Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Intracerebral hemorrhage is associated with stroke and head trauma. The purposes of this study were to investigate the effect of intracortical injections of autologous whole blood and blood components on inflammatory cell infiltration and brain cell death and to determine if nonhemorrhagic lesions differ in these respects. METHODS: Eighty-seven adult rats were subjected to intracortical injections of autologous whole blood or allogeneic plasma, erythrocytes, leukocytes, "activated" leukocytes, and serum. Injections of saline or mineral oil were controls. Blood injections were compared with cortical freeze injury and pial devascularization. Rats were perfusion-fixed 48 hours after injection or lesioning. Eosinophilic neurons, TUNEL-positive cells, brain damage area, infiltrating neutrophils, and CD8a-immunoreactive lymphocytes were quantified. RESULTS: Damage area, dying cells, and inflammatory infiltrate were significantly greater after autologous whole blood, leukocyte, and "activated" leukocyte injections than injection of other fractions. CONCLUSIONS: These results suggest that extravasated whole blood causes a greater degree of cortical cell death and inflammation than ischemic lesions of similar size. Leukocytes "activated" by systemic illness might exacerbate the injury. Secondary hemorrhagic phenomena suggest that the harmful effect is directed toward both brain cells and the vasculature. Further studies are required to delineate the mechanism(s).
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".