Binary credal classification under sparsity constraints.

Binary classification is a well known problem in statistics. Besides classical methods, several techniques such as the naive credal classifier (for categorical data) and imprecise logistic regression (for continuous data) have been proposed to handle sparse data. However, a convincing approach to the classification problem in high dimensional problems (i.e., when the number of attributes is larger than the number of observations) is yet to be explored in the context of imprecise probability. In this article, we propose a sensitivity analysis based on penalised logistic regression scheme that works as binary classifier for high dimensional cases. We use an approach based on a set of likelihood functions (i.e. an imprecise likelihood, if you like), that assigns a set of weights to the attributes, to ensure a robust selection of the important attributes, whilst training the model at the same time, all in one fell swoop. We do a sensitivity analysis on the weights of the penalty term resulting in a set of sparse constraints which helps to identify imprecision in the dataset

Microprocessor mediates transcriptional termination of long noncoding RNA transcripts hosting microRNAs

MicroRNA (miRNA) play a major role in the post-transcriptional regulation of gene expression. Mammalian miRNA biogenesis begins with co-transcriptional cleavage of RNA polymerase II (Pol II) transcripts by the Microprocessor complex. While most miRNA are located within introns of protein coding genes, a substantial minority of miRNA originate from long non coding (lnc) RNA where transcript processing is largely uncharacterized. Here, by detailed characterization of liver-specific lnc-pri-miR-122 and genome-wide analysis, we show that most lnc-pri-miRNA do not use the canonical cleavage and polyadenylation (CPA) pathway but instead use Microprocessor cleavage to terminate transcription. Microprocessor inactivation leads to extensive transcriptional readthrough of lnc-pri-miRNA and transcriptional interference with downstream genes. Consequently we define a novel RNase III-mediated, polyadenylation-independent mechanism of Pol II transcription termination in mammalian cells

Predicting In Vivo Anti-Hepatofibrotic Drug Efficacy Based on In Vitro High-Content Analysis

Background/Aims Many anti-fibrotic drugs with high in vitro efficacies fail to produce significant effects in vivo. The aim of this work is to use a statistical approach to design a numerical predictor that correlates better with in vivo outcomes. Methods High-content analysis (HCA) was performed with 49 drugs on hepatic stellate cells (HSCs) LX-2 stained with 10 fibrotic markers. ~0.3 billion feature values from all cells in >150,000 images were quantified to reflect the drug effects. A systematic literature search on the in vivo effects of all 49 drugs on hepatofibrotic rats yields 28 papers with histological scores. The in vivo and in vitro datasets were used to compute a single efficacy predictor (Epredict). Results We used in vivo data from one context (CCl4 rats with drug treatments) to optimize the computation of Epredict. This optimized relationship was independently validated using in vivo data from two different contexts (treatment of DMN rats and prevention of CCl4 induction). A linear in vitro-in vivo correlation was consistently observed in all the three contexts. We used Epredict values to cluster drugs according to efficacy; and found that high-efficacy drugs tended to target proliferation, apoptosis and contractility of HSCs. Conclusions The Epredict statistic, based on a prioritized combination of in vitro features, provides a better correlation between in vitro and in vivo drug response than any of the traditional in vitro markers considered.Institute of Bioengineering and Nanotechnology (Singapore)Singapore. Biomedical Research CouncilSingapore. Agency for Science, Technology and ResearchSingapore-MIT Alliance for Research and Technology Center (C-185-000-033-531)Janssen Cilag (R-185-000-182-592)Singapore-MIT Alliance Computational and Systems Biology Flagship Project (C-382-641-001-091)Mechanobiology Institute, Singapore (R-714-001-003-271

Gustatory Perception and Fat Body Energy Metabolism Are Jointly Affected by Vitellogenin and Juvenile Hormone in Honey Bees

