Bazedoxifene, a Selective Estrogen Receptor Modulator, Promotes Functional Recovery in a Spinal Cord Injury Rat Model
Bibliographic record
Abstract
In research on various central nervous system injuries, bazedoxifene acetate (BZA) has shown two main effects: neuroprotection by suppressing the inflammatory response and remyelination by enhancing oligodendrocyte precursor cell differentiation and oligodendrocyte proliferation. We examined the effects of BZA in a rat spinal cord injury (SCI) model. Anti-inflammatory and anti-apoptotic effects were investigated in RAW 264.7 cells, and blood-spinal cord barrier (BSCB) permeability and angiogenesis were evaluated in a human brain endothelial cell line (hCMEC/D3). In vivo experiments were carried out on female Sprague Dawley rats subjected to moderate static compression SCI. The rats were intraperitoneally injected with either vehicle or BZA (1mg/kg pre-SCI and 3 mg/kg for 7 days post-SCI) daily. BZA decreased the lipopolysaccharide-induced production of proinflammatory cytokines and nitric oxide in RAW 264.7 cells and preserved BSCB disruption in hCMEC/D3 cells. In the rats, BZA reduced caspase-3 activity at 1 day post-injury (dpi) and suppressed phosphorylation of MAPK (p38 and ERK) at dpi 2, hence reducing the expression of IL-6, a proinflammatory cytokine. BZA also led to remyelination at dpi 20. BZA contributed to improvements in locomotor recovery after compressive SCI. This evidence suggests that BZA may have therapeutic potential to promote neuroprotection, remyelination, and functional outcomes following SCI.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".