Denaturing high-performance liquid chromatography (DHPLC)-based prenatal diagnosis for tuberous sclerosis

Tuberous sclerosis (TSC) is a frequent autosomal-dominant condition (affecting 1 in 6000 individuals) caused by various mutations in either the hamartin (TSC1) or the tuberin gene (TSC2). This allelic and non-allelic heterogeneity makes genetic counseling and prenatal diagnosis difficult, especially as a significant proportion of TSC cases are due to de novo mutations. For this reason the identification of the disease causing mutation is mandatory for accurate counseling, yet current mutation detection methods such as single-strand conformation polymorphism (SSCP) or denaturing gradient gel electrophoresis (DGGE) are labor intensive with limited detection efficiency. Denaturing high-performance liquid chromatography (DHPLC) is a high-throughput, semi-automated mutation detection system with a reported mutation detection rate close to 100% for PCR fragments of up to 800 bp. We used a recently described DHPLC assay allowing the efficient detection of mutations in TSC1 to analyze the DNA extracted from a chorion villus sample in order to perform a prenatal diagnosis for TSC. The fetus was found not to have inherited the deleterious mutation and the DHPLC diagnosis was confirmed by haplotype analysis. This represents the first DHPLC-based prenatal diagnosis of a genetic disease. Copyright © 2001 John Wiley & Sons, Ltd.     

Biologie und Biochemie des Elements Selen

The importance of selenium as an essential trace element has progressively emerged during the last years due to the analysis of selenium deficiency diseases and to the identification and characterization of a number of selenoenzymes. Selenium is incorporated in the catalytic site of the enzymes as an integral selenocysteine residue. The pathway of selenocysteine biosynthesis and incorporation has been elucidated recently for Escherichia coli. This article presents an overview on these subjects and describes the mechanisms which confer selenocysteine specificity in the framework of protein biosynthesis. In addition, some considerations concerning the phylogeny of selenocysteine incorporation are presented and a model for the evolution of the selenocysteine pathway is proposed.     

Simultaneous analysis of endosulfan, chlorpyrifos, and their metabolites in natural soil and water samples using gas chromatography-tandem mass spectrometry

Analysis of endosulfan, chlorpyrifos, and their nonpolar metabolites in extracts from environmental aqueous and soil samples was performed using a gas chromatography-tandem mass spectrometry (GC–MS/MS) technique. Full-scan GC–MS analysis showed poor sensitivity for some of the metabolites (endodiol and endosulfan ether). A multisegment MS/MS method was developed and MS/MS parameter isolation time, excitation time, excitation voltage, and maximum excitation energy were optimized for chosen precursor ions to enhance selectivity and sensitivity of the analysis. The use of MS/MS with optimized parameters quantified analytes with significantly higher accuracy, and detection limits were lowered to ~1/6th compared with the full-scan method. Co-eluting compounds, chlorpyrifos and chlorpyrifos oxon, were also analyzed successfully in the MS/MS mode by choosing exclusive precursor ions. Analysis of soil and water phase samples from contaminated soil slurry bioreactors showed that the MS/MS method could provide more reliable estimates of these pesticide and metabolites (especially those present in low concentrations) by annulling interferences from soil organic matter.     

Soil properties and crop productivity as influenced by flyash incorporation in soil

Field experiments were carried out during 1996–97at Gulawathi, Muthiani and Salarpur Villages, IARI Farm, NewDelhi and NCPP Campus, Dadri to evaluate changes in soilcharacteristics and growth of wheat (Triticum aestivum L.),mustard (Brassica juncea L.), lentil (Lence esculentaMoench.), rice (Oryza sativa L.) and maize (Zea mays L.) byvarying amounts of flyash addition (up to 50t ha^-1) in soils atsowing/transplanting time of crops. Flyash addition in areasadjoining NCPP Thermal Power Plant, Dadri, Ghaziabad, U.P.ranged from 5–12 t ha^-1 yr^-1 in 1995–96. Shoot and root growthand yield of test crops at different locations after flyashincorporation resulted in beneficial effects of flyashaddition in most cases. The silt dominant texture of flyashimproved loamy sand to sandy loam textures of the surfacesoils at the farmers' fields. The increased growth in yield ofcrops with flyash incorporation was possibly due tomodifications in soil moisture retention and transmissioncharacteristics, bulk density, physico-chemical characterssuch as pH and EC and organic carbon content. The response offlyash addition in the soil on soil health and cropproductivity needs to be evaluated on long-term sustainableaspects.     

