VGF is required for recovery after focal stroke
Bibliographic record
Abstract
The high incidence of ischemic stroke worldwide and poor efficacy of neuroprotective drugs has increased the need for novel therapies in stroke recovery. Transcription of the neurosecretory protein VGF (non-acronym) is enhanced following ischemic stroke and proposed to be important for stroke recovery. To determine the requirement for VGF in recovery, we created Vgffl/fl:Nestin-Cre conditional knockout (Vgf cKO) mice and induced a photothrombotic focal ischemic stroke. Naïve Vgf cKO mice had significant less body weight in the absence of gross defects in brain size, cortical lamination, or deficits in locomotor activity compared to wildtype controls. Following a focal stroke, the Vgf cKO mice had greater deficits including impaired recovery of forepaw motor deficits at 2- and 4-weeks post stroke. The increase in deficits occurred in the absence of any difference in lesion size and was accompanied by a striking loss of stroke-induced migration of SVZ-derived immature neurons to the peri-infarct region. Importantly, exogenous adenoviral delivery of VGF (AdVGF) significantly improved recovery in the Vgf cKO mice and was able to rescue the immature neuron migration defect observed. Taken together, our results define a requirement for VGF in post stroke recovery and identify VGF peptides as a potential future therapeutic.
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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".