Inflammatory injury induces pain sensitization that is expressed beyond the site of injury in male (and not in female) mice
Bibliographic record
Abstract
Pain is a crucial protective mechanism for the body. It alerts us to potential tissue damage or injury and promotes the avoidance of harmful stimuli. Injury-induced inflammation and tissue damage lead to pain sensitization, which amplifies responses to subsequent noxious stimuli even after an initial primary injury has recovered. This phenomenon, commonly referred to as hyperalgesic priming, was investigated in male and female mice to determine whether it is specific to the site of previous injury. We used 10μl of 50 % Freund's complete adjuvant (CFA) administered to the left hind paw as a model of peripheral injury. Both male and female mice exhibited robust site-specific mechanical hypersensitivity after CFA, which resolved within one-week post-injection. After injury resolution, only male CFA-primed mice showed enhanced and prolonged mechanical sensitivity in response to a chemical challenge or a single 0.5 mA electric footshock. Among CFA-primed male mice, shock-induced mechanical hypersensitivity was expressed in both the left (previously injured) and the right (uninjured) hind paws, suggesting a pivotal role for altered centralized processes in the expression of pain sensitization. These findings indicate that pain history regulates sensory responses to subsequent mechanical and chemical pain stimuli in a sex-specific manner-foot-shock-induced hyperalgesic priming expression among male mice generalized beyond the initial injury site.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".