A machine-learning framework for predicting multiple air pollutants' concentrations via multi-target regression and feature selection.

Air pollution is considered one of the biggest threats for the ecological system and human existence. Therefore, air quality monitoring has become a necessity in urban and industrial areas. Recently, the emergence of Machine Learning techniques justifies the application of statistical approaches for environmental modeling, especially in air quality forecasting.

A Genome-Wide Association Study Identifies a Novel Locus for Bortezomib-Induced Peripheral Neuropathy in European Patients with Multiple Myeloma.

Purpose: Painful peripheral neuropathy is a frequent toxicity associated with bortezomib therapy. This study aimed to identify loci that affect susceptibility to this toxicity.

Experimental Design: A genome-wide association study (GWAS) of 370,605 SNPs was performed to identify risk variants for developing severe bortezomib-induced peripheral neuropathy (BiPN) in 469 patients with multiple myeloma who received bortezomib-dexamethasone therapy prior to autologous stem cell in randomized clinical trials of the Intergroupe Francophone du Myelome (IFM) and findings were replicated in 114 patients with multiple myeloma of the HOVON-65/GMMG-HD4 clinical trial.