Honey bees (Apis mellifera) provide a system for studying social and food-related behavior. A caste of workers performs age-related tasks: young bees (nurses) usually feed the brood and other adult bees inside the nest, while older bees (foragers) forage outside for pollen, a protein/lipid source, or nectar, a carbohydrate source. The workers' transition from nursing to foraging and their foraging preferences correlate with differences in gustatory perception, metabolic gene expression, and endocrine physiology including the endocrine factors vitellogenin (Vg) and juvenile hormone (JH). However, the understanding of connections among social behavior, energy metabolism, and endocrine factors is incomplete. We used RNA interference (RNAi) to perturb the gene network of Vg and JH to learn more about these connections through effects on gustation, gene transcripts, and physiology. The RNAi perturbation was achieved by single and double knockdown of the genes ultraspiracle (usp) and vg, which encode a putative JH receptor and Vg, respectively. The double knockdown enhanced gustatory perception and elevated hemolymph glucose, trehalose, and JH. We also observed transcriptional responses in insulin like peptide 1 (ilp1), the adipokinetic hormone receptor (AKHR), and cGMP-dependent protein kinase (PKG, or “foraging gene” Amfor). Our study demonstrates that the Vg–JH regulatory module controls changes in carbohydrate metabolism, but not lipid metabolism, when worker bees shift from nursing to foraging. The module is also placed upstream of ilp1, AKHR, and PKG for the first time. As insulin, adipokinetic hormone (AKH), and PKG pathways influence metabolism and gustation in many animals, we propose that honey bees have conserved pathways in carbohydrate metabolism and conserved connections between energy metabolism and gustatory perception. Thus, perhaps the bee can make general contributions to the understanding of food-related behavior and metabolic disorders

Strategies for blocking the fibrogenic actions of connective tissue growth factor (CCN2): From pharmacological inhibition in vitro to targeted siRNA therapy in vivo

Connective tissue growth factor (CCN2) is a major pro-fibrotic factor that frequently acts downstream of transforming growth factor beta (TGF-β)-mediated fibrogenic pathways. Much of our knowledge of CCN2 in fibrosis has come from studies in which its production or activity have been experimentally attenuated. These studies, performed both in vitro and in animal models, have demonstrated the utility of pharmacological inhibitors (e.g. tumor necrosis factor alpha (TNF-α), prostaglandins, peroxisome proliferator-activated receptor-gamma (PPAR-γ) agonists, statins, kinase inhibitors), neutralizing antibodies, antisense oligonucleotides, or small interfering RNA (siRNA) to probe the role of CCN2 in fibrogenic pathways. These investigations have allowed the mechanisms regulating CCN2 production to be more clearly defined, have shown that CCN2 is a rational anti-fibrotic target, and have established a framework for developing effective modalities of therapeutic intervention in vivo

Brain Derived Neurotrophic Factor (BDNF) Expression Is Regulated by MicroRNAs miR-26a and miR-26b Allele-Specific Binding

Brain-derived neurotrophic factor (BDNF) is a neurotrophin that plays an essential role in neuronal development and plasticity. MicroRNA (miRNAs) are small non-coding RNAs of about 22-nucleotides in length regulating gene expression at post-transcriptional level. In this study we explore the role of miRNAs as post-transcriptional inhibitors of BDNF and the effect of 3′UTR sequence variations on miRNAs binding capacity. Using an in silico approach we identified a group of miRNAs putatively regulating BDNF expression and binding to BDNF 3′UTR polymorphic sequences. Luciferase assays demonstrated that these miRNAs (miR-26a1/2 and miR-26b) downregulates BDNF expression and that the presence of the variant alleles of two single nucleotide polymorphisms (rs11030100 and rs11030099) mapping in BDNF 3′UTR specifically abrogates miRNAs targeting. Furthermore we found a high linkage disequilibrium rate between rs11030100, rs11030099 and the non-synonymous coding variant rs6265 (Val66Met), which modulates BDNF mRNA localization and protein intracellular trafficking. Such observation led to hypothesize that miR-26s mediated regulation could extend to rs6265 leading to an allelic imbalance with potentially functional effects, such as peptide's localization and activity-dependent secretion. Since rs6265 has been previously implicated in various neuropsychiatric disorders, we evaluated the distribution of rs11030100, rs11030099 and rs6265 both in a control and schizophrenic group, but no significant difference in allele frequencies emerged. In conclusion, in the present study we identified two novel miRNAs regulating BDNF expression and the first BDNF 3′UTR functional variants altering miRNAs-BDNF binding

Pyrosequencing the Bemisia tabaci Transcriptome Reveals a Highly Diverse Bacterial Community and a Robust System for Insecticide Resistance

