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Record W4206680786 · doi:10.3168/jds.2021-20572

Saccharomyces cerevisiae fermentation products reduce bacterial endotoxin concentrations and inflammation during grain-based subacute ruminal acidosis in lactating dairy cows

2022· article· en· W4206680786 on OpenAlexafffund
Junfei Guo, Lei Xu, H. Khalouei, Kelsey Fehr, V. Senaratne, Jean‐Eric Ghia, I. Yoon, Ehsan Khafipour, J.C. Plaizier

Bibliographic record

VenueJournal of Dairy Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaDairy Farmers of ManitobaDiamond VUniversity of Manitoba
KeywordsRumenTotal mixed rationAcidosisAnimal scienceDry matterNeutral Detergent FiberBiologyLactationFermentationChemistryEndocrinologyInternal medicineFood scienceMedicineIce calving

Abstract

fetched live from OpenAlex

Subacute ruminal acidosis (SARA) is a metabolic disorder in dairy cows that is associated with dysbiosis of rumen and hindgut microbiomes, translocation of immunogenic compounds from the gut lumen into blood circulation, and systemic inflammatory response. In this study we hypothesized that Saccharomyces cerevisiae fermentation products (SCFP) attenuate the increases in ruminal and peripheral bacterial endotoxin concentrations and the inflammation resulting from repeated induction of SARA. Lactating Holstein dairy cows (parity 2 and 3+, n = 32) were fed diets with or without SCFP (all from Diamond V) and subjected to 2 episodes of SARA challenges. Cows received a basal total mixed ration (TMR) containing 34% neutral detergent fiber and 18.6% starch, dry matter (DM) basis. Treatments were randomly assigned to control (basal TMR and 140 g/d of ground corn with no SCFP) or 1 of 3 SCFP treatments: basal TMR and 14 g/d Original XPC (SCFPa), 19 g/d NutriTek (SCFPb-1×), or 38 g/d NutriTek (SCFPb-2×) mixed with 126, 121, or 102 g/d of ground corn, respectively. Treatments were implemented from 4 wk before until 12 wk after parturition. During wk 5 (SARA1) and wk 8 of lactation (SARA2), grain-based SARA challenges were conducted by gradually replacing 20% of DM of the basal TMR over 3 d with pellets containing 50% wheat and 50% barley. Ruminal fluid, fecal, and blood samples were collected weekly during Pre-SARA1 (wk 4, as baseline), Post-SARA1 (wk 7), and Post-SARA2 (wk 10 for blood and wk 12 for rumen and fecal parameters) stages, and twice a week during the challenges SARA1 and SARA2. Rumen papillae samples were taken only during Pre-SARA1 and Post-SARA2. We measured the concentrations of free lipopolysaccharides (LPS) in the rumen fluid and feces; free LPS and lipoteichoic acid (LTA) endotoxins in peripheral plasma; interleukin (IL)-1β and IL-6 in peripheral serum; acute-phase proteins, serum amyloid A (SAA), and LPS-binding protein in peripheral plasma; haptoglobin (Hp) in peripheral serum; and myeloperoxidase (MPO) in rumen papillae. Induction of SARA episodes increased free LPS concentrations in rumen fluid and tended to increase LTA in peripheral plasma. The SARA episodes increased concentration of circulating SAA and tended to increase that of IL-1β compared with Pre-SARA1. Induction of SARA did not affect the concentrations of circulating IL-6, Hp, and MPO. The SCFP supplementation reduced plasma concentrations of LTA and SAA and serum concentration of IL-1β compared with control. Additionally, SCFPb-2× tended to reduce ruminal LPS in second-parity cows compared with control. Overall, SCFP supplementation appeared to stabilize the rumen environment and reduce proinflammatory status, hence attenuating adverse digestive and inflammatory responses associated with SARA episodes.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 integrity0.0000.001
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 head0.021
GPT teacher head0.252
Teacher spread0.231 · 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 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

Citations50
Published2022
Admission routes2
Has abstractyes

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