Results 61 to 70 of about 1,160,351 (242)
Fetal Brain Tumor Harboring a Unique ROCK1::BRAF Fusion
Pediatric Blood &Cancer, EarlyView.
Marllon Cindra Sant'Ana +8 more
wiley +1 more source
Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system
FEBS Letters, EarlyView.Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley +1 more source
External Prestressing Bridge Reinforcement Technology Review
MATEC Web of Conferences, 2015 Externally prestressed bridge can not only limit and reduce the cracks and deformation of the structure, improve the rigidity and bearing capacity of structure, improve the stress state of structure, but also have less interference for bridge operation ...
Zhu Hanbing, Yang Yaxun, Fan Weiya
doaj +1 more source
FEBS Letters, EarlyView.Mitochondrial remodeling shapes neural and glial lineage progression by matching metabolic supply with demand. Elevated OXPHOS supports differentiation and myelin formation, while myelin compaction lowers mitochondrial dependence, revealing mitochondria as key drivers of developmental energy adaptation.
Sahitya Ranjan Biswas +3 more
wiley +1 more source
Influence of Stirrup-Tie Shape on Inelastic Cyclic Response of Flanged Reinforced Concrete Flexural Members [PDF]
, 1981 Three reinforced concrete flanged sections (T-sections) having different shapes of shear reinforcement were subjected to cyclic inelastic flexure representative of what framed structure members might-be forced to endure during a severe earthquake. The
Scribner, C.F., Wilhelm, D.R.
core
An FPGA-Based On-Device Reinforcement Learning Approach using Online Sequential Learning
, 2021 DQN (Deep Q-Network) is a method to perform Q-learning for reinforcement learning using deep neural networks. DQNs require a large buffer and batch processing for an experience replay and rely on a backpropagation based iterative optimization, making ...
Matsutani, Hiroki +2 more
core
FEBS Letters, EarlyView.Plasma membranes contain dynamic nanoscale domains that organize lipids and receptors. Because viruses operate at similar scales, this architecture shapes early infection steps, including attachment, receptor engagement, and entry. Using influenza A virus and HIV‐1 as examples, we highlight how receptor nanoclusters, multivalent glycan interactions ...
Jan Schlegel, Christian Sieben
wiley +1 more source
Risk-sensitive Reinforcement Learning
, 2014 We derive a family of risk-sensitive reinforcement learning methods for agents, who face sequential decision-making tasks in uncertain environments.
Obermayer, Klaus +3 more
core +1 more source
AAA+ protein unfoldases—the Moirai of the proteome
FEBS Letters, EarlyView.AAA+ unfoldases are essential molecular motors that power protein degradation and disaggregation. This review integrates recent cryo‐electron microscopy (cryo‐EM) structures and single‐molecule biophysical data to reconcile competing models of substrate translocation.
Stavros Azinas, Marta Carroni
wiley +1 more source
Potential therapeutic targeting of BKCa channels in glioblastoma treatment
Molecular Oncology, EarlyView.This review summarizes current insights into the role of BKCa and mitoBKCa channels in glioblastoma biology, their potential classification as oncochannels, and the emerging pharmacological strategies targeting these channels, emphasizing the translational challenges in developing BKCa‐directed therapies for glioblastoma treatment.
Kamila Maliszewska‐Olejniczak +4 more
wiley +1 more source