Age-Related Comparisons of Evolution of the Inflammatory Response After Intracerebral Hemorrhage in Rats
Bibliographic record
Abstract
UNLABELLED: In the hours to days after intracerebral hemorrhage (ICH), there is an inflammatory response within the brain characterized by the infiltration of peripheral neutrophils and macrophages and the activation of brain-resident microglia and astrocytes. Despite the strong correlation of aging and ICH incidence, and increasing information about cellular responses, little is known about the temporal- and age-related molecular responses of the brain after ICH. Here, we monitored a panel of 27 genes at 6 h and 1, 3, and 7 days after ICH was induced by injecting collagenase into the striatum of young adult and aged rats. Several molecules (CR3, TLR2, TLR4, IL-1β, TNFα, iNOS, IL-6) were selected to reflect the classical activation of innate immune cells (macrophages, microglia) and the potential to exacerbate inflammation and damage brain cells. Most of the others are associated with the resolution of innate inflammation, alternative pathways of macrophage/microglial activation, and the repair phase after acute injury (TGFβ, IL-1ra, IL-1r2, IL-4, IL-13, IL-4Rα, IL-13Rα1, IL-13Rα2, MRC1, ARG1, CD163, CCL22). In young animals, the up-regulation of 26 in 27 genes (not IL-4) was detected within the first week. Differences in timing or levels between young and aged animals were detected for 18 of 27 genes examined (TLR2, GFAP, IL-1β, IL-1ra, IL-1r2, iNOS, IL-6, TGFβ, MMP9, MMP12, IL-13, IL-4Rα, IL-13Rα1, IL-13Rα2, MRC1, ARG1, CD163, CCL22), with a generally less pronounced or delayed inflammatory response in the aged animals. Importantly, within this complex response to experimental ICH, the induction of pro-inflammatory, potentially harmful mediators often coincided with resolving and beneficial molecules. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12975-012-0151-3) contains supplementary material, which is available to authorized users.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".