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Record W2888657650 · doi:10.3791/58111

Detection of Viruses from Bioaerosols Using Anion Exchange Resin

2018· article· en· W2888657650 on OpenAlexaff
Joshua W. Schaeffer, Jeffrey C. Chandler, Margaret Davidson, Sheryl Magzamen, A. Pérez-Méndez, Stephen J. Reynolds, Lawrence Goodridge, John Volckens, Alan B. Franklin, Susan A. Shriner, Bledar Bisha

Bibliographic record

VenueJournal of Visualized Experiments · 2018
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsMcGill University
FundersNational Institute for Occupational Safety and HealthCenters for Disease Control and Prevention
KeywordsBioaerosolIndoor bioaerosolIon-exchange resinChromatographyEnvironmental scienceChemistryMaterials scienceEnvironmental chemistryAerosolOrganic chemistry

Abstract

fetched live from OpenAlex

This protocol demonstrates a customized bioaerosol sampling method for viruses. In this system, anion exchange resin is coupled with liquid impingement-based air sampling devices for efficacious concentration of negatively-charged viruses from bioaerosols. Thus, the resin serves as an additional concentration step in the bioaerosol sampling workflow. Nucleic acid extraction of the viral particles is then performed directly from the anion exchange resin, with the resulting sample suitable for molecular analyses. Further, this protocol describes a custom-built bioaerosol chamber capable of generating virus-laden bioaerosols under a variety of environmental conditions and allowing for continuous monitoring of environmental variables such as temperature, humidity, wind speed, and aerosol mass concentration. The main advantage of using this protocol is increased sensitivity of viral detection, as assessed via direct comparison to an unmodified conventional liquid impinger. Other advantages include the potential to concentrate diverse negatively-charged viruses, the low cost of anion exchange resin (~$0.14 per sample), and ease of use. Disadvantages include the inability of this protocol to assess infectivity of resin-adsorbed viral particles, and potentially the need for the optimization of the liquid sampling buffer used within the impinger.

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)0.000
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.084
GPT teacher head0.461
Teacher spread0.378 · 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
Published2018
Admission routes1
Has abstractyes

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