Optimization of miRNA-seq data preprocessing.

The past two decades of microRNA (miRNA) research has solidified the role of these small non-coding RNAs as key regulators of many biological processes and promising biomarkers for disease. The concurrent development in high-throughput profiling technology has further advanced our understanding of the impact of their dysregulation on a global scale. Currently, next-generation sequencing is the platform of choice for the discovery and quantification of miRNAs. Despite this, there is no clear consensus on how the data should be preprocessed before conducting downstream analyses. Often overlooked, data preprocessing is an essential step in data analysis: the presence of unreliable features and noise can affect the conclusions drawn from downstream analyses. Using a spike-in dilution study, we evaluated the effects of several general-purpose aligners (BWA, Bowtie, Bowtie 2 and Novoalign), and normalization methods (counts-per-million, total count scaling, upper quartile scaling, Trimmed Mean of M, DESeq, linear regression, cyclic loess and quantile) with respect to the final miRNA count data distribution, variance, bias and accuracy of differential expression analysis. We make practical recommendations on the optimal preprocessing methods for the extraction and interpretation of miRNA count data from small RNA-sequencing experiments

Melanocytes are selectively vulnerable to UVA-mediated bystander oxidative signaling.

Long-wave UVA is the major component of terrestrial UV radiation and is also the predominant constituent of indoor sunlamps, both of which have been shown to increase cutaneous melanoma risk. Using a two-chamber model, we show that UVA-exposed target cells induce intercellular oxidative signaling to non-irradiated bystander cells. This UVA-mediated bystander stress is observed between all three cutaneous cell types (i.e., keratinocytes, melanocytes, and fibroblasts). Significantly, melanocytes appear to be more resistant to direct UVA effects compared with keratinocytes and fibroblasts, although melanocytes are also more susceptible to bystander oxidative signaling. The extensive intercellular flux of oxidative species has not been previously appreciated and could possibly contribute to the observed cancer risk associated with prolonged UVA exposure

Generation of charged droplets by field ionization of liquid helium

Positively charged helium droplets were produced by ionization of liquid helium in an electrostatic spraying experiment, in which fluid emerging from a thin glass capillary was ionized by applying a high voltage to a needle inside the capillary. At 2.2 K, fine droplets (<10 mu m in diameter) were produced in pulsed sprays or showers with total currents as high as 0.4 mu A at relatively low voltages (2-4 kV). Ionization was accompanied by a visible glow at the needle and glass tips. Droplet formation was suppressed at 3.5 K. In contrast, liquid nitrogen formed a well-defined Taylor cone with droplets having diameters comparable to the jet (approximate to 100 mu m) at much lower currents (3 nA) and higher voltages (9 kV), in agreement with previous results. The mechanism for charging in these liquids was proposed to be field ionization, identical to the processes leading to conduction in cryogenic insulating liquids observed by Gomer. The high currents resulting from field ionization in helium, together with the intrinsically low surface tension of helium I, led to charge densities that greatly exceeded the Rayleigh limit, thus preventing formation of a Taylor cone and resulting in Coulomb explosion of the liquid

Curvature dependence of the effect of ionic functionalization on the attraction among nanoparticles in dispersion

Solubilization of nanoparticles facilitates nanomaterial processing and enables new applications. An effective method to improve dispersibility in water is provided by ionic functionalization.We explore how the necessary extent of functionalization depends on the particle geometry. Using molecular dynamics/umbrella sampling simulations, we determine the effect of the solute curvature on solventaveraged interactions among ionizing graphitic nanoparticles in aqueous dispersion. We tune the hydrophilicity of molecular-brush coated fullerenes, carbon nanotubes, and graphane platelets by gradually replacing a fraction of the methyl end groups of the alkyl coating by the ionizing –COOK or –NH3Cl groups. To assess the change in nanoparticles’ dispersibility in water, we determine the potential-of-mean-force profiles at varied degrees of ionization. When the coating comprises only propyl groups, the attraction between the hydrophobic particles intensifies from spherical to cylindrical to planar geometry. This is explained by the increasing fraction of surface groups that can be brought into contact and the reduced access to water molecules, both following the above sequence. When ionic groups are added, however, the dispersibility increases in the opposite order, with the biggest effect in the planar geometry and the smallest in the spherical geometry. These results highlight the important role of geometry in nanoparticle solubilization by ionic functionalities, with about twice higher threshold surface charge necessary to stabilize a dispersion of spherical than planar particles. At 25%–50% ionization, the potential of mean force reaches a plateau because of the counterion condensation and saturated brush hydration. Moreover, the increase in the fraction of ionic groups can weaken the repulsion through counterion correlations between adjacent nanoparticles. High degrees of ionization and concomitant ionic screening gradually reduce the differences among surface interactions in distinct geometries until an essentially curvature-independent dispersion environment is created. Insights into tuning nanoparticle interactions can guide the synthesis of a broad class of nonpolar nanoparticles, where solubility is achieved by ionic functionalization

Development of physical and mathematical models for the Porous Ceramic Tube Plant Nutrification System (PCTPNS)

A physical model of the Porous Ceramic Tube Plant Nutrification System (PCTPNS) was developed through microscopic observations of the tube surface under various operational conditions. In addition, a mathematical model of this system was developed which incorporated the effects of the applied suction pressure, surface tension, and gravitational forces as well as the porosity and physical dimensions of the tubes. The flow of liquid through the PCTPNS was thus characterized for non-biological situations. One of the key factors in the verification of these models is the accurate and rapid measurement of the 'wetness' or holding capacity of the ceramic tubes. This study evaluated a thermistor based moisture sensor device and recommendations for future research on alternative sensing devices are proposed. In addition, extensions of the physical and mathematical models to include the effects of plant physiology and growth are also discussed for future research

