Inhibition of inflammation by minocycline improves heart failure and depression-like behaviour in rats after myocardial infarction
Bibliographic record
Abstract
RATIONALE: Patients with heart failure have an increased incidence of depression. Central and peripheral inflammation play a major role in the pathophysiology of both heart failure and depression. AIM: Minocycline is an antibiotic that inhibits microglia activation and release of pro-inflammatory cytokines. We assessed effects of minocycline on extent of heart failure and depression at 2 and 8 weeks post myocardial infarction. METHODS/RESULTS: Male Wistar rats were randomly divided into 3 groups: (i) sham + vehicle; (ii) MI + vehicle; and (iii) MI + minocycline with n/group of 8, 9 and 9 at 2 weeks, and 10, 16, 8 at weeks, respectively. Oral minocycline (50 mg/kg/day) or vehicle started 2 days before surgery. Depression-like behaviour was assessed with sucrose preference and forced swim tests, and cardiac function with echo and hemodynamics. After myocardial infarction, microglia activation and plasma/brain pro-inflammatory cytokines increased, which were mostly prevented by minocycline. At 8 weeks, cardiac dysfunction was attenuated by minocycline: infarct size (MI + Vehicle 29±1, MI + Min 23±1%), ejection fraction (Sham 80±1, MI + Vehicle 48±2, MI + Min 58±2%) and end diastolic pressure (Sham 3.2±0.3, MI + Vehicle 18.2±1.1, MI + Min 8.5±0.9 mm Hg). Depression-like behaviour was significantly improved by minocycline in sucrose preference test (% Sucrose Intake: Sham 96±1, MI + Vehicle 78±2, MI + Min 87±2) and forced swim test (% Immobile: Sham 40±4, MI + Vehicle 61±3, MI + Min 37±6). CONCLUSION: Rats post myocardial infarction develop systemic inflammation, heart failure and depression-like behaviour that are all attenuated by minocycline. Targeting (neuro) inflammation may represent new therapeutic strategy for patients with heart failure and depression.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".