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Record W2604652079 · doi:10.1128/aem.00258-17

Airborne Pathogens inside Automobiles for Domestic Use: Assessing In-Car Air Decontamination Devices Using Staphylococcus aureus as the Challenge Bacterium

2017· article· en· W2604652079 on OpenAlexaff
Syed A. Sattar, Bahram Zargar, Kathryn E. Wright, Joseph R. Rubino, M. Khalid Ijaz

Bibliographic record

VenueApplied and Environmental Microbiology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHuman decontaminationAerosolizationHEPAStaphylococcus aureusEnvironmental scienceAirborne transmissionBacteriaWaste managementBiologyMedicineInhalationComputer scienceCoronavirus disease 2019 (COVID-19)Engineering

Abstract

fetched live from OpenAlex

ABSTRACT Family cars represent ∼74% of the yearly global output of motorized vehicles. With a life expectancy of ∼8 decades in many countries, the average person spends >100 min daily inside the confined and often shared space of the car, with exposure to a mix of potentially harmful microbes. Can commercial in-car microbial air decontamination devices mitigate the risk? Three such devices (designated devices 1 to 3) with HEPA filters were tested in the modified passenger cabin (3.25 m 3 ) of a four-door sedan housed within a biosafety level 3 containment facility. Staphylococcus aureus (ATCC 6538) was suspended in a soil load to simulate the presence of body fluids and aerosolized into the car's cabin with a 6-jet Collison nebulizer. A muffin fan (80 mm by 80 mm, with an output of 0.17 m 3 /min) circulated the air inside. Plates (150 mm diameter) of Trypticase soy agar (TSA), placed inside a programmable slit-to-agar sampler, were held at 36 ± 1°C for 18 to 24 h and examined for CFU. The input dose of the test bacterium, its rate of biological decay, and the log 10 reductions by the test devices were analyzed. The arbitrarily set performance criterion was the time in hours a device took for a 3-log 10 reduction in the level of airborne challenge bacterium. On average, the level of S. aureus challenge in the air varied between 4.2 log 10 CFU/m 3 and 5.5 log 10 CFU/m 3 , and its rate of biological decay was −0.0213 ± 0.0021 log 10 CFU/m 3 /min. Devices 1 to 3 took 2.3, 1.5, and 9.7 h, respectively, to meet the performance criterion. While the experimental setup was tested using S. aureus as an archetypical airborne pathogen, it can be readily adapted to test other types of pathogens and technologies. IMPORTANCE This study was designed to test the survival of airborne pathogens in the confined and shared space of a family automobile as well as to assess claims of devices marketed for in-car air decontamination. The basic experimental setup and the test protocols reported are versatile enough for work with all major types of airborne human pathogens and for testing a wide variety of air decontamination technologies. This study could also lay the foundation for a standardized test protocol for use by device makers as well as regulators for the registration of such devices.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.018
GPT teacher head0.255
Teacher spread0.237 · 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

Citations16
Published2017
Admission routes1
Has abstractyes

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