Integrated Microfluidic–Electromagnetic System to Probe Single-Cell Magnetotaxis in Microconfinement
Bibliographic record
Abstract
Magnetotactic bacteria have great potential for use in biomedical and environmental applications due to the ability to direct their navigation with a magnetic field. Applying and accurately controlling a magnetic field within a microscopic region during bacterial magnetotaxis studies at the single-cell level is challenging due to bulky microscope components and the inherent curvilinear field lines produced by commonly used bar magnets. In this paper, a system that integrates microfluidics and electromagnetic coils is presented for generating a linear magnetic field within a microenvironment compatible with microfluidics, enabling magnetotaxis analysis of groups or single microorganisms on-chip. The platform, designed and optimised via finite element analysis, is integrated into an inverted fluorescent microscope, enabling visualisation of bacteria at the single-cell level in microfluidic devices. The electromagnetic coils produce a linear magnetic field throughout a central volume where the microfluidic device containing the magnetotactic bacteria is located. The magnetic field, at this central position, can be accurately controlled from 1 to 10 mT, which is suitable for directing the navigation of magnetotactic bacteria. Potential heating of the microfluidic device from the operating coils was evaluated up to 2.5 A, corresponding to a magnetic field of 7.8 mT, for 10 min. The maximum measured heating was 8.4 °C, which enables analysis without altering the magnetotaxis behaviour or the average swimming speed of the bacteria. Altogether, this work provides a design, characterisation and experimental test of an integrated platform that enables the study of individual bacteria confined in microfluidics, under linear and predictable magnetic fields that can be easily and accurately applied and controlled.
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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".