Enhanced stopping of macro-particles in particle-in-cell simulations

We derive an equation for energy transfer from relativistic charged particles to a cold background plasma appropriate for finite-size particles that are used in particle-in-cell simulation codes. Expressions for one-, two-, and three-dimensional particles are presented, with special attention given to the two-dimensional case. This energy transfer is due to the electric field of the wake set up in the background plasma by the relativistic particle. The enhanced stopping is dependent on the q(2)/m, where q is the charge and m is the mass of the relativistic particle, and therefore simulation macro-particles with large charge but identical q/m will stop more rapidly. The stopping power also depends on the effective particle shape of the macro-particle. These conclusions are verified in particle-in-cell simulations. We present 2D simulations of test particles, relaxation of high-energy tails, and integrated fast ignition simulations showing that the enhanced drag on macro-particles may adversely affect the results of these simulations in a wide range of high-energy density plasma scenarios. We also describe a particle splitting algorithm which can potentially overcome this problem and show its effect in controlling the stopping of macro-particles.info:eu-repo/semantics/publishedVersio

BASIS: High-performance bioinformatics platform for processing of large-scale mass spectrometry imaging data in chemically augmented histology

Mass Spectrometry Imaging (MSI) holds significant promise in augmenting digital histopathologic analysis by generating highly robust big data about the metabolic, lipidomic and proteomic molecular content of the samples. In the process, a vast quantity of unrefined data, that can amount to several hundred gigabytes per tissue section, is produced. Managing, analysing and interpreting this data is a significant challenge and represents a major barrier to the translational application of MSI. Existing data analysis solutions for MSI rely on a set of heterogeneous bioinformatics packages that are not scalable for the reproducible processing of large-scale (hundreds to thousands) biological sample sets. Here, we present a computational platform (pyBASIS) capable of optimized and scalable processing of MSI data for improved information recovery and comparative analysis across tissue specimens using machine learning and related pattern recognition approaches. The proposed solution also provides a means of seamlessly integrating experimental laboratory data with downstream bioinformatics interpretation/analyses, resulting in a truly integrated system for translational MSI

Unbounded violation of tripartite Bell inequalities

We prove that there are tripartite quantum states (constructed from random unitaries) that can lead to arbitrarily large violations of Bell inequalities for dichotomic observables. As a consequence these states can withstand an arbitrary amount of white noise before they admit a description within a local hidden variable model. This is in sharp contrast with the bipartite case, where all violations are bounded by Grothendieck's constant. We will discuss the possibility of determining the Hilbert space dimension from the obtained violation and comment on implications for communication complexity theory. Moreover, we show that the violation obtained from generalized GHZ states is always bounded so that, in contrast to many other contexts, GHZ states do in this case not lead to extremal quantum correlations. The results are based on tools from the theories of operator spaces and tensor norms which we exploit to prove the existence of bounded but not completely bounded trilinear forms from commutative C*-algebras.Comment: Substantial changes in the presentation to make the paper more accessible for a non-specialized reade

Small RNA changes en route to distinct cellular states of induced pluripotency

MicroRNAs (miRNAs) are critical to somatic cell reprogramming into induced pluripotent stem cells (iPSCs), however, exactly how miRNA expression changes support the transition to pluripotency requires further investigation. Here we use a murine secondary reprogramming system to sample cellular trajectories towards iPSCs or a novel pluripotent ‘F-class’ state and perform small RNA sequencing. We detect sweeping changes in an early and a late wave, revealing that distinct miRNA milieus characterize alternate states of pluripotency. miRNA isoform expression is common but surprisingly varies little between cell states. Referencing other omic data sets generated in parallel, we find that miRNA expression is changed through transcriptional and post-transcriptional mechanisms. miRNA transcription is commonly regulated by dynamic histone modification, while DNA methylation/demethylation consolidates these changes at multiple loci. Importantly, our results suggest that a novel subset of distinctly expressed miRNAs supports pluripotency in the F-class state, substituting for miRNAs that serve such roles in iPSCs

Culture Adaptation Alters Transcriptional Hierarchies among Single Human Embryonic Stem Cells Reflecting Altered Patterns of Differentiation

