Serum-equivalency comparison, detection, and quantification of Group B <i>Streptococcus</i> anti-capsular polysaccharide antibodies from dried blood spots
Bibliographic record
Abstract
A standardized multiplex immunoassay (MIA) to quantify group B Streptococcus (GBS) anti-capsular polysaccharide (CPS) IgG serum concentrations was adopted by the Group B Streptococcal Assay Standardization (GASTON) consortium as a standardized serological assay with the most immediate applications for facilitating the licensure of GBS vaccines. However, dried blood spot (DBS) samples offer advantages for immunological studies, including cost-effectiveness, ease of transport, and storage. To determine suitability of DBS as an alternative sample matrix to serum in MIA, a contrived GBS seropositive panel, including matched DBS and serum samples, was prepared using established methods. The calculated geometric mean titers of GBS anti-CPS IgG values by individual serotype were compared using a paired t-test to establish serum equivalency. Geometric mean values for the matched panel were assessed via Deming regression for precision, accuracy, and concordance correlation coefficient (CCC). The initial acceptance criterion was set at 0.95 for CCC. Two additional criteria based on confidence intervals of CCC, slope, and intercept were used to determine the necessity of a serotype-specific conversion factor. The paired t-test p-values were >.05 for serum equivalency. For sample matrix concordance, CCC values were >0.95 and met correlation criteria for all serotypes. Conversion factors were applied to four serotypes (II, III, IV, and V) that did not meet the criteria for slope, intercept, or both. This demonstration of equivalency between DBS and serum supports the hypothesis that DBS is a suitable testing matrix from which to elucidate anti-CPS IgG concentrations in seroepidemiological and vaccine evaluation 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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".