Characterization of prostate cancer detected at repeat biopsy

Research articl

Genome-wide study of association and interaction with maternal cytomegalovirus infection suggests new schizophrenia loci.

Genetic and environmental components as well as their interaction contribute to the risk of schizophrenia, making it highly relevant to include environmental factors in genetic studies of schizophrenia. This study comprises genome-wide association (GWA) and follow-up analyses of all individuals born in Denmark since 1981 and diagnosed with schizophrenia as well as controls from the same birth cohort. Furthermore, we present the first genome-wide interaction survey of single nucleotide polymorphisms (SNPs) and maternal cytomegalovirus (CMV) infection. The GWA analysis included 888 cases and 882 controls, and the follow-up investigation of the top GWA results was performed in independent Danish (1396 cases and 1803 controls) and German-Dutch (1169 cases, 3714 controls) samples. The SNPs most strongly associated in the single-marker analysis of the combined Danish samples were rs4757144 in ARNTL (P=3.78 × 10(-6)) and rs8057927 in CDH13 (P=1.39 × 10(-5)). Both genes have previously been linked to schizophrenia or other psychiatric disorders. The strongest associated SNP in the combined analysis, including Danish and German-Dutch samples, was rs12922317 in RUNDC2A (P=9.04 × 10(-7)). A region-based analysis summarizing independent signals in segments of 100 kb identified a new region-based genome-wide significant locus overlapping the gene ZEB1 (P=7.0 × 10(-7)). This signal was replicated in the follow-up analysis (P=2.3 × 10(-2)). Significant interaction with maternal CMV infection was found for rs7902091 (P(SNP × CMV)=7.3 × 10(-7)) in CTNNA3, a gene not previously implicated in schizophrenia, stressing the importance of including environmental factors in genetic studies

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

Exploring Definitions and Predictors of Severe Asthma Clinical Remission Post-Biologic in Adults.

RATIONALE: There is no consensus on criteria to include in an asthma remission definition in real-life. Factors associated with achieving remission post-biologic-initiation remain poorly understood. OBJECTIVES: To quantify the proportion of adults with severe asthma achieving multi-domain-defined remission post-biologic-initiation and identify pre-biologic characteristics associated with achieving remission which may be used to predict it. METHODS: This was a longitudinal cohort study using data from 23 countries from the International Severe Asthma Registry. Four asthma outcome domains were assessed in the 1-year pre- and post-biologic-initiation. A priori-defined remission cut-offs were: 0 exacerbations/year, no long-term oral corticosteroid (LTOCS), partly/well-controlled asthma, and percent predicted forced expiratory volume in one second ≥80%. Remission was defined using 2 (exacerbations + LTOCS), 3 (+control or +lung function) and 4 of these domains. The association between pre-biologic characteristics and post-biologic remission was assessed by multivariable analysis. MEASUREMENTS AND MAIN RESULTS: 50.2%, 33.5%, 25.8% and 20.3% of patients met criteria for 2, 3 (+control), 3 (+lung function) and 4-domain-remission, respectively. The odds of achieving 4-domain remission decreased by 15% for every additional 10-years asthma duration (odds ratio: 0.85; 95% CI: 0.73, 1.00). The odds of remission increased in those with fewer exacerbations/year, lower LTOCS daily dose, better control and better lung function pre-biologic-initiation. CONCLUSIONS: One in 5 patients achieved 4-domain remission within 1-year of biologic-initiation. Patients with less severe impairment and shorter asthma duration at initiation had a greater chance of achieving remission post-biologic, indicating that biologic treatment should not be delayed if remission is the goal. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Alien Invasive Slider Turtle in Unpredicted Habitat: A Matter of Niche Shift or of Predictors Studied?

