Macroporous resin adsorption column chromatography, silica gel column chromatography, ODS column chromatography, and semi-preparative high-performance liquid chromatography, combined with analytical methods such as NMR and MS, were employed to separate and identify compounds from the 70% ethanol extract of Ajania purpurea. A total of 30 compounds were isolated and identified, including 13 phenolic acids, 7 coumarins, 2 lignans, 1 flavonoid, 2 sesquiterpenes, 1 steroid, and 4 others. Among them, compounds 1 and 2 were newly discovered compounds, and compounds 4, 6, 8, 12, 14-23, 25, 28, and 30 were isolated from Ajania plants for the first time. Bioactivity screening showed that multiple compounds significantly inhibited the production of nitric oxide in lipopolysaccharide-stimulated RAW264.7 cells in a dose-dependent manner. Furthermore, compound 2 elevated the levels of glutathione in LPS-induced BEAS-2B cells, reduced the expression of pro-inflammatory cytokines such as tumor necrosis factor(TNF)-α, interleukin(IL)-6, and IL-1β, enhanced the mRNA of GPX4, HMOX1, NFE2L2, and enhanced protein levels of GPX4, HO-1, Nrf2, and SLC7A11, demonstrating potential anti-ferroptotic effect.
Mice ; Animals ; Lignans/isolation & purification* ; RAW 264.7 Cells ; Humans ; Nitric Oxide ; Tumor Necrosis Factor-alpha/immunology* ; Drugs, Chinese Herbal/isolation & purification* ; NF-E2-Related Factor 2/metabolism* ; Macrophages/metabolism* ; Interleukin-6/immunology*

Colorectal cancer(CRC) is one of the most common malignant tumors worldwide, primarily originating from recurrent inflammatory bowel disease(IBD). Therefore, blocking the inflammation-cancer transformation in the colon has become a focus in the early prevention and treatment of CRC. The inflammation-cancer transformation in the colon involves multiple types of cells and complex pathological processes, including inflammatory responses and tumorigenesis. In this complex pathological process, immune cells(including non-specific and specific immune cells) and non-immune cells(such as tumor cells and fibroblasts) interact with each other, collectively promoting the progression of the disease. In traditional Chinese medicine(TCM), inflammation-cancer transformation in the colon belongs to the categories of dysentery and diarrhea, with the main pathogenesis being cold and heat in complexity. This paper first elaborates on the complex molecular mechanisms involved in the inflammation-cancer transformation process in the colon from the perspectives of inflammation, cancer, and their mutual influences. Subsequently, by comparing the pathogenic characteristics and clinical manifestations between inflammation-cancer transformation and the TCM pathogenesis of cold and heat in complexity, this paper explores the intrinsic connections between the two. Furthermore, based on the correlation between inflammation-cancer transformation in the colon and the TCM pathogenesis, this paper delves into the importance of the interaction between inflammation and cancer. Finally, it summarizes and discusses the clinical and basic research progress in the TCM intervention in the inflammation-cancer transformation process, providing a theoretical basis and treatment strategy for the treatment of CRC with integrated traditional Chinese and Western medicine.
Humans ; Colon/pathology* ; Integrative Medicine ; Animals ; Cold Temperature ; Cell Transformation, Neoplastic/drug effects* ; Medicine, Chinese Traditional ; Hot Temperature ; Inflammation ; Drugs, Chinese Herbal/therapeutic use* ; Colonic Neoplasms/drug therapy*

Objective To construct a dynamic framework for bidirectional transitions of mild cognitive impairment(MCI),quantifying both rare reversion and high-risk progression trajectories in cognitive dynamics.Methods Patients diagnosed with MCI at baseline from 2005 to 2022 and completed at least two follow-up visits were selected from the Alzheimer's Disease Neuroimaging Initiative(ADNI),and a retrospective cohort was constructed.Demographic information,APOEε4 genotype,and neuropsychological scales data were collected.Longitudinal cognitive assessments were functionally reconstructed using multivariate functional principal component analysis(MFPCA),with functional principal components(FPCs)extracted based on cumulative variance contribution rate(PVE＞90％).Functional multi-state Markov models were developed to estimate inter-state transition intensities,year to year transition probabilities,and covariate effects.Results Among 1,019 MCI patients(4,657 follow-up visits),93(9.1％)reverted to normal cognition,while 359(35.2％)progressed to Alzheimer's disease(AD).Longitudinal trajectory analysis revealed significant heterogeneity:progressive MCI＞stable MCI＞reverted MCI in the first functional principal component(MFPC1)scores.The transition intensity for MCI reversion(0.020)was approximately one-fourth of the AD progression risk(0.086),but the post-reversion cognitive re-impairment intensity was 0.138.Reduced MFPC1(HR=0.993,95％Cl:0.991,0.995)and elevated MFPC2(HR=1.004,95％Cl:1.001,1.007)were closely associated with MCI reversion.Conclusion MCI exhibits marked heterogeneity in longitudinal cognitive trajectories.Although reversion is rare,reversed patients remain at high risk of cognitive re-impairment.

