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Record W4312269342 · doi:10.1166/jbn.2022.3380

Clinical Significance of Circulating Clonal Plasma Cells Detected by a Novel Microfluidic Chip in Multiple Myeloma

2022· article· en· W4312269342 on OpenAlexaff
Dongfang Ouyang, Hanqing Zhang, Bin Tang, Jaewon Park, Lina Hu, Jenny Hirst, Lidan You, Yonghua Li

Bibliographic record

VenueJournal of Biomedical Nanotechnology · 2022
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMicrofluidic chipMicrofluidicsMinimal residual diseaseFlow cytometryBone marrowMultiple myelomaBiomarkerMedicineBiologyPathologyImmunologyMaterials scienceNanotechnologyBiochemistry

Abstract

fetched live from OpenAlex

Circulating Clonal Plasma cells (cCPCs) in peripheral blood is emerged as an important biomarker in evaluating the Minimal Residual Disease (MRD) status in Multiple myeloma (MM). The elevation of cCPCs is closely related to the recurrence of disease. Comparing to the conventional bone marrow aspirate, it can be accessed regularly in a noninvasive manner. Over the past decade, microfluidic techniques have been widely explored as a platform to segregate the rare cells in blood with the advantages of easy manipulation and low cost. Recently, we and several other groups have reported the successful development of cCPCs-specific microfluidic chip. However, there had been no comparative study of the performance of microfluidic chip to currently available clinical MRD prognostic tools, so we used our previously developed microfluidic platform to explore its clinical utility in comparison with existing methods of Multiparameter Flow Cytometry (MFC) and Serum Protein Electrophoresis analysis. The MRD test results from the 19 MM patients showed 89.47% of overall agreement between MFC and microfluidic chip. Through the monitoring of 2 MM patients before and after treatment, a similar fluctuation pattern was observed between the cCPCs level detected by microfluidic chip and the paraprotein level detected by Serum Protein Electrophoresis.

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 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)0.001
metaresearch head score (Gemma)0.002
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 score0.107
Threshold uncertainty score0.749

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.031
GPT teacher head0.310
Teacher spread0.279 · 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 teacher head, 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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

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