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Record W2974248079 · doi:10.1002/ejoc.201901142

Synthesis of LacNAcLe<sup>x</sup>‐ and DimLe<sup>x</sup>‐BSA Conjugates and Binding to Anti‐Polymeric Le<sup>x</sup> mAbs

2019· article· en· W2974248079 on OpenAlexafffund
Ali Nejatie, Sinthuja Jegatheeswaran, France‐Isabelle Auzanneau

Bibliographic record

VenueEuropean Journal of Organic Chemistry · 2019
Typearticle
Languageen
FieldChemistry
TopicCarbohydrate Chemistry and Synthesis
Canadian institutionsUniversity of GuelphSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryGlycoconjugateStereochemistryTetrasaccharideLinkerGlycosideMonomerResidue (chemistry)MoleculeIodideDisaccharidePolysaccharideBiochemistryPolymerOrganic chemistry

Abstract

fetched live from OpenAlex

The chemical synthesis of tetra‐ and pentasaccharide fragments of the tumor‐associated carbohydrate antigen dimeric Lewis X (dimLex) lacking either both or only the non‐reducing end fucosyl residues is described following a 1 + 1 + 1 synthetic strategy. Use of a 6‐chlorohexyl aglycon gave access to hexyl glycoside soluble inhibitors as well as the 6‐aminohexyl glycoside pentasaccharide. The 6‐aminohexyl glycoside pentasaccharide and a dimLex analogue were conjugated to BSA via a squarate linker and the glycoconjugates were shown by MALDI MS to both display an average of 16 oligosaccharides per BSA molecule. These glycoconjugates were used in the attempt to identify the smallest dimLex fragment required to maintain binding to mAbs SH2 and IG5F6, which are known to bind polymeric Lex structures preferentially over the monomeric Lex antigen. Titration studies showed that the non‐reducing end fucosyl residue in dimLex is involved in the recognition of the antigen by both mAbs SH2 and IG5F6.

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 score0.002
Threshold uncertainty score0.005

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.190
Teacher spread0.182 · 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

Citations4
Published2019
Admission routes2
Has abstractyes

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Same venueEuropean Journal of Organic ChemistrySame topicCarbohydrate Chemistry and SynthesisFrench-language works237,207