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
Background Dietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but many patients fail to achieve clinical goals with diet alone. We sought to evaluate the clinical effects of a personalized postprandial-targeting (PP...
Saved in:
| Published in | BMC medicine Vol. 20; no. 1; pp. 56 - 13 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
BioMed Central
09.02.2022
BioMed Central Ltd BMC |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1741-7015 1741-7015 |
| DOI | 10.1186/s12916-022-02254-y |
Cover
| Abstract | Background
Dietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but many patients fail to achieve clinical goals with diet alone. 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.
Methods
We enrolled 23 adults with newly diagnosed T2DM (aged 53.5 ± 8.9 years, 48% males) for a randomized crossover trial of two 2-week-long dietary interventions. Participants were blinded to their assignment to one of the two sequence groups: either PPT-MED or MED-PPT diets. The PPT diet relies on a machine learning algorithm that integrates clinical and microbiome features to predict personal postprandial glucose responses (PPGR). We further evaluated the long-term effects of PPT diet on glycemic control and metabolic health by an additional 6-month PPT intervention (
n
= 16). Participants were connected to continuous glucose monitoring (CGM) throughout the study and self-recorded dietary intake using a smartphone application.
Results
In the crossover intervention, the PPT diet lead to significant lower levels of CGM-based measures as compared to the MED diet, including average PPGR (mean difference between diets, − 19.8 ± 16.3 mg/dl × h,
p
< 0.001), mean glucose (mean difference between diets, − 7.8 ± 5.5 mg/dl,
p
< 0.001), and daily time of glucose levels > 140 mg/dl (mean difference between diets, − 2.42 ± 1.7 h/day,
p
< 0.001). Blood fructosamine also decreased significantly more during PPT compared to MED intervention (mean change difference between diets, − 16.4 ± 37 μmol/dl,
p
< 0.0001). At the end of 6 months, the PPT intervention leads to significant improvements in multiple metabolic health parameters, among them HbA1c (mean ± SD, − 0.39 ± 0.48%,
p
< 0.001), fasting glucose (− 16.4 ± 24.2 mg/dl,
p
= 0.02) and triglycerides (− 49 ± 46 mg/dl,
p
< 0.001). Importantly, 61% of the participants exhibited diabetes remission, as measured by HbA1c < 6.5%. Finally, some clinical improvements were significantly associated with gut microbiome changes per person.
Conclusion
In this crossover trial in subjects with newly diagnosed T2DM, a PPT diet improved CGM-based glycemic measures significantly more than a Mediterranean-style MED diet. Additional 6-month PPT intervention further improved glycemic control and metabolic health parameters, supporting the clinical efficacy of this approach.
Trial registration
ClinicalTrials.gov
number, NCT01892956 |
|---|---|
| AbstractList | Dietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but many patients fail to achieve clinical goals with diet alone. 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.BACKGROUNDDietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but many patients fail to achieve clinical goals with diet alone. 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.We enrolled 23 adults with newly diagnosed T2DM (aged 53.5 ± 8.9 years, 48% males) for a randomized crossover trial of two 2-week-long dietary interventions. Participants were blinded to their assignment to one of the two sequence groups: either PPT-MED or MED-PPT diets. The PPT diet relies on a machine learning algorithm that integrates clinical and microbiome features to predict personal postprandial glucose responses (PPGR). We further evaluated the long-term effects of PPT diet on glycemic control and metabolic health by an additional 6-month PPT intervention (n = 16). Participants were connected to continuous glucose monitoring (CGM) throughout the study and self-recorded dietary intake using a smartphone application.METHODSWe enrolled 23 adults with newly diagnosed T2DM (aged 53.5 ± 8.9 years, 48% males) for a randomized crossover trial of two 2-week-long dietary interventions. Participants were blinded to their assignment to one of the two sequence groups: either PPT-MED or MED-PPT diets. The PPT diet relies on a machine learning algorithm that integrates clinical and microbiome features to predict personal postprandial glucose responses (PPGR). We further evaluated the long-term effects of PPT diet on glycemic control and metabolic health by an additional 6-month PPT intervention (n = 16). Participants were connected to continuous glucose monitoring (CGM) throughout the study and self-recorded dietary intake using a smartphone application.In the crossover intervention, the PPT diet lead to significant lower levels of CGM-based measures as compared to the MED diet, including average PPGR (mean difference between diets, - 19.8 ± 16.3 mg/dl × h, p < 0.001), mean glucose (mean difference between diets, - 7.8 ± 5.5 mg/dl, p < 0.001), and daily time of glucose levels > 140 mg/dl (mean difference between diets, - 2.42 ± 1.7 h/day, p < 0.001). Blood fructosamine also decreased significantly more during PPT compared to MED intervention (mean change difference between diets, - 16.4 ± 37 μmol/dl, p < 0.0001). At the end of 6 months, the PPT intervention leads to significant improvements in multiple metabolic health parameters, among them HbA1c (mean ± SD, - 0.39 ± 0.48%, p < 0.001), fasting glucose (- 16.4 ± 24.2 mg/dl, p = 0.02) and triglycerides (- 49 ± 46 mg/dl, p < 0.001). Importantly, 61% of the participants exhibited diabetes remission, as measured by HbA1c < 6.5%. Finally, some clinical improvements were significantly associated with gut microbiome changes per person.RESULTSIn the crossover intervention, the PPT diet lead to significant lower levels of CGM-based measures as compared to the MED diet, including average PPGR (mean difference between diets, - 19.8 ± 16.3 mg/dl × h, p < 0.001), mean glucose (mean difference between diets, - 7.8 ± 5.5 mg/dl, p < 0.001), and daily time of glucose levels > 140 mg/dl (mean difference between diets, - 2.42 ± 1.7 h/day, p < 0.001). Blood fructosamine also decreased significantly more during PPT compared to MED intervention (mean change difference between diets, - 