Micro and Nanoscale Technologies for Diagnosis of Viral Infections
Bibliographic record
Abstract
Viral infection is one of the leading causes of mortality worldwide. The growth of globalization significantly increases the risk of virus spreading, making it a global threat to future public health. In particular, the ongoing coronavirus disease 2019 (COVID-19) pandemic outbreak emphasizes the importance of devices and methods for rapid, sensitive, and cost-effective diagnosis of viral infections in the early stages by which their quick and global spread can be controlled. Micro and nanoscale technologies have attracted tremendous attention in recent years for a variety of medical and biological applications, especially in developing diagnostic platforms for rapid and accurate detection of viral diseases. This review addresses advances of microneedles, microchip-based integrated platforms, and nano- and microparticles for sampling, sample processing, enrichment, amplification, and detection of viral particles and antigens related to the diagnosis of viral diseases. Additionally, methods for the fabrication of microchip-based devices and commercially used devices are described. Finally, challenges and prospects on the development of micro and nanotechnologies for the early diagnosis of viral diseases are highlighted.
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 | 0.000 |
| 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 | 0.000 | 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 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".