1.Screen of FDA-approved drug library identifies vitamin K as anti-ferroptotic drug for osteoarthritis therapy through Gas6.
Yifeng SHI ; Sunlong LI ; Shuhao ZHANG ; Caiyu YU ; Jiansen MIAO ; Shu YANG ; Yan CHEN ; Yuxuan ZHU ; Xiaoxiao HUANG ; Chencheng ZHOU ; Hongwei OUYANG ; Xiaolei ZHANG ; Xiangyang WANG
Journal of Pharmaceutical Analysis 2025;15(5):101092-101092
Ferroptosis of chondrocytes is a significant contributor to osteoarthritis (OA), for which there is still a lack of safe and effective therapeutic drugs targeting ferroptosis. Here, we screen for anti-ferroptotic drugs in Food and Drug Administration (FDA)-approved drug library via a high-throughput manner in chondrocytes. We identified a group of FDA-approved anti-ferroptotic drugs, among which vitamin K showed the most powerful protective effect. Further study demonstrated that vitamin K effectively inhibited ferroptosis and alleviated the extracellular matrix (ECM) degradation in chondrocytes. Intra-articular injection of vitamin K inhibited ferroptosis and alleviated OA phenotype in destabilization of the medial meniscus (DMM) mouse model. Mechanistically, transcriptome sequencing and knockdown experiments revealed that the anti-ferroptotic effects of vitamin K depended on growth arrest-specific 6 (Gas6). Furthermore, exogenous expression of Gas6 was found to inhibit ferroptosis through the AXL receptor tyrosine kinase (AXL)/phosphatidylinositol 3-kinase (PI3K)/AKT serine/threonine kinase (AKT) axis. Together, we demonstrate that vitamin K inhibits ferroptosis and alleviates OA progression via enhancing Gas6 expression and its downstream pathway of AXL/PI3K/AKT axis, indicating vitamin K as well as Gas6 to serve as a potential therapeutic target for OA and other ferroptosis-related diseases.
2.Exploring cellular plasticity and resistance mechanisms in lung cancer: Innovations and emerging therapies.
Caiyu JIANG ; Shenglong XIE ; Kegang JIA ; Gang FENG ; Xudong REN ; Youyu WANG
Journal of Pharmaceutical Analysis 2025;15(5):101179-101179
Non-small cell lung cancer (NSCLC) accounts for the majority of lung cancer cases and remains the leading cause of cancer-related mortality worldwide. Firstly, this review explores the limitations of conventional therapies, chemotherapy, radiotherapy, and surgery, focusing on the development of drug resistance and significant toxicity that often hinder their efficacy. Thereafter, advancements in targeted therapies, such as immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs), are discussed, highlighting their impact on improving outcomes for patients with specific genetic mutations, including c-ros oncogene 1 receptor tyrosine kinase (ROS1), anaplastic lymphoma kinase (ALK), and epidermal growth factor receptor (EGFR). Additionally, the emergence of novel immunotherapies and phytochemicals is examined, emphasizing their potential to overcome therapeutic resistance, particularly in advanced-stage diseases. The review also delves into the role of next-generation sequencing (NGS) in enabling personalized treatment approaches and explores the clinical potential of innovative agents, such as bispecific T-cell engagers (BiTEs) and antibody-drug conjugates (ADCs). Finally, we address the socioeconomic barriers that limit the accessibility of these therapies in low-resource settings and propose future research directions aimed at improving the long-term efficacy and accessibility of these treatments.
3.Prediction of risk of in-hospital death in patients with chronic heart failure complicated by lung infections using interpretable machine learning
Caiyu SHEN ; Shuai WANG ; Ruiying ZHOU ; Yuhe WANG ; Qin GAO ; Xingzhi CHEN ; Shu YANG
Journal of Southern Medical University 2024;44(6):1141-1148
Objective To predict the risk of in-hospital death in patients with chronic heart failure(CHF)complicated by lung infections using interpretable machine learning.Methods The clinical data of 1415 patients diagnosed with CHF complicated by lung infections were obtained from the MIMIC-IV database.According to the pathogen type,the patients were categorized into bacterial pneumonia and non-bacterial pneumonia groups,and their risks of in-hospital death were compared using Kaplan-Meier survival curves.Univariate analysis and LASSO regression were used to select the features for constructing LR,AdaBoost,XGBoost,and LightGBM models,and their performance was compared in terms of accuracy,precision,F1 value,and AUC.External validation of the models was performed using the data from eICU-CRD database.SHAP algorithm was applied for interpretive analysis of XGBoost model.Results Among the 4 constructed models,the XGBoost model showed the highest accuracy and F1 value for predicting the risk of in-hospital death in CHF patients with lung infections in the training set.In the external test set,the XGBoost model had an AUC of 0.691(95%CI:0.654-0.720)in bacterial pneumonia group and an AUC of 0.725(95%CI:0.577-0.782)in non-bacterial pneumonia group,and showed better predictive ability and stability than the other models.Conclusion The overall performance of the XGBoost model is superior to the other 3 models for predicting the risk of in-hospital death in CHF patients with lung infections.The SHAP algorithm provides a clear interpretation of the model to facilitate decision-making in clinical settings.
