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Record W2306759775

A simple and efficient method for radiolabeling of preformed liposomes.

2000· article· en· W2306759775 on OpenAlexaff
M.R. Suresh, Cao Y

Bibliographic record

VenuePubMed · 2000
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLiposomeChemistryBiodistributionGlutathioneChloroformChromatographyIminodiacetic acidSpleenExtraction (chemistry)Technetium-99mRadiochemistryBiochemistryNuclear medicineScintigraphyOrganic chemistryChelationImmunologyMedicineIn vitro
DOInot available

Abstract

fetched live from OpenAlex

A simple and efficient method for radiolabeling preformed liposomes was developed using hepatobiliary imaging agent (99m)Tc-diisopropyl iminodiacetic acid ((99m)Tc-DISIDA). Chloroform extraction of (99m)Tc-DISIDA from aqueous solutions results in 80% radioactivity in the organic phase due to its lipophilic properties. However, with the presence of reduced glutathione (gamma-Glu-Cys-Gly), chloroform extraction results in only 30% of label in the organic phase because the (99m)Tc-DISIDA complex undergoes reduction decomposition to more hydrophilic species by reaction with glutathione. The incorporation efficiency of the (99m)Tc-DISIDA into the liposomes containing reduced glutathione was greater than 90%. The labeled liposomes were stable up to 24 h in saline and 90% FBS after preparation. Biodistribution studies in mice showed that (99m)Tc labeled liposomes accumulated in liver and spleen at 24 h postinjection, unlike (99m)Tc-DISIDA. Compared to hexamethylpropyleneamine oxime (HMPAO), the (99m)Tc-DISIDA compound is much cheaper and has a longer shelf life when used for liposome labeling. The labeling technique described here could be used for monitoring pharmacokinetic and pharmacodynamic changes of liposomes, and tumor or infection imaging when coupled with targeting antibodies.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.016
GPT teacher head0.245
Teacher spread0.229 · 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 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

Citations10
Published2000
Admission routes1
Has abstractyes

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