Spinal neurovascular coupling is preserved despite time-dependent alterations of spinal cord blood flow responses in a rat model of chronic back pain: implications for functional spinal cord imaging
Bibliographic record
Abstract
ABSTRACT: Functional magnetic resonance imaging has been used to investigate nociceptive processes in patients with chronic pain. However, the results may be confounded with changes in neurovascular coupling induced by chronic pain. The objective of this study was to examine spinal neurovascular coupling in a rat model of chronic back pain induced by muscle inflammation. Rats received 150 µL intramuscular injections of either complete Freund adjuvant (CFA: n = 18) or saline (control [CTL]: n = 18) in L5-L6 paravertebral muscles. Under 1.2% isoflurane anesthesia, spinal cord blood flow (SCBF) and local field potentials evoked by electrical stimulation of the sciatic nerve were recorded simultaneously in the lumbar enlargement of the spinal cord, 14 or 28 days after the injections. Mechanical hypersensitivity was observed in CFA rats compared with CTL rats for the back ( P < 0.001) and hind paws ( P < 0.01). Spinal cord blood flow response amplitude and local field potential amplitude were not significantly different between groups (day 14: P > 0.5; day 28: P > 0.6). However, the time course of SCBF responses was different between groups on day 14 ( P < 0.001) and day 28 ( P < 0.001). Nevertheless, neurovascular coupling was comparable between groups on days 14 and 28, whether neurovascular coupling was calculated with the amplitude or the area under the curve of SCBF responses (all P > 0.2). These results indicate that spinal hemodynamic changes reflect neuronal activity in this animal model, although the time course of SCBF responses is affected by chronic inflammatory back pain. This warrants a careful use of spinal functional magnetic resonance imaging in animal models and patients with chronic back pain.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".