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Record W1977286905 · doi:10.1038/srep04432

Novel Multiplex MethyLight Protocol for Detection of DNA Methylation in Patient Tissues and Bodily Fluids

2014· article· en· W1977286905 on OpenAlexafffund
Ekaterina Olkhov‐Mitsel, Darko Zdravic, Ken J. Kron, Theodorus van der Kwast, Neil Fleshner, Bharati Bapat

Bibliographic record

VenueScientific Reports · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
FundersProstate Cancer Canada
KeywordsMultiplexDNA methylationMethylationComputational biologyDNABiomarkerMultiplex polymerase chain reactionBiologyMolecular biologyGeneBioinformaticsGeneticsPolymerase chain reactionGene expression

Abstract

fetched live from OpenAlex

Aberrant DNA methylation is a hallmark of cancer and is an important potential biomarker. Particularly, combined analysis of a panel of hypermethylated genes shows the most promising clinical performance. Herein, we developed, optimized and standardized a multiplex MethyLight assay to simultaneously detect hypermethylation of APC, HOXD3 and TGFB2 in DNA extracted from prostate cancer (PCa) cell lines, archival tissue specimens, and urine samples. We established that the assay is capable of discriminating between fully methylated and unmethylated alleles with 100% specificity and demonstrated the assay as highly accurate and reproducible as the singleplex approach. For proof of principle, we analyzed the methylation status of these genes in tissue and urine samples of PCa patients as well as PCa-free controls. These data show that the multiplex MethyLight assay offers a significant advantage when working with limited quantities of DNA and has potential applications in research and clinical settings.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.018
GPT teacher head0.294
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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".

Quick stats

Citations51
Published2014
Admission routes2
Has abstractyes

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