1,475 research outputs found

    A survey on feature weighting based K-Means algorithms

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    This is a pre-copyedited, author-produced PDF of an article accepted for publication in Journal of Classification [de Amorim, R. C., 'A survey on feature weighting based K-Means algorithms', Journal of Classification, Vol. 33(2): 210-242, August 25, 2016]. Subject to embargo. Embargo end date: 25 August 2017. The final publication is available at Springer via http://dx.doi.org/10.1007/s00357-016-9208-4 Β© Classification Society of North America 2016In a real-world data set there is always the possibility, rather high in our opinion, that different features may have different degrees of relevance. Most machine learning algorithms deal with this fact by either selecting or deselecting features in the data preprocessing phase. However, we maintain that even among relevant features there may be different degrees of relevance, and this should be taken into account during the clustering process. With over 50 years of history, K-Means is arguably the most popular partitional clustering algorithm there is. The first K-Means based clustering algorithm to compute feature weights was designed just over 30 years ago. Various such algorithms have been designed since but there has not been, to our knowledge, a survey integrating empirical evidence of cluster recovery ability, common flaws, and possible directions for future research. This paper elaborates on the concept of feature weighting and addresses these issues by critically analysing some of the most popular, or innovative, feature weighting mechanisms based in K-Means.Peer reviewedFinal Accepted Versio

    Systematic identification of yeast cell cycle transcription factors using multiple data sources

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    <p>Abstract</p> <p>Background</p> <p>Eukaryotic cell cycle is a complex process and is precisely regulated at many levels. Many genes specific to the cell cycle are regulated transcriptionally and are expressed just before they are needed. To understand the cell cycle process, it is important to identify the cell cycle transcription factors (TFs) that regulate the expression of cell cycle-regulated genes.</p> <p>Results</p> <p>We developed a method to identify cell cycle TFs in yeast by integrating current ChIP-chip, mutant, transcription factor binding site (TFBS), and cell cycle gene expression data. We identified 17 cell cycle TFs, 12 of which are known cell cycle TFs, while the remaining five (Ash1, Rlm1, Ste12, Stp1, Tec1) are putative novel cell cycle TFs. For each cell cycle TF, we assigned specific cell cycle phases in which the TF functions and identified the time lag for the TF to exert regulatory effects on its target genes. We also identified 178 novel cell cycle-regulated genes, among which 59 have unknown functions, but they may now be annotated as cell cycle-regulated genes. Most of our predictions are supported by previous experimental or computational studies. Furthermore, a high confidence TF-gene regulatory matrix is derived as a byproduct of our method. Each TF-gene regulatory relationship in this matrix is supported by at least three data sources: gene expression, TFBS, and ChIP-chip or/and mutant data. We show that our method performs better than four existing methods for identifying yeast cell cycle TFs. Finally, an application of our method to different cell cycle gene expression datasets suggests that our method is robust.</p> <p>Conclusion</p> <p>Our method is effective for identifying yeast cell cycle TFs and cell cycle-regulated genes. Many of our predictions are validated by the literature. Our study shows that integrating multiple data sources is a powerful approach to studying complex biological systems.</p

    Angioplasty in acute middle cerebral artery stroke due to atrial fibrillation selected by CT perfusion: a case report

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    We report the experience of a case of acute stroke in a patient affected by Rendu Osler syndrome and atrial fibrillation. The combination of dynamic computerized tomography perfusion scans and the use of a high-compliance balloon allowed increasing the treatment window for intra-arterial recanalization over 6 h after stroke onset in a patient with middle cerebral artery occlusion

    A polymorphism at codon 31 of gene p21 is not associated with primary open angle glaucoma in Caucasians

