Using species distribution models to inform IUCN Red List assessments

Characterising a species’ geographical extent is central to many conservation assessments, including those of the IUCN Red List of threatened species. The IUCN recommends that extent of occurrence (EOO) to be quantified by drawing a minimum convex polygon (MCP) around known or inferred presence localities. EOO calculated from verified specimens is commonly used in Red List assessments when other data are scarce, as is the case for many threatened plant species. Yet rarely do these estimates incorporate inferred localities from species distribution models (SDMs). A key impediment stems from uncertainty about how SDM predictions relate to EOO. Here we address this issue by comparing the EOOs estimated from specimen localities with EOOs derived from SDMs for plant species occurring in Costa Rica and Panama. We first analyse 20 plant species, with well-known and well-sampled distributions, and train SDMs to subsamples of the data and assess how well the SDM-derived MCPs predict both the MCPs of the subsamples and the MCPs of the complete dataset. We find that when sample sizes are small (5 or 10 samples) the SDM-derived MCPs are actually closer to the complete dataset than to the MCPs of the subsamples, both in terms of EOO and geographically. This occurs when using a probability threshold based on maximum geographical similarity between the SDM-derived MCP and the subsample MCP; other threshold methods performed less well. For the species with less well-known distributions, the SDM-derived EOOs correlate strongly with, but tend to be larger than, EOOs estimated by point data. This implies that a SDM-derived EOO may be more representative of the full EOO than that drawn around known localities. Our findings reveal situations in which SDMs provide useful information that complements the IUCN Red Listing process.This work is supported by Microsoft Research through its PhD Scholarship Programme.This is the author accepted manuscript. The final version has been published by Elsevier in Biological Conservation and can be found here: http://www.sciencedirect.com/science/article/pii/S0006320714002390

2'-O-(2-methoxyethyl) nucleosides are not phosphorylated or incorporated into the genome of Human Lymphoblastoid TK6 Cells

Nucleoside analogues with 2'-modified sugar moieties are often used to improve the RNA target affinity and nuclease resistance of therapeutic oligonucleotides in preclinical and clinical development. Despite their enhanced nuclease resistance, oligonucleotides could slowly degrade releasing nucleoside analogues that have the potential to become phosphorylated and incorporated into cellular DNA and RNA. For the first time, the phosphorylation and DNA and RNA incorporation of 2'-O-(2-methoxyethyl) (2'-O-MOE) nucleoside analogues have been investigated. Using LC/MS/MS, we showed that enzymes in the nucleotide salvage pathway including deoxycytidine kinase (dCK) and thymidine kinase (TK1) displayed poor reactivity toward 2'-O-MOE nucleoside analogues. On the other hand, 2'-fluoro (F) nucleosides, regardless of the nucleobase, were efficiently phosphorylated to their monophosphate forms by dCK and TK1. Consistent with their efficient phosphorylation by dCK and TK1, 2'-F nucleosides analogues were incorporated into cellular DNA and RNA while no incorporation was detected with 2'-O-MOE nucleoside analogues. In conclusion, these data suggest that the inability of dCK and TK1 to create the monophosphates of 2'-O-MOE nucleoside analogues reduces the risk of their incorporation into cellular DNA and RNA

Clarifying misconceptions of extinction risk assessment with the IUCN Red List

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.The identification of species at risk of extinction is a central goal of conservation. As the use of data compiled for IUCN Red List assessments expands, a number of misconceptions regarding the purpose, application and use of the IUCN Red List categories and criteria have arisen. We outline five such classes of misconception; the most consequential drive proposals for adapted versions of the criteria, rendering assessments among species incomparable. A key challenge for the future will be to recognize the point where understanding has developed so markedly that it is time for the next generation of the Red List criteria. We do not believe we are there yet but, recognizing the need for scrutiny and continued development of Red Listing, conclude by suggesting areas where additional research could be valuable in improving the understanding of extinction risk among species

Targeting tumour re-wiring by triple blockade of mTORC1, epidermal growth factor, and oestrogen receptor signalling pathways in endocrine-resistant breast cancer

