Solid phase immunoadsorption for therapeutic and analytical studies on neuropathy-associated anti-GM1 antibodies
Bibliographic record
Abstract
Autoimmune neuropathies including Guillain-Barré syndrome are frequently associated with anti-GM1 ganglioside antibodies. These are believed to play a pathogenic role and their clearance from the circulation would be predicted to produce therapeutic benefit. This study examines the conditions required for effective immunoadsorption of anti-GM1 antibodies using glycan-conjugated Sepharose as a matrix. In solution inhibition studies using a range of GM1-like saccharides in conjunction with mouse and human anti-GM1 antibodies, the whole GM1 pentasaccharide beta-Gal-(1-3)-beta-GalNAc-(1-4)-[alpha-Neu5Ac-(2-3)]-beta-Gal-(1-4)-beta-Glc was the favored ligand for maximal inhibiton of antibody-GM1 interactions in comparison with monosaccharides, Gal-(1-3)-beta-GalNAc-betaOMe, and synthetic GM1 mimetics. Immunoadsorption studies comparing binding of mouse monoclonal anti-GM1 antibodies to GM1-Sepharose and beta-Gal-(1-3)-beta-GalNAc-Sepharose confirmed the preference seen in solution inhibition studies. GM1-Sepharose columns were then used to adsorb anti-GM1 immunoglobulin G and immunoglobulin M antibodies from human neuropathy sera. Anti-GM1 antibodies subsequently eluted from the columns often showed a striking monoclonal or oligoclonal pattern, indicating that the immune response to GM1 is restricted to a limited number of B-cell clones, even in the absence of a detectable serum paraprotein. These data support the view that immunoadsorption plasmapheresis could potentially be developed for the acute depletion of serum anti-GM1 antibodies in patients with neuropathic disease, and also provide purified human anti-GM1 antibodies for analytical studies.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".