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Record W31330827 · doi:10.3390/toxins11070426

3.日本の牛肉生産の現状と肥育技術(第22回日本獣医畜産大学学術交流会)

2007· article· en· W31330827 on OpenAlexfundaboutno aff
年浩 撫

Bibliographic record

VenueToxins · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicListeria monocytogenes in Food Safety
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates Bio Solutions
KeywordsComputer science

Abstract

fetched live from OpenAlex

<i>Listeria monocytogenes</i> strains are known to harbour plasmids that confer resistance to sanitizers, heavy metals, and antibiotics; however, very little research has been conducted into how plasmids may influence <i>L. monocytogenes</i>' ability to tolerate food-related stresses. To investigate this, a library (<i>n</i> = 93) of <i>L. monocytogenes</i> plasmid sequences were compared. Plasmid sequences were divided into two groups (G1 and G2) based on a <i>repA</i> phylogeny. Twenty-six unique plasmid types were observed, with 13 belonging to each of the two <i>repA</i>-based groups. G1 plasmids were significantly (<i>p</i> < 0.05) smaller than G2 plasmids but contained a larger diversity of genes. The most prevalent G1 plasmid (57,083 bp) was observed in 26 strains from both Switzerland and Canada and a variety of serotypes. Quantitative PCR (qPCR) revealed a >2-fold induction of plasmid-contained genes encoding an NADH peroxidase, cadmium ATPase, multicopper oxidase, and a ClpL chaperone protein during growth under salt (6% NaCl) and acid conditions (pH 5) and ProW, an osmolyte transporter, under salt stress conditions. No differences in salt and acid tolerance were observed between plasmid-cured and wildtype strains. This work highlights the abundance of specific plasmid types among food-related <i>L. monocytogenes</i> strains, the unique characteristics of G1 and G2 plasmids, and the possible contributions of plasmids to <i>L. monocytogenes</i> tolerance to food-related stresses.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.362
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.052
GPT teacher head0.332
Teacher spread0.280 · 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 teacher head, 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
Published2007
Admission routes2
Has abstractyes

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