A combined HIV‐1 protein bead array for serology assay and T‐cell subset immunophenotyping with a hybrid flow cytometer: A step in the direction of a comprehensive multitasking instrument platform for infectious disease diagnosis and monitoring
Bibliographic record
Abstract
BACKGROUND: A new generation of bench-top flow cytometers with digital signal processing to perform suspension array technology (SAT) based bead array assays as well as leukocyte immunophenotyping is now available. These hybrid instruments provide an opportunity for the development of a more cost effective multitasking platform to support infectious disease treatment in resource limited countries. METHODS: We report the development and testing of two modules compatible with the hybrid flow cytometers. The first module is an eleven HIV-1 protein bead array (PBA) for the detection of circulating antibodies and the second is a cell based T-cell enumeration assay. RESULTS: The HIV-1 PBA was tested in parallel with two enzyme immunoassays (EIAs) for the detection of plasma antibodies from 4 HIV-1 seroconversion panels and a low antibody titer panel. The PBA as well as the two EIAs performed equally for the detection of antibody positive samples from all seroconversion panels. One antibody positive sample from the low antibody titer panel was missed by the PBA together with one of the two EIAs tested. A parallel analysis of the HIV-1 PBA with Western blot (a confirmatory test for HIV infection) using plasma from nine HIV-1(+) individuals showed that the HIV-1 PBA detected more of the gp41 and gp120 antibody positive samples. Preliminary CD4 T-cell immunophenotyping results from 14 HIV(+) and 10 HIV(-) whole blood specimens with the hybrid flow cytometer platform compared well to conventional flow cytometry data. CONCLUSION: The successful combination of bead and cell based assays on a single hybrid instrument demonstrated the potential utility of a multitasking platform. The results presented are providing groundwork for future development of more cost effective modular architecture for a flexible flow cytometry based platform.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".