Geographical Distribution Of The Association Between El Niño South Oscillation And Dengue Fever In The Americas: A Continental Analysis Using Geographical Information System-based Techniques.

El Niño South Oscillation (ENSO) is one climatic phenomenon related to the inter-annual variability of global meteorological patterns influencing sea surface temperature and rainfall variability. It influences human health indirectly through extreme temperature and moisture conditions that may accelerate the spread of some vector-borne viral diseases, like dengue fever (DF). This work examines the spatial distribution of association between ENSO and DF in the countries of the Americas during 1995-2004, which includes the 1997-1998 El Niño, one of the most important climatic events of 20(th) century. Data regarding the South Oscillation index (SOI), indicating El Niño-La Niña activity, were obtained from Australian Bureau of Meteorology. The annual DF incidence (AIy) by country was computed using Pan-American Health Association data. SOI and AIy values were standardised as deviations from the mean and plotted in bars-line graphics. The regression coefficient values between SOI and AIy (rSOI,AI) were calculated and spatially interpolated by an inverse distance weighted algorithm. The results indicate that among the five years registering high number of cases (1998, 2002, 2001, 2003 and 1997), four had El Niño activity. In the southern hemisphere, the annual spatial weighted mean centre of epidemics moved southward, from 6° 31' S in 1995 to 21° 12' S in 1999 and the rSOI,AI values were negative in Cuba, Belize, Guyana and Costa Rica, indicating a synchrony between higher DF incidence rates and a higher El Niño activity. The rSOI,AI map allows visualisation of a graded surface with higher values of ENSO-DF associations for Mexico, Central America, northern Caribbean islands and the extreme north-northwest of South America.

Toxicity Of Fungal-generated Silver Nanoparticles To Soil-inhabiting Pseudomonas Putida Kt2440, A Rhizospheric Bacterium Responsible For Plant Protection And Bioremediation.

Silver nanoparticles have attracted considerable attention due to their beneficial properties. But toxicity issues associated with them are also rising. The reports in the past suggested health hazards of silver nanoparticles at the cellular, molecular, or whole organismal level in eukaryotes. Whereas, there is also need to examine the exposure effects of silver nanoparticle to the microbes, which are beneficial to humans as well as environment. The available literature suggests the harmful effects of physically and chemically synthesised silver nanoparticles. The toxicity of biogenically synthesized nanoparticles has been less studied than physically and chemically synthesised nanoparticles. Hence, there is a greater need to study the toxic effects of biologically synthesised silver nanoparticles in general and mycosynthesized nanoparticles in particular. In the present study, attempts have been made to assess the risk associated with the exposure of mycosynthesized silver nanoparticles on a beneficial soil microbe Pseudomonas putida. KT2440. The study demonstrates mycosynthesis of silver nanoparticles and their characterisation by UV-vis spectrophotometry, FTIR, X-ray diffraction, nanosight LM20 - a particle size distribution analyzer and TEM. Silver nanoparticles obtained herein were found to exert the hazardous effect at the concentration of 0.4μg/ml, which warrants further detailed investigations concerning toxicity.

Is size structure a good measure of future trends of plant populations? an empirical approach using five woody species from the Cerrado (Brazilian savanna)

Size distributions in woody plant populations have been used to assess their regeneration status, assuming that size structures with reverse-J shapes represent stable populations. We present an empirical approach of this issue using five woody species from the Cerrado. Considering count data for all plants of these five species over a 12-year period, we analyzed size distribution by: a) plotting frequency distributions and their adjustment to the negative exponential curve and b) calculating the Gini coefficient. To look for a relationship between size structure and future trends, we considered the size structures from the first census year. We analyzed changes in number over time and performed a simple population viability analysis, which gives the mean population growth rate, its variance and the probability of extinction in a given time period. Frequency distributions and the Gini coefficient were not able to predict future trends in population numbers. We recommend that managers should not use measures of size structure as a basis for management decisions without applying more appropriate demographic studies.