Progress in Molecularly Imprinted Polymers for Biomedical Applications
Bibliographic record
Abstract
BACKGROUND: Molecularly Imprinted Polymers (MIPs), a type of biomimetic materials have attracted considerable interest owing to their cost-effectiveness, good physiochemical stability, favorable specificity and selectivity for target analytes, and long shelf life. These materials are able to mimic natural recognition entities, including biological receptors and antibodies, providing a versatile platform to achieve the desirable functionality for various biomedical applications. OBJECTIVE: In this review article, we introduce the most recent development of MIPs to date. We first highlight the advantages of using MIPs for a broad range of biomedical applications. We then review their various methods of synthesis along with their latest progress in biomedical applications, including biosensing, drug delivery, cell imaging and drug discovery. Lastly, the existing challenges and future perspectives of MIPs for biomedical applications are briefly discussed. CONCLUSION: We envision that MIPs may be used as potential materials for diverse biomedical applications in the near future.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".