Emerging Advances of Nanotechnology in Drug and Vaccine Delivery against Viral Associated Respiratory Infectious Diseases (VARID)
Bibliographic record
Abstract
Viral-associated respiratory infectious diseases are one of the most prominent subsets of respiratory failures, known as viral respiratory infections (VRI). VRIs are proceeded by an infection caused by viruses infecting the respiratory system. For the past 100 years, viral associated respiratory epidemics have been the most common cause of infectious disease worldwide. Due to several drawbacks of the current anti-viral treatments, such as drug resistance generation and non-targeting of viral proteins, the development of novel nanotherapeutic or nano-vaccine strategies can be considered essential. Due to their specific physical and biological properties, nanoparticles hold promising opportunities for both anti-viral treatments and vaccines against viral infections. Besides the specific physiological properties of the respiratory system, there is a significant demand for utilizing nano-designs in the production of vaccines or antiviral agents for airway-localized administration. SARS-CoV-2, as an immediate example of respiratory viruses, is an enveloped, positive-sense, single-stranded RNA virus belonging to the coronaviridae family. COVID-19 can lead to acute respiratory distress syndrome, similarly to other members of the coronaviridae. Hence, reviewing the current and past emerging nanotechnology-based medications on similar respiratory viral diseases can identify pathways towards generating novel SARS-CoV-2 nanotherapeutics and/or nano-vaccines.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".