Alzheimer's disease (AD) is a major form of senile dementia, characterized by progressive memory and neuronal loss combined with cognitive impairment. AD is the most common neurodegenerative disease ...worldwide, affecting one-fifth of those aged over 85 years. Recent therapeutic approaches have been strongly influenced by five neuropathological hallmarks of AD: acetylcholine deficiency, glutamate excitotoxicity, extracellular deposition of amyloid-β (Aβ plague), formation of intraneuronal neurofibrillary tangles (NTFs), and neuroinflammation. The lowered concentrations of acetylcholine (ACh) in AD result in a progressive and significant loss of cognitive and behavioral function. Current AD medications, memantine and acetylcholinesterase inhibitors (AChEIs) alleviate some of these symptoms by enhancing cholinergic signaling, but they are not curative. Since 2003, no new drugs have been approved for the treatment of AD. This article focuses on the current research in clinical trials targeting the neuropathological findings of AD including acetylcholine response, glutamate transmission, Aβ clearance, tau protein deposits, and neuroinflammation. These investigations include acetylcholinesterase inhibitors, agonists and antagonists of neurotransmitter receptors, β-secretase (BACE) or γ-secretase inhibitors, vaccines or antibodies targeting Aβ clearance or tau protein, as well as anti-inflammation compounds. Ongoing Phase III clinical trials via passive immunotherapy against Aβ peptides (crenezumab, gantenerumab, and aducanumab) seem to be promising. Using small molecules blocking 5-HT
serotonin receptor (intepirdine), inhibiting BACE activity (E2609, AZD3293, and verubecestat), or reducing tau aggregation (TRx0237) are also currently in Phase III clinical trials. We here systemically review the findings from recent clinical trials to provide a comprehensive review of novel therapeutic compounds in the treatment and prevention of AD.
This study aimed to assess family function in home care for older adults. Understanding family dynamics is essential for providing quality care to older adults choosing to age in place.
In a ...cross-sectional study, 53 patients aged 65 or older receiving home care were evaluated, along with four home care nurses. The General Function of Family Assessment Device (FAD-GF) was used for self-assessment to examine family resources.
Only 5.7% of older adults reported good family function. Strong correlations were found between assessments by nurses and older adults. Among the six aspects of family function, "problem solving," "communication," "affective responsiveness," and the overall results showed no disparities between the evaluations of older adults and nurses.
Home care nurses can effectively assess family function using the FAD-GF, particularly after six months of care. This assessment can help identify family issues and enhance home care quality through nurse training in FAD-GF application.
GPU Computing Gems Emerald Edition offers practical techniques in parallel computing using graphics processing units (GPUs) to enhance scientific research. The first volume in Morgan Kaufmann's ...Applications of GPU Computing Series, this book offers the latest insights and research in computer vision, electronic design automation, and emerging data-intensive applications. It also covers life sciences, medical imaging, ray tracing and rendering, scientific simulation, signal and audio processing, statistical modeling, video and image processing.This book is intended to help those who are facing the challenge of programming systems to effectively use GPUs to achieve efficiency and performance goals. It offers developers a window into diverse application areas, and the opportunity to gain insights from others' algorithm work that they may apply to their own projects. Readers will learn from the leading researchers in parallel programming, who have gathered their solutions and experience in one volume under the guidance of expert area editors. Each chapter is written to be accessible to researchers from other domains, allowing knowledge to cross-pollinate across the GPU spectrum. Many examples leverage NVIDIA's CUDA parallel computing architecture, the most widely-adopted massively parallel programming solution. The insights and ideas as well as practical hands-on skills in the book can be immediately put to use.Computer programmers, software engineers, hardware engineers, and computer science students will find this volume a helpful resource. For useful source codes discussed throughout the book, the editors invite readers to the following website: Covers the breadth of industry from scientific simulation and electronic design automation to audio / video processing, medical imaging, computer vision, and moreMany examples leverage NVIDIA's CUDA parallel computing architecture, the most widely-adopted massively parallel programming solutionOffers insights and ideas as well as practical "hands-on" skills you can immediately put to use
Radiological heart damage (RIHD) is damage caused by unavoidable irradiation of the heart during chest radiotherapy, with a long latency period and a progressively increasing proportion of delayed ...cardiac damage due to conventional doses of chest radiotherapy. There is a risk of inducing diseases such as acute/chronic pericarditis, myocarditis, delayed myocardial fibrosis and damage to the cardiac conduction system in humans, which can lead to myocardial infarction or even death in severe cases. This paper details the pathogenesis of RIHD and gives potential targets for treatment at the molecular and cellular level, avoiding the drawbacks of high invasiveness and immune rejection due to drug therapy, medical device implantation and heart transplantation. Injectable hydrogel therapy has emerged as a minimally invasive tissue engineering therapy to provide necessary mechanical support to the infarcted myocardium and to act as a carrier for various bioactive factors and cells to improve the cellular microenvironment in the infarcted area and induce myocardial tissue regeneration. Therefore, this paper combines bioactive factors and cellular therapeutic mechanisms with injectable hydrogels, presents recent advances in the treatment of cardiac injury after RIHD with different injectable gels, and summarizes the therapeutic potential of various types of injectable hydrogels as a potential solution.
