The brain-gut interaction theory is a multidimensional integrative concept based on the brain-gut axis， involving neural， endocrine， and immune regulatory networks as well as the gut microbiota. Zang-fu organs （脏腑） theory in traditional Chinese medicine （TCM） shows a high degree of consistency with the brain-gut interaction theory， and the core functions such as the spleen and stomach governing the ascending of the clear and descending of the turbid， the liver governing the free flow of qi， and the heart governing mental and emotional activities are closely associated with the multi-level regulatory mechanisms of the brain-gut axis. TCM therapy can modulate brain-gut interactions through multiple pathways in the treatment of spleen and stomach diseases， including the regulation of gastrointestinal hormone secretion， neurotransmitter levels， the hypothalamic-pituitary-adrenal （HPA） axis， immune homeostasis and inflammatory responses， as well as the gut microecology. However， current basic research on the brain-gut interaction theory in TCM for spleen and stomach diseases still faces several challenges， such as difficulties in integrating TCM spleen-stomach theory with modern pathophysiology， lack of innovation in research concepts， and limitations in research methodologies. It is therefore proposed that multidisciplinary collaboration， multi-omics technologies， and targeted research approaches should be adopted to provide more comprehensive methods for basic research on TCM spleen and stomach diseases， thereby promoting the in-depth development of brain-gut interaction theory.

ObjectiveTo investigate the inhibitory effects and mechanisms of Yupingfeng San （YPFS） on high-mobility group box protein 1 （HMGB1）-induced angiogenesis in liver cancer. MethodsAn orthotopic liver cancer model was established in 30 C57BL/6 mice. The mice were randomly divided into a model group， YPFS low-， medium-， and high-dose groups （20， 30， 40 g·kg^-1， respectively）， a positive control group （sorafenib， 10 mg·kg^-1）， and a normal control group. After 14 days of medication， tumor and adjacent tissues were harvested. Tumor inhibition rates were calculated based on tumor weight. Microvascular density was determined via immunohistochemistry. HMGB1 and vascular endothelial growth factor （VEGF） expression levels were determined using immunofluorescence. An HMGB1-induced human umbilical vein endothelial cell （HUVEC） proliferation model was established， and cell proliferation was evaluated by a methylthiazolyldiphenyl-tetrazolium bromide （MTT） assay. HUVECs were randomly divided into a blank group， a model group （HMGB1 800 μg·L^-1）， along with YPFS low-， medium-， and high-dose groups （HMGB1 800 μg·L^-1 + YPFS 10， 30， 50 g·L^-1， respectively）. HUVEC migration ability was evaluated via a scratch assay and a Trans well chamber assay. Tube formation ability was detected by a tube formation assay. Microvascular sprouting ability was evaluated by an aortic ring assay. Furthermore， RAGE/MEK1/2/ERK1/2 pathway-related protein expression in HUVECs was measured using Western blot （WB）. ResultsCompared with the model group， all three doses of YPFS significantly reduced tumor weight in mice with orthotopic liver cancer （P<0.01）， with inhibition rates of 31.49% ± 8.27%， 49.60% ± 3.77%， and 56.81% ± 9.70%， respectively. Also， YPFS significantly decreased microvascular density in tumor and adjacent tissues （P<0.05）， as well as VEGF and HMGB1 expression levels （P<0.01）. Compared with the blank group， HMGB1 promoted HUVEC proliferation， migration， tube formation， and microvascular sprouting in aortic rings （P<0.05）. After YPFS administration， the HMGB1-induced proliferation rate， migration rate， number of tube formations， and microvascular sprouting in aortic rings were significantly reduced compared with the model group （P<0.01）. Additionally， YPFS downregulated receptor for advanced glycation end products （RAGE）， mitogen-activated protein kinase kinase 1/2 （MEK1/2）， phosphorylated MEK1/2 （p-MEK1/2）， extracellular signal-regulated kinase 1/2 （ERK1/2）， and phosphorylated ERK1/2 （p-ERK1/2） protein expression in HMGB1-induced HUVECs （P<0.01）. ConclusionYPFS exerts anti-angiogenic effects against HMGB1 induction by suppressing the RAGE/MEK/ERK signaling pathway， thereby inhibiting liver cancer tumor growth.

