MétaCan
Menu
Back to cohort
Record W4405161825 · doi:10.1021/acsomega.4c06141

An Efficient and Accessible Hectogram-Scale Synthesis for the Selective O-GlcNAcase Inhibitor Thiamet-G

2024· article· en· W4405161825 on OpenAlexafffund
Viktor Holicek, Matthew C. Deen, Sandeep Bhosale, Roger A. Ashmus, David J. Vocadlo

Bibliographic record

VenueACS Omega · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsWeston Brain Institute
KeywordsScale (ratio)Environmental sciencePhysics

Abstract

fetched live from OpenAlex

Altered levels of intracellular protein glycosylation with O-linked β-N-acetylglucosamine (O-GlcNAc) have emerged as being involved in various cancers and neurodegenerative diseases. OGA inhibitors have proven critically useful as tools to help understand the roles of O-GlcNAc, yet accessing large quantities of inhibitors necessary for many animal studies remains a challenge. Herein is described a scalable method to produce Thiamet-G, a potent, selective, and widely used brain-permeable OGA inhibitor. This synthetic route begins with inexpensive precursor, requires no column chromatography, employs simple nontoxic reagents, and in a single campaign can furnish several hundred grams of crystalline Thiamet-G in an overall yield of 44% over six steps.

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 score0.096
Threshold uncertainty score0.305

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 head0.013
GPT teacher head0.311
Teacher spread0.298 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueACS OmegaSame topicGlycosylation and Glycoproteins ResearchFrench-language works237,207