The RAS/Mitogen Activated Protein (MAP) Kinase Pathway in Melanoma Biology and Therapeutics

An effective treatment for metastatic melanoma remains one of the most elusive goals in all of oncology. Several generations of therapeutic trials have yet to yield any agents that can significantly prolong survival for widespread disease. Despite this disheartening history, our understanding of the biology and molecular genetics of melanoma hold the promise of a new era of molecular targets. One pathway that appears to be universally activated in and critically needed for melanoma growth is the Ras/mitogen activated protein (MAP) kinase signaling cascade. Since the enzymatic functions of the signaling partners are well characterized, this pathway offers many potential “druggable” candidates including Braf, Mek and Ras itself. In this review, we describe this pathway in the context of melanoma tumorigenesis and discuss some of the current relevant pharmacologic treatments and clinical trials

Genomes, expression profiles, and diversity of mitochondria of the White-footed Deermouse Peromyscus leucopus, reservoir of Lyme disease and other zoonoses.

The cricetine rodents Peromyscus leucopus and P. maniculatus are key reservoirs for several zoonotic diseases in North America. We determined the complete circular mitochondrial genome sequences of representatives of 3 different stock colonies of P. leucopus, one stock colony of P. maniculatus and two wild populations of P. leucopus. The genomes were syntenic with that of the murids Mus musculus and Rattus norvegicus. Phylogenetic analysis confirmed that these two Peromyscus species are sister taxa in a clade with P. polionotus and also uncovered a distinction between P. leucopus populations in the eastern and the central United States. In one P. leucopus lineage four extended regions of mitochondrial pseudogenes were identified in the nuclear genome. RNA-seq analysis revealed transcription of the entire genome and differences from controls in the expression profiles of mitochondrial genes in the blood, but not in liver or brain, of animals infected with the zoonotic pathogen Borrelia hermsii. PCR and sequencing of the D-loop of the mitochondrion identified 32 different haplotypes among 118 wild P. leucopus at a Connecticut field site. These findings help to further establish P. leucopus as a model organism for studies of emerging infectious diseases, ecology, and in other disciplines

Generation of energetic He atom beams by a pulsed positive corona discharge

Time-of-flight measurements were made of neutral helium atom beams extracted from a repetitive, pulsed, positive-point corona discharge. Two strong neutral peaks, one fast and one slow, were observed, accompanied by a prompt photon peak and a fast ion peak. All peaks were correlated with the pulsing of the discharge. The two types of atoms appear to be formed by different mechanisms at different stages of the corona discharge. The fast atoms had energies of 190 eV and were formed at the onset of the pulsing, approximately 0.7 µs before the maximum of the photon peak. The slow peak, composed of electronically metastable He atoms, originated 30–50 µs after the photon pulse, and possessed a nearly thermal velocity distribution. The velocity distribution was typical of an undisturbed supersonic expansion with a stagnation temperature of 131 K and a speed ratio of 3.6. Peak intensities and velocities were measured as a function of source voltage, stagnation pressure, and skimmer voltage

Centrifugal adsorption system

A gas-liquid separator uses a helical passageway to impart a spiral motion to a fluid passing therethrough. The centrifugal force generated by the spiraling motion urges the liquid component of the fluid radially outward which forces the gas component radially inward. The gas component is then separated through a gas-permeable, liquid-impervious membrane and discharged through a central passageway. A filter material captures target substances contained in the fluid

Exploiting the noise: improving biomarkers with ensembles of data analysis methodologies.

BackgroundThe advent of personalized medicine requires robust, reproducible biomarkers that indicate which treatment will maximize therapeutic benefit while minimizing side effects and costs. Numerous molecular signatures have been developed over the past decade to fill this need, but their validation and up-take into clinical settings has been poor. Here, we investigate the technical reasons underlying reported failures in biomarker validation for non-small cell lung cancer (NSCLC).MethodsWe evaluated two published prognostic multi-gene biomarkers for NSCLC in an independent 442-patient dataset. We then systematically assessed how technical factors influenced validation success.ResultsBoth biomarkers validated successfully (biomarker #1: hazard ratio (HR) 1.63, 95% confidence interval (CI) 1.21 to 2.19, P = 0.001; biomarker #2: HR 1.42, 95% CI 1.03 to 1.96, P = 0.030). Further, despite being underpowered for stage-specific analyses, both biomarkers successfully stratified stage II patients and biomarker #1 also stratified stage IB patients. We then systematically evaluated reasons for reported validation failures and find they can be directly attributed to technical challenges in data analysis. By examining 24 separate pre-processing techniques we show that minor alterations in pre-processing can change a successful prognostic biomarker (HR 1.85, 95% CI 1.37 to 2.50, P &lt; 0.001) into one indistinguishable from random chance (HR 1.15, 95% CI 0.86 to 1.54, P = 0.348). Finally, we develop a new method, based on ensembles of analysis methodologies, to exploit this technical variability to improve biomarker robustness and to provide an independent confidence metric.ConclusionsBiomarkers comprise a fundamental component of personalized medicine. We first validated two NSCLC prognostic biomarkers in an independent patient cohort. Power analyses demonstrate that even this large, 442-patient cohort is under-powered for stage-specific analyses. We then use these results to discover an unexpected sensitivity of validation to subtle data analysis decisions. Finally, we develop a novel algorithmic approach to exploit this sensitivity to improve biomarker robustness