ObjectiveTo construct and validate a clinical prediction model for inflammatory remission outcomes in rheumatoid arthritis （RA） patients with liver and kidney deficiency syndrome treated with Bushen Zhiwang Decoction （补肾治尪汤， BZD） based on metabolomics. MethodsA prospective cohort study was conducted， enrol-ling 60 RA patients with liver and kidney deficiency syndrome. All patients were treated with BZD and conventional-dose oral conventional synthetic disease-modifying antirheumatic drugs （csDMARDs） for 12 months. Clinical data were collected， and the change in disease activity score in 28 joints （DAS28） after treatment compared with baseline （△DAS28） was used as the primary outcome and grouping criterion. Peripheral blood samples were collected before treatment to analyze plasma metabolites. Differential analysis and least absolute shrinkage and selection operator （LASSO） regression were used to preliminarily screen differential metabolites， followed by machine learning algorithms to further identify a core metabolite combination. Based on the expression levels of the core metabolite combination， a novel metabolite index， namely the metabolomics-based inflammatory remission score （Met-IRS）， was calculated using standar-dized metabolite values， and its clinical applicability was evaluated. A clinical prediction model was constructed by integrating clinical characteristics and Met-IRS， and the model performance was assessed. ResultsAmong the 60 patients， those with △DAS28 ≥ 0.27 were assigned to the high inflammatory remission group， while those with △DAS28 ＜ 0.27 were assigned to the low inflammatory remission group， with 30 cases in each group. Compared to the low inflammatory remission group， the high inflammatory remission group showed a higher frequency of methotrexate use and a lower positive rate of rheumatoid factor （RF） （P＜0.05）. Seven core metabolites were identified as the optimal combination， including mangiferic acid， fatty acid-hydroxy fatty acid ester 40∶6， fatty acid-hydroxy fatty acid ester 18∶0， fatty acid-hydroxy fatty acid ester 36∶1， glucosylceramide， lysophosphatidylcholine 22∶5， and pregnanetriol ketone. The calculated Met-IRS comprehensively reflected the characteristics of differential metabolites and demonstrated clinical applicability. Met-IRS was significantly higher in the high inflammatory remission group than in the low inflammatory remission group， and was positively correlated with high inflammatory remission outcomes （P＜0.05）. Based on the variables Met-IRS， methotrexate use， leflunomide use， and RF positivity， a clinical prediction model for inflammatory remission in RA treatment （Cj-RTRM） was constructed. Model performance evaluation demonstrated that the model had good clinical predictive ability， with an area under the receiver operating characteristic curve （AUC） of 0.880， sensitivity 0.967， specificity 0.700 and Youden's index 0.667. ConclusionThe clinical prediction model Cj-RTRM constructed based on the metabolomics-based inflammatory remission score Met-IRS can effectively predict clinical inflammatory remission outcomes in RA patients treated with BZD and accurately identify the advantageous population for this treatment. This model provides guiding evidence for dynamic inflammation monitoring， targeted management， and identification of populations with advantages in traditional Chinese medicine.

Fusarium head blight (FHB), caused by Fusarium graminearum, not only leads to severe yield losses but also poses a threat to food safety due to the mycotoxins produced by the pathogen. Since this disease is preventable but not curable, the current control mainly relies on chemical fungicides, the long-term use of which may lead to pathogen resistance and environmental pollution. To develop green control methods, we screened 13 biocontrol strains from the rhizosphere soil of wheat, among which strain No. 12 (identified as Pythium aphanidermatum) showed significant antifungal effects. In the plate confrontation test, this strain reduced the colony diameter of the pathogen by 69.2% (1.47 mm vs. 4.78 mm in the control group), with an inhibition rate of 77% (P < 0.01). Microscopic observation revealed obvious deformations in the pathogen hyphae, suggesting a lysing effect. The coleoptile experiment further confirmed that the pre-treatment with this strain reduced the incidence rate to 0. These findings provide new candidate strains for the biocontrol of FHB and offer a scientific basis for reducing the use of chemical fungicides and promoting sustainable agricultural development.
Triticum/growth & development* ; Fusarium/growth & development* ; Plant Diseases/prevention & control* ; Soil Microbiology ; Pest Control, Biological/methods* ; Pythium/physiology* ; Biological Control Agents ; Rhizosphere ; Fungicides, Industrial

