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Record W2111467671 · doi:10.1155/2013/136859

Biodistribution of Amikacin Solid Lipid Nanoparticles after Pulmonary Delivery

2013· article· en· W2111467671 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

VenueBioMed Research International · 2013
Typearticle
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsUniversity of Alberta
FundersIsfahan University of Medical Sciences
KeywordsBiodistributionAmikacinSolid lipid nanoparticlePharmacologyDrug deliveryMedicineDrugLungDosingChemistryAntibioticsInternal medicineIn vitroBiochemistry

Abstract

fetched live from OpenAlex

The main purpose of the present work was studying the biodistribution of amikacin solid lipid nanoparticles (SLNs) after pulmonary delivery to increase its concentration in the lungs for treatment of cystic fibrosis lung infections and also providing a new method for clinical application of amikacin. To achieve this aim, (99m)Tc labelled amikacin was loaded in cholesterol SLNs and after in vitro optimization, the desired SLNs and free drug were administered through pulmonary and i.v. routes to male rats and qualitative and biodistribution studies were done. Results showed that pulmonary delivery of SLNs of amikacin by microsprayer caused higher drug concentration in lungs than kidneys while i.v. administration of free drug caused reverse conditions. It seems that pulmonary delivery of SLNs may improve patients' compliance due to reduction of drug side effects in kidneys and elongation of drug dosing intervals due to the sustained drug release from SLNs.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.242
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.047
GPT teacher head0.360
Teacher spread0.313 · 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