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Record W4415466928 · doi:10.1186/s40813-025-00465-2

The role of human–pig interactions in modulating gut microbiota, stress, and performance

2025· article· en· W4415466928 on OpenAlexaff
Lucas Venegas, Rocío Palomo, Nicolás Galarce, Daniela Siel, José M. Yáñez, Florencia Correa‐Fiz, Javiera Calderón-Amor, Daniel Cartes, Maria Camila Ceballos, Agustin Piña-Elgueda, Sergio A. Guzmán-Pino, Daniela Luna

Bibliographic record

VenuePorcine Health Management · 2025
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of Calgary
FundersAgencia Nacional de Investigación y Desarrollo
KeywordsGut floraBacteriaFight-or-flight responseEnzyme

Abstract

fetched live from OpenAlex

BACKGROUND: The microbiota‒gut‒brain axis modulates pigs' stress response, behavior, and overall welfare. Stressful management practices can disrupt gut microbiota (GM), negatively impacting pigs' health and welfare. This study evaluated how the quality of human handling influences stress-related physiological responses, productive performance, and gut microbiota (GM) composition in pigs during the nursery phase. RESULTS: Female pigs (n= 36, 21 days old) were randomly assigned to three experimental groups (12 pigs/group, four pens per treatment): positive human handling (PHH), negative human handling (NHH), and a control group (CG). The PHH group experienced gentle tactile interactions, whereas the NHH group was subjected to chronic intermittent stress through acute stressors, and the CG group received minimal handling for routine practices. Hair cortisol concentrations were measured as an indicator of chronic stress (days 15 and 64). Productive performance was assessed through body weight (BW), average daily gain (ADG), average daily feed intake (ADFI), and feed conversion (FC). Fecal samples were collected at baseline (T0, day 16), mid-study (T1, day 37), and end of the study (T2, day 65) and analyzed using 16S rRNA gene amplicon sequencing to assess GM changes over time. Pigs in the PHH group showed a significant reduction in cortisol levels from baseline to post-treatment (P < 0.0001), while no significant changes were observed in the NHH group (P = 0.26). A smaller but significant decrease was also detected in the CG group (P = 0.001). PHH pigs had higher BW (P = 0.0009) and ADG (P = 0.03) during the later growth phase compared to NHH pigs. At T2, PHH pigs exhibited greater diversity and richness compared to NHH pigs, indicating a restorative effect on GM composition. Differential abundance analyses identified four bacterial genera that distinguished treatment groups: Blautia, Megasphaera, and Subdoligranulum were enriched in PHH pigs, while Terrisporobacter was enriched in NHH pigs. Additionally, bacterial interaction networks exhibited the least complex network in the NHH group, with ecological associations primarily involving Clostridium and Terrisporobacter. CONCLUSIONS: The quality of human handling influenced stress physiology, performance, and gut microbiota in pigs. Positive handling reduced cortisol levels, improved growth, and promoted microbial diversity, while negative handling was linked to decreased performance and reduced microbial network complexity. These results highlight the potential of positive interactions to enhance welfare and productivity, and identify specific bacterial genera as potential biomarkers differentiating negative and positive handling conditions.

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)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.033
GPT teacher head0.369
Teacher spread0.336 · 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
Published2025
Admission routes1
Has abstractyes

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