Cyclosporin A Enhances Cell Survival in Neural Precursor Populations in the Adult Central Nervous System
Bibliographic record
Abstract
Cyclosporin A is a widely used immunosuppressive drug that selectively inhibits cell-mediated immune reactions. The discovery of Cyclosporin A has been critical to the success of transplantation therapies and distinguishing cellular mechanisms of the immune response. This PharmSight will focus on a novel application of Cyclosporin A in modulating the fate and behavior of Neural Precursor Cells (NPCs), a cell population consisting of stem cells and their progeny, which provide the basis for adult neurogenesis. Our recently published data indicate that Cyclosporin A, at therapeutically relevant concentrations, acts directly on NPCs to enhance their survival both in vitro and in vivo. The action of Cyclosporin A on NPC survival is promising for the development of regenerative strategies which aim to utilize NPCs to repair and regenerate damaged or diseased Central Nervous System (CNS) tissue. Herein, we present an overview of our recent findings, and further demonstrate the ability of Cyclosporin A to enhance the survival of regionally distinct NPC populations, as well as consider the potential mechanisms by which Cyclosporin A may mediate this effect. Finally we conclude by speculating on the potential therapeutic benefits of Cyclosporin A in the treatment of CNS injury and 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 | 0.000 |
| 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".