Blood-nerve barrier dysfunction contributes to the generation of neuropathic pain and allows targeting of injured nerves for pain relief
Bibliographic record
Abstract
The blood-nerve barrier (BNB) is a selectively permeable barrier that creates an immunologically and biochemically privileged space for peripheral axons and supporting cells. The breakdown of the BNB allows access of blood-borne (hematogenous) cells and molecules to the endoneurium to engage in the local inflammatory cascade. This process was examined in a mouse model of trauma-associated neuropathic pain. The impact of nerve injury-triggered opening of the BNB in the development of chronic pain behavior was investigated. Partial ligation of the sciatic nerve led to a long-lasting disruption of the BNB distal to the site of injury. Vascular endothelial growth factor (VEGF) was expressed by resident macrophages after nerve injury. Intraneural injection of VEGF decreased mechanical thresholds while opening the BNB. Serum from nerve-injured or lipopolysaccharide-treated animals elicited mechanical allodynia in naive animals, when allowed to bypass the BNB by intraneural injection. Intraneural injection of fibrinogen, a clotting protein in plasma that was found to deposit in the nerve after nerve injury, also produced a decrease in mechanical thresholds when introduced into naive nerves. These results demonstrate that blood-borne molecules may play a role in the generation of neuropathic pain, suggesting that pain may be driven from infection or injury, at a distance from the nervous system. Furthermore, the breakdown of the BNB in neuropathic conditions was exploited to permit the entry of analgesic molecules that typically cannot pass the BNB, such as ProToxin-II, a BNB-impermeable Nav1.7 inhibitor. Therapeutics utilizing this mechanism could have selective access to injured nerves over healthy tissues.
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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 | 0.030 | 0.017 |
| 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; both teacher heads agree on what is shown here.
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".