Localization of S100A8 and S100A9 expressing neutrophils to spinal cord during peripheral tissue inflammation
Bibliographic record
Abstract
Investigation of hyperalgesia at the spinal transcriptome level indicated that carrageenan-induced inflammation of rat hind paws leads to a rapid but sustained increase in S100A8 and S100A9 expression, two genes implicated in the pathology of numerous inflammatory diseases including rheumatoid arthritis and gout. In situ hybridization revealed that the elevation occurred in neutrophils that migrate to the spinal cord vasculature during peripheral inflammation, not in spinal neurons or glial cells. Immunohistochemical analysis suggests, but does not prove, that these neutrophils abundantly release S100A8 and S100A9. Consistent with this, we detected an increase in ICAM and VCAM, both indicators of endothelial activation, a known trigger for secretion of S100A8 and S100A9. Migration of S100A8- and S100A9-expressing neutrophils to spinal cord is selective, since MCP-1- and CD68-expressing leukocytes do not increase in spinal cord vasculature during hind paw inflammation. Examination of many neutrophil granule mediators in spinal cord indicated that they are not regulated to the same degree as S100A8 and S100A9. Neutrophil migration also occurs in the vasculature of brain and pituitary gland during peripheral inflammation. Together, these findings suggest an interaction between a subpopulation of leukocytes and the CNS during peripheral tissue inflammation, as implied by an apparent release and possible diffusion of S100A8 and S100A9 through the endothelial blood-brain barrier. Although the present findings do not establish the neurophysiological or behavioral relevance of these observations to nociceptive processing, the data raise the possibility that selective populations of leukocytes may communicate the presence of disease or tissue damage from the periphery to cells in the central nervous system.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".