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.

ObjectiveTo analyze the pharmacodynamic activity of Bupleuri Radix processed with Trionyx sinensis blood in the treatment of Yin deficiency and study the spectrum-effect relationship of this medicine. MethodsHigh performance liquid chromatography was employed to establish the fingerprints of 15 batches of Bupleuri Radix processed with Trionyx sinensis blood， and the similarity was evaluated according to the SOP of Similarity Evaluation System of Chromatographic Fingerprint of TCM （version 2012）. A mouse model of Yin deficiency induced by thyroxine was established. The relationship between the active components and the effect on Yin deficiency was explored by grey correlation analysis and partial least squares method based on the changes in the serum levels of triiodothyronine （T3）， thyroxine （T4）， cyclic adenosine phosphate （cAMP）， and cyclic guanosine phosphate （cGMP）. The components screened out based on the spectrum-effect relationship were used for retrieval of the targets from the Traditional Chinese Medicine Systems Pharmacology and Analysis Database （TCMSP）， The Encyclopedia of Traditional Chinese Medicine （ETCM）， and Integrative Pharmacology-based Research Platform of Traditional Chinese Medicine （TCMIP）. Furthermore， the Online Mendelian Inheritance in Man （OMIM）， GeneCards， TTD， DisGeNET， and Drugbank were employed to establish the active component-target against Yin deficiency network of Bupleuri Radix processed with Trionyx sinensis blood. Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analyses were carried out for the core targets. Real-time PCR was conducted to verify the predicted key pathways and mechanisms. ResultsThe fingerprints of the 15 batches of Bupleuri Radix processed with Trionyx sinensis blood showed the similarities of 0.976-0.999 with the control fingerprint. Compared with the model group， the drug administration group showed elevated levels of T3 and T4 and lowered levels of cAMP， cGMP and cAMP/cGMP. The results of grey correlation analysis showed that active components in terms of the correlations followed the trend of saikosaponin B₁ > saikosaponin B₂ > saikosaponin C > saikosaponin D > saikosaponin A. The partial least squares analysis showed that saikosaponins A， D， B₁， and B₂ had higher VIP values. Network pharmacology predicted a total of 30 common targets， which were enriched in 276 GO terns and 115 KEGG pathways. The results of Real-time PCR showed that the model group had lower mRNA levels of Caspase-9， kinase insert domain receptor （KDR）， and mammalian target of rapamycin （mTOR） and higher mRNA level of mouse double minute 2 homolog （MDM2） than the blank group and the drug administration group. ConclusionBupleuri Radix processed with Trionyx sinensis blood has therapeutic effect on Yin deficiency syndrome， which provides a new idea for studying Bupleuri Radix processed with Trionyx sinensis blood.

Three taraxerane nortriterpenoids were isolated from mastic by using various modern chromatographic separation techniques. They were identified as(5R,8R,9R,10S,11S,12R,13S,17R,18R)-28-norlupa-11,12-epoxy-14-taraxerene-3,16-dione(1),(5R,8R,9R,10S,11S,12R,13S,17S,18S)-17-hydroxy-28-norlupa-11,12-epoxy-14-taraxerene-3-one(2), and(5R,8R,9R,10R,11S,12R,13R,14S,17S,18S)-14,17-epoxy-28-norlupa-11,12-oxidotaraxerone(3) through the high-resolution electrospray ionization mass spectrometry(HR-ESI-MS), infrared(IR), ultraviolet(UV), nuclear magnetic resonance(NMR), and single-crystal X-ray diffraction techniques as well as comparison with literature data. Compounds 1-3 were C-28 nortriterpenoids and isolated from mastic for the first time, and compounds 1-2 were new ones. In the model for RAW264.7 cell anti-inflammation induced by lipopolysaccharide(LPS), compound 1 demonstrates an inhibitory effect on nitric oxide(NO) [IC_(50)=(13.38±0.68) μmol·L~(-1)], comparable to the activity of the positive control dexamethasone [IC_(50)=(14.59±1.49) μmol·L~(-1)]. Compounds 2 and 3 exhibit weaker inhibitory effects, with IC_(50) values of(24.17±2.56) and(22.25±2.84) μmol·L~(-1), respectively.
Animals ; Mice ; Triterpenes/isolation & purification* ; Drugs, Chinese Herbal/isolation & purification* ; Mastic Resin/chemistry* ; Nitric Oxide ; Molecular Structure ; Macrophages/immunology* ; RAW 264.7 Cells

