Results 101 to 110 of about 234,460 (307)

Genome‐Wide In Vivo RNAi Screening Identifies HOXD4 as a Tumor Metastasis Suppressor in Colorectal Cancer

Advanced Science, EarlyView.
Metastasis remains a major challenge in colorectal cancer. Using an in vivo shRNA screening system, this study identifies Homeobox D4 as a key metastasis suppressor. Reduced Homeobox D4 expression is associated with aggressive tumor features. Functional and mechanistic analyses show that it inhibits epithelial‐mesenchymal transition by repressing ...
Zhi‐hua Ye, Wen‐jing Luo, Lu Li, Wen‐di Shuai, Ling Zhou, You‐fa Duan, Xue Chen, Jun‐kai Zhang, Wenlin Huang, Ran‐yi Liu   +9 more
wiley   +1 more source

Cuproptosis and Mitophagy Mediated by the THUMPD1/IGF2R‐Dependent Suppression of AKT and Activation of AMPK Signaling Suppress Lung Adenocarcinoma Progression

Advanced Science, EarlyView.
THUMPD1 drives a tumor‐suppressive signaling cascade in lung adenocarcinoma by promoting IGF2R expression. IGF2R associates with PPP2R1A to suppress AKT and activate AMPK, leading to SLC31A1 upregulation and copper accumulation. Elevated copper disrupts mitochondrial metabolism and induces excessive mitophagy, thereby restraining tumor growth and ...
Kai Wu, Bo Qin, Zhuoyu Gu, Weizheng Ding, Xiaoming Chen, Kaishang Zhang, Yujin Qiao, Shuang Yuan, Song Zhao, Xiangnan Li, Peng Zhang   +10 more
wiley   +1 more source

Metabolic Imbalance Triggers Adaptive Remodeling to Accelerate Diploidization in Murine Haploid Embryonic Stem Cells

Advanced Science, EarlyView.
In this article, Shuai and colleagues demonstrate that metabolic remodeling drives self‐diploidization in murine haploid ESCs (haESCs). Mitochondrial dysfunction and imbalanced pyruvate metabolism underlie this process. Genome‐wide screening using haESCs identifies key mitochondrial quality‐control related genes, enabling a metabolism‐based medium that
Yi Fu, Wenhao Zhang, Yifan Zhang, Yu He, Yi Du, Yiding Zhao, Chunmeng Yao, Shengyi Sun, Xiaoyan Sheng, Qian Gao, Chao Tong, Ling Shuai   +11 more
wiley   +1 more source

Diagnostic checking of nonlinear multivariate time series with multivariate ARCH errors [PDF]

, 1997
Multivariate time series with multivariate ARCH errors have been found useful in many applications. In order to check the adequacy of these models, we define the sum of squared (standardized) residual autocorrelations and derive their asymptotic ...
Li, W. K., Li, WK, Ling, S, Ling, Shiqing   +3 more
core   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Time–Frequency Parallel and Channel-Adaptive Gating for Multivariate Time Series Prediction

Applied Sciences
In real-world scenarios, multivariate time series data typically presents a variety of complex characteristics simultaneously, including long-term trends, multiple seasonality, sudden event disturbances and random noise. Owing to remarkable discrepancies
Xin He, Zhenwen He
doaj   +1 more source

"Multivariate stochastic volatility" [PDF]

We provide a detailed summary of the large and vibrant emerging literature that deals with the multivariate modeling of conditional volatility of financial time series within the framework of stochastic volatility.
Manabu Asai, Siddhartha Chib, Yasuhiro Omori   +2 more
core  

Schooling Trajectories and the Development of Brain Dynamics: A Comparative Study of Montessori and Traditional Education

Advanced Science, EarlyView.
We investigate whether Montessori and traditional schooling systems shape the developmental trajectory of large‐scale brain dynamics in different ways. We quantify the arrow of time (“non‐reversibility”) in neural activity during resting state and movie‐watching, revealing distinct maturational patterns.
Elvira del Agua, Anira Escrichs, Yonatan Sanz Perl, Morten L. Kringelbach, Adele Diamond, Solange Denervaud, Gustavo Deco   +6 more
wiley   +1 more source

On observational variance learning for multivariate Bayesian time series and related models [PDF]

This thesis is concerned with variance learning in multivariate dynamic linear models (DLMs). Three new models are developed in this thesis. The first one is a dynamic regression model with no distributional assumption of the unknown variance matrix.
Triantafyllopoulos, K.
core  

A Bayesian network approach to explaining time series with changing structure [PDF]

, 2004
Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any model that is learnt from the data will average over the different dependency structures.
Liu, X, Tucker, A
core