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Record W2884237425 · doi:10.31031/igrwh.2018.01.000524

Humanized GHR106 Monoclonal Antibody is a Biosimilar GnRH Antagonist

2018· article· en· W2884237425 on OpenAlexaff
Gregory Lee

Bibliographic record

VenueInvestigations in Gynecology Research & Womens Health (IGRWH) · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsHealth Canada
Fundersnot available
KeywordsMonoclonal antibodyBiosimilarAntibodyAntagonistReceptorHumanized antibodyChemistryIsotypeImmunohistochemistryMolecular biologyPeptidePharmacologyCancer researchBiologyInternal medicineImmunologyMedicineBiochemistry

Abstract

fetched live from OpenAlex

GHR106 is a monoclonal antibody generated against human GnRH receptor. The humanized forms of GHR106 exhibit almost identical biological properties to those of decapeptide GnRH antagonists such as Antide and Cetrorelix. The biosimilarity between these two GnRH receptor ligands was based on the studies of (1) binding affinity and specificity as well as immunohistochemical staining, (2) induced apoptosis to cancer cells and (3) effects of ligand- receptor bindings on gene regulations of cancer cells. Furthermore, the half-life of GHR106 antibody can be reduced from days to hours by means of antibody fragmentations to (Fab’)2 or Fab. The results of these biosimilar studies suggest that humanized GHR106 with IgG4 isotype can be utilized clinically with biosimilar functions as antibody-based GnRH antagonist except, with higher molecular size and longer half-life as compared to those of peptide GnRH antagonists (days vs. hours).

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 score0.004
Threshold uncertainty score0.013

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)0.0040.001

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 head0.054
GPT teacher head0.428
Teacher spread0.374 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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