Based on advancements in modern medical research regarding the intricate connection between the endocrine and exocrine functions of the pancreas， as well as the relationship between pancreatic functions and traditional Chinese medicine （TCM） spleen system， this paper discussed the categorization of the pancreas. It is proposed that the pancreas is neither a true zang organ nor a fu organ， but possessed the attributes of an extraordinary fu-organ and can be classified under the spleen. The spleen governs transportation and transformation， ascent of the clear and dispersion of essence， which encompasses the endocrine and exocrine functions， and pancreatic enzymes and glucose-regulating hormones form the material basis for the spleen's function of dispersing essence. Diseases of the pancreas exhibit characteristics of both zang-organ deficiency and fu-organ excess， so treatment should simultaneously supplement zang-organ disease and regulate fu-organ disease when pancreas showing endocrine and exocrine co-morbidities， with focus on restoring the pancreas （spleen）'s dispersing essence function. Therapeutic strategies include supplementing spleen qi， nourishing spleen yin to strengthen spleen earth， unblocking spleen collaterals， raising spleen yang， and removing spleen turbidity to support the spleen's dispersing essence function， so as to replenish the essential qi of zang-fu organs， ensure their distribution throughout the body， and improve the endocrine and exocrine functions of the pancreas.

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.

Neodymium, one of the important rare earth elements, is widely used in various fields such as industry, agriculture, and medicine. Neodymium and its compounds can accumulate in the human body through exposure to air, soil, food and so on, leading to various toxic effects. However, research on the toxicity effects and mechanisms of neodymium is still limited. This review summarized the toxic effects of neodymium on the liver, lung, and other organs, and discussed its genotoxicity, reproductive toxicity, neurotoxicity, and impacts on the endocrine system. The aim is to provide references for revealing the toxic effects of long-term low-dose exposure to neodymium in occupational exposure and environmental pollution scenarios.

Traditional Chinese medicine (TCM) serves as a treasure trove of ancient knowledge, holding a crucial position in the medical field. However, the exploration of TCM's extensive information has been hindered by challenges related to data standardization, completeness, and accuracy, primarily due to the decentralized distribution of TCM resources. To address these issues, we developed a platform for TCM knowledge discovery (TCMKD, https://cbcb.cdutcm.edu.cn/TCMKD/). Seven types of data, including syndromes, formulas, Chinese patent drugs (CPDs), Chinese medicinal materials (CMMs), ingredients, targets, and diseases, were manually proofread and consolidated within TCMKD. To strengthen the integration of TCM with modern medicine, TCMKD employs analytical methods such as TCM data mining, enrichment analysis, and network localization and separation. These tools help elucidate the molecular-level commonalities between TCM and contemporary scientific insights. In addition to its analytical capabilities, a quick question and answer (Q&A) system is also embedded within TCMKD to query the database efficiently, thereby improving the interactivity of the platform. The platform also provides a TCM text annotation tool, offering a simple and efficient method for TCM text mining. Overall, TCMKD not only has the potential to become a pivotal repository for TCM, delving into the pharmacological foundations of TCM treatments, but its flexible embedded tools and algorithms can also be applied to the study of other traditional medical systems, extending beyond just TCM.

Objective To evaluate the prognostic value of serum tissue factor pathway inhibitor-1(TFPI-1)combined with nuclear factor-κB(NF-κB)in severe traumatic brain injury(STBI).Methods The medical re-cords of 127 patients with STBI admitted to the hospital from July 2022 to August 2024 were retrospectively ana-lyzed and followed up for 6 months.They were divided into poor prognosis group(n=53)and good prognosis group(n=74)according to the prognosis of STBI patients.The serum NF-κB level,clinical data and serum TFPI-1 level of the two groups were compared.The factors affecting the adverse prognosis of STBI patients was screened,and the value of serum NF-κB and serum TFPI-1 in predicting the adverse prognosis of STBI patients were ana-lyzed.Results The serum NF-κB level in the poor prognosis group was higher than good prognosis group,and the serum TFPI-1 level was lower than good prognosis group(P<0.05).The proportion of patients aged>60 years old was higher than good prognosis group(P<0.05).Serum TFPI-1 level(OR=0.328,95%CI:0.156～0.689)was a protective factor for poor prognosis in STBI patients(P<0.05),serum NF-κB level(OR=3.773,95%CI:1.797～7.924)and age>60 years(OR=3.543,95%CI:1.687～7.441)were independent risk factors for poor prognosis in STBI patients(P<0.05).The area under the curve(AUC)of serum TFPI-1 and NF-κB levels and their combined prediction of poor prognosis in STBI patients were 0.784,0.847 and 0.931,respectively(P<0.05),and the AUC value of the combined TFPI-1 and NF-κB levels was higher(P<0.05).Conclusion Serum NF-κB combined with serum TFPI-1 has higher prognostic value in STBI patients.

Objective:To explore the developmental trajectories of depression and their influencing factors among women conceiving through assisted reproductive technology (ART) from the beginning of the treatment cycle to late pregnancy.Methods:A convenience sampling method was used to recruit 863 women who successfully conceived through ART at the International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University between January 2017 and November 2019. Depressive symptoms were assessed using the Center for Epidemiological Studies Depression Scale (CES-D) at the beginning of the ART cycle (T1), early pregnancy (12-14 weeks, T2), mid-pregnancy (22-24 weeks, T3), and late pregnancy (32-34 weeks, T4). Group-based trajectory model was applied to identify developmental trajectories of antenatal depression, and multivariate Logistic regression was used to analyze influencing factors.Results:The detection rates of depressive symptoms among the 863 women conceiving through ART at T1, T2, T3, and T4 were 29.9% (258/863), 33.3% (287/863), 17.1% (148/863), and 19.8% (171/863), respectively. Three distinct trajectory groups were identified: persistently normal group (51.1%, 441/863), high-then-decreasing group (42.3%, 365/863), and persistently high-depression group (6.6%, 57/863). Multivariate Logistic regression analysis revealed that anxiety symptoms, sleep quality, spouse's age, passive smoking, and pre-pregnancy body mass index were significant influencing factors of the developmental trajectories of antenatal depression ( P<0.05) . Conclusions:Healthcare providers should pay close attention to antenatal depression in women conceiving through ART. Targeted interventions addressing the identified influencing factors should be developed to safeguard maternal and infant health.

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.