Requirement for Slit-1 and Robo-2 in zonal segregation of olfactory sensory neuron axons in the main olfactory bulb

The formation of precise stereotypic connections in sensory systems is critical for the ability to detect and process signals from the environment. In the olfactory system, olfactory sensory neurons (OSNs) project axons to spatially defined glomeruli within the olfactory bulb (OB). A spatial relationship exists between the location of OSNs within the olfactory epithelium (OE) and their glomerular targets along the dorsoventral axis in the OB. The molecular mechanisms underlying the zonal segregation of OSN axons along the dorsoventral axis of the OB are poorly understood. Using robo-2/ (roundabout) and slit-1/ mice, we examined the role of the Slit family of axon guidance cues in the targeting of OSN axons during development. We show that a subset of OSN axons that normally project to the dorsal region of the OB mistarget and form glomeruli in the ventral region in robo-2/ and slit-1/ mice. In addition, we show that the Slit receptor, Robo-2, is expressed in OSNs in a high dorsomedial to low ventrolateral gradient across the OE and that Slit-1 and Slit-3 are expressed in the ventral region of the OB. These results indicate that the dorsal-to-ventral segregation of OSN axons are not solely defined by the location of OSNs within the OE but also relies on axon guidance cues

Madonna With a Heart Scarred As a Face With Bad Maybe Smallpox

Aunque las pruebas de mutación son una técnica bien conocida para evaluar la calidad de las pruebas, no hay mucho apoyo disponible para el análisis de mutaciones a nivel de modelo. También se considera costoso debido a: (i) la gran cantidad de mutantes generados; (ii) la actividad lenta de determinar mutantes equivalentes; y (iii) el tiempo de ejecución mutante. También debe recordarse que los artefactos de software reales de tamaño apropiado, incluyendo fallas reales, son difíciles de encontrar y preparar adecuadamente. En este artículo, proponemos una herramienta de mutación para generar mutantes de primer orden (FOM) válidos para esquemas conceptuales (CS) basados ​​en diagramas de clase UML y evaluar su efectividad y eficiencia en la generación de mutantes válidos y no equivalentes. Nuestros principales hallazgos fueron: (1 ) Los operadores de mutación FOM pueden automatizarse para evitar mutantes no válidos (49,1%). (2) Se generaron menos mutantes equivalentes (7,2%) y el 74,3% se redujo analizando la estructura estática de CS en seis CS de sujeto. © Springer International Publishing Suiza 2017.Although mutation testing is a well-known technique for assessing the quality of tests, there is not a lot of support available for model-level mutation analysis. It is also considered to be expensive due to: (i) the large number of mutants generated; (ii) the time-consuming activity of determining equivalent mutants; and (iii) the mutant execution time. It should also be remembered that real software artefacts of appropriate size including real faults are hard to find and prepare appropriately. In this paper we propose a mutation tool to generate valid First Order Mutants (FOM) for Conceptual Schemas (CS) based on UML Class Diagrams and evaluate its effectiveness and efficiency in generating valid and non-equivalent mutants.Our main findings were: (1) FOM mutation operators can be automated to avoiding non-valid mutants (49.1%). (2) Fewer equivalent mutants were generated (7.2%) and 74.3% were reduced by analysing the CS static structure in six subject CSs. © Springer International Publishing Switzerland 2017.Katowic

Systematic Investigation of the Permeability of Androgen Receptor PROTACs

Bifunctional molecules known as PROTACs simultaneously bind an E3 ligase and a protein of interest to direct ubiquitination and clearance of that protein, and they have emerged in the past decade as an exciting new paradigm in drug discovery. In order to investigate the permeability and properties of these large molecules, we synthesized two panels of PROTAC molecules, constructed from a range of protein-target ligands, linkers, and E3 ligase ligands. The androgen receptor, which is a well-studied protein in the PROTAC field was used as a model system. The physicochemical properties and permeability of PROTACs are discussed

Saturn Plasma Sources and Associated Transport Processes

This article reviews the different sources of plasma for Saturn’s magnetosphere, as they are known essentially from the scientific results of the Cassini-Huygens mission to Saturn and Titan. At low and medium energies, the main plasma source is the H2OH2O cloud produced by the “geyser” activity of the small satellite Enceladus. Impact ionization of this cloud occurs to produce on the order of 100 kg/s of fresh plasma, a source which dominates all the other ones: Titan (which produces much less plasma than anticipated before the Cassini mission), the rings, the solar wind (a poorly known source due to the lack of quantitative knowledge of the degree of coupling between the solar wind and Saturn’s magnetosphere), and the ionosphere. At higher energies, energetic particles are produced by energy diffusion and acceleration of lower energy plasma produced by the interchange instabilities induced by the rapid rotation of Saturn, and possibly, for the highest energy range, by contributions from the CRAND process acting inside Saturn’s magnetosphere. Discussion of the transport and acceleration processes acting on these plasma sources shows the importance of rotation-induced radial transport and energization of the plasma, and also shows how much the unexpected planetary modulation of essentially all plasma parameters of Saturn’s magnetosphere remains an unexplained mystery

