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Record W1993494094 · doi:10.1517/13543784.16.10.1627

Omega-3 fatty acid eicosapentaenoic acid. A new treatment for psychiatric and neurodegenerative diseases: a review of clinical investigations

2007· review· en· W1993494094 on OpenAlexaff
Cai Song, Shannon X. Zhao

Bibliographic record

VenueExpert Opinion on Investigational Drugs · 2007
Typereview
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsThe Scarborough HospitalUniversity of TorontoUniversity of Prince Edward Island
Fundersnot available
KeywordsEicosapentaenoic acidClinical trialSchizophrenia (object-oriented programming)DiseaseMedicineDepression (economics)NeuroprotectionOmega 3 fatty acidPsychiatryPlaceboPolyunsaturated fatty acidInternal medicineDocosahexaenoic acidFatty acidBiologyAlternative medicinePathologyBiochemistry

Abstract

fetched live from OpenAlex

Decreased n-3 fatty acid levels have been reported in patients with depression, schizophrenia or Alzheimer's disease. Recently, eicosapentaenoic acid (EPA) has been used to treat several psychiatric and neurodegenerative diseases due to its anti-inflammatory and neuroprotective effects. A total of six out of seven clinical trials have shown that EPA significantly improved depressive symptoms when compared with the placebo-treated populations. Several investigations have also reported that EPA could effectively treat schizophrenia. A case report and a clinical trial have shown that EPA was beneficial for the management of most symptoms of Huntington's disease, while a more extensive clinical investigation has demonstrated that EPA could only improve motor functions. Further clinical studies are required to fully explore the effects of EPA on other neurodegenerative diseases. The limitations of previous studies and further research directions have also been discussed.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.858
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.217
GPT teacher head0.495
Teacher spread0.278 · 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.

Study designNot applicable
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

Citations52
Published2007
Admission routes1
Has abstractyes

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