Mechanical Characterization of Individual Brewing Yeast Cells Using Microelectromechanical Systems (MEMS): Cell Rupture Force and Stiffness
Bibliographic record
Abstract
The mechanical properties of individual yeast cells were measured using microelectromechanical systems (MEMS). Samples were taken throughout two controlled fermentations conducted as per ASBC Yeast-14: one utilized ale yeast (Saccharomyces cerevisiae, “red ale”) and the other utilized a lager strain (S. pastorianus, “SMA”). At least five lager and five ale cells were tested at each fermentation phase (start, middle, and end). Cell compression was induced by a MEMS squeezer, and displacement measurements were taken using optical microphotographs. The failure of each cell was similar; the cell would undergo minor deformation until visible rupture occurred, followed by significant cell shrinkage. Across all fermentation phases ale cells ruptured under an average force of 0.28 ± 0.05 μN, whereas lager cells ruptured at 0.47 ± 0.10 μN. The average stiffness at the midpoint of fermentation was found to be 4.8 ± 1.0 and 5.3 ± 0.9 μN/μm for ale and lager cells, respectively. The use of MEMS technology to study physical characteristics of brewing yeast during fermentation has not previously been attempted (to the authors' knowledge). This study may assist brewers in the selection of process parameters to improve yeast health and in the design of novel yeast handling technologies.
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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 | 0.000 | 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".