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Record W2315560407 · doi:10.1021/la201013v

Synthesis and Mass Cytometric Analysis of Lanthanide-Encoded Polyelectrolyte Microgels

2011· article· en· W2315560407 on OpenAlexaff
Wanjuan Lin, Xiaomei Ma, Jieshu Qian, Ahmed I. Abdelrahman, Adrienne Halupa, Vladimir Baranov, Andrij Pich, Mitchell A. Winnik

Bibliographic record

VenueLangmuir · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCopolymerPolyelectrolyteChemistryMethacrylateMethacrylic acidEthylene glycolLanthanideInductively coupled plasma mass spectrometryPolymer chemistryNanoparticleNuclear chemistryChemical engineeringIonMass spectrometryAnalytical Chemistry (journal)Materials sciencePolymerNanotechnologyChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

This article describes the synthesis and characterization of two series of functional polyelectrolyte copolymer microgels intended for bioassays based upon mass cytometry, a technique that detects metals by inductively coupled plasma mass spectrometry (ICP-MS). The microgels were loaded with Eu(III) ions, which were then converted in situ to EuF(3) nanoparticles (NPs). Both types of microgels are based upon copolymers of N-isopropylacrylamide (NIPAm) and methacrylic acid (MAA), poly(NIPAm/VCL/MAA) (VCL = N-vinylcaprolactam, V series), and poly(NIPAm/MAA/PEGMA) (PEGMA = poly(ethylene glycol)methacrylate, PG series). Very specific conditions (full neutralization of the MAA groups) were required to confine the EuF(3) NPs to the core of the microgels. We used mass cytometry to measure the number and the particle-to-particle variation of Eu ions per microgel. By controlling the amount of EuCl(3) added to the neutralized microgels. we could vary the atomic content of individual microgels from ca. 10(6) to 10(7) Eu atoms, either in the form of Eu(3+) ions or EuF(3) NPs. Leaching profiles of Eu ions from the hybrid microgels were measured by traditional ICP-MS.

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)0.000
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 score0.004
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.232
Teacher spread0.213 · 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

Citations21
Published2011
Admission routes1
Has abstractyes

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