Functional recovery from tactile stimulation after perinatal cortical injury is mediated by FGF-2
Bibliographic record
Abstract
Abstract The consequences of perinatal brain injury can be devastating but currently there are few effective treatments. We sought to determine if tactile stimulation (TS) or exogenous application of fibroblast growth factor-2 (FGF-2) following injury could reverse the behavioral loss. Infant rats received frontal cortex removals on postnatal day 4 (P4) or a sham surgery. The TS animals received thrice-daily 15-minute bouts of stimulation (Experiment 1) on the day following surgery until weaning. In Experiment 2, treated animals received subcutaneous injections of FGF-2 once daily for one week, postsurgery. Behavioral testing began on postnatal day 60. Brains were later processed for Golgi analysis. We show in Experiment 1, that tactilely stimulating infant rats with perinatal cortical injury stimulates functional recovery and reverses injury-related changes in neuronal morphology in the cerebral cortex. The TS induction of recovery is associated with changes in expression of FGF-2 in both the skin and brain. Direct administration of FGF-2 (Experiment 2) is also effective in facilitating recovery, although not as completely as TS. These results suggest that early behavioral intervention after perinatal cortical injury can stimulate plastic neuronal changes that can underlie functional recovery and that these changes are mediated, in part, through an upregulation of FGF-2.
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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) | 0.000 | 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) | 0.002 | 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".