Novel peptide dermaseptin‐<scp>PS</scp>1 exhibits anticancer activity via induction of intrinsic apoptosis signalling
Bibliographic record
Abstract
Abstract Antimicrobial peptides (AMP) secreted by the granular glands of frog skin have been widely reported to exhibit strong bacteriostatic and bactericidal activities. Many of them have been documented with potent antiproliferative effects on multiple cancer cells, many studies also suggested that AMPs exert their functions via disrupting cell membranes. However, whether and how other cell death induction mechanism is involved in mammalian cancer cells has rarely been investigated. In this study, a novel AMP named Dermaseptin‐PS1 was isolated and identified from Phyllomedusa sauvagei, it showed strong antimicrobial activities against three types of microorganisms. In vitro antiproliferative studies on human glioblastoma U‐251 MG cells indicated that Dermaseptin‐PS1 disrupted cell membranes at the concentrations of 10−5 M and above, while the cell membrane integrity was not affected when concentrations were decreased to 10−6 M or lower. Further examinations revealed that, at the relatively low concentration (10−6 M), Dermaseptin‐PS1 induced apoptosis through mitochondrial‐related signal pathway in U‐251 MG cells. Thus, for the first time, we report a novel frog skin derived AMP with anticancer property by distinct mechanisms, which largely depends on its concentration. Together, our study provides new insights into the mechanism‐illustrated drug design and the optimisation of dose control for cancer treatment in clinic.
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.
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".