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Record W4310092550 · doi:10.1371/journal.pone.0277211

Investigating the effects of antipsychotics on brain insulin action: Study protocol for a multi-modality magnetic resonance imaging (MRI) study in healthy controls

2022· article· en· W4310092550 on OpenAlexafffund
Nicolette Stogios, Laurie Hamel, Emily R. Smith, Marcos Sanches, Gary Remington, Aristotle N. Voineskos, Satya Dash, Ariel Graff‐Guerrero, Margaret Hahn, Sri Mahavir Agarwal

Bibliographic record

VenuePLoS ONE · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsToronto General HospitalUniversity Health NetworkDiabetes CanadaUniversity of TorontoCentre for Addiction and Mental Health
FundersNational Institute of Mental HealthCentre for Addiction and Mental Health FoundationCanadian Institutes of Health ResearchNovo NordiskDanish Diabetes AcademyUniversity of TorontoCanada Foundation for InnovationPhysicians' Services Incorporated FoundationDepartment of Psychiatry, University of TorontoBanting and Best Diabetes Centre, University of TorontoNeurocrine BiosciencesHLS Therapeutics
KeywordsInsulin resistanceFunctional magnetic resonance imagingMedicineInsulinDorsolateral prefrontal cortexNeuroimagingPrefrontal cortexNeuroscienceMagnetic resonance imagingInsulin receptorGlutamate receptorInternal medicineEndocrinologyPsychologyCognitionReceptor

Abstract

fetched live from OpenAlex

Antipsychotics (APs) are the cornerstone of treatment for schizophrenia (SCZ) but are unfortunately associated with serious metabolic adverse effects including weight gain and type 2 diabetes. The pathophysiology of AP-induced metabolic dysfunction is largely undetermined. Brain insulin resistance has been posited to be at the cross-roads of many cognitive and metabolic disorders, and disruption of central insulin action has emerged as a possible explanatory mechanism underlying AP induced metabolic dysfunction. Previous studies suggest that change in neuroimaging-based parameters with intranasal insulin administration can be leveraged to investigate brain insulin resistance. In this proof-of-concept study, we will utilize neural signatures of insulin action in the brain to examine if APs disrupt brain insulin signaling. It is hypothesized that: 1) intranasal insulin (INI), but not intranasal placebo (INP), will change cerebral blood flow and resting state connectivity, as well as increase glutamate levels in the striatum and dorsolateral prefrontal cortex; 2) oral olanzapine (OLA), but not oral placebo (PL), will inhibit the effect of INI on these parameters. Thirty-two healthy volunteers will undergo a single blind, cross-over design, wherein all participants receive the following four treatment combinations, 2-6 weeks apart, in a random sequence: INP + PL, INP + OLA, INI + PL, and INI + OLA. Participants will undergo an MRI-based assay of brain insulin resistance 15 minutes after administering 160 IU INI or INP. The scanning protocol includes resting and task-based functional MRI, arterial spin labelling, and proton magnetic resonance spectroscopy. Demonstrating that OLA can acutely induce brain insulin resistance is clinically relevant to metabolic health in SCZ. Evidence of brain insulin resistance induced by acute AP dosing can inform the early use of adjunctive insulin sensitizers for the treatment of metabolic comorbidities associated with AP treatment in severe mental illness. Trial registration ClinicalTrials.gov Registration: NCT03741478.

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)0.006
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.023
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0230.007

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 head0.219
GPT teacher head0.444
Teacher spread0.226 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations3
Published2022
Admission routes2
Has abstractyes

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