MétaCan
Menu
Back to cohort
Record W2148855652 · doi:10.3410/b4-14

Crosstalk between metabolic and neuropsychiatric disorders

2012· article· en· W2148855652 on OpenAlexaff
Oksana Kaidanovich‐Beilin, Roger S. McIntyre

Bibliographic record

VenueF1000 Biology Reports · 2012
Typearticle
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsUniversity of TorontoUniversity Health NetworkLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
Fundersnot available
KeywordsCrosstalkNeuroscienceInsulin resistanceInsulinDiabetes mellitusNeuromodulationMedicineDiseaseCentral nervous systemBioinformaticsPsychologyBiologyEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

Evidence supporting the concurrence of metabolic disturbances (e.g. insulin resistance, diabetes and obesity) and neuropsychiatric disorders has been demonstrated in both human and animal studies, suggesting the possibility that they have shared pathophysiological mechanisms. During the past decade, our understanding for the role of insulin in both normal and abnormal central nervous system (CNS) processes has become increasingly refined. Evidence indicates that insulin is a pleiotropic peptide, critical to neurotrophism, neuroplasticity, and neuromodulation. Moreover, the role of insulin underscores its importance in the development of several neuropsychiatric disorders, including, but not limited to, mechanisms involved in the pathogenesis and progression towards diabetes, obesity, and neurodegenerative disorders, such as Alzheimer's disease. This review focuses on the insulin-mediated effects on normal and abnormal brain function and discusses why targeting insulin-related pathways in the brain may emerge as a new approach for refining treatment of neurological and psychiatric disorders.

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 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 score0.174
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.018
GPT teacher head0.278
Teacher spread0.260 · 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 teacher head, 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

Citations62
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueF1000 Biology ReportsSame topicRegulation of Appetite and ObesityFrench-language works237,207