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Record W4313332959 · doi:10.1055/a-2004-5883

A Robust, Gram-Scale and High-Yield Synthesis of MDP Congeners for Activation of the NOD2 Receptor and Vaccine Adjuvantation

2022· article· en· W4313332959 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.

Bibliographic record

VenueSynthesis · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical Synthesis and Analysis
Canadian institutionsLakehead University
FundersPakistan Science Foundation
KeywordsMuramyl dipeptideChemistryNOD2PharmacophorePeptidoglycanImmunogenicityAdjuvantGlycanInnate immune systemImmune systemMoietyReceptorBiochemistryMicrobiologyIn vitroStereochemistryEnzymeBiologyImmunology

Abstract

fetched live from OpenAlex

Abstract The bacterial peptidoglycan (PGN) constituent muramyl dipeptide (MDP) and its congeners possess immuno-adjuvant activity, and find applications in vaccines to potentiate the immune response of antigens. It confers non-specific resistance towards pathogenic infections and defense against tumors. In this work, the parent MDP molecule is re-designed by replacing its carbohydrate moiety with an immunoregulatory xanthine scaffold, while conserving the l-d configuration of the pharmacophore. Alkyl chains are introduced at the C-terminus of d-isoglutamine to help the molecules access cytoplasmic NOD2 receptors and activate the innate immune system. Lipophilic MDP congeners are thus obtained by adopting a direct or indirect convergent synthetic route with overall yields of >50%. We found that an indirect approach can reliably be implemented on gram scale, thereby unlocking access to substantial amounts of pathogen-associated molecular patterns for in vivo studies, which will accelerate the development of NOD2 immuno-adjuvants against viral and bacterial infections.

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)0.001
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 score0.022
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.010
GPT teacher head0.206
Teacher spread0.196 · 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