Microfluidic platform with integrated thin-film optical oxygen sensors for transient hypoxia
Bibliographic record
Abstract
Physiologically, both chronic and cycling low oxygen level, or hypoxia, can alter tumour cell behaviour and reduce effectiveness of anticancer treatment. In order to create transiently hypoxic environments around tumour cells during drug screening, short diffusion distances between the control gases and the culture media are required in order to reproduce the timescales of a few cycles per hour that have been observed in animal studies. We use a gas-permeable three-layer microfluidic device to achieve spatial and temporal oxygen control with equilibration time less than 10 minutes. We integrate thin optical oxygen sensing films composed of polystyrene with an embedded luminescent oxygen-sensitive dye in order to monitor oxygen levels within the system. We show that the microfluidic oxygen control afforded by this design is sufficient to achieve oxygen concentrations below the sensor limit of detection of 0.08% in the fluidic cell culture environment. This platform allows us to generate complex, time-varying oxygen profiles. The sensors are biocompatible and engineered tumour spheroids cultured in this platform show good viability and cell proliferation over the course of several days with in situ oxygen monitoring.
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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) | 0.001 | 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) | 0.001 | 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".