Selective Depletion of Neuropathy-Related Antibodies from Human Serum by Monolithic Affinity Columns Containing Ganglioside Mimics
Bibliographic record
Abstract
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.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".