Unraveling the potential of gasotransmitters as neurogenic and neuroprotective molecules: focus on Alzheimer’s and Parkinson’s diseases
Bibliographic record
Abstract
Alzheimer's disease and Parkinson's disease are the two most prevalent neurodegenerative disorders worldwide, both characterized by progressive neuronal loss. Despite distinct pathophysiological features, they share cellular dysfunctions such as abnormal protein aggregation, oxidative stress, and neuroinflammation, research into which might be beneficial for developing novel therapeutic strategies that could tackle both conditions. This review highlights the emerging role of the gasotransmitters nitric oxide, carbon monoxide and hydrogen sulfide as modulators of adult neurogenesis and neuroprotection in Alzheimer's disease and Parkinson's disease. We have gathered recent evidence demonstrating that these endogenous gases exert anti-inflammatory, antioxidant, and anti-apoptotic effects, and, critically, promote neurogenesis - suggesting a dual neuroprotective and neuroregenerative therapeutic potential. The unique physicochemical features of these gasotransmitters, including their ability to cross the blood-brain barrier and diffuse rapidly throughout the neural tissue, further support their suitability as candidates for innovative neuroregenerative treatments. While clinical translation remains challenging, harnessing the neurogenic and neuroprotective actions of these gasotransmitters may offer transformative avenues for addressing the increasing burden of Alzheimer's disease and Parkinson's disease.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".