Molecular inventory of faecal microflora in patients with Crohn's disease

Intestinal microbial community is involved in the pathogenesis of Crohn's disease, but knowledge of its potential abnormalities has been limited by the impossibility to grow many dominant intestinal bacteria. Using sequence analysis of randomly cloned bacterial 16S ribosomal DNA, the dominant faecal species from four Crolin's disease patients and four controls were compared. Whereas marked inter-individual differences were observed in the faecal microflora of patients, three remained distantly related to controls on the basis of their operational taxonomic unit composition. Bacteroides vidgatus and closely related organisms represented the only molecular species shared by all patients and exhibited an unusually high rate of occurrence. Escherichia coli clones were isolated only in two patients with ileocolonic Crohn's disease. Moreover, numerous clones belonged to phylogenetic groups or species that are commonly not dominant in the faecal microflora of healthy subjects: Pectinatus, Sutterella, Verritcomicrobium, Fusobacterium, Clostridium disporicum, clostridium glycolicum, Clostridium ramosum, Clostridium innocuum and Clostridium perfringens. (C) 2004 Federation of European Microbiological Societies. Published by Elsevier B.V. All rights reserved.

Historical reconstruction of the Atlantic Meridional Overturning Circulation from the ECMWF operational ocean reanalysis

A reconstruction of the Atlantic Meridional Overturning Circulation (MOC) for the period 1959–2006 has been derived from the ECMWF operational ocean reanalysis. The reconstruction shows a wide range of time-variability, including a downward trend. At 26N, both the MOC intensity and changes in its vertical structure are in good agreement with previous estimates based on trans-Atlantic surveys. At 50N, the MOC and strength of the subpolar gyre are correlated at interannual time scales, but show opposite secular trends. Heat transport variability is highly correlated with the MOC but shows a smaller trend due to the warming of the upper ocean, which partially compensates for the weakening of the circulation. Results from sensitivity experiments show that although the time-varying upper boundary forcing provides useful MOC information, the sequential assimilation of ocean data further improves the MOC estimation by increasing both the mean and the time variability.

The GlobMODEL demonstrator: assimilation of new satellite products in an operational meteorological center

As part of its Data User Element programme, the European Space Agency funded the GlobMODEL project which aimed at investigating the scientific, technical, and organizational issues associated with the use and exploitation of remotely-sensed observations, particularly from new sounders. A pilot study was performed as a "demonstrator" of the GlobMODEL idea, based on the use of new data, with a strong European heritage, not yet assimilated operationally. Two parallel assimilation experiments were performed, using either total column ozone or ozone profiles retrieved at the Royal Netherlands Meteorological Institute (KNMI) from the Ozone Monitoring Instrument (OMI). In both cases, the impact of assimilating OMI data in addition to the total ozone columns from the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) on the European Centre for Medium Range Weather Forecasts (ECMWF) ozone analyses was assessed by means of independent measurements. We found that the impact of OMI total columns is mainly limited to the region between 20 and 80 hPa, and is particularly important at high latitudes in the Southern hemisphere where the stratospheric ozone transport and chemical depletion are generally difficult to model with accuracy. Furthermore, the assimilation experiments carried out in this work suggest that OMI DOAS (Differential Optical Absorption Spectroscopy) total ozone columns are on average larger than SCIAMACHY total columns by up to 3 DU, while OMI total columns derived from OMI ozone profiles are on average about 8 DU larger than SCIAMACHY total columns. At the same time, the demonstrator brought to light a number of issues related to the assimilation of atmospheric composition profiles, such as the shortcomings arising when the vertical resolution of the instrument is not properly accounted for in the assimilation. The GlobMODEL demonstrator accelerated scientific and operational utilization of new observations and its results - prompted ECMWF to start the operational assimilation of OMI total column ozone data.

A glacier inventory for the Buordakh Massif, Cherskiy Range, northeast Siberia, and evidence for recent glacier recession

The Buordakh Massif, in the Cherskiy Range of northeast Siberia, contains mountains over 3000 in and, despite its and climate, numerous glaciers. This paper presents a glacier inventory for the region and documents some 80 glaciers, which range in size from 0.1 to 10.4 km(2) (total glacierized area is ca. 70 km(2)). The inventory is based on mapping derived from Landsat 7 ETM+ satellite imagery from August 2001, augmented with data from field investigations obtained at that time. The glaciers in this region are of the 'firn-less,' cold, continental type, and their mass balance relies heavily on the formation of superimposed ice. The most recent glacier maximum extents have also been delineated, and these are believed to date from the Little Ice Age (ca. A.D. 1550-1850). Glacier areal extent has reduced by some 14.8 km(2) (ca. 17%) since this most. recent maximum. Of the 80 glaciers catalogued, 49 have undergone a measurable retreat from their most recent maximum extent.

An inventory of heavy metals inputs to agricultural soils in England and Wales

An inventory of heavy metal inputs (Zn, Cu, Ni, Pb, Cd, Cr, As and Hg) to agricultural soils in England and Wales in 2000 is presented, accounting for major sources including atmospheric deposition, sewage sludge, livestock manures, inorganic fertilisers and lime, agrochemicals, irrigation water, industrial by-product 'wastes' and composts. Across the whole agricultural land area, atmospheric deposition was the main source of most metals, ranging from 25 to 85% of total inputs. Livestock manures and sewage sludge were also important sources, responsible for an estimated 37-40 and 8-17% of total Zn and Cu inputs, respectively. However, at the individual field scale sewage sludge, livestock manures and industrial wastes could be the major source of many metals where these materials are applied. This work will assist in developing strategies for reducing heavy metal inputs to agricultural land and effectively targeting policies to protect soils from long-term heavy metal accumulation. (C) 2003 Elsevier Science B.V. All rights reserved.

Infant vocabulary development assessed with a British communicative development inventory

Communicative Development Inventories (CDIs) were collected from 669 British children aged between 1;0 and 2;1. Comprehension and production scores in each age group are calculated. This provides norming data for the British infant population. The influence of socioeconomic group on vocabulary scores is considered and shown not to have a significant effect. The data from British infants is compared to data from American infants (Fenson, Dale, Reznick, Bates, Thal & Pethick, 1994). It is found that British infants have lower scores on both comprehension and production than American infants of the same age.

Validation of improved TAMANN neural network for operational satellite-derived rainfall estimation in Africa

Real-time rainfall monitoring in Africa is of great practical importance for operational applications in hydrology and agriculture. Satellite data have been used in this context for many years because of the lack of surface observations. This paper describes an improved artificial neural network algorithm for operational applications. The algorithm combines numerical weather model information with the satellite data. Using this algorithm, daily rainfall estimates were derived for 4 yr of the Ethiopian and Zambian main rainy seasons and were compared with two other algorithms-a multiple linear regression making use of the same information as that of the neural network and a satellite-only method. All algorithms were validated against rain gauge data. Overall, the neural network performs best, but the extent to which it does so depends on the calibration/validation protocol. The advantages of the neural network are most evident when calibration data are numerous and close in space and time to the validation data. This result emphasizes the importance of a real-time calibration system.