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 establish HPLC fingerprint for Jianpi hewei formula （JPHWF）， conduct chemical pattern recognition analysis， and determine the contents of seven components in the formula， aiming to provide a scientific basis for quality control and further research of JPHWF. METHODS Taking 15 batches of standard decoctions of JPHWF as samples， the HPLC fingerprint was established using the Similarity Evaluation System of TCM Chromatographic Fingerprint （2012 edition）. Subsequently， similarity evaluation， as well as identification and attribution analysis of chromatographic peaks， were conducted. Using the common peak areas from the 15 batches of samples as variables， chemical pattern recognition analyses were performed on the samples through hierarchical cluster analysis， principal component analysis， and orthogonal partial least squares-discriminant analysis. The contents of adenine， 5-hydroxymethylfurfural， tetrahydropalmatine， naringin， dehydrocorydaline， neohesperidin and glycyrrhizic acid in 15 batches of samples were determined by HPLC. RESULTS There were 19 common peaks in the characteristic chromatograms for 15 batches of samples with the similarities of more than 0.95. Results of chemical pattern recognition analysis showed that 15 batches of samples could be clustered into 3 categories， and 3 differential compounds were found [peak 7 （5- hydroxymethylfurfural）， peak 17 （neohesperidin）， and peak 15 （naringin）]. The 7 components were linearly good in the respective concentration ranges （R2≥0.999 4）； RSDs of precision， stability and repeatability tests were less than 2% （n＝6）； the average recovery rate of 98.95%-103.81%， RSD of 0.61%-2.75% （n＝6）； the contents of them were 0.031-0.106， 0.267-0.824， 0.089- 0.144， 1.344-2.091， 0.089-0.178， 1.328-2.028， 0.040-0.150 mg/g， respectively. CONCLUSIONS Established HPLC fingerprinting method coupled with multi-index content determination is validated to be accurate and reliable， and its combination with chemical pattern recognition analysis can be applied to the quality control of JPHWF.

Fermented traditional Chinese medicine(TCM) has a long history of medicinal use, such as Sojae Semen Praeparatum, Arisaema Cum Bile, Pinelliae Rhizoma Fermentata, red yeast rice, and Jianqu. Fermentation technology was recorded in the earliest TCM work, Shen Nong's Classic of the Materia Medica. Microorganisms are essential components of the fermentation process. However, the contamination of fermented TCM by toxigenic fungi and mycotoxins due to unstandardized fermentation processes seriously affects the quality of TCM and poses a threat to the life and health of consumers. In this paper, the characteristics, microbial composition, and mycotoxin profile of fermented TCM are systematically summarized to provide a theoretical basis for its quality and safety control.
Fermentation ; Mycotoxins/analysis* ; Drugs, Chinese Herbal/analysis* ; Fungi/classification* ; Bacteria/genetics* ; Drug Contamination ; Medicine, Chinese Traditional

Traditional Chinese medicine(TCM) is the pillar for the development of motherland medicine, and animal medicine has a long history of application in China, characterized by wide resources, strong activity, definite efficacy, and great benefits. It has significant potential and important status in the consumption market of raw materials of TCM. In the context of global climate change, farming system alterations, and low renewability, the depletion of wild medicinal animal resources has accelerated. Accordingly, the conservation and sustainable utilization of wild resources of animal medicinal materials has become a problem that garners increasing attention and urgently needs to be solved. This paper summarizes the current situation of domestic and foreign medicinal animal breeding and research progress in industrial application in recent years and points out the issues related to standardized breeding, germplasm selection and breeding, and quality evaluation standards for medicinal animals. Furthermore, this paper discusses standardized breeding, quality standards, resource protection and utilization, and the search for alternative resources for rare and endangered medicinal animals. It proposes that researchers should systematically carry out in-depth basic research on animal medicine, improve the breeding scale and level of medicinal animals, employ modern technology to enhance the quality standards of medicinal materials, and strengthen the research and development of alternative resources. This approach aims to effectively address the relationship between protection and utilization and make a significant contribution to the sustainable development of medicinal animal resources and the animal-based Chinese medicinal material industry.
Animals ; Breeding ; China ; Medicine, Chinese Traditional ; Conservation of Natural Resources

The choice of biopsy method is critical in diagnosing prostate cancer (PCa). This retrospective cohort study compared systematic biopsy (SB) or cognitive fusion-targeted biopsy combined with SB (CB) in detecting PCa and clinically significant prostate cancer (csPCa). Data from 2572 men who underwent either SB or CB in Fudan University Shanghai Cancer Center (Shanghai, China) between January 2019 and December 2023 were analyzed. Propensity score matching (PSM) was used to balance baseline characteristics, and detection rates were compared before and after PSM. Subgroup analyses based on prostate-specific antigen (PSA) levels and Prostate Imaging-Reporting and Data System (PI-RADS) scores were performed. Primary and secondary outcomes were the detection rates of PCa and csPCa, respectively. Of 2572 men, 1778 were included in the PSM analysis. Before PSM, CB had higher detection rates for both PCa (62.9% vs 52.4%, odds ratio [OR]: 1.54, P < 0.001) and csPCa (54.9% vs 43.3%, OR: 1.60, P < 0.001) compared to SB. After PSM, CB remained superior in detecting PCa (63.1% vs 47.9%, OR: 1.86, P < 0.001) and csPCa (55.0% vs 38.2%, OR: 1.98, P < 0.001). In patients with PSA 4-12 ng ml -1 (>4 ng ml -1 and ≤12 ng ml -1 , which is also applicable to the following text), CB detected more PCa (59.8% vs 40.7%, OR: 2.17, P < 0.001) and csPCa (48.1% vs 27.7%, OR: 2.42, P < 0.001). CB also showed superior csPCa detection in those with PI-RADS 3 lesions (32.1% vs 18.0%, OR: 2.15, P = 0.038). Overall, CB significantly improves PCa and csPCa detection, especially in patients with PSA 4-12 ng ml -1 or PI-RADS 3 lesions.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Propensity Score ; Retrospective Studies ; Middle Aged ; Aged ; Image-Guided Biopsy/methods* ; Prostate-Specific Antigen/blood* ; Prostate/diagnostic imaging*

