Results 61 to 70 of about 108,466 (288)

Promiscuous stimulation of HSP70 ATPase activity by parasite‐derived J‐domains

FEBS Open Bio, EarlyView.
The malaria parasite Plasmodium falciparum exports three highly homologous yet functionally divergent J‐domain proteins into human erythrocytes. Here, we show that J‐domains isolated from all three proteins effectively stimulate the ATPase activity of both endogenous host and exported parasite HSP70 chaperones.
Julian Barth, Moritz Koch, Le‐Han Rössner, Johanna Eichhorn, Denys Pogoryelov, Matthias P. Mayer, Jude M. Przyborski   +6 more
wiley   +1 more source

MiR‐513a promotes human erythroid differentiation by modulating c‐Jun

FEBS Open Bio, EarlyView.
During early human erythropoiesis, miR‐513a promoted erythroid differentiation in primary human CD34+ hematopoietic stem‐progenitor cells and human TF‐1 erythroleukemic cells by indirectly decreasing c‐Jun and phospho‐c‐Jun expression, which are associated with increased GATA1 expression.
MinJung Kim, Brittany Taylor, Shannon Bolten, Christian L. Eberly, Mahliya Abdurahman, T. Michael Creed, Acong Yang, Taylor L. Hatchet, Tristan Dyson, Shuo Gu, Curt I. Civin, Tami J. Kingsbury   +11 more
wiley   +1 more source

TPE-Based Boosting Short-Term Load Forecasting Method

Shanghai Jiaotong Daxue xuebao
Short-term load forecasting is generally applied in power system real-time dispatching and day-ahead generation planning, which is of great significance for power system economic dispatching and safe operation of the system. Many researches on short-term
LUO Min, YANG Jinfeng, YU Hui, LAI Yuchen, GUO Yangyun, ZHOU Shangli, XIANG Rui, TONG Xing, CHEN Xiao
doaj   +1 more source

Application of Deep Learning Long Short-Term Memory in Energy Demand Forecasting

, 2019
The smart metering infrastructure has changed how electricity is measured in both residential and industrial application. The large amount of data collected by smart meter per day provides a huge potential for analytics to support the operation of a ...
D Alahakoon, Damminda Alahakoon, H-T Pao, J Barton, K Kwang-Ho, K Zhao, L Han, MQ Raza, MR Fernández, P Mirowski, P-H Kuo, S Hochreiter, SV Verdu, W Kong, Y Wang   +14 more
core   +1 more source

Remote Monitoring in Myasthenia Gravis: Exploring Symptom Variability

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare, autoimmune disorder characterized by fluctuating muscle weakness and potential life‐threatening crises. While continuous specialized care is essential, access barriers often delay timely interventions. To address this, we developed MyaLink, a telemedical platform for MG patients.
Maike Stein, Maximilian Mönch, Meret Herdick, Frauke Stascheit, Sarah Hoffmann, Hannah Preßler, Philipp Mergenthaler, Carla Dusemund, Paolo Doksani, Haoqi Sun, Pushpa Narayanaswami, Andreas Meisel, Lea Gerischer, Sophie Lehnerer   +13 more
wiley   +1 more source

Short-Term Load Forecasting Based on Multi-Scale Ensemble Deep Learning Neural Network

IEEE Access, 2023
High-precision load forecasting is crucial for the power system planning and electricity market transactions. Recently, deep learning models have been widely used due to their powerful data mining capabilities. However, the existing research mainly focus
Qin Shen, Li Mo, Guanjun Liu, Jianzhong Zhou, Yongchuan Zhang, Pinan Ren   +5 more
doaj   +1 more source

Development of a Prediction Model for Progression Risk in High‐Grade Gliomas Based on Habitat Radiomics and Pathomics

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu, Yuxi Gong, Weilin Xu, Xingjian Sun, Gefei Jiang, Lei Qiu, Kexin Shi, Mengxing Wu, Yinjiao Fei, Jinling Yuan, Jinyan Luo, Yurong Li, Yuandong Cao, Minhong Pan, Shu Zhou   +14 more
wiley   +1 more source

Ultra Short-Term Power Load Forecasting Based on Similar Day Clustering and Ensemble Empirical Mode Decomposition

Energies, 2023
With the increasing demand of the power industry for load forecasting, improving the accuracy of power load forecasting has become increasingly important.
Wenhui Zeng, Jiarui Li, Changchun Sun, Lin Cao, Xiaoping Tang, Shaolong Shu, Junsheng Zheng   +6 more
doaj   +1 more source

Improving Short-Term Electricity Price Forecasting Using Day-Ahead LMP with ARIMA Models

, 2018
Short-term electricity price forecasting has become important for demand side management and power generation scheduling. Especially as the electricity market becomes more competitive, a more accurate price prediction than the day-ahead locational ...
Miller, Carol, Nokleby, Matthew, Wang, Caisheng, Zhao, Zhongyang   +3 more
core   +1 more source

Location‐Specific Hematoma Volume Predicts Early Neurological Deterioration in Supratentorial ICH

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Early neurological deterioration (END) adversely affects outcomes in patients with intracerebral hemorrhage (ICH). This study aimed to determine the location‐specific hematoma volumes for END in supratentorial ICH patients. Methods We retrospectively analyzed supratentorial ICH patients presenting from two prospective cohorts.
Zuoqiao Li, Guilin Meng, Zijie Wang, Xiao Hu, Jing Cheng, Chu Chen, Tiannan Yang, Jiaxin Luo, Zizhen Meng, Xueyun Liu, Qi Li   +10 more
wiley   +1 more source