Cardiometabolic Risk Factors in Experimental Spinal Cord Injury
Bibliographic record
Abstract
Cardiometabolic risk factors are sorely underreported after spinal cord injury (SCI), despite the high prevalence of metabolic disorders and cardiovascular mortality in this population. Body-composition analysis and serum-lipid profiling are two assessments that are beginning to be more widely used to document metabolic changes after clinical SCI. Individuals with SCI have been reported to carry increased visceral fat and to exhibit altered serum-lipid levels. However, little is known about the development of these cardiometabolic risk factors in animal models. Using a combination of magnetic resonance imaging (MRI) and adipose tissue dissection, we show that visceral and subcutaneous adipose tissue were both increased at 1 month, but not at 1 week, after complete T3 SCI in rats. Additionally, at 1 month post injury, T3 SCI rats exhibited nonfasting serum hypertriglyceridemia, a result obtained using both standard clinical methods and a home cholesterol monitoring device (CardioChek). Interestingly, at 1 month post injury, rats with complete T10 SCI did not show an increase in either visceral adiposity or serum triglyceride levels. The fact that complete high-thoracic SCI disrupts lipid metabolism and perturbs fat storage in the subacute period, while low-thoracic SCI does not, suggests that differences in descending sympathetic control of adipose tissue might play a role in these changes. These results provide the first evidence of cardiometabolic risk factors in experimental animals with SCI, and are a starting point for investigations of the etiology of obesity and metabolic dysfunctions that often accompany SCI.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".