12,695 research outputs found
The role of proneurotrophins in apoptotic signaling in rat brain neurons:
No full textProneurotrophins and mature neurotrophins can activate distinct signaling pathways and have opposing effects on cells: proneurotrophins induce apoptotic signaling via p75NTR while mature neurotrophins activate survival signaling by binding to Trk receptors. In the CNS, basal forebrain (BF) neurons express both p75NTR and Trk receptors. The work in this thesis demonstrates that proneurotrophins can induce loss of BF neurons through p75NTR, even in the presence of activated Trk receptors. Moreover, proNGF inhibits the phosphorylation of Akt induced by BDNF, suggesting that proNGF induces apoptotic signaling and simultaneously blocks survival signaling activated by BDNF. Phosphorylation of Akt can prevent proNGF-induced apoptosis, suggesting that regulation of Akt phosphorylation may be a critical point of interaction between survival and death signaling.
PTEN (phosphatase and tensin homologue deleted on chromosome ten) is a dual-specificity phosphatase that can act as an antagonist to the PI3 kinase/Akt pathway. ProNGF induces an increase in PTEN in BF neurons, even in the presence of BDNF, suggesting that proNGF might block survival signaling through PTEN. In the presence of BDNF, proNGF was unable to induce apoptosis when PTEN activity was inhibited both in vitro and in vivo. Also, the PTEN inhibitor blocked proNGF-induced inhibition of Akt phosphorylation by BDNF, suggesting that PTEN is a crucial factor mediating the balance between p75-induced apoptotic signaling and Trk-mediated survival signaling.
Taken together, the interaction of proneurotrophin-p75NTR and mature neurotrophin-Trk systems is partially determined by the balance of PTEN and Akt which eventually causes the cell to die or survive.Ph.D.Includes bibliographical references (p. 97-119)by Wenyu Son
Neural shape codes for 3D model retrieval
No full textThe paradigm of Convolutional Neural Network (CNN) has already shown its potential for many challenging applications of computer vision, such as image classification, object detection and action recognition. In this paper, the task of 3D model retrieval is addressed by exploiting such promising paradigm. However, 3D models are usually represented with a collection of orderless points, lines and surfaces in a three dimensional space, which makes it difficult to involve the operation of convolution, pooling, etc. Yet, we propose a practical and effective way for applying CNN to 3D model retrieval, by training the network with the depth projections of 3D model. This CNN is regarded as a generic feature extractor for depth image. With large amounts of training data, the learned feature, which is called Neural Shape Codes, can handle various deformation changes that exist in shape analysis. The reported experimental results on several 3D shape benchmark datasets show the superior performance of the proposed method
Author Identification from Song Lyrics
No full textMachine Learning (ML) tools have been used extensively in a wide variety of domains
recently. Due the enormous amount of data being produced, machine learning techniques
are being heavily used to make sense of data & derive meaningful results. Using machine
learning tools, we can turn the data into knowledge.
Music is one of the truest forms of art. Bangladesh has a great history of music with a
great tradition of song writing over centuries. Authorship attribution is the way of
identifying the author from a linguistic corpus.
