Impact of tumor‐associated macrophages on invasive ductal carcinoma of the pancreas head
Bibliographic record
Abstract
Tumor-associated macrophages (TAMs) are candidate histological factors in invasive ductal carcinoma (IDC) of the pancreas. Tumor-associated macrophages can be affected by cancer-related inflammation and pancreatitis and interact with important invasive behavior in a recurrent manner in pancreatic IDC. These features may help elucidate the aggressiveness of pancreatic IDC. The aim of this study was to characterize TAMs in pancreatic IDC in comparison with chronic pancreatitis (CP) and to reveal TAM-related factors and the clinical impact of TAMs. CD68 (a pan-macrophage marker) and CD204 (an M2 macrophage marker) immunohistochemistry was carried out in pancreas head specimens from 107 IDC cases and 11 CP cases. Immunopositive cell areas were calculated at the periphery and center of the tumor. The distributions of macrophages in IDC and CP and the relationship between TAMs and histological tumor factors, survival, and recurrence were evaluated. Macrophages were more frequently observed in the lesion periphery than the center in IDC and CP. The density of macrophages was elevated in IDC compared to CP. Dense M2 macrophages at the tumor periphery were frequently seen in large tumors and showed an independent impact on overall survival and disease-free time. Early recurrence in the liver or the local manipulated area was associated with high accumulation of peripheral M2 macrophages. More M2 macrophages were seen in IDC than in CP in both the periphery and the center. High numbers of peripheral M2 macrophages were associated with large tumor size, early recurrence in the liver, local recurrence, and shortened survival time in patients with pancreatic IDC.
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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 | 0.000 |
| 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) | 0.001 | 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".