Assessment of multidrug resistance on cell coculture patterns using scanning electrochemical microscopy
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
The emergence of resistance to multiple unrelated chemotherapeutic drugs impedes the treatment of several cancers. Although the involvement of ATP-binding cassette transporters has long been known, there is no in situ method capable of tracking this transporter-related resistance at the single-cell level without interfering with the cell's environment or metabolism. Here, we demonstrate that scanning electrochemical microscopy (SECM) can quantitatively and noninvasively track multidrug resistance-related protein 1-dependent multidrug resistance in patterned adenocarcinoma cervical cancer cells. Nonresistant human cancer cells and their multidrug resistant variants are arranged in a side-by-side format using a stencil-based patterning scheme, allowing for precise positioning of target cells underneath the SECM sensor. SECM measurements of the patterned cells, performed with ferrocenemethanol and [Ru(NH3)6](3+) serving as electrochemical indicators, are used to establish a kinetic "map" of constant-height SECM scans, free of topography contributions. The concept underlying the work described herein may help evaluate the effectiveness of treatment administration strategies targeting reduced drug efflux.
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 | 0.000 |
| 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 | 0.001 | 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 it