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.

T7 RNA polymerase (T7 RNAP) is one of the simplest known RNA polymerases. Its unique structural features make it a critical model for studying the mechanisms of RNA synthesis. This review systematically examines the static crystal structure of T7 RNAP, beginning with an in-depth examination of its characteristic “thumb”, “palm”, and “finger” domains, which form the classic “right-hand-like” architecture. By detailing these structural elements, this review establishes a foundation for understanding the overall organization of T7 RNAP. This review systematically maps the functional roles of secondary structural elements and their subdomains in transcriptional catalysis, progressively elucidating the fundamental relationships between structure and function. Further, the intrinsic flexibility of T7 RNAP and its applications in research are also discussed. Additionally, the review presents the structural diagrams of the enzyme at different stages of the transcription process, and through these diagrams, it provides a detailed description of the complete transcription process of T7 RNAP. By integrating structural dynamics and kinetics analyses, the review constructs a comprehensive framework that bridges static structure to dynamic processes. Despite its advantages, T7 RNAP has a notable limitation: it generates double-stranded RNA (dsRNA) as a byproduct. The presence of dsRNA not only compromises the purity of mRNA products but also elicits nonspecific immune responses, which pose significant challenges for biotechnological and therapeutic applications. The review provides a detailed exploration of the mechanisms underlying dsRNA formation during T7 RNAP catalysis, reviews current strategies to mitigate this issue, and highlights recent progress in the field. A key focus is the semi-rational design of T7 RNAP mutants engineered to minimize dsRNA generation and enhance catalytic performance. Beyond its role in transcription, T7 RNAP exhibits rapid development and extensive application in fields, including gene editing, biosensing, and mRNA vaccines. This review systematically examines the structure-function relationships of T7 RNAP, elucidates the mechanisms of dsRNA formation, and discusses engineering strategies to optimize its performance. It further explores the engineering optimization and functional expansion of T7 RNAP. Furthermore, this review also addresses the pressing issues that currently need resolution, discusses the major challenges in the practical application of T7 RNAP, and provides an outlook on potential future research directions. In summary, this review provides a comprehensive analysis of T7 RNAP, ranging from its structural architecture to cutting-edge applications. We systematically examine: (1) the characteristic right-hand domains (thumb, palm, fingers) that define its minimalistic structure; (2) the structure-function relationships underlying transcriptional catalysis; and (3) the dynamic transitions during the complete transcription cycle. While highlighting T7 RNAP’s versatility in gene editing, biosensing, and mRNA vaccine production, we critically address its major limitation—dsRNA byproduct formation—and evaluate engineering solutions including semi-rationally designed mutants. By synthesizing current knowledge and identifying key challenges, this work aims to provide novel insights for the development and application of T7 RNAP and to foster further thought and progress in related fields.

Aim To investigate the effect of ellagic acid (EA) on cognitive function in APP/PS 1 double- transgenic mice, and to explore the regulatory mechanism of ellagic acid on the level of oxidative stress in the hippocampus of double-transgenic mice based on the phosphatidylinositol 3-kinase/protein kinase B/glycogen synthase kinase-3 (PI3K/AKT/GSK-3 β) signaling pathway. Methods Thirty-two SPF-grade 6-month-old APP/PS 1 double transgenic mice were randomly divided into four groups, namely, APP/PS 1 group, APP/PS1 + EA group, APP/PS1 + LY294002 group, APP/PS 1 + EA + LY294002 group, with eight mice in each group, and eight SPF-grade C57BL/6J wild type mice ( Wild type) were selected as the blank control group. The APP/PS 1 + EA group was given 50 mg · kg

