Solid-phase PCR with hybridization and time-resolved fluorometry for detection of HLA-B27.
Bibliographic record
Abstract
BACKGROUND: Preactivated solid surfaces provide new possibilities for multiple consecutive reactions in a microtiter plate format. In this study, a combination of PCR and subsequent hybridization in the same microtiter well was applied for the detection of HLA-B27 alleles. METHODS: A multiplex solid-phase PCR to amplify the HLA-B27 alleles together with beta-actin as an amplification control gene was performed on the NucleoLink (Nunc) surface. PCR was followed by hybridization and detection with time-resolved fluorescence. For the covalent capture of the PCR primers onto the solid support via a 1-(3-dimethylamino-propyl)-3-ethylcarbodiimide hydrochloride-mediated reaction, different 5'-end modifications of oligonucleotides were tested [amination, phosphorylation, and a poly(dT)10 linker]. RESULTS: For covalent immobilization of the primers, amination of the 5' end combined with use of the poly(dT)10 linker was superior. At least 19.5% of the primer added per well was attached via a stable bond. When the standard time-resolved, fluorescence-based HLA-B27 detection system was compared with the newly developed method in a sample series of 82 genomic DNAs and the corresponding dried-blood spots, all results were in full agreement. CONCLUSIONS: The new solid-phase PCR approach can be applied for multiple-target DNA detection. PCR followed by hybridization can be accomplished in a few hours using precoated strips and dried-blood spot PCR templates.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".