Bibliographic record
Abstract
The Innate Immune Response (IIR) is an evolutionarily derived process to protect cells and tissues from a broad spectrum of insults. Unfortunately abrogating the insult comes at a cost with compromise of cell or tissue integrity. For the CNS to function it needs to rigorously control its microenvironment and thus is highly susceptible to negative sequelae of the IIR. In the course of studying neuroinflammation in a wide variety of human CNS diseases, we discovered an intriguing molecule, CHI3L1, that appears to be crucial in mitigating untoward CNS effects of IIR. During neuroinflammation the distribution of CHI3L1 is completely unlike that in other tissues. In systemic tissues CHI3L1 is expressed highly in macrophages during the IIR, however in the CNS macrophage expression appears to be severely down-regulated and instead astrocytes express high levels. Experimental studies in animal models of CNS disease have suggested that CHI3L1 is part of a unique anti-inflammatory pathway in the CNS. The mechanism of CHI3L1 down-regulation in CNS macrophages and the role of astrocytic up-regulation remains to be elucidated, however this novel pathway offers a new target to regulate CNS inflammation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".