To study the differences in transcript levels among different organs of Spatholobus suberectus and to explore the genes encoding enzymes related to the catechin biosynthesis pathway, this study utilized the genome and full-length transcriptome data of S. suberectus as references. Transcriptome sequencing and bioinformatics analysis were performed on five different organs of S. suberectus-roots, stems, leaves, flowers, and fruits-using the Illumina NovaSeq 6000 platform. A total of 115.28 Gb of clean data were obtained, with GC content values ranging from 45.19% to 47.54%, Q20 bases at 94.17% and above, and an overall comparison rate with the reference genome around 90%. In comparisons between the stem and root, stem and leaf, stem and flower, and stem and fruit, 10 666, 9 674, 9 320, and 5 896 differentially expressed genes(DEGs) were identified, respectively. The lowest number of DEGs was found in the stem and root comparison group. KEGG enrichment analysis revealed that the DEGs were mainly concentrated in the pathways of phytohormone signaling, phenylalanine biosynthesis, etc. A total of 39 genes were annotated in the catechin biosynthesis pathway, with at least one highly expressed gene found in all organs. Among these, PAL1, PAL2, C4H1, C4H3, 4CL1, 4CL2, and DFR2 showed high expression in the stems, suggesting that they may play important roles in the biosynthesis of flavonoids in S. suberectus. This study aims to provide important information for the in-depth exploration of the regulation of catechin biosynthesis in S. suberectus through transcriptome analysis of its different organs and to provide a reference for the further realization of S. suberectus varietal improvement and molecular breeding.
Catechin/biosynthesis* ; Gene Expression Profiling ; Gene Expression Regulation, Plant ; Plant Proteins/metabolism* ; Fabaceae/metabolism* ; Transcriptome ; Flowers/metabolism* ; Plant Stems/metabolism* ; Plant Leaves/metabolism* ; Plant Roots/metabolism* ; Fruit/metabolism*

This study aims to explore the effects and action mechanisms of the active ingredients in Buyang Huanwu Decoction(BYHWD), namely tetramethylpyrazine(TMP) and hydroxy-safflor yellow A(HSYA), on oxygen-glucose deprivation/reglucose-reoxygenation(OGD/R)-induced inflammation and oxidative stress of microglia(MG). Network pharmacology was used to screen the effective monomer ingredients of BYHWD and determine the safe concentration range for each component. Inflammation and oxidative stress models were established to further screen the best ingredient combination and optimal concentration ratio with the most effective anti-inflammatory and antioxidant effects. OGD/R BV2 cell models were constructed, and BV2 cells in the logarithmic growth phase were divided into a normal group, a model group, an HSYA group, a TMP group, and an HSYA + TMP group. Enzyme-linked immunosorbent assay(ELISA) was used to detect the levels of inflammatory cytokines such as interleukin-1β(IL-1β), tumor necrosis factor-α(TNF-α), and interleukin-6(IL-6). Oxidative stress markers, including superoxide dismutase(SOD), nitric oxide(NO), and malondialdehyde(MDA), were also measured. Western blot was used to analyze the protein expression of both inflammation-related pathway [Toll-like receptor 4(TLR4)/nuclear factor-kappa B(NF-κB)] and oxidative stress-related pathway [nuclear factor erythroid 2-related factor 2(Nrf2)/heme oxygenase-1(HO-1)]. Immunofluorescence was used to assess the expression of proteins such as inducible nitric oxide synthase(iNOS) and arginase-1(Arg-1). The most effective ingredients for anti-inflammatory and antioxidant effects in BYHWD were TMP and HSYA. Compared to the normal group, the model group showed significantly increased levels of IL-1β, TNF-α, IL-6, NO, and MDA, along with significantly higher protein expression of NF-κB, TLR4, Nrf2, and HO-1 and significantly lower SOD levels. The differences between the two groups were statistically significant. Compared to the model group, both the HSYA group and the TMP group showed significantly reduced levels of IL-1β, TNF-α, IL-6, NO, and MDA, lower expression of NF-κB and TLR4 proteins, higher levels of SOD, and significantly increased protein expression of Nrf2 and HO-1. Additionally, the expression of the M1-type MG marker iNOS was significantly reduced, while the expression of the M2-type MG marker Arg-1 was significantly increased. The results of the HSYA group and the TMP group had statistically significant differences from those of the model group. Compared to the HSYA group and the TMP group, the HSYA + TMP group showed further significant reductions in IL-1β, TNF-α, IL-6, NO, and MDA levels, along with significant reductions in NF-κB and TLR4 protein expression, an increase in SOD levels, and elevated Nrf2 and HO-1 protein expression. Additionally, the expression of the M1-type MG marker iNOS was reduced, while the M2-type MG marker Arg-1 expression increased significantly in the HSYA + TMP group compared to the TMP or HSYA group. The differences in the results were statistically significant between the HSYA + TMP group and the TMP or HSYA group. The findings indicated that the combined use of HSYA and TMP, the active ingredients of BYHWD, can effectively inhibit OGD/R-induced inflammation and oxidative stress of MG, showing superior effects compared to the individual use of either component.
