Duraplasty in Traumatic Thoracic Spinal Cord Injury: Impact on Spinal Cord Hemodynamics, Tissue Metabolism, Histology, and Behavioral Recovery Using a Porcine Model
Bibliographic record
Abstract
After acute traumatic spinal cord injury (SCI), the spinal cord can swell to fill the subarachnoid space and become compressed by the surrounding dura. In a porcine model of SCI, we performed a duraplasty to expand the subarachnoid space around the injured spinal cord and evaluated how this influenced acute intraparenchymal hemodynamic and metabolic responses, in addition to histological and behavioral recovery. Female Yucatan pigs underwent a T10 SCI, with or without duraplasty. Using microsensors implanted into the spinal cord parenchyma, changes in blood flow (ΔSCBF), oxygenation (ΔPO 2 ), and spinal cord pressure (ΔSCP) during and after SCI were monitored, alongside metabolic responses. Behavioral recovery was tested weekly using the Porcine Injury Behavior Scale (PTIBS). Thereafter, spinal cords were harvested for tissue sparing analyses. In both duraplasty and non-animals, the ΔSCP increased ∼5 mm Hg in the first 6 h post-injury. After this, the SCP appeared to be slightly reduced in the duraplasty animals, although the group differences were not statistically significant after controlling for injury severity in terms of impact force. During the first seven days post-SCI, the ΔSCBF or ΔPO 2 values were not different between the duraplasty and control animals. Over 12 weeks, there was no improvement in hindlimb locomotion as assessed by PTIBS scores and no reduction in tissue damage at the injury site in the duraplasty animals. In our porcine model of SCI, duraplasty did not provide any clear evidence of long-term behavioral or tissue sparing benefit after SCI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.002 |
| 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".