Geometric aspects of space-time reflection symmetry in quantum mechanics

For nearly two decades, much research has been carried out on properties of physical systems described by Hamiltonians that are not Hermitian in the conventional sense, but are symmetric under space-time reflection; that is, they exhibit PT symmetry. Such Hamiltonians can be used to model the behavior of closed quantum systems, but they can also be replicated in open systems for which gain and loss are carefully balanced, and this has been implemented in laboratory experiments for a wide range of systems. Motivated by these ongoing research activities, we investigate here a particular theoretical aspect of the subject by unraveling the geometric structures of Hilbert spaces endowed with the parity and time-reversal operations, and analyze the characteristics ofPT -symmetric Hamiltonians. A canonical relation between aPT -symmetric operator and a Hermitian operator is established in a geometric setting. The quadratic form corresponding to the parity operator, in particular, gives rise to a natural partition of the Hilbert space into two halves corresponding to states having positive and negative PT norm. Positive definiteness of the norm can be restored by introducing a conjugation operator C ; this leads to a positive-definite inner product in terms of CPT conjugation

Accurate Prediction of Protein Structural Class

Because of the increasing gap between the data from sequencing and structural genomics, the accurate prediction of the structural class of a protein domain solely from the primary sequence has remained a challenging problem in structural biology. Traditional sequence-based predictors generally select several sequence features and then feed them directly into a classification program to identify the structural class. The current best sequence-based predictor achieved an overall accuracy of 74.1% when tested on a widely used, non-homologous benchmark dataset 25PDB. In the present work, we built a multiple linear regression (MLR) model to convert the 440-dimensional (440D) sequence feature vector extracted from the Position Specific Scoring Matrix (PSSM) of a protein domain to a 4-dimensinal (4D) structural feature vector, which could then be used to predict the four major structural classes. We performed 10-fold cross-validation and jackknife tests of the method on a large non-homologous dataset containing 8,244 domains distributed among the four major classes. The performance of our approach outperformed all of the existing sequence-based methods and had an overall accuracy of 83.1%, which is even higher than the results of those predicted secondary structure-based methods

Prevalence of visual impairment, cataract surgery and awareness of cataract and glaucoma in Bhaktapur district of Nepal: The Bhaktapur Glaucoma Study

<p>Abstract</p> <p>Background</p> <p>Cataract and glaucoma are the major causes of blindness in Nepal. Bhaktapur is one of the three districts of Kathmandu valley which represents a metropolitan city with a predominantly agrarian rural periphery. This study was undertaken to determine the prevalence of visual impairment, cataract surgery and awareness of cataract and glaucoma among subjects residing in this district of Nepal.</p> <p>Methods</p> <p>Subjects aged 40 years and above was selected using a cluster sampling methodology and a door to door enumeration was conducted for a population based cross sectional study. During the community field work, 11499 subjects underwent a structured interview regarding awareness (heard of) and knowledge (understanding of the disease) of cataract and glaucoma. At the base hospital 4003 out of 4800 (83.39%) subjects underwent a detailed ocular examination including log MAR visual acuity, refraction, applanation tonometry, cataract grading (LOCSΙΙ), retinal examination and SITA standard perimetry when indicated.</p> <p>Results</p> <p>The age-sex adjusted prevalence of blindness (best corrected <3/60) and low vision (best corrected <6/18 ≥3/60) was 0.43% (95%C.I. 0.25 - 0.68) and 3.97% (95% C.I. 3.40 - 4.60) respectively. Cataract (53.3%) was the principal cause of blindness. The leading causes of low vision were cataract (60.8%) followed by refractive error (12%). The cataract surgical coverage was 90.36% and was higher in the younger age group, females and illiterate subjects. Pseudophakia was seen in 94%. Awareness of cataract (6.7%) and glaucoma (2.4%) was very low. Among subjects who were aware, 70.4% had knowledge of cataract and 45.5% of glaucoma. Cataract was commonly known to be a 'pearl like dot' white opacity in the eye while glaucoma was known to cause blindness. Awareness remained unchanged in different age groups for cataract while for glaucoma there was an increase in awareness with age. Women were significantly less aware (odds ratio (OR): 0.63; 95%, confidence interval (CI): 0.54 - 0.74) for cataract and (OR: 0.64; 95% CI: 0.50 - 0.81) for glaucoma. Literacy was also correlated with awareness.</p> <p>Conclusion</p> <p>The low prevalence of visual impairment and the high cataract surgical coverage suggests that cataract intervention programs have been successful in Bhaktapur. Awareness and knowledge of cataract and glaucoma was very poor among this population. Eye care programs needs to be directed towards preventing visual impairment from refractive errors, screening for incurable chronic eye diseases and promoting health education in order to raise awareness on cataract and glaucoma among this population.</p

