Abstract TP119: Tibia Fracture Leads to Long-Lasting Memory Dysfunction in Mice Through Enhanced Blood-Brain Barrie Breakdown in the Hippocampus and White Matter Damage
Bibliographic record
Abstract
Background and Purpose: Tibia fracture (BF) causes long-lasting memory dysfunction in stroke mice, which is associated with microglia accumulation in the hippocampus ipsilateral to the stroke injury. The underlying mechanism is unclear. Hypothesis: BF exacerbates blood brain barrier (BBB) breakdown and fibrin extravasation in the hippocampus enhancing white matter damage of stroke mice. Method: C57 mice (8-weeks) were randomly assigned to BF, stroke (pMCAO), BF+stroke (BF 6h before stroke) and sham groups. The integrity of BBB, fibrin deposition and CD68 + cells infiltration in the hippocampus were analyzed 3 days and the white matter injury in the basal ganglia was analyzed 8 weeks after the surgeries. Results: Compared to BF group, stroke and BF+stroke groups had lower level of claudin-5, fewer pericytes, more extravascular fibrin and CD68 + cells in the ipsilateral side of stroke 3 days after the injuries. BF+stroke group had the lowest level of claudin-5, fewest pericytes, highest extravascular fibrin and most CD68 + cells among the three groups. BF+stroke group also had a lower level of claudin-5 and fewer CD13 + pericytes in the contralateral side than the other two groups. Compared to sham group, the white matter bundle areas in the basal ganglia were reduced in stroke and BF+stroke groups in both contralateral and ipsilateral sides 8 weeks after the injuries. Stroke and BF+stroke groups also has smaller white matter bundle areas in the ipsilateral than contralateral side, and the white matter bundle areas in the contralateral side of BF+stroke group were also smaller than stroke group. Conclusion: BF shortly before stroke causes long-lasting memory dysfunction in mice through enhancing BBB breakdown and fibrin extravasation in the hippocampus, which exacerbates neuroinflammation and white matter damage.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".