Oxidative Stress/drug effects* ; Drugs, Chinese Herbal/pharmacology* ; Animals ; Mice ; Glucose/metabolism* ; Cell Line ; Inflammation/genetics* ; Oxygen/metabolism* ; Pyrazines/pharmacology* ; Microglia/metabolism* ; NF-E2-Related Factor 2/immunology* ; NF-kappa B/immunology* ; Toll-Like Receptor 4/immunology* ; Anti-Inflammatory Agents/pharmacology* ; Humans

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

BACKGROUND:Knee osteoarthritis(KOA)is a common chronic inflammatory disease that causes damage to joint cartilage and surrounding tissues.Immune cells play an important role in the immune-inflammatory response in knee osteoarthritis,but the specific mechanisms involved are still not fully understood. OBJECTIVE:To evaluate the potential causal relationship between 731 immune cell phenotypes and the risk of knee osteoarthritis using Mendelian randomization. METHODS:Summary statistics of genome-wide association studies(GWAS)for 731 immune cell phenotypes(from GCST0001391 to GCST0002121)obtained from the GWAS catalog and GWAS data for knee osteoarthritis from the IEUGWAS database(ebi-a-GCST007090)were used.Inverse variance-weighted method,MR-Egger regression,weighted median method,weighted mode method,and simple mode method were employed to investigate the causal relationship between immune cells and knee osteoarthritis.Sensitivity analyses were conducted to assess the reliability of the Mendelian randomization results.Reverse Mendelian randomization analysis was also performed using the same methods. RESULTS AND CONCLUSION:The forward MR analysis indicated significant causal relationships(FDR<0.20)between knee osteoarthritis and four immune cell phenotypes,namely CD27 on CD24+CD27+in B cells(OR=1.026,P=0.000 26,Pfdr=0.18),CD33 on CD33dim HLA DR-in myeloid cells(OR=1.014,P=0.000 50,Pfdr=0.18),and CD45RA+CD28-CD8br%CD8br in Treg cells(OR=1.001,P=0.000 78,Pfdr=0.18),and PDL-1 on monocytes in mononuclear cells(OR=0.952,P=0.000 98,Pfdr=0.18).These immune cell phenotypes showed direct positive or negative causal associations with the risk of knee osteoarthritis.Reverse Mendelian randomization analysis revealed no significant causal relationships(FDR<0.20)between knee osteoarthritis as exposure and any of the 731 immune cell phenotypes.The results of sensitivity analysis show that the P-values of the Cochran's Q test and the MR-Egger regression method for bidirectional Mendelian randomization were both greater than 0.05,indicating that there is no significant heterogeneity and pleiotropy in the causal effect analysis between immune cell phenotypes and knee osteoarthritis.To conclude,there may be four potential causal relationships between immune cell phenotypes,such as CD27 on CD24+CD27+cells,CD33 on CD33dim HLA DR-cells,CD45RA+CD28-CD8br%CD8br cells,and PDL-1 on monocytes,and knee osteoarthritis.These findings provide valuable clues for studying the biological mechanisms of knee osteoarthritis and exploring early prevention and treatment strategies.They also offer new directions for the development of intervention drugs.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

