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Record W3183710616 · doi:10.3390/life11070719

In Vitro Assays for the Assessment of Impaired Mitochondrial Bioenergetics in Equine Atypical Myopathy

2021· article· en· W3183710616 on OpenAlexaff
Caroline Kruse, David Stern, Ange Mouithys‐Mickalad, Ariane Niesten, Tatiana Art, Hélène Lemieux, Dominique Votion

Bibliographic record

VenueLife · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of Alberta
FundersFonds De La Recherche Scientifique - FNRS
KeywordsMyopathyBioenergeticsBiologyMitochondrionRespirometryMitochondrial myopathyMyocytePathologyIngestionToxicityBiochemistryEndocrinologyInternal medicineMedicineGeneticsMitochondrial DNA

Abstract

fetched live from OpenAlex

Equine atypical myopathy is a seasonal intoxication of grazing equids. In Europe, this poisoning is associated with the ingestion of toxins contained in the seeds and seedlings of the sycamore maple (Acer pseudoplatanus). The toxins involved in atypical myopathy are known to inhibit ß-oxidation of fatty acids and induce a general decrease in mitochondrial respiration, as determined by high-resolution respirometry applied to muscle samples taken from cases of atypical myopathy. The severe impairment of mitochondrial bioenergetics induced by the toxins may explain the high rate of mortality observed: about 74% of horses with atypical myopathy die, most within the first two days of signs of poisoning. The mechanism of toxicity is not completely elucidated yet. To improve our understanding of the pathological process and to assess therapeutic candidates, we designed in vitro assays using equine skeletal myoblasts cultured from muscle biopsies and subjected to toxins involved in atypical myopathy. We established that equine primary myoblasts do respond to one of the toxins incriminated in the disease.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.241

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.015
GPT teacher head0.293
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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations3
Published2021
Admission routes1
Has abstractyes

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