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Record W2225675026 · doi:10.1155/2008/202615

Quality of Bronchial Biopsies for Morphology Study and Cell Sampling: A Comparison of Asthmatic and Healthy Subjects

2008· article· en· W2225675026 on OpenAlexaff
Isabelle Labonté, Michel Laviolette, Ron Olivenstein, Jamila Chakir, Louis‐Philippe Boulet, Qutayba Hamid

Bibliographic record

VenueCanadian Respiratory Journal · 2008
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsMcGill UniversityChristie (Canada)
Fundersnot available
KeywordsMedicineBiopsyAsthmaBasement membranePathologySampling (signal processing)EpitheliumInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Bronchial biopsies are widely used for histopathological, primary cell culture and genetic studies, but very few reports have evaluated their quality. OBJECTIVES AND METHODS: The present project evaluated the quality (using a scoring system) and the general morphology of a pool of six bronchial biopsy specimens taken from three different sampling sites (the lobar, segmental and subsegmental carinae) in 27 subjects (13 asthmatic subjects and 14 healthy controls). The present study also assessed quantitative measurements of structural changes related to asthma. RESULTS: In total, 94.4% of the biopsy attempts had enough tissue to be processed. From these, 61.7% were scored with a good to excellent quality, while 76.5% presented smooth muscle bundles and 40.5% had an intact epithelium wall. The data also confirmed the structural changes observed in asthma, such as increased apparent thickening of the basement membrane, reduced amounts of smooth muscle for healthy controls and decreased percentage of intact epithelium for asthmatic subjects. CONCLUSION: A pool of six bronchial biopsy specimens can provide tissue of excellent quality in both asthmatic and healthy subjects and, consequently, a valuable sample for morphological analysis of mucosal structures.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.103
GPT teacher head0.369
Teacher spread0.266 · 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.

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

Citations11
Published2008
Admission routes1
Has abstractyes

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