Microfluidic actuation by modulation of surface stresses

We demonstrate the active manipulation of nanoliter liquid samples on the surface of a glass or silicon substrate by combining chemical surface patterning with electronically addressable microheater arrays. Hydrophilic lanes designate the possible routes for liquid migration while activation of specific heater elements determine the trajectories. The induced temperature fields spatially modulate the liquid surface tension thereby providing electronic control over the direction, timing, and flow rate of continuous streams or discrete drops. Temperature maps can be programed to move, split, trap, and mix ultrasmall volumes without mechanically moving parts and with low operating voltages of 2–3 V. This method of fluidic actuation allows direct accessibility to liquid samples for handling and diagnostic purposes and provides an attractive platform for palm-sized and battery-powered analysis and synthesis

The pMSSM Interpretation of LHC Results Using Rernormalization Group Invariants

The LHC has started to constrain supersymmetry-breaking parameters by setting bounds on possible colored particles at the weak scale. Moreover, constraints from Higgs physics, flavor physics, the anomalous magnetic moment of the muon, as well as from searches at LEP and the Tevatron have set additional bounds on these parameters. Renormalization Group Invariants (RGIs) provide a very useful way of representing the allowed parameter space by making direct connection with the values of these parameters at the messenger scale. Using a general approach, based on the pMSSM parametrization of the soft supersymmetry-breaking parameters, we analyze the current experimental constraints to determine the probability distributions for the RGIs. As examples of their application, we use these distributions to analyze the question of Gaugino Mass Unification and to probabilistically determine the parameters of General and Minimal Gauge Mediation with arbitrary Higgs mass parameters at the Messenger Scale.Comment: 38 pages, 10 figure

Information Technologies and Education for the Poor in Africa: Recommendations for a Pro-Poor ICT4D Non-Formal Education Policy

More than half of Africa\u27s youth and adults do not have basic literacy skills and/or have not completed primary or secondary school. It is deeply concerning how little serious attention has been paid to the potential ways in which ICT can enhance such skills, as part of a pro-poor model of ICT for Development (ICT4D). Such work is crucial if the goals of Education for All (EFA) and the Millennium Development Goals (MDG) are to be achieved. The present effort, Information Technologies and Education for the Poor in Africa (ITEPA), is designed to focus attention on what is being and has been attempted in this domain in some of the poorest communities in Africa

Blood-based bioenergetic profiling is related to differences in brain morphology in African Americans with Type 2 diabetes.

Blood-based bioenergetic profiling has promising applications as a minimally invasive biomarker of systemic bioenergetic capacity. In the present study, we examined peripheral blood mononuclear cell (PBMC) mitochondrial function and brain morphology in a cohort of African Americans with long-standing Type 2 diabetes. Key parameters of PBMC respiration were correlated with white matter, gray matter, and total intracranial volumes. Our analyses indicate that these relationships are primarily driven by the relationship of systemic bioenergetic capacity with total intracranial volume, suggesting that systemic differences in mitochondrial function may play a role in overall brain morphology

Immunoregulatory Potential of Exosomes Derived from Cancer Stem Cells.

Head and neck squamous cell carcinomas (HNSCCs) are malignancies that originate in the mucosal lining of the upper aerodigestive tract. Despite advances in therapeutic interventions, survival rates among HNSCC patients have remained static for years. Cancer stem cells (CSCs) are tumor-initiating cells that are highly resistant to treatment, and are hypothesized to contribute to a significant fraction of tumor recurrences. Consequently, further investigations of how CSCs mediate recurrence may provide insights into novel druggable targets. A key element of recurrence involves the tumor's ability to evade immunosurveillance. Recent published reports suggest that CSCs possess immunosuppressive properties, however, the underlying mechanism have yet to be fully elucidated. To date, most groups have focused on the role of CSC-derived secretory proteins, such as cytokines and growth factors. Here, we review the established immunoregulatory role of exosomes derived from mixed tumor cell populations, and propose further study of CSC-derived exosomes may be warranted. Such studies may yield novel insights into new druggable targets, or lay the foundation for future exosome-based diagnostics

High Dimensional Classification of Structural MRI Alzheimer’s Disease Data Based on Large Scale Regularization

In this work we use a large scale regularization approach based on penalized logistic regression to automatically classify structural MRI images (sMRI) according to cognitive status. Its performance is illustrated using sMRI data from the Alzheimer Disease Neuroimaging Initiative (ADNI) clinical database. We downloaded sMRI data from 98 subjects (49 cognitive normal and 49 patients) matched by age and sex from the ADNI website. Images were segmented and normalized using SPM8 and ANTS software packages. Classification was performed using GLMNET library implementation of penalized logistic regression based on coordinate-wise descent optimization techniques. To avoid optimistic estimates classification accuracy, sensitivity, and specificity were determined based on a combination of three-way split of the data with nested 10-fold cross-validations. One of the main features of this approach is that classification is performed based on large scale regularization. The methodology presented here was highly accurate, sensitive, and specific when automatically classifying sMRI images of cognitive normal subjects and Alzheimer disease (AD) patients. Higher levels of accuracy, sensitivity, and specificity were achieved for gray matter (GM) volume maps (85.7, 82.9, and 90%, respectively) compared to white matter volume maps (81.1, 80.6, and 82.5%, respectively). We found that GM and white matter tissues carry useful information for discriminating patients from cognitive normal subjects using sMRI brain data. Although we have demonstrated the efficacy of this voxel-wise classification method in discriminating cognitive normal subjects from AD patients, in principle it could be applied to any clinical population