16.4 ± 37 μmol/dl, p < 0.0001). At the end of 6 months, the PPT intervention leads to significant improvements in multiple metabolic health parameters, among them HbA1c (mean ± SD, - 0.39 ± 0.48%, p < 0.001), fasting glucose (- 16.4 ± 24.2 mg/dl, p = 0.02) and triglycerides (- 49 ± 46 mg/dl, p < 0.001). Importantly, 61% of the participants exhibited diabetes remission, as measured by HbA1c < 6.5%. Finally, some clinical improvements were significantly associated with gut microbiome changes per person.In this crossover trial in subjects with newly diagnosed T2DM, a PPT diet improved CGM-based glycemic measures significantly more than a Mediterranean-style MED diet. Additional 6-month PPT intervention further improved glycemic control and metabolic health parameters, supporting the clinical efficacy of this approach.CONCLUSIONIn this crossover trial in subjects with newly diagnosed T2DM, a PPT diet improved CGM-based glycemic measures significantly more than a Mediterranean-style MED diet. Additional 6-month PPT intervention further improved glycemic control and metabolic health parameters, supporting the clinical efficacy of this approach.ClinicalTrials.gov number, NCT01892956.TRIAL REGISTRATIONClinicalTrials.gov number, NCT01892956. Dietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but many patients fail to achieve clinical goals with diet alone. 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. We enrolled 23 adults with newly diagnosed T2DM (aged 53.5 [+ or -] 8.9 years, 48% males) for a randomized crossover trial of two 2-week-long dietary interventions. Participants were blinded to their assignment to one of the two sequence groups: either PPT-MED or MED-PPT diets. The PPT diet relies on a machine learning algorithm that integrates clinical and microbiome features to predict personal postprandial glucose responses (PPGR). We further evaluated the long-term effects of PPT diet on glycemic control and metabolic health by an additional 6-month PPT intervention (n = 16). Participants were connected to continuous glucose monitoring (CGM) throughout the study and self-recorded dietary intake using a smartphone application. In the crossover intervention, the PPT diet lead to significant lower levels of CGM-based measures as compared to the MED diet, including average PPGR (mean difference between diets, - 19.8 [+ or -] 16.3 mg/dl x h, p < 0.001), mean glucose (mean difference between diets, - 7.8 [+ or -] 5.5 mg/dl, p < 0.001), and daily time of glucose levels > 140 mg/dl (mean difference between diets, - 2.42 [+ or -] 1.7 h/day, p < 0.001). Blood fructosamine also decreased significantly more during PPT compared to MED intervention (mean change difference between diets, - 16.4 [+ or -] 37 [mu]mol/dl, p < 0.0001). At the end of 6 months, the PPT intervention leads to significant improvements in multiple metabolic health parameters, among them HbA1c (mean [+ or -] SD, - 0.39 [+ or -] 0.48%, p < 0.001), fasting glucose (- 16.4 [+ or -] 24.2 mg/dl, p = 0.02) and triglycerides (- 49 [+ or -] 46 mg/dl, p < 0.001). Importantly, 61% of the participants exhibited diabetes remission, as measured by HbA1c < 6.5%. Finally, some clinical improvements were significantly associated with gut microbiome changes per person. In this crossover trial in subjects with newly diagnosed T2DM, a PPT diet improved CGM-based glycemic measures significantly more than a Mediterranean-style MED diet. Additional 6-month PPT intervention further improved glycemic control and metabolic health parameters, supporting the clinical efficacy of this approach. Background Dietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but many patients fail to achieve clinical goals with diet alone. 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. Methods We enrolled 23 adults with newly diagnosed T2DM (aged 53.5 [+ or -] 8.9 years, 48% males) for a randomized crossover trial of two 2-week-long dietary interventions. Participants were blinded to their assignment to one of the two sequence groups: either PPT-MED or MED-PPT diets. The PPT diet relies on a machine learning algorithm that integrates clinical and microbiome features to predict personal postprandial glucose responses (PPGR). We further evaluated the long-term effects of PPT diet on glycemic control and metabolic health by an additional 6-month PPT intervention (n = 16). Participants were connected to continuous glucose monitoring (CGM) throughout the study and self-recorded dietary intake using a smartphone application. Results In the crossover intervention, the PPT diet lead to significant lower levels of CGM-based measures as compared to the MED diet, including average PPGR (mean difference between diets, - 19.8 [+ or -] 16.3 mg/dl x h, p < 0.001), mean glucose (mean difference between diets, - 7.8 [+ or -] 5.5 mg/dl, p < 0.001), and daily time of glucose levels > 140 mg/dl (mean difference between diets, - 2.42 [+ or -] 1.7 h/day, p < 0.001). Blood fructosamine also decreased significantly more during PPT compared to MED intervention (mean change difference between diets, - 16.4 [+ or -] 37 [mu]mol/dl, p < 0.0001). At the end of 6 months, the PPT intervention leads to significant improvements in multiple metabolic health parameters, among them HbA1c (mean [+ or -] SD, - 0.39 [+ or -] 0.48%, p < 0.001), fasting glucose (- 16.4 [+ or -] 24.2 mg/dl, p = 0.02) and triglycerides (- 49 [+ or -] 46 mg/dl, p < 0.001). Importantly, 61% of the participants exhibited diabetes remission, as measured by HbA1c < 6.5%. Finally, some clinical improvements were significantly associated with gut microbiome changes per person. Conclusion In this crossover trial in subjects with newly diagnosed T2DM, a PPT diet improved CGM-based glycemic measures significantly more than a Mediterranean-style MED diet. Additional 6-month PPT intervention further improved glycemic control and metabolic health parameters, supporting the clinical efficacy of this approach. Trial registration ClinicalTrials.gov number, NCT01892956 Keywords: Type 2 diabetes mellitus, Gut microbiome, Dietary intervention, Postprandial glucose responses, Personalized nutrition Abstract Background Dietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but many patients fail to achieve clinical goals with diet alone. 