The interaction between physical and social-psychological factors in indoor environmental health

Indoor environmental health is now recognized as an important factor in preventing respiratory health problems in the United States. It is also a concern in Canada due to the amount of time that Canadians spend indoors because of cold weather and the potential for increased time indoors during the summer if theclimate warms. The negative health effects are often labeled assick building syndrome, but diagnosing a building or itsoccupants as sick is complicated by the variety of symptoms, thepresence of chronic versus acute symptoms and social andpsychological (socio-psychological) factors that may reduce theeffectiveness of an engineering solution. As a case study, thecontribution of various factors to indoor environmental health,in three buildings at the University of Toronto, was examinedusing five different methods. The results indicate that theinhabitants of the buildings consider features other than airquality in considering building health such as design,maintenance, funding cuts and socio-psychological factors.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Comparison of Two Manual Methods of Nitrogen Dioxide Determination in Ambient Air

Sodium arsenite (modified Jacobs and Hochheiser method; hereafter referred as SA), the most widely used manual monitoring method for determination of nitrogen dioxide (NO₂) in ambient air, particularly in developing countries has been evaluated and compared with US EPA recommended equivalent method of TGS-ANSA (hereafter referred as ANSA). NO₂ concentrations generated from laboratory test atmosphere were analyzed by these two methods and were compared statistically. Laboratory evaluations showed that SA method has high sensitivity to different sampling conditions, which normally vary during actual field monitoring. Hence, correction factors for absorption efficiency were estimated for SA and ANSA methods. Absorption efficiency of NO₂ in SA method was found to be much lower (64%) as against the reported value of 82% at the method recommended sampling conditions, whereas for ANSA method, it was found 1.0 as against the reported value of 0.93. After applying derived correction factors, both the methods produced almost similar concentration values of NO₂.     

Investigation of the Influence of Seagrass on Fisheries Catch Level Using Isotonic Regression

The relationship between seagrass area and the commercial catch of some economically important South Australian fish species is not known in any quantitative sense. However, there is evidence in the literature to suggest that seagrass decline will detrimentally impact on species abundance and composition, and consequently that the presence or absence of seagrass will compromise the commercial and recreational fishery. In this paper we describe the construction of models based on order restricted (isotonic) regression and discuss the role of seagrass area, in terms of its influence on the level of commercial catch through modifying the effect of fishing 'effort'.     

Prediction of the solubility of zinc, copper, nickel, cadmium, and lead in metal-contaminated soils

Risk assessment of metal-contaminated soil depends on how precisely one can predict the solubility of metals in soils. Responses of plants and soil organisms to metal toxicity are explained by the variation in free metal ion activity in soil pore water. This study was undertaken to predict the free ion activity of Zn, Cu, Ni, Cd, and Pb in metal-contaminated soil as a function of pH, soil organic carbon, and extractable metal content. For this purpose, 21 surface soil samples (0–15 cm) were collected from agricultural lands of various locations receiving sewage sludge and industrial effluents for a long period. One soil sample was also collected from agricultural land which has been under intensive cropping and receiving irrigation through tube well water. Soil samples were varied widely in respect of physicochemical properties including metal content. Total Zn, Cu, Ni, Cd, and Pb in experimental soils were 2,015?±?3,373, 236?±?286, 103?±?192, 29.8?±?6.04, and 141?±?270 mg kg^?1, respectively. Free metal ion activity, viz., pZn²⁺, pCu²⁺, pNi²⁺, pCd²⁺, and pPb²⁺, as estimated by the Baker soil test was 9.37?±?1.89, 13.1?±?1.96, 12.8?±?1.89, 11.9?±?2.00, and 11.6?±?1.52, respectively. Free metal ion activity was predicted by pH-dependent Freundlich equation (solubility model) as a function of pH, organic carbon, and extractable metal. Results indicate that solubility model as a function of pH, Walkley–Black carbon (WBC), and ethylenediaminetetraacetic acid (EDTA)-extractable metals could explain the variation in pZn²⁺, pCu²⁺, pNi²⁺, pCd²⁺, and pPb²⁺ to the extent of 59, 56, 46, 52, and 51 %, respectively. Predictability of the solubility model based on pH, KMnO₄-oxidizable carbon, and diethylenetriaminepentaacetic acid-extractable or CaCl₂-extractable metal was inferior compared to that based on EDTA-extractable metals and WBC.     

Assessment and monitoring of long-term forest cover changes in Odisha, India using remote sensing and GIS

Deforestation and fragmentation are important concerns in managing and conserving tropical forests and have global significance. In the Indian context, in the last one century, the forests have undergone significant changes due to several policies undertaken by government as well as increased population pressure. The present study has brought out spatiotemporal changes in forest cover and variation in forest type in the state of Odisha (Orissa), India, during the last 75 years period. The mapping for the period of 1924–1935, 1975, 1985, 1995 and 2010 indicates that the forest cover accounts for 81,785.6 km² (52.5 %), 56,661.1 km² (36.4 %), 51,642.3 km² (33.2 %), 49,773 km² (32 %) and 48,669.4 km² (31.3 %) of the study area, respectively. The study found the net forest cover decline as 40.5 % of the total forest and mean annual rate of deforestation as 0.69 %?year^?1 during 1935 to 2010. There is a decline in annual rate of deforestation during 1995 to 2010 which was estimated as 0.15 %. Forest type-wise quantitative loss of forest cover reveals large scale deforestation of dry deciduous forests. The landscape analysis shows that the number of forest patches (per 1,000) are 2.463 in 1935, 10.390 in 1975, 11.899 in 1985, 12.193 in 1995 and 15.102 in 2010, which indicates high anthropogenic pressure on the forests. The mean patch size (km²) of forest decreased from 33.2 in 1935 to 5.5 in 1975 and reached to 3.2 by 2010. The study demonstrated that monitoring of long term forest changes, quantitative loss of forest types and landscape metrics provides critical inputs for management of forest resources.