Microfluidic perfusion system for culturing and imaging yeast cell microarrays and rapidly exchanging media
Bibliographic record
Abstract
High resolution live cell microscopy is increasingly used to detect cellular dynamics in response to drugs and chemicals, but it depends on complex and expensive liquid handling devices that have limited its wider adoption. Here, we present a microfluidic perfusion system that is built without using specialized microfabrication infrastructure, simple to use because only a pipette is needed for liquid handling, and yet allows for rapid media exchange and simultaneous fluorescence microscopy imaging. Yeast cells may be introduced from a culture, or spotted as arrays on a coverslip, and are sandwiched with a 20 mum thick track-etched membrane. A second coverslip and a mesh with 120 mum porosity are placed on top, forming a microfluidic conduit for lateral flow of solutions by capillary effects. Solutions introduced through the inlet flow through the mesh and chemicals diffuse vertically across the membrane to the cells trapped below. Solutions are exchanged by adding a new sample to the inlet. Using this system, we studied the dynamic response of F-actin in living yeast expressing Sac6-EGFP-a protein associated with discrete F-actin structures called "patches"-to the drug latrunculin A, a well known inhibitor of actin polymerization. We observed that the patches disappeared in 85% of the cells within 5 min, and re-assembled in 45 min following exchange of the drug with media. The perfusion system presented here is a simple, inexpensive device suited for analysis of drug dose-response and regeneration of single cells and arrays of cells.
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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) | 0.001 | 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) | 0.002 | 0.001 |
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".