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    BACKGROUND: Primary open angle glaucoma (POAG) is considered to be a neurodegenerative optic neuropathy, in which cell death occurs by apoptosis. p21, is an important protective component of the apoptotic pathway, regulating cellular arrest in the presence of DNA damage. An unstable or altered p21 protein could modify the cellular response to genomic injury and abolish the effect of p21. A previous study on a Chinese cohort suggested that the p21 codon 31 polymorphism may alter the state of apoptosis in glaucomatous optic neuropathy, failing to protect the ganglion cells. The aim of this study was to test the hypothesis that a p21 codon 31 polymorphism is associated with POAG on a Caucasian cohort. METHODS: 140 POAG patients and a control group of 73 healthy individuals were included in the study. All the subjects were of Caucasian origin. Genomic DNA was amplified by polymerase chain reaction, followed by enzymatic restriction fragment length polymorphism technique (PCR-RFLP). Patients and controls were genotyped for a single nucleotide polymorphism (C/A transversion) in the third base of codon 31 of p21, which leads to a serine (Ser)/arginine (Arg) substitution. RESULTS: The distribution of the genotypes in the POAG patients showed 128 (91.4%) Ser homozygotes, 10 (7.1%) Ser/Arg heterozygotes and 2 (1.5%) Arg homozygotes. In the control cohort, there were 61 (83.6%) Ser homozygotes and 12 (16.4%) Ser/Arg heterozygotes. No Arg homozygotes were present amongst the control group. Both the allelic and genotypic frequencies of the Ser or Arg residues at codon 31 were not significantly different between POAG patients and controls (Fisher's exact test, P = 0.20 for alleles and P = 0.0561 for genotypes). CONCLUSION: This study suggests that the p21 codon 31 polymorphism does not contribute to the risk of POAG in the Caucasian population

    Effect of prostaglandin E2 injection on the structural properties of the rat patellar tendon

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    Background: Increased tendon production of the inflammatory mediator prostaglandin E2 (PGE2) has been suggested to be a potential etiologic agent in the development of tendinopathy. Repeated injection of PGE2 into tendon has been proposed as a potential animal model for studying treatments for tendinopathy. In contrast, nonsteroidal anti-inflammatory drugs (NSAIDs) which inhibit PGE2 production and are commonly prescribed in treating tendinopathy have been shown to impair the healing of tendon after acute injury in animal models. The contradictory literature suggests the need to better define the functional effects of PGE2 on tendon. Our objective was to characterize the effects of PGE2 injection on the biomechanical and biochemical properties of tendon and the activity of the animals. Our hypothesis was that weekly PGE2 injection to the rat patellar tendon would lead to inferior biomechanical properties. Methods: Forty rats were divided equally into four groups. Three groups were followed for 4 weeks with the following peritendinous injection procedures: No injection (control), 4 weekly injections of saline (saline), 4 weekly injections of 800 ng PGE2 (PGE2-4 wks). The fourth group received 4 weekly injections of 800 ng PGE2 initially and was followed for a total of 8 weeks. All animals were injected bilaterally. The main outcome measurements included: the structural and material properties of the patellar tendon under tensile loading to failure, tendo

    Hypoxia Inhibits Osteogenesis in Human Mesenchymal Stem Cells through Direct Regulation of RUNX2 by TWIST

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    Bone loss induced by hypoxia is associated with various pathophysiological conditions, however, little is known about the effects of hypoxia and related signaling pathways on osteoblast differentiation and bone formation. Because bone marrow-derived mesenchymal stem cells (MSCs) survive under hypoxic conditions and readily differentiate into osteoblasts by standard induction protocols, they are a good in vitro model to study the effects of hypoxia on osteoblast differentiation.Using human MSCs, we discovered TWIST, a downstream target of HIF-1Ξ±, was induced under hypoxia and acted as a transcription repressor of RUNX2 through binding to the E-box located on the promoter of type 1 RUNX2. Suppression of type 1 RUNX2 by TWIST under hypoxia further inhibited the expression of BMP2, type 2 RUNX2 and downstream targets of RUNX2 in MSCs.Our findings point to the important role of hypoxia-mediated signalling in osteogenic differentiation in MSCs through direct regulation of RUNX2 by TWIST, and provide a method for modifying MSC osteogenesis upon application of these cells in fracture healing and bone reconstruction

    Cooperativity Dominates the Genomic Organization of p53-Response Elements: A Mechanistic View

