Abstract
Type 2 diabetes involves defective insulin secretion with islet inflammation governed in part by IL-1ß. Prolonged exposure of islets to high concentrations of IL-1ß (>24 h, 20 ng/ml) impairs beta cell function and survival. Conversely, exposure to lower concentrations of IL-1ß for >24 h improves these same parameters. The impact on insulin secretion of shorter exposure times to IL-1ßand the underlying molecular mechanisms are poorly understood and were the focus of this study. Treatment of rat primary beta cells, as well as rat or human whole islets, with 0.1 ng/ml IL-1ß for 2 h increased glucose-stimulated (but not basal) insulin secretion, whereas 20 ng/ml was without effect. Similar differential effects of IL-1ß depending on concentration were observed after 15 min of KCl stimulation but were prevented by diazoxide. Studies on sorted rat beta cells indicated that the enhancement of stimulated secretion by 0.1 ng/ml IL-1ß was mediated by the NF-ßB pathway and c-JUN/JNK pathway acting in parallel to elicit focal adhesion remodeling and the phosphorylation of paxillin independently of upstream regulation by focal adhesion kinase. Because the beneficial effect of IL-1ß was dependent in part upon transcription, gene expression was analyzed by RNAseq. There were 18 genes regulated uniquely by 0.1 but not 20 ng/ml IL-1ß, which are mostly involved in transcription and apoptosis. These results indicate that 2h of exposure of beta cells to a low but not a high concentration of IL-1ß enhances glucose-stimulated insulin secretion through focal adhesion and actin remodeling, as well as modulation of gene expression. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Abstract
Phenotypic plasticity is important in adaptation and shapes the evolution of organisms. However, we understand little about what aspects of the genome are important in facilitating plasticity. Eusocial insect societies produce plastic phenotypes from the same genome, as reproductives (queens) and nonreproductives (workers). The greatest plasticity is found in the simple eusocial insect societies in which individuals retain the ability to switch between reproductive and nonreproductive phenotypes as adults. We lack comprehensive data on the molecular basis of plastic phenotypes. Here, we sequenced genomes, microRNAs (miRNAs), and multiple transcriptomes and methylomes from individual brains in a wasp (Polistes canadensis) and an ant (Dinoponera quadriceps) that live in simple eusocial societies. In both species, we found few differences between phenotypes at the transcriptional level, with little functional specialization, and no evidence that phenotype-specific gene expression is driven by DNA methylation or miRNAs. Instead, phenotypic differentiation was defined more subtly by nonrandom transcriptional network organization, with roles in these networks for both conserved and taxon-restricted genes. The general lack of highly methylated regions or methylome patterning in both species may be an important mechanism for achieving plasticity among phenotypes during adulthood. These findings define previously unidentified hypotheses on the genomic processes that facilitate plasticity and suggest that the molecular hallmarks of social behavior are likely to differ with the level of social complexity.

Abstract
A new microstructured optical fiber is demonstrated to detect acetone evaporation by observing the time response of the reflected signal at 1550nm. The sensor consists on a caterpillar-like fiber, with a transversal microfluidic channel created with a Focused Ion Beam technique, spliced to a single-mode fiber. Different stages were visible between the dipping and the evaporation of acetone and of a mixture of water and acetone. It was also possible to detect the presence of water vapor.

Abstract
Fingerprint segmentation is a crucial step of an automatic fingerprint identification system, since an accurate segmentation promote both the elimination of spurious minutiae close to the foreground boundaries and the reduction of the computation time of the following steps. In this paper, a new, and more robust fingerprint segmentation algorithm is proposed. The main novelty is the introduction of a more robust binarization process in the framework, mainly based on the fuzzy C-means clustering algorithm. Experimental results demonstrate significant benchmark progress on three existing FVC datasets.

Abstract

Abstract
Fingerprint liveness detection methods have been developed as an attempt to overcome the vulnerability of fingerprint biometric systems to spoofing attacks. Traditional approaches have been quite optimistic about the behavior of the intruder assuming the use of a previously known material. This assumption has led to the use of supervised techniques to estimate the performance of the methods, using both live and spoof samples to train the predictive models and evaluate each type of fake samples individually. Additionally, the background was often included in the sample representation, completely distorting the decision process. Therefore, we propose that an automatic segmentation step should be performed to isolate the fingerprint from the background and truly decide on the liveness of the fingerprint and not on the characteristics of the background. Also, we argue that one cannot aim to model the fake samples completely since the material used by the intruder is unknown beforehand. We approach the design by modeling the distribution of the live samples and predicting as fake the samples very unlikely according to that model. Our experiments compare the performance of the supervised approaches with the semi-supervised ones that rely solely on the live samples. The results obtained differ from the ones obtained by the more standard approaches which reinforces our conviction that the results in the literature are misleadingly estimating the true vulnerability of the biometric system.