Role of amniotic fluid interphase fluorescence in situ hybridization (FISH) analysis in patient management

We retrospectively reviewed 309 amniotic fluid interphase fluorescence in situ hybridization (FISH) analyses performed from October 1995 to June 1999 to assess the role of interphase FISH in the management of patients at increased risk for fetal aneuploidies. Gestational age and indications for amniocentesis, clinical interventions after FISH results, as well as interventions after final culture reports were analyzed. There were 244 (79%) normal, 50 (16%) abnormal and 15 (5%) inconclusive FISH results. There were no false-positive or false-negative results, but there were nine (3%) clinically significant chromosomal abnormalities not detectable by FISH. Of the 50 women with abnormal FISH results, 26 (52%) elected to terminate the pregnancy prior to the availability of the standard chromosome analysis. In two of the fetuses with trisomy 21 no abnormalities were reported by ultrasound examination. Our experience indicates that interphase FISH results played an important role in decision making, especially for pregnancies close to 24 weeks' gestation. Standard karyotype analysis is still required for detection of chromosome abnormalities not detectable by interphase FISH techniques and for clarification of unusual or inconclusive FISH results. Copyright © 2001 John Wiley & Sons, Ltd.     

Analysis of aerosol particles and coarse particulate matter concentrations in Chillán, Chile, 2001-2003

Daily particle samples were collected in Chillán, Chile, at six urban locations from September 1, 2001, through September 30, 2003. Aerosol samples were collected using monitors equipped with a Sierra Andersen 246-b cyclone inlet on Teflon filters. Average concentrations of coarse particulate matter (PM10) for the 2001-2003 period ranged from 43.4 microg/m3 to 81.8 microg/m3 across the six sites. Annual PM10 concentration levels exceeded the European Union concentration limits. Mean PM10 levels during the cold season (April through September) were more than twice as high as those observed in the warm season (October through March). Average contributions to PM10 from organic matter, soil dust, nitrate (NO3-), elemental carbon, ammonium (NH4+), and sulfate (SO4(2-)) were 31%, 27%, 11%, 8%, 7%, and 5%, respectively. The chemical analyses indicated that carbonaceous substances were the most abundant components of PM10 in cold months, whereas crustal material was the most abundant component of PM10 during warm months. Higher concentration levels were observed in the downtown area suggesting a clear anthropogenic origin, whereas in the rural sites the source was mainly natural, such as resuspended soil dust associated with traffic on unpaved roads and agricultural activities.     

Improving ozonation to remove carbamazepine through ozone-assisted catalysis using different NiO concentrations

The carbamazepine (CBZ) abatement is herein evaluated using catalytic ozonation at different NiO concentrations as catalyst: 100, 300, and 500 mg      

Growth,mortality and recruitment of the yellow clam Mesodesma mactroides on Uruguayan beaches

We studied some aspects of the population dynamics of the yellow clam Mesodesma mactroides (Deshayes, 1854) which inhabits the eastern sandy beaches of Uruguay. Observations were made from March 1983 through March 1985 (harvesting season), and additional data from January 1988 to December 1989 (closed season) were also included in the analyses. Parameters of growth and mortality were estimated by methods that make use of age or length information. An age/length relationship was constructed by counting growth rings. Results were consistent with those obtained with modal class progression analysis and other length/frequency methods. The growth curve obtained from the age/length relationship did not account for seasonality in growth rate, and a seasonal growth model explained growth oscillations in a better way. The instantaneous coefficient of natural mortality (M) estimated for the closed season was 1.64, whereas an increase in fishing mortality (F) was observed during 1984. Age composition did not change during the 2 yr of study, and the first 6 mm class accounted for over 50% of the population. The main contribution of recruits was observed between late summer and early fall (February to April), and the recruitment pattern suggested one main settlement period per year. Growth and recruitment success appeared to be regulated by density-dependence processes. Some implications for management are considered in this context. Methodological aspects concerning the reliability of empirical equations and programs for estimating growth and mortality are discussed.     

