49 research outputs found
Supersymmetry in carbon nanotubes in a transverse magnetic field
Electron properties of Carbon nanotubes in a transverse magnetic field are
studied using a model of a massless Dirac particle on a cylinder. The problem
possesses supersymmetry which protects low energy states and ensures stability
of the metallic behavior in arbitrarily large fields. In metallic tubes we find
suppression of the Fermi velocity at half-filling and enhancement of the
density of states. In semiconducting tubes the energy gap is suppressed. These
features qualitatively persist (although to a smaller degree) in the presence
of electron interactions. The possibilities of experimental observation of
these effects are discussed.Comment: A new section on electron interaction effects added and explanation
on roles of supersymmetry expanded. Revtex4, 6 EPS figure file
Design of Experiments for Screening
The aim of this paper is to review methods of designing screening
experiments, ranging from designs originally developed for physical experiments
to those especially tailored to experiments on numerical models. The strengths
and weaknesses of the various designs for screening variables in numerical
models are discussed. First, classes of factorial designs for experiments to
estimate main effects and interactions through a linear statistical model are
described, specifically regular and nonregular fractional factorial designs,
supersaturated designs and systematic fractional replicate designs. Generic
issues of aliasing, bias and cancellation of factorial effects are discussed.
Second, group screening experiments are considered including factorial group
screening and sequential bifurcation. Third, random sampling plans are
discussed including Latin hypercube sampling and sampling plans to estimate
elementary effects. Fourth, a variety of modelling methods commonly employed
with screening designs are briefly described. Finally, a novel study
demonstrates six screening methods on two frequently-used exemplars, and their
performances are compared
Education and gastric cancer risk-An individual participant data meta-analysis in the StoP project consortium
Low socioeconomic position (SEP) is a strong risk factor for incidence and premature mortality from several cancers. Our study aimed at quantifying the association between SEP and gastric cancer (GC) risk through an individual participant data meta-analysis within the "Stomach cancer Pooling (StoP) Project". Educational level and household income were used as proxies for the SEP. We estimated pooled odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) across levels of education and household income by pooling study-specific ORs through random-effects meta-analytic models. The relative index of inequality (RII) was also computed. A total of 9,773 GC cases and 24,373 controls from 25 studies from Europe, Asia and America were included. The pooled OR for the highest compared to the lowest level of education was 0.60 (95% CI, 0.44-0.84), while the pooled RII was 0.45 (95% CI, 0.29-0.69). A strong inverse association was observed both for noncardia (OR 0.39, 95% CI, 0.22-0.70) and cardia GC (OR 0.47, 95% CI, 0.22-0.99). The relation was stronger among H. pylori negative subjects (RII 0.14, 95% CI, 0.04-0.48) as compared to H. pylori positive ones (RII 0.29, 95% CI, 0.10-0.84), in the absence of a significant interaction (p\u2009=\u20090.28). The highest household income category showed a pooled OR of 0.65 (95% CI, 0.48-0.89), while the corresponding RII was 0.40 (95% CI, 0.22-0.72). Our collaborative pooled-analysis showed a strong inverse relationship between SEP indicators and GC risk. Our data call for public health interventions to reduce GC risk among the more vulnerable groups of the population
Potencial climático para a produção de uvas em sistema de dupla poda anual no estado do Paraná
Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network
Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism
Pervasive gaps in Amazonian ecological research
Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost
Occupational exposures and odds of gastric cancer: a StoP project consortium pooled analysis
BACKGROUND:
Gastric cancer pathogenesis represents a complex interaction of host genetic determinants, microbial virulence factors and environmental exposures. Our primary aim was to determine the association between occupations/occupational exposures and odds of gastric cancer.
METHODS:
We conducted a pooled-analysis of individual-level data harmonized from 11 studies in the Stomach cancer Pooling Project. Multivariable logistic regression was used to estimate the odds ratio (OR) of gastric cancer adjusted for relevant confounders.
RESULTS:
A total of 5279 gastric cancer cases and 12 297 controls were analysed. There were higher odds of gastric cancer among labour-related occupations, including: agricultural and animal husbandry workers [odds ratio (OR) 1.33, 95% confidence interval (CI): 1.06-1.68]; miners, quarrymen, well-drillers and related workers (OR 1.70, 95% CI: 1.01-2.88); blacksmiths, toolmakers and machine-tool operators (OR 1.41, 95% CI: 1.05-1.89); bricklayers, carpenters and construction workers (OR 1.30, 95% CI: 1.06-1.60); and stationary engine and related equipment operators (OR 6.53, 95% CI: 1.41-30.19). The ORs for wood-dust exposure were 1.51 (95% CI: 1.01-2.26) for intestinal-type and 2.52 (95% CI: 1.46-4.33) for diffuse-type gastric cancer. Corresponding values for aromatic amine exposure were 1.83 (95% CI: 1.09-3.06) and 2.92 (95% CI: 1.36-6.26). Exposure to coal derivatives, pesticides/herbicides, chromium, radiation and magnetic fields were associated with higher odds of diffuse-type, but not intestinal-type gastric cancer.
CONCLUSIONS:
Based on a large pooled analysis, we identified several occupations and related exposures that are associated with elevated odds of gastric cancer. These findings have potential implications for risk attenuation and could be used to direct investigations evaluating the impact of targeted gastric cancer prevention/early detection programmes based on occupation