A remotely operated drug delivery system with an electrolytic pump and a thermo-responsive valve
Bibliographic record
Abstract
Implantable drug delivery devices are becoming attractive due to their abilities of targeted and controlled dose release. Currently, two important issues are functional lifetime and non-controlled drug diffusion. In this work, we present a drug delivery device combining an electrolytic pump and a thermo-responsive valve, which are both remotely controlled by an electromagnetic field (40.5 mT and 450 kHz). Our proposed device exhibits a novel operation mechanism for long-term therapeutic treatments using a solid drug in reservoir approach. Our device also prevents undesired drug liquid diffusions. When the electromagnetic field is on, the electrolysis-induced bubble drives the drug liquid towards the Poly (N-Isopropylacrylamide) (PNIPAM) valve that consists of PNIPAM and iron micro-particles. The heat generated by the iron micro-particles causes the PNIPAM to shrink, resulting in an open valve. When the electromagnetic field is turned off, the PNIPAM starts to swell. In the meantime, the bubbles are catalytically recombined into water, reducing the pressure inside the pumping chamber, which leads to the refilling of the fresh liquid from outside the device. A catalytic reformer is included, allowing more liquid refilling during the limited valve's closing time. The amount of body liquid that refills the drug reservoir can further dissolve the solid drug, forming a reproducible drug solution for the next dose. By repeatedly turning on and off the electromagnetic field, the drug dose can be cyclically released, and the exit port of the device is effectively 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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".