Behavioral, Biochemical and Electrophysiological Changes in Spared Nerve Injury Model of Neuropathic Pain
Bibliographic record
Abstract
Neuropathic pain is a pathological condition induced by a lesion or disease affecting the somatosensory system, with symptoms like allodynia and hyperalgesia. It has a multifaceted pathogenesis as it implicates several molecular signaling pathways involving peripheral and central nervous systems. Affective and cognitive dysfunctions have been reported as comorbidities of neuropathic pain states, supporting the notion that pain and mood disorders share some common pathogenetic mechanisms. The understanding of these pathophysiological mechanisms requires the development of animal models mimicking, as far as possible, clinical neuropathic pain symptoms. Among them, the Spared Nerve Injury (SNI) model has been largely characterized in terms of behavioral and functional alterations. This model is associated with changes in neuronal firing activity at spinal and supraspinal levels, and induces late neuropsychiatric disorders (such as anxious-like and depressive-like behaviors, and cognitive impairments) comparable to an advanced phase of neuropathy. The goal of this review is to summarize current findings in preclinical research, employing the SNI model as a tool for identifying pathophysiological mechanisms of neuropathic pain and testing pharmacological agent.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".