4.Prediction of risk of in-hospital death in patients with chronic heart failure complicated by lung infections using interpretable machine learning
Caiyu SHEN ; Shuai WANG ; Ruiying ZHOU ; Yuhe WANG ; Qin GAO ; Xingzhi CHEN ; Shu YANG
Journal of Southern Medical University 2024;44(6):1141-1148
Objective To predict the risk of in-hospital death in patients with chronic heart failure(CHF)complicated by lung infections using interpretable machine learning.Methods The clinical data of 1415 patients diagnosed with CHF complicated by lung infections were obtained from the MIMIC-IV database.According to the pathogen type,the patients were categorized into bacterial pneumonia and non-bacterial pneumonia groups,and their risks of in-hospital death were compared using Kaplan-Meier survival curves.Univariate analysis and LASSO regression were used to select the features for constructing LR,AdaBoost,XGBoost,and LightGBM models,and their performance was compared in terms of accuracy,precision,F1 value,and AUC.External validation of the models was performed using the data from eICU-CRD database.SHAP algorithm was applied for interpretive analysis of XGBoost model.Results Among the 4 constructed models,the XGBoost model showed the highest accuracy and F1 value for predicting the risk of in-hospital death in CHF patients with lung infections in the training set.In the external test set,the XGBoost model had an AUC of 0.691(95%CI:0.654-0.720)in bacterial pneumonia group and an AUC of 0.725(95%CI:0.577-0.782)in non-bacterial pneumonia group,and showed better predictive ability and stability than the other models.Conclusion The overall performance of the XGBoost model is superior to the other 3 models for predicting the risk of in-hospital death in CHF patients with lung infections.The SHAP algorithm provides a clear interpretation of the model to facilitate decision-making in clinical settings.
5. Impact of oxidative stress on renal dopamine D1 receptor dysfunction in offspring of diabetic rat dams
Hao LUO ; Na WANG ; Caiyu CHEN ; Xiaoli LUO ; Hongyong WANG ; Chunyu ZENG
Chinese Journal of Cardiology 2019;47(5):393-398
Objective:
To explore the effects of oxidative stress on renal dopamine D1 receptor dysfunction in offspring of diabetic rat dams.
Methods:
The pregnant Sprague Dawley (SD) rats (
6.Design,Synthesis and in vitro Hypoglycemic Activity Study of N-aroyl Substituted Indoline- 3-Acetic Acid Derivatives
Jiquan ZHANG ; Tingting WU ; Caiyu MA ; Xiao MA ; Jianta WANG ; Lei TANG
China Pharmacy 2019;30(3):318-322
OBJECTIVE: To design and synthesize N-aroyl substituted indoline-3-acetic acid derivatives and evaluate their in vitro hypoglycemic activity. METHODS: Using indoline derivative 2-[5-(benzyloxy)-1-(4-chlorobenzoyl)-2-methyl-1H-inclol-3-yl]acetic acid (GY3) as leading compound, 4-(benzyloxy)phenyl hydrazine hydrochloride and methyl 4-oxopentanoate as raw material, 8 kinds of N-aroyl (3-hydroxybenzoyl, 3-cyanobenzoyl, 4-nitrobenzoyl, 4-methylsulfonylbenzoyl, 4-acetamidobenzoyl, 3-acetylaminobenzoyl, isoniacyl and pyridine-2-formyl) substituted indoline-3-acetic acid derivatives were synthesized via 4 steps reactions: Fischer indole cyclization, reduction, amidation and hydrolyzation. The human hepatoma HepG2 cell lines were used to investigate the glucose consumption activity of the target compounds. RESULTS: Totally 8 various N-aroyl substituted indoline-3-acetic acids were synthesized and their structures were confirmed by mass spectrum(MS), nuclear magnetic resonance 1H-NMR and 13C spectrum. Under the condition of 1.0 μmol/L, the percentage of glucose- promoting consumption of the synthesized compounds on HepG2 cells was 5.4%-9.1%. 2-[(2R, 3S)-5-benzyloxy-2-methyl-1-(4-methylsulfonyl benzoyl)-2,3-dihydro-indole-3-yl] acetic acid showed the best hypoglycemic activity. The percentage of glucose- promoting consumption was (9.1±1.81)%, which was close to that of positive control metformin [(10.58±1.68)%], but less potent than that of leading compound GY3[(12.15±0.78)%]. CONCLUSIONS: Different electron-withdrawing substituents are introduced into N-aroyl aromatic rings of dihydroindole compounds, such as cyano, nitro, methyl sulfonyl; hypoglycemic activity decreases in varying degrees and is weaker than halogen substituents.
