The association of cold weather and all-cause and cause-specific mortality in the island of Ireland between 1984 and 2007

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.This article has been made available through the Brunel Open Access Publishing Fund.Background This study aimed to assess the relationship between cold temperature and daily mortality in the Republic of Ireland (ROI) and Northern Ireland (NI), and to explore any differences in the population responses between the two jurisdictions. Methods A time-stratified case-crossover approach was used to examine this relationship in two adult national populations, between 1984 and 2007. Daily mortality risk was examined in association with exposure to daily maximum temperatures on the same day and up to 6 weeks preceding death, during the winter (December-February) and cold period (October-March), using distributed lag models. Model stratification by age and gender assessed for modification of the cold weather-mortality relationship. Results In the ROI, the impact of cold weather in winter persisted up to 35 days, with a cumulative mortality increase for all-causes of 6.4% (95%CI=4.8%-7.9%) in relation to every 1oC drop in daily maximum temperature, similar increases for cardiovascular disease (CVD) and stroke, and twice as much for respiratory causes. In NI, these associations were less pronounced for CVD causes, and overall extended up to 28 days. Effects of cold weather on mortality increased with age in both jurisdictions, and some suggestive gender differences were observed. Conclusions The study findings indicated strong cold weather-mortality associations in the island of Ireland; these effects were less persistent, and for CVD mortality, smaller in NI than in the ROI. Together with suggestive differences in associations by age and gender between the two Irish jurisdictions, the findings suggest potential contribution of underlying societal differences, and require further exploration. The evidence provided here will hope to contribute to the current efforts to modify fuel policy and reduce winter mortality in Ireland

miR-17* Suppresses Tumorigenicity of Prostate Cancer by Inhibiting Mitochondrial Antioxidant Enzymes

Aberrant micro RNA (miRNA) expression has been implicated in the pathogenesis of cancer. Recent studies have shown that the miR-17-92 cluster is overexpressed in many types of cancer. The oncogenic function of mature miRNAs encoded by the miR-17–92 cluster has been identified from the 5′ arm of six precursors. However, the function of the miRNAs produced from the 3′ arm of these precursors remains unknown. The present study demonstrates that miR-17* is able to suppress critical primary mitochondrial antioxidant enzymes, such as manganese superoxide dismutase (MnSOD), glutathione peroxidase-2 (GPX2) and thioredoxin reductase-2 (TrxR2). Transfection of miR-17* into prostate cancer PC-3 cells significantly reduces levels of the three antioxidant proteins and activity of the luciferase reporter under the control of miR-17* binding sequences located in the 3′-untranslated regions of the three target genes. Disulfiram (DSF), a dithiolcarbomate drug shown to have an anticancer effect, induces the level of mature miR-17* and cell death in PCa cells, which can be attenuated by transfection of antisense miR-17*. Increasing miR-17* level in PC-3 cells by a Tet-on based conditional expression system markedly suppresses its tumorigencity. These results suggest that miR-17* may suppress tumorigenicity of prostate cancer through inhibition of mitochondrial antioxidant enzymes

Effects of apparent temperature on daily mortality in Lisbon and Oporto, Portugal

<p>Abstract</p> <p>Background</p> <p>Evidence that elevated temperatures can lead to increased mortality is well documented, with population vulnerability being location specific. However, very few studies have been conducted that assess the effects of temperature on daily mortality in urban areas in Portugal.</p> <p>Methods</p> <p>In this paper time-series analysis was used to model the relationship between mean apparent temperature and daily mortality during the warm season (April to September) in the two largest urban areas in Portugal: Lisbon and Oporto. We used generalized additive Poisson regression models, adjusted for day of week and season.</p> <p>Results</p> <p>Our results show that in Lisbon, a 1°C increase in mean apparent temperature is associated with a 2.1% (95%CI: 1.6, 2.5), 2.4% (95%CI: 1.7, 3.1) and 1.7% (95%CI: 0.1, 3.4) increase in all-causes, cardiovascular, and respiratory mortality, respectively. In Oporto the increase was 1.5% (95%CI: 1.0, 1.9), 2.1% (95%CI: 1.3, 2.9) and 2.7% (95%CI: 1.2, 4.3) respectively. In both cities, this increase was greater for the group >65 years.</p> <p>Conclusion</p> <p>Even without extremes in apparent temperature, we observed an association between temperature and daily mortality in Portugal. Additional research is needed to allow for better assessment of vulnerability within populations in Portugal in order to develop more effective heat-related morbidity and mortality public health programs.</p

Guidelines for Modeling and Reporting Health Effects of Climate Change Mitigation Actions

