Cell Selective Apoptosis Induced by Polymorphic Alteration of Self-Assembled Silica Nanowebs
Bibliographic record
Abstract
The biocompatibility of silicon-based nanomaterials makes them suitable for biophysical and biomedical applications. However, the application of silicon-based nanomaterials has been mainly restricted to nanoparticles (NPs) as a potential drug carrier and the extracellular matrix (ECM) as a platform for cell adhesion and proliferation. Here, we introduce silica NPs self-assembled into a 3D nanoweb architecture that was shown to inherit the therapeutic and proliferative attributes of both NPs and ECMs. The self-assembled silica nanoweb (SNW) has, therefore, not only shown targeted druglike behavior in HeLa cells without the use of biomarkers but has also shown ECM characteristics. The ECM characteristics of SNWs enhanced the cellular attraction and proliferation by which fibroblasts exhibited tissuelike behavior, and HeLa cells underwent an intensified induction of apoptosis. These properties are tailored by the alteration of the polymorphic heterogeneities of the SNW as a novel nanobiointerface for exceptional apoptosis induction through the enhancement of cellular attraction, which, to the best of our knowledge, has not been previously reported. These attributes enable selective functionality with which cancerous HeLa and mammalian fibroblast cells were affected differently. Moreover, simultaneous control of the packing index and crystallinity of the SNWs, to which the cells had been attracted, possessed the additional advantage of modulating the selective functionality of this nanobiointerface. These polymorphic characteristics were tailored by the alteration of the crystallinity of the synthesized SNW via precision control of the ionization level of the silicon substrate, whose requisite ionization energy was generated by an ultrashort pulsed laser. Our results showed that the therapeutic functionality of the SNW-plated template can be elucidated via the endocytosis of amorphous SNWs. Because of the efficient cellular attraction and remarkable contrast in the cellular response to the SNW-plated template, we expect that these findings will provide new insights and opportunities for designing and engineering novel cell-material interfaces for advanced biomedical applications in cancer research.
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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) | 0.000 | 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 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".