Histopathological Growth Pattern, Proteolysis and Angiogenesis in Chemonaive Patients Resected for Multiple Colorectal Liver Metastases
Bibliographic record
Abstract
The purpose of this study was to characterise growth patterns, proteolysis, and angiogenesis in colorectal liver metastases from chemonaive patients with multiple liver metastases. Twenty-four patients were included in the study, resected for a median of 2.6 metastases. The growth pattern distribution was 25.8% desmoplastic, 33.9% pushing, and 21% replacement. In 20 patients, identical growth patterns were detected in all metastases, but in 8 of these patients, a second growth pattern was also present in one or two of the metastases. In the remaining 4 patients, no general growth pattern was observed, although none of the liver metastases included more than two growth patterns. Overall, a mixed growth pattern was demonstrated in 19.3% of the liver metastases. Compared to metastases with pushing, those with desmoplastic growth pattern had a significantly up-regulated expression of urokinase-type plasminogen activator receptor (P = 0.0008). Angiogenesis was most pronounced in metastases with a pushing growth pattern in comparison to those with desmoplastic (P = 0.0007) and replacement growth pattern (P = 0.021). Although a minor fraction of the patients harboured metastases with different growth patterns, we observed a tendency toward growth pattern uniformity in the liver metastases arising in the same patient. The result suggests that the growth pattern of liver metastases is not a random phenomenon.
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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 | 0.001 | 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".