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. Methods We enrolled 23 adults with newly diagnosed T2DM (aged 53.5 ± 8.9 years, 48% males) for a randomized crossover trial of two 2-week-long dietary interventions. Participants were blinded to their assignment to one of the two sequence groups: either PPT-MED or MED-PPT diets. The PPT diet relies on a machine learning algorithm that integrates clinical and microbiome features to predict personal postprandial glucose responses (PPGR). We further evaluated the long-term effects of PPT diet on glycemic control and metabolic health by an additional 6-month PPT intervention (n = 16). Participants were connected to continuous glucose monitoring (CGM) throughout the study and self-recorded dietary intake using a smartphone application. Results In the crossover intervention, the PPT diet lead to significant lower levels of CGM-based measures as compared to the MED diet, including average PPGR (mean difference between diets, − 19.8 ± 16.3 mg/dl × h, p < 0.001), mean glucose (mean difference between diets, − 7.8 ± 5.5 mg/dl, p < 0.001), and daily time of glucose levels > 140 mg/dl (mean difference between diets, − 2.42 ± 1.7 h/day, p < 0.001). Blood fructosamine also decreased significantly more during PPT compared to MED intervention (mean change difference between diets, − 16.4 ± 37 μmol/dl, p < 0.0001). At the end of 6 months, the PPT intervention leads to significant improvements in multiple metabolic health parameters, among them HbA1c (mean ± SD, − 0.39 ± 0.48%, p < 0.001), fasting glucose (− 16.4 ± 24.2 mg/dl, p = 0.02) and triglycerides (− 49 ± 46 mg/dl, p < 0.001). Importantly, 61% of the participants exhibited diabetes remission, as measured by HbA1c < 6.5%. Finally, some clinical improvements were significantly associated with gut microbiome changes per person. Conclusion In this crossover trial in subjects with newly diagnosed T2DM, a PPT diet improved CGM-based glycemic measures significantly more than a Mediterranean-style MED diet. Additional 6-month PPT intervention further improved glycemic control and metabolic health parameters, supporting the clinical efficacy of this approach. Trial registration ClinicalTrials.gov number, NCT01892956 Dietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but many patients fail to achieve clinical goals with diet alone. 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. We enrolled 23 adults with newly diagnosed T2DM (aged 53.5 ± 8.9 years, 48% males) for a randomized crossover trial of two 2-week-long dietary interventions. Participants were blinded to their assignment to one of the two sequence groups: either PPT-MED or MED-PPT diets. The PPT diet relies on a machine learning algorithm that integrates clinical and microbiome features to predict personal postprandial glucose responses (PPGR). We further evaluated the long-term effects of PPT diet on glycemic control and metabolic health by an additional 6-month PPT intervention (n = 16). Participants were connected to continuous glucose monitoring (CGM) throughout the study and self-recorded dietary intake using a smartphone application. In the crossover intervention, the PPT diet lead to significant lower levels of CGM-based measures as compared to the MED diet, including average PPGR (mean difference between diets, - 19.8 ± 16.3 mg/dl × h, p < 0.001), mean glucose (mean difference between diets, - 7.8 ± 5.5 mg/dl, p < 0.001), and daily time of glucose levels > 140 mg/dl (mean difference between diets, - 2.42 ± 1.7 h/day, p < 0.001). Blood fructosamine also decreased significantly more during PPT compared to MED intervention (mean change difference between diets, - 16.4 ± 37 μmol/dl, p < 0.0001). At the end of 6 months, the PPT intervention leads to significant improvements in multiple metabolic health parameters, among them HbA1c (mean ± SD, - 0.39 ± 0.48%, p < 0.001), fasting glucose (- 16.4 ± 24.2 mg/dl, p = 0.02) and triglycerides (- 49 ± 46 mg/dl, p < 0.001). Importantly, 61% of the participants exhibited diabetes remission, as measured by HbA1c < 6.5%. Finally, some clinical improvements were significantly associated with gut microbiome changes per person. In this crossover trial in subjects with newly diagnosed T2DM, a PPT diet improved CGM-based glycemic measures significantly more than a Mediterranean-style MED diet. Additional 6-month PPT intervention further improved glycemic control and metabolic health parameters, supporting the clinical efficacy of this approach. ClinicalTrials.gov number, NCT01892956. Background Dietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but many patients fail to achieve clinical goals with diet alone. 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. Methods We enrolled 23 adults with newly diagnosed T2DM (aged 53.5 ± 8.9 years, 48% males) for a randomized crossover trial of two 2-week-long dietary interventions. Participants were blinded to their assignment to one of the two sequence groups: either PPT-MED or MED-PPT diets. The PPT diet relies on a machine learning algorithm that integrates clinical and microbiome features to predict personal postprandial glucose responses (PPGR). We further evaluated the long-term effects of PPT diet on glycemic control and metabolic health by an additional 6-month PPT intervention ( n = 16). Participants were connected to continuous glucose monitoring (CGM) throughout the study and self-recorded dietary intake using a smartphone application. Results In the crossover intervention, the PPT diet lead to significant lower levels of CGM-based measures as compared to the MED diet, including average PPGR (mean difference between diets, − 19.8 ± 16.3 mg/dl × h, p < 0.001), mean glucose (mean difference between diets, − 7.8 ± 5.5 mg/dl, p < 0.001), and daily time of glucose levels > 140 mg/dl (mean difference between diets, − 2.42 ± 1.7 h/day, p < 0.001). Blood fructosamine also decreased significantly more during PPT compared to MED intervention (mean change difference between diets, − 16.4 ± 37 μmol/dl, p < 0.0001). At the end of 6 months, the PPT intervention leads to significant improvements in multiple metabolic health parameters, among them HbA1c (mean ± SD, − 0.39 ± 0.48%, p < 0.001), fasting glucose (− 16.4 ± 24.2 mg/dl, p = 0.02) and triglycerides (− 49 ± 46 mg/dl, p < 0.001). Importantly, 61% of the participants exhibited diabetes remission, as measured by HbA1c < 6.5%. Finally, some clinical improvements were significantly associated with gut microbiome changes per person. Conclusion In this crossover trial in subjects with newly diagnosed T2DM, a PPT diet improved CGM-based glycemic measures significantly more than a Mediterranean-style MED diet. Additional 6-month PPT intervention further improved glycemic control and metabolic health parameters, supporting the clinical efficacy of this approach. Trial registration ClinicalTrials.gov number, NCT01892956 Background Dietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but many patients fail to achieve clinical goals with diet alone. 