Acute lung injury （ALI） is one of the most common and critical diseases in clinical practice， with extremely high morbidity and mortality， seriously threatening human life and health. The pathogenesis of ALI is complex， in which the inflammatory response is a key factor. Studies have shown that NOD-like receptor protein 3 （NLRP3） inflammasomes are involved in ALI through mechanisms such as inflammation induction， increased microvascular permeability， recruitment of neutrophils， oxidative stress， and pyroptosis， playing a key role in the occurrence and progression of ALI. Therefore， regulating NLRP3 inflammasomes and inhibiting the release of inflammatory factors can alleviate the damage in ALI. At present， ALI is mainly treated by mechanical ventilation and oxygen therapy， which have problems such as high costs and poor prognosis. In recent years， studies have shown that traditional Chinese medicine （TCM） can reduce the inflammatory response and the occurrence of oxidative stress and pyroptosis by regulating the NLRP3 inflammasome， thus alleviating the damage and decreasing the mortality of ALI. Based on the relevant literature in recent years， this article reviews the research progress in TCM treatment of ALI by regulating NLRP3 inflammasomes， discusses how NLRP3 inflammasomes participate in ALI， and summarizes the active ingredients， extracts， and compound prescriptions of TCM that regulate NLRP3 inflammasomes， aiming to provide new ideas for the clinical treatment of ALI and the development of relevant drugs.

OBJECTIVE To investigate the effects and potential mechanism of paeoniflorin on oxidative stress of ulcerative colitis （UC） mice based on adenosine monophosphate-activated protein kinase （AMPK）/nuclear factor-erythroid 2-related factor 2 （Nrf2） pathway. METHODS Male BALB/c mice were randomly divided into control group， model group， inhibitor group （AMPK inhibitor Compound C 20 mg/kg）， paeoniflorin low-， medium- and high-dose groups （paeoniflorin 12.5， 25， 50 mg/kg）， high- dose of paeoniflorin+inhibitor group （paeoniflorin 50 mg/kg+Compound C 20 mg/kg）， with 8 mice in each group. Except for the control group， mice in all other groups were given 4% dextran sulfate sodium solution for 5 days to establish the UC model. Subsequently， mice in each drug group were given the corresponding drug solution intragastrically or intraperitoneally， once a day， for 7 consecutive days. The changes in body weight of mice were recorded during the experiment. Twenty-four hours after the last administration， colon length， malondialdehyde （MDA） content， and activities of superoxide dismutase （SOD） and glutathione peroxidase （GSH-Px） in colon tissues were measured； histopathological morphology of colon tissues， tight junctions between intestinal epithelial cells， and histopathological scoring were all observed and evaluated； the mRNA expressions of AMPK and Nrf2， as well as the protein expressions of heme oxygenase-1（HO-1）， occludin and claudin-1， were all determined in colon tissue. RESULTS Compared with model group， paeoniflorin groups exhibited recovery from pathological changes such as inflammatory cell infiltration and crypt damage in the colon tissue， as well as improved tight junction damage between intestinal epithelial cells. Additionally， significant increases or upregulations were observed in body weight， colon length， activities of SOD and GSH-Px， phosphorylation level of AMPK， and protein expression of Nrf2， HO-1， occludin， claudin-1， and mRNA expressions of AMPK and Nrf2； concurrently， MDA content and histopathological scores were significantly reduced （P＜ 0.05 or P＜0.01）. In contrast， the inhibitor group showed comparable （P＞0.05） or worse （P＜0.05 or P＜0.01） indicators compared to the model group. Conversely， the addition of AMPK inhibitor could significantly reverse the improvement of high- dose paconiflorin （P＜0.01）. CONCLUSIONS Paeoniflorin can repair intestinal epithelial cell damage in mice， improve tight junctions between epithelial cells， upregulate the expression of related proteins， and promote the expression and secretion of antioxidant-promoting molecules， thereby ameliorating UC； its mechanism may be associated with activating AMPK/Nrf2 antioxidant pathway.

The auxin/indole-3-acetic acid (Aux/IAA) gene family is an important regulator for plant growth hormone signaling, involved in plant growth, development, as well as response to environmental stresses. In the present study, we identified SmIAA7 which is potentially associated with Salvia miltiorrhiza leaf development through comparatively analyzed the transcriptome data from different pinnate leaves. SmIAA7 was successfully isolated from S. miltiorrhiza using the specific primers. Then subsequent bioinformatic analysis, prokaryotic expression and purification, subcellular localization, and induction expression analysis under auxin and abiotic stress were performed. The full-length of SmIAA7 contained an ORF of 684 bp encoding a protein of 227 amino acid with a molecular weight of 25.3 kD. Conserved domain analysis showed that SmIAA7 contains the conserved Aux_IAA domain (pfam02309). Sequence analysis and phylogenetic tree analysis results indicated SmIAA7 was phylogenetically close to IAA7 and IAA14 from other plants, suggesting SmIAA7 involved in plant growth and development as well as response to environmental stresses. The prokaryotic expression vector pET28a-SmIAA7 was constructed and SmIAA7 recombinant protein was successfully expressed in E. coli Rosetta (DE3) strain. Subcellular localization experiment demonstrated that SmIAA7 localized in the nucleus of plant cells. Real-time fluorescence quantitative PCR results showed that the expression level of SmIAA7 was upregulated in response to auxin. Drought, low temperature, and salt stress significantly increased the transcript level of SmIAA7 gene. This study lays a foundation for further elucidating the role of SmIAA7 in leaf development, signal transduction, and stress defense in S. miltiorrhiza.

Objective: To analyze respiratory syncytial virus(RSV) outbreaks surveillance results and the epidemiological characteristics in kindergarten and school in Shenzhen during 2017-2023 , so as to provide a scientific reference for control and prevention of RSV. Methods: Epidemiological data and surveillance results of RSV outbreaks in kindergarten and school from 2017 to 2023 were collected for descriptive analyses. Results: A total of 31 RSV outbreaks were identified in kindergarten and school in 2017-2023 in Shenzhen, 346 cases were reported, the average incidence rate was 22.02%. The most annual RSV outbreaks were reported in 2020 with 14 outbreaks, followed by 8 outbreaks in 2023. A total of 64.52% of RSV outbreaks were identified in kindergarten with rest occurring in primary school or middle school. The greatest monthly count of outbreak was 18 (58.06%) in September, followed by 3 outbreaks (9.68%) in March and October. A total of 244 swab samples were collected, 169 samples were positive for respiratory viruses, the positive rate was 69.26%, 121 samples were positive for RSV,from 31 respiratory syncytical virus outbreaks 57 and samples were positive for other respiratory viruses(9 samples were positive for two respiratory viruses). A toral of 14(45.16%) outbreaks are caused by RSV alone, 17 outbreaks (54.84%) were caused by RSV and other respiratory viruses. Conclusions Most RSV outbreaks in kindergarten and school are reported after 2020 in Shenzhen, most RSV outbreaks occur in kindergarten, peak seasons of RSV outbreaks are autumn and spring.

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.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

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.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

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.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.