Traumatic Injury Reduces Amyloid Plaque Burden in the Transgenic 5xFAD Alzheimer’s Mouse Spinal Cord
Bibliographic record
Abstract
BACKGROUND: Axonal injury has been implicated in the development of amyloid-β in experimental brain injuries and clinical cases. The anatomy of the spinal cord provides a tractable model for examining the effects of trauma on amyloid deposition. OBJECTIVE: Our goal was to examine the effects of axonal injury on plaque formation and clearance using wild type and 5xFAD transgenic Alzheimer's disease mice. METHODS: We contused the spinal cord at the T12 spinal level at 10 weeks, an age at which no amyloid plaques spontaneously accumulate in 5xFAD mice. We then explored plaque clearance by impacting spinal cords in 27-week-old 5xFAD mice where amyloid deposition is already well established. We also examined the cellular expression of one of the most prominent amyloid-β degradation enzymes, neprilysin, at the lesion site. RESULTS: No plaques were found in wild type animals at any time points examined. Injury in 5xFAD prevented plaque deposition rostral and caudal to the lesion when the cords were examined at 2 and 4 months after the impact, whereas age-matched naïve 5xFAD mice showed extensive amyloid plaque deposition. A massive reduction in the number of plaques around the lesion was found as early as 7 days after the impact, preceded by neprilysin upregulation in astrocytes at 3 days after injury. At 7 days after injury, the majority of amyloid was found inside microglia/macrophages. CONCLUSION: These observations suggest that the efficient amyloid clearance after injury in the cord may be driven by the orchestrated efforts of astroglial and immune cells.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".