New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Cross-Layer Latency Minimization in Wireless Networks with SINR Constraints

Recently, there has been substantial interest in the design of cross-\ud layer protocols for wireless networks. These protocols optimize\ud certain performance metric(s) of interest (e.g. latency, energy, rate)\ud by jointly optimizing the performance of multiple layers of the\ud protocol stack. Algorithm designers often use geometric-graph-\ud theoretic models for radio interference to design such cross-layer\ud protocols. In this paper we study the problem of designing cross-\ud layer protocols for multi-hop wireless networks using a more real-\ud istic Signal to Interference plus Noise Ratio (SINR) model for radio\ud interference. The following cross-layer latency minimization prob-\ud lem is studied: Given a set V of transceivers, and a set of source-\ud destination pairs, (i) choose power levels for all the transceivers, (ii)\ud choose routes for all connections, and (iii) construct an end-to-end\ud schedule such that the SINR constraints are satisfied at each time\ud step so as to minimize the make-span of the schedule (the time\ud by which all packets have reached their respective destinations).\ud We present a polynomial-time algorithm with provable worst-case\ud performance guarantee for this cross-layer latency minimization\ud problem. As corollaries of the algorithmic technique we show that\ud a number of variants of the cross-layer latency minimization prob-\ud lem can also be approximated efficiently in polynomial time. Our\ud work extends the results of Kumar et al. (Proc. SODA, 2004) and\ud Moscibroda et al. (Proc. MOBIHOC, 2006). Although our algo-\ud rithm considers multiple layers of the protocol stack, it can natu-\ud rally be viewed as compositions of tasks specific to each layer —\ud this allows us to improve the overall performance while preserving\ud the modularity of the layered structure.\u

Approximation Algorithms for Computing Capacity of Wireless Networks with SINR constraints

Abstract—A fundamental problem in wireless networks is to estimate its throughput capacity- given a set of wireless nodes, and a set of connections, what is the maximum rate at which data can be sent on these connections. Most of the research in this direction has focused on either random distributions of points, or has assumed simple graph-based models for wireless interference. In this paper, we study capacity estimation problem using the more general Signal to Interference Plus Noise Ratio (SINR) model for interference, on arbitrary wireless networks. The problem becomes much harder in this setting, because of the non-locality of the SINR model. Recent work by Moscibroda et al. [16], [18] has shown that the throughput in this model can differ from graph based models significantly. We develop polynomial time algorithms to provably approximate the total throughput in this setting. I

Percoll discontinuous density gradient centrifugation method for the fractionation of the subpopulations of Mycobacterium smegmatis and Mycobacterium tuberculosis from in vitro cultures

Bacterial populations in the in vitro laboratory cultures, environment, and patients contain metabolically different subpopulations that respond differently to stress agents, including antibiotics, and emerge as stress tolerant or resistant strains. To contain the emergence of such strains, it is important to study the features of the metabolic status and response of the subpopulations to stress agents. For this purpose, an efficient method is required for the fractionation and isolation of the subpopulations from the cultures. Here we describe in detail the manual setting up of a simple, easy-to-do, reproducibly robust Percoll discontinuous density gradient centrifugation for the fractionation of subpopulations of short-sized cells (SCs) and normal/long-sized cells (NCs) from Mycobacterium smegmatis and Mycobacterium tuberculosis cultures, which we had reported earlier. About 90-98% enrichment was obtained respectively for SCs and NCs for M. smegmatis and 69-67% enrichment was obtained respectively for the SCs and NCs for M. tuberculosis. • The Percoll discontinuous density gradient centrifugation helps the fractionation and isolation of mycobacterial subpopulations that differ in density. • The method offers a consistently reproducible high enrichment of the subpopulations of SCs and NCs from the in vitro cultures of M. smegmatis and M. tuberculosis. • Our earlier reports on the consistency in the differential response of the subpopulations, enriched using the method, to oxidative, nitrite, and antibiotic stress proves its validity

A framework for resource discovery in pervasive computing for mobile aware task execution

Aimed to provide computation ubiquitously, pervasive computing is perceived as a means to provide a user the transparency of anywhere, anyplace, anytime computing. Pervasive computing is characterized by execution of high-level user tasks in heterogeneous environments that use invisible and ubiquitously distributed computational devices. Resource discovery is an integral part of pervasive computing. Due to the limited computing capacities of the mobile entities in the pervasive space it becomes important for these entities to discover equivalent peers to execute complex tasks. Also requirements of tasks in pervasive space are diverse ranging from static resources like printers to dynamically varying resources like network bandwidth. This requires seamless aggregation of resources/services required for the execution of the task. This is further complicated by frequent associations and disassociation of mobile elements with hotspots which are highly variable in performance and availability. We believe that predicting variability of resources would make the task mobile aware rather than mobility oblivious. We propose a framework for estimation of future resource requirements, which would allow the mobile applications to adapt to wearing (due to disassociations and reassociations) of resources. We also show through case analysis that proactive systems benefit from our architecture

Genomic analysis reveals epistatic silencing of ``expensive'' genes in Escherichia coli K-12

International audienceA barrier for horizontal gene transfer is high gene expression, which is metabolically expensive. Silencing of horizontally-acquired genes in the bacterium Escherichia coli is caused by the global transcriptional repressor H-NS. The activity of H-NS is enhanced or diminished by other proteins including its homologue StpA, and Hha and YdgT. The interconnections of H-NS with these regulators and their role in silencing gene expression in E. coli are not well understood on a genomic scale. In this study, we use transcriptome sequencing to show that there is a bi-layered gene silencing system - involving the homologous H-NS and StpA - operating on horizontally-acquired genes among others. We show that H-NS-repressed genes belong to two types, termed ``epistatic'' and ``unilateral''. In the absence of H-NS, the expression of ``epistatically controlled genes'' is repressed by StpA, whereas that of ``unilaterally controlled genes'' is not. Epistatic genes show a higher tendency to be non-essential and recently acquired, when compared to unilateral genes. Epistatic genes reach much higher expression levels than unilateral genes in the absence of the silencing system. Finally, epistatic genes contain more high affinity H-NS binding motifs than unilateral genes. Therefore, both the DNA binding sites of H-NS as well as the function of StpA as a backup system might be selected for silencing highly transcribable genes