55 resultados para Kinase prediction
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Abstract Background: Many complex systems can be represented and analysed as networks. The recent availability of large-scale datasets, has made it possible to elucidate some of the organisational principles and rules that govern their function, robustness and evolution. However, one of the main limitations in using protein-protein interactions for function prediction is the availability of interaction data, especially for Mollicutes. If we could harness predicted interactions, such as those from a Protein-Protein Association Networks (PPAN), combining several protein-protein network function-inference methods with semantic similarity calculations, the use of protein-protein interactions for functional inference in this species would become more potentially useful. Results: In this work we show that using PPAN data combined with other approximations, such as functional module detection, orthology exploitation methods and Gene Ontology (GO)-based information measures helps to predict protein function in Mycoplasma genitalium. Conclusions: To our knowledge, the proposed method is the first that combines functional module detection among species, exploiting an orthology procedure and using information theory-based GO semantic similarity in PPAN of the Mycoplasma species. The results of an evaluation show a higher recall than previously reported methods that focused on only one organism network.
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Abstract: Asthma prevalence in children and adolescents in Spain is 10-17%. It is the most common chronic illness during childhood. Prevalence has been increasing over the last 40 years and there is considerable evidence that, among other factors, continued exposure to cigarette smoke results in asthma in children. No statistical or simulation model exist to forecast the evolution of childhood asthma in Europe. Such a model needs to incorporate the main risk factors that can be managed by medical authorities, such as tobacco (OR = 1.44), to establish how they affect the present generation of children. A simulation model using conditional probability and discrete event simulation for childhood asthma was developed and validated by simulating realistic scenario. The parameters used for the model (input data) were those found in the bibliography, especially those related to the incidence of smoking in Spain. We also used data from a panel of experts from the Hospital del Mar (Barcelona) related to actual evolution and asthma phenotypes. The results obtained from the simulation established a threshold of a 15-20% smoking population for a reduction in the prevalence of asthma. This is still far from the current level in Spain, where 24% of people smoke. We conclude that more effort must be made to combat smoking and other childhood asthma risk factors, in order to significantly reduce the number of cases. Once completed, this simulation methodology can realistically be used to forecast the evolution of childhood asthma as a function of variation in different risk factors.
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Substantial collective flow is observed in collisions between lead nuclei at Large Hadron Collider (LHC) as evidenced by the azimuthal correlations in the transverse momentum distributions of the produced particles. Our calculations indicate that the global v1-flow, which at RHIC peaked at negative rapidities (named third flow component or antiflow), now at LHC is going to turn toward forward rapidities (to the same side and direction as the projectile residue). Potentially this can provide a sensitive barometer to estimate the pressure and transport properties of the quark-gluon plasma. Our calculations also take into account the initial state center-of-mass rapidity fluctuations, and demonstrate that these are crucial for v1 simulations. In order to better study the transverse momentum flow dependence we suggest a new"symmetrized" vS1(pt) function, and we also propose a new method to disentangle global v1 flow from the contribution generated by the random fluctuations in the initial state. This will enhance the possibilities of studying the collective Global v1 flow both at the STAR Beam Energy Scan program and at LHC.
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This article reports on a lossless data hiding scheme for digital images where the data hiding capacity is either determined by minimum acceptable subjective quality or by the demanded capacity. In the proposed method data is hidden within the image prediction errors, where the most well-known prediction algorithms such as the median edge detector (MED), gradient adjacent prediction (GAP) and Jiang prediction are tested for this purpose. In this method, first the histogram of the prediction errors of images are computed and then based on the required capacity or desired image quality, the prediction error values of frequencies larger than this capacity are shifted. The empty space created by such a shift is used for embedding the data. Experimental results show distinct superiority of the image prediction error histogram over the conventional image histogram itself, due to much narrower spectrum of the former over the latter. We have also devised an adaptive method for hiding data, where subjective quality is traded for data hiding capacity. Here the positive and negative error values are chosen such that the sum of their frequencies on the histogram is just above the given capacity or above a certain quality.
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The study shows that social anxiety and persecutory ideation share many of the same predictive factors. Non-clinical paranoia may be a type of anxious fear. However, perceptual anomalies are a distinct predictor of paranoia. In the context of an individual feeling anxious, the occurrence of odd internal feelings in social situations may lead to delusional ideas through a sense of" things not seeming right". The study illustrates the approach of focusing on experiences such as paranoid thinking rather than diagnoses such as schizophrenia.
