首页|Peking University China-Japan Friendship School of Clinical Medicine Reports Fin dings in Machine Learning (Novel endotypes of antisynthetase syndrome identified independent of anti-aminoacyl transfer RNA synthetase antibody specificity that ...)
Peking University China-Japan Friendship School of Clinical Medicine Reports Fin dings in Machine Learning (Novel endotypes of antisynthetase syndrome identified independent of anti-aminoacyl transfer RNA synthetase antibody specificity that ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting out of Beijing, People's Repu blic of China, by NewsRx editors, research stated, "To systemically analyse the heterogeneity in the clinical manifestations and prognoses of patients with anti synthetase syndrome (ASS) and evaluate the transcriptional signatures related to different clinical phenotypes. A total of 701 patients with ASS were retrospect ively enrolled." Funders for this research include National High Level Hospital, National Natural Science Foundation of China, China-Japan Friendship Hospital. Our news journalists obtained a quote from the research from the Peking Universi ty China-Japan Friendship School of Clinical Medicine, "The clinical presentatio n and prognosis were assessed in association with four anti-aminoacyl transfer R NA synthetase (ARS) antibodies: anti-Jo1, anti-PL7, anti-PL12 and anti-EJ. Unsup ervised machine learning was performed for patient clustering independent of ant i-ARS antibodies. Transcriptome sequencing was conducted in clustered ASS patien ts and healthy controls. Patients with four different anti-ARS antibody subtypes demonstrated no significant differences in the incidence of rapidly progressive interstitial lung disease (RP-ILD) or prognoses. Unsupervised machine learning, independent of anti-ARS specificity, identified three endotypes with distinct c linical features and outcomes. Endotype 1 (RP-ILD cluster, 23.7%) w as characterised by a high incidence of RP-ILD and a high mortality rate. Endoty pe 2 (dermatomyositis (DM)-like cluster, 14.5%) corresponded to pat ients with DM-like skin and muscle symptoms with an intermediate prognosis. Endo type 3 (arthritis cluster, 61.8%) was characterised by arthritis an d mechanic's hands, with a good prognosis. Transcriptome sequencing revealed tha t the different endotypes had distinct gene signatures and biological processes. Anti-ARS antibodies were not significant in stratifying ASS patients into subgr oups with greater homogeneity in RP-ILD and prognoses."
BeijingPeople's Republic of ChinaAsi aAntibodiesBlood ProteinsCyborgsEmerging TechnologiesEnzymes and Coenz ymesGeneticsImmunoglobulinsImmunologyMachine LearningProteinsSynthet ase
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