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Record W2065141568 · doi:10.1089/fpd.2011.1112

Adaptive Acid Tolerance Response of <i>Vibrio parahaemolyticus</i> as Affected by Acid Adaptation Conditions, Growth Phase, and Bacterial Strains

2012· article· en· W2065141568 on OpenAlexfundno aff
Ming‐Lun Chiang, Cheng‐Chun Chou, Hsi-Chia Chen, Yu‐Ting Tseng, Ming‐Ju Chen

Bibliographic record

VenueFoodborne Pathogens and Disease · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVibrio bacteria research studies
Canadian institutionsnot available
FundersBeef Cattle Research CouncilNational Science Council
KeywordsVibrio parahaemolyticusMicrobiologyBiologyBacteria

Abstract

fetched live from OpenAlex

Vibrio parahaemolyticus strain 690 was isolated from gastroenteritis patients. Its thermal and ethanol stress responses have been reported in our previous studies. In this study, we further investigated the effects of various acid adaptation conditions including pH (5.0-6.0) and time (30-90 min) on the acid tolerance in different growth phases of V. parahaemolyticus 690. Additionally, the adaptive acid tolerance among different V. parahaemolyticus strains was compared. Results indicated that the acid tolerance of V. parahaemolyticus 690 was significantly increased after acid adaptation at pH 5.5 and 6.0 for 30-90 min. Among the various acid adaptation conditions examined, V. parahaemolyticus 690 acid-adapted at pH 5.5 for 90 min exhibited the highest acid tolerance. The acid adaptation also influenced the acid tolerance of V. parahaemolyticus 690 in different growth phases with late-exponential phase demonstrating the greatest acid tolerance response (ATR) than other phases. Additionally, the results also showed that the induction of adaptive ATR varied with different strains of V. parahaemolyticus. An increase in acid tolerance of V. parahaemolyticus was observed after prior acid adaptation in five strains (556, 690, BCRC 13023, BCRC 13025, and BCRC 12864), but not in strains 405 and BCRC 12863.

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)0.001
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 score0.214
Threshold uncertainty score0.846

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.014
GPT teacher head0.272
Teacher spread0.258 · 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

Citations10
Published2012
Admission routes1
Has abstractyes

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