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Record W1797555978 · doi:10.3109/02652048.2015.1081416

SN-38 active loading in poly(lactic-co-glycolic acid) nanoparticles and assessment of their anticancer properties on COLO-205 human colon adenocarcinoma cells

2015· article· en· W1797555978 on OpenAlexafffund
Sherief Essa, Jamal Daoud, Michel Lafleur, Sylvain Martel, Maryam Tabrizian

Bibliographic record

VenueJournal of Microencapsulation · 2015
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsPolytechnique MontréalUniversité de MontréalMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaOvarian Cancer Action
KeywordsGlycolic acidCytotoxicityZeta potentialSolubilityLactic acidNanoparticleSolventMaterials scienceApoptosisLactoneDrug deliveryBiophysicsPLGACellCell cultureCell growthNuclear chemistryChemistryIn vitroNanotechnologyStereochemistryOrganic chemistryBiochemistryBiology

Abstract

fetched live from OpenAlex

SN-38 is a highly effective drug against many cancers. The development of an optimal delivery system for SN-38 is extremely challenging due to its low solubility and labile lactone ring. Herein, SN-38 encapsulated in poly(D,L-lactide-co-glycolide) nanoparticles (NPs) is introduced to enhance its solubility, stability and cellular uptake. SN-38-loaded NPs prepared by spontaneous emulsification solvent diffusion (SESD) method had an average diameter of 310 nm, a zeta potential of -9.69 mV and a loading efficiency of 71%. They were able to protect the active lactone ring of SN-38 against inactivation under physiological condition. A colorectal adenocarcinoma cell line (COLO-205) was used to assess the NPs effects on cytotoxicity and cellular uptake. Result showed a significant decreased cell proliferation and cell apoptosis. These results suggest that these SN-38-loaded NPs can be an effective delivery system for the treatment of colon cancer and potentially for other types of cancers.

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 score0.002
Threshold uncertainty score0.004

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)0.0000.000

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 head0.045
GPT teacher head0.297
Teacher spread0.252 · 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

Citations13
Published2015
Admission routes2
Has abstractyes

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