ObjectiveTo preliminarily explore the active components and target pathways of Angelicae Sinensis Radix-Polygonati Rhizoma （ASR-PR） herb pair in the treatment of simple obesity through network pharmacology and molecular docking， and to verify and investigate its mechanism of action via animal experiments. MethodsThe chemical constituents and targets of ASR and PR were predicted using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）. Targets related to simple obesity were identified by retrieving the GeneCards， Online Mendelian Inheritance in Man （OMIM）， Pharmacogenomics Knowledgebase （PharmGKB）， and DisGeNET databases. The intersection of drug and disease targets was used to construct an active component-target network using Cytoscape software. This network was imported into the STRING database to construct a protein-protein interaction （PPI） network， and topological analysis was conducted to identify core genes. Gene Ontology （GO） analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis and mapping were performed using the DAVID database and the Microbioinformatics platform. AutoDock 1.5.7 software was used to perform molecular docking between the top five active components and core targets. An animal model of simple obesity was established by feeding C57BL/6J mice a high-fat diet. The mice were administered ASR （2.06 g·kg^-1）， PR （2.06 g·kg^-1）， or ASR-PR （4.11 g·kg^-1） for 10 weeks， while the model group received an equal volume of purified water by gavage. After the administration period， the mice were sacrificed to measure body fat weight and serum levels of total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein （HDL）， and low-density lipoprotein （LDL）. Hematoxylin-eosin （HE） staining was used to observe histopathological sections of liver and adipose tissue. Serum levels of leptin， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） were determined by enzyme-linked immunosorbent assay （ELISA）， and the mRNA expression levels of epidermal growth factor receptor （EGFR） and signal transducer and activator of transcription 3 （STAT3） in liver tissue were detected by real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsNetwork pharmacology and molecular docking results indicated that the treatment of simple obesity by ASR-PR may involve the regulation of protein expression of core targets EGFR and STAT3 by its main components MOL009760 （Siberian glycoside A_qt）， MOL003889 （methyl protodioscin_qt）， MOL009766 （resveratrol）， MOL006331 （4′，5-dihydroxyflavone）， and MOL004941 （baicalin）， thereby modulating the PI3K/Akt and JAK/STAT signaling pathways. The animal experiment results showed that compared with the normal group， the model group had significantly increased body weight， body fat weight， and serum levels of TG， TC， TNF-α， IL-6， and leptin （P<0.01）. EGFR mRNA expression was significantly elevated （P<0.05）， while STAT3 mRNA expression was significantly decreased （P<0.01）. Histological analysis revealed disordered hepatic architecture in the model group， with pronounced lipid vacuoles， cytoplasmic loosening， lipid accumulation， and steatosis. Adipocytes in white adipose tissue （WAT） and brown adipose tissue （BAT） of the model group exhibited markedly increased diameters， reduced cell counts per unit area， and irregular morphology. Compared with the model group， the ASR-PR group significantly reduced body weight， body fat weight， serum TC， IL-6， TNF-α， leptin levels， and EGFR mRNA expression （P<0.01）. TG levels were also significantly decreased （P<0.05）， while STAT3 mRNA expression was significantly increased （P<0.01）. Histopathological improvements included reduced size and number of hepatic lipid vacuoles and restoration of liver cell morphology toward that of the normal group. The diameter of adipocytes significantly decreased， and the number of adipocytes per unit area increased. ConclusionASR-PR may regulate the expression of key target proteins such as EGFR and STAT3 via its core active components， modulate the PI3K/Akt and JAK/STAT signaling pathways， repair damaged liver and adipose tissues， and thereby alleviate the progression of obesity in mice.