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The human PFKFB3 is composed of 19 exons spanning genomic region about 90,6 Kb (GenBank). Alternative splicing variants have been reported. The main variants corresponding to mRNAs of 4453 bp and 4224 bp for the variant 1 u-PFK2 (NM_004566.3) and variant 2 i-PFK2 (NM_001145443.1), respectively...
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Intrinsic resistance to the epidermal growth factor receptor (EGFR; HER1) tyrosine kinase inhibitor (TKI) gefitinib, and more generally to EGFR TKIs, is a common phenomenon in breast cancer. The availability of molecular criteria for predicting sensitivity to EGFR-TKIs is, therefore, the most relevant issue for their correct use and for planning future research. Though it appears that in non-small-cell lung cancer (NSCLC) response to gefitinib is directly related to the occurrence of specific mutations in the EGFR TK domain, breast cancer patients cannot be selected for treatment with gefitinib on the same basis as such EGFR mutations have beenreported neither in primary breast carcinomas nor in several breast cancer cell lines. Alternatively, there is a generalagreement on the hypothesis that the occurrence of molecular alterations that activate transduction pathways downstreamof EGFR (i.e., MEK1/MEK2 - ERK1/2 MAPK and PI-3'K - AKT growth/survival signaling cascades) significantly affect the response to EGFR TKIs in breast carcinomas. However,there are no studies so far addressing a role of EGF-related ligands as intrinsic breast cancer cell modulators of EGFR TKIefficacy. We recently monitored gene expression profiles andsub-cellular localization of HER-1/-2/-3/-4 related ligands (i.e., EGF, amphiregulin, transforming growth factor-α, ß-cellulin,epiregulin and neuregulins) prior to and after gefitinib treatment in a panel of human breast cancer cell lines. First, gefitinibinduced changes in the endogenous levels of EGF-related ligands correlated with the natural degree of breast cancer cellsensitivity to gefitinib. While breast cancer cells intrinsically resistant to gefitinib (IC50 ≥15 μM) markedly up-regulated(up to 600 times) the expression of genes codifying for HERspecific ligands, a significant down-regulation (up to 106 times)of HER ligand gene transcription was found in breast cancer cells intrinsically sensitive to gefitinib (IC50 ≤1 μM). Second,loss of HER1 function differentially regulated the nuclear trafficking of HER-related ligands. While gefitinib treatment induced an active import and nuclear accumulation of the HER ligand NRG in intrinsically gefitinib-resistant breastcancer cells, an active export and nuclear loss of NRG was observed in intrinsically gefitinib-sensitive breast cancer cells.In summary, through in vitro and pharmacodynamic studies we have learned that, besides mutations in the HER1 gene,oncogenic changes downstream of HER1 are the key players regulating gefitinib efficacy in breast cancer cells. It now appears that pharmacological inhibition of HER1 functionalso leads to striking changes in both the gene expression and the nucleo-cytoplasmic trafficking of HER-specific ligands,and that this response correlates with the intrinsic degree of breast cancer sensitivity to the EGFR TKI gefitinib. Therelevance of this previously unrecognized intracrine feedback to gefitinib warrants further studies as cancer cells could bypassthe antiproliferative effects of HER1-targeted therapeutics without a need for the overexpression and/or activation of other HER family members and/or the activation of HER-driven downstream signaling cascades
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Near-infrared spectroscopy (NIRS) was used to analyse the crude protein content of dried and milled samples of wheat and to discriminate samples according to their stage of growth. A calibration set of 72 samples from three growth stages of wheat (tillering, heading and harvest) and a validation set of 28 samples was collected for this purpose. Principal components analysis (PCA) of the calibration set discriminated groups of samples according to the growth stage of the wheat. Based on these differences, a classification procedure (SIMCA) showed a very accurate classification of the validation set samples : all of them were successfully classified in each group using this procedure when both the residual and the leverage were used in the classification criteria. Looking only at the residuals all the samples were also correctly classified except one of tillering stage that was assigned to both tillering and heading stages. Finally, the determination of the crude protein content of these samples was considered in two ways: building up a global model for all the growth stages, and building up local models for each stage, separately. The best prediction results for crude protein were obtained using a global model for samples in the two first growth stages (tillering and heading), and using a local model for the harvest stage samples.
