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Record W4402541128 · doi:10.1093/jas/skae234.126

296 Saccharomyces cerevisiae derived postbiotic modulates inflammatory response and gut microbiota in large breed dogs exposed to endurance exercise and transport stress

2024· article· en· W4402541128 on OpenAlexaboutno aff
C. Timlin, Fiona B Mccracken, Sarah M. Dickerson, Patrick M Skaggs, Jason W Fowler, Sangita Jalukar, Craid N Coon

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsnot available
Fundersnot available
KeywordsBreedSaccharomyces cerevisiaeGut floraInflammatory responseBiologyMicrobiologyInflammationAnimal scienceImmunologyGeneticsYeast

Abstract

fetched live from OpenAlex

Abstract Postbiotic supplements have been used in various livestock species to mitigate the negative effects of stress. This study aimed to determine if similar responses are seen in canine companion animals. We evaluated the effects of a Saccharomyces cerevisiae (S. cerevisiae) postbiotic supplement on inflammatory biomarkers, cortisol, and microbiota dysbiosis index in Labrador Retrievers exposed to exercise and transport stress. Dogs [n = 36; 3.52 ± 0.21 yr old and body weight (BW) = 27.6 ± 2.97 kg] were blocked by sex, age, and BW and assigned to receive 1 of 3 daily top-dressed treatments: 1) 15 g ground corn germ (Control, n = 12); 2) 7.5 g S. cerevisiae yeast postbiotic (Low, n = 12); or 3) 15 g of S. cerevisiae yeast postbiotic (High, n = 12). Dogs were given 1 wk to acclimate to treatments before beginning a 7-wk exercise regimen consisting of twice weekly 4.8 km guided runs. Dogs were exposed to a transportation stressor in wk 8. Fecal samples from d 0 and 56 were analyzed for calprotectin, calgranulin C (S100A12), α1-protease inhibitor, immunoglobulin A, and microbiota dysbiosis index. Blood was collected on d 0 and 63 for serum chemistries and complete blood counts. Blood collection was also performed prior to and 18 to 20 h after first and final runs of the exercise regimen for analysis of inflammatory cytokines. The Four Rivers Kennel (FRK) Gait Inflammation Index score was assessed prior to and 24 hours after the first and last exercise runs with the Gait4Dogs pressure mat system. Saliva cortisol was measured before and after transportation. Blood chemistry did not differ among treatments (P ≥ 0.19), but Control dogs had increased eosinophils (P = 0.01) and tended to have increased white blood cells (P = 0.08) and lymphocytes (P = 0.08) compared with dogs receiving postbiotic. Dogs fed Low dose had elevated monocyte chemoattractant protein-1 (P = 0.01) and maintained Interleukin (IL) -8 after the initial run (P = 0.03). Males in the Low group had increased IL-10 (P = 0.02). Fecal biomarkers and microbiota dysbiosis index score did not differ among treatments by d 56 (P ≥ 0.19). Blautia abundance was decreased in High (P = 0.04). Fusobacterium abundance tended to be reduced in High and increased in Control and Low (P = 0.07). Clostridium hiranonis tended to be greater in Low compared with Control (P = 0.07). The FRK Total Gait Inflammation Index scores decreased over time with acclimation to running (P < 0.01). Saliva cortisol concentrations did not differ among treatments (P ≥ 0.20). The Saccharomyces cerevisiae-based postbiotic tested in this study has potential as a functional ingredient to modulate immune function, improve muscle recovery shortly after exercise and positively change diversity of the gut microbiome in canine companion animal diets.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.281
Teacher spread0.267 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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