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Record W2981580852 · doi:10.1016/j.nicl.2019.102049

Blood-brain barrier imaging as a potential biomarker for bipolar disorder progression

2019· article· en· W2981580852 on OpenAlex

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNeuroImage Clinical · 2019
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsHealth Sciences CentreNova Scotia Health AuthorityDalhousie University
FundersMitacsFondation Brain CanadaEuropean CommissionNova Scotia Health Research FoundationNational Alliance for Research on Schizophrenia and DepressionBrain and Behavior Research Foundation
KeywordsBipolar disorderCohortManiaMedicineDepression (economics)MoodInternal medicineMood disordersAnxietyBiomarkerPopulationOncologyPsychiatryPsychology

Abstract

fetched live from OpenAlex

Bipolar disorder affects approximately 2% of the population and is typically characterized by recurrent episodes of mania and depression. While some patients achieve remission using mood-stabilizing treatments, a significant proportion of patients show progressive changes in symptomatology over time. Bipolar progression is diverse in nature and may include a treatment-resistant increase in the frequency and severity of episodes, worse psychiatric and functional outcomes, and a greater risk of suicide. The mechanisms underlying bipolar disorder progression remain poorly understood and there are currently no biomarkers for identifying patients at risk. The objective of this study was to explore the potential of blood-brain barrier (BBB) imaging as such a biomarker, by acquiring the first imaging data of BBB leakage in bipolar patients, and evaluating the potential association between BBB dysfunction and bipolar symptoms. To this end, a cohort of 36 bipolar patients was recruited through the Mood Disorders Clinic (Nova Scotia Health Authority, Canada). All patients, along with 14 control subjects (matched for sex, age and metabolic status), underwent contrast-enhanced dynamic MRI scanning for quantitative assessment of BBB leakage as well as clinical and psychiatric evaluations. Outlier analysis has identified a group of 10 subjects with significantly higher percentages of brain volume with BBB leakage (labeled the "extensive BBB leakage" group). This group consisted exclusively of bipolar patients, while the "normal BBB leakage" group included the entire control cohort and the remaining 26 bipolar subjects. Among the bipolar cohort, patients with extensive BBB leakage were found to have more severe depression and anxiety, and a more chronic course of illness. Furthermore, all bipolar patients within this group were also found to have co-morbid insulin resistance, suggesting that insulin resistance may increase the risk of BBB dysfunction in bipolar patients. Our findings demonstrate a clear link between BBB leakage and greater psychiatric morbidity in bipolar patients and highlight the potential of BBB imaging as a mechanism-based biomarker for bipolar disorder progression.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.323
Threshold uncertainty score0.850

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0010.000

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 head0.024
GPT teacher head0.375
Teacher spread0.350 · 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