The general models for intermediates quality analysis in the production process of Yaobitong capsule were established by near infrared spectroscopy (NIRS) combined with chemometrics, realizing the rapid determination of notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1, ginsenoside Rd and moisture. The spray-dried fine powder and total mixed granule were selected as research objects. The contents of five saponins were determined by high performance liquid chromatography and the moisture content was determined by drying method. The measured contents were used as reference values. Meanwhile, NIR spectra were collected. After removing abnormal samples by Monte Carlo cross validation (MCCV), Monte Carlo uninformative variables elimination (MC-UVE) and competitive adaptive reweighted sampling (CARS) were used to select feature variables respectively. Based on the feature variables, quantitative models were established by partial least squares regression (PLSR), extreme learning machine (ELM) and ant lion optimization least squares support vector machine (ALO-LSSVM). The results showed that CARS-ALO-LSSVM model had the optimum effect. The correlation coefficients of the six index components were greater than 0.93, and the relative standard errors were controlled within 6%. ALO-LSSVM was more suitable for a large number of samples with rich information, and the prediction effect and stability of the model were significantly improved. The general models with good predicting effect can be used for the rapid quality determination of Yaobitong capsule intermediates.

Objective To understand the epidemic characteristics and genotype distribution of acute hepatitis B in Tianjin, and to find out the relationship between genotype and epidemic characteristics. Methods The information of acute hepatitis B cases with a local address in Tianjin was collected through the National Infectious Disease Surveillance System in Tianjin from 2018 to 2022. The patient outcomes were followed up through hospital system records and telephone survey, and hepatitis B virus (HBV) genotypes were detected by fluorescent PCR. Results From 2018 to 2022, there were 387 cases of acute hepatitis B with local address reported in Tianjin, with an average annual reported incidence rate of 0.52/100 000, showing a downward trend in general (χ²=28.553，P<0.001). The reported male to female incidence ratio was 1.68. The age distribution was mainly concentrated in the 30-65 age group, with the highest incidence rate (1.22/100 000) reported in the 35-39 age group. 72.87% of cases showed negative HBsAg after 6 months of follow-up following diagnosis. The proportion of cadres and staff who turned negative (92.16%) was significantly higher than that of those who did not turn negative (0%). The median ALT (1508.00 U/L) in the turning negative group was significantly higher than that in the non-turning negative group (976.00 U/L). Among 315 cases with successful genotyping, genotype C accounted for 81.27%, and genotype B accounted for 14.92%, with 47 cases. The median ALT of genotype B patients with acute hepatitis B (1585.00 U/L) was significantly higher than that of genotype C patients (988.00 U/L). Conclusion The reported incidence rate of acute hepatitis B in Tianjin is relatively low, and shows a downward trend. Young and middle-aged men are prone to infect HBV. Genotype C is the main genotype, and genotype B HBV causes more serious liver damage in patients with acute hepatitis B.

Background Exposure to polycyclic aromatic hydrocarbons (PAHs) is associated with the development of metabolic syndrome (MS). However, the role of amino acids in PAH-induced MS remains unclear. Objective To explore the impact of PAHs exposure on the incidence of MS among coking workers, and to determine potential modifying effect of amino acid on this relationship. Methods Unmatched nested case-control design was adopted and the baseline surveys of coking workers were conducted in two plants in Taiyuan in 2017 and 2019, followed by a 4-year follow-up. The cohort comprised 667 coking workers. A total of 362 participants were included in the study, with 84 newly diagnosed cases of MS identified as the case group and 278 as the control group. Urinary levels of 11 PAH metabolites and plasma levels of 17 amino acids were measured by ultrasensitive performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Logistic regression was used to estimate the association between individual PAH metabolites and MS. Stratified by the median concentration of amino acids, Bayesian kernel machine regression (BKMR) model was employed to assess the mixed effects of PAHs on MS. Due to the skewed data distribution, all PAH metabolites and amino acids in the analysis were converted by natural logarithm ln (expressed as lnv). Results The median age of the 362 participants was 37 years, and 83.2% were male. Compared to the control group, the case group exhibited higher concentrations of urinary 2-hydroxyphenanthrene (2-OHPhe), 9-hydroxyphenanthrene (9-OHPhe), and hydroxyphenanthrene (OHPhe) (P=0.005, P=0.049, and P=0.004, respectively), as well as elevated levels of plasma branched chain amino acid (BCAA) and aromatic amino acid (AAA) (P<0.05). After being adjusted for confounding factors, for every unit increase in lnv_2-OHPhe in urine, the OR (95%CI) of MS was 1.57 (1.11, 2.26), and for every unit increase in lnv_OHPhe, the OR (95%CI) of MS was 1.82 (1.16, 2.90). Tyrosine, leucine, and AAA all presented a significant nonlinear correlation with MS. At low levels, tyrosine, leucine, and AAA did not significantly increase the risk of MS, but at high levels, they increased the risk of MS. In the low amino acid concentration group, as well as in the low BCAA and low AAA concentration groups, it was found that compared to the PAH metabolite levels at the 50th percentile (P₅₀), the log-odds of MS when the PAH metabolite levels was at the 75th percentile (P₇₅) were 0.158 (95%CI: 0.150, 0.166), 0.218 (95%CI: 0.209, 0.227), and 0.262 (95% CI: 0.241, 0.282), respectively, However, no correlation between PAHs and MS was found in the high amino acid concentration group. Conclusion Amino acids modify the effect of PAHs exposure on the incidence of MS. In individuals with low plasma amino acid levels, the risk of developing MS increases with higher concentrations of mixed PAH exposure. This effect is partly due to the low concentrations of BCAA and AAA.

