A Nanobioarray Chip Intended for Fast and Multiplex Antibody Detection in Biological Fluids Delivered by Centrifugal Pumping
Bibliographic record
Abstract
A nanobioarray (NBA) chip has been developed with the goal of having a high throughput system that analyze proteins of low sample volumes against multiple probes in a short time. A combination of horizontal and vertical channels are produced to create an antigen array on the surface of the NBA chip in one dimension that is probed by flowing protein samples (e.g. antibodies) from biological fluids in the orthogonal dimension. To improve sensitivity, we have tested the NBA chip by immobilizing streptavidin and then biotinylated peptide to detect the presence of a mouse monoclonal antibody (MAb) that is specific for the peptide. Bound antibody is detected by an AlexaFluor 647 labeled goat (anti-mouse IgG) polyclonal antibody. Using this NBA chip, we have successfully detected antibodies in samples in 500 nL containing 50 pM of MAb (or 25 attomoles), and this demonstrates a detection limit below that of a comparable ELISA, utilizing a shorter reaction time. Such a system is intended for assays of protein mixtures in biofluids, even for proteomic studies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.004 | 0.003 |
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".