MétaCan
Menu
Back to cohort
Record W3123858093 · doi:10.1186/s12931-021-01700-4

Effects of elevated CO2 levels on lung immune response to organic dust and lipopolysaccharide

2021· article· en· W3123858093 on OpenAlexafffund
David Schneberger, Upkardeep Pandher, Brooke Thompson, Shelley Kirychuk

Bibliographic record

VenueRespiratory Research · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsUniversity of Saskatchewan
FundersUniversity of Saskatchewan
KeywordsLipopolysaccharideImmune systemInnate immune systemChemistryRespiratory systemInflammatory responseLungImmunologyInflammationAnimal scienceInternal medicineBiologyMedicine

Abstract

fetched live from OpenAlex

Abstract Workplaces with elevated organic dust levels such as animal feed barns also commonly have elevated levels of gasses, such as CO 2 . Workers exposed to such complex environments often experience respiratory effects that may be due to a combination of respirable factors. We examined the effects of CO 2 on lung innate immune responses in mice co-exposed to the inflammatory agents lipopolysaccharide (LPS) and organic dust. We evaluated CO 2 levels at the building recommended limit (1000 ppm) as well as the exposure limit (5000 ppm). Mice were nasally instilled with dust extracts or LPS and immediately put into chambers with a constant flow of room air (avg. 430 ppm CO 2 ), 1000 ppm, or 5000 ppm CO 2 enriched air. Results reveal that organic dust exposures tended to show decreased inflammatory responses with 1000 ppm CO 2 and increased responses at 5000 ppm CO 2 . Conversely, LPS with addition of CO 2 as low as 1000 ppm tended to inhibit several inflammatory markers. In most cases saline treated animals showed few changes with CO 2 exposure, though some changes in mRNA levels were present. This shows that CO 2 as low as 1000 ppm CO 2 was capable of altering innate immune responses to both LPS and organic dust extracts, but each response was altered in a different fashion.

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)0.004
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.305
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.094
GPT teacher head0.397
Teacher spread0.303 · 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.

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

Citations8
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueRespiratory ResearchSame topicAir Quality and Health ImpactsFrench-language works237,207