OBJECTIVE To evaluate the safety of fondaparinux in pregnancy and provide reference for its rational clinical application. METHODS A search was conducted in databases including CNKI， Wanfang， PubMed， Embase， and Elsevier （the search time was from the construction of the database to December 17， 2024） to collect case report literature on fondaparinux use during pregnancy. Patient demographic information， fondaparinux use during pregnancy， concomitant medications， clinical manifestations， and treatment details were extracted for descriptive statistical analysis. RESULTS A total of 17 case reports regarding the use of fondaparinux during pregnancy were collected， involving 42 patients from 11 countries and 47 pregnancy records. Among these， 20 cases involved the use of fondaparinux for the prevention of pregnancy-related venous thromboembolism （VTE）， while 27 cases were fondaparinux treatment due to related conditions. A total of 29 occurrences of the patients were treated with fondaparinux due to a （family） history of VTE. Nine occurrences of complicated pregnancies were reported， and 35 patients had records of comorbidities or relevant medical histories. The adverse events that occurred during pregnancy with the use of fondaparinux include postpartum hemorrhage （7 cases） and excessive anticoagulation caused by inappropriate dosage （1 case）. Among the 7 cases of postpartum hemorrhage， 3 cases had a blood loss of no less than 1 000 mL （including 2 cases with uterine atony）， 3 cases had a drug discontinuation time of ≤12 h. CONCLUSIONS Based on the existing literature， the safety of fondaparinux during pregnancy is generally manageable， with the main adverse event being postpartum hemorrhage. The dosage， interval between discontinuation，comorbidities/medical history， and concomitant medications of fondaparinux may be the main causes of its adverse events.

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.

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.

ObjectiveTo construct a group-based trajectory model (GBTM) for early medication adherence check-in, and to analyze the relationship between different trajectories and treatment outcomes in tuberculosis patients using data that were generated from smart tools for monitoring their medication adherence and check-in. MethodsFrom October 1, 2022 to September 30, 2023, a total of 163 pulmonary tuberculosis patients diagnosed in Fengxian District were selected as the study subjects. The GBTM was utilized to analyze the weekly active check-in trajectories of the subjects during the first 4 weeks and establish different trajectory groups. The χ² tests were employed to compare the differences between groups and logistic regression analysis was conducted to explore the relationship between different trajectory groups and treatment outcomes. ResultsA total of four groups were generated by GBTM analyses, of which a low level of punch card was maintained in group A, 6% of the drug users increased rapidly from a low level in group B, 17% of drug users increased gradually from a low level in group C, and 18% of drug users maintained a high level of punch card in group D. The trajectory group was divided into two groups according to homogeneity, namely the low level medication punch card group (group A) and the high level medication punch card group (group B, group C, and group D). The results of multivariate logistic regression analyses revealed that low-level medication check-in (OR=3.250, 95%CI: 1.089‒9.696), increasing age (OR=1.030, 95%CI: 1.004‒1.056), and not undergoing sputum examination at the end of the fifth month (OR=2.746, 95%CI: 1.090‒7.009) were significantly associated with poor treatment outcomes. ConclusionThe medication check-in trajectory of pulmonary tuberculosis patients within the first 4 weeks is correlated with adverse outcomes, or namely consistent low-level medication adherence check-ins are associated with poor treatment outcomes, while high-level medication adherence check-ins are associated with a lower incidence of adverse outcomes.

This study explored the active ingredients for anti-angiogenesis in Wenyujin Rhizoma Concisum. Ten sesquiterpenoids were isolated from Wenyujin Rhizoma Concisum by silica gel column chromatography, thin layer chromatography, and high performance liquid chromatography. According to the results of multiple spectroscopic methods and circular dichroism, they were identified as wenyujinlactam A(1),(4S,7S)11-hydroxycurdione(2), 8,9-seco-4β-hydroxy-1α,5βH-7(11)-guaen-8,10-olide(3), curcumadione(4), phaeocaulisin E(5), procurcumadiol(6), zedouronediol(7), epiprocurcumenol(8), gajutsulactone A(9), and(7Z)-1β,4α-dihydroxy-5α,8β(H)-eudesm-7(11)-en-8,12-olide(10). Compounds 1 and 2 were new sesquiterpenoids. Compounds 1, 6, 8, and 10 can inhibit human umbilical vein endothelial cells(HUVEC) proliferation with IC_(50) values of 38.83, 45.19, 32.12, and 37.80 μmol·L~(-1), respectively. Compounds 1 and 10 can inhibit HUVEC migration with IC_(50) values of 29.70 and 36.48 μmol·L~(-1), respectively.
Sesquiterpenes/isolation & purification* ; Humans ; Drugs, Chinese Herbal/isolation & purification* ; Rhizome/chemistry* ; Human Umbilical Vein Endothelial Cells/drug effects* ; Molecular Structure ; Cell Proliferation/drug effects*