Objective:To analyze the current status of the research in two emerging fields-digital health and digital medicine,and the distinctions and interconnections between them,and to explore critical cognitionfor benign development of this field.Methods:Based on bibliometric method,this study analyzed 1 747 papers published in two Q1 journals categorized under"medical informatics"in Chinese Academy of Sciences Journal Citation Reports between January 1st,2019,and June 30th,2024.A biclustering analysis of highly cited and source article was conducted using a"co-cited literature clustering and all articles citing this cluster"approach.Results:In 1 747 literature,a total of 28 classic high cited articles in digital medicinejournals and digital health journals were screened out afterthe literatures of irrelevant citations were deleted,and then,they were further analyzed.The clustering performancesof similar clusters for high cited articles of two kinds of journals were similar,and the difference of intra-cluster similarity(Isim)between them was not statistically significant(P>0.05).The inter-cluster similarity(Esim)of digital health journal was 0.0480,which was significantly higher than that of digital health journal,and the difference of that between them wasstatistically significant(t=-3.925,P<0.05).The clustering result of digital medicine was better,which whole research direction could be divided into deep learning-based ophthalmic medical image analysis,image recognition with artificial intelligence(AI),algorithm model of using AI,reporting standard and assessment method of digital medicine and scientific research by using AI.However,the contents of high cited literatures of digital health field had a lot of overlap with digital medicine field,and various clusters of literature have inconsistent themesafter these literatures were clustered.Conclusions:Research of digital medicine is tending towards two primary directions:specific application of AI,and theimprovement of digital medical standards and processes.Meanwhile,the articles and literatures with high quality in digital health still cannot divorce the medical field,and the discipline system still is immature.

AIM To explore the effects of Hofmeister series ions on encapsulation efficiencies of cinnamaldehyde,paeonol,and ligustilide in inclusion complex of volatile oils from Wenjing Decoction.METHODS The volatile oils were extracted,after which the β-cyclodextrin inclusion complex was prepared,the thermal stability was evaluated,and encapsulation efficiencies and inclusion complex constants of various volatile components in Na2SO4,NaH2PO4,NaCl,NaI,NaSCN solutions were determined.RESULTS The β-cyclodextrin inclusion complex demonstrated good thermal stability within 10 d.After the addtion of Hofmeister series ions,various volatile components displayed increased encapsulation efficiencies and inclusion complex constants,and concentration-dependent manner was observable in the latter.CONCLUSION Hofmeister series ions can affect the binding affinities of volatile components and β-cyclodextrin in volatile oils from Wenjing Decoction,thus regulate their encapsulation efficiencies.

Objective:To evaluate the prevalence, potential risk factors, and correlation between coronary and peripheral microvascular dysfunction in heart failure with non-reduced ejection fraction (nHFrEF) patients.Methods:This was a prospective registry study. nHFrEF patients admitted to Zhongshan Hospital affiliated with Fudan University from December 2021 to December 2023 were enrolled. According to coronary flow reserve (CFR) or reactive congestion index (RHI), enrolled patients were divided into coronary microvascular endothelial dysfunction (CMD) group (CFR<2.5) and no CMD group (CFR≥2.5) or peripheral microvascular endothelial dysfunction (MED) group (RHI<1.67) and no MED group (RHI≥1.67). Patients′ general information, laboratory and auxiliary examination data were collected. Univariate and multivariate logistic regression were used to analyze the influencing factors of CMD and MED in nHFrEF patients, and Spearman correlation analysis was used to evaluate the correlation between MED and CMD.Results:A total of 142 nHFrEF patients were enrolled, aged 69.0 (59.0, 74.0) years, with a male proportion of 66.9% (95/142). The grouping results were as follows: (1) According to CFR, there were 73 cases in the CMD group and 69 cases in the no CMD group; (2) According to RHI, there were 57 cases in the MED group and 85 cases in the no MED group. The prevalence of CMD and MED in this study was 51.4% (73/142) and 40.1% (57/142), respectively. Univariate logistic regression analysis showed that increased heart rate, chronic kidney disease, atrial fibrillation, elevated N-terminal pro-B type natriuretic peptide levels, and increased urinary albumin/creatinine ratio were risk factors for CMD, while increased RHI was a protective factor for CMD; Atrial fibrillation is a risk factor for MED, while increased CFR is a protective factor for MED. Incorporating clinically significant variables from univariate analysis into multivariate analysis, the results showed that increased heart rate and elevated RHI remained risk and protective factors for CMD, respectively; increased CFR remains a protective factor for MED. Spearman correlation analysis showed that CFR was negatively correlated with lg urinary albumin/creatinine ratio, lg cardiac troponin T, lg N-terminal pro-B type natriuretic peptide, and heart rate; RHI is positively correlated with CFR.Conclusions:The prevalence of CMD and MED in nHFrEF patients is high, and the two have a certain positive correlation. Increased heart rate and RHI are risk and protective factors for CMD, respectively, while increased CFR is a protective factor for MED. MED may be a potential therapeutic target for nHFrEF patients.