Functional discrimination of membrane proteins using machine learning techniques

<p>Abstract</p> <p>Background</p> <p>Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amino acid residues in membrane proteins that perform major functions, such as channels/pores, electrochemical potential-driven transporters and primary active transporters.</p> <p>Results</p> <p>We observed that the residues Asp, Asn and Tyr are dominant in channels/pores whereas the composition of hydrophobic residues, Phe, Gly, Ile, Leu and Val is high in electrochemical potential-driven transporters. The composition of all the amino acids in primary active transporters lies in between other two classes of proteins. We have utilized different machine learning algorithms, such as, Bayes rule, Logistic function, Neural network, Support vector machine, Decision tree etc. for discriminating these classes of proteins. We observed that most of the algorithms have discriminated them with similar accuracy. The neural network method discriminated the channels/pores, electrochemical potential-driven transporters and active transporters with the 5-fold cross validation accuracy of 64% in a data set of 1718 membrane proteins. The application of amino acid occurrence improved the overall accuracy to 68%. In addition, we have discriminated transporters from other α-helical and β-barrel membrane proteins with the accuracy of 85% using k-nearest neighbor method. The classification of transporters and all other proteins (globular and membrane) showed the accuracy of 82%.</p> <p>Conclusion</p> <p>The performance of discrimination with amino acid occurrence is better than that with amino acid composition. We suggest that this method could be effectively used to discriminate transporters from all other globular and membrane proteins, and classify them into channels/pores, electrochemical and active transporters.</p

'Unite and conquer': enhanced prediction of protein subcellular localization by integrating multiple specialized tools

<p>Abstract</p> <p>Background</p> <p>Knowing the subcellular location of proteins provides clues to their function as well as the interconnectivity of biological processes. Dozens of tools are available for predicting protein location in the eukaryotic cell. Each tool performs well on certain data sets, but their predictions often disagree for a given protein. Since the individual tools each have particular strengths, we set out to integrate them in a way that optimally exploits their potential. The method we present here is applicable to various subcellular locations, but tailored for predicting whether or not a protein is localized in mitochondria. Knowledge of the mitochondrial proteome is relevant to understanding the role of this organelle in global cellular processes.</p> <p>Results</p> <p>In order to develop a method for enhanced prediction of subcellular localization, we integrated the outputs of available localization prediction tools by several strategies, and tested the performance of each strategy with known mitochondrial proteins. The accuracy obtained (up to 92%) surpasses by far the individual tools. The method of integration proved crucial to the performance. For the prediction of mitochondrion-located proteins, integration via a two-layer decision tree clearly outperforms simpler methods, as it allows emphasis of biologically relevant features such as the mitochondrial targeting peptide and transmembrane domains.</p> <p>Conclusion</p> <p>We developed an approach that enhances the prediction accuracy of mitochondrial proteins by uniting the strength of specialized tools. The combination of machine-learning based integration with biological expert knowledge leads to improved performance. This approach also alleviates the conundrum of how to choose between conflicting predictions. Our approach is easy to implement, and applicable to predicting subcellular locations other than mitochondria, as well as other biological features. For a trial of our approach, we provide a webservice for mitochondrial protein prediction (named YimLOC), which can be accessed through the AnaBench suite at http://anabench.bcm.umontreal.ca/anabench/. The source code is provided in the Additional File <supplr sid="S2">2</supplr>.</p> <suppl id="S2"> <title> <p>Additional file 2</p> </title> <text> <p>This file contains scripts for the online server YimLOC. Please note that there scripts only codes for the ready-to-use STACK-mem-DT described in the main text. The scripts do not provide the training process.</p> </text> <file name="1471-2105-8-420-S2.pdf"> <p>Click here for file</p> </file> </suppl

