Cognitive impairment and pain in depression: The mediating role of the kynurenine pathway
Bibliographic record
Abstract
BACKGROUND: The tryptophan-kynurenine (TRP-KYN) pathway may be implicated in the pathophysiology of cognitive impairment and pain severity in major depressive disorder (MDD); however, few studies have explored the intricacies of their interaction. AIM: To investigate the relationship between the TRP-KYN pathway and cognitive function in MDD patients with and without painful physical symptoms (PPS). METHODS: Seventy patients with MDD were recruited, including 33 and 37 with and without PSS, respectively. The Hamilton Depression Scale, the Hamilton Anxiety Scale, and the Short-form of McGill pain questionnaire (SFMPQ) were used to assess clinical symptoms. Cognitive function was assessed by the MATRICS Consensus Cognitive Battery (MCCB) score. TRP-KYN pathway metabolites' serum levels were measured using high-performance liquid chromatography-tandem mass spectrometry. RESULTS: The with PPS group exhibited significantly higher TRP-KYN ratios than did the without PPS group; in the former, the SFMPQ scores positively and negatively correlated with the TRP-KYN ratio and total MCCB score, respectively. Regression analysis indicated that body mass index and SFMPQ scores were significantly associated with the TRP-KYN ratio, predicting 30% of the variance. CONCLUSION: The TRP-KYN ratio is a potential biomarker for identifying patients with depression accompanied by pain symptoms, and targeting it may represent a novel therapeutic strategy for managing pain in these individuals. Further elucidation of the biological mechanisms underlying cognitive impairment in MDD patients with PPS is warranted.
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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 | 0.001 |
| 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".