Mass-Matching in Higgsless

Modern extra-dimensional Higgsless scenarios rely on a mass-matching between fermionic and bosonic KK resonances to evade constraints from precision electroweak measurements. After analyzing all of the Tevatron and LEP bounds on these so-called Cured Higgsless scenarios, we study their LHC signatures and explore how to identify the mass-matching mechanism, the key to their viability. We find singly and pair produced fermionic resonances show up as clean signals with 2 or 4 leptons and 2 hard jets, while neutral and charged bosonic resonances are visible in the dilepton and leptonic WZ channels, respectively. A measurement of the resonance masses from these channels shows the matching necessary to achieve $S\simeq 0$. Moreover, a large single production of KK-fermion resonances is a clear indication of compositeness of SM quarks. Discovery reach is below 10 fb$^{-1}$ of luminosity for resonances in the 700 GeV range.Comment: 28 pages, 18 figure

Genetic determinants of co-accessible chromatin regions in activated T cells across humans.

Over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found that regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution, consistent with the three-dimensional chromatin organization measured by in situ Hi-C in T cells. Fifteen percent of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (local-ATAC-QTLs). Local-ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression

Simulating the carbon balance of a temperate larch forest under various meteorological conditions

<p>Abstract</p> <p>Background</p> <p>Changes in the timing of phenological events may cause the annual carbon budget of deciduous forests to change. Therefore, one should take such events into account when evaluating the effects of global warming on deciduous forests. In this article, we report on the results of numerical experiments done with a model that includes a phenological module simulating the timing of bud burst and other phenological events and estimating maximum leaf area index.</p> <p>Results</p> <p>This study suggests that the negative effects of warming on tree productivity (net primary production) outweigh the positive effects of a prolonged growing season. An increase in air temperature by 3°C (5°C) reduces cumulative net primary production by 21.3% (34.2%). Similarly, cumulative net ecosystem production (the difference between cumulative net primary production and heterotrophic respiration) decreases by 43.5% (64.5%) when temperatures are increased by 3°C (5°C). However, the positive effects of CO₂enrichment (2 × CO₂) outweigh the negative effects of warming (<5°C).</p> <p>Conclusion</p> <p>Although the model was calibrated and validated for a specific forest ecosystem, the implications of the study may be extrapolated to deciduous forests in cool-temperate zones. These forests share common features, and it can be conjectured that carbon stocks would increase in such forests in the face of doubled CO₂and increased temperatures as long as the increase in temperature does not exceed 5°C.</p

Risk Factors of Peritoneal Recurrence and Outcome of Resected Peritoneal Recurrence After Liver Resection in Hepatocellular Carcinoma: Review of 1222 Cases of Hepatectomy in a Tertiary Institution

10.1245/s10434-012-2260-3Annals of Surgical Oncology1972246-225

Weighted gene coexpression network analysis strategies applied to mouse weight

Systems-oriented genetic approaches that incorporate gene expression and genotype data are valuable in the quest for genetic regulatory loci underlying complex traits. Gene coexpression network analysis lends itself to identification of entire groups of differentially regulated genes—a highly relevant endeavor in finding the underpinnings of complex traits that are, by definition, polygenic in nature. Here we describe one such approach based on liver gene expression and genotype data from an F2 mouse intercross utilizing weighted gene coexpression network analysis (WGCNA) of gene expression data to identify physiologically relevant modules. We describe two strategies: single-network analysis and differential network analysis. Single-network analysis reveals the presence of a physiologically interesting module that can be found in two distinct mouse crosses. Module quantitative trait loci (mQTLs) that perturb this module were discovered. In addition, we report a list of genetic drivers for this module. Differential network analysis reveals differences in connectivity and module structure between two networks based on the liver expression data of lean and obese mice. Functional annotation of these genes suggests a biological pathway involving epidermal growth factor (EGF). Our results demonstrate the utility of WGCNA in identifying genetic drivers and in finding genetic pathways represented by gene modules. These examples provide evidence that integration of network properties may well help chart the path across the gene–trait chasm

Effects of FVB/NJ and C57Bl/6J strain backgrounds on mammary tumor phenotype in inducible nitric oxide synthase deficient mice

The ability to genetically manipulate mice has led to rapid progress in our understanding of the roles of different gene products in human disease. Transgenic mice have often been created in the FVB/NJ (FVB) strain due to its high fecundity, while gene-targeted mice have been developed in the 129/SvJ-C57Bl/6J strains due to the capacity of 129/SvJ embryonic stem cells to facilitate germline transmission. Gene-targeted mice are commonly backcrossed into the C57Bl/6J (B6) background for comparison with existing data. Genetic modifiers have been shown to modulate mammary tumor latency in mouse models of breast cancer and it is commonly known that the FVB strain is susceptible to mammary tumors while the B6 strain is more resistant. Since gene-targeted mice in the B6 background are frequently bred into the polyomavirus middle T (PyMT) mouse model of breast cancer in the FVB strain, we have sought to understand the impact of the different genetic backgrounds on the resulting phenotype. We bred mice deficient in the inducible nitric oxide synthase (iNOS) until they were congenic in the PyMT model in the FVB and B6 strains. Our results reveal that the large difference in mean tumor latencies in the two backgrounds of 53 and 92 days respectively affect the ability to discern smaller differences in latency due to the Nos2 genetic mutation. Furthermore, the longer latency in the B6 strain enables a more detailed analysis of tumor formation indicating that individual tumor development is not stoichastic, but is initiated in the #1 glands and proceeds in early and late phases. NO production affects tumors that develop early suggesting an association of iNOS-induced NO with a more aggressive tumor phenotype, consistent with human clinical data positively correlating iNOS expression with breast cancer progression. An examination of lung metastases, which are significantly reduced in PyMT/iNOS(−/−) mice compared with PyMT/iNOS(+/+) mice only in the B6 background, is concordant with these findings. Our data suggest that PyMT in the B6 background provides a useful model for the study of inflammation-induced breast cancer