 and TSM BMI. The proportion of individuals with low muscle mass and strength was determined according to the recommended method by the Asian Working Group for Sarcopenia (AWGS). Descriptive analysis was conducted on the population and regional distribution characteristics of people with different muscle mass and grip strength. A generalized additive model was used to analyze the age-related trends of muscle mass and grip strength. Results:The age of 4 662 study subjects was (82.69±10.54) years, men accounted for 46.85% (2 184 cases) and Han Chinese accounted for 96.27% (4 488 cases). The M( Q1, Q3) of TSM, TSM Ht2 and TSM BMI in men were 23.30 (20.50, 26.20) kg, 9.02 (8.13, 9.89) kg/m 2, and 1.01 (0.90, 1.13) kg·(kg/m 2) -1, respectively, which were all higher than those in women [TSM: 18.20 (15.70, 20.70) kg, TSM Ht2: 8.18 (7.42, 9.07) kg/m 2 and TSM BMI: 0.79 (0.69, 0.90) kg·(kg/m 2) -1], the differences were significant (all P<0.001). The grip strength of men [ M( Q1, Q3): 24.50 (17.80, 30.80) kg] was higher than that of women [ M( Q1, Q3): 15.60 (11.10, 19.90) kg], the difference was significant ( P<0.001). Southern elderly men had lower TSM and TSM Ht2 compared with northern elderly men (all P<0.001), while there was no significant regional difference in TSM BMI ( P>0.05). Southern elderly women had higher TSM Ht2 and TSM BMI compared with northern elderly women (all P<0.001), while there was no significant regional difference in TSM ( P>0.05). Furthermore, according to the method recommended by AWGS, the elderly with low muscle mass and grip strength were characterized by older age, illiteracy, being unmarried/divorced/widowed, poor chewing ability, impaired activity of daily living and living in southern region. Conclusion:There were population and regional differences in muscle mass and grip strength in the older adults over 65 years in 18 longevity areas of China, and these differences showed decreasing trends with age.