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Record W2045410409 · doi:10.1021/la201940r

Surface Functionalization of Silica Nanoparticles with Cysteine: A Low-Fouling Zwitterionic Surface

2011· article· en· W2045410409 on OpenAlex
Joshua E. Rosen, Frank Gu

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

VenueLangmuir · 2011
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSurface modificationBovine serum albuminNanoparticleChemistryBiomoleculeLysozymeCysteineFoulingChemical engineeringNanomedicineNanotechnologyCombinatorial chemistryMaterials scienceOrganic chemistryChromatographyMembraneBiochemistry

Abstract

fetched live from OpenAlex

Herein, we report on the functionalization of silica nanoparticles with a small molecule, the amino acid cysteine, in order to create a low-fouling zwitterionic surface for nanomedicine applications. The cysteine functionalization was shown to impart the particles with excellent stability in both salt and single-protein solutions of lysozyme (positively charged) and bovine serum albumin (negatively charged). Bare silica particles precipitated immediately in a lysozyme solution, while cysteine-functionalized particles were stable for 20 h. Furthermore, the particles displayed excellent long-term stability in solutions of human serum showing no aggregation over a period of 14 days. The functionalized particles also possess multiple reactive surface groups for further coupling reactions. We believe that the surface functionalization schemes described in this report represent a versatile and effective method of stabilizing nanoparticle systems in biological media for their use in a variety of therapeutic and diagnostic applications.

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)0.000
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 score0.007
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

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 head0.019
GPT teacher head0.213
Teacher spread0.194 · 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