Quantifying Blood-Spinal Cord Barrier Permeability after Peripheral Nerve Injury in the Living Mouse
Bibliographic record
Abstract
BACKGROUND: Genetic polymorphisms, gender and age all influence the risk of developing chronic neuropathic pain following peripheral nerve injury (PNI). It is known that there are significant inter-strain differences in pain hypersensitivity in strains of mice after PNI. In response to PNI, one of the earliest events is thought to be the disruption of the blood-spinal cord barrier (BSCB). The study of BSCB integrity after PNI may lead to a better understanding of the mechanisms that contribute to chronic pain. RESULTS: Here we used in vivo dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to establish a timecourse for BSCB permeability following PNI, produced by performing a spared nerve injury (SNI). From this longitudinal study, we found that the SNI group had a significant increase in BSCB permeability over time throughout the entire spinal cord. The BSCB opening had a delayed onset and the increase in permeability was transient, returning to control levels just over one day after the surgery. We also examined inter-strain differences in BSCB permeability using five mouse strains (B10, C57BL/6J, CD-1, A/J and BALB/c) that spanned the range of pain hypersensitivity. We found a significant increase in BSCB permeability in the SNI group that was dependent on strain but that did not correlate with the reported strain differences in PNI-induced tactile hypersensitivity. These results were consistent with a previous experiment using Evans Blue dye to independently assess the status of the BSCB permeability. CONCLUSIONS: DCE-MRI provides a sensitive and non-invasive method to follow BSCB permeability in the same group of mice over time. Examining differences between mouse strains, we demonstrated that there is an important genetically-based control of the PNI-induced increase in BSCB permeability and that the critical genetic determinants of BSCB opening after PNI are distinct from those that determine genetic variability in PNI-induced pain hypersensitivity.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".