Aim To study the neuroprotective effects of Herba siegesbeckiae extract on cerebral ischemia/ reperfusion rats and its mechanism. Methods Sixty SD rats were randomly divided into model group, low, middle and high dose groups of Herba siegesbeckiae, and Sham operation group, and the drug was given continuously for seven days. The degree of neurologic impairment was evaluated by mNSS, and the infarct volume was measured by MRI. The number of Nissl-posi- tive cells was detected by Nissl staining, and the apop- tosis was accessed by Tunel staining. Furthermore, the expression of Bax, Bcl-2 and NeuN was observed by Western blot, and the expression of NeuN was detected by immunofluorescence staining. The expression of IL- 1β, TNF-α and IL-6 mRNA was performed by RT- qPCR. Results The mNSS score and the volume of ischemic cerebral infarction in the model group were significantly increased, and Herba siegesbeckiae extract treatment significantly decreased the mNSS score and infarct volume (P<0.05, P<0.01). Herba siegesbeckiae extract could increase the number of Nissl-pos- itive cells and the expression of NeuN (P<0.01), and reduce the number of Tunel-positive cells (P<0.01). Western blot showed that Herba siegesbeckiae extract inhibited the expression of Bax, increased Bcl-2 and NeuN in ischemic brain tissue (P<0.01). RT-qPCR showed that Herba siegesbeckiae extract inhibited the expression of IL-1 β, TNF-α and IL-6 mRNA in the is-chemic brain tissue (P<0.01). Conclusions Herba siegesbeckiae extract can reduce the cerebral infarction volume, improve the neurological function damage, inhibit the apoptosis of nerve cells and the expression of inflammatory factors and promote the expression of NeuN, there by exerting protective effects on MCAO rats.

Objective:To construct prediction models of necrotizing enterocolitis (NEC) using machine learning (ML) methods.Methods:From January 2015 to October 2021, neonates with suspected NEC symptoms receiving abdominal ultrasound examinations in our hospital were retrospectively analyzed. The neonates were assigned into NEC group (modified Bell's staging≥Ⅱ) and non-NEC group for diagnostic prediction analysis (dataset 1). The NEC group was subgrouped into surgical NEC group (staging≥Ⅲ) and conservative NEC group for severity analysis (dataset 2). Feature selection algorithms including extremely randomized trees, elastic net and recursive feature elimination were used to screen all variables. The diagnostic and severity prediction models for NEC were established using logistic regression, support vector machine (SVM), random forest, light gradient boosting machine and other ML methods. The performances of different models were evaluated using area under the receiver operating characteristic curve (AUC), sensitivity, specificity, negative predictive value and positive predictive value.Results:A total of 536 neonates were enrolled, including 234 in the NEC group and 302 in the non-NEC group (dataset 1).70 were in the surgical NEC group and 164 in the conservative NEC group (dataset 2). The variables selected by extremely randomized trees showed the best predictive performance in two datasets. For diagnostic prediction models, the SVM model had the best predictive performance, with AUC of 0.932 (95% CI 0.891-0.973) and accuracy of 0.844 (95% CI 0.793-0.895). A total of 11 predictive variables were determined, including portal venous gas, intestinal dilation, neutrophil percentage and absolute monocyte count at the onset of illness. For NEC severity prediction models, the SVM model showed the best predictive performance, with AUC of 0.835 (95% CI 0.737-0.933) and accuracy of 0.787 (95% CI 0.703-0.871). A total of 25 predictive variables were identified, including age of onset, C-reactive protein and absolute neutrophil count at clincial onset. Conclusions:NEC prediction model established using feature selection algorithm and SVM classification model in ML is helpful for the diagnosis of NEC and grading of disease severity.

