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Microfluidic Devices for Molecular Monitoring of Clonotypic IgH VDJ Signatures and the T(4;14) Translocation in Multiple Myeloma.

2005· article· en· W2587934392 on OpenAlexaff
Linda M. Pilarski, Govindkrishna V. Kaigala, Jaron VanDjiken, Alexey Atrazhev, Brian J. Taylor, Andrew R. Belch, C. Backhouse

Bibliographic record

VenueBlood · 2005
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMicrofluidicsLab-on-a-chipMaterials scienceChipMolecular biologyNanotechnologyBiologyComputer science

Abstract

fetched live from OpenAlex

Abstract Integrated microfluidic chips offer fast, inexpensive and sensitive detection of molecular characteristics of cancer. PCR was performed using a hybrid polymer/glass chip comprising of wells and channels moulded in polydimethyl siloxane (PDMS) using photolithographic procedures and bonded to glass by a simple rapid prototyping procedure. Fluidic flow was performed by a microprocessor with an in-house built intelligent system for a fully reusable, scalable valving and pumping operation. We successfully performed on-chip PCR with 2 ul of template/PCR mix. Multiple Myeloma (MM) is characterized by a distinct immunoglobulin gene rearrangements, and by IgH translocations that enable unequivocal identification of the MM clone. To detect these molecular signatures, PCR was performed in the central enclosed chamber of a 3-well PCR chip (the other two being the loading and the unloading open wells) using fluorescent-tagged primers, operated using miniaturized user controlled instrumentation. After PCR amplification, product was detected by fragment analysis on a glass capillary electrophoresis (CE) chip using 50–250pl of the amplified product, performed in about 2 minutes. Unlike PCR using plasmid templates, successful PCR using nucleic acid from patient cells required passivation of the PDMS and glass inner surfaces to minimize adsorption of PCR components, and the use of approximately 1–2ng of cDNA template. Amplified products were run through a polymer filled separation channel with size standards to confirm the product size. For two MM patients, using the CE chip, both genomic DNA and IgH VDJ transcripts amplified from individual cells are detectable on-chip with as little as 0.001% of the product (50pL) amplified from one individual MM cell or from groups of MM cells. IgH VDJ product was detectable on the CE chip after a single stage conventional PCR of 30 cycles to amplify genomic DNA from 100 ex-vivo MM cells (100 copies of template). For detection of the single rearranged copy of IgH VDJ in genomic DNA from individual MM cells, a nested PCR strategy was required to amplify sufficient product for detection using either on chip CE or the ABI3100. Compared to analysis on the ABI3100, the gold standard technology, the chip provided approximately 20 fold greater sensitivity for detecting fluorescent product. To further test the microfluidic system, we amplified cDNA from ex-vivo MM cells having the t(4;14)+ translocation to detect hybrid transcripts (IgH-MMSET) on-chip. Cells from MM patients having either the MB4-1 or MB4-3 breakpoint were amplified using the PDMS/glass hybrid chip, and products of the appropriate size were detected using either conventional or on-chip CE. Finally, PCR was performed on an integrated chip that seamlessly incorporates both the PCR and the CE components as a single unit with minimal manual intervention, aiming towards higher levels of on-chip integration. Work is in progress to implement sample processing and cell selection on-chip. This work forecasts automated cost-effective devices able to analyze genetic information in minutes. Real-time detection of complex genetic abnormalities will allow sensitive detection of emerging aggressive variants as disease progresses. This will enable custom tailored therapies that target the genetic vulnerabilities of the malignant clone in each individual patient.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.200
Teacher spread0.194 · 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
GenreEmpirical

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

Citations1
Published2005
Admission routes1
Has abstractyes

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