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Record W4410535850 · doi:10.1093/jas/skaf102.348

PSVI-15 Impact of high zinc oxide supplementation or lignocellulose supplement on fecal microbiota of weaned piglets

2025· article· en· W4410535850 on OpenAlexaffabout
Eya Selmi, Clara Negrini, Antony T. Vincent, Marie-Pierre Létourneau-Montminy, Luca Lo Verso, Bertrand Medina, Frédéric Guay

Bibliographic record

VenueJournal of Animal Science · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsFecesZincFood scienceAnimal scienceChemistryBiologyMicrobiology

Abstract

fetched live from OpenAlex

Abstract This project aimed to study the effect of high zinc oxide (ZO) and fiber supplementation from lignocellulose (LIGCEL) on the fecal microbiota of weaned piglets. At weaning (21 days), 150 piglets (6.39 ± 0.28 kg) were transferred to a nursery farm, and divided into 30 pens of 5 piglets each according to their weaning weight. Each pen was assigned to one of the following treatments: Control (CON, 150 mg/kg of zinc), ZO (2,500 mg/kg of zinc), and LIGCEL (CON + 3% lignocellulose). fed to the animalsadministered for 14 days. In each pen, 2 to 3 fresh fecal samples were collected and pooled on day 14. The 16s RNA gene amplification and sequencing were performed at the Genomic Analysis Platform (Université Laval, Québec, Canada). Amplicon sequence variants (ASVs) were generated using the DADA2 pipeline, considering the SILVA rRNA database. Alpha diversity was calculated on normalized data (evenness: Shannon and Simpson). For the beta diversity, the Bray Curtis distance matrix was calculated and plotted using a Nonmetric multidimensional scaling (NMDS) plot. The effects of diets were tested using a non-parametric PERMANOVA model, with 999 permutations. The differential abundance analysis on the different taxa was performed using Linear discriminant analysis Effect Size (LEfSe) at family level. An LDA score of 3 was used as a cutoff value. A total of 11,083 ASVs were obtained. The ASVs were associated with 23 phyla and 107 families. The most abundant phyla were Firmicutes (71 ± 0.08%), Bacteroidota (25 ± 0.07%), and Proteobacteria (2 ± 0.04%); the most abundant families were Lachnospiraceae (30 ± 0.11%), Lactobacillaceae (26 ± 0.13%), and Prevotellaceae (20 ± 0.08%). Alpha diversity was not affected by diet. Diet significantly affected the Adonis test (R² = 0.20, P = 0.001). Piglets receiving the LIGCEL supplement were characterized by a higher abundance of Lactobacillaceae (P:adj= 0.0007, LDA:score= 5.20), Veillonellaceae (P:adj= 0.026, LDA:score= 4.38), Rikenellaceae (P:adj= 0.009, LDA:score= 3.78), Succinivibrionaceae (P:adj= 0.001, LDA:score= 3.68), and Selenomonadaceae (P:adj= 0.038, LDA:score= 3.61). CON piglets were characterized by a higher abundance of Enterobacteriaceae (P:adj= 0.046, LDA:score= 4.35), Christensenellaceae (P:adj= 0.0003, LDA:score= 4.09), and Spirochaetaceae (P:adj= 0.0003, LDA:score= 4.09). Piglets receiving the ZO diet were characterized by a higher abundance of Lachnospiraceae (P:adj= 0.0002, LDA:score= 5.11), Prevotellaceae (P:adj= 0.011, LDA:score= 4.88), Ruminococcaceae (P:adj= 0.0009, LDA:score= 4.30), Clostridiaceae (P:adj= 0.045, LDA:score= 4.00), and Butyricicoccaceae (P:adj= 0.015, LDA:score= 3.76). The addition of ZO clearly modified the fecal microbiota of piglets, highlighting families positively associated with intestinal health, as Lachnospiraceae, Prevotellaceae, and Ruminococcaceae. The lignocellulose supplement also promoted the development of favorable families, namely Lactobacillaceae and Rikenellaceae. In contrast, CON piglets were characterized by the presence of bacteria from the Enterobacteriaceae family.

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)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.008
GPT teacher head0.283
Teacher spread0.275 · 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".

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Citations0
Published2025
Admission routes2
Has abstractyes

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