Eduard Koifman

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OBJECTIVES Thiopurines are effective for maintenance of remission in inflammatory bowel disease (IBD) in only about half of patients. Predictors of response may assist in selecting the most appropriate patients for thiopurine therapy. Thiopurines inhibit Rac1, a GTPase that exerts an antiapoptotic effect on T-lymphocytes. A genetic association was recently(More)
BACKGROUND Thiopurines are efficacious in the treatment of Crohn's disease and were recently shown to induce T-cell apoptosis by modulation of Rac1 activation. To assess whether polymorphisms in Rac1 and other apoptosis-related genes, combined with clinical parameters, can predict response to thiopurines. METHODS A retrospective cohort of 156(More)
We report on an artificially intelligent nanoarray based on molecularly modified gold nanoparticles and a random network of single-walled carbon nanotubes for noninvasive diagnosis and classification of a number of diseases from exhaled breath. The performance of this artificially intelligent nanoarray was clinically assessed on breath samples collected(More)
OBJECTIVE Malnourished patients suffer from higher morbidity and mortality rates than well-nourished patients do. However, few studies have controlled the outcomes for the underlying illnesses. Our aim was to determine the prevalence of malnutrition among patients admitted to the internal medicine ward and to determine whether malnutrition is an independent(More)
PURPOSE Thiopurines are effective in attaining and maintaining remission in patients with inflammatory bowel diseases (IBD). The major drawback of these drugs are their serious adverse effects (SAE), highlighting the importance of preemptive identification of patients at risk. We aimed to examine whether gene polymorphisms in GSTM1, GSTT1 and TPMT, combined(More)
Chemical sensors based on programmable molecularly modified gold nanoparticles are tailored for the detection and discrimination between the breathprint of irritable bowel syndrome (IBS) and inflammatory bowel diseases (IBD). The sensors are examined in both lab- and real-world clinical conditions. The results reveal a discriminative power accuracy of 81%(More)
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