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Record W2336599563 · doi:10.1002/slct.201600230

Synthesis of a TLR4 Agonist‐Carbohydrate Antigen Conjugate As A Self‐Adjuvanting Cancer Vaccine

2016· article· en· W2336599563 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemistrySelect · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsNOSM UniversityLakehead University
FundersLakehead University
KeywordsImmunogenicityAntigenChemistryDisaccharideEpitopeLinkerBiochemistryImmunostimulantLipid ACarbohydrateConjugate vaccineConjugateAntigenicityImmune systemBiologyImmunologyLipopolysaccharide

Abstract

fetched live from OpenAlex

Abstract Tumour‐associated carbohydrate antigens (TACAs) are promising targets for therapeutic cancer vaccination efforts. However, an inherent limitation of this approach is the poor immunogenicity of carbohydrate epitopes. In an effort to overcome this problem, a self‐adjuvanting TACA has been targeted and synthesized herein, in which a Toll‐like receptor 4 activating lipid A mimic is employed as an immunostimulant and covalently linked to a broadly expressed TACA, the Thomsen‐Freidenreich (TF) antigen. Individual components were first prepared, including the lipid A mimic, the Galβ(1‐3)GalNAc disaccharide building block, and the tetraethylene glycol‐derived linker. The linker was then coupled with the TF disaccharide, and then with the lipid A mimic, both under HBTU‐mediated peptide coupling condition, to provide the conjugated precursor. Global debenzylation via catalytic hydrogenation afforded the designed self‐adjuvanting TF antigen in overall good yield.

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 score0.013
Threshold uncertainty score0.631

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 head0.008
GPT teacher head0.273
Teacher spread0.265 · 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