Prognostic Role of Serum Sialyl Lewis<sup>x</sup> (CD15s) in Colorectal Cancer
Bibliographic record
Abstract
OBJECTIVE: Sialyl Lewis(x) (sLe(x)) is one ligand for E selectin (CD62E), a glycoprotein that is expressed on activated endothelial cells. Adhesion mediated by endothelial E selectin and sLe(x) expressed on human tumor cells could be relevant for the development of metastases. The aim of this study was to investigate whether or not a correlation exists between pre-operative levels of ganglioside serum sLe(x) and disease-free interval and survival in colorectal cancer patients. PATIENTS AND METHODS: Thirty Duke's B and 52 Duke's C patients undergoing resection for colorectal cancer were studied. The median follow-up time was 34.8 months. A pool of 57 sera from normal subjects was used as an Internal Normal Standard (INS). sLe(x) analyses were performed by a thin layer chromatography (TLC) immunostaining technique. Results were expressed as the ratio (R) between bands of INS and bands from each neoplastic serum. RESULTS: The median R value was 0.80 in normal subjects, 0.70 in Duke's B patients and 1.0 in Duke's C patients. No significant differences were detected between sLe(x) concentrations in sera from normal and neoplastic subjects (p = 0.1). Using an arbitrary cutoff of R = 0.9, the mean disease-free interval in the whole series was 47.4 months for R <0.9 and 126.0 months for R > or = 0.9 (p = 0.04). The survival time was 76.8 months for patients with R values <0.9 and 156.3 months for patients with R values > or =0.9 (p = 0.1). CONCLUSIONS: High serum levels of ganglioside sLe(x) significantly correlate with a favorable prognosis and with a lower occurrence of metastases. It is conceivable that soluble sLe(x) may compete with membrane-bound sLe(x) in the course of interactions between activated endothelium and tumor cells that have reached the circulation.
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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 | 0.001 |
| 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".