Trehalose enhanced cold atmospheric plasma-mediated cancer treatment
Bibliographic record
Abstract
Cold atmospheric plasma (CAP) is a unique form of physical plasma that has shown great potential for cancer therapy. CAP uses ionized gas to induce lethal oxidative stress on cancer cells; however, the efficacy of CAP therapy continues to be improved. Here, we report an injectable hydrogel-mediated approach to enhance the anti-tumor efficacy of CAP by regulating the phosphorylation of eIF2α. We discovered that reactive oxygen and nitrogen species (ROS/RNS), two main anti-tumor components in CAP, can lead to lethal oxidative stress on tumor cells. Elevated oxidative stress subsequently induces eIF2α phosphorylation, a pathognomonic marker of immunogenic cell death (ICD). Trehalose, a natural disaccharide sugar, can further enhance CAP-induced ICD by elevating the phosphorylation of eIF2α. Moreover, injectable hydrogel-mediated delivery of CAP/trehalose treatment promoted dendritic cell (DC) maturation, initiating tumor-specific T-cell mediated anti-tumor immune responses. The combination therapy also supported the polarization of tumor-associated macrophages to an M1-like phenotype, reversing the immunosuppressive tumor microenvironment and promoting tumor antigen presentation to T cells. In combination with immune checkpoint inhibitors (i.e., anti-programmed cell death protein 1 antibody, aPD1), CAP/trehalose therapy further inhibited tumor growth. Importantly, our findings also indicated that this hydrogel-mediated local combination therapy engaged the host systemic innate and adaptive immune systems to impair the growth of distant tumors.
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 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 | 0.000 |
| 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 | 0.001 |
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 teacher head, 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".