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Record W2921141222 · doi:10.1289/isee.2014.s-045

Characterization of Microbial Communities on Caps in Controlled Human Exposures

2014· article· en· W2921141222 on OpenAlexaff
Diane R. Gold, Bruce Urch, Erica Sodergren, George M. Weinstock, Mary Speck, Yanjiao Zhou, Brent A. Coull, Koutrakis Petros, Tania Kotlov, Ling Liu, James Scott, Robert D. Brook, Frances Silverman, Joanne E. Sordillo

Bibliographic record

VenueISEE Conference Abstracts · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsHealth CanadaSt. Michael's HospitalPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsBiologyProteobacteriaActinobacteriaMetagenomicsPhylumBacteroidetesRelative species abundanceAscomycotaBacterial phylaAlternariaBotanyAbundance (ecology)Microbiology16S ribosomal RNAEcologyBacteria

Abstract

fetched live from OpenAlex

Background: While a few small studies suggest that endotoxin from gram-negative bacteria on ambient pollution particles may increase systemic inflammation, the contribution of microbes on pollution particles to their inflammatory and cardiovascular effects is poorly understood. Methods/ Results: We conducted a blinded, randomized, cross-over trial of controlled human exposures to concentrated ambient particles (CAPs). Fifty-five healthy adult volunteers were exposed for 130 min to fine, coarse, or ultrafine CAPs; HEPA-filtered air or medical air with = 2-week washout between exposures. CAPs were sampled immediately prior to testing (calibration samples), and during each exposure. We conducted a pilot study to characterize the bacterial and fungal communities on CAPs at the phylum and genus level with the ultimate goal of assessing their health effects. Metagenomic DNA was extracted from CAPs on nine pre-exposure calibration filters, and 16S, 18S, and ITS sequencing was performed. Scaling to 2,000 reads, bacterial and fungal relative abundance was characterized at the phylum and genus level. The five most abundant bacterial phyla were Proteobacteria (59%) (i.e, gram negatives, which varied by CAP sample with a relative abundance ranging from 50% to 71% with 16 distinct genera identified), Actinobacteria (15%), Firmicules (10%), Bacteroidetes (8%), and Cyanobacteria/Chloroplast (5%). For fungi, by ITS sequencing the most abundant phyla were Basidiomycota (overall relative abundance: 83%; range: 73-95%), followed by Ascomycota (16%), Polyporales, Glomeromycota, and Zygomycota. Twenty-three fungal genera were identified, including Alternaria and Penicillium in low abundance. Further classification will be performed. Conclusion: Metagenomic characterization of the variability of bacterial and fungal communities on CAPs opens up opportunities to assess the contribution of microbes on ambient pollution particles to their inflammatory and physiologic effects.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.049
GPT teacher head0.289
Teacher spread0.240 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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