Radio Variability of Radio Quiet and Radio Loud Quasars

The majority of quasars are weak in their radio emission, with flux densities comparable to those in the optical, and energies far lower. A small fraction, about 10%, are hundreds to thousands of times stronger in the radio. Conventional wisdom holds that there are two classes of quasars, the radio quiets and radio louds, with a deficit of sources having intermediate power. Are there really two separate populations, and if so, is the physics of the radio emission fundamentally different between them? This paper addresses the second question, through a study of radio variability across the full range of radio power, from quiet to loud. The basic findings are that the root mean square amplitude of variability is independent of radio luminosity or radio-to-optical flux density ratio, and that fractionally large variations can occur on timescales of months or less in both radio quiet and radio loud quasars. Combining this with similarities in other indicators, such as radio spectral index and the presence of VLBI-scale components, leads to the suggestion that the physics of radio emission in the inner regions of all quasars is essentially the same, involving a compact, partially opaque core together with a beamed jet.Comment: 32 pages, 9 figures. Astrophysical Journal, in pres

Genetic characterization of Theileria equi infecting horses in North America: evidence for a limited source of U.S. introductions

Background: Theileria equi is a tick-borne apicomplexan hemoparasite that causes equine piroplasmosis. This parasite has a worldwide distribution but the United States was considered to be free of this disease until recently. Methods: We used samples from 37 horses to determine genetic relationships among North American T. equi using the 18S rRNA gene and microsatellites. We developed a DNA fingerprinting panel of 18 microsatellite markers using the first complete genome sequence of T. equi. Results: A maximum parsimony analysis of 18S rRNA sequences grouped the samples into two major clades. The first clade (n= 36) revealed a high degree of nucleotide similarity in U.S. T. equi, with just 0–2 single nucleotide polymorphisms (SNPs) among samples. The remaining sample fell into a second clade that was genetically divergent (48 SNPs) from the other U.S. samples. This sample was collected at the Texas border, but may have originated in Mexico. We genotyped T. equi from the U.S. using microsatellite markers and found a moderate amount of genetic diversity (2–8 alleles per locus). The field samples were mostly from a 2009 Texas outbreak (n= 22) although samples from five other states were also included in this study. Using Weir and Cockerham’s FST estimator (θ) we found strong population differentiation of the Texas and Georgia subpopulations (θ= 0.414), which was supported by a neighbor-joining tree created with predominant single haplotypes. Single-clone infections were found in 27 of the 37 samples (73%), allowing us to identify 15 unique genotypes. Conclusions: The placement of most T. equi into one monophyletic clade by 18S is suggestive of a limited source of introduction into the U.S. When applied to a broader cross section of worldwide samples, these molecular tools should improve source tracking of T. equi outbreaks and may help prevent the spread of this tick-borne parasite

Ecosystem Consequences of Plant Genetic Divergence with Colonization of New Habitat

When plants colonize new habitats altered by natural or anthropogenic disturbances, those individuals may encounter biotic and abiotic conditions novel to the species, which can cause plant functional trait divergence. Over time, site-driven adaptation can give rise to population-level genetic variation, with consequences for plant community dynamics and ecosystem processes. We used a series of 3000-yr-old, lava-created forest fragments on the Island of Hawai`i to examine whether disturbance and subsequent colonization can lead to genetically differentiated populations, and where differentiation occurs, if there are ecosystem consequences of trait-driven changes. These fragments are dominated by a single tree species, Metrosideros polymorpha (Myrtaceae) or ʻohiʻa, which have been actively colonizing the surrounding lava flow created in 1858. To test our ideas about differentiation of genetically determined traits, we (1) created rooted cuttings of ʻohiʻa individuals sampled from fragment interiors and open lava sites, raised these individuals in a greenhouse, and then used these cuttings to create a common garden where plant growth was monitored for three years; and (2) assessed genetic variation and made QST/FST comparisons using microsatellite repeat markers. Results from the greenhouse showed quantitative trait divergence in plant height and pubescence across plants sampled from fragment interior and matrix sites. Results from the subsequent common garden study confirmed that the matrix environment can select for individuals with 9.1% less shoot production and 17.3% higher leaf pubescence. We found no difference in molecular genetic variation indicating gene flow among the populations. The strongest QST level was greater than the FST estimate, indicating sympatric genetic divergence in growth traits. Tree height was correlated with ecosystem properties such as soil carbon and nitrogen storage, soil carbon turnover rates, and soil phosphatase activity, indicating that selection for growth traits will influence structure, function, and dynamics of developing ecosystems. These data show that divergence can occur on centennial timescales of early colonization