5,087 research outputs found
Roles of PLODs in Collagen Synthesis and Cancer Progression
Collagen is the major component of extracellular matrix. Collagen cross-link and deposition depend on lysyl hydroxylation, which is catalyzed by procollagen-lysine, 2-oxoglutarate 5-dioxygenase (PLOD). Aberrant lysyl hydroxylation and collagen cross-link contributes to the progression of many collagen-related diseases, such as fibrosis and cancer. Three lysyl hydroxylases (LH1, LH2, and LH3) are identified, encoded by PLOD1, PLOD2, and PLOD3 genes. Expression of PLODs is regulated by multiple cytokines, transcription factors and microRNAs. Dysregulation of PLODs promotes cancer progression and metastasis, suggesting that targeting PLODs is potential strategy for cancer treatment. Here, we summarize the recent progress in the investigation of function and regulation of PLODs in normal tissue development and disease progression, especially in cancer
Learning When to Concentrate or Divert Attention: Self-Adaptive Attention Temperature for Neural Machine Translation
Most of the Neural Machine Translation (NMT) models are based on the
sequence-to-sequence (Seq2Seq) model with an encoder-decoder framework equipped
with the attention mechanism. However, the conventional attention mechanism
treats the decoding at each time step equally with the same matrix, which is
problematic since the softness of the attention for different types of words
(e.g. content words and function words) should differ. Therefore, we propose a
new model with a mechanism called Self-Adaptive Control of Temperature (SACT)
to control the softness of attention by means of an attention temperature.
Experimental results on the Chinese-English translation and English-Vietnamese
translation demonstrate that our model outperforms the baseline models, and the
analysis and the case study show that our model can attend to the most relevant
elements in the source-side contexts and generate the translation of high
quality.Comment: To appear in EMNLP 201
Construction of spirocarbocycles via gold-catalyzed intramolecular dearomatization of naphthols.
A highly efficient, gold-catalyzed intramolecular dearomatization reaction of naphthols via 5-endo-dig cyclization is described. This facile and direct approach furnishes spirocarbocycles in excellent yields under mild conditions
Roles of PLODs in Collagen Synthesis and Cancer Progression
Collagen is the major component of extracellular matrix. Collagen cross-link and deposition depend on lysyl hydroxylation, which is catalyzed by procollagen-lysine, 2-oxoglutarate 5-dioxygenase (PLOD). Aberrant lysyl hydroxylation and collagen cross-link contributes to the progression of many collagen-related diseases, such as fibrosis and cancer. Three lysyl hydroxylases (LH1, LH2, and LH3) are identified, encoded by PLOD1, PLOD2, and PLOD3 genes. Expression of PLODs is regulated by multiple cytokines, transcription factors and microRNAs. Dysregulation of PLODs promotes cancer progression and metastasis, suggesting that targeting PLODs is potential strategy for cancer treatment. Here, we summarize the recent progress in the investigation of function and regulation of PLODs in normal tissue development and disease progression, especially in cancer
Review-Driven Multi-Label Music Style Classification by Exploiting Style Correlations
This paper explores a new natural language processing task, review-driven
multi-label music style classification. This task requires the system to
identify multiple styles of music based on its reviews on websites. The biggest
challenge lies in the complicated relations of music styles. It has brought
failure to many multi-label classification methods. To tackle this problem, we
propose a novel deep learning approach to automatically learn and exploit style
correlations. The proposed method consists of two parts: a label-graph based
neural network, and a soft training mechanism with correlation-based continuous
label representation. Experimental results show that our approach achieves
large improvements over the baselines on the proposed dataset. Especially, the
micro F1 is improved from 53.9 to 64.5, and the one-error is reduced from 30.5
to 22.6. Furthermore, the visualized analysis shows that our approach performs
well in capturing style correlations
The Quantitative Diagnosis Method of Rubbing Rotor System
The dynamics of the rubbing rotor system is analyzed by applying harmonic balance method. The relationship between harmonic components in the response of the rubbing rotor system and the dynamic stiffness matrix of the fault free rotor system is revealed, based on which a new model based method for rubbing identification is presented. By applying this method, the fault location and rubbing forces of the single rubbing rotor system can be identified by using vibration data of only two nodes, the rubbing locations and rubbing forces of the double rubbing rotor system can be identified by using vibration data of three nodes. The numerical simulations and experiments on the rotor test-rig are carried out to verify the efficiency of the present method
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