Objective: To evaluate the effect of exercise prescription intervention among patients with type 2 diabetes mellitus (T2DM), so as to provide the evidence for guiding appropriate physical activity and glycemic control in this population. Methods: In July 2023, T2DM patients managed by two community health service centers in Qingjiangpu District, Huai'an City, Jiangsu Province, were selected as the study participants and randomly assigned divided into a control group and an intervention group. The control group received routine chronic disease management under the basic public health services, while the intervention group, in addition to receiving the same routine chronic disease management, was provided with exercise prescription to guide their physical activity at baseline (T0), after 3 months of intervention (T1), and after 6 months of intervention (T2). Data on weight-related indicators, glycated hemoglobin (HbA1c), and blood lipid were collected through physical examinations and laboratory tests at T0 and after 12 months of intervention (T3). The differences in indicators between the two groups before and after the intervention were analyzed using generalized estimating equations. Results: The intervention group consisted of 197 patients, including 99 males, accounting for 50.25%. The median disease duration was 7.10 (interquartile range, 7.80) years, and 113 patients had suboptimal HbA1c levels, accounting for 57.36%. The control group included 196 patients, including 99 females, accounting for 50.51%. The median disease duration was 6.10 (interquartile range, 7.00) years, and 100 patients had suboptimal HbA1c levels, accounting for 51.02%. Before the intervention, no statistically significant differences were observed between the two groups in gender, educational level, disease duration, pharmacological treatment, smoking, alcohol consumption, and HbA1c levels (all P>0.05). In the intervention group, the proportion of participants engaging in aerobic exercise and strength training increased from 78.17% and 8.12% at T0 to 85.79% and 16.24% at T3, respectively (both P<0.05). The results of the generalized estimating equations revealed significant interactions between group and time for waist-to-hip ratio, total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-C) following the intervention (all P<0.05). A statistically significant difference in waist-to-hip ratio was found between the two groups (P<0.05), with a greater reduction observed in the intervention group compared to the control group. Significant differences in TC and LDL-C levels were noted across different intervention time points (both P<0.05). Specifically, the intervention group demonstrated reductions of 0.35 mmol/L in TC and 0.42 mmol/L in LDL-C from baseline to follow-up (both P<0.05). Conclusion The 12-month exercise prescription intervention can effectively enhance exercise participation and reduce waist-to-hip ratio, TC, and LDL-C levels among patients with T2DM.

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.

Iodine speciations in aquatic environments are affected by dissolved oxygen,redox potential,microbial activity,organic matter decomposition,light reaction,etc.Accurate quantification of iodine speciation can not only help to understand the geochemical cycle of iodine,but also help to trace and study environmental processes.Based on the combination of ion chromatography(IC)and inductively coupled plasma mass spectrometry(ICP-MS),a rapid and sensitive method was established for determining the speciations of iodine in environmental water samples including seawater,river water,lake water,rainwater,groundwater,etc.The results presented here showed that IO3?and I?in seawater were quickly separated and measured within 120 s when using guard column AG22 and 8 mmol/L(NH4)2CO3 as the mobile phase.While for lake water,river water and precipitation samples with high soluble organically bond iodine(SOI),an AS22 separation column(250 mm×4 mm)connected with a guard column and using 50 mmol/L(NH4)2CO3 as mobile phase could effectively separate unknown SOI from IO3? to achieve accurate quantification of IO3?.For accurate correction of iodine measurement signal fluctuations,133Cs was directly added to the(NH4)2CO3 mobile phase as an internal standard.The SOI content was calculated by the total iodine concentrations minus the sum of IO3?and I?.The precision of the established iodine speciation analytical method was better than 3.5%,and the standard addition experiment showed that the analytical method was accurate.When the injection volume was 25 μL,the detection limits were 0.011?0.025 μg/L for IO3? and 0.023?0.031 μg/L for I?,respectively.The method was successfully used to analyze IO3?,SOI and I? in environmental water samples,such as seawater,river water,rainwater and groundwater.

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.