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Record W4404827336 · doi:10.3390/brainsci14121199

Mitochondrial Dysfunction as a Biomarker of Illness State in Bipolar Disorder: A Critical Review

2024· review· en· W4404827336 on OpenAlexaff
Anna Giménez‐Palomo, Helena Andreu, Oscar De Juan, Luis Olivier, Iñaki Ochandiano, Lídia Ilzarbe, Marc Valentí, Aldo Stoppa, Cristian-Daniel Llach, Giulio Pacenza, Ana C. Andreazza, Michael Berk, Eduard Vieta, Isabella Pacchiarotti

Bibliographic record

VenueBrain Sciences · 2024
Typereview
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersMinisterio de Ciencia e Innovación
KeywordsBipolar disorderBiomarkerMoodMood disordersMitochondrionMedicinePsychologyPsychiatryBioinformaticsNeuroscienceClinical psychologyBiologyAnxietyGenetics

Abstract

fetched live from OpenAlex

Mitochondria are organelles involved in different cellular functions, especially energy production. A relationship between mitochondrial dysfunction and mood disorders, especially bipolar disorder (BD), has been reported in the scientific literature, which suggests altered energy production and higher levels of oxidative stress compared to healthy controls. Specifically, in BD, the hypothesis of a biphasic pattern of energy availability has been postulated according to mood states. Current evidence highlights the presence of mitochondrial dysfunction in BD and variations between the manic, depressive, and euthymic phases. These findings need to be confirmed in future studies to identify biomarkers that may lead to individualized management of patients with BD and also to identify profiles with a higher risk of presenting an unfavorable course of illness, which would enable the design of preventive and therapeutic strategies in determined subpopulations of patients with BD. The limitations of this review include the non-systematic methodology, variety of mitochondrial-related functions associated with BD, heterogeneous study designs, preliminary evidence for specific findings, and limited recommendations regarding the use of mitochondrial modulators in BD.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.927
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
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 head0.059
GPT teacher head0.397
Teacher spread0.338 · 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 designOther design
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

Citations24
Published2024
Admission routes1
Has abstractyes

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