A versatile and multifunctional metal–organic framework nanocomposite toward chemo-photodynamic therapy
Bibliographic record
Abstract
Previously most of the applications of targeting components have been based on the enhanced permeability and retention effect achieved using folic acid, which consider the side effects of the targeting components to some extent. Herein, we report a new strategy to decorate the surface of MOFs using a pemetrexed (MTA) targeting molecule, affording a new drug delivery system of ALA@UIO-66-NH-FAM/MTA (ALA = 5-amino-levulinic acid and FAM = 5-carboxyfluorescein). The confocal microscopy and flow cytometry results showed that ALA@UIO-66-NH-FAM/MTA presented a better targeting effect compared to ALA@UIO-66-NH-FAM/FA (FA = folic acid) and indicated a gradually increasing tendency of the targeting effect with the increasing expression of folate receptors on the tumor cell cytomembrane. Furthermore, the cytotoxicity experiment indicates that the combination of chemotherapy and photodynamic therapy is a more effective therapy model than single chemotherapy and photodynamic therapy. This work demonstrates the first attempt at folic acid antagonist (MTA) modification for NMOFs, providing a new concept for the design of MOFs with folate receptor targeting capacity for clinical applications.
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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".