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Record W2041686893 · doi:10.1177/0883911506073639

Pulmonary Anti-inflammatory Effects of Chitosan Microparticles Containing Betamethasone

2006· article· en· W2041686893 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Bioactive and Compatible Polymers · 2006
Typearticle
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsBetamethasoneBronchoalveolar lavageMyeloperoxidaseChemistryInhalationLactate dehydrogenaseInflammationLungPharmacologyAnti-inflammatoryChitosanDrug deliveryInfiltration (HVAC)ImmunologyBiochemistryEnzymeMedicineInternal medicineAnesthesia

Abstract

fetched live from OpenAlex

Chitosan microparticles (CMs) are of potential interest for controlled delivery of therapeutic agents to cells and tissues, especially to mucosal-epithelial surfaces in the body. CM incorporation efficiency and release kinetics for betamethasone (B), an epimeric synthetic glucocorticoid, were investigated. Evidence for mild but significant inflammatory reactions in rat lung exposed to high CM concentrations was observed. Inflammation in the rat lung was significantly decreased by inhalation of B-loaded CMs (BCMs). Decreases in bronchoalveolar lavage fluid protein, content of polymorphonuclear neutrophils, lactate dehydrogenase (LDH) activity, lung tissue myeloperoxidase (MPO) activity, and leukocyte infiltration were observed. For all biochemical parameters tested, CMs loaded with 1.0-1.2mg/kg B decrease the inflammation by 1.63±0.14 fold, to near air-inhalation control levels. Thus, the drug was efficiently delivered and active in the pulmonary tissues by this technique.

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.

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 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 score0.068
Threshold uncertainty score0.355

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.006
GPT teacher head0.228
Teacher spread0.222 · 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