Objective: To investigate the association of physical activity and screen time with overweight and obesity among children and adolescents with special needs in Tianjin, so as to provide scientific evidence for childhood obesity prevention and intervention measures in the population. Methods: From January 2022 to June 2024, 296 children and adolescents with intellectual disabilities and autism spectrum disorders aged 2-18 years were recruited from special education schools and institutions in Tianjin. Height and weight were measured, and a standardized questionnaire was used to assess physical activity and screen time. Binary Logistic regression analysis was carried out to investigate the association of physical activity and screen time with overweight and obesity. Results: The prevalence of overweight and obesity among children and adolescents with special needs in Tianjin were 17.2% and 21.6%, respectively, and the combined prevalence of overweight and obesity was 38.9%. The median of moderatetovigorous physical activity (MVPA) time was 0.20 h/d, and physical activity sufficiency rate was 7.8%. The median of screen time was 1.79 h/d, and the screen time compliance rate was 68.2%. The binary Logistic regression results showed that lower levels of MVPA time and increased screen time were associated with a higher risk of overweight and obesity among children and adolescents with special needs [OR(95%CI)=1.80(1.06-3.07), 2.40(1.42-4.07),P<0.05]. Conclusions Insufficient physical activity and excessive screen time are associated with an increased risk of overweight and obesity among children and adolescents with special needs. Therefore, comprehensive intervention measures should be implemented as early as possible to prevent and reduce the incidence of overweight and obesity in this population.

Cardiotoxicity is a critical issue in drug development that poses serious health risks,including potentially fatal arrhythmias.The human ether-à-go-go related gene(hERG)potassium channel,as one of the pri-mary targets of cardiotoxicity,has garnered widespread attention.Traditional cardiotoxicity testing methods are expensive and time-consuming,making computational virtual screening a suitable alter-native.In this study,we employed machine learning techniques utilizing molecular fingerprints and descriptors to predict the cardiotoxicity of compounds,with the aim of improving prediction accuracy and efficiency.We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms,including Gaussian naive Bayes(NB),random forest(RF),support vector machine(SVM),K-nearest neighbors(KNN),eXtreme gradient boosting(XGBoost),and Trans-former models,to build predictive models.Our models demonstrated advanced predictive performance.The best machine learning model,XGBoost Morgan,achieved an accuracy(ACC)value of 0.84,and the deep learning model,Transformer_Morgan,achieved the best ACC value of 0.85,showing a high ability to distinguish between toxic and non-toxic compounds.On an external independent validation set,it achieved the best area under the curve(AUC)value of 0.93,surpassing ADMETlab3.0,Cardpred,and CardioDPi.In addition,we explored the integration of molecular descriptors and fingerprints to enhance model performance and found that ensemble methods,such as voting and stacking,provided slight improvements in model stability.Furthermore,the SHapley Additive exPlanations(SHAP)explanations revealed the relationship between benzene rings,fluorine-containing groups,NH groups,oxygen in ether groups,and cardiotoxicity,highlighting the importance of these features.This study not only improved the predictive accuracy of cardiotoxicity models but also promoted a more reliable and scientifically interpretable method for drug safety assessment.Using computational methods,this study facilitates a more efficient drug development process,reduces costs,and improves the safety of new drug candidates,ultimately benefiting medical and public health.