Programming cancer through phase-functionalized silicon based biomaterials
Bibliographic record
Abstract
<p>Applications of biomaterials in cancer therapy has been limited to drug delivery systems and markers in radiation therapy. In this article, we introduce the concept of phase-functionalization of silicon to preferentially select cancer cell populations for survival in a catalyst and additive free approach. Silicon is phase-functionalized by the interaction of ultrafast laser pulses, resulting in the formation of rare phases of SiO2 in conjunction with differing silicon crystal lattices. The degree of phase-functionalization is programmed to dictate the degree of repulsion of cancer cells. Unstable phases of silicon oxides are synthesized during phase-functionalization and remain stable at ambient conditions. This change in phase of silicon as well as formation of oxides contributes to changes in surface chemistry as well as surface energy. These material properties elicit in precise control of migration, cytoskeleton shape, direction and population. To the best of our knowledge, phasefunctionalized silicon without any changes in topology or additive layers and its applications in cancer therapy has not been reported before. This unique programmable phase-functionalized silicon has the potential to change current trends in cancer research and generate focus on biomaterials as cancer repelling or potentially cancer killing surfaces.</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) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.309 | 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".