MétaCan
Menu
Back to cohort
Record W4387999701 · doi:10.1093/jas/skad341.078

106 Using Postbiotic <i>Saccharomyces Cerevisiae</i> Yeast in Gestation and Lactation Diets of Gilts to Improve Immunoglobulin Transfer and Offspring Growth Pre-Weaning

2023· article· en· W4387999701 on OpenAlexaff
Brenda Christensen, Hagen Schulze, Elijah G. Kiarie, Lee‐Anne Huber

Bibliographic record

VenueJournal of Animal Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsLactationLitterColostrumWeaningGestationAnimal scienceBiologyOffspringWeight gainPregnancyAntibodyEndocrinologyBody weightImmunologyEcology

Abstract

fetched live from OpenAlex

Abstract Gilts [n = 50; initial body weight (BW) 190.7 ± 4.2 kg] were used to determine the optional inclusion level of postbiotic Saccharomyces cerevisiae in late gestation and lactation diets to improve immunoglobulin transfer and piglet growth performance during the suckling period. Gilts were assigned to one of five (n = 10) diets: standard gestation and lactation diets (Y0) or diets with postbiotic yeast included at either 0.25% (Y0.25), 0.5% (Y0.5), 1.0% (Y1), or 1.2% (Y1.2). Diets were fed from d 85 of gestation until weaning (d 21 after farrowing). During gestation gilts were fed 2.6kg/d and feed was offered ad libitum during lactation. Gilt BW was recorded on d 85 and 110 of gestation, and gilt and piglet BW were recorded on d 1 and 21 of lactation. Twenty-four hours after farrowing, plasma was collected from each gilt and two median BW piglets per litter via orbital sinus. Additionally, 50 mL of colostrum was collected in equal parts from all functional teats on the right side. On d 21, plasma samples were collected from each gilt and two median BW piglets per litter. Concentrations of immunoglobulin (Ig) A, G, and M were quantified in plasma and colostrum. Data were analyzed in SAS with treatment as the main effect. Linear, quadratic, and yeast vs. no yeast contrast statements were used to assess responses to dietary inclusion of yeast. Time (minutes) between farrowing (defined as birth of the first piglet, confirmed by video recording) and sampling was used as a covariate for d 1 Ig concentrations. There were no differences in number of piglets born alive (12.5 ± 0.9), birth weight (1.40 ± 0.45kg), or gilt BW change during lactation (-7.98 ± 6.68kg). Lactation average daily feed intake tended to be 14.6% greater for gilts provided yeast versus no yeast (5.11 vs. 4.46 ± 0.31kg, respectively; P = 0.069). At weaning, offspring from Y0.25 fed gilts had greater BW than piglets from Y0- or Y1.2-fed gilts (6.48 vs. 5.66 and 5.82 kg ± 0.16, respectively; P < 0.001), with all other treatments intermediate. On d 1, colostrum and gilt plasma Ig concentrations were unaffected by diets. However, yeast increased piglet plasma concentrations of IgM (linear; P = 0.034) and tended to increase IgA (linear; P=0.093), and total Ig (linear; P = 0.074). On d 21, gilts fed yeast-containing diets tended to have greater plasma IgA (yeast vs. no yeast and quadratic; P = 0.063 and P = 0.076, respectively), but IgM was greater for gilts fed Y0 (yeast vs. no yeast; P < 0.05). On d 21, piglet plasma IgA tended to be greater when gilts were provided yeast-containing diets (yeast vs. no yeast; P = 0.069). Therefore, postbiotic Saccharomyces cerevisiae was effective in improving maternal transfer, with piglet IgA and IgM concentrations increasing linearly with increasing yeast inclusion, while Y0.25 also improved piglet growth performance during the suckling phase.

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 score0.004

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 integrity0.0000.001
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 head0.020
GPT teacher head0.257
Teacher spread0.237 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Animal ScienceSame topicAnimal Nutrition and PhysiologyFrench-language works237,207