Mechanisms of tissue injury in multiple sclerosis: opportunities for neuroprotective therapy
Bibliographic record
Abstract
Development of neuroprotective therapies for multiple sclerosis is dependent on defining the precise mechanisms whereby immune effector cells and molecules are able to induce relatively selective injury of oligodendrocytes (OLs) and their myelin membranes. The selectivity of this injury could be conferred either by the properties of the effectors or the targets. The former would involve antigen specific recognition by either antibody or T cell receptor of the adaptive immune system. OLs are also susceptible to non antigen restricted injury mediated by components of the innate immune system including macrophages/microglia and NK cells. Target related selectivity could reflect the expression of death inducing surface receptors (such as Fas or TNFR-1) required for interaction with effector mediators and subsequent intracellular signaling pathways, including the caspase cascade. Development of therapeutic delivery systems, which would reach the site of disease activity within the CNS, will permit the administration of inhibitors either of the cell death pathway or of effector target interaction and opens new avenues to neuroprotection approach.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".