Axotomy-induced up-regulation of tumor necrosis factor-alpha in the dorsal root ganglia
Bibliographic record
Abstract
OBJECTIVES: Neuropathic pain is a chronic pain syndrome associated with drug, injury or disease-induced damage or destruction of sensory afferent fibers of the dorsal root ganglia (DRG). Although the exact underlying pathologic mechanisms are not known, pro-inflammatory cytokines such as tumor necrosis factor-alpha (TNF-alpha) are recognized as potential modulators of peripheral and central nervous system inflammatory responses. They play a crucial role in injury and the pathologic development of chronic pain syndromes such as neuropathic pain. METHODS: Twenty-four rats were divided into a naive control (n=6), sham (surgery exposing sciatic nerve, n=6), and peripheral nerve lesion group (unilateral axotomy of sciatic nerve, n=12). RESULTS: The results of this study demonstrate a transient up-regulation of TNF-alpha expression within ipsi- and contralateral DRG following complete unilateral sciatic nerve axotomy as confirmed by immunohistochemistry, reverse transcriptase-polymerase chain reaction (RT-PCR) and real-time PCR. Elevated expression of TNF-alpha was noted to occur within the first 7 days post-axotomy, which subsequently normalized to baseline levels by day 14. This transient up-regulation was also associated with a switch in cellular source from predominant satellite cell expression at baseline to that involving satellite cells and abundant numbers of sensory neurons. DISCUSSION: These results support the role of TNF-alpha in the upstream cascade of cellular events involved in the underlying pathogenesis of neuropathic pain. Strategies targeting the early attenuation of TNF-alpha within the DRG during the first week post-injury may have significant clinical impact in preventing the downstream cascade of events involved in the underlying cellular pathology of neuropathic 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".