Objective To observe the level of serum peptidyl arginine deiminase 4(PAD4)in patients with polymyositis/dermato-myositis(PM/DM)and its correlation with serum neutrophil extracellular traps(NET)markers and other clinical indicators.Methods The peripheral blood of 60 patients with PM/DM(36 cases of DM,24 cases of PM)and 20healthy controls were collected.The levels of PAD4 and NET markers[citrullinated histone H3(CitH3)and cell free DNA(cfDNA)]in serum were detected,the correlation between them was analyzed,and their correlation with clinical data were also analyzed.Results Compared with healthy controls,the level of ser-um PAD4 in PM/DM patients was significantly increased(t=13.21,P＜0.001).The level of serum NET markers in PM/DM patients was significantly higher than that in healthy controls(CitH3:t=9.518,P＜0.001;cfDNA:t=2.984,P=0.0038).The correlation a-nalysis between serum PAD4 and NET marker levels in PM/DM patients showed that there was a positive correlation(PAD4 and CitH3:r=0.835,P＜0.001;PAD4 and cfDNA:r=0.322,P=0.012).The correlation analysis of serum PAD4,CitH3 and cfDNA levels with clinical data showed that PAD4 levels were positively correlated with erythrocyte sedimentation rate(ESR)and procalcitonin(PCT),and negatively correlated with albumin(ALB)levels.There was a positive correlation between serum CitH3 level and alanine aminotrans-ferase(ALT).Serum cfDNA level was positively correlated with white blood cell(WBC),neutrophil(NE#),neutrophil ratio(NE％),C-reactive protein(CRP),interleukin-6(IL-6),ALT,aspartate aminotransferase(AST),creatine kinase(CK),lactate dehydro-genase(LDH)and UREA,and negatively correlated with ALB level.Conclusion Serum PAD4 levels in PM/DM patients were signifi-cantly increased and correlated with abnormal increase of NET.Meanwhile,PAD4 and NET marker levels in serum were positively corre-lated with inflammatory markers of PM/DM patients,suggesting that abnormal increase of PAD4mediated excessive formation of NET may be involved in the pathogenesis of PM/DM.

The technologies such as deep learning and machine learning enable the rapid screening for potential drug candidate molecules and the prediction of their interactions with biological targets.Additionally,artificial intelligence exhibits great potential in drug design,synthesis pathway planning and clinical trial data analysis,and is expected to shorten the time from laboratory to market for new drugs and reduce research and development costs.Herein the study reviews the application of artificial intelligence technology in new drug research and development,explores the challenges it faces,and discusses the future development directions.