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Record W2096301773 · doi:10.1021/jm101594s

Selective Depletion of Neuropathy-Related Antibodies from Human Serum by Monolithic Affinity Columns Containing Ganglioside Mimics

2011· article· en· W2096301773 on OpenAlexaff
Kishore K. R. Tetala, Astrid P. Heikema, Aliaksei V. Pukin, C.A.G.M. Weijers, Anne P. Tio‐Gillen, Michel Gilbert, Hubert P. Endtz, Alex van Belkum, Han Zuilhof, Gerben M. Visser, Bart C. Jacobs, Teris A. van Beek

Bibliographic record

VenueJournal of Medicinal Chemistry · 2011
Typearticle
Languageen
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsNational Research Council CanadaInstitute for Biological Sciences
Fundersnot available
KeywordsGangliosideChemistryAntibodyMonoclonal antibodyChromatographyMolecular biologyBiochemistryImmunologyBiology

Abstract

fetched live from OpenAlex

Monolithic columns containing ganglioside GM2 and GM3 mimics were prepared for selective removal of serum anti-ganglioside antibodies from patients with acute and chronic immune-mediated neuropathies. ELISA results demonstrated that anti-GM2 IgM antibodies in human sera and a mouse monoclonal anti-GM2 antibody were specifically and selectively adsorbed by monolithic GM2 mimic columns and not by blank monolithic columns or monolithic GM3 mimic columns. In control studies, serum antibodies against the ganglioside GQ1b from another neuropathy patient were not depleted by monolithic GM2 mimic columns. Fluorescence microscopy with FITC-conjugated anti-human immunoglobulin antibodies showed that the immobilized ganglioside mimics were evenly distributed along the column. The columns were able to capture ∼95% of the anti-GM2 antibodies of patients after only 2 min of incubation. A monolithic column of 4.4 μL can deplete 28.2 μL of undiluted serum. These columns are potential diagnostic and therapeutic tools for neuropathies related to anti-ganglioside antibodies.

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)0.001
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 score0.115
Threshold uncertainty score0.701

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.019
GPT teacher head0.247
Teacher spread0.229 · 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

Citations2
Published2011
Admission routes1
Has abstractyes

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