BACKGROUND: Bemisia tabaci (Gennadius) is a phloem-feeding insect poised to become one of the major insect pests in open field and greenhouse production systems throughout the world. The high level of resistance to insecticides is a main factor that hinders continued use of insecticides for suppression of B. tabaci. Despite its prevalence, little is known about B. tabaci at the genome level. To fill this gap, an invasive B. tabaci B biotype was subjected to pyrosequencing-based transcriptome analysis to identify genes and gene networks putatively involved in various physiological and toxicological processes. METHODOLOGY AND PRINCIPAL FINDINGS: Using Roche 454 pyrosequencing, 857,205 reads containing approximately 340 megabases were obtained from the B. tabaci transcriptome. De novo assembly generated 178,669 unigenes including 30,980 from insects, 17,881 from bacteria, and 129,808 from the nohit. A total of 50,835 (28.45%) unigenes showed similarity to the non-redundant database in GenBank with a cut-off E-value of 10-5. Among them, 40,611 unigenes were assigned to one or more GO terms and 6,917 unigenes were assigned to 288 known pathways. De novo metatranscriptome analysis revealed highly diverse bacterial symbionts in B. tabaci, and demonstrated the host-symbiont cooperation in amino acid production. In-depth transcriptome analysis indentified putative molecular markers, and genes potentially involved in insecticide resistance and nutrient digestion. The utility of this transcriptome was validated by a thiamethoxam resistance study, in which annotated cytochrome P450 genes were significantly overexpressed in the resistant B. tabaci in comparison to its susceptible counterparts. CONCLUSIONS: This transcriptome/metatranscriptome analysis sheds light on the molecular understanding of symbiosis and insecticide resistance in an agriculturally important phloem-feeding insect pest, and lays the foundation for future functional genomics research of the B. tabaci complex. Moreover, current pyrosequencing effort greatly enriched the existing whitefly EST database, and makes RNAseq a viable option for future genomic analysis

Rule-Based Cell Systems Model of Aging using Feedback Loop Motifs Mediated by Stress Responses

Investigating the complex systems dynamics of the aging process requires integration of a broad range of cellular processes describing damage and functional decline co-existing with adaptive and protective regulatory mechanisms. We evolve an integrated generic cell network to represent the connectivity of key cellular mechanisms structured into positive and negative feedback loop motifs centrally important for aging. The conceptual network is casted into a fuzzy-logic, hybrid-intelligent framework based on interaction rules assembled from a priori knowledge. Based upon a classical homeostatic representation of cellular energy metabolism, we first demonstrate how positive-feedback loops accelerate damage and decline consistent with a vicious cycle. This model is iteratively extended towards an adaptive response model by incorporating protective negative-feedback loop circuits. Time-lapse simulations of the adaptive response model uncover how transcriptional and translational changes, mediated by stress sensors NF-κB and mTOR, counteract accumulating damage and dysfunction by modulating mitochondrial respiration, metabolic fluxes, biosynthesis, and autophagy, crucial for cellular survival. The model allows consideration of lifespan optimization scenarios with respect to fitness criteria using a sensitivity analysis. Our work establishes a novel extendable and scalable computational approach capable to connect tractable molecular mechanisms with cellular network dynamics underlying the emerging aging phenotype

The Lysosome and Intracellular Signalling.

In addition to being the terminal degradative compartment of the cell's endocytic and autophagic pathways, the lysosome is a multifunctional signalling hub integrating the cell's response to nutrient status and growth factor/hormone signalling. The cytosolic surface of the limiting membrane of the lysosome is the site of activation of the multiprotein complex mammalian target of rapamycin complex 1 (mTORC1), which phosphorylates numerous cell growth-related substrates, including transcription factor EB (TFEB). Under conditions in which mTORC1 is inhibited including starvation, TFEB becomes dephosphorylated and translocates to the nucleus where it functions as a master regulator of lysosome biogenesis. The signalling role of lysosomes is not limited to this pathway. They act as an intracellular Ca2+ store, which can release Ca2+ into the cytosol for both local effects on membrane fusion and pleiotropic effects within the cell. The relationship and crosstalk between the lysosomal and endoplasmic reticulum (ER) Ca2+ stores play a role in shaping intracellular Ca2+ signalling. Lysosomes also perform other signalling functions, which are discussed. Current views of the lysosomal compartment recognize its dynamic nature. It includes endolysosomes, autolysosome and storage lysosomes that are constantly engaged in fusion/fission events and lysosome regeneration. How signalling is affected by individual lysosomal organelles being at different stages of these processes and/or at different sites within the cell is poorly understood, but is discussed