Protein Bead Array for the Detection of HIV-1 Antibodies from Fresh Plasma and Dried-Blood-Spot Specimens
Bibliographic record
Abstract
Simultaneous multianalyte immunoassays offer advantages, including reduction of technical operations, execution time, and overall costs. The suspension array technology (SAT), which uses microfluorospheres with flow cytometry, is a multianalyte immunoassay that requires small specimen volumes, such as those obtained by less-invasive blood sampling approaches such as heel or finger sticks, as well as those obtained in pediatric specimens. The dried-blood-spot (DBS) technology has become an important screening tool for clinical and epidemiologic testing (1)(2)(3). It is particularly convenient in rural, resource-limited settings where trained personnel and adequate facilities for blood collection, processing, transport, and storage may not be available. This approach, however, provides limited specimen volume (∼5–6 μL of serum/6-mm punch) (2). Fortunately, SAT is well suited to support such a format (4)(5). The range of applications for SAT includes antibody, oligonucleotide, peptide, and protein bead arrays (PBAs) (4)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17). PBAs have been used for the simultaneous detection of serum antibodies to infectious agents for systemic candidiasis (18), herpes viruses (19), measles, mumps (20), and HIV (21)(22). The successful detection of HIV-1 serum antibodies by a four-protein bead array was first reported by Scillian et al. (21), who used beads of various sizes and proteins noncovalently coupled to beads. Reagents are now available that permit covalent coupling of proteins to beads and simultaneous analysis of up to 100 color-coded bead sets in a high-throughput, 96-well plate format. In addition, a new generation of flow cytometers compatible with SAT has recently been introduced, e.g., the Luminex-100 System (Luminex Corp.) and the FACSArray (BD Biosciences). We have developed and evaluated a HIV-1 PBA for the rapid detection of antibodies to seven viral proteins from fresh plasma and DBS specimens.
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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 | 0.001 |
| 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) | 0.012 | 0.012 |
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".