The short-range correlation (SRC) induced by the tensor force in the isosinglet neutron-proton interaction channel leads to a high-momentum tail (HMT) in the single-nucleon momentum distributions ...n(k) in nuclei. Owing to the remaining uncertainties about the tensor force, the shape of the nucleon HMT may be significantly different from the dilute interacting Fermi gas model prediction n(k) ~ 1/k4 similar to the HMT in cold atoms near the unitary limit. Within an isospin- and momentum-dependent Boltzmann-Uehling-Uhlenbeck transport model incorporating approximately the nucleon HMT, we investigate hard photon emissions in 14N + 12C and 48Ca + 124Sn reactions at beam energies around the Fermi energy. Imprints of different shapes of the HMT on the energy spectrum, angular distribution and transverse momentum spectrum of hard photons are studied. Furthermore, while the angular distribution does not carry any information about the shape of the nucleon HMT, the energy spectra and especially the mid-rapidity transverse momentum spectra of hard photons are found to bare strong imprints of the shapes of nucleon HMTs in the two colliding nuclei.
The exploding complexity and computation efficiency requirements of applications are stimulating a strong demand for hardware acceleration with heterogeneous platforms such as FPGAs. However, a ...high-quality FPGA design is very hard to create and optimize as it requires FPGA expertise and a long design iteration time. In contrast, software applications are typically developed in a short development cycle, with high-level languages like Python, which have much higher levels of abstraction than all existing hardware design flows. To close this gap between hardware design flows and software applications, and simplify FPGA programming, we create PyLog, a high-level, algorithm-centric Python-based programming and synthesis flow for FPGA. PyLog is powered by a set of compiler optimization passes and a type inference system to generate high-quality hardware design. It abstracts away the implementation details, and allows designers to focus on algorithm specification. PyLog takes in Python functions, generates PyLog intermediate representation (PyLog IR), performs several optimization passes, including pragma insertion, design space exploration, and memory customization, etc., and creates complete FPGA system designs. PyLog also has a runtime that allows users to run the PyLog code directly on the target FPGA platform without any extra code development. The whole design flow is automated. Evaluation shows that PyLog significantly improves FPGA design productivity and generates highly efficient FPGA designs that outperform highly optimized CPU implementation and state-of-the-art FPGA implementation by <inline-formula><tex-math notation="LaTeX">3.17\times</tex-math> <mml:math><mml:mrow><mml:mn>3</mml:mn><mml:mo>.</mml:mo><mml:mn>17</mml:mn><mml:mo>×</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="huang-ieq1-3123465.gif"/> </inline-formula> and <inline-formula><tex-math notation="LaTeX">1.24\times</tex-math> <mml:math><mml:mrow><mml:mn>1</mml:mn><mml:mo>.</mml:mo><mml:mn>24</mml:mn><mml:mo>×</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="huang-ieq2-3123465.gif"/> </inline-formula> on average.
