Hydrogel-delivered brain-derived neurotrophic factor promotes tissue repair and recovery after stroke
Bibliographic record
Abstract
Stroke is the leading cause of adult disability. Systemic delivery of candidate neural repair therapies is limited by the blood-brain barrier and off-target effects. We tested a bioengineering approach for local depot release of BDNF from the infarct cavity for neural repair in chronic periods after stroke. The brain release levels of a hyaluronic acid hydrogel + BDNF were tested in several stroke models in mouse (strains C57Bl/6, DBA) and non-human primate ( Macaca fascicularis) and tracked with MRI. The behavioral recovery effects of hydrogel + BDNF and the effects on tissue repair outcomes were determined. Hydrogel-delivered BDNF diffuses from the stroke cavity into peri-infarct tissue over 3 weeks in two mouse stroke models, compared with 1 week for direct BDNF injection. Hydrogel delivery of BDNF promotes recovery of motor function. Mapping of motor system connections indicates that hydrogel-BDNF induces axonal sprouting within existing cortical and cortico-striatal systems. Pharmacogenetic studies show that hydrogel-BDNF induces the initial migration of immature neurons into the peri-infarct cortex and their long-term survival. In chronic stroke in the non-human primate, hydrogel-released BDNF can be detected up to 2 cm from the infarct, a distance relevant to human functional recovery in stroke. The hydrogel can be tracked by MRI in mouse and primate.
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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".