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.

Haloacetic acids(HAAs),as a class of disinfection byproducts in drinking water,pose potential threats to human health,so the rapid,accurate and simultaneous detection of HAAs is of great significance for ensuring drinking water safety.Aiming at the challenges in HAAs detection and risk analysis,a novel method for synchronous rapid detection of seven kinds of HAAs in drinking water based on in situ derivatization technology and headspace gas chromatography was developed in this study.Through single-factor optimization experiments,the optimal reaction parameters for in situ derivatization were determined,including the type and dosage of salting-out agent,the acidity of reaction system,the amount of phase transfer catalyst,the dosage of derivatization agent,and the extraction solvent volume.Methodologic validation showed that the seven kinds of HAAs exhibited excellent linear relationships within their respective detection concentration ranges(R2>0.998).The method detection limits(MDLs)ranged from 0.04 to 0.33 μg/L,and the limits of quantification(LOQs)were between 0.14 and 1.34 μg/L.For real water samples,the average spiked recoveries of the seven HAAs ranged from 90.9%to 107.7%,with relative standard deviation(RSDs)between 1.55%and 6.49%,and the HAAs contents in all tested samples were below the limits specified in the Standards for Drinking Water Quality(GB 5749-2022)of China.This method was featured with simple operation,fast analysis speed,high sensitivity,and good accuracy,providing an efficient and reliable technical support for routine monitoring of HAAs contaminants in drinking water and showing promising application value for widespread promotion.

Objective:To investigate clinicopathologic characteristics and molecular genetic profiles of embryonal rhabdomyosarcoma (ERMS) of the middle ear.Methods:A total of 11 cases of primary middle ear ERMS diagnosed and treated at the Fudan University Affiliated Eye and ENT Hospital between January 2016 and June 2024 were collected. Their clinicopathologic features, immunophenotypes, and molecular genetic alterations were analyzed. Relevant literature was reviewed.Results:There were 8 male and 3 female children. The mean age was 6 years, median age, 6 (5, 7) years, with a range of 1 to 11 years. Clinical manifestations included otorrhea, ear pain, ear fullness, tinnitus, and hearing loss, with some patients also presenting with facial paralysis, hoarseness, and choking on drinking. Otoscopic examination revealed granulomatous neoplasms in the external auditory canal. Imaging studies showed irregular soft-tissue masses in the middle ear region, accompanied by bony destruction and invasion of adjacent structures. Histologically, 10 of the tumors were composed of primitive small round cells, stellate cells, and short spindle-shaped cells, with an alternating loose and dense distribution pattern, and varying degrees of rhabdomyoblastic differentiation in some areas. One tumor exhibited the classic botryoid subtype morphology. Immunohistochemistry supported the diagnosis of rhabdomyosarcoma, and the Ki-67 proliferation index ranged from 40% to 80%. Next-generation sequencing (DNA-seq) was performed on 9 cases, revealing copy number variations of chromosome 7 in 4 cases, PDE4DIP mutations in 5 cases, and C19orf69::TPM3 gene fusions in 6 cases. HPV PCR testing showed HPV11 positivity in 2 cases. All 11 patients underwent surgical treatment, with 4 patients receiving adjuvant chemoradiotherapy. Follow-up until February 2025 revealed 8 deaths, among which 4 cases harbored both C19orf69::TPM3 fusions and PDE4DIP mutations and one had C19orf69::TPM3 fusions alone.Conclusions:ERMS of the middle ear is a rare type of malignant tumor with a relatively poor prognosis. Our study indicates that the concurrence of PDE4DIP mutation and C19orf69::TPM3 gene fusion may indicate poor prognosis in middle ear EMRS, providing a potential target for subsequent individualized treatment.