Dissimilarity in the Folding of Human Cytosolic Creatine Kinase Isoenzymes

Creatine kinase (CK, EC 2.7.3.2) plays a key role in the energy homeostasis of excitable cells. The cytosolic human CK isoenzymes exist as homodimers (HMCK and HBCK) or a heterodimer (MBCK) formed by the muscle CK subunit (M) and/or brain CK subunit (B) with highly conserved three-dimensional structures composed of a small N-terminal domain (NTD) and a large C-terminal domain (CTD). The isoforms of CK provide a novel system to investigate the sequence/structural determinants of multimeric/multidomain protein folding. In this research, the role of NTD and CTD as well as the domain interactions in CK folding was investigated by comparing the equilibrium and kinetic folding parameters of HMCK, HBCK, MBCK and two domain-swapped chimeric forms (BnMc and MnBc). Spectroscopic results indicated that the five proteins had distinct structural features depending on the domain organizations. MBCK BnMc had the smallest CD signals and the lowest stability against guanidine chloride-induced denaturation. During the biphasic kinetic refolding, three proteins (HMCK, BnMc and MnBc), which contained either the NTD or CTD of the M subunit and similar microenvironments of the Trp fluorophores, refolded about 10-fold faster than HBCK for both the fast and slow phase. The fast folding of these three proteins led to an accumulation of the aggregation-prone intermediate and slowed down the reactivation rate thereby during the kinetic refolding. Our results suggested that the intra- and inter-subunit domain interactions modified the behavior of kinetic refolding. The alternation of domain interactions based on isoenzymes also provides a valuable strategy to improve the properties of multidomain enzymes in biotechnology

Life-threatening hemobilia caused by hepatic pseudoaneurysm after T-tube choledochostomy: report of a case

<p>Abstract</p> <p>Background</p> <p>Hemobilia is a rare but lethal biliary tract complication. There are several causes of hemobilia which might be classified as traumatic or nontraumatic. Hemobilia caused by pseudoaneurysm might result from hepatobiliary surgery or percutaneous interventional hepatobiliary procedures. However, to our knowledge, there are no previous reports pertaining to hemobilia caused by hepatic pseudoaneurysm after T-tube choledochostomy.</p> <p>Case presentation</p> <p>A 65-year-old male was admitted to our hospital because of acute calculous cholecystitis and cholangitis. He underwent cholecystectomy, choledocholithotomy via a right upper quadrant laparotomy and a temporary T-tube choledochostomy was created. However, on the 19th day after operation, he suffered from sudden onset of hematemesis and massive fresh blood drainage from the T-tube choledochostomy. Imaging studies confirmed the diagnosis of pseudoaneurysm associated hemobilia. The probable association of T-tube choledochostomy with pseudoaneurysm and hemobilia is also demonstrated. He underwent emergent selective microcoils emobolization to occlude the feeding artery of the pseudoaneurysm.</p> <p>Conclusions</p> <p>Pseudoaneurysm associated hemobilia may occur after T-tube choledochostomy. This case also highlights the importance that hemobilia should be highly suspected in a patient presenting with jaundice, right upper quadrant abdominal pain and upper gastrointestinal bleeding after liver or biliary surgery.</p

SOCS2-Induced Proteasome-Dependent TRAF6 Degradation: A Common Anti-Inflammatory Pathway for Control of Innate Immune Responses

Pattern recognition receptors and receptors for pro-inflammatory cytokines provide critical signals to drive the development of protective immunity to infection. Therefore, counter-regulatory pathways are required to ensure that overwhelming inflammation harm host tissues. Previously, we showed that lipoxins modulate immune response during infection, restraining inflammation during infectious diseases in an Aryl hydrocarbon receptor (AhR)/suppressors of cytokine signaling (SOCS)2-dependent-manner. Recently, Indoleamine-pyrrole 2,3- dioxygenase (IDO)-derived tryptophan metabolites, including L-kynurenine, were also shown to be involved in several counter-regulatory mechanisms. Herein, we addressed whether the intracellular molecular events induced by lipoxins mediating control of innate immune signaling are part of a common regulatory pathway also shared by L-kynurenine exposure. We demonstrate that Tumor necrosis factor receptor-associated factor (TRAF)6 – member of a family of adapter molecules that couple the TNF receptor and interleukin-1 receptor/Toll-like receptor families to intracellular signaling events essential for the development of immune responses – is targeted by both lipoxins and L-kynurenine via an AhR/SOCS2-dependent pathway. Furthermore, we show that LXA4- and L-kynurenine-induced AhR activation, its subsequent nuclear translocation, leading SOCS2 expression and TRAF6 Lys47-linked poly-ubiquitination and proteosome-mediated degradation of the adapter proteins. The in vitro consequences of such molecular interactions included inhibition of TLR- and cytokine receptor-driven signal transduction and cytokine production. Subsequently, in vivo proteosome inhibition led to unresponsiveness to lipoxins, as well as to uncontrolled pro-inflammatory reactions and elevated mortality during toxoplasmosis. In summary, our results establish proteasome degradation of TRAF6 as a key molecular target for the anti-inflammatory pathway triggered by lipoxins and L-kynurenine, critical counter-regulatory mediators in the innate and adaptive immune systems

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal