The age‐related attenuation in long‐term potentiation is associated with microglial activation
Bibliographic record
Abstract
It is well established that inflammatory changes contribute to brain ageing, and an increased concentration of proinflammatory cytokine, interleukin-1beta (IL-1beta), has been reported in the aged brain associated with a deficit in long-term potentiation (LTP) in rat hippocampus. The precise age at which changes are initiated is unclear. In this study, we investigate parallel changes in markers of inflammation and LTP in 3-, 9- and 15-month-old rats. We report evidence of increased hippocampal concentrations of the proinflammatory cytokines IL-1alpha, IL-18 and interferon-gamma (IFNgamma), which are accompanied by deficits in LTP in the older rats. We also show an increase in expression of markers of microglial activation, CD86, CD40 and intercellular adhesion molecules (ICAM). Associated with these changes, we observed a significant impairment of hippocampal LTP in the same rats. The importance of microglial activation in the attenuation of long-term potentiation (LTP) was demonstrated using an inhibitor of microglial activation, minocycline; partial restoration of LTP in 15-month-old rats was observed following administration of minocycline. We propose that signs of neuroinflammation are observed in middle age and that these changes, which are characterized by microglial activation, may be triggered by IL-18.
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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) | 0.000 | 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 | 0.001 |
| 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".