18 papers · ranked by Valyu relevance
Ling-Yun Zhou, Chen-Xi Jin, Wen-Xiao Wang, Lei Song + 3 more
The MRTF-SRF pathway has been extensively studied for its crucial role in driving the expression of a large number of genes involved in actin cytoskeleton of various cell types. However, the specific contribution of MRTF-SRF in hair cells remains unknown. In this study, we showed that hair cell-specific deletion of Srf…
Jinghu He, Xiaohong Yang, Chuansen Zhang, Ang Li + 8 more
'Junjie Xing' 'Jifu E' 'Xiaodong Xu' 'Hao Wang' 'Enda Yu' 'Debing Shi' 'Hantao Wang'] In colorectal cancer (CRC), CNN2 was found to form a complex with YAP1 and EGR1, thus regulating EGR1 expression and promoting CRC, which could be considered as a potential therapeutic target for CRC.
Yuan Gui, Jianling Tao, Yuanyuan Wang, Zachary Palanza + 9 more
In the fibrotic kidneys, the extent of a formed deleterious microenvironment is determined by cellular mechanical forces. This process requires metabolism for energy; however, how cellular mechanics and metabolism are connected remains unclear. Our proteomics revealed that actin filament binding and cell metabolism are…
Yuan Gui, Zachary Palanza, Priya Gupta, Hanwen Li + 9 more
'Yuanyuan Wang' 'Geneva Hargis' 'Donald L. Kreutzer' 'Yanlin Wang' 'Sheldon I. Bastacky' 'Yansheng Liu' 'Silvia Liu' 'Dong Zhou'] Calponin 2 (CNN2) is a prominent actin stabilizer. It regulates fatty acid oxidation (FAO) by interacting with estrogen receptor 2 (ESR2) to determine kidney fibrosis. However, whether CNN2…
Xiaoyun Bin, Yu Luo, Zefeng Sun, Chaoqun Lin + 9 more
'Zhenbo Tu' 'Ling Li' 'Cong Qu' 'Jiamin Long' 'Sufang Zhou' 'Nam Deuk Kim' 'Steven Fiering' 'Dario Marchetti'] To investigate the potential of H2-calponin (CNN2) as a serum biomarker for hepatocellular carcinoma (HCC), this study employed the serological analysis of recombinantly expressed cDNA clone (SEREX) technique…
Tzu-Bou Hsieh, Jian-Ping Jin
Background Premature ovarian insufficiency (POI) is a condition defined as women developing menopause before 40 years old. These patients display low ovarian reserve at young age and difficulties to conceive even with assisted reproductive technology. The pathogenesis of ovarian insufficiency is not fully understood.…
Zewen Li, Wenjie Yang, Shouheng Peng, Fan Liu
—Convolutional Neural Network (CNN) is one of the most significant networks in the deep learning field. Since CNN made impressive achievements in many areas, including but not limited to computer vision and natural language processing, it attracted much attention both of industry and academia in the past few years. The…
Vasiliki Bikia, Marija Lazaroska, Deborah Scherrer Ma, Méline Zhao + 3 more
'Georgios Rovas' 'Stamatia Pagoulatou' 'Nikolaos Stergiopulos'] Determination of left ventricular (LV) end-systolic elastance (Ees) is of utmost importance for assessing the cardiac systolic function and hemodynamical state in humans. Yet, the clinical use of Ees is not established due to the invasive nature and high…
Rais Mohammad Salman, Muhammad Mahbubur Rashid, Rupal Roy, Md Manjurul Ahsan + 1 more
'Md Manjurul Ahsan' 'Zahed Siddique'] Driver drowsiness detection using videos/images is one of the most essential areas in today's time for driver safety. The development of deep learning techniques, notably Convolutional Neural Networks (CNN), applied in computer vision applications such as drowsiness detection, has…
Authors not listed
This research presents a novel approach to obstacle detection during navigation using a combination of Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. The primary objective is to generate accurate image captions that describe the content of images, which is crucial for applications such…
Xu Shen, Xinmei Tian, Anfeng He, Shaoyan Sun + 1 more
Convolutional neural networks (CNNs) have achieved stateof-the-art results on many visual recognition tasks. However, current CNN models still exhibit a poor ability to be invariant to spatial transformations of images. Intuitively, with sufficient layers and parameters, hierarchical combinations of convolution (matrix…
Wei Zhang, Zuoxiang Zeng
With the improvement of computer performance and the increase of data volume, the object detection based on convolutional neural network (CNN) has become the main algorithm for object detection. This paper summarizes the research progress of convolutional neural networks and their applications in object detection, and…
Sanket Kadulkar, Michael Howard, Thomas Truskett, Venkat Ganesan
We develop a convolutional neural network (CNN) model to predict the diffusivity of cations in nanoparticle-based electrolytes, and use it to identify the characteristics of morphologies which exhibit optimal transport properties. The ground truth data is obtained from kinetic Monte Carlo (kMC) simulations of cation…
Ivan Kolesnikov, Nadezhda Semenova
In this paper, we investigate the impact of noise on a simplified trained convolutional network. The types of noise studied originate from a real optical implementation of a neural network, but we generalize these types to enhance the applicability of our findings on a broader scale. The noise types considered include…
Mikhail Kiselev, Andrey Lavrentyev
—We consider an implementation of convolutional architecture in a spiking neural network (SNN) used to classify images. As in the traditional neural network, the convolutional layers form informational "features" used as predictors in the SNN-based classifier with CoLaNET architecture. Since weight sharing contradicts…
Yaoda Xu, Maryam Vaziri-Pashkam
Convolutional neural networks (CNNs) have achieved very high object categorization performance recently. It has increasingly become a common practice in human fMRI research to regard CNNs as working model of the human visual system. Here we reevaluate this approach by comparing fMRI responses from the human brain in…
Kandan Ramakrishnan, Iris I.A. Groen, Arnold W.M. Smeulders, H. Steven Scholte + 1 more
Convolutional neural networks (CNNs) have recently emerged as promising models of human vision based on their ability to predict hemodynamic brain responses to visual stimuli measured with functional magnetic resonance imaging (fMRI). However, the degree to which CNNs can predict temporal dynamics of visual object…
Chenxi Sui, Ziyang Jiang, Genesis Higueros, David Carlson + 1 more
High-performance batteries are poised for electrification of vehicles and therefore mitigate greenhouse gas emissions, which, in turn, promote a sustainable future. However, the design of optimized batteries is challenging due to the nonlinear governing physics and electrochemistry. Recent advancements have…