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Record W4233369363 · doi:10.26434/chemrxiv.12151671

Enabling Indium Channels for Mass Cytometry by Using Reinforced Cyclambased Chelating Polylysine

2020· preprint· en· W4233369363 on OpenAlexaff
Laura Grenier, Maryline Beyler, Taunia Closson, Nick Zabinyakov, Alexandre Bouzekri, Yefeng Zhang, Jothir Mayanantham Pichaandi, Mitchell A. Winnik, Peng Liu, Olga Ornatsky, Vladimir Baranov, Raphaël Tripier

Bibliographic record

VenueChemRxiv · 2020
Typepreprint
Languageen
FieldMaterials Science
TopicAnodic Oxide Films and Nanostructures
Canadian institutionsUniversity of TorontoFluidigm (Canada)
FundersUniversité de Bretagne OccidentaleCentre National de la Recherche Scientifique
KeywordsPolylysineMass cytometryChemistryMolecular biologyFlow cytometryChelationBiotinylationPrimary and secondary antibodiesAntibodyNuclear chemistryChromatographyBiochemistryImmunologyBiologyInorganic chemistry

Abstract

fetched live from OpenAlex

A metal containing polymer (MCP) based on a polylysine functionalized by In(III) chelates was synthesized. The chelator is based on a constrained dipicolinate cyclam that forms a highly inert In(III) complex. The MCP was conjugated to anti CD20 antibody using the very strong neutravidin/biotin interaction. Two cell lines, one expressing CD20 the other not, were stained with the modified antibody and analysed by mass cytometry using the In-115 channel. The results showed a specific antigen-antibody recognition and images by mass cytometry imaging could be obtained thanks to In-115 detection. Finally, overtime stability tests of the bioconjugate as well as multiplex experiments using the In-115 channel underline the high potentiel of this new In based MCP. <br><p></p>

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 score0.001
Threshold uncertainty score0.003

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 communication0.0010.000
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 head0.035
GPT teacher head0.280
Teacher spread0.245 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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