One-pot direct synthesis for multifunctional ultrasmall hybrid silica nanoparticles
Bibliographic record
Abstract
Ultrasmall silica nanoparticles (NPs), having hydrodynamic diameters under 10 nm are promising inorganic platforms for imaging and therapeutic applications in medicine. Herein is described a new way for synthesizing such kind of NPs in a one-pot scalable protocol. These NPs bear DOTA (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid) ligands on their surface that can chelate different metals suitable for a wide variety of biomedical applications. By varying the ratio of the precursors, the hydrodynamic diameters of the particles can be controlled over the range of 3 to 15 nm. The resulting NPs have been characterized extensively by complementary techniques like dynamic light scattering (DLS), high performance liquid chromatography (HPLC), nuclear magnetic resonance (NMR), mass spectrometry (MS), phosphorescence titration, photophysical measurements, relaxometry and elemental analysis to elucidate their structures. Chelation of gadolinium (Gd) allowed its use as an effective intravenous contrast agent in MRI and was illustrated in mice bearing colorectal CT26 tumors. The new particle appears to sufficiently accumulate in the tumors and efficiently clear out of animal bodies through kidneys. This new synthesis is an original, time/material-saving and very flexible process that can be applied for creating versatile ultrasmall multifunctional nanomedicines.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| 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) | 0.003 | 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 teacher head, 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".