49 research outputs found
Resolution requirements for numerical simulations of transition
The resolution requirements for direct numerical simulations of transition to turbulence are investigated. A reliable resolution criterion is determined from the results of several detailed simulations of channel and boundary-layer transition
Best practices in heterotrophic high-cell-density microalgal processes: achievements, potential and possible limitations
Microalgae of numerous heterotrophic genera (obligate or facultative) exhibit considerable metabolic versatility and flexibility but are currently underexploited in the biotechnological manufacturing of known plant-derived compounds, novel high-value biomolecules or enriched biomass. Highly efficient production of microalgal biomass without the need for light is now feasible in inexpensive, well-defined mineral medium, typically supplemented with glucose. Cell densities of more than 100 g l−1 cell dry weight have been achieved with Chlorella, Crypthecodinium and Galdieria species while controlling the addition of organic sources of carbon and energy in fedbatch mode. The ability of microalgae to adapt their metabolism to varying culture conditions provides opportunities to modify, control and thereby maximise the formation of targeted compounds with non-recombinant microalgae. This review outlines the critical aspects of cultivation technology and current best practices in the heterotrophic high-cell-density cultivation of microalgae. The primary topics include (1) the characteristics of microalgae that make them suitable for heterotrophic cultivation, (2) the appropriate chemical composition of mineral growth media, (3) the different strategies for fedbatch cultivations and (4) the principles behind the customisation of biomass composition. The review confirms that, although fundamental knowledge is now available, the development of efficient, economically feasible large-scale bioprocesses remains an obstacle to the commercialisation of this promising technology
Whole-body tissue stabilization and selective extractions via tissue-hydrogel hybrids for high-resolution intact circuit mapping and phenotyping
To facilitate fine-scale phenotyping of whole specimens, we describe here a set of tissue fixation-embedding, detergent-clearing and staining protocols that can be used to transform excised organs and whole organisms into optically transparent samples within 1–2 weeks without compromising their cellular architecture or endogenous fluorescence. PACT (passive CLARITY technique) and PARS (perfusion-assisted agent release in situ) use tissue-hydrogel hybrids to stabilize tissue biomolecules during selective lipid extraction, resulting in enhanced clearing efficiency and sample integrity. Furthermore, the macromolecule permeability of PACT- and PARS-processed tissue hybrids supports the diffusion of immunolabels throughout intact tissue, whereas RIMS (refractive index matching solution) grants high-resolution imaging at depth by further reducing light scattering in cleared and uncleared samples alike. These methods are adaptable to difficult-to-image tissues, such as bone (PACT-deCAL), and to magnified single-cell visualization (ePACT). Together, these protocols and solutions enable phenotyping of subcellular components and tracing cellular connectivity in intact biological networks
Two-particle BoseEinstein correlations in pp collisions at √s = 0.9 and 7 TeV measured with the ATLAS detector
The paper presents studies of Bose–Einstein Correlations (BEC) for pairs of like-sign charged particles measured in the kinematic range pT > 100 MeV and |η| <2.5 in proton–proton collisions at centre-of-mass energies of 0.9 and 7
TeV with the ATLAS detector at the CERN Large Hadron
Collider. The integrated luminosities are approximately 7
μb−1, 190 μb−1 and 12.4 nb-1 for 0.9 TeV,7 TeV minimum-bias and 7 TeV high-multiplicity data samples, respectively. The multiplicity dependence of the BEC parameters characterizing the correlation strength and the correlation source size are investigated for charged-particle multiplicities of up to 240. A saturation effect in the multiplicity dependence of the correlation source size parameter is observed using the high-multiplicity 7 TeV
data sample. The dependence of the BEC parameters on the average transverse momentum of the particle pair is also investigated
Pan-cancer analysis of whole genomes
Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe