Several viral infectious diseases appear limitless since the beginning of the 21stcentury, expanding into pandemic lengths. Thus, there are extensive efforts to provide more efficient means of diagnosis, a better understanding of acquired immunity, and improved monitoring of inflammatory biomarkers, as these are all crucial for controlling the spread of infection while aiding in vaccine development and improving patient outcomes. In this regard, various biosensors have been developed recently to streamline pathogen and immune response detection by addressing the limitations of traditional methods, including isothermal amplification‐based systems and lateral flow assays. This review explores state‐of‐the‐art biosensors for detecting viral pathogens, serological assays, and inflammatory biomarkers from the material perspective, by discussing their advantages, limitations, and further potential regarding their analytical performance, clinical utility, and point‐of‐care adaptability. Additionally, next‐generation biosensing technologies that offer better sensitivity and selectivity, and easy handling for end‐users are highlighted. An emerging example of these next‐generation biosensors are those powered by novel synthetic biology tools, such as clustered regularly interspaced short palindromic repeats (CRISPR) with CRISPR‐associated proteins (Cas), in combination with integrated point‐of‐care devices. Lastly, the current challenges are discussed and a roadmap for furthering these advanced biosensing technologies to manage future pandemics is provided.
Hypertension is associated with more end-organ damage, cardiovascular events, and disability-adjusted life years lost in the United States compared with all other modifiable risk factors. Several guidelines and scientific statements now endorse the use of out-of-office blood pressure (BP) monitoring with ambulatory BP monitoring or home BP monitoring to confirm or exclude hypertension status based on office BP measurement. Current ambulatory or home BP monitoring devices have been reliant on the placement of a BP cuff, typically on the upper arm, to measure BP. There are numerous limitations to this approach. Cuff-based BP may not be well-tolerated for repeated measurements as is utilized with ambulatory BP monitoring. Furthermore, improper technique, including incorrect cuff placement or use of the wrong cuff size, may lead to erroneous readings, affecting diagnosis and management of hypertension. Compared with devices that utilize a cuff, cuffless BP devices may overcome challenges related to technique, tolerability, and overall utility in the outpatient setting. However, cuffless devices have several potential limitations that limit its routine use for the diagnosis and management of hypertension. The review discusses the different approaches for determining BP using various cuffless devices including engineering aspects of cuffless device technologies, validation protocols to test accuracy of cuffless devices, potential barriers to widespread implementation, and future areas of research. This review is intended for the clinicians who utilize out-of-office BP monitoring for the diagnosis and management of hypertension.
more » « less- NSF-PAR ID:
- 10366857
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- American Journal of Hypertension
- Volume:
- 35
- Issue:
- 5
- ISSN:
- 0895-7061
- Page Range / eLocation ID:
- p. 380-387
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Zama, Fabiana (Ed.)Despite the world-wide prevalence of hypertension, there is a lack in open-source software for analyzing blood pressure data. The R package bp fills this gap by providing functionality for blood pressure data processing, visualization, and feature extraction. In addition to the comprehensive functionality, the package includes six sample data sets covering continuous arterial pressure data (AP), home blood pressure monitoring data (HBPM) and ambulatory blood pressure monitoring data (ABPM), making it easier for researchers to get started. The R package bp is publicly available on CRAN and at https://github.com/johnschwenck/bp .more » « less
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