Bibliographic record
Abstract
At first glance, secretory leukocyte protease inhibitor (SLPI) would appear to have little relevance to the central nervous system (CNS). This serine protease inhibitor is most commonly found in mucosal fluids such as saliva and is best known for its anti-inflammatory and antimicrobial properties. It has been shown to promote wound healing by reducing expression of pro-inflammatory cytokines, and it can also inhibit bacterial growth and block HIV infection of macrophages. In the past 10 years, however, several studies have reported that SLPI is strongly up-regulated in response to CNS injury and that exogenous administration of SLPI is neuroprotective. It has also been shown that SLPI can overcome inhibition by CNS myelin and promote axonal regeneration. In this review, we will discuss these studies, examine the molecular mechanisms underlying SLPI's effects, and consider SLPI's potential for therapeutic use in cerebral ischemia, spinal cord injury, and multiple sclerosis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".