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Record W4388539541 · doi:10.1093/jas/skad281.121

190 The Nutrigenomic Effects of Dietary Choline and L-Carnitine on the Muscle and Liver of Lean and Overweight Cats

2023· article· en· W4388539541 on OpenAlexaffabout
Jess Fletcher, Sophie Grapentine, Alexandra Rankovic, Brigitte A. Brisson, Melissa Sinclair, Anna K. Shoveller, Eric K Altom, Marica Bakovic, Adronie Verbrugghe

Bibliographic record

VenueJournal of Animal Science · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCholineOverweightInternal medicineEndocrinologyCATSBiologyMedicineObesity

Abstract

fetched live from OpenAlex

Abstract The objective of this study was to investigate the effects of dietary choline and L-carnitine on the lipotropic gene expression in the muscle and liver of overweight and lean cats, when fed for body weight (BW)maintenance. Overweight [n = 6, body fat percent (BF%): 33.2 ± 1.38] and lean (n = 6, BF%:18.4 ± 0.93), 1-2 year old, male, neutered cats received choline (378 mg/kg BW0.67), L-carnitine (200 mg/kg BW) and no supplementation (control) in a 3x3 Latin square design for 6 weeks, with a 2-week washout between treatments periods. Each treatment was offered with a commercial extruded diet; diet amount was provided to maintain current BW. Cats were anesthetized and quadriceps vastus lateralis (30-50 mg) and liver (30-50 mg) biopsies were harvested after each treatment period using an open muscle or laparoscopic biopsy technique respectively. Tissue RNA was isolated with TRIzol and sequenced using directional PolyA RNA-seq. The expressed genes were aligned using the reference genome, Felis_catus_9.0, Ensembl v.107. Differential gene expression was analyzed for 29,928 genes with SEQUIN, using edgeR and TMM normalization. Pathway analysis was performed using EnrichR databases, BioPlanet 2019 and KEGG 2021. Using a two-group comparison, global analysis revealed 92 and 759 differentially expressed genes in the liver and muscle, respectively of overweight cats compared with lean (P < 0.05). Affected pathways included fat digestion and absorption, including peroxisome proliferator-activated receptor (PPAR) signaling in the liver, and immunity related pathways in muscle (P < 0.05). Upon further analysis using a two-group comparison between overweight and lean cats for each treatment, 11 and 692 significant genes were found in choline treated liver samples and L-carnitine treated muscle samples, respectively (P < 0.05). Similar to the global analysis, genes related to fat metabolism, including PPAR signaling, were significant in the choline treated liver samples, and immunity related genes were significant in the L-carnitine treated muscle samples (P < 0.05). Based on preliminary data, supplemental dietary choline may be beneficial for overweight cats as it may increase fat metabolism in the liver, mitigating risks associated with feline hepatic lipidosis (FHL). Supplemental dietary L-carnitine may also be beneficial due to its effects on immunity related pathways, including pathogen defense. To investigate the full effects of choline and L-carnitine on gene expression, further studies are warranted including older, chronically obese cats, as well as confirmed cases of FHL. Acknowledgements: Natural Sciences and Engineering Council of Canada, Elmira Pet Products and Balchem Corp.

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 score0.003
Threshold uncertainty score0.005

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 head0.012
GPT teacher head0.245
Teacher spread0.233 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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