Attomolar detection of extracellular microRNAs released from living prostate cancer cells by a plasmonic nanowire interstice sensor
Bibliographic record
Abstract
Prostate cancer (PC) is the second leading cause of cancer death for men worldwide. The serum prostate-specific antigen level test has been widely used to screen for PC. This method, however, exhibits a high false-positive rate, leading to over-diagnosis and over-treatment of PC patients. Extracellular microRNAs (miRNAs) recently provided valuable information including the site and the status of the cancers and thus emerged as new biomarkers for several cancers. Among them, miR141 and miR375 are the most pronounced biomarkers for the diagnosis of high-risk PC. Herein, we report an attomolar detection of miR141 and miR375 released from living PC cells by using a plasmonic nanowire interstice (PNI) sensor. This sensor showed a very low detection limit of 100 aM as well as a wide dynamic range from 100 aM to 100 pM for all target miRNAs. In addition, the PNI sensor could discriminate perfectly the diverse single-base mismatches in the miRNAs. More importantly, the PNI sensor successfully detected the extracellular miR141 and miR375 released from living PC cell lines (LNCaP and PC-3), proving the diagnostic ability of the sensor for PC. We anticipate that the present PNI sensor can hold great promise for the precise diagnosis and prognosis of various cancer patients as well as PC patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".