Results 121 to 130 of about 234,460 (307)

Aptamer‐Targeted PrPC Drives Colorectal Cancer Metastasis via a LYN‐STAT3 Complex and Enables Liquid Biopsy Detection

open access: yesAdvanced Science, EarlyView.
The aptamer WHY‐3E identifies PrPC as a CRC driver. Stabilized by USP18, endocytosed PrPC forms a LYN/STAT3 complex, upregulating MSN transcription to promote metastasis. Crucially, WHY‐3E sensitively detects PrPC‐positive circulating exosomes, establishing a robust theoretical foundation for non‐invasive clinical diagnostics.
Chunlin Wang   +23 more
wiley   +1 more source

Graphical Models for Multivariate Time-Series

open access: yes, 2019
Gaussian graphical models have received much attention in the last years, due to their flexibility and expression power. In particular, lots of interests have been devoted to graphical models for temporal data, or dynamical graphical models, to understand the relation of variables evolving in time.
openaire   +2 more sources

SSR4 sustains Tertiary Lymphoid Structures by Regulation Quality Control of N‐linked Glycosylation During B‐cell Differentiation Into Plasmacyte in Colorectal Cancer

open access: yesAdvanced Science, EarlyView.
SSR4, a TRAP component induced in B cells, governs BAFFR N‐glycosylation via DDOST to sustain NF‐κB signaling, B‐cell differentiation, and TLS maturation. Its loss impairs anti‐tumor immunity, while overexpression improves antibody glycosylation and ADCC, revealing a critical regulator for cancer immunotherapy.
Wei Zhao   +15 more
wiley   +1 more source

Deep Learning for Anomaly Detection in Time-Series Data: An Analysis of Techniques, Review of Applications, and Guidelines for Future Research

open access: yesIEEE Access
Industries are generating massive amounts of data due to increased automation and interconnectedness. As data from various sources becomes more available, the extraction of relevant information becomes crucial for understanding complex systems’ ...
Usman Ahmad Usmani   +3 more
doaj   +1 more source

Detecting anomalies in multivariate time series from automotive systems [PDF]

open access: yes, 2013
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In the automotive industry test drives are conducted during the development of new vehicle models or as a part of quality assurance for series vehicles ...
Theissler, Andreas
core  

mTORC2 Phosphorylation of GSDME‐N Drives Cullin4B‐Mediated Proteasomal Degradation to Suppress Pyroptosis and Confer Radioresistance in Small Cell Lung Cancer

open access: yesAdvanced Science, EarlyView.
Radioresistance severely limits the efficacy of therapies for small cell lung cancer (SCLC). This study reveals a novel mechanism of resistance driven by the active suppression of pyroptosis. Specifically, the mTORC2 complex directly phosphorylates GSDME‐N and promotes its CUL4B‐mediated ubiquitination and proteasomal degradation.
Qing‐qing Xu   +11 more
wiley   +1 more source

Testing for Causality in Variance using Multivariate GARCH Models [PDF]

open access: yes
Tests of causality in variance in multiple time series have been proposed recently, based on residuals of estimated univariate models. Although such tests are applied frequently little is known about their power properties.
Herwartz, Helmut, Hafner, Christian M.
core  

Beyond d‐Band Catalysis: A Critical Review and Descriptor Framework for Rare‐Earth Engineering in Lithium–Sulfur Batteries

open access: yesAdvanced Science, EarlyView.
Rare‐earth catalysts regulate lithium–sulfur battery chemistry through f‐orbital–mediated interactions, enabling simultaneous polysulfide adsorption and catalytic conversion on conductive carbon hosts. This synergistic control suppresses the shuttle effect, accelerates redox kinetics, and guides stable Li2S nucleation, providing a mechanistic framework
Fan Wang   +5 more
wiley   +1 more source

Disentangling dynamic and stochastic modes in multivariate time series

open access: yesFrontiers in Applied Mathematics and Statistics
A signal decomposition is presented that disentangles the deterministic and stochastic components of a multivariate time series. The dynamical component analysis (DyCA) algorithm is based on the assumption that an unknown set of ordinary differential ...
Christian Uhl   +5 more
doaj   +1 more source

Exponential Smoothing for Multivariate Time Series

open access: yesJournal of the Royal Statistical Society Series B: Statistical Methodology, 1966
Summary A method is presented for estimating the optimum weight matrix for the exponential smoothing and prediction of multivariate time series. A recursive version of the estimation equations is given. A variation allows the estimation to forget the remote past in order to follow a process in which the structure varies slowly with time.
openaire   +2 more sources

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