Fabrication of Smart Tantalum Carbide MXene Quantum Dots with Intrinsic Immunomodulatory Properties for Treatment of Allograft Vasculopathy
Bibliographic record
Abstract
Abstract MXene nanomaterials have sparked significant interest among interdisciplinary researchers to tackle today's medical challenges. In particular, colloidal MXene quantum dots (MQDs) offer the high specific surface area and compositional flexibility of MXene while providing improvements to aqueous stability and material–cell interactions. The current study for the first time reports the development and application of immunoengineered tantalum‐carbide (Ta4C3Tx) MQDs for in vivo treatment of transplant vasculopathy. This report comes at a critical juncture in the field as poor long‐term safety of other MXene compositions challenge the eventual clinical translatability of these materials. Using rational design and synthesis strategies, the Ta4C3Tx MQDs leverage the intrinsic anti‐inflammatory and antiapoptotic properties of tantalum to provide a novel nanoplatform for biomedical engineering. In particular, these MQDs are synthesized with high efficiency and purity using a facile hydrofluoric acid‐free protocol and are enriched with different bioactive functional groups and stable surface TaO2 and Ta2O5. Furthermore, MQDs are spontaneously uptaken into antigen‐presenting endothelial cells and alter surface receptor expression to reduce their activation of allogeneic T‐lymphocytes. Finally, when applied in vivo, Ta4C3Tx MQDs ameliorate the cellular and structural changes of early allograft vasculopathy. These findings highlight the robust potential of tailored Ta4C3Tx MQDs for future applications in medicine.
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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) | 0.000 | 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 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".