OBJECTIVE: Ulcerative colitis is closely associated with intestinal stem cell (ISC) loss and impaired intestinal mucus barrier. Sinisan (SNS), a compound Chinese herbal medicine, has a long history in the treatment of intestinal dysfunction, yet whether SNS can relieve acute experimental colitis by modulating ISC proliferation and secretory cell differentiation has not been studied. Our study tested the effect of SNS against acute colitis and focused on the mechanisms involving intestinal barrier recovery. METHODS: Network pharmacology analysis and blood entry component analysis of SNS were used to explore the underlying mechanism by which SNS affects the acute dextran sulfate sodium (DSS)-induced murine colitis model. RNA-sequencing was used to demonstrate the mechanism. Further, reverse transcription-quantitative polymerase chain reaction, immunofluorescence staining, and alcian blue and periodic acid-Schiff staining were performed in vivo and in the colonic organoids to investigate the cell lineage differentiation-related mechanism of SNS. Furthermore, potential active ingredients from SNS were predicted by network pharmacology analysis. RESULTS: SNS dramatically suppressed DSS-induced acute colonic inflammation in mice. RNA-sequencing analysis revealed downregulation of inflammation and apoptosis-related genes, and upregulation of lipid metabolism and proliferation-related genes, such as Irf7, Pparα, Clspn and Hspa5. Additionally, ISC renewal and intestinal secretory cell lineage commitment were significantly promoted by SNS both in vivo and in vitro in colonic organoids, leading to enhanced mucin expression. Furthermore, potential active ingredients from SNS that mediated inflammation, lipid metabolism, proliferation, apoptosis, stem cells and secretory cells were predicted using a network pharmacology approach. CONCLUSION Our study shed light on the underlying mechanism of SNS in attenuating acute colitis from the perspective of ISC renewal and secretory lineage cell differentiation, suggesting a of novel therapeutic strategy against colitis. Please cite this article as: Cai YJ, Lan JH, Li S, Feng YN, Li FH, Guo MY, et al. Sinisan, a compound Chinese herbal medicine, alleviates acute colitis by facilitating colonic secretory cell lineage commitment and mucin production. J Integr Med. 2025; 23(4): 429-444.
Animals ; Drugs, Chinese Herbal/therapeutic use* ; Mice ; Colon/pathology* ; Mucins/metabolism* ; Mice, Inbred C57BL ; Cell Differentiation/drug effects* ; Male ; Colitis/metabolism* ; Cell Lineage/drug effects* ; Dextran Sulfate ; Stem Cells/drug effects* ; Disease Models, Animal

This study investigates the pharmacokinetics and metabolic characteristics of three marine-derived piericidins as potential drug leads for kidney disease: piericidin A (PA) and its two glycosides (GPAs), glucopiericidin A (GPA) and 13-hydroxyglucopiericidin A (13-OH-GPA). The research aims to facilitate lead selection and optimization for developing a viable preclinical candidate. Rapid absorption of PA and GPAs in mice was observed, characterized by short half-lives and low bioavailability. Glycosides and hydroxyl groups significantly enhanced the absorption rate (13-OH-GPA > GPA > PA). PA and GPAs exhibited metabolic instability in liver microsomes due to Cytochrome P450 enzymes (CYPs) and uridine diphosphoglucuronosyl transferases (UGTs). Glucuronidation emerged as the primary metabolic pathway, with UGT1A7, UGT1A8, UGT1A9, and UGT1A10 demonstrating high elimination rates (30%-70%) for PA and GPAs. This rapid glucuronidation may contribute to the low bioavailability of GPAs. Despite its low bioavailability (2.69%), 13-OH-GPA showed higher kidney distribution (19.8%) compared to PA (10.0%) and GPA (7.3%), suggesting enhanced biological efficacy in kidney diseases. Modifying the C-13 hydroxyl group appears to be a promising approach to improve bioavailability. In conclusion, this study provides valuable metabolic insights for the development and optimization of marine-derived piericidins as potential drug leads for kidney disease.
Animals ; Male ; Mice ; Aquatic Organisms/chemistry* ; Biological Availability ; Cytochrome P-450 Enzyme System/metabolism* ; Glucuronosyltransferase/metabolism* ; Microsomes, Liver/metabolism* ; Molecular Structure ; Biological Products/pharmacokinetics* ; Pyridines/pharmacokinetics*