Complex systems analysis of bladder cancer susceptibility reveals a role for decarboxylase activity in two genome-wide association studies

BACKGROUND: Bladder cancer is common disease with a complex etiology that is likely due to many different genetic and environmental factors. The goal of this study was to embrace this complexity using a bioinformatics analysis pipeline designed to use machine learning to measure synergistic interactions between single nucleotide polymorphisms (SNPs) in two genome-wide association studies (GWAS) and then to assess their enrichment within functional groups defined by Gene Ontology. The significance of the results was evaluated using permutation testing and those results that replicated between the two GWAS data sets were reported. RESULTS: In the first step of our bioinformatics pipeline, we estimated the pairwise synergistic effects of SNPs on bladder cancer risk in both GWAS data sets using Multifactor Dimensionality Reduction (MDR) machine learning method that is designed specifically for this purpose. Statistical significance was assessed using a 1000-fold permutation test. Each single SNP was assigned a p-value based on its strongest pairwise association. Each SNP was then mapped to one or more genes using a window of 500 kb upstream and downstream from each gene boundary. This window was chosen to capture as many regulatory variants as possible. Using Exploratory Visual Analysis (EVA), we then carried out a gene set enrichment analysis at the gene level to identify those genes with an overabundance of significant SNPs relative to the size of their mapped regions. Each gene was assigned to a biological functional group defined by Gene Ontology (GO). We next used EVA to evaluate the overabundance of significant genes in biological functional groups. Our study yielded one GO category, carboxy-lysase activity (GO:0016831), that was significant in analyses from both GWAS data sets. Interestingly, only the gamma-glutamyl carboxylase (GGCX) gene from this GO group was significant in both the detection and replication data, highlighting the complexity of the pathway-level effects on risk. The GGCX gene is expressed in the bladder, but has not been previously associated with bladder cancer in univariate GWAS. However, there is some experimental evidence that carboxy-lysase activity might play a role in cancer and that genes in this pathway should be explored as drug targets. This study provides a genetic basis for that observation. CONCLUSIONS: Our machine learning analysis of genetic associations in two GWAS for bladder cancer identified numerous associations with pairs of SNPs. Gene set enrichment analysis found aggregation of risk-associated SNPs in genes and significant genes in GO functional groups. This study supports a role for decarboxylase protein complexes in bladder cancer susceptibility. Previous research has implicated decarboxylases in bladder cancer etiology; however, the genes that we found to be significant in the detection and replication data are not known to have direct influence on bladder cancer, suggesting some novel hypotheses. This study highlights the need for a complex systems approach to the genetic and genomic analysis of common diseases such as cancer

N=4 Superconformal Algebra and the Entropy of HyperKahler Manifolds

We study the elliptic genera of hyperKahler manifolds using the representation theory of N=4 superconformal algebra. We consider the decomposition of the elliptic genera in terms of N=4 irreducible characters, and derive the rate of increase of the multiplicities of half-BPS representations making use of Rademacher expansion. Exponential increase of the multiplicity suggests that we can associate the notion of an entropy to the geometry of hyperKahler manifolds. In the case of symmetric products of K3 surfaces our entropy agrees with the black hole entropy of D5-D1 system.Comment: 25 pages, 1 figur

The effect of intolerance of uncertainty on anxiety and depression, and their symptom networks, during the COVID-19 pandemic

Individuals vary in their ability to tolerate uncertainty. High intolerance of uncertainty (the tendency to react negatively to uncertain situations) is a known risk factor for mental health problems. In the current study we examined the degree to which intolerance of uncertainty predicted depression and anxiety symptoms and their interrelations across the first year of the COVID-19 pandemic. We examined these associations across three time points (May 2020 – April 2021) in an international sample of adults (N = 2087, Mean age = 41.13) from three countries (UK, USA, Australia) with varying degrees of COVID-19 risk. We found that individuals with high and moderate levels of intolerance of uncertainty reported reductions in depression and anxiety symptoms over time. However, symptom levels remained significantly elevated compared to individuals with low intolerance of uncertainty. Individuals with low intolerance of uncertainty had low and stable levels of depression and anxiety across the course of the study. Network analyses further revealed that the relationships between depression and anxiety symptoms became stronger over time among individuals with high intolerance of uncertainty and identified that feeling afraid showed the strongest association with intolerance of uncertainty. Our findings are consistent with previous work identifying intolerance of uncertainty as an important risk factor for mental health problems, especially in times marked by actual health, economic and social uncertainty. The results highlight the need to explore ways to foster resilience among individuals who struggle to tolerate uncertainty, as ongoing and future geopolitical, climate and health threats will likely lead to continued exposure to significant uncertainty

