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.

Objective To develop an ICU patient care difficulty index based on psychosocial factors and to evaluate its reliability and validity,thereby providing a comprehensive tool for assessing the difficulties in ICU patient care.Methods Guided by Guarinoni theory,an index system was developed through systematic literature reviews,semi-structured interviews,two rounds of Delphi expert consultation and the analytic hierarchy process.Based on the drafted system,a questionnaire was formulated.The tests for validity and reliability were conducted on 290 patients selected by convenience sampling.Results The finalised ICU patient care difficulty index system was composed of 5 primary indices(the general condition of the patient,disease condition,nursing condition,social support,and organizational characteristics),13 secondary indices and 27 tertiary indices.The Kendall's coefficient of coordination W values were 0.380 and 0.498,respectively,indicating a statistically significant agreement(both P<0.001).The system demonstrated a robust reliability(Cronbach's α=0.896)and a good internal consistency.Validity was confirmed through a scale level-content validity index(S-CVI)of 0.94 and the item level-content validity indices(I-CVI)ranged from 0.87 to 1.00.Structural validity analysis,based on 8 extracted public factors,showed a cumulative variance contribution rate of 66.34%.Conclusion The ICU patient care difficulty index system shows a high reliability and validity,making it a valuable tool for accurately quantification of the difficulty in ICU patient care.This system provides a scientific basis for allocation of ICU nursing resource and performance distribution.

Objective To develop an ICU patient care difficulty index based on psychosocial factors and to evaluate its reliability and validity,thereby providing a comprehensive tool for assessing the difficulties in ICU patient care.Methods Guided by Guarinoni theory,an index system was developed through systematic literature reviews,semi-structured interviews,two rounds of Delphi expert consultation and the analytic hierarchy process.Based on the drafted system,a questionnaire was formulated.The tests for validity and reliability were conducted on 290 patients selected by convenience sampling.Results The finalised ICU patient care difficulty index system was composed of 5 primary indices(the general condition of the patient,disease condition,nursing condition,social support,and organizational characteristics),13 secondary indices and 27 tertiary indices.The Kendall's coefficient of coordination W values were 0.380 and 0.498,respectively,indicating a statistically significant agreement(both P<0.001).The system demonstrated a robust reliability(Cronbach's α=0.896)and a good internal consistency.Validity was confirmed through a scale level-content validity index(S-CVI)of 0.94 and the item level-content validity indices(I-CVI)ranged from 0.87 to 1.00.Structural validity analysis,based on 8 extracted public factors,showed a cumulative variance contribution rate of 66.34%.Conclusion The ICU patient care difficulty index system shows a high reliability and validity,making it a valuable tool for accurately quantification of the difficulty in ICU patient care.This system provides a scientific basis for allocation of ICU nursing resource and performance distribution.

AIM To establish a UPLC-MS/MS method for the simultaneous content determination of Asp,Guad,Adeno,Arg,Ade,Cyti,Phe,Leu,Ile,Glu,Ser,Gln,Gly,Ala,Hyp,Thr,Pro and Lys in Asini Corii Colla.METHODS The analysis was performed on a 45℃ thermostatic Waters BEH C18column(2.1 mm×50 mm,1.7 μm),with the mobile phase comprising of acetonitrile(containing 0.1% formic acid)-water flowing at 0.35 mL/min in a gradient elution manner,and electron spray ionization source was adopted in positive ion scanning with multiple reaction monitoring mode.Subsequently,chemical pattern recognition was performed by hierarchical clustering analysis,principal component analysis and orthogonal partial least squares-discriminant analysis.RESULTS Eighteen nucleosides and free amino acids showed good linear relationships within their own ranges(r≥0.999 0),whose average recoveries were 98.0%-104.9% with the RSDs of 1.6%-4.9% .Seventeen batches of samples were clustered into two categories,two principal components demonstrated the accumulative variance contribution rate of 60.75%,Leu,Phe,Ade and Guad were potential index constituents.CONCLUSION This stable and reliable method can be used for the quality control of Asini Corii Colla.

