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Record W2766183409 · doi:10.1038/s41598-017-13751-z

In vitro selections of mammaglobin A and mammaglobin B aptamers for the recognition of circulating breast tumor cells

2017· article· en· W2766183409 on OpenAlexafffund
Eman M. Hassan, William G. Willmore, Bruce C. McKay, Maria C. DeRosa

Bibliographic record

VenueScientific Reports · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsCarleton UniversityInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ottawa
KeywordsAptamerMammaglobinBreast cancerSystematic evolution of ligands by exponential enrichmentCirculating tumor cellCancer researchMetastatic breast cancerIn vitroCancerBiologyMolecular biologyMedicineComputational biologyMetastasisInternal medicineBiochemistryGene

Abstract

fetched live from OpenAlex

Abstract Mammaglobin B (MGB2) and mammaglobin A (MGB1) are proteins expressed in metastatic breast cancers. The early detection of circulating tumor cells (CTCs) in breast cancer patients is crucial to decrease mortality rate. Herein, novel aptamers were successfully selected and characterized against MGB2 and MGB1 proteins using a hybrid SELEX approach. The potential use of the selected aptamers in breast CTC detection was studied using spiked breast cancer cells in whole blood lysate. The results obtained from this study showed that the selected aptamers (MAMB1 and MAMA2) bind to their target breast cancer cell lines with high affinity (low nanomolar K d values) and specificity. They also bind to their free recombinant target proteins and show minimal non-specific binding to normal and other cancer cell lines. Additionally, they were able to distinguish a low number of breast cancer cells spiked in whole blood lysate containing normal blood cells. The results obtained in this study indicate the great potential for the use of aptamers to detect MGB1 and MGB2 protein biomarkers, expressed on the surface of breast CTCs.

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)0.000
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 score0.006
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.012
GPT teacher head0.268
Teacher spread0.256 · 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

Citations30
Published2017
Admission routes2
Has abstractyes

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