The Neurovascular Education and Training in Stroke Management and Acute Reperfusion Therapy (NET SMART) program for advanced practice nursing (APN) offers a first-of-its-kind, academic, postgraduate, fellowship program for APNs that is modeled after physician academic fellowship programs but supported by a flexible Internet-based platform. This article details the rationale, methods, and preliminary results of the NET SMART APN experience, which serves as a unique template for the development of academic postgraduate nursing fellowship programs across a variety of specialty practices.
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http://dx.doi.org/10.1016/j.ccell.2009.09.001 | DOI Listing |
J Mark Access Health Policy
March 2025
BHF Cardiovascular Research Centre, University of Glasgow, Glasgow G12 8TA, UK;
This study illustrates the utility of a mixed-methods approach in assessing the value of an example novel technology-biosensor-integrated self-reporting arteriovenous grafts (smart AVGs). Currently in preclinical development, the device will detect arteriovenous graft stenosis (surveillance-only use case) and treat stenosis (interventional use case). The approach to value assessment adopted in this study was multifaceted, with one stage informing the next and comprised a stakeholder engagement with clinical experts to explore the device's clinical value, a cost-utility analysis (CUA) from a US Medicare perspective to estimate pricing headroom, and an investment model estimating risk-adjusted net present value analysis (rNPVs) to determine commercial viability.
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January 2025
College of Ecology and Environment, Hainan University, Haikou, 570228, China.
Agroforestry systems are known to enhance soil health and climate resilience, but their impact on greenhouse gas (GHG) emissions in rubber-based agroforestry systems across diverse configurations is not fully understood. Here, six representative rubber-based agroforestry systems (encompassing rubber trees intercropped with arboreal, shrub, and herbaceous species) were selected based on a preliminary investigation, including Hevea brasiliensis intercropping with Alpinia oxyphylla (AOM), Alpinia katsumadai (AKH), Coffea arabica (CAA), Theobroma cacao (TCA), Cinnamomum cassia (CCA), and Pandanus amaryllifolius (PAR), and a rubber monoculture as control (RM). Soil physicochemical properties, enzyme activities, and GHG emission characteristics were determined at 0-20 cm soil depth.
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January 2025
School of Computer Science and Engineering, Changchun University of Technology, Changchun, 130102, People's Republic of China.
Atrial fibrillation (AF) is a common arrhythmia disease with a higher incidence rate. The diagnosis of AF is time-consuming. Although many ECG classification models have been proposed to assist in AF detection, they are prone to misclassifying indistinguishable noise signals, and the context information of long-term signals is also ignored, which impacts the performance of AF detection.
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January 2025
Department of Life Science and Biochemical Engineering, Graduate School, SunMoon University, Asan, 31460, Republic of Korea; Genome-based Bio-IT Convergence Institute, Asan, 31460, Republic of Korea; Bio Big Data-based Chungnam Smart Clean Research Leader Training Program, SunMoon University, Asan, 31460, Republic of Korea; Department of Pharmaceutical Engineering and Biotechnology, SunMoon University, Asan, 31460, Republic of Korea. Electronic address:
Laccases are of particular interest in addressing environmental challenges, such as the degradation of triphenylmethane (TPM) dyes, including crystal violet (CV) and Coomassie Brilliant Blue (CBB), which are commonly used in SDS-PAGE for protein visualization. However, these dyes present significant environmental concerns due to their resistance to degradation, which makes their removal from industrial wastewater a major challenge. To address this, the current study investigates the potential of a novel CotA laccase derived from Bacillus sp.
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January 2025
Institute of Agricultural Information Technology, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China.
Identification and diagnosis of tobacco diseases are prerequisites for the scientific prevention and control of these ailments. To address the limitations of traditional methods, such as weak generalization and sensitivity to noise in segmenting tobacco leaf lesions, this study focused on four tobacco diseases: angular leaf spot, brown spot, wildfire disease, and frog eye disease. Building upon the Unet architecture, we developed the Multi-scale Residual Dilated Segmentation Model (MD-Unet) by enhancing the feature extraction module and integrating attention mechanisms.
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