Unbelievable O(L1.5)O(L^{1.5}) worst case computational complexity achieved by spdspdsspdspds algorithm for linear programming problem

The Symmetric Primal-Dual Simplex Pivot Decision Strategy (spdspds) is a novel iterative algorithm to solve linear programming problems. Here, a simplex pivoting operation is considered simply as an exchange between a basic (dependent) variable and a non-basic (independent) variable, in the Tucker's Compact Symmetric Tableau (CST) which is a unique symmetric representation common to both the primal as well as the dual of a linear programming problem in its standard canonical form. From this viewpoint, the classical simplex pivoting operation of Dantzig may be considered as a restricted special case. The infeasibility index associated with a simplex tableau is defined as the sum of the number of primal variables and the number of dual variables, which are infeasible. A measure of goodness as a global effectiveness measure of a pivot selection is defined/determined as/by the decrease in the infeasibility index associated with such a pivot selection. At each iteration the selection of the simplex pivot element is governed by the anticipated decrease in the infeasibility index - seeking the best possible decrease in the infeasibility index - from among a wide range of candidate choices with non-zero values - limited only by considerations of potential numerical instability. Significant enhancement in computational efficiency can also be achieved by the utilization of the proposed concept of binding constraints. The algorithm terminates when further reduction in the infeasibility index is not possible; then the tableau is checked for the terminal tableau type to facilitate the problem classification - a termination with an infeasibility index of zero indicates optimum solution. The worst case computational complexity of spdspds is shown to be $O(L^{1.5})$.Comment: 20 pages, 7 figure

Mind Control Robotic Arm: Augmentative and Alternative Communication in the Classroom Environment

In recent years, technological advancements have greatly benefited the field of prosthetics. A large number of disabled people depend on prosthetics because they are an important technology. In order to provide augmentative and alternative methods of communication to these disabled people with various neuromuscular disorders, we must make sure they are provided with appropriate equipment to express themselves. Different types of arms are evaluated under robotic technology in terms of resistance, usability, flexibility, cost, and potential (such as robotic, surgical, bionic, prosthetic, and static arms). The main problems with these techniques are their high cost, the difficulty of installing and maintaining them, and the possibility of requiring surgery may arise. As a result, this paper is going to provide a description of the idea for combining an EEG controlled smart prosthetic arm with a smart robotic hand. An electrode headset is used to capture the signals from the robotic hand in order to control the device. Creating a robot arm that can help disabled people lead a more independent life is the main objective of this paper

TSLP signaling pathway map: a platform for analysis of TSLP-mediated signaling

Thymic stromal lymphopoietin (TSLP) is a four-helix bundle cytokine that plays a critical role in the regulation of immune responses and in the differentiation of hematopoietic cells. TSLP signals through a heterodimeric receptor complex consisting of an interleukin-7 receptor α chain and a unique TSLP receptor (TSLPR) [also known as cytokine receptor-like factor 2 (CRLF2)]. Cellular targets of TSLP include dendritic cells, B cells, mast cells, regulatory T (Treg) cells and CD4+ and CD8+ T cells. The TSLP/TSLPR axis can activate multiple signaling transduction pathways including the JAK/STAT pathway and the PI-3 kinase pathway. Aberrant TSLP/TSLPR signaling has been associated with a variety of human diseases including asthma, atopic dermatitis, nasal polyposis, inflammatory bowel disease, eosinophilic eosophagitis and, most recently, acute lymphoblastic leukemia. A centralized resource of the TSLP signaling pathway cataloging signaling events is not yet available. In this study, we present a literature-annotated resource of reactions in the TSLP signaling pathway. This pathway map is publicly available through NetPath (http://www.netpath.org/), an open access signal transduction pathway resource developed previously by our group. This map includes 236 molecules and 252 reactions that are involved in TSLP/TSLPR signaling pathway. We expect that the TSLP signaling pathway map will provide a rich resource to study the biology of this important cytokine as well as to identify novel therapeutic targets for diseases associated with dysregulated TSLP/TSLPR signaling. Database URL: http://www.netpath.org/pathways?path_id=NetPath_2

