Stress-induced glucocorticoid receptor activation determines functional recovery following ischemic stroke
Bibliographic record
Abstract
BACKGROUND: A major consequence of stroke is permanent motor disturbance, such as postural imbalance and loss of skilled movement. The degree of neuronal and functional loss and subsequent recovery after stroke is influenced by hypothalamic-pituitary-adrenal axis activation and the response to glucocorticoid hormones. This study investigated if recovery after stroke is related to glucocorticoid receptor (GR) activation in a rat model of stroke. METHODS: Adult male rats were pre-trained and tested in a skilled reaching task and received a focal ischemic motor cortex lesion. One group of animals received daily restraint stress starting one week pre-lesion up to three weeks post-lesion. Immuno-histochemical analysis of GR expression was performed to determine receptor activation. RESULTS: Stress reduced reaching success in naïve animals and diminished recovery of limb use. Exaggerated functional loss in stressed rats was related to increased GR activation in the lesion hemisphere as indicated by nuclear GR location. CONCLUSION: These findings provide a mechanistic link between stress-induced motor disability and GR activation in a rat model of stroke. The elevated receptor activation proposes synergistic effects of stress and stroke to modulate the impact of glucocorticoids on motor system function at the genomic level. The modulation of GR biosynthesis may alter responsiveness to stroke treatment and compromise recovery.
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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 | 0.000 |
| 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".