We investigated the frequency based mediator-free glucose sensor in the radio-frequency (RF) range. Frequency dependent power signal showed clear dependence on the glucose concentration with free enzymatic condition. Also, the passive electrical components such as the resistance, inductance, shunt conductance, and capacitance were extracted based on the transmission line model for further analysis. These various parameters proposed by the signal processing provided more effective verification for instant multi-components in-situ readings without any added supporters. Additionally the residual signal (RS), impedance (Z), and propagation constant (γ) were also calculated from measured S-parameters for glucose analysis. These parameters basically showed amplitude variation and interestingly, some parameters such as inductance and impedance showed frequency shift of resonance dip. The results support that the frequency based sensing technique including the parameter based analysis can enable effective multi-dimensional detection of glucose. Moreover, this technique showed that glucose sensing is also possible over a diabetic patient's serum.
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http://dx.doi.org/10.1016/j.bios.2013.10.053 | DOI Listing |
Int J Med Inform
January 2025
Rheumatology and Allergy Clinical Epidemiology Research Center and Division of Rheumatology, Allergy, and Immunology, and Mongan Institute, Department of Medicine, Massachusetts General Hospital Boston MA USA. Electronic address:
Background: ANCA-associated vasculitis (AAV) is a rare but serious disease. Traditional case-identification methods using claims data can be time-intensive and may miss important subgroups. We hypothesized that a deep learning model analyzing electronic health records (EHR) can more accurately identify AAV cases.
View Article and Find Full Text PDFJ Infect Dev Ctries
December 2024
Faculdade de Medicina de Campos, Campos dos Goytacazes, Brazil.
Introduction: Despite efforts by health organizations to share evidence-based information, fake news hindered the promotion of social distancing and vaccination during the coronavirus disease 2019 (COVID-19) pandemic. This study analyzed COVID-19 knowledge and practices in a vulnerable area in northern Rio de Janeiro, acknowledging the influence of the complex social and economic landscape on public health perceptions.
Methodology: This cross-sectional study was conducted in Novo Eldorado - a low-income, conflict-affected neighborhood in Campos dos Goytacazes - using a structured questionnaire, following the peak of COVID-19 deaths in Brazil (July-December 2021).
J Infect Dev Ctries
December 2024
Institute of Public Health, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Introduction: Significant challenges to implementing international health regulations (IHR) at points of entry (PoEs) have been highlighted by the coronavirus disease 2019 (COVID-19) pandemic. Better assessment of the capacities of the PoEs may promote focused interventions. This study aimed to assess the capacities and practices at PoEs.
View Article and Find Full Text PDFIntroduction: China implemented a dynamic zero-COVID strategy to curb viral transmission in response to the coronavirus disease 2019 (COVID-19) pandemic. This strategy was designed to inhibit mutation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for COVID-19. This study explores the dynamics of viral evolution under stringent non-pharmaceutical interventions (NPIs) through real-world observations.
View Article and Find Full Text PDFLipids Health Dis
January 2025
Department of Neurosurgery, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213000, China.
Background: Stroke has emerged as an escalating public health challenge among middle-aged and older individuals in China, closely linked to glycolipid metabolic abnormalities. The Hemoglobin A1c/High-Density Lipoprotein Cholesterol (HbA1c/HDL-C) ratio, an integrated marker of glycolipid homeostasis, may serve as a novel predictor of stroke risk.
Methods: Our investigation utilized data from the China Health and Retirement Longitudinal Study cohort (2011-2018).
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