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. Methods We enrolled 23 adults with newly diagnosed T2DM (aged 53.5 ± 8.9 years, 48% males) for a randomized crossover trial of two 2-week-long dietary interventions. Participants were blinded to their assignment to one of the two sequence groups: either PPT-MED or MED-PPT diets. The PPT diet relies on a machine learning algorithm that integrates clinical and microbiome features to predict personal postprandial glucose responses (PPGR). We further evaluated the long-term effects of PPT diet on glycemic control and metabolic health by an additional 6-month PPT intervention (n = 16). Participants were connected to continuous glucose monitoring (CGM) throughout the study and self-recorded dietary intake using a smartphone application. Results In the crossover intervention, the PPT diet lead to significant lower levels of CGM-based measures as compared to the MED diet, including average PPGR (mean difference between diets, − 19.8 ± 16.3 mg/dl × h, p < 0.001), mean glucose (mean difference between diets, − 7.8 ± 5.5 mg/dl, p < 0.001), and daily time of glucose levels > 140 mg/dl (mean difference between diets, − 2.42 ± 1.7 h/day, p < 0.001). Blood fructosamine also decreased significantly more during PPT compared to MED intervention (mean change difference between diets, − 16.4 ± 37 μmol/dl, p < 0.0001). At the end of 6 months, the PPT intervention leads to significant improvements in multiple metabolic health parameters, among them HbA1c (mean ± SD, − 0.39 ± 0.48%, p < 0.001), fasting glucose (− 16.4 ± 24.2 mg/dl, p = 0.02) and triglycerides (− 49 ± 46 mg/dl, p < 0.001). Importantly, 61% of the participants exhibited diabetes remission, as measured by HbA1c < 6.5%. Finally, some clinical improvements were significantly associated with gut microbiome changes per person. Conclusion In this crossover trial in subjects with newly diagnosed T2DM, a PPT diet improved CGM-based glycemic measures significantly more than a Mediterranean-style MED diet. Additional 6-month PPT intervention further improved glycemic control and metabolic health parameters, supporting the clinical efficacy of this approach. Trial registration ClinicalTrials.gov number, NCT01892956 |
| ArticleNumber | 56 |
| Audience | Academic |
| Author | Ben-Yacov, Orly Elinav, Eran Zmora, Niv Weinberger, Adina Rein, Michal Lotan-Pompan, Maya Kosower, Noa Wolf, Bat-Chen Godneva, Anastasia Kolobkov, Dmitry Zelber-Sagi, Shira Segal, Eran Cohen-Dolev, Noa Halpern, Zamir Shilo, Smadar |
| Author_xml | – sequence: 1 givenname: Michal surname: Rein fullname: Rein, Michal organization: Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Department of Molecular Cell Biology, Weizmann Institute of Science, School of Public Health, University of Haifa – sequence: 2 givenname: Orly surname: Ben-Yacov fullname: Ben-Yacov, Orly organization: Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Department of Molecular Cell Biology, Weizmann Institute of Science – sequence: 3 givenname: Anastasia surname: Godneva fullname: Godneva, Anastasia organization: Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Department of Molecular Cell Biology, Weizmann Institute of Science – sequence: 4 givenname: Smadar surname: Shilo fullname: Shilo, Smadar organization: Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Department of Molecular Cell Biology, Weizmann Institute of Science, Pediatric Diabetes Unit, Ruth Rappaport Children’s Hospital, Rambam Healthcare Campus – sequence: 5 givenname: Niv surname: Zmora fullname: Zmora, Niv organization: Immunology Department, Weizmann Institute of Science, Digestive Center, Tel Aviv Sourasky Medical Center, Internal Medicine Department, Tel Aviv Sourasky Medical Center – sequence: 6 givenname: Dmitry surname: Kolobkov fullname: Kolobkov, Dmitry organization: Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Department of Molecular Cell Biology, Weizmann Institute of Science – sequence: 7 givenname: Noa surname: Cohen-Dolev fullname: Cohen-Dolev, Noa organization: Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Department of Molecular Cell Biology, Weizmann Institute of Science – sequence: 8 givenname: Bat-Chen surname: Wolf fullname: Wolf, Bat-Chen organization: Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Department of Molecular Cell Biology, Weizmann Institute of Science – sequence: 9 givenname: Noa surname: Kosower fullname: Kosower, Noa organization: Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Department of Molecular Cell Biology, Weizmann Institute of Science – sequence: 10 givenname: Maya surname: Lotan-Pompan fullname: Lotan-Pompan, Maya organization: Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Department of Molecular Cell Biology, Weizmann Institute of Science – sequence: 11 givenname: Adina surname: Weinberger fullname: Weinberger, Adina organization: Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Department of Molecular Cell Biology, Weizmann Institute of Science – sequence: 12 givenname: Zamir surname: Halpern fullname: Halpern, Zamir organization: Digestive Center, Tel Aviv Sourasky Medical Center, Internal Medicine Department, Tel Aviv Sourasky Medical Center – sequence: 13 givenname: Shira surname: Zelber-Sagi fullname: Zelber-Sagi, Shira organization: School of Public Health, University of Haifa – sequence: 14 givenname: Eran surname: Elinav fullname: Elinav, Eran email: eran.elinav@weizmann.ac.il organization: Immunology Department, Weizmann Institute of Science – sequence: 15 givenname: Eran surname: Segal fullname: Segal, Eran email: eran.segal@weizmann.ac.il organization: Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Department of Molecular Cell Biology, Weizmann Institute of Science |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35135549$$D View this record in MEDLINE/PubMed |
