Permittivity-Inspired Microwave Resonator-Based Biosensor Based on Integrated Passive Device Technology for Glucose Identification

In this study, we propose a high-performance resonator-based biosensor for mediator-free glucose identification. The biosensor is characterized by an air-bridge capacitor and fabricated via integrated passive device technology on gallium arsenide (GaAs) substrate. The exterior design of the structure is a spiral inductor with the air-bridge providing a sensitive surface, whereas the internal capacitor improves indicator performance. The sensing relies on repolarization and rearrangement of surface molecules, which are excited by the dropped sample at the microcosmic level, and the resonance performance variation corresponds to the difference in glucose concentration at the macroscopic level. The air-bridge capacitor in the modeled RLC circuit serves as a bio-recognition element to glucose concentration (εglucoseC0), generating resonant frequency shifts at 0.874 GHz and 1.244 GHz for concentrations of 25 mg/dL and 300 mg/dL compared to DI water, respectively. The proposed biosensor exhibits excellent sensitivity at 1.38 MHz per mg/dL with a wide detection range for glucose concentrations of 25–300 mg/dL and a low detection limit of 24.59 mg/dL. Additionally, the frequency shift and concentration are highly linear with a coefficient of determination of 0.98823. The response time is less than 3 s. We performed multiple experiments to verify that the surface morphology reveals no deterioration and chemical binding, thus validating the reusability and reliability of the proposed biosensor.

Intercalation in 2D transition metal chalcogenides: interlayer engineering and applications

Intercalation is basically a process of putting one or multiple guest elements in the van der Waals (vdW) gaps of a parent crystal in a reversible way. Two-dimensional (2D) materials showed great promise for different intercalant species ranging from organic molecules to ions. Apart from graphene, the most studied 2D materials are the transition metal di-chalcogenides (TMDs). The intercalation in TMDs has reinvented the strategies beyond graphene in 2D structure in material science, materials engineering, chemistry, and physics. This review deals with the possible mechanism as well as the window that intercalation can open for compact and ultrathin device technology. Modulation of the physicochemical properties in the intercalated TMDs has been thoroughly reviewed. Finally, the device performance, especially energy storage and energy harvesting devices, has been evaluated, and specific issues have been chalked out that need attention for future development.

Therapeutic Advancements in the Endovascular Management of Acute Ischemic Stroke

Stroke is the major cause of disability and the second leading cause of death worldwide. Acute ischemic stroke is responsible for ∼85% of all strokes, with 24% to 46% attributable to large‐vessel occlusion, which are typically associated with worse outcomes. Although the initial efforts to develop endovascular treatment for acute ischemic stroke took place over 6 decades ago, critical gaps in device technology and treatment selection existed, resulting in 3 failed randomized clinical trials published in 2013. Fortunately, devices and techniques have dramatically evolved over the past decade, leading to significant improvements in the safety, speed, and completeness of reperfusion. Since 2015, a total of 9 randomized trials have consistently demonstrated an overwhelming benefit to endovascular reperfusion. In this article, we will review the evolution of endovascular treatment for acute ischemic stroke, including the technical and technological advances as well as the perspectives in terms of patient selection and procedural and clinical outcomes of the landmark past and recent trials.

Evaluating Digital Device Technology in Alzheimer's Disease via Artificial Intelligence

The use of digital technologies may help to diagnose Alzheimer's Disease (AD) at the pre-symptomatic stage. However, before implementation into clinical practice, digital measures (DMs) need to be evaluated for their diagnostic benefit compared to established questionnaire-based assessments, such as Mini-Mental State Examination (MMSE) and Functional Activity Questionnaire (FAQ). We analyzed data from smartphone based virtual reality game and Alzheimer's Disease Neuroimaging Initiative (ADNI). We employed an Artificial Intelligence (AI) based approach to elucidate the relationship of DMs to MMSE and FAQ. Furthermore, we used Machine Learning (ML) and statistical methods to assess the diagnostic benefit of DMs compared to questionnaire-based scores. We found non-trivial relationships between DMs, MMSE, and FAQ which can be visualized as a complex network. DM showed a better ability to discriminate between different stages of the disease than questionnaire-based methods. Our results indicate that DMs have the potential to act as a crucial measure in the early diagnosis and staging of AD.

A Disruption in Personal Development: Using Appreciative Inquiry During the Pandemic to Identify Aspirations and Inspire Action

During the pandemic, individuals became isolated and often unemployed, compounding the need for affordable, self-service content that facilitates personal growth and well-being. A journey of personal change which reinforces Appreciative Inquiry’s wholeness principle is being developed in a program that guides users in identifying aspirations and inspiring action towards them. Learners use mobile device technology to practice positive cognition and flourish.