Background Endocrine therapies are the mainstay of treatment for oestrogen receptor (ER)-positive (ER+) breast cancer (BC). However, resistance remains problematic largely due to enhanced cross-talk between ER and growth factor pathways, circumventing the need for steroid hormones. Previously, we reported the anti-proliferative effect of everolimus (RAD001-mTORC1 inhibitor) with endocrine therapy in resistance models; however, potential routes of escape from treatment via ERBB2/3 signalling were observed. We hypothesised that combined targeting of three cellular nodes (ER, ERBB, and mTORC1) may provide enhanced long-term clinical utility. Methods A panel of ER+ BC cell lines adapted to long-term oestrogen deprivation (LTED) and expressing ESR1wt or ESR1Y537S, modelling acquired resistance to an aromatase-inhibitor (AI), were treated in vitro with a combination of RAD001 and neratinib (pan-ERBB inhibitor) in the presence or absence of oestradiol (E2), tamoxifen (4-OHT), or fulvestrant (ICI182780). End points included proliferation, cell signalling, cell cycle, and effect on ER-mediated transactivation. An in-vivo model of AI resistance was treated with monotherapies and combinations to assess the efficacy in delaying tumour progression. RNA-seq analysis was performed to identify changes in global gene expression as a result of the indicated therapies. Results Here, we show RAD001 and neratinib (pan-ERBB inhibitor) caused a concentration-dependent decrease in proliferation, irrespective of the ESR1 mutation status. The combination of either agent with endocrine therapy further reduced proliferation but the maximum effect was observed with a triple combination of RAD001, neratinib, and endocrine therapy. In the absence of oestrogen, RAD001 caused a reduction in ER-mediated transcription in the majority of the cell lines, which associated with a decrease in recruitment of ER to an oestrogen-response element on the TFF1 promoter. Contrastingly, neratinib increased both ER-mediated transactivation and ER recruitment, an effect reduced by the addition of RAD001. In-vivo analysis of an LTED model showed the triple combination of RAD001, neratinib, and fulvestrant was most effective at reducing tumour volume. Gene set enrichment analysis revealed that the addition of neratinib negated the epidermal growth factor (EGF)/EGF receptor feedback loops associated with RAD001. Conclusions Our data support the combination of therapies targeting ERBB2/3 and mTORC1 signalling, together with fulvestrant, in patients who relapse on endocrine therapy and retain a functional ER

Green Plants in the Red: A Baseline Global Assessment for the IUCN Sampled Red List Index for Plants

Plants provide fundamental support systems for life on Earth and are the basis for all terrestrial ecosystems; a decline in plant diversity will be detrimental to all other groups of organisms including humans. Decline in plant diversity has been hard to quantify, due to the huge numbers of known and yet to be discovered species and the lack of an adequate baseline assessment of extinction risk against which to track changes. The biodiversity of many remote parts of the world remains poorly known, and the rate of new assessments of extinction risk for individual plant species approximates the rate at which new plant species are described. Thus the question ‘How threatened are plants?’ is still very difficult to answer accurately. While completing assessments for each species of plant remains a distant prospect, by assessing a randomly selected sample of species the Sampled Red List Index for Plants gives, for the first time, an accurate view of how threatened plants are across the world. It represents the first key phase of ongoing efforts to monitor the status of the world’s plants. More than 20% of plant species assessed are threatened with extinction, and the habitat with the most threatened species is overwhelmingly tropical rain forest, where the greatest threat to plants is anthropogenic habitat conversion, for arable and livestock agriculture, and harvesting of natural resources. Gymnosperms (e.g. conifers and cycads) are the most threatened group, while a third of plant species included in this study have yet to receive an assessment or are so poorly known that we cannot yet ascertain whether they are threatened or not. This study provides a baseline assessment from which trends in the status of plant biodiversity can be measured and periodically reassessed

Ty1 integrase overexpression leads to integration of non-Ty1 DNA fragments into the genome of Saccharomyces cerevisiae

The integrase of the Saccharomyces cerevisiae retrotransposon Ty1 integrates Ty1 cDNA into genomic DNA likely via a transesterification reaction. Little is known about the mechanisms ensuring that integrase does not integrate non-Ty DNA fragments. In an effort to elucidate the conditions under which Ty1 integrase accepts non-Ty DNA as substrate, PCR fragments encompassing a selectable marker gene were transformed into yeast strains overexpressing Ty1 integrase. These fragments do not exhibit similarity to Ty1 cDNA except for the presence of the conserved terminal dinucleotide 5′-TG-CA-3′. The frequency of fragment insertion events increased upon integrase overexpression. Characterization of insertion events by genomic sequencing revealed that most insertion events exhibited clear hallmarks of integrase-mediated reactions, such as 5 bp target site duplication and target site preferences. Alteration of the terminal dinucleotide abolished the suitability of the PCR fragments to serve as substrates. We hypothesize that substrate specificity under normal conditions is mainly due to compartmentalization of integrase and Ty cDNA, which meet in virus-like particles. In contrast, recombinant integrase, which is not confined to virus-like particles, is able to accept non-Ty DNA, provided that it terminates in the proper dinucleotide sequence

Methodological issues in cross-cultural research

Regardless of whether the research goal is to establish cultural universals or to identify and explain cross-cultural differences, researchers need measures that are comparable across different cultures when conducting cross-cultural studies. In this chapter, we describe two major strategies for enhancing cross-cultural comparability. First, we discuss a priori methods to ensure the comparability of data in cross-cultural surveys. In particular, we review findings on cross-cultural differences based on the psychology of survey response and provide suggestions on how to deal with these cultural differences in the survey design stage. Second, we discuss post hoc methods to ascertain data comparability and enable comparisons in the presence of threats to equivalence

