Quantum birth of the Universe in the varying speed of light cosmologies

In the framework of the varying speed of light theory the Wheeler-DeWitt equation is considered in the minisuperspace approximation. The quantum potential is obtained and the tunneling probability is studied in both Vilenkin and Hartle-Hawking approaches.published_or_final_versio

Structural assembly of two-domain proteins by rigid-body docking.

BACKGROUND: Modelling proteins with multiple domains is one of the central challenges in Structural Biology. Although homology modelling has successfully been applied for prediction of protein structures, very often domain-domain interactions cannot be inferred from the structures of homologues and their prediction requires ab initio methods. Here we present a new structural prediction approach for modelling two-domain proteins based on rigid-body domain-domain docking. RESULTS: Here we focus on interacting domain pairs that are part of the same peptide chain and thus have an inter-domain peptide region (so called linker). We have developed a method called pyDockTET (tethered-docking), which uses rigid-body docking to generate domain-domain poses that are further scored by binding energy and a pseudo-energy term based on restraints derived from linker end-to-end distances. The method has been benchmarked on a set of 77 non-redundant pairs of domains with available X-ray structure. We have evaluated the docking method ZDOCK, which is able to generate acceptable domain-domain orientations in 51 out of the 77 cases. Among them, our method pyDockTET finds the correct assembly within the top 10 solutions in over 60% of the cases. As a further test, on a subset of 20 pairs where domains were built by homology modelling, ZDOCK generates acceptable orientations in 13 out of the 20 cases, among which the correct assembly is ranked lower than 10 in around 70% of the cases by our pyDockTET method. CONCLUSION: Our results show that rigid-body docking approach plus energy scoring and linker-based restraints are useful for modelling domain-domain interactions. These positive results will encourage development of new methods for structural prediction of macromolecules with multiple (more than two) domains.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Initial results of selective renal parenchymal clamping with an adjustable kidney clamp in nephron-sparing surgery: an easy way to minimise renal ischaemia

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Deconvolution of positron annihilation coincidence Doppler broadening spectra using an iterative projected Newton method with non-negativity constraints

A generalized least-square method with Tikonov-Miller regularization and non-negativity constarints was developed for deconvoluting two-dimensional coincidence Doppler broadening spectroscopy (CDBS) spectra. A projected Newton algorithm was developed to solve the generalized least-square problem. The algorithm was used to deconvolute experimental CDBS data from aluminum was tested on Monte Carlo generated spectra. The retrieval of the positron-electron momentum distributions in the low momentum region was also demonstrated.published_or_final_versio

Prediction by graph theoretic measures of structural effects in proteins arising from non-synonymous single nucleotide polymorphisms.

Recent analyses of human genome sequences have given rise to impressive advances in identifying non-synonymous single nucleotide polymorphisms (nsSNPs). By contrast, the annotation of nsSNPs and their links to diseases are progressing at a much slower pace. Many of the current approaches to analysing disease-associated nsSNPs use primarily sequence and evolutionary information, while structural information is relatively less exploited. In order to explore the potential of such information, we developed a structure-based approach, Bongo (Bonds ON Graph), to predict structural effects of nsSNPs. Bongo considers protein structures as residue-residue interaction networks and applies graph theoretical measures to identify the residues that are critical for maintaining structural stability by assessing the consequences on the interaction network of single point mutations. Our results show that Bongo is able to identify mutations that cause both local and global structural effects, with a remarkably low false positive rate. Application of the Bongo method to the prediction of 506 disease-associated nsSNPs resulted in a performance (positive predictive value, PPV, 78.5%) similar to that of PolyPhen (PPV, 77.2%) and PANTHER (PPV, 72.2%). As the Bongo method is solely structure-based, our results indicate that the structural changes resulting from nsSNPs are closely associated to their pathological consequences

Minimal intervention for controlling nosocomial transmission of Methicillin-Resistant Staphylococcus aureus in resource limited setting with high endemicity