Acute-on-chronic liver failure （ACLF） is a complex clinical syndrome， and early identification and accurate prognostic evaluation are of great importance for patient treatment and management. In recent years， with in-depth research on the pathogenesis of ACLF， multiple prognostic biomarkers have been proposed and used in clinical practice. This article systematically reviews the research advances in prognostic biomarkers for ACLF from the aspects of clinical predictive models， immunological biomarkers， metabolic biomarkers， genetic and epigenetic biomarkers， microbiome-related biomarkers， and emerging technologies such as artificial intelligence and multi-omics， and it also discusses the value and application prospects of these biomarkers in the prognostic evaluation of ACLF and proposes future research directions， in order to provide a scientific and comprehensive reference for clinicians， guide individualized treatment and management of ACLF patients， and finally improve the clinical outcomes of patients.

Objective:To evaluate the clinical value of an obstetric intelligent assistant in predicting postpartum hemorrhage (PPH) after vaginal delivery.Methods:This retrospective cohort study included 4 832 women who delivered vaginally at ≥26 weeks of gestation at the Third Affiliated Hospital, Guangzhou Medical University between May 2023 and April 2025. Participants were categorized into PPH (382 cases, blood loss ≥500 ml within 24 h after delivery) and non-PPH groups (4 450 cases). Using traditional statistical methods combined with machine learning approaches, including support vector machines and extreme gradient boosting, supplemented with deep learning techniques, we developed a novel artificial neural network model—the obstetric intelligent assistant. This model provides a refined classification of PPH occurrence and estimated blood loss volume. The obstetric intelligent assistant integrates 70 antenatal and intrapartum risk factors through hospital information system interfacing to generate visualized risk probability outputs. Predictive performance was compared between the obstetric intelligent assistant and four conventional prediction tools (Chinese Labor Room Traffic Light System; Association of Women's Health, Obstetric and Neonatal Nurses; American College of Obstetrics and Gynecology Safe Motherhood Initiative; and California Maternal Quality Care Collaborative prediction tools) using receiver operating characteristic curve.Results:(1) For antenatal prediction, the obstetric intelligent assistant achieved an area under the curve of 0.826 (95% CI: 0.774-0.838), with sensitivity of 0.794 and specificity of 0.712, while the four conventional prediction tools showed area under the curve ranging from 0.569 to 0.586. (2) For intrapartum prediction, the obstetric intelligent assistant achieved an area under the curve of 0.786 (95% CI: 0.751-0.820), with sensitivity of 0.837 and specificity of 0.762, whereas the conventional tools showed area under the curve between 0.600 and 0.613. Conclusion:The obstetric intelligent assistant demonstrates superior performance in predicting PPH compared to conventional prediction tools.

Hepatitis B virus（HBV）infection poses a significant global health burden，with chronic infection driving progression to cirrhosis，hepatic failure，and hepatocellular carcinoma（HCC）. Mounting evidence implicates immune dysfunction and microbiota dysbiosis as core drivers of disease progression across all HBV infection stages. Gut and tissue-specific microbiota alterations disrupt innate/adaptive immunity，fueling inflammation，immunosuppression，and tumor immune evasion in chronic and end-stage disease. This review synthesizes mechanisms of immune-microbiota interplay in HBV pathogenesis and explores their translational potential for diagnostics and targeted interventions，including microbiota modulation and microbial biomarker applications.

