Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3651108 | PMC |
http://dx.doi.org/10.1097/WOX.0b013e31820f8fae | DOI Listing |
A simple and rapid method based on Raman microsphere immunochromatography was developed in this study for the simultaneous detection of influenza A and B viruses and SARS-CoV-2 on a single test T-line. Three types of Raman microspheres with different Raman characteristics were used as the signal sources and were labelled with monoclonal antibodies against FluA, FluB and SARS-CoV-2, respectively. A mixture of antibodies containing anti-FluA monoclonal antibody, anti-FluB monoclonal antibody and anti-SARS-CoV-2 was sprayed on the detection line (T), and goat polyclonal antibody to chicken (IgY) encapsulated on the quality control line (C), for qualitative detection of these three viruses by the double antibody sandwich method.
View Article and Find Full Text PDFOphthalmic Plast Reconstr Surg
November 2024
Division of Ophthalmic Plastic and Reconstructive Surgery, Department of Ophthalmology and Visual Sciences, Federal University of São Paulo, São Paulo, Brazil.
J Clin Sleep Med
November 2024
Indiana University School of Medicine, Department of Internal Medicine, Division of General Internal Medicine.
Objective: To evaluate and determine the prevalence of ingredients in over-the-counter (OTC) nasal sprays.
Study Design: Cross-sectional.
Setting: Retail pharmacies.
Asia Pac J Ophthalmol (Phila)
October 2024
Xiamen University affiliated Xiamen Eye Center, Fujian Provincial Key Laboratory of Ophthalmology and Visual Science, Fujian Engineering and Research Center of Eye Regenerative Medicine, Eye Institute of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian 361005, China; Department of Ophthalmology, the First Affiliated Hospital of University of South China, Hengyang, Hunan 421001, China; Department of Ophthalmology, Xiang'an Hospital of Xiamen University, Xiamen, Fujian 361005, China. Electronic address:
Purpose And Design: This study aimed to evaluate the risk of drug-related dry eye using real-world data, underscoring the significance of tracing pharmacological etiology for distinct clinical types of dry eye.
Methods: Analyzing adverse event reports in the Food and Drug Administration Adverse Event Reporting System (FAERS) from January 2004 to September 2023, we employed disproportionality analysis and the Bayesian confidence propagation neural network algorithm. The analysis involved categorizing drugs causing dry eye, assessing risk levels, and conducting segmental assessments based on the time of onset of drug-related dry eye adverse reactions.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!