BACKGROUND: Species Distribution Models (SDMs) aim on the characterization of a species' ecological niche and project it into geographic space. The result is a map of the species' potential distribution, which is, for instance, helpful to predict the capability of alien invasive species. With regard to alien invasive species, recently several authors observed a mismatch between potential distributions of native and invasive ranges derived from SDMs and, as an explanation, ecological niche shift during biological invasion has been suggested. We studied the physiologically well known Slider turtle from North America which today is widely distributed over the globe and address the issue of ecological niche shift versus choice of ecological predictors used for model building, i.e., by deriving SDMs using multiple sets of climatic predictor. PRINCIPAL FINDINGS: In one SDM, predictors were used aiming to mirror the physiological limits of the Slider turtle. It was compared to numerous other models based on various sets of ecological predictors or predictors aiming at comprehensiveness. The SDM focusing on the study species' physiological limits depicts the target species' worldwide potential distribution better than any of the other approaches. CONCLUSION: These results suggest that a natural history-driven understanding is crucial in developing statistical models of ecological niches (as SDMs) while "comprehensive" or "standard" sets of ecological predictors may be of limited use

The bone morphogenetic protein antagonist gremlin 1 is overexpressed in human cancers and interacts with YWHAH protein

BACKGROUND: Basic studies of oncogenesis have demonstrated that either the elevated production of particular oncogene proteins or the occurrence of qualitative abnormalities in oncogenes can contribute to neoplastic cellular transformation. The purpose of our study was to identify an unique gene that shows cancer-associated expression, and characterizes its function related to human carcinogenesis. METHODS: We used the differential display (DD) RT-PCR method using normal cervical, cervical cancer, metastatic cervical tissues, and cervical cancer cell lines to identify genes overexpressed in cervical cancers and identified gremlin 1 which was overexpressed in cervical cancers. We determined expression levels of gremlin 1 using Northern blot analysis and immunohistochemical study in various types of human normal and cancer tissues. To understand the tumorigenesis pathway of identified gremlin 1 protein, we performed a yeast two-hybrid screen, GST pull down assay, and immunoprecipitation to identify gremlin 1 interacting proteins. RESULTS: DDRT-PCR analysis revealed that gremlin 1 was overexpressed in uterine cervical cancer. We also identified a human gremlin 1 that was overexpressed in various human tumors including carcinomas of the lung, ovary, kidney, breast, colon, pancreas, and sarcoma. PIG-2-transfected HEK 293 cells exhibited growth stimulation and increased telomerase activity. Gremlin 1 interacted with homo sapiens tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, eta polypeptide (14-3-3 eta; YWHAH). YWHAH protein binding site for gremlin 1 was located between residues 61–80 and gremlin 1 binding site for YWHAH was found to be located between residues 1 to 67. CONCLUSION: Gremlin 1 may play an oncogenic role especially in carcinomas of the uterine cervix, lung, ovary, kidney, breast, colon, pancreas, and sarcoma. Over-expressed gremlin 1 functions by interaction with YWHAH. Therefore, Gremlin 1 and its binding protein YWHAH could be good targets for developing diagnostic and therapeutic strategies against human cancers

Site-Specific Bioconjugation of a Murine Dihydrofolate Reductase Enzyme by Copper(I)-Catalyzed Azide-Alkyne Cycloaddition with Retained Activity

Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC) is an efficient reaction linking an azido and an alkynyl group in the presence of copper catalyst. Incorporation of a non-natural amino acid (NAA) containing either an azido or an alkynyl group into a protein allows site-specific bioconjugation in mild conditions via CuAAC. Despite its great potential, bioconjugation of an enzyme has been hampered by several issues including low yield, poor solubility of a ligand, and protein structural/functional perturbation by CuAAC components. In the present study, we incorporated an alkyne-bearing NAA into an enzyme, murine dihydrofolate reductase (mDHFR), in high cell density cultivation of Escherichia coli, and performed CuAAC conjugation with fluorescent azide dyes to evaluate enzyme compatibility of various CuAAC conditions comprising combination of commercially available Cu(I)-chelating ligands and reductants. The condensed culture improves the protein yield 19-fold based on the same amount of non-natural amino acid, and the enzyme incubation under the optimized reaction condition did not lead to any activity loss but allowed a fast and high-yield bioconjugation. Using the established conditions, a biotin-azide spacer was efficiently conjugated to mDHFR with retained activity leading to the site-specific immobilization of the biotin-conjugated mDHFR on a streptavidin-coated plate. These results demonstrate that the combination of reactive non-natural amino acid incorporation and the optimized CuAAC can be used to bioconjugate enzymes with retained enzymatic activityope

