Search results for: Alleleustrious pmWasabiZyxin fusion vector
#38650695 
2024/04/22
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Feature Importance Analysis and Machine Learning for Alzheimer's Disease Early Detection: Feature Fusion of the Hippocampus, Entorhinal Cortex, and Standardized Uptake Value Ratio.
Alzheimer's disease (AD) is a progressive neurological disorder characterized by mild memory loss and ranks as a leading cause of mortality in the USA, accounting for approximately 120,000 deaths per year. It is also the primary form of dementia. Early detection is critical for timely intervention as the neurodegenerative process often starts 15-20 years before cognitive symptoms manifest. This study focuses on determining feature importance in AD classification using fused texture features from 3D magnetic resonance imaging hippocampal and entorhinal cortex and standardized uptake value ratio (SUVR) derived from positron emission tomography (PET) images.Aya Hassouneh, Bradley Bazuin, Alessander Danna-Dos-Santos, Ilgin Acar, Ikhlas Abdel-Qader,
2030 related Products with: Feature Importance Analysis and Machine Learning for Alzheimer's Disease Early Detection: Feature Fusion of the Hippocampus, Entorhinal Cortex, and Standardized Uptake Value Ratio.
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#38645872 //
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[Prokaryotic Expression and Bioinformatic Analysis of Rv3432c From ].
To express the protein enconded by the 3432 gene of (.) by prokaryotic expression, to analyze the structure of the Rv3432c protein by using bioinformatics software, and to explore for new drug targets against ..Haibo Yi, Xinghong Gao, Guo Luo, Peng Xu, Huan Wang
1516 related Products with: [Prokaryotic Expression and Bioinformatic Analysis of Rv3432c From ].
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#38644712 2024/04/19
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A Novel Detection of Cerebrovascular Disease using Multimodal Medical Image Fusion.
Diseases are medical situations that are allied with specific signs and symptoms. A disease may be instigated by internal dysfunction or external factors like pathogens. Cerebrovascular disease can progress from diverse causes, comprising thrombosis, atherosclerosis, cerebral venous thrombosis, or embolic arterial blood clot.Sudip Paul, Shruti Jain
1680 related Products with: A Novel Detection of Cerebrovascular Disease using Multimodal Medical Image Fusion.
500 tests430 Tests / Kit 50 UG100 15 ml 25 assays0.1 mg
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#38643206 2024/04/20
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Construction of power network security risk assessment model based on LSA-SVM algorithm in the background of smart grid.
Due to theintricate and interdependent nature of the smart grid, it has encountered an increasing number of security threats in recent years. Currently, conventional security measures such as firewalls, intrusion detection, and malicious detection technologies offer specific protection based on their unique perspectives. However, as the types and concealment of attacksincrease, these measures struggle to detect them promptly and respond accordingly. In order to meet the social demand for the accuracy and computation speed of the power network security risk evaluation model, the study develops a fusion power network security risk evaluation algorithm by fusing the flash search algorithm with the support vector machine. This algorithm is then used as the foundation for building an improved power network security risk evaluation model based on the fusion algorithm.The study's improved algorithm's accuracy is 96.2%, which is higher than the accuracy of the other comparative algorithms; its error rate is 3.8%, which is lower than the error rate of the other comparative algorithms; and its loss function curve convergence is quicker than that of the other algorithms.The risk evaluation model's accuracy is 97.8%, which is higher than the accuracy of other comparative models; the error rate is 1.9%, which is lower than the error rate of other comparative models; the computing time of the improved power network security risk evaluation model is 4.4 s, which is lower than the computing time of other comparative models; and its expert score is high. These findings are supported by empirical analysis of the improved power network security risk evaluation model proposed in the study. According to the study's findings, the fusion algorithm and the upgraded power network security risk evaluation model outperform other approaches in terms of accuracy and processing speed. This allows the study's maintenance staff to better meet the needs of the community by assisting them in identifying potential security hazards early on and taking the necessary preventative and remedial action to ensure the power system's continued safe operation.Haojin Qi, Wan Zhu, Mingda Ye, Yichen Hu, Yong Wang
2379 related Products with: Construction of power network security risk assessment model based on LSA-SVM algorithm in the background of smart grid.
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#38641498 2024/04/18
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Immunogenicity and protective efficacy of a multivalent herpesvirus vectored vaccine against H9N2 low pathogenic avian influenza in chicken.
