Hormonal And Immunological Changes in Mice after Spinal Cord Injury
Bibliographic record
Abstract
Spinal cord injury (SCI) is associated with immune deficiencies and life-threatening infections. However, the specific mechanisms underlying this pathological condition remain unclear. In recent years, increasing evidence has suggested that anabolic hormones may be involved in immunological complications. Here, we monitored candidate hormone concentrations and immune cell counts, in CD1 mice, for 4 weeks after low-thoracic transection of the spinal cord (Tx). Serum dihydroepiandrosterone (DHEA), insulin, and parathyroid hormone (PTH) levels decreased throughout the time period studied compared with control, non-Tx mice. In turn, testosterone and growth hormone (GH) levels were only transiently changed, with a decrease of testosterone during the first 2 weeks and an increase of GH at 1 week post-Tx. A complete blood count revealed either unchanged or moderately decreased erythrocyte, platelet, hemoglobin and hematocrit levels. Total leukocyte, lymphocyte, and eosinophil counts also decreased, whereas neutrophils and monocytes did not change significantly. In the bone marrow, lymphocyte numbers decreased and neutrophils increased, whereas monocytes, eosinophils, and megakariocytes did not change significantly. These results revealed significant changes occurring rapidly (<1-2 weeks) after Tx in both hormonal and immunological systems, providing compelling evidence of a role for anabolic hormones in SCI-related immune deficiencies.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".