Background Cardiovascular disease (CVD) annually claims more lives and costs more dollars than any other disease globally amid widening health disparities, despite the known significant reductions in this burden by low cost dietary changes. The world's first medical school-based teaching kitchen therefore launched CHOP-Medical Students as the largest known multisite cohort study of hands-on cooking and nutrition education versus traditional curriculum for medical students. Methods This analysis provides a novel integration of artificial intelligence-based machine learning (ML) with causal inference statistics. 43 ML automated algorithms were tested, with the top performer compared to triply robust propensity score-adjusted multilevel mixed effects regression panel analysis of longitudinal data. Inverse-variance weighted fixed effects meta-analysis pooled the individual estimates for competencies. Results 3,248 unique medical trainees met study criteria from 20 medical schools nationally from August 1, 2012, to June 26, 2017, generating 4,026 completed validated surveys. ML analysis produced similar results to the causal inference statistics based on root mean squared error and accuracy. Hands-on cooking and nutrition education compared to traditional medical school curriculum significantly improved student competencies (OR 2.14, 95% CI 2.00–2.28, p < 0.001) and MedDiet adherence (OR 1.40, 95% CI 1.07–1.84, p = 0.015), while reducing trainees' soft drink consumption (OR 0.56, 95% CI 0.37–0.85, p = 0.007). Overall improved competencies were demonstrated from the initial study site through the scale-up of the intervention to 10 sites nationally (p < 0.001). Discussion This study provides the first machine learning-augmented causal inference analysis of a multisite cohort showing hands-on cooking and nutrition education for medical trainees improves their competencies counseling patients on nutrition, while improving students' own diets. This study suggests that the public health and medical sectors can unite population health management and precision medicine for a sustainable model of next-generation health systems providing effective, equitable, accessible care beginning with reversing the CVD epidemic.

NAD kinase (NADK) catalyzes the phosphorylation of nicotinamide adenine dinucleotide (NAD) to nicotinamide adenine dinucleotide phosphate (NADP) using ATP as the phosphate donor. NADP is then reduced to NADPH by dehydrogenases, in particular glucose-6-phosphate dehydrogenase and the malic enzymes. NADPH functions as an important cofactor in a variety of metabolic and biosynthetic pathways. The demand for NADPH is particularly high in proliferating cancer cells, where it acts as a cofactor for the synthesis of nucleotides, proteins, and fatty acids. Moreover, NADPH is essential for the neutralization of the dangerously high levels of reactive oxygen species (ROS) generated by increased metabolic activity. Given its key role in metabolism and regulation of ROS, it is not surprising that several recent studies, including in vitro and in vivo assays of tumor growth and querying of patient samples, have identified NADK as a potential therapeutic target for the treatment of cancer. In this review, we will discuss the experimental evidence justifying further exploration of NADK as a clinically relevant drug target and describe our studies with a lead compound, thionicotinamide, an NADK inhibitor prodrug. Clin Cancer Res; 22(21); 5189-95. ©2016 AACR.

Human dihydrofolate reductase (DHFR) protein levels rapidly increase upon exposure to methotrexate, a potent inhibitor of this enzyme. A model to explain this increase proposes that DHFR inhibits its own translation by binding to its cognate mRNA and that methotrexate disrupts the DHFR protein-mRNA complex allowing its translation to resume. In the present study, Chinese hamster ovary cells lacking DHFR were transfected with wild type and mutants of human DHFR to identify amino acids that are essential for increases in DHFR in response to methotrexate. Glu-30, Leu-22, and Ser-118 were involved in the up-regulation of DHFR protein levels by methotrexate and certain other antifolates. Cells transfected with E30A, L22R, and S118A mutants that did not respond to methotrexate up-regulation had higher basal levels of DHFR, consistent with the model, i.e. lack of feedback regulation of these enzymes. Although cells containing the S118A mutant enzyme had higher levels of DHFR and had catalytic activity similar to that of wild type DHFR, they had the same sensitivity to the cytotoxicity of methotrexate, as were cells with wild type DHFR. This finding provides evidence that the adaptive up-regulation of DHFR by methotrexate contributes to the decreased sensitivity to this drug. Based on these observations, a new model is proposed whereby DHFR exists in two conformations, one bound to DHFR mRNA and the other bound to NADPH. The mutants that are not up-regulated by methotrexate are unable to bind their cognate mRNA.

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