Objective: To control nosocomial transmission of methicillin-resistant Staphylococcus aureus (MRSA) in resource-limited healthcare setting with high endemicity. Methods: Three phases of infection control interventions were implemented in a University-affiliated hospital between 1- January-2004 and 31-December-2012. The first phase of baseline period, defined as the first 48-months of the study period, when all MRSA patients were managed with standard precautions, followed by a second phase of 24-months, when a hospital-wide hand hygiene campaign was launched. In the third phase of 36-months, contact precautions in open cubicle, use of dedicated medical items, and 2% chlorhexidine gluconate daily bathing for MRSA-positive patients were implemented while hand hygiene campaign was continued. The changes in the incidence rates of hospital-acquired MRSA-per- 1000-patient admissions, per-1000-patient-days, and per-1000-MRSA-positive-days were analyzed using segmented Poisson regression (an interrupted time series model). Usage density of broad-spectrum antibiotics was monitored. Results: During the study period, 4256 MRSA-positive patients were newly diagnosed, of which 1589 (37.3%) were hospitalacquired. The reduction of hospital-acquired MRSA per 1000-patient admissions, per 1000-patient-days, and per 1000- MRSA-positive-days from phase 1 to 2 was 36.3% (p<0.001), 30.4% (p<0.001), and 19.6% (p = 0.040), while the reduction of hospital-acquired MRSA per 1000-patient admissions, per 1000-patient-days, and per 1000-MRSA-positive-days from phase 2 to 3 was 27.4% (p<0.001), 24.1% (p<0.001), and 21.9% (p = 0.041) respectively. This reduction is sustained despite that the usage density of broad-spectrum antibiotics has increased from 132.02 (phase 1) to 168.99 per 1000 patient-days (phase 3). Conclusions: Nosocomial transmission of MRSA can be reduced with hand hygiene campaign, contact precautions in open cubicle, and 2% chlorhexidine gluconate daily bathing for MRSA-positive despite an increasing consumption of broadspectrum antibiotics. © 2014 Cheng et al.published_or_final_versio

Emergence of Carbapenem-Resistant Acinetobacter baumannii in Nursing Homes With High Background Rates of MRSA Colonization

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A time-domain control signal detection technique for OFDM

Transmission of system-critical control information plays a key role in efficient management of limited wireless network resources and successful reception of payload data information. This paper uses an orthogonal frequency division multiplexing (OFDM) architecture to investigate the detection performance of a time-domain approach used to detect deterministic control signalling information. It considers a type of control information chosen from a finite set of information, which is known at both transmitting and receiving wireless terminals. Unlike the maximum likelihood (ML) estimation method, which is often used, the time-domain detection technique requires no channel estimation and no pilots as it uses a form of time-domain correlation as the means of detection. Results show that when compared with the ML method, the time-domain approach improves detection performance even in the presence of synchronisation error caused by carrier frequency offset

3D time series analysis of cell shape using Laplacian approaches

Background: Fundamental cellular processes such as cell movement, division or food uptake critically depend on cells being able to change shape. Fast acquisition of three-dimensional image time series has now become possible, but we lack efficient tools for analysing shape deformations in order to understand the real three-dimensional nature of shape changes. Results: We present a framework for 3D+time cell shape analysis. The main contribution is three-fold: First, we develop a fast, automatic random walker method for cell segmentation. Second, a novel topology fixing method is proposed to fix segmented binary volumes without spherical topology. Third, we show that algorithms used for each individual step of the analysis pipeline (cell segmentation, topology fixing, spherical parameterization, and shape representation) are closely related to the Laplacian operator. The framework is applied to the shape analysis of neutrophil cells. Conclusions: The method we propose for cell segmentation is faster than the traditional random walker method or the level set method, and performs better on 3D time-series of neutrophil cells, which are comparatively noisy as stacks have to be acquired fast enough to account for cell motion. Our method for topology fixing outperforms the tools provided by SPHARM-MAT and SPHARM-PDM in terms of their successful fixing rates. The different tasks in the presented pipeline for 3D+time shape analysis of cells can be solved using Laplacian approaches, opening the possibility of eventually combining individual steps in order to speed up computations