OBJECTIVE: To assess the efficacy and safety of a new conditioning regimen with chidamide and BEAM for autologous hematopoietic stem cell transplantation (AHSCT) in patients with lymphoma. METHODS: Medical records and further follow-up data from 85 patients with lymphoma from May 2015 to September 2020 in our hospital were retrospectively collected and analyzed. RESULTS: Among 85 patients, 52 cases accepted BEAM regimen and 33 cases accepted CBEAM followed by AHSCT. In CBEAM group, 18 patients (54.5%) received AHSCT as salvage therapy, while only 26.9% (14 cases) for salvage in BEAM group ( P < 0.01). CBEAM conditioning resulted in shorter neutrophil engraftment of 2 days, while no significant difference was found in platelet engraftment. Although the incidence of liver impairment was higher in CBEAM group (12.1%), the grade of impairment was only Ⅰ to Ⅱ. The two conditioning regimens both achieved good complete remission rate of over 90%, and no transplant-related death occurred. The median follow-up time in the CBEAM group was 18(12, 22) months, and 39(20, 59) months in the BEAM group. There were no significantly differences in 2-year progression-free survival (PFS) and overall survival (OS) rate between the two groups (P >0.05). In patients with refractory or relapsed non-Hodgkin lymphoma, the 2-year PFS rate after transplantation in BEAM group and CBEAM group was 74.1% and 92.9%, respectively (P >0.05), indicating that chidamide may have certain advantages in prolonging PFS. CONCLUSION CBEAM conditioning regimen has a good efficacy and safety in lymphoma patients before AHSCT, especially in refractory and relapsed non-Hodgkin lymphoma patients, suggesting that it could serve as an alternative conditioning regimen prior to AHSCT for lymphoma.
Humans ; Hematopoietic Stem Cell Transplantation ; Transplantation Conditioning/methods* ; Transplantation, Autologous ; Retrospective Studies ; Aminopyridines/therapeutic use* ; Lymphoma/therapy* ; Benzamides/therapeutic use* ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Male ; Female ; Cytarabine/therapeutic use* ; Melphalan/therapeutic use* ; Adult ; Middle Aged ; Podophyllotoxin/therapeutic use* ; Carmustine ; Etoposide

OBJECTIVE: To analyze the Epstein-Barr virus (EBV) load in different lymphocyte subsets, as well as clinical characteristics and outcomes in patients with hematologic malignancies experiencing EBV reactivation. METHODS: Peripheral blood samples from patients were collected. B, T, and NK cells were isolated sorting with magnetic beads by flow cytometry. The EBV load in each subset was quantitated by real-time quantitative polymerase chain reaction (RT-qPCR). Clinical data were colleted from electronic medical records. Survival status was followed up through outpatient visits and telephone calls. Statistical analyses were performed using SPSS 25.0. RESULTS: A total of 39 patients with hematologic malignancies were included, among whom 35 patients had undergone allogeneic hematopoietic stem cell transplantation (allo-HSCT). The median time to EBV reactivation was 4.8 months (range: 1.7-57.1 months) after allo-HSCT. EBV was detected in B, T, and NK cells in 20 patients, in B and T cells in 11 patients, and only in B cells in 4 patients. In the 35 patients, the median EBV load in B cells was 2.19×10⁴ copies/ml, significantly higher than that in T cells (4.00×10³ copies/ml, P <0.01) and NK cells (2.85×10² copies/ml, P <0.01). Rituximab (RTX) was administered for 32 patients, resulting in EBV negativity in 32 patients with a median time of 8 days (range: 2-39 days). Post-treatment analysis of 13 patients showed EBV were all negative in B, T, and NK cells. In the four non-transplant patients, the median time to EBV reactivation was 35 days (range: 1-328 days) after diagnosis of the primary disease. EBV was detected in one or two subsets of B, T, or NK cells, but not simultaneously in all three subsets. These patients received a combination chemotherapy targeting at the primary disease, with 3 patients achieving EBV negativity, and the median time to be negative was 40 days (range: 13-75 days). CONCLUSION In hematologic malignancy patients after allo-HSCT, EBV reactivation commonly involves B, T, and NK cells, with a significantly higher viral load in B cells compared to T and NK cells. Rituximab is effective for EBV clearance. In non-transplant patients, EBV reactivation is restricted to one or two lymphocyte subsets, and clearance is slower, highlighting the need for prompt anti-tumor therapy.
Humans ; Hematologic Neoplasms/virology* ; Herpesvirus 4, Human/physiology* ; Epstein-Barr Virus Infections ; Hematopoietic Stem Cell Transplantation ; Virus Activation ; Lymphocyte Subsets/virology* ; Flow Cytometry ; Killer Cells, Natural/virology* ; Male ; Female ; B-Lymphocytes/virology* ; Viral Load ; Adult ; T-Lymphocytes/virology* ; Middle Aged