Crack-Like Processes Governing the Onset of Frictional Slip

We perform real-time measurements of the net contact area between two blocks of like material at the onset of frictional slip. We show that the process of interface detachment, which immediately precedes the inception of frictional sliding, is governed by three different types of detachment fronts. These crack-like detachment fronts differ by both their propagation velocities and by the amount of net contact surface reduction caused by their passage. The most rapid fronts propagate at intersonic velocities but generate a negligible reduction in contact area across the interface. Sub-Rayleigh fronts are crack-like modes which propagate at velocities up to the Rayleigh wave speed, VR, and give rise to an approximate 10% reduction in net contact area. The most efficient contact area reduction (~20%) is precipitated by the passage of slow detachment fronts. These fronts propagate at anomalously slow velocities, which are over an order of magnitude lower than VR yet orders of magnitude higher than other characteristic velocity scales such as either slip or loading velocities. Slow fronts are generated, in conjunction with intersonic fronts, by the sudden arrest of sub-Rayleigh fronts. No overall sliding of the interface occurs until either of the slower two fronts traverses the entire interface, and motion at the leading edge of the interface is initiated. Slip at the trailing edge of the interface accompanies the motion of both the slow and sub-Rayleigh fronts. We might expect these modes to be important in both fault nucleation and earthquake dynamics.Comment: 19 page, 5 figures, to appear in International Journal of Fractur

Constitutive activation of the PI3K-Akt-mTORC1 pathway sustains the m.3243 A > G mtDNA mutation

Mutations of the mitochondrial genome (mtDNA) cause a range of profoundly debilitating clinical conditions for which treatment options are very limited. Most mtDNA diseases show heteroplasmy – tissues express both wild-type and mutant mtDNA. While the level of heteroplasmy broadly correlates with disease severity, the relationships between specific mtDNA mutations, heteroplasmy, disease phenotype and severity are poorly understood. We have carried out extensive bioenergetic, metabolomic and RNAseq studies on heteroplasmic patient-derived cells carrying the most prevalent disease related mtDNA mutation, the m.3243 A > G. These studies reveal that the mutation promotes changes in metabolites which are associated with the upregulation of the PI3K-Akt-mTORC1 axis in patient-derived cells and tissues. Remarkably, pharmacological inhibition of PI3K, Akt, or mTORC1 reduced mtDNA mutant load and partially rescued cellular bioenergetic function. The PI3K-Akt-mTORC1 axis thus represents a potential therapeutic target that may benefit people suffering from the consequences of the m.3243 A > G mutation

Oligo-DNA Custom Macroarray for Monitoring Major Pathogenic and Non-Pathogenic Fungi and Bacteria in the Phyllosphere of Apple Trees

BACKGROUND: To monitor the richness in microbial inhabitants in the phyllosphere of apple trees cultivated under various cultural and environmental conditions, we developed an oligo-DNA macroarray for major pathogenic and non-pathogenic fungi and bacteria inhabiting the phyllosphere of apple trees. METHODS AND FINDINGS: First, we isolated culturable fungi and bacteria from apple orchards by an agar-plate culture method, and detected 32 fungal and 34 bacterial species. Alternaria, Aureobasidium, Cladosporium, Rhodotorula, Cystofilobasidium, and Epicoccum genera were predominant among the fungi, and Bacillus, Pseudomonas, Sphingomonas, Methylobacterium, and Pantoea genera were predominant among the bacteria. Based on the data, we selected 29 major non-pathogenic and 12 phytopathogenic fungi and bacteria as the targets of macroarray. Forty-one species-specific 40-base pair long oligo-DNA sequences were selected from the nucleotide sequences of rDNA-internal transcribed spacer region for fungi and 16S rDNA for bacteria. The oligo-DNAs were fixed on nylon membrane and hybridized with digoxigenin-labeled cRNA probes prepared for each species. All arrays except those for Alternaria, Bacillus, and their related species, were specifically hybridized. The array was sensitive enough to detect 10(3) CFU for Aureobasidium pullulans and Bacillus cereus. Nucleotide sequencing of 100 each of independent fungal rDNA-ITS and bacterial 16S-rDNA sequences from apple tree was in agreement with the macroarray data obtained using the same sample. Finally, we analyzed the richness in the microbial inhabitants in the samples collected from apple trees in four orchards. Major apple pathogens that cause scab, Alternaria blotch, and Marssonina blotch were detected along with several non-phytopathogenic fungal and bacterial inhabitants. CONCLUSIONS: The macroarray technique presented here is a strong tool to monitor the major microbial species and the community structures in the phyllosphere of apple trees and identify key species antagonistic, supportive or co-operative to specific pathogens in the orchard managed under different environmental conditions