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Record W6982473489

Induction and elimination of viable but non-culturable Campylobacter jejuni in agri-food systems

2023· dissertation· en· W6982473489 on OpenAlexafffund

Bibliographic record

VenueeScholarship@McGill (McGill) · 2023
Typedissertation
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsCampylobacter jejuniCampylobacter fetusBacteriaCampylobacterAntibiotics
DOInot available

Abstract

fetched live from OpenAlex

Numerous bacterial species possess the ability to enter a state known as viable but non-culturable (VBNC) in response to adverse environmental conditions.Although pathogenic bacteria are unlikely to cause diseases in the VBNC state, they can regain virulence upon resuscitation under favorable conditions, thereby posing a substantial threat to food safety and public health.Moreover, the inability to detect VBNC bacteria using conventional microbiological culture-based methods further accentuates the risk.Therefore, it is imperative to inactivate pathogenic bacteria in the VBNC state before they regain culturability.Due to the high antimicrobial tolerance exhibited by VBNC bacterial pathogens, current inactivation methods may be ineffective, necessitating the development of novel strategies to control these pathogens in the VBNC state.Campylobacter jejuni is a leading cause of human gastroenteritis worldwide and is commonly found in both food production and environmental settings.However, the mechanisms by which this microaerophilic microbe survives in the aerobic environment and disseminates throughout the food supply chain remain incompletely understood.The factors involved in inducing C. jejuni to enter the VBNC state during food processing and the persistence of VBNC C. jejuni to antimicrobials are largely unknown and require further investigation.This dissertation aims to address the aforementioned knowledge gaps and enhance our understanding of the persistence of C. jejuni in the agri-food system, with the ultimate goal of developing more effective intervention strategies.C. jejuni encounters various stressors that can trigger the induction of the VBNC state during food processing and within food products.Notably, when exposed to chlorine, C. jejuni completely lost VI its ability to form colonies, but a fraction of the bacteria (1-10%) maintained their viability.In contrast, under aerobic and low temperatures conditions, ~10% of C. jejuni entered the VBNC state after 24 h and 20 days, respectively.Furthermore, the strain C. jejuni ATCC 33560 showed a higher propensity for entering the VBNC state in both refrigerated UHT and pasteurized milk compared to other strains such as F38011, NCTC 11168, and 81116.These observations of heterogeneous behavior among different strains suggest the existence of strain-specific variations in response to stressors.By conducting the time-kill assay, notable variations were observed in the response of VBNC C. jejuni towards plant-based antimicrobials and metal oxide nanoparticles (NPs).Specifically, the bacterium exhibited a remarkable persistence against carvacrol or diallyl sulfide, whereas it displayed susceptibility to aluminum oxide NPs.Moreover, the interactions among these antimicrobials were thoroughly investigated.The combination of carvacrol and diallyl sulfide resulted in an additive antimicrobial effect.Furthermore, synergistic effects were observed when either carvacrol or diallyl sulfide was combined with Al2O3 NPs.Remarkably, the ternary combination of carvacrol, diallyl sulfide, and Al2O3 NPs demonstrated a synergistic effect, enabling reduced concentrations of these antimicrobials to achieve effective inactivation.Subsequently, these antimicrobial treatments were employed to inactivate VBNC C. jejuni under poultry processing conditions.However, relatively lower effectiveness was observed, possibly attributed to the presence of lipids and proteins in chicken juice.These components have the potential to interact with antimicrobials, resulting in reduced antimicrobial availability and compromised efficacy.The interactions among the antimicrobials were first assessed using the time-kill assay, revealing additive effects in all combinations tested.To ensure accurate assessment without overestimation or underestimation, a novel mathematical model was developed to further investigate these antimicrobial interactions.The application of this computational approach

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.010
GPT teacher head0.196
Teacher spread0.186 · 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 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
Published2023
Admission routes2
Has abstractyes

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