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Regression equations predicting dissectable muscle weight in rabbits from external measurements were presented. Bone weight and weight of muscle groups were also carcass predicted. Predictive capacity of external measurements, retail cuts and muscle groups on total muscle, percent muscle, total bone and muscle to bone ratio were studied separately. Measurements on dissected retail cuts should be included in ordcr to obtain good equations for prediction of percent muscle in the carcass. Equations for predicting the muscle to bone ratio using external mcasurcments and data from the dissection of one hind leg were suggested. The equations had generally high coefficients of determination. The coefficient of determination for prediction of dissectable muscle was 0.91, and for percent muscle in the carcass 0.79.
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Modulation of signalling pathways can trigger different cellular responses, including differences in cell fate. This modulation can be achieved by controlling the pathway activity with great precision to ensure robustness and reproducibility of the specification of cell fate. The development of the photoreceptor R7 in the Drosophila melanogasterretina has become a model in which to investigate the control of cell signalling. During R7 specification, a burst of Ras small GTPase (Ras) and mitogen-activated protein kinase (MAPK) controlled by Sevenless receptor tyrosine kinase (Sev) is required. Several cells in each ommatidium express sev. However, the spatiotemporal expression of the boss ligand and the action of negative regulators of the Sev pathway will restrict the R7 fate to a single cell. The Drosophila suppressor of cytokine signalling 36E (SOCS36E) protein contains an SH2 domain and acts as a Sev signalling attenuator. By contrast, downstream of receptor kinase (Drk), the fly homolog of the mammalian Grb2 adaptor protein, which also contains an SH2 domain, acts as a positive activator of the pathway. Here, we apply the Förster resonance energy transfer (FRET) assay to transfected Drosophila S2 cells and demonstrate that Sev binds directly to either the suppressor protein SOCS36E or the adaptor protein Drk. We propose a mechanistic model in which the competition between these two proteins for binding to the same docking site results in either attenuation of the Sev transduction in cells that should not develop R7 photoreceptors or amplification of the Ras-MAPK signal only in the R7 precursor.
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The recently discovered apolipoprotein AV (apoAV) gene has been reported to be a key player in modulating plasma triglyceride levels. Here we identify the hepatocyte nuclear factor-4 (HNF-4 ) as a novel regulator of human apoAV gene. Inhibition of HNF-4 expression by small interfering RNA resulted in down-regulation of apoAV. Deletion, mutagenesis, and binding assays revealed that HNF-4 directly regulates human apoAV promoter through DR1 [a direct repeat separated by one nucleotide (nt)], and via a novel element for HNF-4 consisting of an inverted repeat separated by 8 nt (IR8). In addition, we show that the coactivator peroxisome proliferator-activated receptor- coactivator-1 was capable of stimulating the HNF-4 -dependent transactivation of apoAV promoter. Furthermore, analyses in human hepatic cells demonstrated that AMP-activated protein kinase (AMPK) and the MAPK signaling pathway regulate human apoAV expression and suggested that this regulation may be mediated, at least in part, by changes in HNF-4 . Intriguingly, EMSAs and mice with a liver-specific disruption of the HNF-4 gene revealed a species-distinct regulation of apoAV by HNF-4 , which resembles that of a subset of HNF-4 target genes. Taken together, our data provide new insights into the binding properties and the modulation of HNF-4 and underscore the role of HNF-4 in regulating triglyceride metabolism.
