Preserving entanglement under decoherence and sandwiching all separable states

Every entangled state can be perturbed, for instance by decoherence, and stay entangled. For a large class of pure entangled states, we show how large the perturbation can be. Our class includes all pure bipartite and all maximally entangled states. For an entangled state, E, the constucted neighborhood of entangled states is the region outside two parallel hyperplanes, which sandwich the set of all separable states. The states for which these neighborhoods are largest are the maximally entangled ones. As the number of particles, or the dimensions of the Hilbert spaces for two of the particles increases, the distance between two of the hyperplanes which sandwich the separable states goes to zero. It is easy to decide if a state Q is in the neighborhood of entangled states we construct for an entangled state E. One merely has to check if the trace of EQ is greater than a constant which depends upon E and which we determine.Comment: Corrected first author's e-mail address. All the rest remains unchange

On the Numerical Study of the Complexity and Fractal Dimension of CMB Anisotropies

We consider the problem of numerical computation of the Kolmogorov complexity and the fractal dimension of the anisotropy spots of Cosmic Microwave Background (CMB) radiation. Namely, we describe an algorithm of estimation of the complexity of spots given by certain pixel configuration on a grid and represent the results of computations for a series of structures of different complexity. Thus, we demonstrate the calculability of such an abstract descriptor as the Kolmogorov complexity for CMB digitized maps. The correlation of complexity of the anisotropy spots with their fractal dimension is revealed as well. This technique can be especially important while analyzing the data of the forthcoming space experiments.Comment: LATEX, 3 figure

Treatment utilization and outcomes in elderly patients with locally advanced esophageal carcinoma: A review of the National Cancer Database

For elderly patients with locally advanced esophageal cancer, therapeutic approaches and outcomes in a modern cohort are not well characterized. Patients ≥70 years old with clinical stage II and III esophageal cancer diagnosed between 1998 and 2012 were identified from the National Cancer Database and stratified based on treatment type. Variables associated with treatment utilization were evaluated using logistic regression and survival evaluated using Cox proportional hazards analysis. Propensity matching (1:1) was performed to help account for selection bias. A total of 21,593 patients were identified. Median and maximum ages were 77 and 90, respectively. Treatment included palliative therapy (24.3%), chemoradiation (37.1%), trimodality therapy (10.0%), esophagectomy alone (5.6%), or no therapy (12.9%). Age ≥80 (OR 0.73), female gender (OR 0.81), Charlson-Deyo comorbidity score ≥2 (OR 0.82), and high-volume centers (OR 0.83) were associated with a decreased likelihood of palliative therapy versus no treatment. Age ≥80 (OR 0.79) and Clinical Stage III (OR 0.33) were associated with a decreased likelihood, while adenocarcinoma histology (OR 1.33) and nonacademic cancer centers (OR 3.9), an increased likelihood of esophagectomy alone compared to definitive chemoradiation. Age ≥80 (OR 0.15), female gender (OR 0.80), and non-Caucasian race (OR 0.63) were associated with a decreased likelihood, while adenocarcinoma histology (OR 2.10) and high-volume centers (OR 2.34), an increased likelihood of trimodality therapy compared to definitive chemoradiation. Each treatment type demonstrated improved survival compared to no therapy: palliative treatment (HR 0.49) to trimodality therapy (HR 0.25) with significance between all groups. Any therapy, including palliative care, was associated with improved survival; however, subsets of elderly patients with locally advanced esophageal cancer are less likely to receive aggressive therapy. Care should be taken to not unnecessarily deprive these individuals of treatment that may improve survival

Comparing postural stability entropy analyses to differentiate fallers and non-fallers

The health and financial cost of falls has spurred research to differentiate the characteristics of fallers and non-fallers. Postural stability has received much of the attention with recent studies exploring various measures of entropy. This study compared the discriminatory ability of several entropy methods at differentiating two paradigms in the center-of-pressure of elderly individuals: (1) eyes open (EO) vs. eyes closed (EC) and (2) fallers (F) vs. non-fallers (NF). Methods were compared using the area under the curve (AUC) of the receiver-operating characteristic curves developed from logistic regression models. Overall, multiscale entropy (MSE) and composite multiscale entropy (CompMSE) performed the best with AUCs of 0.71 for EO/EC and 0.77 for F/NF. When methods were combined together to maximize the AUC, the entropy classifier had an AUC of for 0.91 the F/NF comparison. These results suggest researchers and clinicians attempting to create clinical tests to identify fallers should consider a combination of every entropy method when creating a classifying test. Additionally, MSE and CompMSE classifiers using polar coordinate data outperformed rectangular coordinate data, encouraging more research into the most appropriate time series for postural stability entropy analysis

