Manipulating mammalian cell morphologies using chemical-mechanical polished integrated circuit chips
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 it