[11C]-(R)-PK11195 positron emission tomography in patients with complex regional pain syndrome
Bibliographic record
Abstract
Complex regional pain syndrome (CRPS) is characterized by severe and chronic pain, but the pathophysiology of this disease are not clearly understood. The primary aim of our case-control study was to explore neuroinflammation in patients with CRPS using positron emission tomography (PET), with an 18-kDa translocator protein specific radioligand [C]-(R)-PK11195. [C]-(R)-PK11195 PET scans were acquired for 11 patients with CRPS (30-55 years) and 12 control subjects (30-52 years). Parametric image of distribution volume ratio (DVR) for each participant was generated by applying a relative equilibrium-based graphical analysis. The DVR of [C]-(R)-PK11195 in the caudate nucleus (t(21) = -3.209, P = 0.004), putamen (t(21) = -2.492, P = 0.022), nucleus accumbens (t(21) = -2.218, P = 0.040), and thalamus (t(21) = -2.395, P = 0.026) were significantly higher in CRPS patients than in healthy controls. Those of globus pallidus (t(21) = -2.045, P = 0.054) tended to be higher in CRPS patients than in healthy controls. In patients with CRPS, there was a positive correlation between the DVR of [C]-(R)-PK11195 in the caudate nucleus and the pain score, the visual analog scale (r = 0.661, P = 0.026, R = 0.408) and affective subscales of McGill Pain Questionnaire (r = 0.604, P = 0.049, R = 0.364). We demonstrated that neuroinflammation of CRPS patients in basal ganglia. Our results suggest that microglial pathology can be an important pathophysiology of CRPS. Association between the level of caudate nucleus and pain severity indicated that neuroinflammation in this region might play a key role. These results may be essential for developing effective medical treatments.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 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".