Results 121 to 130 of about 5,254 (231)

Class A CpG oligodeoxynucleotide inhibits IFN-γ-induced signaling and apoptosis in lung cancer. [PDF]

open access: yesThorac Cancer, 2020
Teranishi S   +9 more
europepmc   +1 more source

CpG-oligodeoxynucleotides inhibit airway remodeling in a murine model of chronic asthma [PDF]

open access: bronze, 2002
Vipul V. Jain   +6 more
openalex   +1 more source

Polyethyleneimine-functionalized boron nitride nanospheres as efficient carriers for enhancing the immunostimulatory effect of CpG oligodeoxynucleotides

open access: yesInternational Journal of Nanomedicine, 2015
Huijie Zhang,1 Shini Feng,1 Ting Yan,1 Chunyi Zhi,2 Xiao-Dong Gao,1 Nobutaka Hanagata3,41The Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, People’s Republic of
Zhang HJ   +5 more
doaj  

Pristine large pore benzene-bridged mesoporous organosilica nanoparticles as an adjuvant and co-delivery platform for eliciting potent antitumor immunity

open access: yesMaterials Today Advances, 2020
Nanomaterials have provided an emerging solution to improve the efficacy of cancer vaccines against malignant tumors. However, developing nanoparticles possessing both potent immunoadjuvant and co-delivery activities without tedious functionalization ...
M. Jambhrunkar   +9 more
doaj  

Toll-Like Receptor 21 of Chicken and Duck Recognize a Broad Array of Immunostimulatory CpG-oligodeoxynucleotide Sequences. [PDF]

open access: yesVaccines (Basel), 2020
Chuang YC   +9 more
europepmc   +1 more source

Convolution-based Probability Gradient Loss for Semantic Segmentation [PDF]

open access: yesarXiv
In this paper, we introduce a novel Convolution-based Probability Gradient (CPG) loss for semantic segmentation. It employs convolution kernels similar to the Sobel operator, capable of computing the gradient of pixel intensity in an image. This enables the computation of gradients for both ground-truth and predicted category-wise probabilities.
arxiv  

Advancing Spiking Neural Networks for Sequential Modeling with Central Pattern Generators [PDF]

open access: yesarXiv
Spiking neural networks (SNNs) represent a promising approach to developing artificial neural networks that are both energy-efficient and biologically plausible. However, applying SNNs to sequential tasks, such as text classification and time-series forecasting, has been hindered by the challenge of creating an effective and hardware-friendly spike ...
arxiv  

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