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    p53-response elements (p53-REs) are organized as two repeats of a palindromic DNA segment spaced by 0 to 20 base pairs (bp). Several experiments indicate that in the vast majority of the human p53-REs there are no spacers between the two repeats; those with spacers, particularly with sizes beyond two nucleotides, are rare. This raises the question of what it indicates about the factors determining the p53-RE genomic organization. Clearly, given the double helical DNA conformation, the orientation of two p53 core domain dimers with respect to each other will vary depending on the spacer size: a small spacer of 0 to 2 bps will lead to the closest p53 dimer-dimer orientation; a 10-bp spacer will locate the p53 dimers on the same DNA face but necessitate DNA looping; while a 5-bp spacer will position the p53 dimers on opposite DNA faces. Here, via conformational analysis we show that when there are 0–2 bp spacers, p53-DNA binding is cooperative; however, cooperativity is greatly diminished when there are spacers with sizes beyond 2 bp. Cooperative binding is broadly recognized to be crucial for biological processes, including transcriptional regulation. Our results clearly indicate that cooperativity of the p53-DNA association dominates the genomic organization of the p53-REs, raising questions of the structural organization and functional roles of p53-REs with larger spacers. We further propose that a dynamic landscape scenario of p53 and p53-REs can better explain the selectivity of the degenerate p53-REs. Our conclusions bear on the evolutionary preference of the p53-RE organization and as such, are expected to have broad implications to other multimeric transcription factor response element organization

    Disease-Free Survival after Hepatic Resection in Hepatocellular Carcinoma Patients: A Prediction Approach Using Artificial Neural Network

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    Background: A database for hepatocellular carcinoma (HCC) patients who had received hepatic resection was used to develop prediction models for 1-, 3- and 5-year disease-free survival based on a set of clinical parameters for this patient group. Methods: The three prediction models included an artificial neural network (ANN) model, a logistic regression (LR) model, and a decision tree (DT) model. Data for 427, 354 and 297 HCC patients with histories of 1-, 3- and 5-year disease-free survival after hepatic resection, respectively, were extracted from the HCC patient database. From each of the three groups, 80 % of the cases (342, 283 and 238 cases of 1-, 3- and 5-year disease-free survival, respectively) were selected to provide training data for the prediction models. The remaining 20 % of cases in each group (85, 71 and 59 cases in the three respective groups) were assigned to validation groups for performance comparisons of the three models. Area under receiver operating characteristics curve (AUROC) was used as the performance index for evaluating the three models. Conclusions: The ANN model outperformed the LR and DT models in terms of prediction accuracy. This study demonstrated the feasibility of using ANNs in medical decision support systems for predicting disease-free survival based on clinical databases in HCC patients who have received hepatic resection

    Role of the Two Component Signal Transduction System CpxAR in Conferring Cefepime and Chloramphenicol Resistance in Klebsiella pneumoniae NTUH-K2044

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    Background: Klebsiella pneumoniae is a Gram-negative, non-motile, facultative anaerobe belonging to the Enterobacteriaceae family of the c-Proteobacteria class in the phylum Proteobacteria. Multidrug resistant K. pneumoniae have caused major therapeutic problems worldwide due to emergence of extended-spectrum b-lactamase producing strains. Twocomponent systems serve as a basic stimulus-response coupling mechanism to allow organisms to sense and respond to changes in many different environmental conditions including antibiotic stress. Principal Findings: In the present study, we investigated the role of an uncharacterized cpxAR operon in bacterial physiology and antimicrobial resistance by generating isogenic mutant (DcpxAR) deficient in the CpxA/CpxR component derived from the hyper mucoidal K1 strain K. pneumoniae NTUH-K2044. The behaviour of DcpxAR was determined under hostile conditions, reproducing stresses encountered in the gastrointestinal environment and deletion resulted in higher sensitivity to bile, osmotic and acid stresses. The DcpxAR was more susceptible to b-lactams and chloramphenicol than the wild-type strain, and complementation restored the altered phenotypes. The relative change in expression of acrB, acrD, eefB efflux genes were decreased in cpxAR mutant as evidenced by qRT-PCR. Comparison of outer membrane protein profiles indicated a conspicuous difference in the knock out background. Gel shift assays demonstrated direct binding of CpxR KP to promoter region of ompC KP in a concentration dependent manner
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