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Record W2798782349 · doi:10.1101/308825

Fungal Bioaerosols at Five Dairy Farms: A Novel Approach to Describe Workers’ Exposure

2018· preprint· en· W2798782349 on OpenAlexafffundabout
Hamza Mbareche, Marc Veillette, Guillaume J. Bilodeau, Caroline Duchaine

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2018
Typepreprint
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsCanadian Food Inspection AgencyUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
FundersFonds de recherche du Québec – Nature et technologiesInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsIndoor bioaerosolBioaerosolCladosporiumPenicilliumAspergillusEnvironmental healthAspergillus fumigatusBiologyOccupational exposureBiotechnologyToxicologyVeterinary medicineMicrobiologyFood scienceMedicineEcologyGeographyAerosol

Abstract

fetched live from OpenAlex

Abstract Occupational exposure to harmful bioaerosols in industrial environments is a real treat to the workers. In particular, dairy-farm workers are exposed to high levels of fungal bioaerosols on a daily basis. Associating bioaerosol exposure and health problems is challenging and adequate exposure monitoring is a top priority for aerosol scientists. Using only culture-based tools do not express the overall microbial diversity and underestimate the large spectrum of microbes in bioaerosols and therefore the identification of new airborne etiological agents. The aim of this study was to provide an in-depth characterization of fungal exposure at Eastern Canadian dairy farms using qPCR and next-generation sequencing methods. Concentrations of Penicillium/Aspergillus ranged from 4.6 × 10 6 to 9.4 × 10 6 gene copies/m 3 and from 1 × 10 4 gene copies/m 3 to 4.8 × 10 5 gene copies/m 3 for Aspergillus fumigatus . Differences in the diversity profiles of the five dairy farms support the idea that the novel approach identifies a large number of fungal taxa. These variations may be explained by the presence of different and multiple sources of fungal bioaerosols at dairy farms. The presence of a diverse portrait of fungi in air may represent a health risk for workers who are exposed on a daily basis. In some cases, the allergen/infective activity of the fungi may not be known and can increase the risks to workers. The broad spectrum of fungi detected in this study includes many known pathogens and proves that adequate monitoring of bioaerosol exposure is necessary to evaluate and minimize risks. Importance While bioaerosols are a major concern for public health, accurately assessing human exposure is challenging. Highly contaminated environments, such as agricultural facilities, contain a broad diversity of aerosolized fungi that may impact human health. Effective bioaerosol monitoring is increasingly recognized as a strategic approach for achieving occupational exposure description. Workers exposure to diverse fungal communities is certain, as fungi are ubiquitous in the environments and the presence of potential sources increase their presence in the air. Applying new molecular approaches to describe occupational exposure is a necessary work around the traditional culture approaches and the biases they introduce to such studies. The importance of the newly developed approach can help to prevent worker’s health problems.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.583

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.021
GPT teacher head0.215
Teacher spread0.193 · 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

Citations2
Published2018
Admission routes3
Has abstractyes

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