Background: Modeling suggests that climate change mitigation actions can have substantial human health benefits that accrue quickly and locally. Documenting the benefits can help drive more ambitious and health-protective climate change mitigation actions; however, documenting the adverse health effects can help to avoid them. Estimating the health effects of mitigation (HEM) actions can help policy makers prioritize investments based not only on mitigation potential but also on expected health benefits. To date, however, the wide range of incompatible approaches taken to developing and reporting HEM estimates has limited their comparability and usefulness to policymakers. Objective: The objective of this effort was to generate guidance for modeling studies on scoping, estimating, and reporting population health effects from climate change mitigation actions. Methods: An expert panel of HEM researchers was recruited to participate in developing guidance for conducting HEM studies. The primary literature and a synthesis of HEM studies were provided to the panel. Panel members then participated in a modified Delphi exercise to identify areas of consensus regarding HEM estimation. Finally, the panel met to review and discuss consensus findings, resolve remaining differences, and generate guidance regarding conducting HEM studies. Results: The panel generated a checklist of recommendations regarding stakeholder engagement: HEM modeling, including model structure, scope and scale, demographics, time horizons, counterfactuals, health response functions, and metrics; parameterization and reporting; approaches to uncertainty and sensitivity analysis; accounting for policy uptake; and discounting. Discussion: This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers. Harmonization of HEM estimates has the potential to lead to advances in and improved synthesis of policy-relevant research that can inform evidence-based decision making and practice

Expression-Based In Silico Screening of Candidate Therapeutic Compounds for Lung Adenocarcinoma

BACKGROUND:Lung adenocarcinom (AC) is the most common form of lung cancer. Currently, the number of medical options to deal with lung cancer is very limited. In this study, we aimed to investigate potential therapeutic compounds for lung adenocarcinoma based on integrative analysis. METHODOLOGY/PRINCIPAL FINDINGS:The candidate therapeutic compounds were identified in a two-step process. First, a meta-analysis of two published microarray data was conducted to obtain a list of 343 differentially expressed genes specific to lung AC. In the next step, expression profiles of these genes were used to query the Connectivity-Map (C-MAP) database to identify a list of compounds whose treatment reverse expression direction in various cancer cells. Several compounds in the categories of HSP90 inhibitor, HDAC inhibitor, PPAR agonist, PI3K inhibitor, passed our screening to be the leading candidates. On top of the list, three HSP90 inhibitors, i.e. 17-AAG (also known as tanespimycin), monorden, and alvespimycin, showed significant negative enrichment scores. Cytotoxicity as well as effects on cell cycle regulation and apoptosis were evaluated experimentally in lung adenocarcinoma cell line (A549 or GLC-82) with or without treatment with 17-AAG. In vitro study demonstrated that 17-AAG alone or in combination with cisplatin (DDP) can significantly inhibit lung adenocarcinoma cell growth by inducing cell cycle arrest and apoptosis. CONCLUSIONS/SIGNIFICANCE:We have used an in silico screening to identify compounds for treating lung cancer. One such compound 17-AAG demonstrated its anti-lung AC activity by inhibiting cell growth and promoting apoptosis and cell cycle arrest

Multicentre prospective phase II trial of gefitinib for advanced non-small cell lung cancer with epidermal growth factor receptor mutations: results of the West Japan Thoracic Oncology Group trial (WJTOG0403)

The purpose of this study was to evaluate the efficacy of gefitinib and the feasibility of screening for epidermal growth factor receptor (EGFR) mutations among select patients with advanced non-small cell lung cancer (NSCLC). Stage IIIB/IV NSCLC, chemotherapy-naive patients or patients with recurrences after up to two prior chemotherapy regimens were eligible. Direct sequencing using DNA from tumour specimens was performed by a central laboratory to detect EGFR mutations. Patients harbouring EGFR mutations received gefitinib. The primary study objective was response; the secondary objectives were toxicity, overall survival (OS), progression-free survival (PFS), 1-year survival (1Y-S) and the disease control rate (DCR). Between March 2005 and January 2006, 118 patients were recruited from 15 institutions and were screened for EGFR mutations, which were detected in 32 patients – 28 of whom were enrolled in the present study. The overall response rate was 75%, the DCR was 96% and the median PFS was 11.5 months. The median OS has not yet been reached, and the 1Y-S was 79%. Thus, gefitinib chemotherapy in patients with advanced NSCLC harbouring EGFR mutations was highly effective. This trial documents the feasibility of performing a multicentre phase II study using a central typing laboratory, demonstrating the benefit to patients of selecting gefitinib treatment based on their EGFR mutation status