LncRNAs as nodes for the cross-talk between autophagy and Wnt signaling in pancreatic cancer drug resistance
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
Pancreatic cancer is a malignancy with high mortality. In addition to the few symptoms until the disease reaches an advanced stage, the high fatality rate is attributed to its rapid development, drug resistance and lack of appropriate treatment. In the selection and research of therapeutic drugs, gemcitabine is the first-line drug for pancreatic cancer. Solving the problem of gemcitabine resistance in pancreatic cancer will contribute to the progress of pancreatic cancer treatment. Long non coding RNAs (lncRNAs), which are RNA transcripts longer than 200 nucleotides, play vital roles in cellular physiological metabolic activities. Currently, our group and others have found that some lncRNAs are aberrantly expressed in pancreatic cancer cells, which can regulate the process of cancer through autophagy and Wnt/β-catenin pathways simultaneously and affect the sensitivity of cancer cells to therapeutic drugs. This review presents an overview of the recent evidence concerning the node of lncRNA for the cross-talk between autophagy and Wnt/β-catenin signaling in pancreatic cancer, together with the practicability of lncRNAs and the core regulatory factors as targets in therapeutic resistance.
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 | 0.001 | 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