| BookMark | eNp9k89u1DAQxiNURP_AC3BAkZAQly22k9gJh0pVKVCpiEs5W7POOOuVYy92tmh5Gp6BR-DJcHZbdrdCVRQlmXzfb-wZz3F24LzDLHtJySmlNX8XKWsonxDGxrsqJ6sn2REVJZ0IQquDnffD7DjGOSGsEqJ8lh0WFS2qqmyOst-XWqMaYu51vsAQvQNrfmKbtwZTdLrKFwFbowbj3ajp7Ephb1QeMC68i5icbhtV3g3B2xxcm_c4wNTbFJ0h2GGWG5c7_GFXiQ2d8zFluWEfvrzPIQ_J4Psx8Z9fY2YIqyQfMNyiW6deGOuHfAgG7PPsqQYb8cXd8yT79vHy5uLz5Prrp6uL8-uJEqQcJqKuOPCmYjVqQaekaKZQUCwAocSqrRgSYIw0vGAVaaDmWCrNQXEQGlo6LU6yqw239TCXi2D6tCrpwch1wIdOQhiMsihVo7jWdQ0aWamwrUtek7al6Ys3TJeJdbZhLZbTHluVdhXA7kH3_zgzk52_lXXNOOc0Ad7eAYL_vsQ4yN5EhdaCQ7-MknEmaMELWiXp6wfSuV-G1NdRVZBSCM7IVtVB2oBx2qe8aoTKc94UvBacjKzT_6jS1Y7tTsdRmxTfM7zZMWwaH71djk2M-8JXuxX5V4r7o5kE9Uaggo8xoJbKDDBy0hKMlZTIcQrkZgpkmgC5ngK5Slb2wHpPf9RUbEwxiV2HYVu2R1x_AdUXHbs |
| CitedBy_id | crossref_primary_10_1007_s11883_022_01078_8 crossref_primary_10_1038_s41598_024_55105_6 crossref_primary_10_1016_j_chom_2022_05_007 crossref_primary_10_1186_s12982_024_00213_x crossref_primary_10_1038_s41564_024_01728_4 crossref_primary_10_3390_nu15143250 crossref_primary_10_1016_j_ajcnut_2024_11_028 crossref_primary_10_1016_j_cmet_2024_02_002 crossref_primary_10_1002_pdi_2475 crossref_primary_10_1007_s11154_023_09830_4 crossref_primary_10_1016_j_cmpbup_2024_100141 crossref_primary_10_1186_s40795_024_00836_y crossref_primary_10_1210_clinem_dgae061 crossref_primary_10_1016_j_crbiot_2024_100211 crossref_primary_10_1186_s13073_022_01092_0 crossref_primary_10_3389_fendo_2023_1168688 crossref_primary_10_1016_j_lfs_2022_121265 crossref_primary_10_1097_HEP_0000000000000987 crossref_primary_10_1016_j_arcmed_2023_02_007 crossref_primary_10_3390_ijms24076775 crossref_primary_10_3390_nu16010164 crossref_primary_10_1038_s41579_023_00998_9 crossref_primary_10_1007_s13300_024_01545_2 crossref_primary_10_1002_14651858_CD015877 crossref_primary_10_1146_annurev_med_042423_042542 crossref_primary_10_1016_j_ijbiomac_2024_134331 crossref_primary_10_1007_s11892_024_01553_3 crossref_primary_10_1021_acsami_2c18452 crossref_primary_10_1080_1061186X_2024_2448711 crossref_primary_10_1038_s41598_024_52461_1 crossref_primary_10_1111_dom_16261 crossref_primary_10_1016_j_ajcnut_2024_04_031 crossref_primary_10_3389_fnut_2023_1308348 crossref_primary_10_2478_jtim_2023_0116 crossref_primary_10_3390_diagnostics13121995 crossref_primary_10_1016_S2468_1253_23_00357_6 crossref_primary_10_1186_s13098_022_00969_9 crossref_primary_10_1186_s13063_024_08337_w crossref_primary_10_1038_s41467_024_45355_3 crossref_primary_10_1016_j_cmet_2024_06_001 crossref_primary_10_1177_19322968241274800 crossref_primary_10_1093_nsr_nwaf039 crossref_primary_10_1186_s13098_023_00992_4 crossref_primary_10_1016_j_tifs_2023_02_007 crossref_primary_10_3389_fnut_2023_1282741 crossref_primary_10_1016_j_diabres_2025_112111 crossref_primary_10_3390_cells13060477 crossref_primary_10_1016_j_bbi_2023_09_022 crossref_primary_10_1016_j_xcrm_2024_101759 crossref_primary_10_1038_s43016_024_00959_2 crossref_primary_10_1128_msystems_01300_22 crossref_primary_10_1038_s41467_024_53832_y crossref_primary_10_4093_jkd_2023_24_4_190 crossref_primary_10_1001_jamanetworkopen_2022_33760 crossref_primary_10_1016_j_copbio_2022_102884 crossref_primary_10_1016_j_pcd_2024_03_006 crossref_primary_10_1136_bmjopen_2022_062498 crossref_primary_10_1089_jmf_2022_0154 crossref_primary_10_1111_joim_13574 crossref_primary_10_3390_nu15163571 crossref_primary_10_1016_j_advnut_2025_100398 crossref_primary_10_1016_S2213_8587_24_00093_7 crossref_primary_10_1093_infdis_jiae167 crossref_primary_10_1177_19322968251321508 crossref_primary_10_15252_embr_202255664 crossref_primary_10_4103_ijdt_ijdt_26_23 crossref_primary_10_1016_j_bspc_2023_105809 crossref_primary_10_1021_acs_jafc_4c04949 |
| Cites_doi | 10.1016/j.cell.2015.11.001 10.2337/dc11-0567 10.1093/ajcn/34.3.362 10.1016/j.atherosclerosis.2013.12.033 10.2337/dc13-0325 10.2337/dc19-S006 10.3945/an.116.012120 10.1038/nmeth.2221 10.1038/nature05414 10.2337/diaclin.33.2.97 10.1111/dme.13603 10.1016/j.ebiom.2019.11.051 10.3945/ajcn.111.012138 10.1111/1462-2920.13589 10.1038/4441022a 10.2337/dc17-0636 10.3390/nu6041406 10.1001/jama.2018.0245 10.2337/dc21-0162 10.1016/S2213-8587(20)30117-0 10.2337/cd17-0119 10.3390/nu5041071 10.1161/CIRCULATIONAHA.114.010815 10.1093/ajcn/nqaa046 10.3390/nu11030655 10.1093/ajcn/51.2.241 10.1016/S0140-6736(11)60442-X 10.1016/B978-0-323-54835-9.00004-1 10.2337/dc13-2899 10.1016/j.cell.2019.01.001 10.1136/bmjdrc-2016-000354 10.1016/j.diabres.2017.03.024 10.1016/j.numecd.2013.04.008 10.1093/clinchem/36.1.136 10.1172/JCI100818 10.1038/nbt.2942 10.1038/nmeth.1923 10.1073/pnas.0504978102 10.1016/0009-8981(84)90251-1 10.1016/j.cmet.2017.09.008 |
| ContentType | Journal Article |
| Copyright | The Author(s) 2022 2022. The Author(s). COPYRIGHT 2022 BioMed Central Ltd. 2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| Copyright_xml | – notice: The Author(s) 2022 – notice: 2022. The Author(s). – notice: COPYRIGHT 2022 BioMed Central Ltd. – notice: 2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| DBID | C6C AAYXX CITATION CGR CUY CVF ECM EIF NPM 3V. 7QL 7U9 7X7 7XB 88E 8FI 8FJ 8FK ABUWG AFKRA AZQEC BENPR C1K CCPQU DWQXO FYUFA GHDGH H94 K9. M0S M1P M7N PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQQKQ PQUKI 7X8 5PM DOA |
| DOI | 10.1186/s12916-022-02254-y |
| DatabaseName | Springer Nature OA Free Journals CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed ProQuest Central (Corporate) Bacteriology Abstracts (Microbiology B) Virology and AIDS Abstracts Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest Central UK/Ireland ProQuest Central Essentials ProQuest Central Environmental Sciences and Pollution Management ProQuest One ProQuest Central Korea Proquest Health Research Premium Collection Health Research Premium Collection (Alumni) AIDS and Cancer Research Abstracts ProQuest Health & Medical Complete (Alumni) ProQuest Health & Medical Collection Medical Database Algology Mycology and Protozoology Abstracts (Microbiology C) ProQuest Central Premium ProQuest One Academic (New) Publicly Available Content Database ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic ProQuest One Academic UKI Edition MEDLINE - Academic PubMed Central (Full Participant titles) DOAJ Directory of Open Access Journal Collection |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) ProQuest One Community College ProQuest One Health & Nursing Environmental Sciences and Pollution Management ProQuest Central Health Research Premium Collection Health and Medicine Complete (Alumni Edition) ProQuest Central Korea Bacteriology Abstracts (Microbiology B) Algology Mycology and Protozoology Abstracts (Microbiology C) Health & Medical Research Collection AIDS and Cancer Research Abstracts ProQuest Central (New) ProQuest Medical Library (Alumni) Virology and AIDS Abstracts ProQuest One Academic Eastern Edition ProQuest Hospital Collection Health Research Premium Collection (Alumni) ProQuest Hospital Collection (Alumni) ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic |
