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Record W2346076365 · doi:10.1021/acs.analchem.5b04446

Dielectrophoretic Microfluidic Chip Enables Single-Cell Measurements for Multidrug Resistance in Heterogeneous Acute Myeloid Leukemia Patient Samples

2016· article· en· W2346076365 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnalytical Chemistry · 2016
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsSimon Fraser UniversityTerry Fox Research InstituteBC Cancer Agency
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryMyeloid leukemiaMicrofluidicsMicrofluidic chipMultiple drug resistanceCellMyeloidNanotechnologyChipCancer researchBiochemistry

Abstract

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The front-line treatment for adult acute myeloid leukemia (AML) is anthracycline-based combination chemotherapy. However, treatment outcomes remain suboptimal with relapses frequently observed. Among the mechanisms of treatment failure is multidrug resistance (MDR) mediated by the ABCB1, ABCC1, and ABCG2 drug-efflux transporters. Although genetic and phenotypic heterogeneity between leukemic blast cells is a well-recognized phenomenon, there remains minimal data on differences in MDR activity at the individual cell level. Specifically, functional assays that can distinguish the variability in MDR activity between individual leukemic blasts are lacking. Here, we outline a new dielectrophoretic (DEP) chip-based assay. This assay permits measurement of drug accumulation in single cells, termed same-single-cell analysis in the accumulation mode (SASCA-A). Initially, the assay was optimized in pretherapy samples from 20 adults with AML whose leukemic blasts had MDR activity against the anthracyline daunorubicin (DNR) tested using multiple MDR inhibitors. Parameters tested were initial drug accumulation, time to achieve signal saturation, fold-increase of DNR accumulation with MDR inhibition, ease of cell trapping, and ease of maintaining the trapped cells stationary. This enabled categorization into leukemic blast cells with MDR activity (MDR(+)) and leukemic blast cells without MDR activity (MDR(-ve)). Leukemic blasts could also be distinguished from benign white blood cells (notably these also lacked MDR activity). MDR(-ve) blasts were observed to be enriched in samples taken from patients who went on to enter complete remission (CR), whereas MDR(+) blasts were frequently observed in patients who failed to achieve CR following front-line chemotherapy. However, pronounced variability in functional MDR activity between leukemic blasts was observed, with MDR(+) cells not infrequently seen in some patients that went on to achieve CR. Next, we tested MDR activity in two paired AML patient samples. Pretherapy samples taken from patients that achieved CR to front-line chemotherapy were compared with samples taken at time of subsequent relapse. MDR(+) cells were frequently observed in leukemic blast cells in both pretherapy and relapsed samples, consistent with MDR as a mechanism of relapse in these patients. We demonstrate the ability of a new DEP microfluidic chip-based assay to identify heterogeneity in MDR activity in leukemic blasts. The test provides a platform for future studies to characterize the mechanistic basis for heterogeneity in MDR activity at the individual cell level.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.007
Threshold uncertainty score0.920

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.020
GPT teacher head0.206
Teacher spread0.186 · 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