TDAG51 is an ERK signaling target that opposes ERK-mediated HME16C mammary epithelial cell transformation

<p>Abstract</p> <p>Introduction</p> <p>Signaling downstream of Ras is mediated by three major pathways, Raf/ERK, phosphatidylinositol 3 kinase (PI3K), and Ral guanine nucleotide exchange factor (RalGEF). Ras signal transduction pathways play an important role in breast cancer progression, as evidenced by the frequent over-expression of the Ras-activating epidermal growth factor receptors EGFR and ErbB2. Here we investigated which signal transduction pathways downstream of Ras contribute to EGFR-dependent transformation of telomerase-immortalized mammary epithelial cells HME16C. Furthermore, we examined whether a highly transcriptionally regulated ERK pathway target, PHLDA1 (TDAG51), suggested to be a tumor suppressor in breast cancer and melanoma, might modulate the transformation process.</p> <p>Methods</p> <p>Cellular transformation of human mammary epithelial cells by downstream Ras signal transduction pathways was examined using anchorage-independent growth assays in the presence and absence of EGFR inhibition. TDAG51 protein expression was down-regulated by interfering small hairpin RNA (shRNA), and the effects on cell proliferation and death were examined in Ras pathway-transformed breast epithelial cells.</p> <p>Results</p> <p>Activation of both the ERK and PI3K signaling pathways was sufficient to induce cellular transformation, which was accompanied by up-regulation of EGFR ligands, suggesting autocrine EGFR stimulation during the transformation process. Only activation of the ERK pathway was sufficient to transform cells in the presence of EGFR inhibition and was sufficient for tumorigenesis in xenografts. Up-regulation of the PHLDA1 gene product, TDAG51, was found to correlate with persistent ERK activation and anchorage-independent growth in the absence or presence of EGFR inhibition. Knockdown of this putative breast cancer tumor-suppressor gene resulted in increased ERK pathway activation and enhanced matrix-detached cellular proliferation of Ras/Raf transformed cells.</p> <p>Conclusion</p> <p>Our results suggest that multiple Ras signal transduction pathways contribute to mammary epithelial cell transformation, but that the ERK signaling pathway may be a crucial component downstream of EGFR activation during tumorigenesis. Furthermore, persistent activation of ERK signaling up-regulates TDAG51. This event serves as a negative regulator of both Erk activation as well as matrix-detached cellular proliferation and suggests that TDAG51 opposes ERK-mediated transformation in breast epithelial cells.</p

High Chromosome Number in hematological cancer cell lines is a Negative Predictor of Response to the inhibition of Aurora B and C by GSK1070916

<p>Abstract</p> <p>Background</p> <p>Aurora kinases play critical roles in mitosis and are being evaluated as therapeutic targets in cancer. GSK1070916 is a potent, selective, ATP competitive inhibitor of Aurora kinase B and C. Translation of predictive biomarkers to the clinic can benefit patients by identifying the tumors that are more likely to respond to therapies, especially novel inhibitors such as GSK1070916.</p> <p>Methods</p> <p>59 Hematological cancer-derived cell lines were used as models for response where <it>in vitro </it>sensitivity to GSK1070916 was based on both time and degree of cell death. The response data was analyzed along with karyotype, transcriptomics and somatic mutation profiles to determine predictors of response.</p> <p>Results</p> <p>20 cell lines were sensitive and 39 were resistant to treatment with GSK1070916. High chromosome number was more prevalent in resistant cell lines (p-value = 0.0098, Fisher Exact Test). Greater resistance was also found in cell lines harboring polyploid subpopulations (p-value = 0.00014, Unpaired t-test). A review of NOTCH1 mutations in T-ALL cell lines showed an association between NOTCH1 mutation status and chromosome number (p-value = 0.0066, Fisher Exact Test).</p> <p>Conclusions</p> <p>High chromosome number associated with resistance to the inhibition of Aurora B and C suggests cells with a mechanism to bypass the high ploidy checkpoint are resistant to GSK1070916. High chromosome number, a hallmark trait of many late stage hematological malignancies, varies in prevalence among hematological malignancy subtypes. The high frequency and relative ease of measurement make high chromosome number a viable negative predictive marker for GSK1070916.</p

'Omic approaches to preventing or managing metastatic breast cancer

Early detection of metastasis-prone breast cancers and characterization of residual metastatic cancers are important in efforts to improve management of breast cancer. Applications of genome-scale molecular analysis technologies are making these complementary approaches possible by revealing molecular features uniquely associated with metastatic disease. Assays that reveal these molecular features will facilitate development of anatomic, histological and blood-based strategies that may enable detection prior to metastatic spread. Knowledge of these features also will guide development of therapeutic strategies that can be applied when metastatic disease burden is low, thereby increasing the probability of a curative response