Low autocorrelated multi-phase sequences

The interplay between the ground state energy of the generalized Bernasconi model to multi-phase, and the minimal value of the maximal autocorrelation function, $C_{max}=\max_K{|C_K|}$, $K=1,..N-1$, is examined analytically and the main results are: (a) The minimal value of $\min_N{C_{max}}$ is $0.435\sqrt{N}$ significantly smaller than the typical value for random sequences $O(\sqrt{\log{N}}\sqrt{N})$. (b) $\min_N{C_{max}}$ over all sequences of length N is obtained in an energy which is about 30% above the ground-state energy of the generalized Bernasconi model, independent of the number of phases m. (c) The maximal merit factor $F_{max}$ grows linearly with m. (d) For a given N, $\min_N{C_{max}}\sim\sqrt{N/m}$ indicating that for m=N, $\min_N{C_{max}}=1$, i.e. a Barker code exits. The analytical results are confirmed by simulations.Comment: 4 pages, 4 figure

The dynamics of proving uncolourability of large random graphs I. Symmetric Colouring Heuristic

We study the dynamics of a backtracking procedure capable of proving uncolourability of graphs, and calculate its average running time T for sparse random graphs, as a function of the average degree c and the number of vertices N. The analysis is carried out by mapping the history of the search process onto an out-of-equilibrium (multi-dimensional) surface growth problem. The growth exponent of the average running time is quantitatively predicted, in agreement with simulations.Comment: 5 figure

Multi-Player and Multi-Choice Quantum Game

We investigate a multi-player and multi-choice quantum game. We start from two-player and two-choice game and the result is better than its classical version. Then we extend it to N-player and N-choice cases. In the quantum domain, we provide a strategy with which players can always avoid the worst outcome. Also, by changing the value of the parameter of the initial state, the probabilities for players to obtain the best payoff will be much higher that in its classical version.Comment: 4 pages, 1 figur

The influence of feature selection methods on accuracy, stability and interpretability of molecular signatures

Motivation: Biomarker discovery from high-dimensional data is a crucial problem with enormous applications in biology and medicine. It is also extremely challenging from a statistical viewpoint, but surprisingly few studies have investigated the relative strengths and weaknesses of the plethora of existing feature selection methods. Methods: We compare 32 feature selection methods on 4 public gene expression datasets for breast cancer prognosis, in terms of predictive performance, stability and functional interpretability of the signatures they produce. Results: We observe that the feature selection method has a significant influence on the accuracy, stability and interpretability of signatures. Simple filter methods generally outperform more complex embedded or wrapper methods, and ensemble feature selection has generally no positive effect. Overall a simple Student's t-test seems to provide the best results. Availability: Code and data are publicly available at http://cbio.ensmp.fr/~ahaury/

Management of hydrocele in adolescent patients

Hydrocele is defined as an abnormal collection of serous fluid in the potential space between the parietal and visceral layers of the tunica vaginalis. In the majority of affected adolescents, hydrocele is acquired and is idiopathic in origin. The pathogenesis of idiopathic hydrocele is thought to be an imbalance in the normal process of fluid production and reabsorption. The diagnosis is usually clinical. Taking a thorough history is essential to rule out any fluctuation in size, which is an indication of a patent processus vaginalis. Scrotal ultrasonography is mandatory in nonpalpable testicles to rule out a subtending testicular solid mass requiring inguinal exploration. Otherwise, open hydrocelectomy via a scrotal incision is the standard treatment of idiopathic hydroceles. The second most common cause of hydrocele in adolescents is varicocelectomy. The risk of hydrocele formation is higher with non-artery-sparing procedures or those performed without microsurgical aid, and in surgery requiring cord dissection. If hydrocele occurs after varicocelectomy, initial management should include observation with or without hydrocele aspiration. Large persistent hydroceles are best served by open hydrocelectomy

Towards eco-friendly batteries: high temperature baking of carbonaceous (MCMB) Li-ion anodes containing advanced water-based natural polymer binders results in superior performance

Replacing common polymeric binder materials in lithium-ion batteries (LIBs) with more sustainable and environmentally friendly options is one of the challenges in designing new generations of LIBs. Here, we explain how incorporating protein-based polymers into the binder formulation can enhance binder performance in the graphite anode of LIBs. The electrode preparation with these binders involves an atypical thermal treatment (“baking”) that causes structural transformation. The effect of baking temperature on battery performance is examined using various methods covering morphological, structural, and electrochemical aspects. We find that baking the binders at temperatures above 120 °C removes tightly bound water molecules, which impair LIB performance. Water removal promotes intra- and inter-molecular bond formation among the binder components, while the primary covalent structure of these binders remains unchanged. Ultimately, using thermally treated binders enhances the electrochemical performance of graphite anodes and provides strong adhesion. The ideas presented here could significantly influence the design of new binders for LIBs

Incorporating topological information for predicting robust cancer subnetwork markers in human protein-protein interaction network

