Gut microbiota, dysbiosis and atrial fibrillation. Arrhythmogenic mechanisms and potential clinical implications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recent preclinical and observational cohort studies have implicated imbalances in gut microbiota composition as a contributor to atrial fibrillation (AF). The gut microbiota is a complex and dynamic ecosystem containing trillions of microorganisms, which produces bioactive metabolites influencing host health and disease development. In addition to host-specific determinants, lifestyle-related factors such as diet and drugs are important determinants of the gut microbiota composition. In this review, we discuss the evidence suggesting a potential bidirectional association between AF and gut microbiota, identifying gut microbiota-derived metabolites as possible regulators of the AF substrate. We summarize the effect of gut microbiota on the development and progression of AF risk factors, including heart failure, hypertension, obesity, and coronary artery disease. We also discuss the potential anti-arrhythmic effects of pharmacological and diet-induced modifications of gut microbiota composition, which may modulate and prevent the progression to AF. Finally, we highlight important gaps in knowledge and areas requiring future investigation. Although data supporting a direct relationship between gut microbiota and AF are very limited at the present time, emerging preclinical and clinical research dealing with mechanistic interactions between gut microbiota and AF is important as it may lead to new insights into AF pathophysiology and the discovery of novel therapeutic targets for AF.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 it