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1,781 results

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Page 1
Personalized Nutrition by Prediction of Glycemic Responses.
Zeevi D, Korem T, Zmora N, Israeli D, Rothschild D, Weinberger A, Ben-Yacov O, Lador D, Avnit-Sagi T, Lotan-Pompan M, Suez J, Mahdi JA, Matot E, Malka G, Kosower N, Rein M, Zilberman-Schapira G, Dohnalová L, Pevsner-Fischer M, Bikovsky R, Halpern Z, Elinav E, Segal E. Zeevi D, et al. Cell. 2015 Nov 19;163(5):1079-1094. doi: 10.1016/j.cell.2015.11.001. Cell. 2015. PMID: 26590418 Free article. Clinical Trial.
Here, we continuously monitored week-long glucose levels in an 800-person cohort, measured responses to 46,898 meals, and found high variability in the response to identical meals, suggesting that universal dietary recommendations may have limited utility. We …
Here, we continuously monitored week-long glucose levels in an 800-person cohort, measured responses to 46,898 meals, and foun …
Personalized nutrition in type 2 diabetes remission: application of digital twin technology for predictive glycemic control.
Shamanna P, Joshi S, Thajudeen M, Shah L, Poon T, Mohamed M, Mohammed J. Shamanna P, et al. Front Endocrinol (Lausanne). 2024 Nov 20;15:1485464. doi: 10.3389/fendo.2024.1485464. eCollection 2024. Front Endocrinol (Lausanne). 2024. PMID: 39634180 Free PMC article. Clinical Trial.
Traditional dietary interventions, such as low-calorie or low-carbohydrate diets, typically overlook individual variability in postprandial glycemic responses (PPGRs), which can lead to suboptimal management of the disease. Recent advancements suggest that person …
Traditional dietary interventions, such as low-calorie or low-carbohydrate diets, typically overlook individual variability in postprandial …
Personalized microbiome-driven effects of non-nutritive sweeteners on human glucose tolerance.
Suez J, Cohen Y, Valdés-Mas R, Mor U, Dori-Bachash M, Federici S, Zmora N, Leshem A, Heinemann M, Linevsky R, Zur M, Ben-Zeev Brik R, Bukimer A, Eliyahu-Miller S, Metz A, Fischbein R, Sharov O, Malitsky S, Itkin M, Stettner N, Harmelin A, Shapiro H, Stein-Thoeringer CK, Segal E, Elinav E. Suez J, et al. Cell. 2022 Sep 1;185(18):3307-3328.e19. doi: 10.1016/j.cell.2022.07.016. Epub 2022 Aug 19. Cell. 2022. PMID: 35987213 Free article. Clinical Trial.
Non-nutritive sweeteners (NNS) are commonly integrated into human diet and presumed to be inert; however, animal studies suggest that they may impact the microbiome and downstream glycemic responses. ...Collectively, human NNS consumption may induce person …
Non-nutritive sweeteners (NNS) are commonly integrated into human diet and presumed to be inert; however, animal studies suggest that …
Effect of a Personalized Diet to Reduce Postprandial Glycemic Response vs a Low-fat Diet on Weight Loss in Adults With Abnormal Glucose Metabolism and Obesity: A Randomized Clinical Trial.
Popp CJ, Hu L, Kharmats AY, Curran M, Berube L, Wang C, Pompeii ML, Illiano P, St-Jules DE, Mottern M, Li H, Williams N, Schoenthaler A, Segal E, Godneva A, Thomas D, Bergman M, Schmidt AM, Sevick MA. Popp CJ, et al. JAMA Netw Open. 2022 Sep 1;5(9):e2233760. doi: 10.1001/jamanetworkopen.2022.33760. JAMA Netw Open. 2022. PMID: 36169954 Free PMC article. Clinical Trial.
IMPORTANCE: Interindividual variability in postprandial glycemic response (PPGR) to the same foods may explain why low glycemic index or load and low-carbohydrate diet interventions have mixed weight loss outcomes. A precision nutrition approach that e …
IMPORTANCE: Interindividual variability in postprandial glycemic response (PPGR) to the same foods may explain why low glyc …
A New Approach to Personalized Nutrition: Postprandial Glycemic Response and its Relationship to Gut Microbiota.
