Editorial: Neuro-immune players of peripheral pain signalling
Bibliographic record
Abstract
Neuro-immune players of peripheral pain signalingNociceptors comprise a subpopulation of specialised sensory neurons capable of sensing and responding to (potentially) harmful stimuli.This process, termed nociception and often translated into a painful sensation, is essential for the survival and wellbeing of living animals, including humans.However, when pain becomes chronic, it is debilitating and significantly impairs the quality of life.Notably, expression of receptors that recognise immune-derived mediators (1, 2) allow nociceptors to identify cues from the immune system.Indeed, activation of nociceptive nerve fibres by inflammatory molecules leads to the generation of action potentials which are received by the central nervous system and may provoke painful sensation (3).Importantly, immune system perturbations, for instance in response to exogenous agents (4) or after nerve injury (5), can cause aberrant nociceptive signalling and drive the development of chronic pain.All these aspects were within the scope of this Research Topic entitled "Neuro-Immune Players of Peripheral Pain Signalling".There were two review articles, three original research articles and one hypothesis and theory article published.Starting with the latter, Dong and Ubogu provided preliminary data on the potential role of CD11b + CD45 + leukocyte infiltration in the sciatic nerve in the context of neuropathic pain.To this end, the authors utilised three mouse models of inflammatory and traumatic peripheral neuropathies (modelling Guillain-Barré syndrome, spontaneous autoimmune peripheral polyneuropathy and sciatic nerve crush), and showed that an increase in CD11b + CD45 + leukocyte counts in endoneurial sciatic nerves was associated with an impairment in the severity of motor progression.Interestingly, treatment with monoclonal anti-CD11b antibody reduced cold-and heat-induced nociception in their model of traumatic peripheral neuropathy.While it will be important to test the effectiveness of this treatment in other models, these data suggest that targeting CD11b could be developed into a treatment option for patients suffering from neuropathic pain.Further research addressing this possibility is hence warranted.The two reviews used different approaches.Koop et al. opted for a systematic review with meta-analysis of animal studies to assess the effects of pre-injury exercise on neuroimmune and other physiological and behavioural responses following Frontiers in Immunology frontiersin.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.018 | 0.012 |
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".