Methylation Specific Multiplex Droplet PCR using Polymer Droplet Generator Device for Hematological Diagnostics
Bibliographic record
Abstract
A multiplexed droplet PCR (mdPCR) workflow and detailed protocol for determining epigenetic-based white blood cell (WBC) differential count is described, along with a thermoplastic elastomer (TPE) microfluidic droplet generation device. Epigenetic markers are used for WBC subtyping which is of important prognostic value in different diseases. This is achieved through the quantification of DNA methylation patterns of specific CG-rich regions in the genome (CpG loci). In this paper, bisulfite-treated DNA from peripheral blood mononuclear cells (PBMCs) is encapsulated in droplets with mdPCR reagents including primers and hydrolysis fluorescent probes specific for CpG loci that correlate with WBC sub-populations. The multiplex approach allows for the interrogation of many CpG loci without the need for separate mdPCR reactions, enabling more accurate parametric determination of WBC sub-populations using epigenetic analysis of methylation sites. This precise quantification can be extended to different applications and highlights the benefits for clinical diagnosis and subsequent prognosis.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".