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Record W2328042137 · doi:10.1021/bm201011t

Curious Results with Palladium- and Platinum-Carrying Polymers in Mass Cytometry Bioassays and an Unexpected Application as a Dead Cell Stain

2011· article· en· W2328042137 on OpenAlexafffund
Daniel Majonis, Olga Ornatsky, Robert Kinach, Mitchell A. Winnik

Bibliographic record

VenueBiomacromolecules · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryLanthanideDOTAPalladiumPlatinumPolymerMass cytometryPolymer chemistryConjugated systemMetal ions in aqueous solutionChelationNuclear chemistryMetalOrganic chemistryIonBiochemistry

Abstract

fetched live from OpenAlex

We describe the synthesis of metal-chelating polymers (MCPs) with four different pendant polyaminocarboxylate ligands (EDTA, DTPA, TTHA, DOTA) and an orthogonal end-group, either a fluorescein molecule or a bismaleimide linker for antibody attachment. Polymer characterization by a combination of (1)H NMR, UV/vis absorption measurements, and thermal gravimetric analysis (TGA) indicated that each chain of the fluorescein-terminated polymers contained one dye molecule. These polymer samples were loaded with three different types of lanthanide ions as well as palladium and platinum ions. The numbers of metal atoms per chain were determined by a combination of UV/vis and conventional ICP-MS measurements. The experiments with lanthanide ions demonstrated that a net anionic charge on the polymer is important for water solubility. These experiments also showed that at least one type of lanthanide ion (La(3+)) is capable of forming a bimetallic complex with pendant DTPA groups. Conditions were developed for loading these polymers with palladium and platinum ions. While these polymers could be conjugated to antibodies, the presence of Pd or Pt ions in the polymer interfered with the ability of the antibody to recognize its antigen. For example, a goat anti-mouse (secondary) antibody labeled with polymers that contain Pd or Pt no longer recognized a primary antibody in a sandwich assay. In mass cytometry assays, these Pd- or Pt-containing MCPs were very effective in recognizing dead cells and provide a new and robust assay for distinguishing live cells from dead cells.

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 score0.013
Threshold uncertainty score0.814

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)0.0000.000

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 head0.009
GPT teacher head0.253
Teacher spread0.244 · 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

Citations51
Published2011
Admission routes2
Has abstractyes

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