Jack of many trades: Multifaceted role of neuropilins in pancreatic cancer
Bibliographic record
Abstract
Neuropilins (NRPs) have been described as receptors for class 3 semaphorins and coreceptors for a plethora of ligands, such as members of the vascular endothelial growth factor (VEGF) family of angiogenic cytokines and transforming growth factor (TGF). Initial studies using genetic models have indicated that neuropilin-1 (NRP-1) is essential for axonal guidance during neuronal and cardiovascular development, regulated via semaphorins and VEGF, respectively, whereas the other homolog of neuropilin, NRP-2, has been shown to play a more specific role in neuronal patterning and lymphangiogenesis. Pancreatic ductal adenocarcinoma (PDAC) remains a significant cause of cancer mortality with the lowest five-year survival rate compared to other types of cancer. Recent findings have indicated that NRPs are abundantly expressed in pancreatic cancer cell lines and pancreatic tumor tissues, where they mediate several essential cancer-initiating and cancer-promoting functional responses through their unique ability to bind multiple ligands. Specifically, NRPs have been implicated in numerous biological processes such as cancer cell proliferation, survival, invasion, and tumor growth. More recently, several other protumorigenic roles mediated by NRPs have emerged, advocating NRPs as ideal therapeutic targets against PDAC.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".