Early Changes in Deep Vein Diameter and Biochemical Markers Associated with Thrombi Formation after Spinal Cord Injury in Mice
Bibliographic record
Abstract
Spinal cord injury (SCI) is associated with the development of deep venous thrombosis (DVT) in the lower limbs and, hence, with rapidly increasing risks of cardiovascular and pulmonary complications soon after trauma. However, specific mechanisms underlying DVT formation following SCI are poorly understood. Here, we studied in mice, employing in vivo confocal microscopy, changes in deep vein size over 4 weeks after spinal cord transection (Tx). Changing levels of biochemical markers that may be associated with DVT formation were also examined. The results showed decreased concentrations of cholesterols, triglycerides, and low-density lipoprotein (LDL), but not of high-density lipoproteins (HDL) and platelets. Concentrations of creatinine, bilirubin, glucose, albumin, total protein and uric acid did not significantly change. In turn, the femoral and saphenous veins underwent a large increase (>1.5-fold) in diameter throughout the entire period studied. Overall, this study reveals that a profound change in deep vein size and, an unsuspected decrease in triglyceride and LDL levels, occur as early as at one week post-Tx in mice. This indicates, given the well-documented risk of DVT formation soon after SCI, that deep vein enlargement, but not lipoprotein level changes, may constitute an early event contributing to venous stasis and thrombi formation in paralyzed individuals.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".