Phosphoproteomics of retinoblastoma:A pilot study identifies aberrant kinases

Retinoblastoma is a malignant tumour of the retina which most often occurs in children. Earlier studies on retinoblastoma have concentrated on the identification of key players in the disease and have not provided information on activated/inhibited signalling pathways. The dysregulation of protein phosphorylation in cancer provides clues about the affected signalling cascades in cancer. Phosphoproteomics is an ideal tool for the study of phosphorylation changes in proteins. Hence, global phosphoproteomics of retinoblastoma (RB) was carried out to identify signalling events associated with this cancer. Over 350 proteins showed differential phosphorylation in RB compared to control retina. Our study identified stress response proteins to be hyperphosphorylated in RB which included H2A histone family member X (H2AFX) and sirtuin 1. In particular, Ser140 of H2AFX also known as gamma-H2AX was found to be hyperphosphorylated in retinoblastoma, which indicated the activation of DNA damage response pathways. We also observed the activation of anti-apoptosis in retinoblastoma compared to control. These observations showed the activation of survival pathways in retinoblastoma. The identification of hyperphosphorylated protein kinases including Bromodomain containing 4 (BRD4), Lysine deficient protein kinase 1 (WNK1), and Cyclin-dependent kinase 1 (CDK1) in RB opens new avenues for the treatment of RB. These kinases can be considered as probable therapeutic targets for RB, as small-molecule inhibitors for some of these kinases are already in clinical trials for the treatment other cancers

A Bioinformatics Resource for TWEAK-Fn14 Signaling Pathway

TNF-related weak inducer of apoptosis (TWEAK) is a new member of the TNF superfamily. It signals through TNFRSF12A, commonly known as Fn14. The TWEAK-Fn14 interaction regulates cellular activities including proliferation, migration, differentiation, apoptosis, angiogenesis, tissue remodeling and inflammation. Although TWEAK has been reported to be associated with autoimmune diseases, cancers, stroke, and kidney-related disorders, the downstream molecular events of TWEAK-Fn14 signaling are yet not available in any signaling pathway repository. In this paper, we manually compiled from the literature, in particular those reported in human systems, the downstream reactions stimulated by TWEAK-Fn14 interactions. Our manual amassment of the TWEAK-Fn14 pathway has resulted in cataloging of 46 proteins involved in various biochemical reactions and TWEAK-Fn14 induced expression of 28 genes. We have enabled the availability of data in various standard exchange formats from NetPath, a repository for signaling pathways. We believe that this composite molecular interaction pathway will enable identification of new signaling components in TWEAK signaling pathway. This in turn may lead to the identification of potential therapeutic targets in TWEAK-associated disorders

5. 慢性円板状エリテマトーデスに続発せる棘細胞癌の1例について(第434(B)回千葉医学会例会 第15回千葉皮膚科臨床談話会)

Additional file 3: Table S3. Details of proteins identified in the study with reports on whether or not reported in PPD and gene ontology-based classification

MedlineRanker: flexible ranking of biomedical literature

The biomedical literature is represented by millions of abstracts available in the Medline database. These abstracts can be queried with the PubMed interface, which provides a keyword-based Boolean search engine. This approach shows limitations in the retrieval of abstracts related to very specific topics, as it is difficult for a non-expert user to find all of the most relevant keywords related to a biomedical topic. Additionally, when searching for more general topics, the same approach may return hundreds of unranked references. To address these issues, text mining tools have been developed to help scientists focus on relevant abstracts. We have implemented the MedlineRanker webserver, which allows a flexible ranking of Medline for a topic of interest without expert knowledge. Given some abstracts related to a topic, the program deduces automatically the most discriminative words in comparison to a random selection. These words are used to score other abstracts, including those from not yet annotated recent publications, which can be then ranked by relevance. We show that our tool can be highly accurate and that it is able to process millions of abstracts in a practical amount of time. MedlineRanker is free for use and is available at http://cbdm.mdc-berlin.de/tools/medlineranker

Discovering modulators of gene expression

Proteins that modulate the activity of transcription factors, often called modulators, play a critical role in creating tissue- and context-specific gene expression responses to the signals cells receive. GEM (Gene Expression Modulation) is a probabilistic framework that predicts modulators, their affected targets and mode of action by combining gene expression profiles, protein–protein interactions and transcription factor–target relationships. Using GEM, we correctly predicted a significant number of androgen receptor modulators and observed that most modulators can both act as co-activators and co-repressors for different target genes

HLungDB: an integrated database of human lung cancer research

The human lung cancer database (HLungDB) is a database with the integration of the lung cancer-related genes, proteins and miRNAs together with the corresponding clinical information. The main purpose of this platform is to establish a network of lung cancer-related molecules and to facilitate the mechanistic study of lung carcinogenesis. The entries describing the relationships between molecules and human lung cancer in the current release were extracted manually from literatures. Currently, we have collected 2585 genes and 212 miRNA with the experimental evidences involved in the different stages of lung carcinogenesis through text mining. Furthermore, we have incorporated the results from analysis of transcription factor-binding motifs, the promoters and the SNP sites for each gene. Since epigenetic alterations also play an important role in lung carcinogenesis, genes with epigenetic regulation were also included. We hope HLungDB will enrich our knowledge about lung cancer biology and eventually lead to the development of novel therapeutic strategies. HLungDB can be freely accessed at http://www.megabionet.org/bio/hlung