The application of recombinant herpesvirus of turkey, expressing the H9 hemagglutinin gene from low pathogenic avian influenza virus (LPAIV) H9N2 and the avian orthoavulavirus-1 (AOAV-1) (commonly known as Newcastle Disease virus (NDV)) fusion protein (F) as an rHVT-H9-F vaccine, is an alternative to currently used classical vaccines. This study investigated H9- and ND-specific humoral and mucosal responses, H9-specific cell-mediated immunity, and protection conferred by the rHVT-H9-F vaccine in specific pathogen-free (SPF) chickens. Vaccination elicited systemic NDV F- and AIV H9-specific antibody response but also local antibodies in eye wash fluid and oropharyngeal swabs. The ex vivo H9-specific stimulation of splenic and pulmonary T cells in the vaccinated group demonstrated the ability of vaccination to induce systemic and local cellular responses. The clinical protection against a challenge using a LPAIV H9N2 strain of the G1 lineage isolated in Morocco in 2016 was associated with a shorter duration of shedding along with reduced viral genome load in the upper respiratory tract and reduced cloacal shedding compared to unvaccinated controls.Fiona Ingrao, Eva Ngabirano, Fabienne Rauw, Gwenaëlle Dauphin, Bénédicte Lambrecht
1146 related Products with: Immunogenicity and protective efficacy of a multivalent herpesvirus vectored vaccine against H9N2 low pathogenic avian influenza in chicken.
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#38639795 2024/04/19
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Gn protein expressed in plants for diagnosis of severe fever with thrombocytopenia syndrome virus.
SYu-Chih Chang, Hiroshi Shimoda, Min-Chao Jiang, Yau-Heiu Hsu, Ken Maeda, Yumiko Yamada, Wei-Li Hsu
1787 related Products with: Gn protein expressed in plants for diagnosis of severe fever with thrombocytopenia syndrome virus.
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#38631709 2024/04/17
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Preclinical evaluation of two phylogenetically distant arenavirus vectors for the development of novel immunotherapeutic combination strategies for cancer treatment.
Engineered arenavirus vectors have recently been developed to leverage the body's immune system in the fight against chronic viral infections and cancer. Vectors based on Pichinde virus (artPICV) and lymphocytic choriomeningitis virus (artLCMV) encoding a non-oncogenic fusion protein of human papillomavirus (HPV)16 E6 and E7 are currently being tested in patients with HPV16+ cancer, showing a favorable safety and tolerability profile and unprecedented expansion of tumor-specific CD8 T cells. Although the strong antigen-specific immune response elicited by artLCMV vectors has been demonstrated in several preclinical models, PICV-based vectors are much less characterized.Josipa Raguz, Catarina Pinto, Theresa Pölzlbauer, Mohamed Habbeddine, Sandra Rosskopf, Judith Strauß, Valentin Just, Sarah Schmidt, Katell Bidet Huang, Felix Stemeseder, Timo Schippers, Ethan Stewart, Jakub Jez, Pedro Berraondo, Klaus K Orlinger, Henning Lauterbach
1831 related Products with: Preclinical evaluation of two phylogenetically distant arenavirus vectors for the development of novel immunotherapeutic combination strategies for cancer treatment.
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#38631117 2024/04/06
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Computer aided diagnosis of diabetic retinopathy based on multi-view joint learning.
Diabetic retinopathy (DR) is a kind of ocular complication of diabetes, and its degree grade is an essential basis for early diagnosis of patients. Manual diagnosis is a long and expensive process with a specific risk of misdiagnosis. Computer-aided diagnosis can provide more accurate and practical treatment recommendations. In this paper, we propose a multi-view joint learning DR diagnostic model called RT2Net, which integrates the global features of fundus images and the local detailed features of vascular images to reduce the limitations of single fundus image learning. Firstly, the original image is preprocessed using operations such as contrast-limited adaptive histogram equalization, and the vascular structure of the extracted DR image is segmented. Then, the vascular image and fundus image are input into two branch networks of RT2Net for feature extraction, respectively, and the feature fusion module adaptively fuses the feature vectors' output from the branch networks. Finally, the optimized classification model is used to identify the five categories of DR. This paper conducts extensive experiments on the public datasets EyePACS and APTOS 2019 to demonstrate the method's effectiveness. The accuracy of RT2Net on the two datasets reaches 88.2% and 85.4%, and the area under the receiver operating characteristic curve (AUC) is 0.98 and 0.96, respectively. The excellent classification ability of RT2Net for DR can significantly help patients detect and treat lesions early and provide doctors with a more reliable diagnosis basis, which has significant clinical value for diagnosing DR.Xuebin Xu, Dehua Liu, Guohua Huang, Muyu Wang, Meng Lei, Yang Jia