Effects of transcranial direct current stimulation associated with hypocaloric diet on glucose homeostasis in obesity
Bibliographic record
Abstract
Abstract Objective The aim of this study was to test the effects of repetitive active transcranial direct current stimulation (tDCS) over the right dorsolateral prefrontal cortex (rDLPFC) associated with a hypocaloric diet on glucose homeostasis in people with excessive weight. Methods Adults with overweight or obesity were selected in a randomized, double‐blind pilot study to complete 4 weeks (20 sessions) of fixed‐dose tDCS (2 mA, 20 minutes) delivered over the rDLPFC and associated with a standard hypocaloric diet. Participants were randomly assigned (1:1) and stratified by sex to the active tDCS group (active) or the sham tDCS group (sham). Changes in glucose homeostasis were assessed in a 4‐hour liquid meal tolerance test, performed before and after the intervention. Results Twenty‐eight participants were randomized (79% with obesity; mean [SD] age 37.6 [5.8] years). After the intervention, fasting plasma glucose (mean [95% CI], −7.8 mg/dL [−14.0 to −1.6]) and insulin levels (−7.7 μIU/mL [−13.9 to −1.6]) decreased in the active compared with the sham. Similarly, the Matsuda insulin sensitivity index increase in the active (4.7 pmol−1 × mmol−1 [1.6 to 7.8]) compared with the sham (0.6 pmol−1 × mmol−1 [−1.4 to 3.2]). Conclusions Repetitive, active tDCS over the rDLPFC could be a promising noninvasive technique to improve glucose homeostasis in individuals with overweight or obesity on a low‐calorie diet, highlighting the importance of investigating this intervention modality in individuals with type 2 diabetes mellitus.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".