mTOR inhibitors response and mTOR pathway in pancreatic neuroendocrine tumors
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
Medical therapy of pancreatic neuroendocrine tumors (P-NET) may take advantage of Everolimus treatment. However, the extent of therapeutic response cannot be predicted. This study was aimed to identify the possible predictive markers of response to Everolimus in P-NET. We found that Everolimus reduced the cell viability and induced apoptosis in primary cultures of 6 P-NET (P-NET-R), where the proliferative and antiapoptotic effects of IGF1 were blocked by Everolimus. On the contrary, 14 P-NET primary cultures (P-NET-NR) were resistant to Everolimus and IGF1, suggesting an involvement of PI3K/AKT/mTOR pathway in the mechanism of resistance. The response to Everolimus in vitro was associated with an active AKT/mTOR pathway and seemed to be associated with a greater clinical aggressiveness. In addition, a patient sensitive to Everolimus in vitro was sensitive to this drug in vivo also and showed a positive p-AKT immunohistochemistry (IHC) at tissue level. Similarly, a patient resistant to Everolimus treatment after surgery was not sensitive to the drug in vitro and had a negative p-AKT IHC staining. Therefore, present data confirm that P-NET primary cultures may be considered a model for testing medical treatment efficacy and that IHC characterization of p-AKT might help in identifying human P-NET who can benefit from Everolimus treatment. These data encourage conducting a prospective multicenter study involving different groups of P-NET patients treated with Everolimus.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it