Kynurenic Acid in Schizophrenia: A Systematic Review and Meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
Kynurenic acid (KYNA) is an endogenous antagonist of N-methyl-D-aspartate and α7 nicotinic acetylcholine receptors that is derived from astrocytes as part of the kynurenine pathway of tryptophan degradation. Evidence suggests that abnormal KYNA levels are involved in the pathophysiology of schizophrenia. However, this has never been assessed through a meta-analysis. A literature search was conducted through Ovid using Embase, Medline, and PsycINFO databases (last search: December 2016) with the search terms: (kynuren* or KYNA) and (schizophreni* or psychosis). English language studies measuring KYNA levels using any method in patients with schizophrenia and healthy controls (HCs) were identified. Standardized mean differences (SMDs) were calculated to determine differences in KYNA levels between groups. Subgroup analyses were separately performed for nonoverlapping participant samples, KYNA measurement techniques, and KYNA sample source. The influences of patients' age, antipsychotic status (%medicated), and sex (%male) on study SMDs were assessed through a meta-regression. Thirteen studies were deemed eligible for inclusion in the meta-analysis. In the main analysis, KYNA levels were elevated in the patient group. Subgroup analyses demonstrated that KYNA levels were increased in nonoverlapping participant samples, and centrally (cerebrospinal fluid and brain tissue) but not peripherally. Patients' age, %medicated, and %male were each positively associated with study SMDs. Overall, KYNA levels are increased in patients with schizophrenia, specifically within the central nervous system. An improved understanding of KYNA in patients with schizophrenia may contribute to the development of novel diagnostic approaches and therapeutic strategies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.005 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 it