Multiplex Assay Detection of Immunoglobulin G Antibodies That Recognize<i>Giardia intestinalis</i>and<i>Cryptosporidium parvum</i>Antigens
Bibliographic record
Abstract
Giardiasis and cryptosporidiosis are common enteric parasitic diseases that have similar routes of transmission. In this work, we have identified epitopes within the Giardia variant-specific surface protein (VSP) sequences that are recognized by IgG antibodies from 13 of 14 (93%) sera from patients with stool-confirmed giardiasis. The conserved epitopes are shared among VSPs from both of the assemblages that commonly infect humans, and they are likely to be structural, as both sodium dodecyl sulfate treatment and dithiothreitol reduction decrease antibody recognition. In a multiplex bead assay (MBA), we used three VSP fragments from an assemblage A Giardia strain, three VSP fragments from assemblage B strains, and the α-1 giardin structural antigen to detect IgG antibodies to Giardia and used the recombinant 17- and 27-kDa antigens to simultaneously detect IgG antibodies to Cryptosporidium. The MBA differentiated between sera from Giardia and Cryptosporidium outbreaks and also identified a giardiasis outbreak that may have included cryptosporidiosis cases. Approximately 40% of cryptosporidiosis outbreak samples had high MBA responses for both the 27- and 17-kDa antigens, while <10% of nonoutbreak and giardiasis outbreak samples had high responses. At least 60% of giardiasis outbreak samples were positive for antibodies to multiple Giardia antigens, while ≤12% of nonoutbreak samples and samples from U.S. and British Columbia cryptosporidiosis outbreaks met our definition for Giardia seropositivity. A MBA using multiple parasite antigens may prove useful in the epidemiologic analysis of future waterborne or food-borne outbreaks of diarrheal disease.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".