Development of Biocompatible Aptamer Films as Smart Materials for Novel Fertilizer Systems
Bibliographic record
Abstract
Aptamers are short, single stranded nucleic acids that fold into welldefined 3D structures which bind to a single target molecule with affinities and specificities that can rival or in some cases exceed those of antibodies.Unlike antibodies, aptamers can be chemically synthesized, which eliminates the need for animals, and can be used under non-physiological as well as physiological conditions.Due to their chemical nature, aptamers can be readily modified with reporter molecules and other functional groups making them versatile analytical tools with great promise in biotechnological applications.The compatibility of aptamers with nanostructures such as thin films, in combination with their affinity, selectivity, and conformational changes upon target interaction could set the foundation for the development of smart materials.This research will focus on development of a biocompatible aptamer-polyelectrolyte film system for use in controlled-release applications.We will study the efficacy and feasibility of this system.In doing this, we demonstrated the ability of the sulforhodamine B aptamer to function while sequestered in a chitosan-hyaluronan film matrix (Chapter 2).Our results also suggest that deposition conditions such as rinsing time and volume play a strong role in the internal film interactions and growth mechanism.As a secondary objective, the protective role of the polyelectrolytes against nuclease-mediated aptamer degradation was investigated (Chapter 3).Degradation remains one of the biggest challenges in nucleic acid-based technologies.This research has the potential to revolutionize materials used in iii controlled-release platforms with possible application to fertilizer systems which will be discussed.iv
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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 | 0.001 |
| 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".