7.Pathogenic characteristic and distribution of Yersinia enterocolitica in Citellus dauricus plague focuses,Inner Mongolia
Li DONG ; Huixia YU ; Caiyu CHEN ; Lixin WANG ; Huabin WANG ; Huaiqi JING ; Xin WANG
Chinese Journal of Zoonoses 2017;33(3):256-259
In order to investigate the distribution of Yersinia enterocolitica in Citellus dauricus plague focuses in Inner Mongolia,three different ecological environ/ments were chosen as the sampling area.Feces,tongue roots throat swabs,and intestinal contents of rodent,livestock,and poultry were separately collected,and different Y.enterocolitica strains were isolated,and identified.PCR analysis was conducted to detect the toxicity genes of Y.enterocolitica.Statiscal analysis was performed by chisquare test.Of the 3 260 samples,65 Y.enterocolitica strains were isolated and the overall detection rate was 1.99%.To include O ∶ 3/3,O ∶ 5/1A,O ∶ 4/4 serum biological type,the pathogenic strain of serotype O ∶ 3 and biological typt 3 carryinq toxicity genes ail,ystA,VirF yadA and rfbc was isolated from pigs in Citellus dauricus plague focuses,Inner Mongolia are the major carrier of pathogenic Y.enterocolitica distributed in three different ecological environment,and distributed mainly in agricultural area.
8.The effect of high-fat diet-induced obesity on oxidative stress and klotho methylation in lung tissue of C57/BL6 mice
Lu YU ; Yuxia WANG ; Caiyu JIANG ; Jiang HUANG
The Journal of Practical Medicine 2017;33(18):3017-3020
Objective To investigate the effect of high-fat diet-induced obesity on oxidative stress and klotho promoter methylation in lung tissue of C57/BL6 mice. Methods Mice in the control group were feed with the normal diet,and mice in the obesity group were feed with high-fat diet. The lung tissue level of uperoxide dis-mutase(SOD)and malondialdehyde(MDA)were determined by using mice enzyme-linked immunosorbent assay (ELISA)kit. The klotho mRNA and protein expression was determined by qPCR and Western-blot ,respectively. The Klotho gene methylation status was determined by methylation specific PCR(MS-PCR). Results Compared with the control group,mice in the obesity group had high level of oxidative stress in lung tissue. Meanwhile,mice in the experimental group had lower levels of klotho mRNA and protein expression than those in the control group. The high-fat diet increased the degree of Klotho gene methylation. Conclusion High-fat diet could lead injure in lung tissue in C57/BL6 mice,klorho promoter methylation may play an important role involved in the process.
9."Construction of the Periodical Resources in Libraries of Medical College in the Era of ""Internet +"""
Caiyu LIU ; Xiaoxia LI ; Xueyun WANG ; Fangfang LI
Journal of Medical Informatics 2017;38(6):77-80
The paper analyzes the effect ofInternet +on the purchase of periodical resources for libraries of medical colleges based on the discussion of the concept of Internet + ,points out the current situation and problems of purchase of periodicals for libraries of medical college,puts forward the periodical purchase modes and scheme proposals that conform to the current trend,and lays a foundation for the development of libraries of medical colleges.
10.Teaching reform of medical literature novelty assessment course
Fangfang LI ; Yanan HAO ; Yanling WANG ; Caiyu LIU
Chinese Journal of Medical Library and Information Science 2015;24(12):73-76
The target of offering medical literature novelty assessment course for medical postgraduates was analyzed with the problems in its teaching and the significance of its teaching reform pointed out.Its teaching contents, teaching methods, examination methods and its assessment system reform were described with suggestions proposed for its successful reform.

Result Analysis
Print
Save
E-mail