Manipulating mammalian cell morphologies using chemical-mechanical polished integrated circuit chips
Bibliographic record
Abstract
Tungsten chemical-mechanical polished integrated circuits were used to study the alignment and immobilization of mammalian (Vero) cells. These devices consist of blanket silicon oxide thin films embedded with micro- and nano-meter scale tungsten metal line structures on the surface. The final surfaces are extremely flat and smooth across the entire substrate, with a roughness in the order of nanometers. Vero cells were deposited on the surface and allowed to adhere. Microscopy examinations revealed that cells have a strong preference to adhere to tungsten over silicon oxide surfaces with up to 99% of cells adhering to the tungsten portion of the surface. Cells self-aligned and elongated into long threads to maximize contact with isolated tungsten lines as thin as 180 nm. The orientation of the Vero cells showed sensitivity to the tungsten line geometric parameters, such as line width and spacing. Up to 93% of cells on 10 μm wide comb structures were aligned within ± 20° of the metal line axis. In contrast, only ~22% of cells incubated on 0.18 μm comb patterned tungsten lines were oriented within the same angular interval. This phenomenon is explained using a simple model describing cellular geometry as a function of pattern width and spacing, which showed that cells will rearrange their morphology to maximize their contact to the embedded tungsten. Finally, it was discovered that the materials could be reused after cleaning the surfaces, while maintaining cell alignment capability.
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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".