ArticleJournal of nanobiotechnology2022
Repellent active ingredients encapsulated in polymeric nanoparticles: potential alternative formulations to control arboviruses.
Article in Journal of nanobiotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 15 citations in OpenAlex.
- Applied Nanobiotechnology for Vector-borne Disease Management: Drug Delivery, Diagnostics, and Sustainable Vector Control.Applied biochemistry and biotechnology · 2026Review
- Harnessing insect-derived oils for enhanced efficacy of plant-based repellents against disease-transmitting mosquitoes.Scientific reports · 2026Article
- Reducing Close Encounters with Insect Pests and Vectors: The Past, Present and Future of Insect Repellents.Insects · 2026Review
- Insecticidal Potential ofPlants (Basel, Switzerland) · 2025Article
- A Review of Botanical Extracts with Repellent and Insecticidal Activity and Their Suitability for Managing Mosquito-Borne Disease Risk in Mexico.Pathogens (Basel, Switzerland) · 2024Review
- Nanocomposite Gels Loaded with Flurbiprofen: Characterization and Skin Permeability Assessment in Different Skin Species.Gels (Basel, Switzerland) · 2024Article
- Tiny Green Army: Fighting Malaria with Plants and Nanotechnology.Pharmaceutics · 2024Review
- Poloxamer-based nanogels as delivery systems: how structural requirements can drive their biological performance?Biophysical reviews · 2023Review
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
Abstract
Dengue, yellow fever, Chinkungunya, Zika virus, and West Nile fever have infected millions and killed a considerable number of humans since their emergence. These arboviruses are transmitted by mosquito bites and topical chemical repellents are the most commonly used method to protect against vector arthropod species. This study aimed to develop a new generation of repellent formulations to promote improved arboviruses transmission control. A repellent system based on polycaprolactone (PCL)-polymeric nanoparticles was developed for the dual encapsulation of IR3535 and geraniol and further incorporation into a thermosensitive hydrogel. The physicochemical and morphological parameters of the prepared formulations were evaluated by dynamic light scattering (DLS), nano tracking analysis (NTA), atomic force microscopy (AFM). In vitro release mechanisms and permeation performance were evaluated before and after nanoparticles incorporation into the hydrogels. FTIR analysis was performed to evaluate the effect of formulation epidermal contact. Potential cytotoxicity was evaluated using the MTT reduction test and disc diffusion methods. The nanoparticle formulations were stable over 120 days with encapsulation efficiency (EE) of 60% and 99% for IR3535 and geraniol, respectively. AFM analysis revealed a spherical nanoparticle morphology. After 24 h, 7 ± 0.1% and 83 ± 2% of the GRL and IR3535, respectively, were released while the same formulation incorporated in poloxamer 407 hydrogel released 11 ± 0.9% and 29 ± 3% of the loaded GRL and IR3535, respectively. GRL permeation from PCL nanoparticles and PCL nanoparticles in the hydrogel showed similar profiles, while IR3535 permeation was modulated by formulation compositions. Differences in IR3535 permeated amounts were higher for PCL nanoparticles in the hydrogels (36.9 ± 1.1 mg/cm
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.