Aptamer-Based Biosensors for Environmental Monitoring
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Due to their relative synthetic and chemical simplicity compared to antibodies, aptamers afford enhanced stability and functionality for the detection of environmental contaminants and for use in environmental monitoring. Furthermore, nucleic acid aptamers can be selected for toxic targets which may prove difficult for antibody development. Of particular relevance, aptamers have been selected and used to develop biosensors for environmental contaminants such as heavy metals, small-molecule agricultural toxins, and water-borne bacterial pathogens. This review will focus on recent aptamer-based developments for the detection of diverse environmental contaminants. Within this domain, aptamers have been combined with other technologies to develop biosensors with various signal outputs. The goal of much of this work is to develop cost-effective, user-friendly detection methods that can complement or replace traditional environmental monitoring strategies. This review will highlight recent examples in this area. Additionally, with innovative developments such as wearable devices, sentinel materials, and lab-on-a-chip designs, there exists significant potential for the development of multifunctional aptamer-based biosensors for environmental monitoring. Examples of these technologies will also be highlighted. Finally, a critical perspective on the field, and thoughts on future research directions will be offered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| 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 | 0.001 | 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 it