In vitro selections of mammaglobin A and mammaglobin B aptamers for the recognition of circulating breast tumor cells
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".