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Record W4283725016 · doi:10.1016/j.nsa.2022.100108

Metabolomics analysis of cerebrospinal fluid suggests citric acid cycle aberrations in bipolar disorder

2022· article· en· W4283725016 on OpenAlex
Erik Smedler, Alireza M. Salehi, Aurimantas Pelanis, Ana C. Andreazza, Erik Pålsson, Timea Sparding, Mikael Landén

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNeuroscience Applied · 2022
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCerebrospinal fluidCitric acidBipolar disorderCitric acid cycleLithium (medication)Internal medicineMetabolomicsEndocrinologyProton magnetic resonanceMedicineChemistryBiochemistryNuclear magnetic resonanceMetabolismChromatography

Abstract

fetched live from OpenAlex

Mounting evidence indicates mitochondrial dysfunction in bipolar disorder pathophysiology. Here, we employed Proton Nuclear Magnetic Resonance Spectroscopy (1H NMR) of cerebrospinal fluid (CSF) samples from well-characterized bipolar disorder patients (n = 67) and healthy controls (n = 55) in order to measure absolute concentrations of multiple metabolites. Focusing on four citric acid cycle metabolites — citrate, glucose, lactate, and pyruvate — we found higher concentrations of both citrate and glucose in patients compared with controls after correcting for age, sex and body mass index, but only the difference in CSF citrate survived correction for multiple comparisons. Within the patient group, CSF citrate concentrations were higher among lithium users than non-users. In conclusion, this report adds further evidence for a mitochondrial dysfunction in bipolar disorder.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.402
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.264
Teacher spread0.250 · 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