RGDSK:K1 helical rosette nanotube induces apoptosis in human lung carcinoma cells through p38 MAPK cascade
Bibliographic record
Abstract
Helical rosette nanotubes (HRN) are a novel class of biologically inspired nanotubes that are metal‐free and water‐soluble. To explore the tremendous potential of self‐assembled Arg‐Gly‐Asp‐Ser‐Lys (RGDSK):K1 HRN (1:10 M) for targeted drug delivery, especially into the lung, there is a critical need to understand cellular and molecular actions of these nanotubes. Therefore, we investigated p38 Mitogen‐activated protein kinase (MAPK) cascade, caspase‐3 activity and apoptosis in human lung carcinoma cells (Calu3) exposed to RGDSK:K1 HRN at various concentrations and times. RGDSK:K1 HRN (1:10 μM) induced phosphorylation of a 38 KDa band of p38 MAPK within 5 minutes which was inhibited by MAPK kinase (MEK) inhibitors (PD98059 & U0126; 20 μM). All of the tested concentrations of RGDSK:K1 HRN (1:10 to 40:400 μM) caused a concentration‐dependent increase in Caspase‐3 activity in Calu‐3 cells at 18 hours of the exposure. Highest concentration of RGDSK:K1 HRN (40:400 μM) caused a 10 fold increase in Caspase‐3 activity over the control which was significantly blocked by MEK inhibitor U0126 (20 μM). Flow cytometeric analyses of Calu‐3 cells exposed to RGDSD:K1 and stained with FITC‐Annexin‐V and propidium iodide showed apoptosis in the cells. We conclude that RGDSK:K1 HRN induces p38 MAPK phosphorylation which regulates activation of Caspase‐3 and apoptosis Calu‐3 cells. (NSERC Canada)
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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 | 0.000 |
| 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".