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Record W2031899339 · doi:10.1139/cjm-2013-0708

The effects of fungal volatile organic compounds on bone marrow stromal cells

2013· article· en· W2031899339 on OpenAlexvenueno aff
Kirsten L. Hokeness, Jacqueline Kratch, Christina Nadolny, Kristie Aicardi, Christopher W. Reid

Bibliographic record

VenueCanadian Journal of Microbiology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsnot available
FundersNational Institute of General Medical Sciences
KeywordsStromal cellImmune systemBone marrowMembrane fluidityMembraneChemistryCellCell membraneCytotoxic T cellImmunologyBiologyBiochemistryCancer researchIn vitro

Abstract

fetched live from OpenAlex

Evidence has shown that individuals exposed to indoor toxic molds for extended periods of time have elevated risk of developing numerous respiratory illnesses. It is not clear at the cellular level what impact mold exposure has on the immune system. Herein, we show that 2 fungal volatiles (E)-2-octenal and oct-1-en-3-ol have cytotoxic effects on murine bone marrow stromal cells. To further analyze alterations to the cell, we evaluated the impact these volatile organic compounds have on membrane composition and hence fluidity. Both (E)-2-octenal and oct-1-en-3-ol exposure caused a shift to unsaturated fatty acids and lower cholesterol levels in the membrane. This indicates that the volatile organic compounds under investigation increased membrane fluidity. These vast changes to the cell membrane are known to contribute to the breakdown of normal cell function and possibly lead to death. Since bone marrow stromal cells are vital for the appropriate development and activation of immune cells, this study provides the foundation for understanding the mechanism at a cellular level for how mold exposure can lead to immune-related disease conditions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.004
GPT teacher head0.169
Teacher spread0.165 · 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

Citations18
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of MicrobiologySame topicIndoor Air Quality and Microbial ExposureFrench-language works237,207