Results 121 to 130 of about 622,624 (287)

Metformin promotes mitochondrial integrity through AMPK‐signaling in Leber's hereditary optic neuropathy

open access: yesFEBS Open Bio, EarlyView.
Metformin mediates mitochondrial quality control in Leber's hereditary optic neuropathy (LHON) fibroblasts carrying mtDNA mutations. At therapeutic levels, metformin activates AMPK signaling to restore mitochondrial dynamics by promoting fusion and restraining fission, while preserving mitochondrial mass, enhancing autophagy/mitophagy and biogenesis ...
Chatnapa Panusatid   +3 more
wiley   +1 more source

Graph-Based EEG Signal Compression for Human–Machine Interaction

open access: yesIEEE Access
Communication of bioelectric signals, such as electroencephalography (EEG) signals, will be a key technology for smooth interaction between users and remote robots.
Takuya Fujihashi, Toshiaki Koike-Akino
doaj   +1 more source

Characterization and prediction of clinical pathways of vulnerability to psychosis through graph signal processing. [PDF]

open access: yesElife, 2021
Sandini C   +25 more
europepmc   +1 more source

FGFR Like1 drives esophageal cancer progression via EMT, PI3K/Akt, and notch signalling: insights from clinical data and next‐generation sequencing analysis

open access: yesFEBS Open Bio, EarlyView.
Clinical analysis reveals significant dysregulation of FGFRL1 in esophageal cancer (EC) patients. RNAi‐coupled next‐generation sequencing (NGS) and in vitro study reveal FGFRL1‐mediated EC progression via EMT, PI3K/Akt, and Notch pathways. Functional assays confirm its role in tumor growth, migration, and invasion.
Aprajita Srivastava   +3 more
wiley   +1 more source

Cortical Surface-Informed Volumetric Spatial Smoothing of fMRI Data via Graph Signal Processing. [PDF]

open access: yesAnnu Int Conf IEEE Eng Med Biol Soc, 2021
Behjat H, Westin CF, Aganj I.
europepmc   +1 more source

Modelling Graph Errors: Towards Robust Graph Signal Processing

open access: yes, 2019
The first step for any graph signal processing (GSP) procedure is to learn the graph signal representation, i.e., to capture the dependence structure of the data into an adjacency matrix. Indeed, the adjacency matrix is typically not known a priori and has to be learned. However, it is learned with errors.
Miettinen, Jari   +2 more
openaire   +2 more sources

Evaluation of in vitro toxicity of common phytochemicals included in weight loss supplements using 1H NMR spectroscopy

open access: yesFEBS Open Bio, EarlyView.
We investigated the toxicity of 12 active compounds commonly found in herbal weight loss supplements (WLS) using human liver and colon cell models. Epigallocatechin‐3‐gallate was the only compound showing significant toxicity. Metabolic profiling revealed protein degradation, disrupted energy and lipid metabolism suggesting that the inclusion of EGCG ...
Emily C. Davies   +3 more
wiley   +1 more source

Mycobacterial cell division arrest and smooth‐to‐rough envelope transition using CRISPRi‐mediated genetic repression systems

open access: yesFEBS Open Bio, EarlyView.
CRISPRI‐mediated gene silencing and phenotypic exploration in nontuberculous mycobacteria. In this Research Protocol, we describe approaches to control, monitor, and quantitatively assess CRISPRI‐mediated gene silencing in M. smegmatis and M. abscessus model organisms.
Vanessa Point   +7 more
wiley   +1 more source

Domain associated with zinc fingers‐containing NF90‐NF45 complex inhibits m6A modification of primary microRNA by suppressing METTL3/14 activity

open access: yesFEBS Open Bio, EarlyView.
NF90–NF45 functions as a negative regulator of methyltransferase‐like 3/14 (METTL3/14)‐mediated N6‐methyladenosine (m6A) modification on primary microRNAs (pri‐miRNAs). NF90–NF45 binds to anti‐oncogenic pri‐miRNAs and inhibits their m6A modification, thereby suppressing the biogenesis of anti‐oncogenic miRNAs.
Takuma Higuchi   +6 more
wiley   +1 more source

Verifying the Smoothness of Graph Signals: A Graph Signal Processing Approach

open access: yesIEEE Transactions on Signal Processing
Graph signal processing (GSP) deals with the representation, analysis, and processing of structured data, i.e. graph signals that are defined on the vertex set of a generic graph. A crucial prerequisite for applying various GSP and graph neural network (GNN) approaches is that the examined signals are smooth graph signals with respect to the underlying
Lital Dabush, Tirza Routtenberg
openaire   +2 more sources

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