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Record W4413840875 · doi:10.1093/jas/skaf298

Serum metabolomics reveals one-carbon metabolism differences between lean and obese cats not affected by L-carnitine or choline supplementation

2025· article· en· W4413840875 on OpenAlexafffund
Alexandra Rankovic, Anna K. Shoveller, Marica Bakovic, Gordon M. Kirby, Adronie Verbrugghe

Bibliographic record

VenueJournal of Animal Science · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism and Genetic Disorders
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaBalchem
KeywordsCATSCholineCarnitineInternal medicineEndocrinologyOverweightMedicineAnalysis of varianceLipid metabolismAnimal scienceChemistryBody mass indexBiology

Abstract

fetched live from OpenAlex

The supplementation of choline and L-carnitine in obese cats has garnered attention as a potential method for preventing and treating feline hepatic lipidosis (FHL). Providing dietary choline above the current recommended allowance to overweight and obese cats may have positive effects on one-carbon metabolism and hepatic lipid mobilization. Research on the metabolomic effects of L-carnitine supplementation in cats, however, remains limited. This study aimed to investigate the individual effects of choline and L-carnitine supplementation on the fasted serum metabolomic profiles of obese (n = 9; body condition score [BCS]: 8-9/9) and lean (n = 9; BCS: 4-5/9) adult male neutered cats fed at maintenance energy requirements. Cats were fed a commercial extruded cat food top-dressed with choline (6 x National Research Council recommended allowance: 378 mg/kg BW0.67), L-carnitine (200 mg/kg BW), or control (no supplement) in a 3 × 3 complete Latin square design for 6 wk per treatment, with a 2-wk washout between each treatment period. The cats were fed once daily, and BW and BCS were assessed weekly. Fasted serum metabolites were analyzed at the end of each treatment period using direct infusion mass spectrometry (DI-MS) and liquid chromatography-mass spectrometry (LC-MS). The data were analyzed using SAS with proc GLIMMIX, considering group and period as random effects, and treatment, body condition, and their interaction as fixed effects. Statistical significance was set at P < 0.05, and Tukey's post-hoc test was used for multiple comparisons when significance was observed. Obese cats had greater concentrations of s-adenosylhomocysteine, cysteine, cystine, reduced glutathione, and oxidized glutathione (GSSG), suggestive of alterations in one-carbon metabolism with obesity. The oxidation of fatty acids may have improved with both L-carnitine and choline supplementation. While choline and L-carnitine independently affected concentrations of betaine, GSSG, and decarboxylated S-adenosylmethionine, respectively, neither supplement broadly altered one-carbon metabolism. The present study suggests that dysfunction in one-carbon metabolism should be taken into consideration when examining the pathogenesis and increased FHL risk in obese cats.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.019
GPT teacher head0.301
Teacher spread0.281 · 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 designObservational
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

Citations2
Published2025
Admission routes2
Has abstractyes

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