Of Mice and Men: Not ExAKTly the Same?

The serine-threonine protein kinase Akt2, also known as PKBβ, has been shown to regulate glucose and lipid metabolism in animal models. In a recent study published in Science, Hussain et al. (2011) report that in human subjects an activating mutation of Akt2 leads to hypoglycemia and, unexpectedly, asymmetric overgrowth

A comparative investigation of the combined effects of pre-processing, wavelength selection and regression methods on near infrared calibration model performance

Near-infrared (NIR) spectroscopy is being widely used in various fields ranging from pharmaceutics to the food industry for analyzing chemical and physical properties of the substances concerned. Its advantages over other analytical techniques include available physical interpretation of spectral data, nondestructive nature and high speed of measurements, and little or no need for sample preparation. The successful application of NIR spectroscopy relies on three main aspects: pre-processing of spectral data to eliminate nonlinear variations due to temperature, light scattering effects and many others, selection of those wavelengths that contribute useful information, and identification of suitable calibration models using linear/nonlinear regression . Several methods have been developed for each of these three aspects and many comparative studies of different methods exist for an individual aspect or some combinations. However, there is still a lack of comparative studies for the interactions among these three aspects, which can shed light on what role each aspect plays in the calibration and how to combine various methods of each aspect together to obtain the best calibration model. This paper aims to provide such a comparative study based on four benchmark data sets using three typical pre-processing methods, namely, orthogonal signal correction (OSC), extended multiplicative signal correction (EMSC) and optical path-length estimation and correction (OPLEC); two existing wavelength selection methods, namely, stepwise forward selection (SFS) and genetic algorithm optimization combined with partial least squares regression for spectral data (GAPLSSP); four popular regression methods, namely, partial least squares (PLS), least absolute shrinkage and selection operator (LASSO), least squares support vector machine (LS-SVM), and Gaussian process regression (GPR). The comparative study indicates that, in general, pre-processing of spectral data can play a significant role in the calibration while wavelength selection plays a marginal role and the combination of certain pre-processing, wavelength selection, and nonlinear regression methods can achieve superior performance over traditional linear regression-based calibration

Caenorhabditis elegans RIG-I Homolog Mediates Antiviral RNA Interference Downstream of Dicer-Dependent Biogenesis of Viral Small Interfering RNAs.

Dicer enzymes process virus-specific double-stranded RNA (dsRNA) into small interfering RNAs (siRNAs) to initiate specific antiviral defense by related RNA interference (RNAi) pathways in plants, insects, nematodes, and mammals. Antiviral RNAi in Caenorhabditis elegans requires Dicer-related helicase 1 (DRH-1), not found in plants and insects but highly homologous to mammalian retinoic acid-inducible gene I (RIG-I)-like receptors (RLRs), intracellular viral RNA sensors that trigger innate immunity against RNA virus infection. However, it remains unclear if DRH-1 acts analogously to initiate antiviral RNAi in C. elegans Here, we performed a forward genetic screen to characterize antiviral RNAi in C. elegans Using a mapping-by-sequencing strategy, we uncovered four loss-of-function alleles of drh-1, three of which caused mutations in the helicase and C-terminal domains conserved in RLRs. Deep sequencing of small RNAs revealed an abundant population of Dicer-dependent virus-derived small interfering RNAs (vsiRNAs) in drh-1 single and double mutant animals after infection with Orsay virus, a positive-strand RNA virus. These findings provide further genetic evidence for the antiviral function of DRH-1 and illustrate that DRH-1 is not essential for the sensing and Dicer-mediated processing of the viral dsRNA replicative intermediates. Interestingly, vsiRNAs produced by drh-1 mutants were mapped overwhelmingly to the terminal regions of the viral genomic RNAs, in contrast to random distribution of vsiRNA hot spots when DRH-1 is functional. As RIG-I translocates on long dsRNA and DRH-1 exists in a complex with Dicer, we propose that DRH-1 facilitates the biogenesis of vsiRNAs in nematodes by catalyzing translocation of the Dicer complex on the viral long dsRNA precursors.IMPORTANCE The helicase and C-terminal domains of mammalian RLRs sense intracellular viral RNAs to initiate the interferon-regulated innate immunity against RNA virus infection. Both of the domains from human RIG-I can substitute for the corresponding domains of DRH-1 to mediate antiviral RNAi in C. elegans, suggesting an analogous role for DRH-1 as an intracellular dsRNA sensor to initiate antiviral RNAi. Here, we developed a forward genetic screen for the identification of host factors required for antiviral RNAi in C. elegans Characterization of four distinct drh-1 mutants obtained from the screen revealed that DRH-1 did not function to initiate antiviral RNAi. We show that DRH-1 acted in a downstream step to enhance Dicer-dependent biogenesis of viral siRNAs in C. elegans As mammals produce Dicer-dependent viral siRNAs to target RNA viruses, our findings suggest a possible role for mammalian RLRs and interferon signaling in the biogenesis of viral siRNAs

