Capillary-Assisted Molecular Pendulum Bioanalysis
Bibliographic record
Abstract
The development of robust biosensing strategies that can be easily implemented in everyday life remains a challenge for the future of modern biosensor research. While several reagentless approaches have attempted to address this challenge, they often achieve user-friendliness through sacrificing sensitivity or universality. While acceptable for certain applications, these trade-offs hinder the widespread adoption of reagentless biosensing technologies. Here, we report a novel approach to reagentless biosensing that achieves high sensitivity, rapid detection, and universality using the SARS-CoV-2 virus as a model target. Universality is achieved by using nanoscale molecular pendulums, which enables reagentless electrochemical biosensing through a variable antibody recognition element. Enhanced sensitivity and rapid detection are accomplished by incorporating the coffee-ring phenomenon into the sensing scheme, allowing for target preconcentration on a ring-shaped electrode. Using this approach, we obtained limits of detection of 1 fg/mL and 20 copies/mL for the SARS-CoV-2 nucleoproteins and viral particles, respectively. In addition, clinical sample analysis showed excellent agreement with Ct values from PCR-positive SARS-CoV-2 patients.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".