Objective:To evaluate the clinical value of an obstetric intelligent assistant in predicting postpartum hemorrhage (PPH) after vaginal delivery.Methods:This retrospective cohort study included 4 832 women who delivered vaginally at ≥26 weeks of gestation at the Third Affiliated Hospital, Guangzhou Medical University between May 2023 and April 2025. Participants were categorized into PPH (382 cases, blood loss ≥500 ml within 24 h after delivery) and non-PPH groups (4 450 cases). Using traditional statistical methods combined with machine learning approaches, including support vector machines and extreme gradient boosting, supplemented with deep learning techniques, we developed a novel artificial neural network model—the obstetric intelligent assistant. This model provides a refined classification of PPH occurrence and estimated blood loss volume. The obstetric intelligent assistant integrates 70 antenatal and intrapartum risk factors through hospital information system interfacing to generate visualized risk probability outputs. Predictive performance was compared between the obstetric intelligent assistant and four conventional prediction tools (Chinese Labor Room Traffic Light System; Association of Women's Health, Obstetric and Neonatal Nurses; American College of Obstetrics and Gynecology Safe Motherhood Initiative; and California Maternal Quality Care Collaborative prediction tools) using receiver operating characteristic curve.Results:(1) For antenatal prediction, the obstetric intelligent assistant achieved an area under the curve of 0.826 (95% CI: 0.774-0.838), with sensitivity of 0.794 and specificity of 0.712, while the four conventional prediction tools showed area under the curve ranging from 0.569 to 0.586. (2) For intrapartum prediction, the obstetric intelligent assistant achieved an area under the curve of 0.786 (95% CI: 0.751-0.820), with sensitivity of 0.837 and specificity of 0.762, whereas the conventional tools showed area under the curve between 0.600 and 0.613. Conclusion:The obstetric intelligent assistant demonstrates superior performance in predicting PPH compared to conventional prediction tools.

Hepatitis B virus（HBV）infection poses a significant global health burden，with chronic infection driving progression to cirrhosis，hepatic failure，and hepatocellular carcinoma（HCC）. Mounting evidence implicates immune dysfunction and microbiota dysbiosis as core drivers of disease progression across all HBV infection stages. Gut and tissue-specific microbiota alterations disrupt innate/adaptive immunity，fueling inflammation，immunosuppression，and tumor immune evasion in chronic and end-stage disease. This review synthesizes mechanisms of immune-microbiota interplay in HBV pathogenesis and explores their translational potential for diagnostics and targeted interventions，including microbiota modulation and microbial biomarker applications.

Objective: To provide high-quality clinical evidence of the efficacy of Tibetan medicine Honghua Ruyi (HHRY) pills for endometriosis-associated dysmenorrhea. Methods: This study constitutes a multicenter, randomized, double-blind, placebo-controlled trial encompassing a three-menstrual cycle intervention followed by a three-menstrual cycle follow-up period. A total of 164 eligible females with endometriosis-associated dysmenorrhea were randomly divided into HHRY pills and placebo groups in a 1:1 ratio. The primary outcome included dysmenorrhea symptoms assessed using Visual Analog Scale (VAS) scores and quality of life, whereas the secondary outcome measures included the maximum VAS for non-menstrual pelvic pain, duration of pain episodes (in days), frequency and quantity of the consumption of ibuprofen sustained-release capsules (or other non-steroidal anti-inflammatory drugs), and days off work/study for staff/student due to dysmenorrhea, ovarian cyst, and/or pelvic nodule size. The safety was monitored throughout the treatment period. All the analyses were based on the intention-to-treat principle. For continuous outcomes, simple or multiple linear regressions were used to estimate the differences between the HHRY pills and placebo groups, with categorical data expressed as the number and percentage of occurrences. Differences were compared using the chi-square test or Fisher's exact test. The predefined analysis was adjusted for concomitant treatment, a variable considered to be associated with outcomes but unaffected by treatment allocation. Estimates of treatment effects were reported with 95% confidence intervals. Two-tailed P values ≤ .05 were considered statistically significant. Conclusion Positive results from this trial, upon completion would provide robust evidence for the efficacy and safety of HHRY pills in treating dysmenorrhea in patients with endometriosis.

