Results 221 to 230 of about 1,272,387 (291)
Contextual quantum neural networks for stock price prediction. [PDF]
Mourya S, Leipold H, Adhikari B.
europepmc +1 more source
This study shows that Salmonella VNP20009 recruits pro‐tumor neutrophils that reduce its anticancer efficacy. Combining VNP with amodiaquine selectively eliminates these neutrophils by targeting glutathione reductase. A GR‐shRNA‐loaded VNP strain was further developed, demonstrating an innovative strategy integrating drug repurposing with synthetic ...
Wanfa Dong +13 more
wiley +1 more source
A strategy utilizing high‐energy ion beam technology to engineer defects in layered double hydroxide (LDH) nanosheets enables the high loading of non‐noble metal Mo single atoms. The synergistic effect between oxygen vacancies and single atoms promotes a novel mechanism for lattice oxygen activation, thereby significantly enhancing the oxygen evolution
Shixin Wu +9 more
wiley +1 more source
Graph attention-based heterogeneous multi-agent deep reinforcement learning for adaptive portfolio optimization. [PDF]
Zhang B.
europepmc +1 more source
This study identifies L‐type calcium channel blockers as novel ferroptosis inhibitors. It reveals that PKCβ, activated in calcium dependent manner, phosphorylates and activates ACSL4 and ALOX15, relocating them to lipid droplets to promote lethal lipid peroxidation and ferroptosis.
Guoyuan Hou +8 more
wiley +1 more source
The glycosyltransferase GALNT10 facilitates ovarian cancer metastasis through the induction of tumor cell EMT and tumor vascular dysfunction. GALNT10 enhanced the extracellular secretion of IGFBP7 through O‐GalNAc glycosylation modification at the T188 site, which subsequently interacts with CD93 on endothelial cells, leading to vascular remodeling ...
Yanan Zhang +9 more
wiley +1 more source
Information-Processing Entropy and Heterogeneous Sentiment Reaction Windows: Evidence from S&P 500 Stocks. [PDF]
Peng CY.
europepmc +1 more source
S3RL: Enhancing Spatial Single‐Cell Transcriptomics With Separable Representation Learning
Separable Spatial Representation Learning (S3RL) is introduced to enhance the reconstruction of spatial transcriptomic landscapes by disentangling spatial structure and gene expression semantics. By integrating multimodal inputs with graph‐based representation learning and hyperspherical prototype modeling, S3RL enables high‐fidelity spatial domain ...
Laiyi Fu +6 more
wiley +1 more source

