New technologies for the detection of circulating tumour cells
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.
Bibliographic record
Abstract
The vast majority of cancer-related death is due to the metastatic spread of the primary tumour. Circulating tumour cells (CTC) are essential for establishing metastasis and their detection has long been considered as a possible tool to assess the aggressiveness of a given tumour and its potential of subsequent growth at distant organs. Conventional markers are not reliable in detecting occult metastasis and, for example, fail to identify approximately 40% of cancer patients in need of more aggressive or better adjusted therapies. Recent studies in metastatic breast cancer have shown that CTC detection can be used as a marker for overall survival and assessment of the therapeutic response. The benefits of CTC detection in early breast cancer and other solid tumours need further validation. Moreover, optimal CTC detection techniques are the subject of controversy as several lack reproducibility, sensitivity and/or specificity. Recent technical advances allow CTC detection and characterization at the single-cell level in the blood or in the bone marrow. Their reproducibility propels the use of CTC in cancer staging and real-time monitoring of systemic anticancer therapies in several large clinical trials. CTC assays are being integrated in large clinical trials to establish their potential in the management of cancer patients and improve our understanding of metastasis biology. This review will focus on the techniques currently used, the technical advancements made, the limitations of CTC detection and future perspectives in this field.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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 it