Thrombin Causes Neuronal Atrophy and Acute but not Chronic Cell Death
Bibliographic record
Abstract
BACKGROUND: Brain injury after intracerebral hemorrhage (ICH) arises from numerous contributors, of which some also play essential roles. Notably, thrombin production, needed to stop bleeding, also causes acute cell death and edema. In some rodent models of ICH, peri-hematoma neurons die over weeks. Hence we evaluated whether thrombin is responsible for this chronic degeneration. Functional impairments after ICH also result from sub-lethal damage to neurons, especially the loss of dendrites. Thus, we evaluated whether thrombin infusion alone, a reductionist model of ICH, causes similar injury. METHODS: Adult rats had a modest intra-striatal infusion of thrombin (1 U) or saline followed by a behavioral test, to verify impairment, 7 days later. After this they were euthanized and tissue stained with Golgi-Cox solution to allow the assessment of dendritic morphology in striatal neurons. In a second experiment, rats survived 7 or 60 days after thrombin infusion in order to histologically determine lesion volume. RESULTS: Thrombin caused early cell death and considerable atrophy in surviving peri-lesion neurons, which had less than half of their usual numbers of branches. However, total tissue loss was comparable at 7 (24.1 mm3) and 60 days (25.6 mm3). CONCLUSION: Thrombin infusion causes early cell death and neuronal atrophy in nearby surviving striatal neurons but thrombin does not cause chronic tissue loss. Thus, the chronic degeneration found after ICH in rats is not simply and solely due to acute thrombin production. Nonetheless, thrombin is an important contributor to behavioral dysfunction because it causes cell death and substantial dendritic injury.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".