Bioresponsive and immunotherapeutic nanomaterials to remodel tumor microenvironment for enhanced immune checkpoint blockade
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Immune checkpoint blockade (ICB) therapy is a revolutionary approach to treat cancers, but still have limited clinical applications. Accumulating evidence pinpoints the immunosuppressive characteristics of the tumor microenvironment (TME) as one major obstacle. The TME, characterized by acidity, hypoxia and elevated ROS levels, exerts its detrimental effects on infiltrating anti-tumor immune cells. Here, we developed a TME-responsive and immunotherapeutic catalase-loaded calcium carbonate nanoparticles (termed as CAT@CaCO3 NPs) as the simple yet versatile multi-modulator for TME remodeling. CaCO3 NPs can consume protons in the acidic TME to normalize the TME pH. CAT catalyzed the decomposition of ROS and thus generated O2. The released Ca2+ led to Ca2+ overload in the tumor cells which then triggered the release of damage-associated molecular patterns (DAMP) signals to initiate anti-tumor immune responses, including tumor antigen presentation by dendritic cells. Meanwhile, CAT@CaCO3 NPs-induced immunosupportive TME also promoted the polarization of the M2 tumor-associated macrophages to the M1 phenotype, further enhancing tumor antigen presentation. Consequently, T cell-mediated anti-tumor responses were activated, the efficacy of which was further boosted by aPD-1 immune checkpoint blockade. Our study demonstrated that local treatment of CAT@CaCO3 NPs and aPD-1 combination can effectively evoke local and systemic anti-tumor immune responses, inhibiting the growth of treated tumors and distant diseases.
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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) | 0.000 | 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 it