Jingrui Zhang

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In this study, 24 standard nontuberculous mycobacteria (NTM) species strains including 12 slowly growing mycobacteria strains and 12 rapidly growing mycobacteria strains were subjected to drug susceptibility testing using microplate Alamar Blue assay-based 7H9 broth. The most active antimicrobial agents against the 24 NTM strains were streptomycin,(More)
Isoniazid (INH) and rifampicin (RIF) are the two most effective drugs in tuberculosis therapy. Understanding the molecular mechanisms of resistance to these two drugs is essential to quickly diagnose multidrug-resistant (MDR) tuberculosis and extensive drug-resistant tuberculosis. Nine clinical Mycobacterium tuberculosis isolates resistant to only INH and(More)
Iron is essential for organisms. It is mainly utilized in mitochondria for biosynthesis of iron-sulfur clusters, hemes and other cofactors. Mitoferrin 1 and mitoferrin 2, two homologues proteins belonging to the mitochondrial solute carrier family, are required for iron delivery into mitochondria. Mitoferrin 1 is highly expressed in developing erythrocytes(More)
Pulmonary diseases caused by nontuberculous mycobacteria (NTM) are increasing in incidence and prevalence worldwide. In this study, we identified NTM species of the clinical isolates from 8 provinces in China, in order to preliminarily provide some basic scientific data in the different species and distribution of NTM related to pulmonary disease in China.(More)
Unit commitment problem is a large scale nonlinear hybrid integer programming problem. Optimal unit commitment scheduling involves determining on/off states of units and determining generations of units. This paper proposes an improved particle swarm optimization (IPSO) for the solution of optimal unit commitment problem (UCP). In the proposed approach, the(More)
—To understand users' preference and business performance in terms of customer interest, rating prediction systems are wildly deployed on many social websites. These systems are usually based on the users past history of reviews and similar users. Such traditional recommendation systems 1 suffer from two problems. The first is the cold start problem. In(More)