Habenula activation patterns in a preclinical model of neuropathic pain accompanied by depressive-like behaviour
Bibliographic record
Abstract
Pain and depression are complex disorders that frequently co-occur, resulting in diminished quality of life. The habenula is an epithalamic structure considered to play a pivotal role in the neurocircuitry of both pain and depression. The habenula can be divided into two major areas, the lateral and medial habenula, that can be further subdivided, resulting in 6 main subregions. Here, we investigated habenula activation patterns in a rat model of neuropathic pain with accompanying depressive-like behaviour. Wistar rats received active surgery for the development of neuropathic pain (chronic constriction injury of the sciatic nerve; CCI), sham surgery (surgical control), or no surgery (behavioural control). All animals were evaluated for mechanical nociceptive threshold using the paw pressure test and depressive-like behaviour using the forced swimming test, followed by evaluation of the immunoreactivity to cFos-a marker of neuronal activity-in the habenula and subregions. The Open Field Test was used to evaluate locomotor activity. Animals with peripheral neuropathy (CCI) showed decreased mechanical nociceptive threshold and increased depressive-like behaviour compared to control groups. The CCI group presented decreased cFos immunoreactivity in the total habenula, total lateral habenula and lateral habenula subregions, compared to controls. No difference was found in cFos immunoreactivity in the total medial habenula, however when evaluating the subregions of the medial habenula, we observed distinct activation patterns, with increase cFos immunoreactivity in the superior subregion and decrease in the central subregion. Taken together, our data suggest an involvement of the habenula in neuropathic pain and accompanying depressive-like behaviour.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".