Results 141 to 150 of about 1,122,669 (279)

Dual‐Targeting Cuproptosis and Mitophagy via a Flavopiridol‐Copper Nanoplatform Potentiates Immunotherapy Against Uveal Melanoma

Advanced Science, EarlyView.
This study develops a GSH‐responsive nanoplatform, NP@Fla‐Cu, to co‐activate cuproptosis and excessive mitophagy in uveal melanoma. The nanoplatform enhances tumor‐specific copper delivery, depletes antioxidant defenses, and remodels the tumor immune microenvironment.
Hong Ren, Zhihong Deng, Sheng Lu, Jing Zhang, Wenbin Liu, Jia Tan   +5 more
wiley   +1 more source

Bias in data-driven replicability analysis of univariate brain-wide association studies

Scientific Reports
Recent studies have used big neuroimaging datasets to answer an important question: how many subjects are required for reproducible brain-wide association studies?
Charles D. G. Burns, Alessio Fracasso, Guillaume A. Rousselet   +2 more
doaj   +1 more source

Imaging of Osteoarthritic Human Articular Cartilage using Fourier Transform Infrared Microspectroscopy Combined with Multivariate and Univariate Analysis. [PDF]

Sci Rep, 2016
Oinas J, Rieppo L, Finnilä MA, Valkealahti M, Lehenkari P, Saarakkala S.   +5 more
europepmc   +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

Spatiotemporal linear mixed effects modeling for the mass-univariate analysis of longitudinal neuroimage data. [PDF]

Neuroimage, 2013
Bernal-Rusiel JL, Reuter M, Greve DN, Fischl B, Sabuncu MR, Alzheimer's Disease Neuroimaging Initiative.   +5 more
europepmc   +1 more source

Bayesian Value-at-Risk for a Portfolio: Multi- and Univariate Approaches Using MSF-SBEKK Models [PDF]

The s-period ahead Value-at-Risk (VaR) for a portfolio of dimension n is considered and its Bayesian analysis is discussed. The VaR assessment can be based either on the n-variate predictive distribution of future returns on individual assets, or on the ...
Anna Pajor, Jacek Osiewalski
core  

Tumor‐Derived Exosomes Deliver Membrane‐Bound Fgl2 to Activate FcγRIIB‐Mediated Immunosuppression in Myeloid‐Derived Suppressor Cells

Advanced Science, EarlyView.
This study reveals that the Fgl2‐FcγRIIB signaling axis is a key mechanism by which MDSCs mediate tumor immune evasion. Tumor‐derived exosomes systemically activate MDSCs via this pathway, positioning this axis as a promising broad‐spectrum target for cancer immunotherapy.
Fenglin Lin, Dingqin Cai, Chunli Jian, Yaxian Qi, Linpeng Zheng, Qiao Yang, Longyao Zhang, Diangang Chen, Lingchen Li, Ping Cai, Lingyou Sun, Luping Zhang, Jianguo Sun   +12 more
wiley   +1 more source

Promoter Hypermethylation‐Induced Silencing of FXYD1 Drives Breast Cancer Metastasis via DDX5‐Mediated Wnt/β‐Catenin Pathway Activation

Advanced Science, EarlyView.
This study identifies FXYD1 as an epigenetically silenced tumor suppressor in breast cancer. DNA methylation turns off the gene FXYD1 in breast cancer, and low levels predict worse outcomes. Restoring FXYD1 limits breast cancer cells proliferation and metastasis. In the nucleus, FXYD1 recruits the E3 ligase MAEA to K63‐ubiquitinate DDX5 for proteasomal
Ping Wen, Fanli Qu, Long Wang, Qing Shao, Sisi Li, Yang Qin, Dongping Jiang, Senmiao Zhang, Jiangdong Sui, Guanwen Wang, Ningning Zhang, Xiaohua Zeng   +11 more
wiley   +1 more source

Forecasting Inflation in China [PDF]

This paper forecasts inflation in China over a 12-month horizon. The analysis runs 15 alternative models and finds that only those considering many predictors via a principal component display a better relative forecasting performance than the univariate
Mehrotra , Aaron, Sánchez-Fung, José R.   +1 more
core  

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source