| DatabaseTitleList | MEDLINE - Academic MEDLINE Publicly Available Content Database |
| Database_xml | – sequence: 1 dbid: C6C name: Springer Nature OA Free Journals url: http://www.springeropen.com/ sourceTypes: Publisher – sequence: 2 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 3 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 4 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database – sequence: 5 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Medicine |
| EISSN | 1741-7015 |
| EndPage | 13 |
| ExternalDocumentID | oai_doaj_org_article_c9c6ff88afe24ced84680dd1e24692f4 PMC8826661 A693687605 35135549 10_1186_s12916_022_02254_y |
| Genre | Randomized Controlled Trial Research Support, Non-U.S. Gov't Journal Article |
| GeographicLocations | Israel |
| GeographicLocations_xml | – name: Israel |
| GrantInformation_xml | – fundername: DayTwo inc. – fundername: ; |
| GroupedDBID | --- 0R~ 23N 2WC 4.4 53G 5GY 5VS 6J9 6PF 7X7 88E 8FI 8FJ AAFWJ AAJSJ AASML AAWTL ABDBF ABUWG ACGFO ACGFS ACIHN ACPRK ACUHS ADBBV ADRAZ ADUKV AEAQA AENEX AFKRA AFPKN AFRAH AHBYD AHMBA AHYZX ALMA_UNASSIGNED_HOLDINGS AMKLP AMTXH AOIJS BAPOH BAWUL BCNDV BENPR BFQNJ BMC BPHCQ BVXVI C6C CCPQU CS3 DIK DU5 E3Z EAD EAP EAS EBD EBLON EBS EMB EMK EMOBN ESX F5P FYUFA GROUPED_DOAJ GX1 HMCUK HYE IAO IHR IHW INH INR ITC KQ8 M1P M48 MK0 M~E O5R O5S OK1 OVT P2P PGMZT PHGZM PHGZT PIMPY PJZUB PPXIY PQQKQ PROAC PSQYO PUEGO RBZ RNS ROL RPM RSV SMD SOJ SV3 TR2 TUS UKHRP WOQ WOW XSB AAYXX ALIPV CITATION -5E -5G -A0 -BR 3V. ACRMQ ADINQ C24 CGR CUY CVF ECM EIF NPM PMFND 7QL 7U9 7XB 8FK AZQEC C1K DWQXO H94 K9. M7N PKEHL PQEST PQUKI 7X8 5PM |
| ID | FETCH-LOGICAL-c704t-7856a69528ef71b039ba31e3aea4e5d52e0a2209632509a86e4cf6ac6a7fad1b3 |
| IEDL.DBID | M48 |
| ISSN | 1741-7015 |
| IngestDate | Wed Aug 27 01:20:41 EDT 2025 Thu Aug 21 18:19:19 EDT 2025 Sun Aug 24 03:15:59 EDT 2025 Sat Jul 26 02:22:05 EDT 2025 Tue Jun 17 21:05:45 EDT 2025 Tue Jun 10 20:36:36 EDT 2025 Thu May 22 21:23:31 EDT 2025 Thu Jan 02 22:54:50 EST 2025 Tue Jul 01 02:51:29 EDT 2025 Thu Apr 24 23:09:16 EDT 2025 Sat Sep 06 07:29:14 EDT 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 1 |
| Keywords | Personalized nutrition Dietary intervention Type 2 diabetes mellitus Gut microbiome Postprandial glucose responses |
| Language | English |
| License | 2022. The Author(s). Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c704t-7856a69528ef71b039ba31e3aea4e5d52e0a2209632509a86e4cf6ac6a7fad1b3 |
| Notes | ObjectType-Article-2 SourceType-Scholarly Journals-1 content type line 14 ObjectType-Feature-3 ObjectType-Evidence Based Healthcare-1 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 ObjectType-Undefined-3 |
| OpenAccessLink | https://www.proquest.com/docview/2630477620?pq-origsite=%requestingapplication% |
| PMID | 35135549 |
| PQID | 2630477620 |
| PQPubID | 42775 |
| PageCount | 13 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_c9c6ff88afe24ced84680dd1e24692f4 pubmedcentral_primary_oai_pubmedcentral_nih_gov_8826661 proquest_miscellaneous_2627136315 proquest_journals_2630477620 gale_infotracmisc_A693687605 gale_infotracacademiconefile_A693687605 gale_healthsolutions_A693687605 pubmed_primary_35135549 crossref_citationtrail_10_1186_s12916_022_02254_y crossref_primary_10_1186_s12916_022_02254_y springer_journals_10_1186_s12916_022_02254_y |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2022-02-09 |
| PublicationDateYYYYMMDD | 2022-02-09 |
| PublicationDate_xml | – month: 02 year: 2022 text: 2022-02-09 day: 09 |
| PublicationDecade | 2020 |
| PublicationPlace | London |
| PublicationPlace_xml | – name: London – name: England |
| PublicationTitle | BMC medicine |
| PublicationTitleAbbrev | BMC Med |
| PublicationTitleAlternate | BMC Med |
| PublicationYear | 2022 |
| Publisher | BioMed Central BioMed Central Ltd BMC |
| Publisher_xml | – name: BioMed Central – name: BioMed Central Ltd – name: BMC |
| References | K Ogurtsova (2254_CR3) 2017; 128 PA Dyson (2254_CR25) 2018; 35 CD Gardner (2254_CR12) 2018; 319 O Ben-Yacov (2254_CR22) 2021; 44 E Pasolli (2254_CR32) 2019; 176 HU Wolf (2254_CR26) 1984; 136 S Taheri (2254_CR8) 2020; 8 K Esposito (2254_CR7) 2014; 37 RE Ley (2254_CR35) 2006; 444 J Bao (2254_CR10) 2011; 34 2254_CR20 MD Mifflin (2254_CR23) 1990; 51 M Georgoulis (2254_CR24) 2014; 6 American Diabetes Association (2254_CR9) 2015; 33 J Li (2254_CR29) 2014; 32 E Selvin (2254_CR2) 2014; 130 ED Schleicher (2254_CR27) 1990; 36 American Diabetes Association (2254_CR1) 2018; 36 American Diabetes Association (2254_CR5) 2019; 42 DC Greenwood (2254_CR18) 2013; 36 PJ Turnbaugh (2254_CR36) 2006; 444 O Snorgaard (2254_CR13) 2017; 5 RS Kootte (2254_CR34) 2017; 26 RC Andrews (2254_CR40) 2011; 378 JW Conn (2254_CR11) 1936; 15 H Dodd (2254_CR15) 2011; 94 DJ Jenkins (2254_CR14) 1981; 34 M Gurung (2254_CR38) 2020; 51 2254_CR4 RW Beck (2254_CR6) 2017; 40 BE Millen (2254_CR19) 2016; 7 D Zeevi (2254_CR21) 2015; 163 B Langmead (2254_CR31) 2012; 9 AS Kristo (2254_CR16) 2013; 5 L Schwingshackl (2254_CR17) 2013; 23 T Miida (2254_CR28) 2014; 233 P Louis (2254_CR37) 2017; 19 GK Fragiadakis (2254_CR39) 2020; 111 RE Ley (2254_CR33) 2005; 102 S Marco-Sola (2254_CR30) 2012; 9 |
