Intracellular Mechanistic Understanding of 2D MoS<sub>2</sub> Nanosheets for Anti-Exocytosis-Enhanced Synergistic Cancer Therapy
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
Emerging two-dimensional (2D) nanomaterials, such as transition-metal dichalcogenide (TMD) nanosheets (NSs), have shown tremendous potential for use in a wide variety of fields including cancer nanomedicine. The interaction of nanomaterials with biosystems is of critical importance for their safe and efficient application. However, a cellular-level understanding of the nano-bio interactions of these emerging 2D nanomaterials (i.e., intracellular mechanisms) remains elusive. Here we chose molybdenum disulfide (MoS2) NSs as representative 2D nanomaterials to gain a better understanding of their intracellular mechanisms of action in cancer cells, which play a significant role in both their fate and efficacy. MoS2 NSs were found to be internalized through three pathways: clathrin → early endosomes → lysosomes, caveolae → early endosomes → lysosomes, and macropinocytosis → late endosomes → lysosomes. We also observed autophagy-mediated accumulation in the lysosomes and exocytosis-induced efflux of MoS2 NSs. Based on these findings, we developed a strategy to achieve effective and synergistic in vivo cancer therapy with MoS2 NSs loaded with low doses of drug through inhibiting exocytosis pathway-induced loss. To the best of our knowledge, this is the first systematic experimental report on the nano-bio interaction of 2D nanomaterials in cells and their application for anti-exocytosis-enhanced synergistic cancer therapy.
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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) | 0.001 | 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