Rapid, Sensitive, and Selective Quantification of Bacillus cereus Spores Using xMAP Technology
Bibliographic record
Abstract
Bacillus cereus is a spore-forming ubiquitous bacterium notable as a food poisoning agent. Detection of B. cereus spores using selective media is laborious and non-specific. Herein, the quantitative detection of B. cereus spores was investigated with commercial antibodies and published aptamer sequences. Several detection reagents were screened for affinity to Bacillus collagen-like protein A (BclA), an abundant exosporium glycoprotein. Sensitivity and selectivity toward B. cereus spores were tested using immunoassays and multi-analyte profiling (xMAP). A recombinant antibody developed in llama against BclA protein showed B. cereus spore selectivity and sensitivity between 102 and 105 spores/mL using xMAP. DNA aptamer sequences demonstrated sensitivity from 103 to 107 spores/mL and no cross-reaction to B. megaterium and B. subtilis. Selectivity for B. cereus spores was also demonstrated in a mixture of several diverse microorganisms and within a food sample with no compromise of sensitivity. As proof of concept for multiplexed measurement of human pathogens, B. cereus and three other microorganisms, E. coli, P. aeruginosa, and S. cerevisiae, were simultaneously detected using xMAP. These data support the development of a rapid, sensitive, and selective system for quantitation of B. cereus spores and multiplexed monitoring of human pathogens in complex matrices.
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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".