Scan statistics analysis of forest fire clusters

Spatio-temporal clusters in 1997?2003 fire sequences of Tuscany region (central Italy) have been identified and analysed by using the scan statistic, a method which was devised to evidence clusters in epidemiology. Results showed that the method is reliable to find clusters of events and to evaluate their significance via Monte Carlo replication. The evaluation of the presence of spatial and temporal patterns in fire occurrence and their significance could have a great impact in forthcoming studies on fire occurrences prediction.

Cardiac expression of ms1/STARS, a novel gene involved in cardiac development and disease, is regulated by GATA4.

Ms1/STARS is a novel muscle-specific actin-binding protein that specifically modulates the myocardin-related transcription factor (MRTF)-serum response factor (SRF) regulatory axis within striated muscle. This ms1/STARS-dependent regulatory axis is of central importance within the cardiac gene regulatory network and has been implicated in cardiac development and postnatal cardiac function/homeostasis. The dysregulation of ms1/STARS is associated with and causative of pathological cardiac phenotypes, including cardiac hypertrophy and cardiomyopathy. In order to gain an understanding of the mechanisms governing ms1/STARS expression in the heart, we have coupled a comparative genomic in silico analysis with reporter, gain-of-function, and loss-of-function approaches. Through this integrated analysis, we have identified three evolutionarily conserved regions (ECRs), α, SINA, and DINA, that act as cis-regulatory modules and confer differential cardiac cell-specific activity. Two of these ECRs, α and DINA, displayed distinct regulatory sensitivity to the core cardiac transcription factor GATA4. Overall, our results demonstrate that within embryonic, neonatal, and adult hearts, GATA4 represses ms1/STARS expression with the pathologically associated depletion of GATA4 (type 1/type 2 diabetic models), resulting in ms1/STARS upregulation. This GATA4-dependent repression of ms1/STARS expression has major implications for MRTF-SRF signaling in the context of cardiac development and disease.

Qualité des données fournies par la statistique médicale VESKA: le cas de la fracture du fémur proximal. [Quality of data provided by VESKA medical statistics: the case of the fractured proximal femur].

Within the framework of a retrospective study of the incidence of hip fractures in the canton of Vaud (Switzerland), all cases of hip fracture occurring among the resident population in 1986 and treated in the hospitals of the canton were identified from among five different information sources. Relevant data were then extracted from the medical records. At least two sources of information were used to identify cases in each hospital, among them the statistics of the Swiss Hospital Association (VESKA). These statistics were available for 9 of the 18 hospitals in the canton that participated in the study. The number of cases identified from the VESKA statistics was compared to the total number of cases for each hospital. For the 9 hospitals the number of cases in the VESKA statistics was 407, whereas, after having excluded diagnoses that were actually "status after fracture" and double entries, the total for these hospitals was 392, that is 4% less than the VESKA statistics indicate. It is concluded that the VESKA statistics provide a good approximation of the actual number of cases treated in these hospitals, with a tendency to overestimate this number. In order to use these statistics for calculating incidence figures, however, it is imperative that a greater proportion of all hospitals (50% presently in the canton, 35% nationwide) participate in these statistics.

Forest fires cluster detection with space-time scan statistics

Forest fires are defined as uncontrolled fires often occurring in wildland areas, but that can also affect houses or agricultural resources. Causes are both natural (e.g.,lightning phenomena) and anthropogenic (human negligence or arsons).Major environmental factors influencing the fire ignition and propagation are climate and vegetation. Wildfires are most common and severe during drought period and on windy days. Moreover, under water-stress conditions, which occur after a long hot and dry period, the vegetation is more vulnerable to fire. These conditions are common in the United State and Canada, where forest fires represent a big problem. We focused our analysis on the state of Florida, for which a big dataset on forest fires detection is readily available. USDA Forest Service Remote Sensing Application Center, in collaboration with NASA-Goddard Space Flight Center and the University of Maryland, has compiled daily MODIS Thermal Anomalies (fires and biomass burning images) produced by NASA using a contextual algorithm that exploits the strong emission of mid-infrared radiation from fires. Fire classes were converted in GIS format: daily MODIS fire detections are provided as the centroids of the 1 kilometer pixels and compiled into daily Arc/INFO point coverage.