Purinergic signaling systems across comparative models of spinal cord injury
Bibliographic record
Abstract
Within the last several decades, the scientific community has made substantial progress in elucidating the complex pathophysiology underlying spinal cord injury. However, despite the many advances using conventional mammalian models, both cellular and axonal regeneration following spinal cord injury have remained out of reach. In this sense, turning to non-mammalian, regenerative species presents a unique opportunity to identify pro-regenerative cues and characterize a spinal cord microenvironment permissive to re-growth. Among the signaling pathways hypothesized to be dysregulated during spinal cord injury is the purinergic signaling system. In addition to its well-known role as energy currency in cells, ATP and its metabolites are small molecule neurotransmitters that mediate many diverse cellular processes within the central nervous system. While our understanding of the roles of the purinergic system following spinal cord injury is limited, this signaling pathway has been implicated in all injury-induced secondary processes, including cellular death, inflammation, reactive gliosis, and neural regeneration. Given that the purinergic system is also evolutionarily conserved between mammalian and non-mammalian species, comparisons of these roles may provide important insights into conditions responsible for recovery success. Here, we compare the secondary processes between key model species and the influence of purinergic signaling in each context. As our understanding of this signaling system and pro-regenerative conditions continues to evolve, so does the potential for the development of novel therapeutic interventions for spinal cord injury.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".