Data incongruence and the problem of avian louse phylogeny

Recent studies based on different types of data (i.e. morphological and molecular) have supported conflicting phylogenies for the genera of avian feather lice (Ischnocera: Phthiraptera). We analyse new and published data from morphology and from mitochondrial (12S rRNA and COI) and nuclear (EF1-) genes to explore the sources of this incongruence and explain these conflicts. Character convergence, multiple substitutions at high divergences, and ancient radiation over a short period of time have contributed to the problem of resolving louse phylogeny with the data currently available. We show that apparent incongruence between the molecular datasets is largely attributable to rate variation and nonstationarity of base composition. In contrast, highly significant character incongruence leads to topological incongruence between the molecular and morphological data. We consider ways in which biases in the sequence data could be misleading, using several maximum likelihood models and LogDet corrections. The hierarchical structure of the data is explored using likelihood mapping and SplitsTree methods. Ultimately, we concede there is strong discordance between the molecular and morphological data and apply the conditional combination approach in this case. We conclude that higher level phylogenetic relationships within avian Ischnocera remain extremely problematic. However, consensus between datasets is beginning to converge on a stable phylogeny for avian lice, at and below the familial rank

Nonlinear software sensor for monitoring genetic regulation processes with noise and modeling errors

Nonlinear control techniques by means of a software sensor that are commonly used in chemical engineering could be also applied to genetic regulation processes. We provide here a realistic formulation of this procedure by introducing an additive white Gaussian noise, which is usually found in experimental data. Besides, we include model errors, meaning that we assume we do not know the nonlinear regulation function of the process. In order to illustrate this procedure, we employ the Goodwin dynamics of the concentrations [B.C. Goodwin, Temporal Oscillations in Cells, (Academic Press, New York, 1963)] in the simple form recently applied to single gene systems and some operon cases [H. De Jong, J. Comp. Biol. 9, 67 (2002)], which involves the dynamics of the mRNA, given protein, and metabolite concentrations. Further, we present results for a three gene case in co-regulated sets of transcription units as they occur in prokaryotes. However, instead of considering their full dynamics, we use only the data of the metabolites and a designed software sensor. We also show, more generally, that it is possible to rebuild the complete set of nonmeasured concentrations despite the uncertainties in the regulation function or, even more, in the case of not knowing the mRNA dynamics. In addition, the rebuilding of concentrations is not affected by the perturbation due to the additive white Gaussian noise and also we managed to filter the noisy output of the biological systemComment: 21 pages, 7 figures; also selected in vjbio of August 2005; this version corrects a misorder in the last three references of the published versio

Proteinase-activated receptor 2 modulates OA-related pain, cartilage and bone pathology

Objective Proteinase-activated receptor 2 (PAR2) deficiency protects against cartilage degradation in experimental osteoarthritis (OA). The wider impact of this pathway upon OA-associated pathologies such as osteophyte formation and pain is unknown. Herein, we investigated early temporal bone and cartilage changes in experimental OA in order to further elucidate the role of PAR2 in OA pathogenesis. Methods OA was induced in wild-type (WT) and PAR2-deficient (PAR2−/−) mice by destabilisation of the medial meniscus (DMM). Inflammation, cartilage degradation and bone changes were monitored using histology and microCT. In gene rescue experiments, PAR2−/− mice were intra-articularly injected with human PAR2 (hPAR2)-expressing adenovirus. Dynamic weight bearing was used as a surrogate of OA-related pain. Results Osteophytes formed within 7 days post-DMM in WT mice but osteosclerosis was only evident from 14 days post induction. Importantly, PAR2 was expressed in the proliferative/hypertrophic chondrocytes present within osteophytes. In PAR2−/− mice, osteophytes developed significantly less frequently but, when present, were smaller and of greater density; no osteosclerosis was observed in these mice up to day 28. The pattern of weight bearing was altered in PAR2−/− mice, suggesting reduced pain perception. The expression of hPAR2 in PAR2−/− mice recapitulated osteophyte formation and cartilage damage similar to that observed in WT mice. However, osteosclerosis was absent, consistent with lack of hPAR2 expression in subchondral bone. Conclusions This study clearly demonstrates PAR2 plays a critical role, via chondrocytes, in osteophyte development and subchondral bone changes, which occur prior to PAR2-mediated cartilage damage. The latter likely occurs independently of OA-related bone changes

GoArrays: highly dynamic and efficient microarray probe design

MOTIVATION: The use of oligonucleotide microarray technology requires a very detailed attention to the design of specific probes spotted on the solid phase. These problems are far from being commonplace since they refer to complex physicochemical constraints. Whereas there are more and more publicly available programs for microarray oligonucleotide design, most of them use the same algorithm or criteria to design oligos, with only little variation. RESULTS: We show that classical approaches used in oligo design software may be inefficient under certain experimental conditions, especially when dealing with complex target mixtures. Indeed, our biological model is a human obligate parasite, the microsporidia Encephalitozoon cuniculi. Targets that are extracted from biological samples are composed of a mixture of pathogen transcripts and host cell transcripts. We propose a new approach to design oligonucleotides which combines good specificity with a potentially high sensitivity. This approach is original in the biological point of view as well as in the algorithmic point of view. We also present an experimental validation of this new strategy by comparing results obtained with standard oligos and with our composite oligos. A specific E.cuniculi microarray will overcome the difficulty to discriminate the parasite mRNAs from the host cell mRNAs demonstrating the power of the microarray approach to elucidate the lifestyle of an intracellular pathogen using mix mRNAs