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6-Phosphofructo-2-kinase/fructose-2,6-bisphosphatase (PFKFB)catalyzes the synthesis and degradation of fructose-2,6-bisphosphate, a key modulator of glycolysis-gluconeogenesis. To gain insight into the molecular mechanism behind hormonal and nutritional regulation of PFKFB expression, we have cloned and characterized the proximal promoter region of the liver isoform of PFKFB (PFKFB1) from gilthead sea bream (Sparus aurata). Transient transfection of HepG2 cells with deleted gene promoter constructs and electrophoretic mobility shift assays allowed us to identify a sterol regulatory element (SRE) to which SRE binding protein-1a (SREBP-1a)binds and transactivates PFKFB1 gene transcription. Mutating the SRE box abolished SREBP-1a binding and transactivation. The in vivo binding of SREBP-1a to the SRE box in the S. aurata PFKFB1 promoter was confirmed by chromatin immunoprecipitation assays. There is a great deal of evidence for a postprandial rise of PFKB1 mRNA levels in fish and rats. Consistently, starved-to-fed transition and treatment with glucose or insulin increased SREBP-1 immunodetectable levels, SREBP-1 association to PFKFB1 promoter, and PFKFB1 mRNA levels in the piscine liver. Our findings demonstrate involvement of SREBP-1a in the transcriptional activation of PFKFB1, and we conclude that SREBP-1a may exert a key role mediating postprandial activation of PFKFB1 transcription.
Resumo:
6-Phosphofructo-2-kinase/fructose-2,6-bisphosphatase (PFKFB)catalyzes the synthesis and degradation of fructose-2,6-bisphosphate, a key modulator of glycolysis-gluconeogenesis. To gain insight into the molecular mechanism behind hormonal and nutritional regulation of PFKFB expression, we have cloned and characterized the proximal promoter region of the liver isoform of PFKFB (PFKFB1) from gilthead sea bream (Sparus aurata). Transient transfection of HepG2 cells with deleted gene promoter constructs and electrophoretic mobility shift assays allowed us to identify a sterol regulatory element (SRE) to which SRE binding protein-1a (SREBP-1a)binds and transactivates PFKFB1 gene transcription. Mutating the SRE box abolished SREBP-1a binding and transactivation. The in vivo binding of SREBP-1a to the SRE box in the S. aurata PFKFB1 promoter was confirmed by chromatin immunoprecipitation assays. There is a great deal of evidence for a postprandial rise of PFKB1 mRNA levels in fish and rats. Consistently, starved-to-fed transition and treatment with glucose or insulin increased SREBP-1 immunodetectable levels, SREBP-1 association to PFKFB1 promoter, and PFKFB1 mRNA levels in the piscine liver. Our findings demonstrate involvement of SREBP-1a in the transcriptional activation of PFKFB1, and we conclude that SREBP-1a may exert a key role mediating postprandial activation of PFKFB1 transcription.
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Abstract Objective: We aimed to determine the validity of two risk scores for patients with non-muscle invasive bladder cancer in different European settings, in patients with primary tumours. Methods: We included 1,892 patients with primary stage Ta or T1 non-muscle invasive bladder cancer who underwent a transurethral resection in Spain (n = 973), the Netherlands (n = 639), or Denmark (n = 280). We evaluated recurrence-free survival and progression-free survival according to the European Organisation for Research and Treatment of Cancer (EORTC) and the Spanish Urological Club for Oncological Treatment (CUETO) risk scores for each patient and used the concordance index (c-index) to indicate discriminative ability. Results: The 3 cohorts were comparable according to age and sex, but patients from Denmark had a larger proportion of patients with the high stage and grade at diagnosis (p,0.01). At least one recurrence occurred in 839 (44%) patients and 258 (14%) patients had a progression during a median follow-up of 74 months. Patients from Denmark had the highest 10- year recurrence and progression rates (75% and 24%, respectively), whereas patients from Spain had the lowest rates (34% and 10%, respectively). The EORTC and CUETO risk scores both predicted progression better than recurrence with c-indices ranging from 0.72 to 0.82 while for recurrence, those ranged from 0.55 to 0.61. Conclusion: The EORTC and CUETO risk scores can reasonably predict progression, while prediction of recurrence is more difficult. New prognostic markers are needed to better predict recurrence of tumours in primary non-muscle invasive bladder cancer patients.
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The prediction filters are well known models for signal estimation, in communications, control and many others areas. The classical method for deriving linear prediction coding (LPC) filters is often based on the minimization of a mean square error (MSE). Consequently, second order statistics are only required, but the estimation is only optimal if the residue is independent and identically distributed (iid) Gaussian. In this paper, we derive the ML estimate of the prediction filter. Relationships with robust estimation of auto-regressive (AR) processes, with blind deconvolution and with source separation based on mutual information minimization are then detailed. The algorithm, based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics. Experimental results emphasize on the interest of this approach.