Making frequent large-scale screenings for several diseases economically affordable would represent a real breakthrough in healthcare. One of the most promising routes to pursue such an objective is developing rapid, non-invasive, and cost-effective home-testing devices. As a first step toward a diagnostic revolution, glycemia self-monitoring represents a solid base to start exploring new diagnostic strategies. Glucose self-monitoring is improving people's life quality in recent years; however, current approaches still present vast room for improvement. In most cases, they still involve invasive sampling processes (i.e., finger-prick), quite discomforting for frequent measurements, or implantable devices which are costly and commonly dedicated to selected chronic patients, thus precluding large-scale monitoring. Thanks to their unique physicochemical properties, nanoparticles hold great promises for the development of rapid colorimetric devices. Here, we overview and analyze the main instrument-free nanosensing strategies reported so far for glucose detection, highlighting their advantages/disadvantages in view of their implementation as cost-effective rapid home-testing devices, including the potential use of alternative non-invasive biofluids as samples sources.
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http://dx.doi.org/10.3390/ma14081978 | DOI Listing |
EBioMedicine
January 2025
Department of Chemistry, Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology, Tsinghua University, New Cornerstone Science Foundation, Beijing, 100084, China. Electronic address:
Background: The widespread and evolution of RNA viruses, such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), highlights the importance of fast identification of virus subtypes, particularly in non-laboratory settings. Rapid and inexpensive at-home testing of viral nucleic acids with single-base resolution remains a challenge.
Methods: Topologically constrained DNA ring is engineered as substrates for the trans-cleavage of Cas13a to yield an accelerated post isothermal amplification.
Sens Diagn
December 2024
Department of Bioengineering, Rice University Houston TX 77030 USA
CRISPR-Cas-based lateral flow assays (LFAs) have emerged as a promising diagnostic tool for ultrasensitive detection of nucleic acids, offering improved speed, simplicity and cost-effectiveness compared to polymerase chain reaction (PCR)-based assays. However, visual interpretation of CRISPR-Cas-based LFA test results is prone to human error, potentially leading to false-positive or false-negative outcomes when analyzing test/control lines. To address this limitation, we have developed two neural network models: one based on a fully convolutional neural network and the other on a lightweight mobile-optimized neural network for automated interpretation of CRISPR-Cas-based LFA test results.
View Article and Find Full Text PDFACS Sens
January 2025
School of Materials Science and Engineering, Guangzhou Key Laboratory of Flexible Electronic Materials and Wearable Devices, Key Laboratory for Polymeric Composite and Functional Materials of Ministry of Education, State Key Laboratory of Optoelectronic Materials and Technologies, Sun Yat-sen University, Guangzhou 510275, People's Republic of China.
Steroid hormones, especially progesterone (P), estradiol (E), and testosterone (T), are key bioactive regulators in various female physiological processes, including growth and development, ovulation, and the reproductive cycle, as well as metabolism and mental health. As lipophilic molecules produced in sex glands, these steroid female hormones can be transported through blood vessels into various body fluids such as saliva, sweat, and urine. However, the ultralow concentration of steroid hormones down to picomolar (pM) level necessitates great demands for ultrasensitive but low-cost analytic tools to implement accurate, point-of-care or even continuous monitoring in a user-friendly fashion.
View Article and Find Full Text PDFNeurology
January 2025
From the Department of Neurology (A.R.R., C.A., S.K.), Miller School of Medicine, University of Miami, FL; University of California, San Diego (K.A.G., H.M.G.); Wayne State University (W.T.), Detroit, MI; Institute of Minority Health Research (M.D.), University of Illinois College of Medicine, Chicago; Department of Psychology (L.C.G., A.M.S., G.A.T.), San Diego State University, CA; Albert Einstein College of Medicine (C.I.I., R.B.L.), New York, NY; Department of Medicine (S.R.P.), University of Pittsburgh School of Medicine, PA; Brigham Women's Hospital (S.R.), Harvard School of Medicine, Boston, MA; Gillings School of Global Public Health (D.S.-A.), University of North Carolina, Chapel Hill; Department of Neurology and Rehabilitation (F.D.T.), University of Illinois College of Medicine, Chicago; and University of California, Davis (C.S.D.).
Front Digit Health
November 2024
Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA, United States.
Introduction: Current preoperative exam guidelines utilize extensive lab tests, including blood tests and urine analysis, which are crucial for assessing surgical readiness. However, logistical challenges, especially for patients traveling long distances for high-quality medical care, create significant delays and burdens. This study aims to address these challenges by applying a previously developed point-of-care (POC) device system to perform accurate and rapid lab tests.
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