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

OBJECTIVES: To study the clinical effect of the L-shape technique combined with concentrated growth factor on the horizontal bone defects of maxillary anterior teeth. METHODS: Twenty-five implants from 25 patients who underwent single maxillary anterior tooth implantation with simultaneous bone grafting were selected as the study subjects. Based on the bone grafting techniques, the patients were divided into a test group (L-shaped technique with guided bone regeneration combined with concentrated growth factor, 11 cases) and a control group (traditional guided bone regeneration combined with concentrated growth factor, 14 cases). The early discomfort and wound healing conditions in the two groups at two weeks after surgery were compared. The horizontal bone thickness, vertical bone thickness, and grayscale values in the augmentation area were measured immediately postsurgery and six months after surgery. Implant stability, hard tissue resorption within six months, and grayscale values were compared between the two groups. RESULTS: Differences in early discomfort, wound healing, implant stability, and grayscale values between the two groups were not statistically significant (P>0.05). Vertical bone thickness in the test group was significantly better than that in the control group at six months after surgery (P<0.05). The variation in horizontal bone thickness in the test group was significantly higher than that in the control group (P<0.05). CONCLUSIONS The application of the L-shape technique with concentrated growth factor for horizontal bone defects in the anterior maxillary area yielded satisfactory short-term results in terms of bone augmentation, early discomfort, wound healing, and implant stability at six months after surgery.
Humans ; Maxilla/diagnostic imaging* ; Intercellular Signaling Peptides and Proteins/therapeutic use* ; Wound Healing ; Bone Transplantation/methods* ; Dental Implantation, Endosseous/methods* ; Bone Regeneration ; Male ; Female ; Adult ; Dental Implants, Single-Tooth ; Middle Aged

Aim To elucidate whether Astragaloside Ⅳcould ameliorate pathological myocardial hypertrophy and fibrosis via the EGR1-SIRT1-PPARα-SCAD signa-ling pathway in TAC mice.Methods After randomi-zing mice into groups,the Sham+AS-Ⅳ group and TAC+AS-Ⅳ group were intragastrically administered 20 mg·kg-1AS-Ⅳ once daily,whereas the Sham+NS group and TAC+NS group were given equivalent saline.Six weeks post-surgery,an evaluation of cardiac function was conducted,heart weight index was compu-ted,morphological alterations in heart were noted,vari-ations in collagen and myocardial hypertrophy indexes were analyzed,ATP content,free fatty acid content,hydroxyproline content,SCAD expression,and enzyme activity were measured,and an initial investigation into the protein expression of EGR1-SIRT1-PPARα-SCAD in myocardial tissues was undertaken.Results After AS-Ⅳ intervention,the heart weight index of TAC mice decreased(P＜0.01),LVAWd,LVAWs,LVPWd and LVPWs values decreased(P＜0.01,P＜0.05),EF％and FS％values increased(all P＜0.01),myocardial hypertrophy markers and collagen area decreased,FFA content,HYP content and collagen expression de-creased(all P＜0.01),SCAD enzyme activity and ex-pression increased(P＜0.01,P＜0.05),and ATP content increased(P＜0.01).The expression of EGR1 protein decreased,and the expression of SIRT1 and PPARα protein increased(all P＜0.01).Conclu-sions AS-Ⅳ may improve fatty acid oxidation via the EGR1-SIRT1-PPARα-SCAD signaling pathway,thereby ameliorating pathological myocardial hypertrophy and fibrosis in TAC model mice.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To explore the value of spectral CT quantitative parameters combined with clinical and CT features for predicting lymphovascular invasion(LVI)of colorectal cancer.Methods Clinical,pathological and preoperative abdominal spectral CT data of 98 colorectal cancer patients were retrospectively analyzed.According to pathological results,the patients were divided into LVI group(n=36)and non-LVI group(n=62).Univariate and multivariate logistic regression were used to compared clinical,pathological,conventional CT manifestations and spectral CT quantitative parameters between groups to screen independent predictors for LVI of colorectal cancer,and then a regression model was constructed.Receiver operating characteristic(ROC)curves were drawn,and the area under the curves(AUC)were calculated to evaluate the predictive efficacy of each single independent predictor and regression model for predicting LVI of colorectal cancer.Results Serum carbohydrate antigen 724,CT showed periintestinal fat infiltration and effective atomic number(Zeff)at venous phase were all independent predictors of LVI of colorectal cancer(OR=4.723,7.301 and 18.912,all P＜0.05).AUC of the above independent predictors was 0.582,0.723 and 0.691,respectively,while of the regression model was 0.837.Conclusion Spectral CT quantitative parameters combined with clinical and CT features could effectively predict LVI of colorectal cancer.