Thermal scribing to prototype plastic microfluidic devices, applied to study the formation of neutrophil extracellular traps
Bibliographic record
Abstract
Innovation in microfluidics-based biological research has been aided by the growing accessibility of versatile microscale fabrication techniques, particularly in rapid prototyping of elastomeric polydimethylsiloxane (PDMS) based devices. However, the use of PDMS presents considerable and often unexpected limitations, particularly in interpreting and validating biological data. To rapidly prototype microfluidic culture systems in conventional plastics commonly used in cell culture, we developed 'thermal scribing', a one-step micromachining technique in which thermoplastics are locally patterned by a heated tip, moving in user-controlled patterns. To demonstrate and study the thermal scribing process, we modified an inexpensive desktop hobby craft cutter with a soldering iron to scribe micropatterns on polystyrene substrates. The thermal scribing technique is useful for creating a variety of channel profiles and geometries, which cannot be readily achieved using other microfabrication approaches. The entire fabrication process, including post-processing operations needed to fabricate devices, can be completed within a few hours without the need for skilled engineering expertise or expensive equipment. We apply this technique to demonstrate that induction of functional neutrophil extracellular traps (NETs) can be significantly enhanced over previous studies, when experiments are conducted in microfluidic channels prototyped in an appropriate material. These results ultimately inform the design of neutrophil culture systems and suggest that the inherent ability of neutrophils to form NETs may have been significantly under-reported.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".