A MACHINE LEARNING MODEL FOR PREDICTING PATIENTS WITH MAJOR DEPRESSIVE DISORDER: A STUDY BASED ON TRANSCRIPTOMIC DATA

A machine learning model for predicting patients with major depressive disorder: A study based on transcriptomic data

BackgroundIdentifying new biomarkers of major depressive disorder (MDD) would be of great significance for its early diagnosis and treatment.Herein, we constructed a diagnostic model of MDD using machine learning methods.MethodsThe GSE98793 and GSE19738 datasets were obtained from the Gene Expression Omnibus database, and the limma R package was us

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Metabolomic and phenotypic implications of the application of fertilization products containing microcontaminants in lettuce (Lactuca sativa)

Abstract Cultivation practice using organic amendments is plausible to ensure global food security.However, plant abiotic stress due to the presence of metals and organic microcontaminants (OMCs) in fertilization products cannot be overlooked.In this study, we monitored lettuce metabolism and phenotypic response following the application of either

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An Archaeological Investigation of the Unexcavated Neolithic and Megalithic Sites in Kashmir Valley, India: Landscape, Settlement Pattern and Material Culture

This research embarks on an archaeological investigation of the sixty-eight fresh documented unexcavated Neolithic and Megalithic sites scattered throughout Kashmir Valley, India.Focused on three key aspects - landscape, settlement patterns, and material culture, the study aims to unveil the hidden historical treasures of this region.By employing a

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