Baselines for land-use change in the tropics: application to avoided deforestation projects

Although forest conservation activities, particularly in the tropics, offer significant potential for mitigating carbon (C) emissions, these types of activities have faced obstacles in the policy arena caused by the difficulty in determining key elements of the project cycle, particularly the baseline. A baseline for forest conservation has two main components: the projected land-use change and the corresponding carbon stocks in applicable pools in vegetation and soil, with land-use change being the most difficult to address analytically. In this paper we focus on developing and comparing three models, ranging from relatively simple extrapolations of past trends in land use based on simple drivers such as population growth to more complex extrapolations of past trends using spatially explicit models of land-use change driven by biophysical and socioeconomic factors. The three models used for making baseline projections of tropical deforestation at the regional scale are: the Forest Area Change (FAC) model, the Land Use and Carbon Sequestration (LUCS) model, and the Geographical Modeling (GEOMOD) model. The models were used to project deforestation in six tropical regions that featured different ecological and socioeconomic conditions, population dynamics, and uses of the land: (1) northern Belize; (2) Santa Cruz State, Bolivia; (3) Paraná State, Brazil; (4) Campeche, Mexico; (5) Chiapas, Mexico; and (6) Michoacán, Mexico. A comparison of all model outputs across all six regions shows that each model produced quite different deforestation baselines. In general, the simplest FAC model, applied at the national administrative-unit scale, projected the highest amount of forest loss (four out of six regions) and the LUCS model the least amount of loss (four out of five regions). Based on simulations of GEOMOD, we found that readily observable physical and biological factors as well as distance to areas of past disturbance were each about twice as important as either sociological/demographic or economic/infrastructure factors (less observable) in explaining empirical land-use patterns. We propose from the lessons learned, a methodology comprised of three main steps and six tasks can be used to begin developing credible baselines. We also propose that the baselines be projected over a 10-year period because, although projections beyond 10 years are feasible, they are likely to be unrealistic for policy purposes. In the first step, an historic land-use change and deforestation estimate is made by determining the analytic domain (size of the region relative to the size of proposed project), obtaining historic data, analyzing candidate baseline drivers, and identifying three to four major drivers. In the second step, a baseline of where deforestation is likely to occur–a potential land-use change (PLUC) map—is produced using a spatial model such as GEOMOD that uses the key drivers from step one. Then rates of deforestation are projected over a 10-year baseline period based on one of the three models. Using the PLUC maps, projected rates of deforestation, and carbon stock estimates, baseline projections are developed that can be used for project GHG accounting and crediting purposes: The final step proposes that, at agreed interval (e.g., about 10 years), the baseline assumptions about baseline drivers be re-assessed. This step reviews the viability of the 10-year baseline in light of changes in one or more key baseline drivers (e.g., new roads, new communities, new protected area, etc.). The potential land-use change map and estimates of rates of deforestation could be re-done at the agreed interval, allowing the deforestation rates and changes in spatial drivers to be incorporated into a defense of the existing baseline, or the derivation of a new baseline projection.     

Disaster risk from a macroeconomic perspective: a metric for fiscal vulnerability evaluation

The Disaster Deficit Index (DDI) measures macroeconomic and financial risk in a country according to possible catastrophic scenario events. Extreme disasters can generate financial deficit due to sudden and elevated need of resources to restore affected inventories. The DDI captures the relationship between the economic loss that a country could experience when a catastrophic event occurs and the availability of funds to address the situation. The proposed model utilises the procedures of the insurance industry in establishing probable losses, based on critical impacts during a given period of exposure; for economic resilience, the model allows one to calculate the country's financial ability to cope with a critical impact. There are limitations and costs associated with access to resources that one must consider as feasible values according to the country's macroeconomic and financial conditions. This paper presents the DDI model and the results of its application to 19 countries of the Americas and aims to guide governmental decision‐making in disaster risk reduction.