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Record W1025527978 · doi:10.1007/978-3-7643-8567-5_6

Understanding the neurobiology of bipolar depression

2009· book-chapter· en· W1025527978 on OpenAlexaff
Jun-Feng Wang, L. Trevor Young

Bibliographic record

VenueBirkhäuser Basel eBooks · 2009
Typebook-chapter
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSerotoninBipolar disorderSerotonin transporterNeuroscienceNeuroplasticityEndocrinologyDepression (economics)Internal medicinePsychologyMood disordersMedicinePsychiatryCognitionAnxiety

Abstract

fetched live from OpenAlex

Many studies have shown decreased brain volume and cell number in prefrontal and limbic regions of bipolar disorder subjects, suggesting presence of disturbed neuronal circuitry and impaired neuroplasticity in these regions. The serotonin system plays an important role in depression and is a target of antidepressants. Studies have shown that the major serotonin metabolite 5-HIAA and serotonin transporter activity are decreased in cerebrospinal fluid, brain or platelets of subjects with bipolar depression, indicating that an abnormal serotonin system also contributes significantly to this disease. Mitochondria regulate synthesis, release and uptake of neurotransmitters via energy production. Evidence has shown that glucose metabolic rate and cerebral blood flow are decreased in bipolar depression. Studies also suggest defects in mitochondrial electron transport chain and oxidative damage in bipolar disorder. These studies together indicate that bipolar depression may be associated with an abnormal serotonin system resulting from mitochondrial dysfunction-induced impaired neuroplasticity in neuronal circuitry related to mood regulation. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0120.006

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 head0.076
GPT teacher head0.262
Teacher spread0.185 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations1
Published2009
Admission routes1
Has abstractyes

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