The history of disaster incidents and impact in Nepal 1900-2005: ecological, geographical, and development perspectives

The people of Nepal today are exposed to perennial local disaster events and profound vulnerability to disaster. The combined efforts of government, donors, UN agencies, NGOs, and Nepalese communities are needed to avert the impacts of disaster events. Much more can be done immediately to reduce the impacts by reviewing the scope and distribution of past disaster events. This article provides an overview of Nepal’s disaster vulnerability through an analysis of the record of disaster events that occurred from 1900 to 2005. The data were generated from historical archives and divided into incidents at the district, subnational, and national levels. Statistical and Geographical Information System (GIS) analyses were carried out to generate district level disaster vulnerability maps. It is concluded that small-scale, local disasters have a greater cumulative impact in terms of casualties than large-scale, national disasters

Genome-wide analyses of cassava Pathogenesis-related (PR) gene families reveal core transcriptome responses to whitefly infestation, salicylic acid and jasmonic acid

BACKGROUND:Whiteflies are a threat to cassava (Manihot esculenta), an important staple food in many tropical/subtropical regions. Understanding the molecular mechanisms regulating cassava's responses against this pest is crucial for developing control strategies. Pathogenesis-related (PR) protein families are an integral part of plant immunity. With the availability of whole genome sequences, the annotation and expression programs of the full complement of PR genes in an organism can now be achieved. An understanding of the responses of the entire complement of PR genes during biotic stress and to the defense hormones, salicylic acid (SA) and jasmonic acid (JA), is lacking. Here, we analyze the responses of cassava PR genes to whiteflies, SA, JA, and other biotic aggressors. RESULTS:The cassava genome possesses 14 of the 17 plant PR families, with a total of 447 PR genes. A cassava PR gene nomenclature is proposed. Phylogenetic relatedness of cassava PR proteins to each other and to homologs in poplar, rice and Arabidopsis identified cassava-specific PR gene family expansions. The temporal programs of PR gene expression in response to the whitefly (Aleurotrachelus socialis) in four whitefly-susceptible cassava genotypes showed that 167 of the 447 PR genes were regulated after whitefly infestation. While the timing of PR gene expression varied, over 37% of whitefly-regulated PR genes were downregulated in all four genotypes. Notably, whitefly-responsive PR genes were largely coordinately regulated by SA and JA. The analysis of cassava PR gene expression in response to five other biotic stresses revealed a strong positive correlation between whitefly and Xanthomonas axonopodis and Cassava Brown Streak Virus responses and negative correlations between whitefly and Cassava Mosaic Virus responses. Finally, certain associations between PR genes in cassava expansions and response to biotic stresses were observed among PR families. CONCLUSIONS:This study represents the first genome-wide characterization of PR genes in cassava. PR gene responses to six biotic stresses and to SA and JA are demonstrably different to other angiosperms. We propose that our approach could be applied in other species to fully understand PR gene regulation by pathogens, pests and the canonical defense hormones SA and JA

A metabolomics characterisation of natural variation in the resistance of cassava to whitefly

Background: Cassava whitefly outbreaks were initially reported in East and Central Africa cassava (Manihot esculenta Crantz) growing regions in the 1990's and have now spread to other geographical locations, becoming a global pest severely affecting farmers and smallholder income. Whiteflies impact plant yield via feeding and vectoring cassava mosaic and brown streak viruses, making roots unsuitable for food or trading. Deployment of virus resistant varieties has had little impact on whitefly populations and therefore development of whitefly resistant varieties is also necessary as part of integrated pest management strategies. Suitable sources of whitefly resistance exist in germplasm collections that require further characterization to facilitate and assist breeding programs. Results: In the present work, a hierarchical metabolomics approach has been employed to investigate the underlying biochemical mechanisms associated with whitefly resistance by comparing two naturally occurring accessions of cassava, one susceptible and one resistant to whitefly. Quantitative differences between genotypes detected at pre-infestation stages were consistently observed at each time point throughout the course of the whitefly infestation. This prevalent differential feature suggests that inherent genotypic differences override the response induced by the presence of whitefly and that they are directly linked with the phenotype observed. The most significant quantitative changes relating to whitefly susceptibility were linked to the phenylpropanoid super-pathway and its linked sub-pathways: monolignol, flavonoid and lignan biosynthesis. These findings suggest that the lignification process in the susceptible variety is less active, as the susceptible accession deposits less lignin and accumulates monolignol intermediates and derivatives thereof, differences that are maintained during the time-course of the infestation. Conclusions: Resistance mechanism associated to the cassava whitefly-resistant accession ECU72 is an antixenosis strategy based on reinforcement of cell walls. Both resistant and susceptible accessions respond differently to whitefly attack at biochemical level, but the inherent metabolic differences are directly linked to the resistance phenotype rather than an induced response in the plant

