Cell‐Electronic Sensing of Cellular Responses to Micro‐ and Nanoparticles for Environmental Applications
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
Cell‐based biosensors ( CBB s) utilizing impedance measurement have become a powerful tool for cytotoxicity analysis of (i) engineered micro‐ and nanoparticles (NPs) and (ii) complex mixtures of environmental particulate matter ( PM ). With the recent increase in the development and application of NPs, bio‐analytical techniques capable of fast, reliable, and accurate cytotoxicity analysis are needed to prioritize these materials for further toxicological testing to ensure their safe use, both for human health and environmental safety. This article focuses on the development and application of impedance‐based CBBs for rapid, sensitive, efficient, and label‐free analysis of micro‐ and nanoparticle‐induced cytotoxicity through the monitoring of several cellular responses, including cell adhesion, spreading, proliferation, transepithelial or trans endothelial electrical resistance ( TER ), and micromotion. In addition, these techniques are potentially useful for air quality monitoring, as demonstrated through the cytotoxicity analysis of complex mixtures of PM. Instruments based on electric cell–substrate impedance sensing ( ECIS ) and real‐time cell analysis ( RTCA ) are the two most widely used impedance‐based devices commercially available. Thus, detailed descriptions of the principles directing the impedance‐based measurements and data analysis employed in these systems are presented.
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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 it