Background
Leprosy is a chronic infectious disease that causes disabilities and deformities. Early detection is a major strategy for leprosy control. This study reported a new practice of suspicious ...symptom monitoring for early detection of leprosy.
Methods
A descriptive and comparative analysis between a non‐strategy group of pre‐implementation of suspicious symptom monitoring in 2005–2011 and a strategy group of strategy implementation in 2012–2018 was conducted through indicators of the number of times of misdiagnoses, delayed period, proportion of early detected cases, and proportion of disabilities.
Result
Compared with the non‐strategy group in 2005–2011, the median number of times of misdiagnoses was decreased from two times to zero times (z = 4.387, P < 0.001), and the median delayed period of newly detected cases were shortened from 24 months to 13 months (z = 2.381, P < 0.001), the proportion of early detected cases was increased from 43.7% to 75.2% (χ2 = 29.464, P < 0.001), the proportion of grade 2 disabilities was decreased from 28.6% in the highest year of 2005 to 4.0% in the lowest year of 2014, and the average proportion of disabilities was decreased from 33.5% to 17.6% (χ2 = 9.421, P = 0.002) in the strategy group in 2012–2018, respectively.
Conclusion
Suspicious symptom monitoring promoted early detection of cases by reducing the number of times misdiagnosis of leprosy patients, shortening the delayed period, increasing the proportion of early detection, and decreasing the proportion of disabilities. It is an important and recommendable public health strategy for leprosy prevention and control in a low epidemic condition.
Abstract
On the basis of traditional unequal clustering protocol for wireless sensor networks, an energy-balance unequal clustering routing protocol is proposed. In the clustering stage, the entire ...network is divided into clusters of different sizes based on the remaining energy and the distance from the sink node to the node. In the cluster establishment phase, each node calculates the cluster head selection time based on the relative remaining energy, the position, the average distance between the nodes in the cluster. The cluster head is selected by time series, and non-cluster head nodes are selected to join the cluster based on the distance between cluster heads and the remaining energy of the relay cluster head. In the route establishment phase, an optimal transmission path based on minimum spanning tree is built, based on the distance between cluster heads, the residual energy and the distance from node to the sink node. During data transmission, a single hop within a cluster is adopted, and a minimum spanning tree multi-hop method is used between clusters, and the data is finally transmitted to the sink node. The simulation shows that the routing protocol can effectively balance energy consumption and save energy, and the life cycle of the network is prolonged.
Building a high-performance FPGA accelerator for Deep Neural Networks (DNNs) often requires RTL programming, hardware verification, and precise resource allocation, all of which can be time-consuming ...and challenging to perform even for seasoned FPGA developers. To bridge the gap between fast DNN construction in software (e.g., Caffe, TensorFlow) and slow hardware implementation, we propose DNNBuilder for building high-performance DNN hardware accelerators on FPGAs automatically. Novel techniques are developed to meet the throughput and latency requirements for both cloud- and edge-devices. A number of novel techniques including high-quality RTL neural network components, a fine-grained layer-based pipeline architecture, and a column-based cache scheme are developed to boost throughput, reduce latency, and save FPGA on-chip memory. To address the limited resource challenge, we design an automatic design space exploration tool to generate optimized parallelism guidelines by considering external memory access bandwidth, data reuse behaviors, FPGA resource availability, and DNN complexity. DNNBuilder is demonstrated on four DNNs (Alexnet, ZF, VGG16, and YOLO) on two FPGAs (XC7Z045 and KU115) corresponding to the edge- and cloud-computing, respectively. The fine-grained layer-based pipeline architecture and the column-based cache scheme contribute to 7.7x and 43x reduction of the latency and BRAM utilization compared to conventional designs. We achieve the best performance (up to 5.15x faster) and efficiency (up to 5.88x more efficient) compared to published FPGA-based classification-oriented DNN accelerators for both edge and cloud computing cases. We reach 4218 GOPS for running object detection DNN which is the highest throughput reported to the best of our knowledge. DNNBuilder can provide millisecond-scale real-time performance for processing HD video input and deliver higher efficiency (up to 4.35x) than the GPU-based solutions.
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