Robotic Control of a Magnetic Swarm for On-Demand Intracellular Measurement
Bibliographic record
Abstract
In biology, fluorescent dyes are routinely used for biochemical measurements such as pH and ion concentrations. They, especially when used for detecting a low concentration of ions, suffer from low signal-to-noise ratios (SNR); and increasing the concentration of fluorescent dyes causes more sever cytotoxicity. We invented a new approach that uses a low amount of fluorescent dye-coated magnetic nanoparticles for on-demand, accurately aggregating the nanoparticles and thus fluorescent dyes in a local region inside a cell for intracellular measurement. Experiments proved this approach is capable of achieving a significantly higher SNR and lower cytotoxicity. Different from existing magnetic micromanipulation systems that generate large swarms (several microns and above) or cannot move the generated swarm to an arbitrary position, we developed a five-pole magnetic micromanipulation system and technique for generating a small swarm (e.g., 1 μm; capable of generating a magnetic swarm from 0.52 μm to 52.7 μm with an error <; 7.5 %) and accurately positioning the small swarm (position control accuracy: 0.76 μm). As an example, the system performed intracellular pH mapping using a 1 μm swarm of pH sensitive fluorescent dye-coated magnetic nanoparticles. The swarm had an SNR inside a cell 10 times that by the traditional method, i.e., global dye treatment, with both cases using the same fluorescent dye concentration. Our intracellular measurement results, for the first time, quantitatively revealed the existence of pH gradient and polarized pH distribution in live migrating cells.
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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".