Val66Met BDNF Polymorphism Implies a Different Way to Recover From Stroke Rather Than a Worse Overall Recoverability
Bibliographic record
Abstract
In search for individualized predictors of stroke recovery, the Val66Met polymorphism of the brain-derived neurotrophic factor (BDNF) is attracting great interest, because it has a negative impact on neurotrophin function. Since stroke recovery relies on brain plastic processes, on which BDNF is permissive, the dominant thought is in favor of a worse recovery in Met carriers. Conversely, we suggest that Met carriers do not differ in terms of absolute ability to recover from stroke, but they do differ on the way they recover. In particular, Met carriers rely more on subcortical plasticity, while ValVal patients more on intracortical plastic processes. Indeed, the direct evidence of impaired Met carrier recovery is inconsistent, as a high worldwide diffusion of the polymorphism suggests. The plasticity taking place in cortex, which is the one targeted by noninvasive brain stimulation strategies aimed at enhancing recovery, is less pronounced in Met carrier stroke patients, who have instead spared global recovery potential. Enhanced subcortical plasticity sustains better stroke recovery of Met carrier mice: this may also happen in humans, explaining the weaker interhemispheric cortical excitability imbalance recently described in Met carriers. Thus, BDNF haplotype determines mechanisms and structures involved in stroke recovery. The less pronounced cortical plasticity of Met carrier implies that plastic changes induced by interventional neurophysiological protocols would be better predictors of ValVal chronic outcome and those protocols would be more effective to boost their recovery. Other strategies, more focused on subcortical mechanisms, should be used in Met carriers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".