Subgrouping the autism "spectrum": reflections on DSM-5

DSM-5 has moved autism from the level of subgroups ("apples and oranges") to the prototypical level ("fruit"). But making progress in research, and ultimately improving clinical practice, will require identifying subgroups within the autism spectrum.

Una biografia per immagini

Life and work of screen-writer Enrico Medioli (b. 1925), following the criteria of Dizionario Biografico degli Italiani (by Istituto Enciclopedia Italiana), tht is the top of Italian tools (I wrote several items for it).

A multi-scale framework for strategic management of diffuse pollution

A multi-scale framework for decision support is presented that uses a combination of experiments, models, communication, education and decision support tools to arrive at a realistic strategy to minimise diffuse pollution. Effective partnerships between researchers and stakeholders play a key part in successful implementation of this strategy. The Decision Support Matrix (DSM) is introduced as a set of visualisations that can be used at all scales, both to inform decision making and as a communication tool in stakeholder workshops. A demonstration farm is presented and one of its fields is taken as a case study. Hydrological and nutrient flow path models are used for event based simulation (TOPCAT), catchment scale modelling (INCA) and field scale flow visualisation (TopManage). One of the DSMs; The Phosphorus Export Risk Matrix (PERM) is discussed in detail. The PERM was developed iteratively as a point of discussion in stakeholder workshops, as a decision support and education tool. The resulting interactive PERM contains a set of questions and proposed remediation measures that reflect both expert and local knowledge. Education and visualisation tools such as GIS, risk indicators, TopManage and the PERM are found to be invaluable in communicating improved farming practice to stakeholders. (C) 2008 Elsevier Ltd. All rights reserved.

Improving flood models using LiDAR: progress and problems

Airborne scanning laser altimetry (LiDAR) is an important new data source for river flood modelling. LiDAR can give dense and accurate DTMs of floodplains for use as model bathymetry. Spatial resolutions of 0.5m or less are possible, with a height accuracy of 0.15m. LiDAR gives a Digital Surface Model (DSM), so vegetation removal software (e.g. TERRASCAN) must be used to obtain a DTM. An example used to illustrate the current state of the art will be the LiDAR data provided by the EA, which has been processed by their in-house software to convert the raw data to a ground DTM and separate vegetation height map. Their method distinguishes trees from buildings on the basis of object size. EA data products include the DTM with or without buildings removed, a vegetation height map, a DTM with bridges removed, etc. Most vegetation removal software ignores short vegetation less than say 1m high. We have attempted to extend vegetation height measurement to short vegetation using local height texture. Typically most of a floodplain may be covered in such vegetation. The idea is to assign friction coefficients depending on local vegetation height, so that friction is spatially varying. This obviates the need to calibrate a global floodplain friction coefficient. It’s not clear at present if the method is useful, but it’s worth testing further. The LiDAR DTM is usually determined by looking for local minima in the raw data, then interpolating between these to form a space-filling height surface. This is a low pass filtering operation, in which objects of high spatial frequency such as buildings, river embankments and walls may be incorrectly classed as vegetation. The problem is particularly acute in urban areas. A solution may be to apply pattern recognition techniques to LiDAR height data fused with other data types such as LiDAR intensity or multispectral CASI data. We are attempting to use digital map data (Mastermap structured topography data) to help to distinguish buildings from trees, and roads from areas of short vegetation. The problems involved in doing this will be discussed. A related problem of how best to merge historic river cross-section data with a LiDAR DTM will also be considered. LiDAR data may also be used to help generate a finite element mesh. In rural area we have decomposed a floodplain mesh according to taller vegetation features such as hedges and trees, so that e.g. hedge elements can be assigned higher friction coefficients than those in adjacent fields. We are attempting to extend this approach to urban area, so that the mesh is decomposed in the vicinity of buildings, roads, etc as well as trees and hedges. A dominant points algorithm is used to identify points of high curvature on a building or road, which act as initial nodes in the meshing process. A difficulty is that the resulting mesh may contain a very large number of nodes. However, the mesh generated may be useful to allow a high resolution FE model to act as a benchmark for a more practical lower resolution model. A further problem discussed will be how best to exploit data redundancy due to the high resolution of the LiDAR compared to that of a typical flood model. Problems occur if features have dimensions smaller than the model cell size e.g. for a 5m-wide embankment within a raster grid model with 15m cell size, the maximum height of the embankment locally could be assigned to each cell covering the embankment. But how could a 5m-wide ditch be represented? Again, this redundancy has been exploited to improve wetting/drying algorithms using the sub-grid-scale LiDAR heights within finite elements at the waterline.