| References_xml | – volume: 163 start-page: 1079 issue: 5 year: 2015 ident: 2254_CR21 publication-title: Cell doi: 10.1016/j.cell.2015.11.001 – volume: 34 start-page: 2146 issue: 10 year: 2011 ident: 2254_CR10 publication-title: Diabetes Care doi: 10.2337/dc11-0567 – volume: 34 start-page: 362 issue: 3 year: 1981 ident: 2254_CR14 publication-title: Am J Clin Nutr doi: 10.1093/ajcn/34.3.362 – volume: 233 start-page: 253 issue: 1 year: 2014 ident: 2254_CR28 publication-title: Atherosclerosis doi: 10.1016/j.atherosclerosis.2013.12.033 – volume: 36 start-page: 4166 issue: 12 year: 2013 ident: 2254_CR18 publication-title: Diabetes Care doi: 10.2337/dc13-0325 – volume: 42 start-page: S61 issue: Supplement_1 year: 2019 ident: 2254_CR5 publication-title: Diabetes Care doi: 10.2337/dc19-S006 – volume: 7 start-page: 438 issue: 3 year: 2016 ident: 2254_CR19 publication-title: Adv Nutr doi: 10.3945/an.116.012120 – volume: 9 start-page: 1185 issue: 12 year: 2012 ident: 2254_CR30 publication-title: Nat Methods doi: 10.1038/nmeth.2221 – volume: 444 start-page: 1027 issue: 7122 year: 2006 ident: 2254_CR36 publication-title: Nature doi: 10.1038/nature05414 – volume: 33 start-page: 97 issue: 2 year: 2015 ident: 2254_CR9 publication-title: Clin Diabetes doi: 10.2337/diaclin.33.2.97 – volume: 35 start-page: 541 issue: 5 year: 2018 ident: 2254_CR25 publication-title: Diabet Med doi: 10.1111/dme.13603 – volume: 51 start-page: 102590 year: 2020 ident: 2254_CR38 publication-title: EBioMedicine doi: 10.1016/j.ebiom.2019.11.051 – volume: 94 start-page: 992 issue: 4 year: 2011 ident: 2254_CR15 publication-title: Am J Clin Nutr doi: 10.3945/ajcn.111.012138 – volume: 19 start-page: 29 issue: 1 year: 2017 ident: 2254_CR37 publication-title: Environ Microbiol doi: 10.1111/1462-2920.13589 – volume: 444 start-page: 1022 issue: 7122 year: 2006 ident: 2254_CR35 publication-title: Nature doi: 10.1038/4441022a – volume: 40 start-page: 994 issue: 8 year: 2017 ident: 2254_CR6 publication-title: Diabetes Care doi: 10.2337/dc17-0636 – volume: 6 start-page: 1406 issue: 4 year: 2014 ident: 2254_CR24 publication-title: Nutrients doi: 10.3390/nu6041406 – volume: 319 start-page: 667 issue: 7 year: 2018 ident: 2254_CR12 publication-title: JAMA doi: 10.1001/jama.2018.0245 – volume: 44 start-page: 1980 issue: 9 year: 2021 ident: 2254_CR22 publication-title: Diabetes Care doi: 10.2337/dc21-0162 – volume: 8 start-page: 477 issue: 6 year: 2020 ident: 2254_CR8 publication-title: Lancet Diabetes Endocrinol doi: 10.1016/S2213-8587(20)30117-0 – volume: 36 start-page: 14 issue: 1 year: 2018 ident: 2254_CR1 publication-title: Clin Diabetes doi: 10.2337/cd17-0119 – volume: 5 start-page: 1071 issue: 4 year: 2013 ident: 2254_CR16 publication-title: Nutrients doi: 10.3390/nu5041071 – volume: 130 start-page: 1374 issue: 16 year: 2014 ident: 2254_CR2 publication-title: Circulation doi: 10.1161/CIRCULATIONAHA.114.010815 – volume: 111 start-page: 1127 issue: 6 year: 2020 ident: 2254_CR39 publication-title: Am J Clin Nutr doi: 10.1093/ajcn/nqaa046 – ident: 2254_CR20 doi: 10.3390/nu11030655 – volume: 51 start-page: 241 issue: 2 year: 1990 ident: 2254_CR23 publication-title: Am J Clin Nutr doi: 10.1093/ajcn/51.2.241 – volume: 378 start-page: 129 issue: 9786 year: 2011 ident: 2254_CR40 publication-title: Lancet doi: 10.1016/S0140-6736(11)60442-X – ident: 2254_CR4 doi: 10.1016/B978-0-323-54835-9.00004-1 – volume: 37 start-page: 1824 issue: 7 year: 2014 ident: 2254_CR7 publication-title: Diabetes Care doi: 10.2337/dc13-2899 – volume: 176 start-page: 649 year: 2019 ident: 2254_CR32 publication-title: Cell doi: 10.1016/j.cell.2019.01.001 – volume: 5 issue: 1 year: 2017 ident: 2254_CR13 publication-title: BMJ Open Diabetes Res Care doi: 10.1136/bmjdrc-2016-000354 – volume: 128 start-page: 40 year: 2017 ident: 2254_CR3 publication-title: Diabetes Res Clin Pract doi: 10.1016/j.diabres.2017.03.024 – volume: 23 start-page: 699 issue: 8 year: 2013 ident: 2254_CR17 publication-title: Nutr Metab Cardiovasc Dis doi: 10.1016/j.numecd.2013.04.008 – volume: 36 start-page: 136 issue: 1 year: 1990 ident: 2254_CR27 publication-title: Clin Chem doi: 10.1093/clinchem/36.1.136 – volume: 15 start-page: 665 issue: 6 year: 1936 ident: 2254_CR11 publication-title: J Clin Invest doi: 10.1172/JCI100818 – volume: 32 start-page: 834 issue: 8 year: 2014 ident: 2254_CR29 publication-title: Nat Biotechnol doi: 10.1038/nbt.2942 – volume: 9 start-page: 357 issue: 4 year: 2012 ident: 2254_CR31 publication-title: Nat Methods doi: 10.1038/nmeth.1923 – volume: 102 start-page: 11070 issue: 31 year: 2005 ident: 2254_CR33 publication-title: Proc Natl Acad Sci USA doi: 10.1073/pnas.0504978102 – volume: 136 start-page: 95 issue: 1 year: 1984 ident: 2254_CR26 publication-title: Clin Chim Acta doi: 10.1016/0009-8981(84)90251-1 – volume: 26 start-page: 611 year: 2017 ident: 2254_CR34 publication-title: Cell Metab doi: 10.1016/j.cmet.2017.09.008 |
| SSID | ssj0025774 |
| Score | 2.5825887 |
| Snippet | Background
Dietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but many... Dietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but many patients fail... Background Dietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but many... Abstract Background Dietary modifications are crucial for managing newly diagnosed type 2 diabetes mellitus (T2DM) and preventing its health complications, but... |
| SourceID | doaj pubmedcentral proquest gale pubmed crossref springer |
| SourceType | Open Website Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 56 |
| SubjectTerms | Adult Algorithms Analysis Biomedicine Blood Glucose - metabolism Blood Glucose Self-Monitoring Blood sugar monitoring Carbohydrates Care and treatment Clinical medicine Complications Customization Dairy products Diabetes Diabetes mellitus Diabetes mellitus (non-insulin dependent) Diabetes Mellitus, Type 2 - diagnosis Diagnosis Diet Diet, Mediterranean Dietary intake Dietary intervention Evaluation Female Food Food intake Glucose Glucose monitoring Glycemic Control Glycemic index Glycosylated hemoglobin Gut microbiome Hemoglobin Humans Intervention Intestinal microflora Learning algorithms Long-term effects Machine learning Male Meals Medical diagnosis Medicine Medicine & Public Health Metabolism Methods Microbiomes Middle Aged Nutrition research Parameters Personalized nutrition Pilot Projects Postprandial glucose responses Questionnaires Remission Research Article Risk factors Triglycerides Type 2 diabetes Type 2 diabetes mellitus |
| SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journal Collection dbid: DOA link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV3NbtQwELZQD4gL4p-UAkZC4gBR49hxYm7lp6qQllMr9Wb5F1ZKs6vd7SE8Dc_AI_BkjO1kuykCLhz2sONxnMyMPd_I4zFCLwsgg9-p88oXLmeK6FwoqnOjADto7QCShMPJs8_85Ix9Oq_Od676CjlhqTxwEtyhEYZ73zTKu5IZZ8FfNoW1BP5xUfpYCbQQxRhMDaFWBahmPCLT8MM1eDUSkm3L8KtY3k_cUKzW__uavOOUridMXts1jc7o-A66PaBIfJTe_i664bp76OZs2Ce_j36kosRrvPB4OcLtb85iO3dA1T1ergJz0Erg-dL2JmTJ41VKmXXQs7uiDvnsWHUWX7gN2E0L1HSEEs87DNC87eHZMWsPRjktP8zeYoXBD9rFRRj45_cwslr1eL6TZImX83axwfHmkAfo7Pjj6fuTfLidITd1wTZ53VRccVGVjfM10QUVWlHiqHKKucpWpStUCarhFFCWUA13zHiuDFe1V5Zo-hDtdYvOPUbYW9dQ5izV2jNiPEBprzj3THlGuRAZIqOypBlKl4cbNFoZQ5iGy6RgCcqVUcGyz9DrbZ9lKtzxV-53wQa2nKHodiSAKcrBFOW_TDFDz4MFyST-7dIhj7igHLxOUWXoVeQIiwd8gFHDGQgQQyjDNeE8mHDCpDfT5tFK5bDorGXJwx4qeLciQy-2zaFnSKTr3OIy8JQ1oZwSeMSjZNTbj6YVCegTxF1PzH0ilWlLN_8aS5JDnAZxMMnQm3FiXL3Wn6W-_z-k_gTdKtPEzgtxgPY2q0v3FIDiRj-La8IvuoRqeA priority: 102 providerName: Directory of Open Access Journals – databaseName: Health & Medical Collection dbid: 7X7 link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwfV1Jb9QwFLagSIgLYidQwEhIHCBqvMRJuKCyVBXScGqluVmOl3akaTLMTA_hX_EPeXacTFNEDznEfk5iv-1z_PyM0LsMisHvFGnuMptyReq0UqxOtQLsUNcWIInfnDz7KY5P-Y95Po8_3DYxrHKwicFQm1b7f-QHVPgFIlDd7PPqV-pPjfKrq_EIjdvoTkhdBvJczHcTrhywzbBRphQHG_BtxIfcUn_lPO0mzijk7P_XMl9xTdfDJq-tnQaXdPQA3Y9YEh_2zH-IbtnmEbo7i6vlj9GfPjXxBrcOrwbQ_dsabBYWSusOr9ae2PPG05wtO-1j5fG6D5y10LLZlcaodqwagy_sFqRnCaX9Rkq8aDAA9GUHzw6xe_CWE_pt9gkrDN7QtBfji9W6w4srkZZ4tVi2WxyOD3mCTo--n3w9TuMRDakuMr5NizIXSlQ5La0rSJ2xqlaMWKas4jY3ObWZohSmSQygVqVKYbl2QmmhCqcMqdlTtNe0jX2OsDO2ZNwaVteOE-0ATzslhOPKcSaqKkFk4JXUMX-5P0ZjKcM8phSy568E3srAX9kl6MPYZtVn77iR-osXgZHSZ94OBe36TEZFlrrSwrmyVM5Srq0B_FZmxhC4ExV1PEFvvADJfvRH-yEPRcUEuJ4sT9D7QOEtCHRAq7gRAobB5-KaUO5PKEHz9bR6EFIZLc9G7vQkQW_Hat_SR9M1tr30NLQgTDACj3jWy_TYaZYTD0FhuIuJtE9GZVrTLM5DXnKYrMFkmCTo46AXu8_6_6i_uLkXL9E92mtsmlX7aG-7vrSvAAdu69dB2f8C6mBfpw priority: 102 providerName: ProQuest – databaseName: Springer Nature OA Free Journals dbid: C6C link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwELagSIgL4k2ggJGQOEBE_IiTcCuFqkJaTq3Um-UnXWmbrHa3h_Br-hv6E_hljJ1HN-UhcdjDjsdx4pnxfJZnxgi9yYAMfqdIc5-5lCui00oxnRoF2EFrB5AkJCfPvonDY_71JD_py-SEXJjt83tSig9r8EckhMnS8Mt52t5Et3LCRDyYFfvj5ioHHDMkxfyx38TxxPr8v6_CW27oeojktXPS6H4O7qG7PW7Ee52g76Mbrn6Abs_6k_GH6LIrQ7zGjcfLAWD_cBbbuQOqbvFyFZiDHALP90VrQlw8XnVBsg561lfUPoIdq9riM7cBTVkAtUuaxPMaAxhftPDsGKcHoxzRz7OPWGHwfLY5CwP_vAgjq1WL51thlXg5XzQbHO8KeYSOD74c7R-m_X0MqSkyvkmLMhdKVDktnS-IzlilFSOOKae4y21OXaYohT0RA1xVqVI4brxQRqjCK0s0e4x26qZ2TxH21pWMO8u09pwYD-DZKyE8V54zUVUJIoOwpOmLlYc7MxYyblpKITsBSxCujAKWbYLejX2WXamOf3J_CjowcoYy25EA2id7q5WmMsL7slTeUW6cBbBWZtYS-Ccq6nmCXgUNkt30j4uF3BMVE-BnsjxBbyNHWC7gA4zqsx5gGkLhrQnn7oQTzNxMmwctlf0ys5ZUhFNT8GdZgl6PzaFnCJ2rXXMeeGgR7IXAI550Sj1-NANLAjwJ011M1H0yK9OWen4ai5DDzgx2viRB7wfDuHqtv8_6s_9jf47u0M6E06zaRTub1bl7ASBwo19G6_8FwRJaTg priority: 102 providerName: Springer Nature |
| Title | 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 |
| URI | https://link.springer.com/article/10.1186/s12916-022-02254-y https://www.ncbi.nlm.nih.gov/pubmed/35135549 https://www.proquest.com/docview/2630477620 https://www.proquest.com/docview/2627136315 https://pubmed.ncbi.nlm.nih.gov/PMC8826661 https://doaj.org/article/c9c6ff88afe24ced84680dd1e24692f4 |
| Volume | 20 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlR1ri9QwMNwDxC_i2-q5RhD8oPWaJk1bQeR2veMQ9pDjFha_hLRNzoVeu3b3wPpr_A3-BH-Zk_Rx1_MU_LALnUyS7TwyM5vJBKEXHoDB7oRuoD3lMkkSN5Y0cVMJvkOSKHBJzOHk6RE_nLGP82C-gbrrjloCrq4N7cx9UrMqf_Pta_0eFP6dVfiI767AZhGTSuubT8DcehNtg2XiJhibsn5XAaTTVmUGJ5y4IdjB7hDNtWMMDJWt5__nqn3JbF1Nqbyyr2rN1cFtdKv1M_FeIxh30IYq7qIb03Yn_R762ZQtXuFS42XnkH9XGc4WCqBJjZeVQTZ8MzineZ2aPHpcNUm1CnoWF9A24x3LIsNnag2SlQO0OWSJFwUG5z2vYWyb1weznPgfpm-xxGAps_LMTPzrh5lZVjVeXErDxMtFXq6xvVvkPpod7J9MDt32_gY3DT22dsMo4JLHgR8pHZLEo3EiKVFUKslUkAW-8qTvQwxFwQ-LZcQVSzWXKZehlhlJ6AO0VZSFeoSwzlREmcpokmhGUg3OtpacayY1ozyOHUQ6Zom0LW5u7tjIhQ1yIi4aBgtgrrAMFrWDXvV9lk1pj39ij40M9JimLLcFlNWpaLVcpHHKtY4iqZXPUpWBcxd5WUbgice-Zg56ZiRINOTvFxexx2PKwS55gYNeWgwj8PACqWxPSQAZTKGuAebOABOWhXTY3Emp6LRK-NzssoL98xz0vG82PU2qXaHKc4Pjh4RySmCIh41Q9y9NA2L8UyB3OBD3AVWGLcXiiy1aDpEcRMrEQa87xbj4WX-n-uP_4tETdNNvNNj14h20ta7O1VPwGdfJCG2G83CEtsf7R5-O4WnCJyP7_8vILhHwfTz-_Bt2m2-n |
| linkProvider | Scholars Portal |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtR3bbtMw1BqdBLwg7hQGMxKIB4gWX-IkSAhtbFPH1gqhTtqbcRx7VOqS0nZC4aOQ-EOOc-syxN72kIfYx07tc3wu9bkg9MqHZpA7oRdY33hckcSLFUs8rUB3SBIDKokLTh6OxOCYfz4JTtbQ7yYWxrlVNjyxZNRprt1_5FtUuAsiOLr-x9kPz1WNcrerTQmNiiwOTfETTLbFh4NdwO9rSvf3xp8GXl1VwNOhz5deGAVCiTigkbEhSXwWJ4oRw5RR3ARpQI2vKAXNnoF2EKtIGK6tUFqo0KqUJAzmvYHWuYto7aH1nb3Rl6-tiReANtWE5kRiawHSlDgnX-qegHtFR_yVVQL-lQUXhOFlR81Lt7WlENy_i-7U2iversjtHloz2X10c1jfzz9Af6pkyAucWzxr1PxfJsXpxEBrUuDZ3AE7anAwp9NCO-98PK9cdQ2MzFattR89VlmKz8wS6HUKrVXoJp5kGEyCaQFzl96C8JUx3R2-xwqD_E3zs_bDal7gyQXfTjybTPMlLguWPETH14K-R6iX5Zl5grBNTcS4SVmSWE60BQ3eKiEsV5YzEcd9RBpcSV1nTHeFO6aytJwiISv8SsCtLPEriz56246ZVflCroTecSTQQrpc32VDPj-VNeuQOtbC2ihS1lCuTQoaY-SnKYE3EVPL-2jTEZCsdr_lWHJbxEyAsPODPnpTQjieBQvQqg69gG1w2b86kBsdSOA1utvdEKmsed1Crk5mH71su91I57-XmfzcwdCQMMEITPG4oul20SwgTumF7Q471N7ZlW5PNvleZkIH8xDMb9JH75pzsfpZ_9_1p1evYhPdGoyHR_LoYHT4DN2m1en1_HgD9Zbzc_MctNBl8qI--hh9u25u8xdAsZ4I |
| linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Lb9QwELagSBUXxLuBQo2ExAGixrHjJNxKy6o8WnFopd4sx4-y0jZZ7aaH8Gv4DfwEfhkzeWw35SFx2MPa4zjxzHi-kWfGhLyMoBnsThomPnKh0KwIc82L0GjADkXhAJJgcvLRsTw8FR_PkrO1LP422n04kuxyGrBKU1nvzq3vVDyTu0uwUgyDZ2P8JSJsbpJbAk0fHtfK_ZXLlQC6GVJl_jhuZI7aqv2_781rxul64OS109PWKE3ukjs9mqR7HfvvkRuuvE82j_rz8gfkR1eceEkrT-cD7P7mLLVTB61FQ-cLJEbuIM35rDEYLU8XXeisg5HlVWsf1051aemFq0F-ZtDapVLSaUkBos8aeHYbvQeznMQHR2-ppmAPbXWBE__8jjPrRUOna8GWdD6dVTVtbxB5SE4n70_2D8P-lobQpJGowzRLpJZ5EmfOp6yIeF5ozhzXTguX2CR2kY5j8JQ4oK1cZ9IJ46U2UqdeW1bwR2SjrEq3Rai3LuPCWV4UXjDjAVJ7LaUX2gsu8zwgbGCWMn0Jc7xJY6ZaVyaTqmOwAuaqlsGqCcjr1Zh5V8Djn9TvUAZWlFh8u22oFueq12VlciO9zzLtXSyMswDhsshaBv9kHnsRkB2UINUt_2oLUXsy5xKsT5QE5FVLgZsIfIDRfS4ELAOW4xpRbo8oQfnNuHuQUtVvPksVSzxLBSsXBeTFqhtHYkBd6apLpIlTxiVn8IjHnVCvPponDFEoLHc6EvfRqox7yunXtjQ5-GvgD7OAvBkU4-q1_r7qT_6PfIdsfjmYqM8fjj89JbfjTpvDKN8mG_Xi0j0DlFgXz9uN4BcJhGWC |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Effects+of+personalized+diets+by+prediction+of+glycemic+responses+on+glycemic+control+and+metabolic+health+in+newly+diagnosed+T2DM%3A+a+randomized%C2%A0dietary+intervention+pilot+trial&rft.jtitle=BMC+medicine&rft.au=Rein%2C+Michal&rft.au=Ben-Yacov%2C+Orly&rft.au=Godneva%2C+Anastasia&rft.au=Shilo%2C+Smadar&rft.date=2022-02-09&rft.issn=1741-7015&rft.eissn=1741-7015&rft.volume=20&rft.issue=1&rft_id=info:doi/10.1186%2Fs12916-022-02254-y&rft.externalDBID=n%2Fa&rft.externalDocID=10_1186_s12916_022_02254_y |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1741-7015&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1741-7015&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1741-7015&client=summon |