Comparative effectiveness of Anti-IL5 and Anti-IgE biologic classes in patients with severe asthma eligible for both.

BACKGROUND: Patients with severe asthma may present with characteristics representing overlapping phenotypes, making them eligible for more than one class of biologic. Our aim was to describe the profile of adult patients with severe asthma eligible for both anti-IgE and anti-IL5/5R and to compare the effectiveness of both classes of treatment in real life. METHODS: This was a prospective cohort study that included adult patients with severe asthma from 22 countries enrolled into the International Severe Asthma registry (ISAR) who were eligible for both anti-IgE and anti-IL5/5R. The effectiveness of anti-IgE and anti-IL5/5R was compared in a 1:1 matched cohort. Exacerbation rate was the primary effectiveness endpoint. Secondary endpoints included long-term-oral corticosteroid (LTOCS) use, asthma-related emergency room (ER) attendance, and hospital admissions. RESULTS: In the matched analysis (n = 350/group), the mean annualized exacerbation rate decreased by 47.1% in the anti-IL5/5R group and 38.7% in the anti-IgE group. Patients treated with anti-IL5/5R were less likely to experience a future exacerbation (adjusted IRR 0.76; 95% CI 0.64, 0.89; p < 0.001) and experienced a greater reduction in mean LTOCS dose than those treated with anti-IgE (37.44% vs. 20.55% reduction; p = 0.023). There was some evidence to suggest that patients treated with anti-IL5/5R experienced fewer asthma-related hospitalizations (IRR 0.64; 95% CI 0.38, 1.08), but not ER visits (IRR 0.94, 95% CI 0.61, 1.43). CONCLUSIONS: In real life, both anti-IgE and anti-IL5/5R improve asthma outcomes in patients eligible for both biologic classes; however, anti-IL5/5R was superior in terms of reducing asthma exacerbations and LTOCS use

Effects of the Training Dataset Characteristics on the Performance of Nine Species Distribution Models: Application to Diabrotica virgifera virgifera

Many distribution models developed to predict the presence/absence of invasive alien species need to be fitted to a training dataset before practical use. The training dataset is characterized by the number of recorded presences/absences and by their geographical locations. The aim of this paper is to study the effect of the training dataset characteristics on model performance and to compare the relative importance of three factors influencing model predictive capability; size of training dataset, stage of the biological invasion, and choice of input variables. Nine models were assessed for their ability to predict the distribution of the western corn rootworm, Diabrotica virgifera virgifera, a major pest of corn in North America that has recently invaded Europe. Twenty-six training datasets of various sizes (from 10 to 428 presence records) corresponding to two different stages of invasion (1955 and 1980) and three sets of input bioclimatic variables (19 variables, six variables selected using information on insect biology, and three linear combinations of 19 variables derived from Principal Component Analysis) were considered. The models were fitted to each training dataset in turn and their performance was assessed using independent data from North America and Europe. The models were ranked according to the area under the Receiver Operating Characteristic curve and the likelihood ratio. Model performance was highly sensitive to the geographical area used for calibration; most of the models performed poorly when fitted to a restricted area corresponding to an early stage of the invasion. Our results also showed that Principal Component Analysis was useful in reducing the number of model input variables for the models that performed poorly with 19 input variables. DOMAIN, Environmental Distance, MAXENT, and Envelope Score were the most accurate models but all the models tested in this study led to a substantial rate of mis-classification