OBJECTIVE To investigate the mechanism of anti-colorectal cancer growth and metastasis-related effects of Astraga-lus mongholicus Bunge-Curcuma aromatica-Paridis Rhizoma(Qi-Zhu-Zao)pairing through PERK/eIF2α/ATF4 signaling pathway mediating endoplasmic reticulum stress.METHODS Twenty-four BALB/c male mice were randomly divided into sham-operated group,model group,5-FU(5-fluorouracil)group(25 mg·kg-1),and Qi-Zhu-Zao high dose group(5.85 g·kg-1),Qi-Zhu-Zao low dose group(2.925 g·kg-1)(n=6)to construct a mouse model of colorectal cancer in situ transplantation tumor,and the inter-vention effect of Qi-Zhu-Zao combination on tumor growth was assessed by the change of tumor volume size after 15 days of administra-tion;the intervention effect of Qi-Zhu-Zao combination on tumor growth was assessed by H&E.Pathological staining was used to eval-uate the effect of Qi-Zhu-Zao combination on the liver and tumor tissues of mice.The changes of MDA,SOD and GSH-Px levels were detected by enzyme-linked immunosorbent assay(ELISA);the expression of PERK/eIF2α/ATF4 signaling pathway and EMT-related proteins were detected by protein immunoblotting(Western blot).RESULTS Compared with the model group,the tumor volume was significantly reduced(P＜0.000 1),liver and spleen metastases were less pronounced in the Qi-Zhu-Zao high-dose group,and his-topathological staining results of liver tissue and tumor produced changes in oxidative stress indicators SOD,MDA,and GSH-Px,up-regulation of ER stress-related proteins p-PERK,p-IF2α,and ATF4,etc.,upregulated the protein expression levels of E-Cadherin,downregulated N-Cadherin,Vimentin,and Snail,and inhibited the EMT process(P＜0.01 or P＜0.05).CONCLUSION In this paper,we investigated the regulatory mechanism related to the inhibition of colorectal cancer growth and metastasis by the combination of Qi-Zhu-Zao trigonal medicine,and demonstrated that it may inhibit the growth and metastasis of colorectal cancer by activating the PERK/eIF2α/ATF4 pathway to induce sustained ER stress and affect the EMT process of colorectal cancer.

Objective:To explore the expression levels and the clinical significance of serum secreted frizzled-related protein 5 (SFRP5) and miR-124-3p in patients with hypertension during pregnancy.Methods:Ninety-eight patients with hypertension during pregnancy diagnosed from Jan. 2019 to Feb. 2022 were selected as the observation group. According to the degree of the condition of patients, they were divided into 41 cases of pregnancy hypertension, 32 cases of mild preeclampsia, and 25 cases of severe preeclampsia, and 80 healthy subjects during the same period were selected as the control group. Enzyme-linked immunosorbent assay (ELISA) was used to detect the expression level of serum SFRP5 in patients, real-time fluorescence quantitative method (qRT-PCR) was used to detect the expression level of miR-124-3p. The relationship between SFRP5, miR-124-3p levels and clinicopathological indicators in patients with hypertension in pregnancy was analyzed, Pearson correlation analysis was used to analyze the correlation between SFRP5 and miR-124-3p. Multivariate Logistic regression was used to analyze the risk factors of hypertension in pregnancy.Results:Compared with the control group, the serum SFRP5 expression level of the observation group [ (33.78±5.21) ng/L vs (43.34±8.56) ng/L] was down-regulated, while the miR-124-3p level [ (2.16±0.41) vs (1.01±0.17) ] was up-regulated, and the serum SFRP5 level of the observation group decreased with the severity of the disease[ (38.43±6.37) ng/L (33.18±5.14) ng/L (26.94±3.38) ng/L], while the level of miR-124-3p increased with the severity of the disease[ (1.62±0.24) (2.19±0.43) (3.01±0.69) ], the difference was statistically significant ( P<0.05) . The expression levels of SFRP5 and miR-124-3p in the serum of patients with hypertension in pregnancy were related to the age, pregnancy, pre-pregnancy BMI, and fasting blood glucose level of patients ( P<0.05) , but not related to the gestational age of patients ( P>0.05) . Bioinformatics TargetScan website showed that SFRP5 and miR-124-3p had binding sites. Pearson correlation analysis showed that SFRP5 and miR-124-3p were negatively correlated ( r=-0.610, P<0.05) . Multivariate Logistic regression analysis showed that SFRP5 was a protective factor for pregnancy-induced hypertension in pregnant women, and miR-124-3p was a risk factor ( P<0.05) . Conclusion:The serum levels of SFRP5 and miR-124-3p are abnormally expressed in patients with hypertension during pregnancy, and there is a certain relationship with the degree of disease. Both are involved in the occurrence and development of hypertension during pregnancy.