In schizophrenia, psychomotor retardation is associated with executive and memory impairments, negative and psychotic symptoms, neurotoxic immune products and lower natural IgM to malondialdehyde
Bibliographic record
Abstract
Objectives: Stable-phase schizophrenia comprises two distinct entities namely Major Neuro-Cognitive Psychosis (MNP) and simple NP (SNP), which are defined by neuroimmune and neurocognitive abnormalities.Methods: This study investigates associations of psychomotor retardation (PMR), clinical and biomarker characteristics of schizophrenia. We recruited 40 healthy controls and 79 schizophrenia patients and measured IgA responses to tryptophan catabolites (TRYCATs), IgM to malondialdehyde and nitroso (NO)-cysteinyl, CCL-11, an immune activation index based on cytokine levels, and motor screening task (MOT) scores.Results: PMR differentiated schizophrenia from controls and MNP from SNP. In addition, PMR was strongly associated with impairments in executive functions and episodic and semantic memory, psychotic, hostility, excitation, mannerism and negative (PHEMN) symptoms. Around 50% of the variance in PMR was predicted by the cumulative effects of the immune activation index, CCL-11, TRYCATs, NO-Cysteinyl and natural IgM. PRM can reliably be combined with PHEMN symptoms, memory and executive impairments into one latent vector reflecting overall severity of schizophrenia.Conclusions: PMR is a key psychopathological feature of schizophrenia mainly MNP. In addition, PMR may be driven by deficits in the compensatory immune-regulatory system and increased production of neurotoxic immune products, namely TRYCATs, IgM to NO-cysteinyl, and CCL-11, an endogenous cognition deteriorating chemokine.
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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) | 0.001 | 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 | 0.000 |
| 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".