Low‑intensity low‑frequency ultrasound enhances the chemosensitivity of gemcitabine‑resistant ASPC‑1 cells via PI3K/AKT/NF‑κB pathway‑mediated ABC transporters
Bibliographic record
Abstract
Tumor drug resistance (TDR) invariably leads to the failure of chemotherapy. In addition, current treatment strategies for TDR are not satisfactory due to limitations in terms of safety and feasibility. The aim of the present study was to determine whether low‑intensity low‑frequency ultrasound (LILFU) could improve the effect of chemotherapy and reverse TDR in gemcitabine‑resistant ASPC‑1 (ASPC‑1/GEM) cells. The investigation focused on the association between LILFU effectiveness and the adenosine triphosphate‑binding cassette (ABC) transporters and the phosphoinositide 3‑kinase (PI3K)/protein kinase B (AKT)/nuclear factor (NF)‑κB signaling pathway. A Cell Counting Kit‑8 assay was used to determine the appropriate acoustic intensity, half‑maximal inhibitory concentration of gemcitabine (GEM) and the viability of ASPC‑1/GEM cells. ASPC‑1/GEM cells were divided into control, GEM, LILFU and GEM+LILFU groups. Cell proliferation was evaluated through colony formation assays, whereas cell apoptosis was detected using flow cytometry. Western blotting was used to explore the expression levels of ABC transporters and PI3K/AKT/NF‑κB signaling pathway‑associated proteins. Xenograft models in mice were established to identify the enhancing effect of GEM+LILFU in vivo. Immunohistochemistry was used to detect the expression levels of Ki‑67 in tumor tissues. The acoustic parameter of 0.2 W/cm2 and a GEM concentration of 6.63 mg/ml were used in subsequent experiments. Following treatment with GEM+LILFU, the cell viability and proliferation ability were decreased, whereas the apoptotic rate was increased compared with the GEM group. The expression levels of ABC transporters, PI3K‑P110α and NF‑κB were decreased in the GEM+LILFU group. Notably, LILFU increased the effectiveness of GEM in inhibiting tumor growth, and reduced the expression levels of Ki‑67 in the xenograft mouse model. LILFU improved the chemosensitivity of ASPC‑1/GEM cells via inhibition of cell viability and proliferation, and promoted cell apoptosis in the GEM+LILFU group. In conclusion, LILFU may downregulate the expression levels of ABC transporters by inhibiting the PI3K‑p110α/AKT/NF‑κB signaling pathway, thereby reversing resistance in pancreatic cancer.
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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 | 0.001 |
| 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 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".