Personalized Carbon Monoxide‐Loaded Biomimetic Single‐Atom Nanozyme for Ferroptosis‐Enhanced FLASH Radioimmunotherapy
Bibliographic record
Abstract
Abstract Ultra‐high dose rate radiotherapy (FLASH‐RT) has emerged as a novel tool for cancer radiotherapy owing to its extremely rapid radiation delivery to target species. Although FLASH‐RT can protect normal tissues and organs, tumor self‐protection mechanisms limit its therapeutic effect, thus necessitating technological improvement. Here, a multipathway ferroptosis‐enhanced radioimmunotherapeutic strategy that combines single‐atom nanozyme (SAzyme)‐based GSH depletion and CO gas therapy is reported. Personalized FLASH radioimmunotherapy is achieved through encapsulation of the carbon monoxide donor (MnCO)‐loaded porous Pd‐C SAzyme (SM) within 4T1 cancer cell membranes (CSM). Camouflaging with the cancer cell membrane enables the navigation of the MnCO‐loaded Pd‐C SAzyme to the tumor region via homologous targeting. There, it releases MnCO, which generates CO from overexpressed H2O2 to induce mitochondrial apoptosis. Furthermore, the generated CO and Pd‐C SAzyme oxidized glutathione and downregulates glutathione peroxidase 4 (GPX4) expression to induce ferroptosis. The palladium in the SAzyme of the CSM further enhances the photoelectric effects of FLASH‐RT. The CSM‐mediated FLASH‐RT also invokes potent antitumor immunity, suppressing distant tumors, and immune memory, inhibiting tumor recurrence. This work presents a unique personalized nanozyme and CO gas synergistic approach wherein FLASH radioimmunotherapy avoids damage of normal tissues while simultaneously inducing ferroptosis for orthotopic tumor treatment.
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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".