Saccharospirillum impatiens gen. nov., sp nov., a novel gamma-Proteobacterium isolated from hypersaline Ekho Lake (East Antarctica)

Five Gram-negative, motile, aerobic to microaerophilic spirilla were isolated from various depths of the hypersaline, heliothermal and meromictic Ekho Lake (East Antarctica). The strains are oxidase- and catalase-positive, metabolize a variety of sugars and carboxylic acids and have an absolute requirement for sodium ions. The predominant fatty acids of the organisms are C-16: (1)omega7c, C-16:0 and C(18:1)omega7c, with C-10:1 3-OH, C-10:0 3-OH, C-12:0 3-OH, C-14:1 3-OH, C-14:0 3-OH and C-19:1 present in smaller amounts. The main polar lipids are diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylglycerol and phosphatidylmonomethylamine. The DNA base composition of the strains is 54-55 mol% G + C. 16S rRNA gene sequence comparisons show that the isolates are related to the genera Oceanospirillum, Pseudospirillum, Marinospirillum, Halomonas and Chromohalobacter in the gamma-Proteobacteria. Morphological, physiological and genotypic differences from these previously described genera support the description of a novel genus and species, Saccharospirillum impatiens gen. nov., sp. nov. The type strain is EL-105(T) (= DSM 12546(T) = CECT 5721(T)).

Roseisalinus antarcticus gen. nov., sp nov., a novel aerobic bacteriochlorophyll a-producing alpha-proteobacterium isolated from hypersaline Ekho Lake, Antarctica

A Gram-negative, aerobic to microaerophilic rod was isolated from 10 m depths of the hypersaline, heliothermal and meromictic Ekho Lake (East Antarctica). The strain was oxidase- and catalase-positive, metabolized a variety of carboxylic acids and sugars and produced lipase. Cells had an absolute requirement for artificial sea water, which could not be replaced by NaCl. A large in vivo absorption band at 870 nm indicated production of bacteriochlorophyll a. The predominant fatty acids of this organism were 16:0 and 18:1omega7c, with 3-OH 10:0, 16:1omega7c and 18:0 in lower amounts. The main polar lipids were diphosphatidylglycerol, phosphatidylglycerol and phosphatidylcholine. Ubiquinone 10 was produced. The DNA G + C content was 67 mol%. 16S rRNA gene sequence comparisons indicated that the isolate represents a member of the Roseobacter clade within the alpha-Proteobacteria. The organism showed no particular relationship to any members of this clade but clustered on the periphery of the genera Jannaschia, Octadecabacter and 'Marinosulfonomonas' and the species Ruegeria gelatinovorans. Distinct morphological, physiological and genotypic differences to these previously described taxa supported the description of a new genus and a novel species, for which the name Roseisalinus antarcticus gen. nov., sp. nov. is proposed. The type strain is EL-88(T) (= DSM 11466(T) = CECT 7023(T)).

Subdoligranulum variabile gen. nov., sp nov from human feces

During studies on the microflora of human feces we have isolated a strictly anaerobic, non-spore-forming, Gram-negative staining organism which exhibits a somewhat variable coccus-shaped morphology. Comparative 16S ribosomal RNA gene sequencing studies show the unidentified organism is phylogenetically a member of the Clostridium leptum supra-generic rRNA cluster and displays a close affinity to some rDNA clones derived from human and pig feces. The nearest named relatives of the unidentified isolate corresponded to Faecalibacterium prausnitzii (formerly Fusobacterium prausnitzii) displaying a 16S rRNA sequence divergence of approximately 9%, with Anaerofilum agile and A. pentosovorans the next closest relatives of the unidentified bacterium (sequence divergence approximately 10%). Based on phenotypic and phylogenetic considerations, it is proposed that the unusual coccoid-shaped organism be classified as a new genus and species, Subdoligranulum variabile. The type strain of S. variabile is BI 114(T) (= CCUG 47106(T) = DSM 15176(T)). (C) 2004 Elsevier Ltd. All rights reserved.

Allobaculum stercoricanis gen. nov., sp nov., isolated from canine feces

Morphological, biochemical, and molecular genetic studies were performed on an unknown anaerobic, catalase-negative, nonspore-forming, rod-shaped bacterium isolated from dog feces. The unknown bacterium was tentatively identified as a Eubacterium species, based on cellular morphological and biochemical tests. 16S rRNA gene sequencing studies, however, revealed that it was phylogenetically distant from Eubacterium limosum, the type species of the genus Eubacterium. Phylogenetically, the unknown species forms a hitherto unknown sub-line proximal to the base of a cluster of organisms (designated rRNA cluster XVI), which includes Clostridium innocuum, Streptococcus pleomorphus, and some Eubacterium species. Based on both phenotypic and phylogenetic criteria, it is proposed that the unknown bacterium be classified as a new genus and species, Allobaculum stercoricanis. Using a specific rRNA-targeted probe designed to identify Allobacultan stercoricanis, in situ hybridisation showed this novel species represents a significant organism in canine feces comprising between 0.1% and 3.7% of total cells stained with DAPI (21 dog fecal samples). The type strain of Allobaculum stereoricanis is DSM 13633(T) = CCUG 45212(T). (C) 2004 Elsevier Ltd. All rights reserved.