Background: Emtricitabine (ETC), tenofovir disoproxil fumarate (TNF), elvitegravir (EVG), and cobicistat (CBS) are antiviral drugs used to treat human immunodeficiency virus (HIV) infections.
Objective: To develop chemometric-aided UV spectrophotometric methods for concurrent estimation of the aforementioned drugs used to treat HIV. This method can be used to reduce modification of the calibration model by assessing the absorbance at various points in the zero-order spectra within the selected wavelength range. Additionally, it eliminates interfering signals and provides sufficient resolution in multi-component systems.
Methods: Two chemometric-assisted UV spectrophotometric methods, namely, partial least-squares (PLS) and principal component regression (PCR) models, were established for the concurrent assessment of EVG, CBS, TNF, and ETC in tablet formulations. The proposed methods were applied to decrease complexity of overlapped spectra and to achieve maximum sensitivity and the lowest error. These approaches were performed in accordance with International Council on Harmonization (ICH) criteria and compared to the reported HPLC method.
Results: The proposed methods were used to assess EVG, CBS, TNF, and ETC in the ranges of 5-30, 5-30 , 5-50, and 5-50 µg/mL, respectively, with an excellent correlation coefficient (r2 ≥ 0.998). The accuracy and precision results were found to be within the acceptable limits. No statistical difference was observed between the proposed and reported studies.
Conclusion: The chemometric-aided UV spectrophotometric approaches could be considered as alternatives to chromatographic procedures in the pharmaceutical industry for routine analysis and testing of readily accessible commercial formulations.
Highlights: Novel chemometric-assisted UV spectrophotometric techniques were developed for assessment of multicomponent antiviral combinations in single-tablet formulations. The proposed methods were performed without using harmful solvents, tedious preparation, or expensive instruments. The proposed methods were compared statistically with a reported HPLC method. Assessment of EVG, CBS, TNF, and ETC was performed without interference from excipients in their multicomponent formulations.
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http://dx.doi.org/10.1093/jaoacint/qsad067 | DOI Listing |
Biomed Phys Eng Express
January 2025
National School of Electronics and Telecommunication of Sfax, Sfax rte mahdia, sfax, sfax, 3012, TUNISIA.
Deep learning has emerged as a powerful tool in medical imaging, particularly for corneal topographic map classification. However, the scarcity of labeled data poses a significant challenge to achieving robust performance. This study investigates the impact of various data augmentation strategies on enhancing the performance of a customized convolutional neural network model for corneal topographic map classification.
View Article and Find Full Text PDFJMIR Form Res
January 2025
Smith School of Business, Queen's University, Kingston, ON, Canada.
Background: Depression significantly impacts an individual's thoughts, emotions, behaviors, and moods; this prevalent mental health condition affects millions globally. Traditional approaches to detecting and treating depression rely on questionnaires and personal interviews, which can be time consuming and potentially inefficient. As social media has permanently shifted the pattern of our daily communications, social media postings can offer new perspectives in understanding mental illness in individuals because they provide an unbiased exploration of their language use and behavioral patterns.
View Article and Find Full Text PDFInteract J Med Res
January 2025
Department of Nursing Science, Diagnostics in Healthcare and eHealth, Trier University, Trier, Germany.
Background: Psychoeducation positively influences the psychological components of chronic low back pain (CLBP) in conventional treatments. The digitalization of health care has led to the discussion of virtual reality (VR) interventions. However, CLBP treatments in VR have some limitations due to full immersion.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
School of Computer Science, University of Technology Sydney, Sydney, Australia.
The integration of artificial intelligence (AI) into health communication systems has introduced a transformative approach to public health management, particularly during public health emergencies, capable of reaching billions through familiar digital channels. This paper explores the utility and implications of generalist conversational artificial intelligence (CAI) advanced AI systems trained on extensive datasets to handle a wide range of conversational tasks across various domains with human-like responsiveness. The specific focus is on the application of generalist CAI within messaging services, emphasizing its potential to enhance public health communication.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Shenzhen, China.
Background: With the rapid expansion of social media platforms, the demand for health information has increased substantially, leading to innovative approaches and new opportunities in health education.
Objective: This study aims to analyze the characteristics of articles published on the "Dr Ding Xiang" WeChat official account (WOA), one of the most popular institutional accounts on the WeChat platform, to identify factors influencing readership engagement and to propose strategies for enhancing the effectiveness of health information dissemination.
Methods: A total of 5286 articles published on the "Dr Ding Xiang" WOA from January 2021 to December 2021 were collected and analyzed.
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