Guizar-Heredia R, Noriega LG, Rivera AL, Resendis-Antonio O, Guevara-Cruz M, Torres N, Tovar AR. Guizar-Heredia R, et al. Arch Med Res. 2023 Apr;54(3):176-188. doi: 10.1016/j.arcmed.2023.02.007. Epub 2023 Mar 27. Arch Med Res. 2023. PMID: 36990891 Review.
In recent years, continuous glucose monitoring has made it possible to establish predictions on the effect of different dietary foods on PPGRs through machine learning methods, which use algorithms that integrate genetic, biochemical, physiological and gut microbiota variables fo …
In recent years, continuous glucose monitoring has made it possible to establish predictions on the effect of different dietary foods on PPG …
Effect of low glycaemic index or load dietary patterns on glycaemic control and cardiometabolic risk factors in diabetes: systematic review and meta-analysis of randomised controlled trials.
Chiavaroli L, Lee D, Ahmed A, Cheung A, Khan TA, Blanco S, Mejia, Mirrahimi A, Jenkins DJA, Livesey G, Wolever TMS, Rahelić D, Kahleová H, Salas-Salvadó J, Kendall CWC, Sievenpiper JL. Chiavaroli L, et al. BMJ. 2021 Aug 4;374:n1651. doi: 10.1136/bmj.n1651. BMJ. 2021. PMID: 34348965 Free PMC article.
ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Randomised controlled trials of three or more weeks investigating the effect of diets with low glycaemic index (GI)/glycaemic load (GL) in diabetes. OUTCOME AND MEASURES: The primary outcome was glycated haemoglobin (HbA1c …
ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Randomised controlled trials of three or more weeks investigating the effect of diets with low …
Precision nutrition for prevention and management of type 2 diabetes.
Wang DD, Hu FB. Wang DD, et al. Lancet Diabetes Endocrinol. 2018 May;6(5):416-426. doi: 10.1016/S2213-8587(18)30037-8. Epub 2018 Feb 9. Lancet Diabetes Endocrinol. 2018. PMID: 29433995 Review.
By integrating these technologies with big data analytics, precision nutrition has the potential to provide personalised nutrition guidance for more effective prevention and management of type 2 diabetes. ...Evidence is needed to support the efficacy, cost-ef …
By integrating these technologies with big data analytics, precision nutrition has the potential to provide personalised nu …
Effects of personalized diets by prediction of glycemic responses on glycemic control and metabolic health in newly diagnosed T2DM: a randomized dietary intervention pilot trial.
Rein M, Ben-Yacov O, Godneva A, Shilo S, Zmora N, Kolobkov D, Cohen-Dolev N, Wolf BC, Kosower N, Lotan-Pompan M, Weinberger A, Halpern Z, Zelber-Sagi S, Elinav E, Segal E. Rein M, et al. BMC Med. 2022 Feb 9;20(1):56. doi: 10.1186/s12916-022-02254-y. BMC Med. 2022. PMID: 35135549 Free PMC article. Clinical Trial.
We sought to evaluate the clinical effects of a personalized postprandial-targeting (PPT) diet on glycemic control and metabolic health in individuals with newly diagnosed T2DM as compared to the commonly recommended Mediterranean-style (MED) diet. ...The PPT diet r …
We sought to evaluate the clinical effects of a personalized postprandial-targeting (PPT) diet on glycemic control and metabol …
Human postprandial responses to food and potential for precision nutrition.
Berry SE, Valdes AM, Drew DA, Asnicar F, Mazidi M, Wolf J, Capdevila J, Hadjigeorgiou G, Davies R, Al Khatib H, Bonnett C, Ganesh S, Bakker E, Hart D, Mangino M, Merino J, Linenberg I, Wyatt P, Ordovas JM, Gardner CD, Delahanty LM, Chan AT, Segata N, Franks PW, Spector TD. Berry SE, et al. Nat Med. 2020 Jun;26(6):964-973. doi: 10.1038/s41591-020-0934-0. Epub 2020 Jun 11. Nat Med. 2020. PMID: 32528151 Free PMC article.
Metabolic responses to food influence risk of cardiometabolic disease, but large-scale high-resolution studies are lacking. ...We developed a machine-learning model that predicted both triglyceride (r = 0.47) and glycemic (r = 0.77) responses to food intake. …
Metabolic responses to food influence risk of cardiometabolic disease, but large-scale high-resolution studies are lacking. ...We dev …
1,781 results