ObjectiveTo preliminarily explore the active components and target pathways of Angelicae Sinensis Radix-Polygonati Rhizoma （ASR-PR） herb pair in the treatment of simple obesity through network pharmacology and molecular docking， and to verify and investigate its mechanism of action via animal experiments. MethodsThe chemical constituents and targets of ASR and PR were predicted using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）. Targets related to simple obesity were identified by retrieving the GeneCards， Online Mendelian Inheritance in Man （OMIM）， Pharmacogenomics Knowledgebase （PharmGKB）， and DisGeNET databases. The intersection of drug and disease targets was used to construct an active component-target network using Cytoscape software. This network was imported into the STRING database to construct a protein-protein interaction （PPI） network， and topological analysis was conducted to identify core genes. Gene Ontology （GO） analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis and mapping were performed using the DAVID database and the Microbioinformatics platform. AutoDock 1.5.7 software was used to perform molecular docking between the top five active components and core targets. An animal model of simple obesity was established by feeding C57BL/6J mice a high-fat diet. The mice were administered ASR （2.06 g·kg^-1）， PR （2.06 g·kg^-1）， or ASR-PR （4.11 g·kg^-1） for 10 weeks， while the model group received an equal volume of purified water by gavage. After the administration period， the mice were sacrificed to measure body fat weight and serum levels of total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein （HDL）， and low-density lipoprotein （LDL）. Hematoxylin-eosin （HE） staining was used to observe histopathological sections of liver and adipose tissue. Serum levels of leptin， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） were determined by enzyme-linked immunosorbent assay （ELISA）， and the mRNA expression levels of epidermal growth factor receptor （EGFR） and signal transducer and activator of transcription 3 （STAT3） in liver tissue were detected by real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsNetwork pharmacology and molecular docking results indicated that the treatment of simple obesity by ASR-PR may involve the regulation of protein expression of core targets EGFR and STAT3 by its main components MOL009760 （Siberian glycoside A_qt）， MOL003889 （methyl protodioscin_qt）， MOL009766 （resveratrol）， MOL006331 （4′，5-dihydroxyflavone）， and MOL004941 （baicalin）， thereby modulating the PI3K/Akt and JAK/STAT signaling pathways. The animal experiment results showed that compared with the normal group， the model group had significantly increased body weight， body fat weight， and serum levels of TG， TC， TNF-α， IL-6， and leptin （P<0.01）. EGFR mRNA expression was significantly elevated （P<0.05）， while STAT3 mRNA expression was significantly decreased （P<0.01）. Histological analysis revealed disordered hepatic architecture in the model group， with pronounced lipid vacuoles， cytoplasmic loosening， lipid accumulation， and steatosis. Adipocytes in white adipose tissue （WAT） and brown adipose tissue （BAT） of the model group exhibited markedly increased diameters， reduced cell counts per unit area， and irregular morphology. Compared with the model group， the ASR-PR group significantly reduced body weight， body fat weight， serum TC， IL-6， TNF-α， leptin levels， and EGFR mRNA expression （P<0.01）. TG levels were also significantly decreased （P<0.05）， while STAT3 mRNA expression was significantly increased （P<0.01）. Histopathological improvements included reduced size and number of hepatic lipid vacuoles and restoration of liver cell morphology toward that of the normal group. The diameter of adipocytes significantly decreased， and the number of adipocytes per unit area increased. ConclusionASR-PR may regulate the expression of key target proteins such as EGFR and STAT3 via its core active components， modulate the PI3K/Akt and JAK/STAT signaling pathways， repair damaged liver and adipose tissues， and thereby alleviate the progression of obesity in mice.

OBJECTIVE To study the pharmacokinetic characteristics of ciprofol in pregnant and fetal rats， and provide reference for the application of ciprofol in cesarean section. METHODS Eight pregnant rats were selected. A single dose of 2.4 mg/kg of ciprofol was administered via the tail vein. One fetal rat was selected at 2， 4， 8， 12， 16， 25， 35， 45， 60， and 90 minutes respectively after ciprofol administration. Subsequently， whole blood samples were collected simultaneously from both the pregnant rats and fetal rats. HPLC-MS/MS method was used to determine the concentration of ciprofol in the bodies of pregnant and fetal rats. The ratios of fetal-to-maternal blood concentrations （F/M ratios） at each time point were calculated， and the F/M-time curves were plotted. Subsequently， non-compartmental pharmacokinetic parameters were computed using DAS 2.0 software. RESULTS Compared with pregnant rats， cmax， AUC0-90 min and AUC0-∞ of ciprofol in fetal rats were decreased significantly， while MRT was increased significantly （P＜0.05）. The F/M curve of ciprofol initially increased and then decreased， and between 0.16- 0.84， reaching a maximum value of 0.84 at 45 minutes. CONCLUSIONS Ciprofol can penetrate the placental barrier， and there are significant differences in pharmacokinetic parameters between pregnant and fetal rats. Moreover， the exposure level of ciprofol in fetal rats is much lower than that in pregnant rats. Therefore， ciprofol shows promise as an ideal anesthetic agent for cesarean section delivery.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.