Probing the redox environment of single human cancer cells using scanning electrochemical microscopy
Bibliographic record
Abstract
Complex biological processes, such as the transport of molecules across cell membranes, are often difficult to understand or even to monitor using purely biological methodologies. Investigating these transport processes remains challenging, because biological objects exhibit highly complex chemical composition, target substances exist in small concentrations and studies require the analysis of living samples. Scanning electrochemical microscopy (SECM) is an electrochemical analytical technique, offering the detection of single molecules released from a single cell non-invasively. It does so by detecting electron transfer reactions at a biased microelectrode positioned in close proximity to a target cell.The presented dissertation investigates and quantifies the efflux of glutathione from human adenocarcinoma cervical cancer cells (HeLa) and a multidrug resistant variant (HeLa-R). Due to its ubiquitous antioxidant and regulatory redox properties, glutathione provides information about the overall cellular redox state. Herein, two methods are proposed to quantify the heterogeneous rate constant (kinetics) in HeLa and HeLa-R by means of SECM. First, the use of both, a cell permeable and a cell impermeable redox mediator during 3D live cell imaging and application of SECM theory leads to a direct comparison of HeLa and HeLa-R cell kinetics. Secondly, SECM line scan imaging at different scan velocities, supported by numerical simulations offers a rapid and convenient alternative solution for the quantitative determination of cellular glutathione efflux. Furthermore, issues related to a long experimental acquisition time during the mediator-based methodology could be resolved.To apply the SECM scan velocity based glutathione efflux quantification method to a biological relevant model as a proof of concept, the influence of Epigallocatechine gallate (EGCg), the most abundant catechin in tea, on HeLa cell kinetics is investigated. After exposure to EGCg the cells metabolic response is monitored electrochemically and biochemically over time. Finally, a direct comparison of the two proposed electroanalytical methods is conducted and discussed in the context of current literature. Suggestions are made for future studies and their impact in analytical and medical research is discussed.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".