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Record W3017084649 · doi:10.24869/psyd.2020.55

PHOSPHATIDYLCHOLINE CONTAINING LONG CHAIN OMEGA-3 FATTY ACIDS: A TREATMENT ADJUNCT FOR PATIENTS WITH ANOREXIA NERVOSA?

2020· review· en· W3017084649 on OpenAlexaff
Olivia Patsalos, Theodoros Mavrogiannidis, Bethan Dalton, Catherine J. Field, Hubertus Himmerich

Bibliographic record

VenuePsychiatria Danubina · 2020
Typereview
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsUniversity of Alberta
FundersErasmus+Aristotle University of ThessalonikiInstitute of Psychiatry, Psychology and Neuroscience, King’s College LondonKing's College LondonNational Institute for Health and Care ResearchSouth London and Maudsley NHS Foundation Trust
KeywordsAdjunctAnorexia nervosaOmegaPhosphatidylcholineMedicineInternal medicineEndocrinologyPsychiatryChemistryEating disordersBiochemistryPhospholipidPhilosophy

Abstract

fetched live from OpenAlex

BACKGROUND: Anorexia nervosa (AN) is a serious mental disorder with a high mortality rate and often a chronic course. In contrast to many other common mental disorders, there is no drug therapy approved for AN. METHODS: We performed a narrative literature review to consider whether a choline-containing molecule, such as phosphatidylcholine (PC), with an omega (ω)-3 long chain polyunsaturated fatty acid (LCPUFA) could be a potential future medicinal treatment for AN. RESULTS: Choline and LCPUFAs have individually shown benefit for mental health. Case series and pilot studies suggest ω-3 LCPUFAs may be effective in eating disorders. However, pharmacodynamic and pharmacokinetic considerations suggest a greater benefit from the combination of both components. CONCLUSION: The combination of a choline-containing molecule with an ω-3 LCPUFA may be clinically effective and well tolerated. This idea is supported by the current literature on the role of inflammation, the microbiome, the gut-brain-axis, hormonal, neurotransmitter and intracellular signalling, and on the structure and fluidity of nerve cells membranes in patients with AN.

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 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 score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.041
GPT teacher head0.305
Teacher spread0.264 · 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

Citations4
Published2020
Admission routes1
Has abstractyes

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