Differences in cecal microbiome of selected high and low feather-pecking laying hens
Bibliographic record
Abstract
In mammals, it has become increasingly clear that the gut microbiota influences not only gastrointestinal physiology but also modulates behavior. In domestic birds, ceca have the greatest gastrointestinal microbial population. Feather-pecking (FP) behavior in laying hens is one of the most important unsolved behavioral issues in modern agriculture. The aim of the present study was to assess the cecal microbial community of divergently selected high (HFP; n = 20) and low (LFP; n = 20) feather-pecking birds at 60 wk of age. The cecal samples were subjected to community profiling of 16S rRNA and in silico metagenomics using a modified bar-coded Illumina sequencing method on a MiSeq Illumina sequencer. Our results revealed that compared to HFP birds, LFP birds are characterized by an increased overall microbial diversity (beta diversity) shown by a difference in the Bray-Curtis index (R2 = 0.171, P < 0.05). Furthermore, operational taxonomic unit comparisons showed an increased presence of Clostridiae and decreased presence of Lactobaccillacae in HFP birds when compared to LFP birds (False Discovery Rate < 0.05, Mann-Whitney comparisons). Our data indicate that there may be differences in the cecal profile between these 2 lines of laying hens. More research, building on this first study using sequencing technology for profiling the chicken cecal microbiome, will be needed in order to reveal if and how there exists a functional link between the performance of FP and the cecal microbial community.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".