Intermittent fasting positively modulates human gut microbial diversity and ameliorates blood lipid profile
Bibliographic record
Abstract
Aim The aim was to evaluate the impact of intermittent fasting (IF) on human body mass index (BMI) and serum lipid profile thorough constructive rectification of gut microbiota. Methods and results Fourteen healthy women and thirty-one men were included in the study. Their blood and fecal samples were collected before and at the end of the study. Blood parameters, anthropometric values, and gut microbiology were noted to investigate the impact of intermittent fasting (IF) on human gut microbiota and physiology. Our data revealed that IF reduces the body weight and improves blood lipid profile, such as increasing high-density lipoprotein (HDL) and decreasing total cholesterol, triglycerides, and low- and very low-density lipoprotein levels. IF also decreases culturable aerobic bacterial count and increased fungal count. It was also found that the gut metagenome is altered considerably after IF. The human fecal bacterial diversity exhibited significant changes in decreased overall bacterial population, increased bacterial diversity (alpha diversity), and promoted evenness within the bacterial population at the species level. Anti-inflammatory bacteria Lactobacillus and Bifidobacterium were favorably increased, while pathogenic bacteria were decreased. Conclusion Collectively, these results indicated that IF could improve lipid profile and body weight in humans, and the potential mechanisms might be via regulating gut microbiota. Significance and impact of the study We demonstrated for the first time that IF improved body weight and blood lipid profile, indicating that IF could mitigate gut microbiota in humans.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".