A Xenograft Nude Mouse Model for Perineural Invasion and Recurrence in Pancreatic Cancer
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
OBJECTIVE: Pancreatic cancer recurrence after initially "curative" resection is an unresolved clinical problem in the management of patients with this disease. Perineural invasion correlates with and might be partially responsible for tumor recurrence and poor survival. However, no adequate preclinical animal model is yet available to study this aspect of pancreatic cancer biology. METHODS: We modified our orthotopic xenograft model of pancreatic cancer in nude mice to develop a model for pancreatic cancer perineural invasion and recurrence. RESULTS: After initial orthotopic transplantation, complete surgical resection of MIA PaCa-2 (undifferentiated) and Capan-2 (well-differentiated) tumors at 4, 6, and 8 weeks was attempted. All animals that had undergone tumor resection survived the operation. Animals that had the MIA PaCa-2 tumor resected after 6 weeks developed recurrent pancreatic cancer with local invasion and distant metastasis. Histological evaluation revealed extensive invasion of retroperitoneal nerves by the cancer cells. CONCLUSION: Complete resection of orthotopically transplanted pancreatic cancer in nude mice leads to local tumor recurrence. This model may eventually prove valuable for studying the mechanisms of pancreatic cancer perineural invasion and recurrence.
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 | 0.000 | 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) | 0.000 | 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