BACKGROUND: Discovering robust markers for cancer prognosis based on gene expression data is an important yet challenging problem in translational bioinformatics. By integrating additional information in biological pathways or a protein-protein interaction (PPI) network, we can find better biomarkers that lead to more accurate and reproducible prognostic predictions. In fact, recent studies have shown that, “modular markers,” that integrate multiple genes with potential interactions can improve disease classification and also provide better understanding of the disease mechanisms. RESULTS: In this work, we propose a novel algorithm for finding robust and effective subnetwork markers that can accurately predict cancer prognosis. To simultaneously discover multiple synergistic subnetwork markers in a human PPI network, we build on our previous work that uses affinity propagation, an efficient clustering algorithm based on a message-passing scheme. Using affinity propagation, we identify potential subnetwork markers that consist of discriminative genes that display coherent expression patterns and whose protein products are closely located on the PPI network. Furthermore, we incorporate the topological information from the PPI network to evaluate the potential of a given set of proteins to be involved in a functional module. Primarily, we adopt widely made assumptions that densely connected subnetworks may likely be potential functional modules and that proteins that are not directly connected but interact with similar sets of other proteins may share similar functionalities. CONCLUSIONS: Incorporating topological attributes based on these assumptions can enhance the prediction of potential subnetwork markers. We evaluate the performance of the proposed subnetwork marker identification method by performing classification experiments using multiple independent breast cancer gene expression datasets and PPI networks. We show that our method leads to the discovery of robust subnetwork markers that can improve cancer classification. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1224-1) contains supplementary material, which is available to authorized users

Finding consistent disease subnetworks across microarray datasets

<p>Abstract</p> <p>Background</p> <p>While contemporary methods of microarray analysis are excellent tools for studying individual microarray datasets, they have a tendency to produce different results from different datasets of the same disease. We aim to solve this reproducibility problem by introducing a technique (SNet). SNet provides both quantitative and descriptive analysis of microarray datasets by identifying specific connected portions of pathways that are significant. We term such portions within pathways as “subnetworks”.</p> <p>Results</p> <p>We tested SNet on independent datasets of several diseases, including childhood ALL, DMD and lung cancer. For each of these diseases, we obtained two independent microarray datasets produced by distinct labs on distinct platforms. In each case, our technique consistently produced almost the same list of significant nontrivial subnetworks from two independent sets of microarray data. The gene-level agreement of these significant subnetworks was between 51.18% to 93.01%. In contrast, when the same pairs of microarray datasets were analysed using GSEA, t-test and SAM, this percentage fell between 2.38% to 28.90% for GSEA, 49.60% tp 73.01% for t-test, and 49.96% to 81.25% for SAM. Furthermore, the genes selected using these existing methods did not form subnetworks of substantial size. Thus it is more probable that the subnetworks selected by our technique can provide the researcher with more descriptive information on the portions of the pathway actually affected by the disease.</p> <p>Conclusions</p> <p>These results clearly demonstrate that our technique generates significant subnetworks and genes that are more consistent and reproducible across datasets compared to the other popular methods available (GSEA, t-test and SAM). The large size of subnetworks which we generate indicates that they are generally more biologically significant (less likely to be spurious). In addition, we have chosen two sample subnetworks and validated them with references from biological literature. This shows that our algorithm is capable of generating descriptive biologically conclusions.</p

AA-Amyloidosis Can Be Transferred by Peripheral Blood Monocytes

Spongiform encephalopathies have been reported to be transmitted by blood transfusion even prior to the clinical onset. Experimental AA-amyloidosis shows similarities with prion disease and amyloid-containing organ-extracts can prime a recipient for the disease. In this systemic form of amyloidosis N-terminal fragments of the acute-phase reactant apolipoprotein serum amyloid A are the main amyloid protein. Initial amyloid deposits appear in the perifollicular region of the spleen, followed by deposits in the liver. We used the established murine model and induced AA-amyloidosis in NMRI mice by intravenous injections of purified amyloid fibrils (‘amyloid enhancing factor’) combined with inflammatory challenge (silver nitrate subcutaneously). Blood plasma and peripheral blood monocytes were isolated, sonicated and re-injected into new recipients followed by an inflammatory challenge during a three week period. When the animals were sacrificed presence of amyloid was analyzed in spleen sections after Congo red staining. Our result shows that some of the peripheral blood monocytes, isolated from animals with detectable amyloid, contained amyloid-seed that primed for AA-amyloid. The seeding material seems to have been phagocytosed by the cells since the AA-precursor (SAA1) was found not be expressed by the monocytes. Plasma recovered from mice with AA amyloidosis lacked seeding capacity. Amyloid enhancing activity can reside in monocytes recovered from mice with AA-amyloidosis and in a prion-like way trigger amyloid formation in conjunction with an inflammatory disorder. Human AA-amyloidosis resembles the murine form and every individual is expected to be exposed to conditions that initiate production of the acute-phase reactant. The monocyte-transfer mechanism should be eligible for the human disease and we point out blood transfusion as a putative route for transfer of amyloidosis