A gas chromatography-triple quadrupole mass spectrometry(GC-MS) method was established for the simultaneous determination of eleven volatile components in Cinnamomi Oleum and the chemical pattern recognition was utilized to evaluate the quality of essential oil obtained from Cinnamomi Fructus medicinal materials in various habitats. The Cinnamomi Fructus medicinal materials were treated by water distillation, analyzed using GC-MS, and detected by selective ion monitoring(SIM), and the internal standards were used for quantification. The content results of Cinnamomi Oleum from various batches were analyzed by hierarchical clustering analysis(HCA), principal component analysis(PCA), and orthogonal partial least squares-discriminant analysis(OPLS-DA) for the statistic analysis. Eleven components showed good linear relationships within their respective concentration ranges(R~2>0.999 7), with average recoveries of 92.41%-102.1% and RSD of 1.2%-3.2%(n=6). The samples were classified into three categories by HCA and PCA, and 2-nonanone was screened as a marker of variability between batches in combination with OPLS-DA. This method is specific, sensitive, simple, and accurate, and the screened components can be utilized as a basis for the quality control of Cinnamomi Oleum.
Gas Chromatography-Mass Spectrometry ; Plant Oils ; Oils, Volatile ; Drugs, Chinese Herbal/analysis* ; Cluster Analysis

Endocrine-resistance remains a major challenge in estrogen receptor α positive (ERα⁺) breast cancer (BC) treatment and constitutively active somatic mutations in ERα are a common mechanism. There is an urgent need to develop novel drugs with new mode of mechanism to fight endocrine-resistance. Given aberrant ERα activity, we herein report the identification of novel covalent selective estrogen receptor degraders (cSERDs) possessing the advantages of both covalent and degradation strategies. A highly potent cSERD 29c was identified with superior anti-proliferative activity than fulvestrant against a panel of ERα⁺ breast cancer cell lines including mutant ERα. Crystal structure of ERα‒ 29c complex alongside intact mass spectrometry revealed that 29c disrupted ERα protein homeostasis through covalent targeting C530 and strong hydrophobic interaction collied on H11, thus enforcing a unique antagonist conformation and driving the ERα degradation. These significant effects of the cSERD on ERα homeostasis, unlike typical ERα degraders that occur directly via long side chains perturbing the morphology of H12, demonstrating a distinct mechanism of action (MoA). In vivo, 29c showed potent antitumor activity in MCF-7 tumor xenograft models and low toxicity. This proof-of-principle study verifies that novel cSERDs offering new opportunities for the development of innovative therapies for endocrine-resistant BC.

ObjectiveTo establish a traditional Chinese medicine （TCM） syndrome model with yin deficiency and internal heat， discuss the rationality of model evaluation， and analyze differentially expressed genes in multiple dimensions to explore the molecular mechanism-signaling pathways as well as key targets of Baihe Dihuangtang （BHDH） in treating depression with Yin deficiency and internal heat. MethodForty male SD rats were randomly divided into a blank control group，a model group，a fluoxetine group （positive drug），a BHDH group， and a Zhibai Dihuangtang group （positive drug for Yin deficiency and internal heat）. The depression model with Yin deficiency and internal heat was induced by chronic unpredictable mild stress （CUMS）combined with Chinese herbal drugs with warm and heat nature. The model established was comprehensively evaluated by the detection of the basic condition， behavioral performance， and biochemical indicators of rats in each group. The differentially expressed genes were screened out by mRNA sequencing and underwent Gene Ontology（GO） and Kyoto Encyclopedia of Genes and Genomes（KEGG） pathway enrichment analyses. The protein-protein interaction （PPI） network was plotted and key genes were analyzed to explore the underlying mechanism of BHDH in treating depression with Yin deficiency and internal heat. ResultThe comparison of basic conditions， behavioral assays， energy metabolism， endocrine hormones， cytokines， and neurotransmitters showed that the model was properly induced. BHDH could significantly improve depression with Yin deficiency and internal heat by regulating the pathways related to the nervous system， endocrine system， and inflammatory and immune system. The key genes of the PPI network were Fos， Epha8， Npy2r， Htr2c， and Nr4a1. ConclusionUnder the guidance of TCM theories of treatment based on syndrome differentiation and etiology and pathogenesis，this study established a depression model with yin deficiency and internal heat in animals and evaluation system in accordance with the symptoms and signs of emotional diseases， and further confirmed the scientificity of the modeling method and the underlying mechanism of BHDH in interfering with depression with Yin deficiency and internal heat based on the results of mRNA sequencing.