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Record W2020008986 · doi:10.1517/13543776.12.8.1215

Gangliosides: therapeutic agents or therapeutic targets?

2002· article· en· W2020008986 on OpenAlexaff
H. Uri Saragovi, Martin Gagnon

Bibliographic record

VenueExpert Opinion on Therapeutic Patents · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsNeurodegenerationDrugComputational biologyGlycolipidDrug discoveryBiologyNeurosciencePharmacologyMedicineImmunologyBioinformaticsDisease

Abstract

fetched live from OpenAlex

A wide array of pathologies make gangliosides interesting molecules either as therapeutic targets or as possible therapeutic agents. This review covers recent patents and ongoing research focusing on the use of gangliosides as drugs and drug targets for indications such as cancer, neurodegeneration, viral and bacterial infections and immunosuppression. A major deficit of gangliosides as therapeutics is that they are ubiquitous cell membrane components whose cognate functions remain puzzling. Understanding the cognate biology of gangliosides and the nature of the molecules that interact with gangliosides will undoubtedly unlock novel approaches for making use of these interesting glycolipids for therapeutic intervention.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.861
Threshold uncertainty score1.000

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.111
GPT teacher head0.348
Teacher spread0.238 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations14
Published2002
Admission routes1
Has abstractyes

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