We have used single cell transcriptome analysis to re-examine the substates of early passage, karyotypically Normal, and late passage, karyotypically Abnormal (‘Culture Adapted’) human embryonic stem cells characterized by differential expression of the cell surface marker antigen, SSEA3. The results confirmed that culture adaptation is associated with alterations to the dynamics of the SSEA3(+) and SSEA3(-) substates of these cells, with SSEA3(-) Adapted cells remaining within the stem cell compartment whereas the SSEA3(-) Normal cells appear to have differentiated. However, the single cell data reveal that these substates are characterized by further heterogeneity that changes on culture adaptation. Notably the Adapted population includes cells with a transcriptome substate suggestive of a shift to a more naïve-like phenotype in contrast to the cells of the Normal population. Further, a subset of the Normal SSEA3(+) cells expresses genes typical of endoderm differentiation, despite also expressing the undifferentiated stem cell genes, POU5F1 (OCT4) and NANOG, whereas such apparently lineage-primed cells are absent from the Adapted population. These results suggest that the selective growth advantage gained by genetically variant, culture adapted human embryonic stem cells may derive in part from a changed substate structure that influences their propensity for differentiation

Proteomic Comparison of Entamoeba histolytica and Entamoeba dispar and the Role of E. histolytica Alcohol Dehydrogenase 3 in Virulence

The protozoan intestinal parasite Entamoeba histolytica infects millions of people worldwide and is capable of causing amebic dysentery and amebic liver abscess. The closely related species Entamoeba dispar colonizes many more individuals, but this organism does not induce disease. To identify molecular differences between these two organisms that may account for their differential ability to cause disease in humans, we used two-dimensional gel-based (DIGE) proteomic analysis to compare whole cell lysates of E. histolytica and E. dispar. We observed 141 spots expressed at a substantially (>5-fold) higher level in E. histolytica HM-1∶IMSS than E. dispar and 189 spots showing the opposite pattern. Strikingly, 3 of 4 proteins consistently identified as different at a greater than 5-fold level between E. histolytica HM-1∶IMSS and E. dispar were identical to proteins recently identified as differentially expressed between E. histolytica HM-1∶IMSS and the reduced virulence strain E. histolytica Rahman. One of these was E. histolytica alcohol dehydrogenase 3 (EhADH3). We found that E. histolytica possesses a higher level of NADP-dependent alcohol dehydrogenase activity than E. dispar and that some EhADH3 can be localized to the surface of E. histolytica. Episomal overexpression of EhADH3 in E. histolytica trophozoites resulted in only subtle phenotypic differences in E. histolytica virulence in animal models of amebic colitis and amebic liver abscess, making it difficult to directly link EhADH3 levels to virulence differences between E. histolytica and less-pathogenic Entamoeba

Tourism Partnerships in Protected Areas: Exploring Contributions to Sustainability

Partnerships between natural-area managers and the tourism industry have been suggested to contribute to sustainability in protected areas. This article explores how important sustainability outcomes of partnerships are to their members, how well they are realised and the features of partnerships leading to their achievement. In 21 case studies in Australia, interviews (n = 97) and surveys (n = 100) showed that of 14 sustainability outcomes, improved understanding of protected areas values and improved biodiversity conservation were the most important. Other highly ranked outcomes were greater respect for culture, heritage, and/or traditions; improved quality of environmental conditions; social benefits to local communities; and improved economic viability of the protected area. Scores for satisfaction with outcomes were, like those for importance, all high but were less than those for importance for the majority, with improvement in quality of environmental conditions showing the largest gap. The satisfaction score exceeded that for importance only for increased competitiveness of the protected area as a tourist destination. “Brown” aspects of sustainability, i.e., decreased waste or energy use, were among the lowest-scoring outcomes for both importance and satisfaction. The most important factor enabling sustainability outcomes was provision of benefits to partnership members. Others were increased financial support, inclusiveness, supportive organisational and administrative arrangements, direct involvement of decision makers, partnership maturity, creation of new relationships, decreased conflict, and stimulation of innovation. Improving sustainability outcomes, therefore, requires maintaining these partnership attributes and also increasing emphasis on reducing waste and resource use

Prepatterning in the Stem Cell Compartment

The mechanism by which an apparently uniform population of cells can generate a heterogeneous population of differentiated derivatives is a fundamental aspect of pluripotent and multipotent stem cell behaviour. One possibility is that the environment and the differentiation cues to which the cells are exposed are not uniform. An alternative, but not mutually exclusive possibility is that the observed heterogeneity arises from the stem cells themselves through the existence of different interconvertible substates that pre-exist before the cells commit to differentiate. We have tested this hypothesis in the case of apparently homogeneous pluripotent human embryonal carcinoma (EC) stem cells, which do not follow a uniform pattern of differentiation when exposed to retinoic acid. Instead, they produce differentiated progeny that include both neuronal and non-neural phenotypes. Our results suggest that pluripotent NTERA2 stem cells oscillate between functionally distinct substates that are primed to select distinct lineages when differentiation is induced