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Record W2782157118 · doi:10.1093/annweh/wxx109

Combining Environmental Investigation and a Dual-Analytical Strategy to Isolate the Legionella longbeachae Strain Linked to Two Occupational Cases of Legionellosis

2017· article· en· W2782157118 on OpenAlexaffabout
Geneviève Marchand, Judith Lord, Carole Pépin, Nancy Lacombe

Bibliographic record

VenueAnnals of Work Exposures and Health · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLegionella and Acanthamoeba research
Canadian institutionsCentre intégré de santé et de services sociaux de la Montérégie-CentreCentre intégré de santé et de services sociaux de Chaudière-AppalachesCentre Intégré de Santé et de Services Sociaux des LaurentidesUniversité de MontréalSanté MontérégieInstitut de recherche Robert-Sauvé en santé et en sécurité du travail
Fundersnot available
KeywordsLegionellaLegionella pneumophilaMicrobiologyLegionnaires' diseaseOutbreakPathogenStrain (injury)False positive paradoxBiologyBacteriaVirology

Abstract

fetched live from OpenAlex

Legionella has a global distribution, mainly in aquatic and man-made environments. Under the right conditions, this bacterium is a notorious human pathogen responsible for severe pulmonary illnesses. Legionellosis outbreaks are reported around the world, and exposure to water droplet aerosols containing Legionella pneumophila is usually the mechanism of its transmission. Even if L. pneumophila causes most outbreaks, Legionella longbeachae also accounts for some cases. Unlike most other Legionella strains, L. longbeachae is typically found in soil. Given the wide diversity and high concentration of microorganisms found in soil, isolating L. longbeachae by culture can be challenging. Because the chances of successfully isolating the strain are low, it is often not even attempted. This study reports the strategies used to successfully isolate L. longbeachae strain that was responsible of the two occupational legionellosis in Quebec. Fifteen random samples were collected from the soil of the metal recycling plant where the diagnosed workers were employed, covering 1.5% of the accessible surface of the plant. All samples were analyzed with both the quantitative polymerase chain reaction (qPCR) and culture methods. Four qPCR detection systems targeting Legionella spp, L. pneumophila, L. pneumophila serogroup 1, and L. longbeachae were used. Acid, heat, and acid/heat treatments were used for the culture method. For the qPCR method, all samples were positives for Legionella spp but only four were positives for L. longbeachae. For the culture method, only one isolate could be confirmed to be L. longbeachae. However, that strain proves to be the same one that caused the occupational legionellosis. Detecting the presence of L. longbeachae using the qPCR method made it possible to target the right samples to enable the cultivable strain of L. longbeachae to be isolated from the soil of the metal recycling plant. The complementarity of the two methods was established. This paper demonstrated the advantages of selecting the proper sampling and analytical strategies to achieve the isolation of the strain responsible for the infections. It also highlights for the first time in Quebec the potential occupational risks associated with L. longbeachae from soil and should motivate questioning soil exposures when all sources of water contamination have been eliminated from the causal analysis of legionellosis.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.151
GPT teacher head0.402
Teacher spread0.251 · 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 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

Citations1
Published2017
Admission routes2
Has abstractyes

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