In vivo characterisation of a therapeutically relevant self-assembling 18 F-labelled β-sheet forming peptide and its hydrogel using positron emission tomography

Positron emission tomography (PET) and fluorescence labelling have been used to assess the pharmacokinetics, biodistribution and eventual fate of a hydrogel-forming nonapeptide, FEFKFEFKK (F9) in healthy mice, using 18F-labelled and fluoresceinisothiocyanate (FITC) - labelled F9 analogues. F9 was site-specifically radiolabelled with 2-[18F]fluoro-3-pyridinecarboxaldehyde ([18F]FPCA) via oxime bond formation. [18F]FPCA-F9 in vivo fate was evaluated both as a solution, following intravenous administration, and as a hydrogel when subcutaneously injected. The behaviour of FITC-F9 hydrogel was assessed following subcutaneous injection. [18F]FPCA-F9 demonstrated high plasma stability and primarily renal excretion; [18F]FPCA-F9 when in solution and injected into the bloodstream displayed prompt bladder uptake (53.4 ± 16.6 SUV at 20 minutes post injection) and rapid renal excretion, whereas [18F]FPCA-F9 hydrogel, formed by co-assembly of [18F]FPCA-F9 monomer with unfunctionalised F9 peptide and injected subcutaneously, showed gradual bladder accumulation of hydrogel fragments (3.8 ± 0.4 SUV at 20 minutes post injection), resulting in slower renal excretion. Gradual disaggregation of the F9 hydrogel from the site of injection was monitored using FITC-F9 hydrogel in healthy mice (60 ± 3 over 96 hours), indicating a biological half-life between 1-4 days. The in vivo characterisation of F9, both as a gel and a solution highlights its potential as a biomaterial

Metrology of DNA Arrays by Super-Resolution Microscopy

Recent results in the assembly of DNA into structures and arrays with nanoscale features and patterns have opened the possibility of using DNA for sub-10 nm lithographic patterning of semiconductor devices. Super-resolution microscopy is being actively developed for DNA-based imaging and is compatible with inline optical metrology techniques for high volume manufacturing. Here, we combine DNA tile assembly with state-dependent super-resolution microscopy to introduce crystal-PAINT as a novel approach for metrology of DNA arrays. Using this approach, we demonstrate optical imaging and characterization of DNA arrays revealing grain boundaries and the temperature dependence of array quality. For finite arrays, analysis of crystal-PAINT images provides further quantitative information of array properties. This metrology approach enables defect detection and classification and facilitates statistical analysis of self-assembled DNA nanostructures

Evaluation of pooled association tests for rare variant identification

Genome-wide association studies have successfully identified many common variants associated with complex human diseases. However, a large portion of the remaining heritability cannot be explained by these common variants. Exploring rare variants associated with diseases is now catching more attention. Several methods have been recently proposed for identification of rare variants. Among them, the fixed-threshold, weighted-sum, and variable-threshold methods are effective in combining the information of multiple variants into a functional unit; these approaches are commonly used. We evaluate the performance of these three methods. Based on our analyses of the Genetic Analysis Workshop 17 data, we find that no method is universally better than the others. Furthermore, adjusting for potential covariates can not only increase the true-positive proportions but also reduce the false-positive proportions. Our study concludes that there is no uniformly most powerful test among the three methods we compared (the fixed-threshold, weighted-sum, and variable-threshold methods), and their performances depend on the underlying genetic architecture of a disease

25 years of epidermal stem cell research.

This is a chronicle of concepts in the field of epidermal stem cell biology and a historic look at their development over time. The past 25 years have seen the evolution of epidermal stem cell science, from first fundamental studies to a sophisticated science. The study of epithelial stem cell biology was aided by the ability to visualize the distribution of stem cells and their progeny through lineage analysis studies. The excellent progress we have made in understanding epidermal stem cell biology is discussed in this article. The challenges we still face in understanding epidermal stem cells include defining molecular markers for stem and progenitor sub-populations, determining the locations and contributions of the different stem cell niches, and mapping regulatory pathways of epidermal stem cell proliferation and differentiation. However, our rapidly evolving understanding of epidermal stem cells has many potential uses that promise to translate into improved patient therapy