Double-digest restriction-associated DNA sequencing-based genotyping and its applications in sesame germplasm management

Sesame (Sesamum indicum L.) is an ancient oilseed crop belonging to the family Pedaliaceae and a globally cultivated crop for its use as oil and food. In this study, 2496 sesame accessions, being conserved at the National Genebank of ICAR-National Bureau of Plant Genetic Resources (NBPGR), were genotyped using genomics-assisted double-digest restriction-associated DNA sequencing (ddRAD-seq) approach. A total of 64,910 filtered single-nucleotide polymorphisms (SNPs) were utilized to assess the genome-scale diversity. Applications of this genome-scale information (reduced representation using restriction enzymes) are demonstrated through the development of a molecular core collection (CC) representing maximal SNP diversity. This information is also applied in developing a mid-density panel (MDP) comprising 2515 hyper-variable SNPs, representing almost equally the genic and non-genic regions. The sesame CC comprising 384 accessions, a representative set of accessions with maximal diversity, was identified using multiple criteria such as k-mer (subsequence of length “k” in a sequence read) diversity, observed heterozygosity, CoreHunter3, GenoCore, and genetic differentiation. The coreset constituted around 15% of the total accessions studied, and this small subset had captured >60% SNP diversity of the entire population. In the coreset, the admixture analysis shows reduced genetic complexity, increased nucleotide diversity (π), and is geographically distributed without any repetitiveness in the CC germplasm. Within the CC, India-originated accessions exhibit higher diversity (as expected based on the center of diversity concept), than those accessions that were procured from various other countries. The identified CC set and the MDP will be a valuable resource for genomics-assisted accelerated sesame improvement program

Neutrino interactions in the deuterium-neon 14 foot double bubble chamber

We propose to study the interactions of high energy neutrinos in the 14 foot bubble chamber. The target chamber to be filled with Deuterium and the surrounding region filled with nearly pure Neon. An exposure of one million pictures is requested, in order to map out the s and t dependences of the basic interaction in which neutrinos participate

Induction of plasminogen activator inhibitor type-1 (PAI-1) by hypoxia and irradiation in human head and neck carcinoma cell lines

Contains fulltext : 53187.pdf ( ) (Open Access)BACKGROUND: Squamous cell carcinoma of the head and neck (SCCHN) often contain highly radioresistant hypoxic regions, nonetheless, radiotherapy is a common treatment modality for these tumours. Reoxygenation during fractionated radiotherapy is desired to render these hypoxic tumour regions more radiosensitive. Hypoxia additionally leads to up-regulation of PAI-1, a protein involved in tumour progression and an established prognostic marker for poor outcome. However, the impact of reoxygenation and radiation on PAI-1 levels is not yet clear. Therefore, we investigated the kinetics of PAI-1 expression and secretion after hypoxia and reoxygenation, and determined the influence of ionizing radiation on PAI-1 levels in the two human SCCHN cell lines, BHY and FaDu. METHODS: HIF-1alpha immunoblot was used to visualize the degree of hypoxia in the two cell lines. Cellular PAI-1 expression was investigated by immunofluorescence microscopy. ELISA was used to quantify relative changes in PAI-1 expression (cell lysates) and secretion (cell culture supernatants) in response to various lengths (2-4 h) of hypoxic exposure (< 0.66% O2), reoxygenation (24 h, 20% O2), and radiation (0, 2, 5 and 10 Gy). RESULTS: HIF-1alpha expression was induced between 2 and 24 h of hypoxic exposure. Intracellular PAI-1 expression was significantly increased in BHY and FaDu cells as early as 4 h after hypoxic exposure. A significant induction in secreted PAI-1 was seen after 12 to 24 h (BHY) and 8 to 24 h (FaDu) hypoxia, as compared to the normoxic control. A 24 h reoxygenation period caused significantly less PAI-1 secretion than a 24 h hypoxia period in FaDu cells. Irradiation led to an up-regulation of PAI-1 expression and secretion in both, BHY and FaDu cells. CONCLUSION: Our data suggest that both, short-term (approximately 4-8 h) and long-term (approximately 20-24 h) hypoxic exposure could increase PAI-1 levels in SCCHN in vivo. Importantly, radiation itself could lead to PAI-1 up-regulation in head and neck tumours, whereas reoxygenation of hypoxic tumour cells during fractionated radiotherapy could counteract the increased PAI-1 levels

Distributed Dynamical Computation in Neural Circuits with Propagating Coherent Activity Patterns

Activity in neural circuits is spatiotemporally organized. Its spatial organization consists of multiple, localized coherent patterns, or patchy clusters. These patterns propagate across the circuits over time. This type of collective behavior has ubiquitously been observed, both in spontaneous activity and evoked responses; its function, however, has remained unclear. We construct a spatially extended, spiking neural circuit that generates emergent spatiotemporal activity patterns, thereby capturing some of the complexities of the patterns observed empirically. We elucidate what kind of fundamental function these patterns can serve by showing how they process information. As self-sustained objects, localized coherent patterns can signal information by propagating across the neural circuit. Computational operations occur when these emergent patterns interact, or collide with each other. The ongoing behaviors of these patterns naturally embody both distributed, parallel computation and cascaded logical operations. Such distributed computations enable the system to work in an inherently flexible and efficient way. Our work leads us to propose that propagating coherent activity patterns are the underlying primitives with which neural circuits carry out distributed dynamical computation

The Online Shadow of Offline Signals: Which Sellers Get Contacted in Online B2B Marketplaces?

This article extends the understanding of what impels buyers to contact particular sellers in online business-to-business (B2B) marketplaces, which are typically characterized by sparse social structures and concomitant limitations in observing social cues. Integrating an institutional perspective with signaling theory, our core argument is that offline seller characteristics that are visible online—in particular, geographic location and legal status—convey credible signals of seller behavior because they provide buyers with information on sellers’ local institutional quality and the institutionally-induced obligations and controls acting on sellers. Using unique data from a large Italian online B2B marketplace between the fourth quarter of 1999 and July 2001, we find that both sellers’ local institutional quality and their legal statuses affect a buyer’s likelihood of contacting a seller. Moreover, consistent with the idea that a buyer’s own local institutional quality generates a relevant reference point against which sellers are evaluated, we find that a buyer is progressively more likely to contact sellers the higher their local institutional quality relative to the buyer. Jointly, our findings imply that in online B2B marketplaces, signals conveyed by sellers’ geographic locations and legal statuses may constitute substantive sources of competitive heterogeneity and market segmentation

The Relationship between Healthcare Expenditure and Disposable Personal Income in the US States: A Fractional Integration and Cointegration Analysis

This study examines the relationship between healthcare expenditure and disposable income in the 50 US states over the period 1966-2009 using fractional integration and cointegration techniques. The degree of integration and nonlinearity of both series are found to vary considerably across states, whilst the fractional cointegration analysis suggests that a long-run relationship exists between them in only 11 out of the 50 US states. The estimated long-run income elasticity of healthcare expenditure suggests that health care is a luxury good in these states. By contrast, the short-run elasticity obtained from the regressions in first differences is in the range (0,1) for most US states, which suggests that health care is a necessity good instead. The implications of these results for health policy are also discussed