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Record W2083797855 · doi:10.1115/1.2932346

On Formation of Uniform Microspheres for Drug Delivery Using a Perforated Silicon Membrane: A Preliminary Study

2008· article· en· W2083797855 on OpenAlexaff
Ki‐Young Song, Urs O. Häfeli, Boris Stoeber, Mu Chiao, Wenjun Zhang

Bibliographic record

VenueJournal of Medical Devices · 2008
Typearticle
Languageen
FieldMaterials Science
TopicMesoporous Materials and Catalysis
Canadian institutionsUniversity of British ColumbiaUniversity of Saskatchewan
Fundersnot available
KeywordsMembrane emulsificationMaterials sciencePLGADispersityDrug deliveryMicrosphereMembraneChemical engineeringNanotechnologyParticle sizeSiliconDosage formPhase (matter)Biomedical engineeringChromatographyNanoparticlePolymer chemistryChemistryOrganic chemistryOptoelectronics

Abstract

fetched live from OpenAlex

A novel method to generate uniform biodegradable microspheres for drug delivery applications has been developed. A liquid phase containing the dissolved microsphere matrix material reaches a continuous phase through a silicon membrane with micron-sized perforations, where it forms microdroplets. The solvent diffuses out of the droplets into the continuous phase leading to the formation of solid microspheres. Experiments with poly (lactic-co-glycolic acid) (PLGA) as the matrix material produced microspheres of which 95% had a diameter between 1 and 2μm, a smaller size and a narrower size distribution than those reported elsewhere using glass or ceramic membranes. Such microspheres will be useful for the intravascular application and pharmaceutical drug delivery with a slow release of the drug at narrowly defined rates. Drug desorption and biodegradation rates induce controllable drug release from functionalized biodegradable microspheres. Those rates are directly proportional to microsphere size. One problem in conventional methods is how to achieve a desired average size and a narrow size distribution of the microspheres. Using a perforated silicon membrane, the size of the microdroplets mainly depends on the pore size and the speed of the continuous phase. By controlling these two parameters, it will be possible to fabricate monodisperse microspheres. The MEMS based approach to microsphere fabrication provided in this paper allows a better control over microsphere dimensions and therefore better control over drug delivery than those reported elsewhere.

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)0.002
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 score0.009
Threshold uncertainty score0.599

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.027
GPT teacher head0.282
Teacher spread0.256 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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