IRX-2, a Novel Immunotherapeutic, Enhances Functions of Human Dendritic Cells

Background: In a recent phase II clinical trial for HNSCC patients, IRX-2, a cell-derived biologic, promoted T-cell infiltration into the tumor and prolonged overall survival. Mechanisms responsible for these IRX-2-mediated effects are unknown. We hypothesized that IRX-2 enhanced tumor antigen-(TA)-specific immunity by up-regulating functions of dendritic cells (DC). Methodology/Principal Findings: Monocyte-derived DC obtained from 18 HNSCC patients and 12 healthy donors were matured using IRX-2 or a mix of TNF-α, IL-1β and IL-6 ("conv. mix"). Multicolor flow cytometry was used to study the DC phenotype and antigen processing machinery (APM) component expression. ELISPOT and cytotoxicity assays were used to evaluate tumor-reactive cytotoxic T lymphocytes (CTL). IL-12p70 and IL-10 production by DC was measured by Luminex® and DC migration toward CCL21 was tested in transwell migration assays. IRX-2-matured DC functions were compared with those of conv. mix-matured DC. IRX-2-matured DC expressed higher levels (p<0.05) of CD11c, CD40, CCR7 as well as LMP2, TAP1, TAP2 and tapasin than conv. mix-matured DC. IRX-2-matured DC migrated significantly better towards CCL21, produced more IL-12p70 and had a higher IL12p70/IL-10 ratio than conv. mix-matured DC (p<0.05 for all). IRX-2-matured DC carried a higher density of tumor antigen-derived peptides, and CTL primed with these DC mediated higher cytotoxicity against tumor targets (p<0.05) compared to the conv. mix-matured DC. Conclusion: Excellent ability of IRX-2 to induce ex vivo DC maturation in HNSCC patients explains, in part, its clinical benefits and emphasizes its utility in ex vivo maturation of DC generated for therapy. © 2013 Schilling et al

Accurate reconstruction of insertion-deletion histories by statistical phylogenetics

The Multiple Sequence Alignment (MSA) is a computational abstraction that represents a partial summary either of indel history, or of structural similarity. Taking the former view (indel history), it is possible to use formal automata theory to generalize the phylogenetic likelihood framework for finite substitution models (Dayhoff's probability matrices and Felsenstein's pruning algorithm) to arbitrary-length sequences. In this paper, we report results of a simulation-based benchmark of several methods for reconstruction of indel history. The methods tested include a relatively new algorithm for statistical marginalization of MSAs that sums over a stochastically-sampled ensemble of the most probable evolutionary histories. For mammalian evolutionary parameters on several different trees, the single most likely history sampled by our algorithm appears less biased than histories reconstructed by other MSA methods. The algorithm can also be used for alignment-free inference, where the MSA is explicitly summed out of the analysis. As an illustration of our method, we discuss reconstruction of the evolutionary histories of human protein-coding genes.Comment: 28 pages, 15 figures. arXiv admin note: text overlap with arXiv:1103.434

What do we have to know about PD-L1 expression in prostate cancer? A systematic literature review. part 4: Experimental treatments in pre-clinical studies (cell lines and mouse models)

In prostate cancer (PC), the PD-1/PD-L1 axis regulates various signaling pathways and it is influenced by extracellular factors. Pre-clinical experimental studies investigating the effects of various treatments (alone or combined) may discover how to overcome the immunotherapyresistance in PC-patients. We performed a systematic literature review (PRISMA guidelines) to delineate the landscape of pre-clinical studies (including cell lines and mouse models) that tested treatments with effects on PD-L1 signaling in PC. NF-kB, MEK, JAK, or STAT inhibitors on human/mouse, primary/metastatic PC-cell lines variably down-modulated PD-L1-expression, reducing chemoresistance and tumor cell migration. If PC-cells were co-cultured with NK, CD8+ Tcells or CAR-T cells, the immune cell cytotoxicity increased when PD-L1 was downregulated (opposite effects for PD-L1 upregulation). In mouse models, radiotherapy, CDK4/6-inhibitors, and RB deletion induced PD-L1-upregulation, causing PC-immune-evasion. Epigenetic drugs may reduce PD-L1 expression. In some PC experimental models, blocking only the PD-1/PD-L1 pathway had limited efficacy in reducing the tumor growth. Anti-tumor effects could be increased by combining the PD-1/PD-L1 blockade with other approaches (inhibitors of tyrosine kinase, PI3K/mTOR or JAK/STAT3 pathways, p300/CBP; anti-RANKL and/or anti-CTLA-4 antibodies; cytokines; nitroxoline; DNA/cell vaccines; radiotherapy/Radium-223)

What do we have to know about pd-l1 expression in prostate cancer? A systematic literature review. part 1: Focus on immunohistochemical results with discussion of pre-analytical and interpretation variables

Immunotherapy targeting the PD-1–PD-L1 axis yielded good results in treating different immunologically ‘‘hot’’ tumors. A phase II study revealed good therapeutic activity of pembroli-zumab in selected prostatic carcinoma (PC)-patients. We performed a systematic literature review (PRISMA guidelines), which analyzes the immunohistochemical expression of PD-L1 in human PC samples and highlights the pre-analytical and interpretation variables. Interestingly, 29% acinar PCs, 7% ductal PCs, and 46% neuroendocrine carcinomas/tumors were PD-L1+ on immunohisto-chemistry. Different scoring methods or cut-off criteria were applied on variable specimen-types, evaluating tumors showing different clinic-pathologic features. The positivity rate of different PD-L1 antibody clones in tumor cells ranged from 3% (SP142) to 50% (ABM4E54), excluding the single case tested for RM-320. The most tested clone was E1L3N, followed by 22C3 (most used for pem-brolizumab eligibility), SP263, SP142, and 28-8, which gave the positivity rates of 35%, 11–41% (de-pending on different scoring systems), 6%, 3%, and 15%, respectively. Other clones were tested in &lt;200 cases. The PD-L1 positivity rate was usually higher in tumors than benign tissues. It was higher in non-tissue microarray specimens (41–50% vs. 15%), as PC cells frequently showed heterogenous or focal PD-L1-staining. PD-L1 was expressed by immune or stromal cells in 12% and 69% cases, respectively. Tumor heterogeneity, inter-institutional preanalytics, and inter-observer interpretation variability may account for result biases

Low Complexity Regularization of Linear Inverse Problems

Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of $\ell^2$-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem