MétaCan
Menu
Back to cohort
Record W3098967502 · doi:10.3174/ajnr.a6879

Preliminary Findings Associate Hippocampal <sup>1</sup>H-MR Spectroscopic Metabolite Concentrations with Psychotic and Manic Symptoms in Patients with Schizophrenia

2020· article· en· W3098967502 on OpenAlexfundno aff
Dolores Malaspina, Eyal Lotan, Henry Rusinek, Santiago A. Pérez, Julie Walsh‐Messinger, Thorsten M. Kranz, Oded Gonen

Bibliographic record

VenueAmerican Journal of Neuroradiology · 2020
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsnot available
FundersNational Institute on AgingSchool of Medicine, New York UniversityNational Institutes of HealthCenter for Scientific ReviewNational Institute of Mental HealthNational Institute of Biomedical Imaging and BioengineeringYork University
KeywordsMetaboliteMedicineSchizophrenia (object-oriented programming)Hippocampal formationPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: Previous hippocampal proton MR spectroscopic imaging distinguished patients with schizophrenia from controls by elevated Cr levels and significantly more variable NAA and Cho concentrations. This goal of this study was to ascertain whether this metabolic variability is associated with clinical features of the syndrome, possibly reflecting heterogeneous hippocampal pathologies and perhaps variability in its “positive” (psychotic) and “negative” (social and emotional deficits) symptoms. MATERIALS AND METHODS: In a sample of 15 patients with schizophrenia according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, we examined the association of NAA and Cho levels with research diagnostic interviews and clinical symptom ratings of the patients. Metabolite concentrations were previously obtained with 3D proton MR spectroscopic imaging at 3T, a technique that facilitates complete coverage of this small, irregularly shaped, bilateral, temporal lobe structure. RESULTS: The patient cohort comprised 8 men and 7 women (mean age, 39.1 [SD, 10.8] years, with a mean disease duration of 17.2 [SD, 10.8] years. Despite the relatively modest cohort size, we found the following: 1) Elevated Cho levels predict the positive (psychotic, r = 0.590, P = .021) and manic (r = 0.686, P = .005) symptom severity; and 2) lower NAA levels trend toward negative symptoms (r = 0.484, P = .08). No clinical symptoms were associated with Cr level or hippocampal volume (all, P ≥ .055). CONCLUSIONS: These preliminary findings suggest that NAA and Cho variations reflect different pathophysiologic processes, consistent with microgliosis/astrogliosis and/or lower vitality (reduced NAA) and demyelination (elevated Cho). In particular, the active state–related symptoms, including psychosis and mania, were associated with demyelination. Consequently, their deviations from the means of healthy controls may be a marker that may benefit precision medicine in selection and monitoring of schizophrenia treatment.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.007
GPT teacher head0.248
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of NeuroradiologySame topicAdvanced MRI Techniques and ApplicationsFrench-language works237,207