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Record W3206404393 · doi:10.1002/jimd.12449

Interplay between cardiolipin and plasmalogens in Barth syndrome

2021· review· en· W3206404393 on OpenAlexaff
José Carlos Bozelli, Richard M. Epand

Bibliographic record

VenueJournal of Inherited Metabolic Disease · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsHealth Sciences CentreMcMaster University Medical Centre
Fundersnot available
KeywordsPlasmalogenCardiolipinMitochondrionBiologyBiochemistryChemistryPhospholipidMembrane

Abstract

fetched live from OpenAlex

Barth syndrome (BTHS) is a rare inherited metabolic disease resulting from mutations in the gene of the enzyme tafazzin, which catalyzes the acyl chain remodeling of the mitochondrial-specific lipid cardiolipin (CL). Tissue samples of individuals with BTHS present abnormalities in the level and the molecular species of CL. In addition, in tissues of a tafazzin knockdown mouse as well as in cells derived from BTHS patients it has been shown that plasmalogens, a subclass of glycerophospholipids, also have abnormal levels. Likewise, administration of a plasmalogen precursor to cells derived from BTHS patients led to an increase in plasmalogen and to some extent CL levels. These results indicate an interplay between CL and plasmalogens in BTHS. This interdependence is supported by the concomitant loss in these lipids in different pathological conditions. However, currently the molecular mechanism linking CL and plasmalogens is not fully understood. Here, a review of the evidence showing the linkage between the levels of CL and plasmalogens is presented. In addition, putative mechanisms that might play a role in this interplay are proposed. Finally, the opportunity of therapeutic approaches based on the regulation of plasmalogens as new therapies for the treatment of BTHS is 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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.026
GPT teacher head0.328
Teacher spread0.302 · 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 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

Citations13
Published2021
Admission routes1
Has abstractyes

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