Use of <i>Moraxella catarrhalis</i> Lipooligosaccharide Mutants To Identify Specific Oligosaccharide Epitopes Recognized by Human Serum Antibodies
Bibliographic record
Abstract
Moraxella catarrhalis is a causative agent of otitis media in children and lower respiratory tract infections in adults suffering from chronic obstructive pulmonary disease (COPD). This strict human pathogen continues to be a significant cause of disease in this broad spectrum of patients because there is no available vaccine. Although numerous putative vaccine antigens have been described, little is known about the human immune response to M. catarrhalis infection in vivo. Human serum antibodies are directed at a number of surface proteins, and lipooligosaccharides (LOS) and detoxified LOS may be an effective immunogen in mice. In this study, we used a specific LOS-based enzyme-linked immunosorbent assay (ELISA), containing the three major M. catarrhalis serotypes together with a complete series of truncated LOS mutants, to detect the development of new antibodies to specific regions of the oligosaccharide molecule. We compared serum samples from COPD patients who had recently cleared an M. catarrhalis infection to serum samples collected prior to their infection. Variability in the antibody response to LOS was observed, as some patients developed serotype-specific antibodies, others developed antibodies to the LOS of each serotype, others developed broadly cross-reactive antibodies, and some did not develop new antibodies. These newly developed human antibodies are directed at both side chains and core structures in the LOS molecule. This LOS-based ELISA can be used to dissect the human antibody response to both internal and external carbohydrate epitopes, thus providing a better understanding of the humoral immune response to M. catarrhalis LOS epitopes developed during natural infection.
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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) | 0.000 | 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".