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Record W3097406364 · doi:10.1152/ajplung.00362.2020

Microvesicles in bronchoalveolar lavage as a potential biomarker of COPD

2020· article· en· W3097406364 on OpenAlexaff
Erica Bazzan, Claudia Maria Radu, Mariaenrica Tinè, Tommaso Neri, Davide Biondini, Umberto Semenzato, Alvise Casara, Elisabetta Balestro, Paolo Simioni, Alessandro Celi, Manuel G. Cosío, Marina Saetta

Bibliographic record

VenueAmerican Journal of Physiology-Lung Cellular and Molecular Physiology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicExtracellular vesicles in disease
Canadian institutionsMcGill UniversityChristie (Canada)
FundersUniversità degli Studi di Padova
KeywordsBronchoalveolar lavageMicrovesiclesBiomarkerCOPDMedicineImmunologyPathologyLungInternal medicineChemistrymicroRNA

Abstract

fetched live from OpenAlex

Microvesicles (MVs) released from almost all cells are recognized as cell communication tools. MVs have been investigated in several inflammatory diseases but poorly in biological fluids like bronchoalveolar lavage (BAL) of smokers. The purpose of this study was to investigate the presence and source of MVs in BAL of smokers with and without chronic obstructive pulmonary disease (COPD) compared with nonsmoking controls. Using flow cytometry in BAL, we detected endothelial and alveolar macrophage (AM)-derived MVs and found a higher number of AM-MVs in the BAL of smokers with COPD than in smokers without COPD and nonsmokers, which correlated with the pack-years ( r = 0.46; P = 0.05) and with the degree of airway obstruction measured by the forced expiratory volume in 1 s percent predicted ( r = −0.56; P = 0.01). Endothelial and alveolar macrophage-derived MVs are present and measurable in human BAL fluid. In response to smoking and to the development of COPD, inflammatory signals in AM-derived MVs can be quantified, and their numbers are related to the pack-years and the decrease in lung function. These results open the opportunity for future investigation of these microvesicles as biomarkers and possible mechanistic guides in COPD.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.227
Teacher spread0.223 · 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

Citations26
Published2020
Admission routes1
Has abstractyes

Explore more

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