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Molecular analysis of bacterial populations in the ileum of broiler chickens and comparison with bacteria in the cecum

2002· article· en· W2087877512 on OpenAlexaff
Jianhua Gong, Robert J. Forster, Hai Yu, James R. Chambers, Roger Wheatcroft, Parviz M. Sabour, Shu Chen

Bibliographic record

VenueFEMS Microbiology Ecology · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of GuelphAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiologyCecumIleumBacteriaMicrobiology16S ribosomal RNABroilerRestriction fragment length polymorphismPopulationEnterococcusGeneGeneticsPolymerase chain reactionFood scienceBiochemistryEcology

Abstract

fetched live from OpenAlex

Bacterial populations in the ileum of broiler chickens were analyzed by molecular analysis of 16S rRNA genes and compared to those in the cecum. Bacteria found in the ileal mucosa were mainly Gram-positive with low G+C content. There were 15 molecular species among 51 cloned sequences. More than 70% of the cloned sequences were related to lactobacilli and Enterococcus cecorum. Two sequences had 95% or less homology to existing database sequences. Terminal restriction fragment length polymorphism (T-RFLP) analysis revealed differences among bacterial populations present in the mucosa and lumen of the ileum. Comparative studies by T-RFLP and sequence analyses of 16S rRNA genes indicated a less diverse bacterial population in the ileum (mucosa and lumen) than in the cecum. Lactobacilli, E. cecorum, and butyrate-producing bacteria related (including both identified and unidentified species) sequences were the three major groups detected in ilea and ceca. Although butyrate-producing bacteria may have good potential in the development of novel probiotics for poultry, verifying the presence of the bacteria in the chicken gut is required to warrant further investigation.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.237
Teacher spread0.204 · 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

Citations206
Published2002
Admission routes1
Has abstractyes

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