Gut Microbiota in Acute Ischemic Stroke: From Pathophysiology to Therapeutic Implications
Bibliographic record
Abstract
The microbiota–gut–brain axis is considered a central regulator of the immune system after acute ischemic stroke (AIS), with a potential role in determining outcome. Several pathways are involved in the evolution of gut microbiota dysbiosis after AIS. Brain–gut and gut–brain signaling pathways involve bidirectional communication between the hypothalamic–pituitary–adrenal axis, the autonomic nervous system, the enteric nervous system, and the immune cells of the gut. Alterations in gut microbiome can be a risk factor and may also lead to AIS. Both risk factors for AIS and gut-microbiome composition are influenced by similar factors, including diabetes, hypertension, hyperlipidemia, obesity, and vascular dysfunction. Furthermore, the systemic inflammatory response after AIS may yield liver, renal, respiratory, gastrointestinal, and cardiovascular impairment, including the multiple organ dysfunction syndrome. This review focus on biochemical, immunological and neuroanatomical modulation of gut microbiota and its possible systemic harmful effects after AIS, as well as the role of ischemic stroke on microbiota composition. Finally, we highlight the role of gut microbiota as a potential novel therapeutic target in acute ischemic stroke.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".