Interactive interdisciplinary pain research in adolescent and young adult females: a pilot investigation of brain, physiological, and emotional functioning following orthopedic surgery
Bibliographic record
Abstract
OBJECTIVE: In this pilot investigation, we aimed to explore the neurological and biobehavioral mechanisms underlying pain outcomes in adolescent and young adult (AYA) females following orthopedic surgery, an area largely unexplored. METHODS: Functional near-infrared spectroscopy was used to investigate brain responses in the primary sensory cortex (sensory pain processing) and the prefrontal regions (emotional processing) in 24 AYA females who underwent orthopedic surgery within the previous 2 years compared to 20 group-matched controls without a surgical or chronic pain history. A battery of self-reported pain-related and emotional functioning measures (PROMIS; pain catastrophizing) were also administered. Cortical activations and functional connectivity (FC), involving the prefrontal (PFC) and somatosensory cortices (SMC), were assessed during resting state and a descending pain modulation task (conditioned pain modulation). RESULTS: In the control group, PFC-SMC FC in response to pain was significantly linked to anxiety, whereas this correlation was absent in the post-surgical cohort. CONCLUSION: These results highlight distinct altered responses in sensory and emotional brain functioning in AYA females following orthopedic surgery. We suggest that such changes may be related to the involvement of the PFC-SMC communication in the maintenance of chronic pain.
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) | 0.000 | 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".