This paper demonstrates a guideline to identify the author of a Bengali song from the
lyrics of that song using machine learning. This research work presents the first work on
machine learning approach for author attribution from the lyrics of a song. Here six
methods of machine learning are used for the author identification and high accuracies
have been achieved from these methods. It is observed that Naïve Bayes method provides
higher accuracy in comparison with the other methods
Song
No full textAuthor attribution from Rudolph, 240. Printed on yellow paper with black ink. Set to the tune of "Happy land of Canaan". First line "You Rebels come along and listen to my song"
sj-csv-2-cix-10.1177_11769351221140101 – Supplemental material for Single-Cell Transcriptome Analysis Reveals Paraspeckles Expression in Osteosarcoma Tissues
No full textSupplemental material, sj-csv-2-cix-10.1177_11769351221140101 for Single-Cell Transcriptome Analysis Reveals Paraspeckles Expression in Osteosarcoma Tissues by Emel Rothzerg, Wenyu Feng, Dezhi Song, Hengyuan Li, Qingjun Wei, Archa Fox, David Wood, Jiake Xu and Yun Liu in Cancer Informatics</p
sj-docx-1-cix-10.1177_11769351221140101 – Supplemental material for Single-Cell Transcriptome Analysis Reveals Paraspeckles Expression in Osteosarcoma Tissues
No full textSupplemental material, sj-docx-1-cix-10.1177_11769351221140101 for Single-Cell Transcriptome Analysis Reveals Paraspeckles Expression in Osteosarcoma Tissues by Emel Rothzerg, Wenyu Feng, Dezhi Song, Hengyuan Li, Qingjun Wei, Archa Fox, David Wood, Jiake Xu and Yun Liu in Cancer Informatics</p
The Singer or the Song? Developments in Performers' Rights from the Perspective of a Cultural Economist
No full textOver the last century, performers gradually acquired statutory protection of their economic and moral
rights. These rights are not copyright in the legal sense but neighboring rights and until recently, they
were mainly remuneration rights that are collectively administered. With the WPPT (WIPO
Performers and Phonograms Treaty), performers now have individual exclusive rights for digital
performances; this leads to the question: what has motivated this change – is it a change in the
perception of the value of performer or a change brought about by the changing technology of copying or,
indeed, a change that reflects different economic costs and benefits? The paper discusses the role of
copyright law as an incentive to performers and asks if the economic role of the performer is so different
from that of the author. The conclusion is that a complex interaction of the legal regulations, economic
conditions and institutional arrangements for administering these new rights will determine the outcome
sj-pptx-1-cix-10.1177_11769351231161478 – Supplemental material for RNA-seq and Single-Cell Transcriptome Analyses of TRAIL Receptors Gene Expression in Human Osteosarcoma Cells and Tissues
No full textSupplemental material, sj-pptx-1-cix-10.1177_11769351231161478 for RNA-seq and Single-Cell Transcriptome Analyses of TRAIL Receptors Gene Expression in Human Osteosarcoma Cells and Tissues by Wenyu Feng, Haiyingjie Lin, Emel Rothzerg, Dezhi Song, Wenxiang Zhao, Tingting Ning, Qingjun Wei, Jinmin Zhao, David Wood, Yun Liu and Jiake Xu in Cancer Informatics</p
sj-pptx-2-cix-10.1177_11769351231161478 – Supplemental material for RNA-seq and Single-Cell Transcriptome Analyses of TRAIL Receptors Gene Expression in Human Osteosarcoma Cells and Tissues
No full textSupplemental material, sj-pptx-2-cix-10.1177_11769351231161478 for RNA-seq and Single-Cell Transcriptome Analyses of TRAIL Receptors Gene Expression in Human Osteosarcoma Cells and Tissues by Wenyu Feng, Haiyingjie Lin, Emel Rothzerg, Dezhi Song, Wenxiang Zhao, Tingting Ning, Qingjun Wei, Jinmin Zhao, David Wood, Yun Liu and Jiake Xu in Cancer Informatics</p
sj-pptx-3-cix-10.1177_11769351231161478 – Supplemental material for RNA-seq and Single-Cell Transcriptome Analyses of TRAIL Receptors Gene Expression in Human Osteosarcoma Cells and Tissues
No full textSupplemental material, sj-pptx-3-cix-10.1177_11769351231161478 for RNA-seq and Single-Cell Transcriptome Analyses of TRAIL Receptors Gene Expression in Human Osteosarcoma Cells and Tissues by Wenyu Feng, Haiyingjie Lin, Emel Rothzerg, Dezhi Song, Wenxiang Zhao, Tingting Ning, Qingjun Wei, Jinmin Zhao, David Wood, Yun Liu and Jiake Xu in Cancer Informatics</p
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