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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 OpenAlexaff
Jaleh Varshosaz, Solmaz Ghaffari, Seyedeh Fatemeh Mirshojaei, Abbas Jafarian‐Dehkordi, Fatemeh Atyabi, Farzad Kobarfard, S H Azarmi

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.

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 score0.001
Threshold uncertainty score0.002

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 head0.047
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

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

Citations108
Published2013
Admission routes1
Has abstractyes

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