Engineering functionalized multiphased silicon/silicon oxide nanobiomaterials to passivate the aggressive proliferation of cancer
Bibliographic record
Abstract
<p>Currently, the use of nano silicon in cancer therapy is limited as drug delivery vehicles and markers in imaging, not as manipulative/controlling agents. This is due to limited properties that native states of nano silicon and silicon oxides offers. We introduce nano-functionalized multi-phased silicon/ silicon oxide biomaterials synthesized via ultrashort pulsed laser synthesis, with tunable properties that possess inherent cancer controlling properties that can passivate the progression of cancer. This nanostructured biomaterial is composed of individual functionalized nanoparticles made of a homogenous hybrid of multiple phases of silicon and silicon oxide in increasing concentration outwards from the core. The chemical properties of the proposed nanostructure such as number of phases, composition of phases and crystal orientation of each functionalized nanoparticle in the three dimensional nanostructure is defined based on precisely tuned ultrashort pulsed laser-material interaction mechanisms. The amorphous rich phased biomaterial shows a 30 fold (95%) reduction in number of cancer cells compared to bulk silicon in 48hours. Further, the size of the cancer cells reduces by 76% from 24 to 48hours. This method exposes untapped properties of combination of multiple phases of silicon oxides and its applications in cancer therapy</p>
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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 | 0.000 | 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) | 0.004 | 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".