Polymer-Based Microneedles for Decentralized Diagnostics and Monitoring: Concepts, Potentials, and Challenges
Bibliographic record
Abstract
Owing to their ability to breach the skin in a minimally invasive manner, microneedles (MNs) have seen increased interest for potential diagnostic applications. This is particularly true of polymeric MNs, as the structural and functional properties of the polymer materials used in their fabrication can provide unparalleled advantages and open the door to the diagnostic and monitoring strategies of the future. Polymeric MNs used for diagnostic applications can be broadly divided into swelling MNs for the extraction of dermal interstitial fluid (ISF), surface-functionalized MNs for direct analyte detection, and dissolving MNs for the delivery of diagnostic agents to the skin. In this perspective, we use emblematic examples to highlight the major recent advances in this field and provide commentary and insight into the potential opportunities and remaining challenges faced by each of these MN classes, with a specific focus on the role of materials research in the further development of this field.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".