Objective:To investigate the value of 18F-FDG PET/CT imaging in the diagnosis of suspected autoimmune encephalitis (AE) in children with epilepsy and negative MRI. Methods:From May 2019 to August 2022, 94 suspected AE children (49 males, 45 females; age 1-15 years) with epilepsy and negative MRI who underwent brain 18F-FDG PET/CT imaging at Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine were retrospectively analyzed. All patients were divided into AE and non-AE groups based on clinical final diagnosis. The effectiveness of visual diagnosis was evaluated. The cortical lesion extent score (S), and SUV max, SUV mean and minimum of SUV (SUV min) of cortical lesions (L), basal ganglia (B) and thalamus (T) were measured and SUV ratios (SUVR) of L/B or L/T were obtained. Independent-sample t test or Mann-Whitney U test was used to analyze data. Binary logistic regression analysis was used to screen the diagnostic factors of AE, and a diagnostic model was established. The diagnostic efficiency was evaluated by ROC curve analysis and Delong test. Results:There were 53 cases in AE group and 41 cases in non-AE group. Based on visual analysis, the sensitivity, specificity and accuracy of 18F-FDG PET/CT for AE were 100%(53/53), 43.9%(18/41) and 75.5%(71/94), respectively. Differences of LSUV max, LSUV mean, LSUV min, L/BSUVR max, L/BSUVR mean, L/BSUVR min, L/TSUVR max, L/TSUVR mean, L/TSUVR min and S between AE and non-AE groups were statistically significant ( z=-6.74, t values: from -8.51 to -3.97, all P<0.001). ROC curve analysis showed that the AUC of L/BSUVR max was the highest (0.914) among visual analysis and semi-quantitative parameters. Logistic regression analysis showed that S (odds ratio ( OR)=11.40, 95% CI: 2.18-59.52, P=0.004), L/BSUVR max( OR=13.19, 95% CI: 2.11-82.51, P=0.006) and L/TSUVR max( OR=9.66, 95% CI: 1.57-59.55, P=0.015) were independent diagnostic factors for AE. Regression model was established: P=1/(1+ e - x), x=2.433×S+ 2.580×L/BSUVR max+ 2.267×L/TSUVR max-3.802. The AUC of this model was 0.948, with the sensitivity, specificity and accuracy of 98.1%(52/53), 90.2%(37/41) and 94.7%(89/94), respectively. The diagnostic efficacy of the optimized scoring system was consistent with the pre-optimization model, and were both superior to L/BSUVR max(both z=2.01, both P=0.040). Conclusion:The diagnostic model and scoring system based on the semi-quantitative analysis of 18F-FDG PET/CT have better diagnostic efficacy for AE and are superior to semi-quantitative parameters alone.

Objective To explore the effects of ropivacaine on cognitive dysfunction and synapses in aged rats after tibial fracture.Methods SD male rats were divided into sham operation group,model group and low,medium,high dose experimental groups.Sham operation group was incised and sutured under local anesthesia,and other four groups underwent open tibial fracture operation.Sham operation group and model group were given sevoflurane anesthesia,low,medium and high dose experimental groups were given 0.5,1.0,2.0 mg·kg-1 ropivacaine on the basis of sevoflurane anesthesia.Open field test and Morris water maze test were performed 7 days after operation;Longa score was evaluated;neurotransmitter levels were detected by kit;and Syn1 in hippocampus of rats was detected by immunohistochemistry.Western blot analysis was used to detected the expression of N-methyl-D-aspartate receptor 2B(NMDAR2B),calmodulin-dependent protein kinase Ⅱ(CaMK Ⅱ)and Syn1.Results The Longa scores of sham operation group,model group and low,medium,high dose experimental groups were 0,(3.50±0.71),(2.80±0.63),(2.20±0.63)and(0.90±0.32)points;the integrated optical density of Syn1 were 0.56±0.09,0.25±0.03,0.34±0.03,0.42±0.03 and 0.50±0.05;the expression of Syn1 protein were 1.08±0.12,0.42±0.05,0.55±0.07,0.72±0.06 and 0.86±0.05;the expression of NMDAR2B protein were 1.28±0.13,0.51±0.07,0.69±0.06,0.84±0.07 and 1.02±0.11;CaMK Ⅱ protein were 0.94±0.08,0.36±0.04,0.50±0.06,0.71±0.06 and 0.86±0.06.There were statistically significant differences between sham operation group and model group(P＜0.05);there were significant differences in the above indexes between model group and low,medium,high dose experimental groups(all P＜0.05).Conclusion Ropivacaine can improve cognitive dysfunction and synapses in aged rats after tibial fracture.