Zamir Halpern

TL;DR: A machine-learning algorithm is devised that integrates blood parameters, dietary habits, anthropometrics, physical activity, and gut microbiota measured in an 800-person cohort and shows that it accurately predicts personalized postprandial glycemic response to real-life meals, and a blinded randomized controlled dietary intervention based on this algorithm resulted in significantly lower postpr andial responses and consistent alterations to gut microbiota configuration.

TL;DR: Genotype and microbiome data from 1,046 healthy individuals with several distinct ancestral origins who share a relatively common environment are examined, and it is demonstrated that the gut microbiome is not significantly associated with genetic ancestry, and that host genetics have a minor role in determining microbiome composition.

TL;DR: It is demonstrated that consumption of commonly used NAS formulations drives the development of glucose intolerance through induction of compositional and functional alterations to the intestinal microbiota, thereby calling for a reassessment of massive NAS usage.

TL;DR: The metagenomically characterized the murine and human mucosal-associated gastrointestinal microbiome and found it to only partially correlate with stool microbiome, indicating that empiric probiotics supplementation may be limited in universally and persistently impacting the gut mucosa.

TL;DR: Evidence of coordinated metaorganism diurnal rhythmicity is provided and jet-lag-induced dysbiosis in both mice and humans promotes glucose intolerance and obesity that are transferrable to germ-free mice upon fecal transplantation.