Changes in energy homeostasis, gut peptides, and gut microbiota in Emiratis with obesity after bariatric surgery
Bibliographic record
Abstract
BACKGROUND: Obesity is a growing health concern worldwide, including United Arab Emirates. Bariatric surgery is an effective treatment option, with to date unclear weight loss mechanisms. In this prospective study, we explored post-bariatric surgery changes in energy homeostasis, gut peptides, hormones, and gut microbiota. METHOD: We recruited 19 Emirati adults who were planning to undergo sleeve gastrectomy (SG). We assessed the energy requirements using 24-hour diet recalls, indirect calorimetry for resting energy expenditure (REE), and a questionnaire for appetite. Anthropometrics included body mass index (BMI), waist circumference, waist-to-height ratio, fat mass, fat-free mass, and percentage of body fat. Gut peptides, including peptide YY (PYY), glucagon-like peptide-1/2 (GLP-1/2), ghrelin (GHR), cholecystokinin (CCK), insulin, and leptin, were quantified using ELISA. Gut microbiota composition at phylum and genus levels, including the Firmicutes/Bacteroidetes (F/B) ratio and alpha (α) and beta (β) diversity, was determined by sequencing amplicons of the V3-V4 region of the 16S rRNA at baseline and three months post-surgery. Comparisons used paired sample T-test, Wilcoxon, and McNemar test. QIIME 2 was used to identify taxa and their relative abundance; subsequent analyses were done in R for (α) and (β) diversity (package qiime2R) and Wilcoxon signed-rank test in R for differences in microbiota at phylum and genus levels. We conducted Spearman correlation analyses between genera and energy homeostasis, appetite, anthropometrics, hormones, and gut peptides. RESULTS: At three months post-SG, energy intake, appetite, all anthropometric indices, insulin, leptin, and GLP-1 significantly decreased; PYY and GHR significantly increased, and REE was stable. β-diversity of the gut microbiota and its composition at phylum and genus levels significantly changed post-surgery, yet F/B remained constant. Energy intake, BMI, and appetite negatively correlated with several taxa that significantly increased post-SG. CONCLUSION: Gut peptides, hormones, and microbiota change partly account for bariatric surgery's weight-loss benefits. Understanding these alterations can inform personalized interventions targeting obesity.
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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 | 0.001 |
| 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".