The expression of CD markers in solid tumors: Significance in metastasis and prognostic value.
Bibliographic record
Abstract
OBJECTIVE: The clusters of differentiations (CDs) are among the surface markers expressed on different cells in the body, which are involved in the communication of cells with each other and the induction of signaling. Moreover, the evaluation of the ectopic expression of these markers in solid tumors has led to the detection of disease in early stages. In this paper, we have examined the effect of CD markers expression on the function of cancer cells, as well as their importance as the diagnostic and prognostic factors for monitoring the progression of solid tumors. MATERIALS AND METHODS: Relevant literature was identified by a PubMed search (1988-2017) of English language papers using the terms "CD markers", "diagnostic", "prognostic", "predictive marker" and "solid tumors." DISCUSSION: Finally, it can be stated that the evaluation of CDs is not only of diagnostic value at disease onset, but these markers can be used as prognostic and predictive markers to contribute to the treatment of disease and predict its relapse. CONCLUSION: Monitoring of tumors progression through CDs expressed on circulating tumor cells could be a new diagnostic and prognostic factor in the future.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".