Use of machine learning to shorten observation-based screening and diagnosis of autism

The Autism Diagnostic Observation Schedule-Generic (ADOS) is one of the most widely used instruments for behavioral evaluation of autism spectrum disorders. It is composed of four modules, each tailored for a specific group of individuals based on their language and developmental level. On average, a module takes between 30 and 60 min to deliver. We used a series of machine-learning algorithms to study the complete set of scores from Module 1 of the ADOS available at the Autism Genetic Resource Exchange (AGRE) for 612 individuals with a classification of autism and 15 non-spectrum individuals from both AGRE and the Boston Autism Consortium (AC). Our analysis indicated that 8 of the 29 items contained in Module 1 of the ADOS were sufficient to classify autism with 100% accuracy. We further validated the accuracy of this eight-item classifier against complete sets of scores from two independent sources, a collection of 110 individuals with autism from AC and a collection of 336 individuals with autism from the Simons Foundation. In both cases, our classifier performed with nearly 100% sensitivity, correctly classifying all but two of the individuals from these two resources with a diagnosis of autism, and with 94% specificity on a collection of observed and simulated non-spectrum controls. The classifier contained several elements found in the ADOS algorithm, demonstrating high test validity, and also resulted in a quantitative score that measures classification confidence and extremeness of the phenotype. With incidence rates rising, the ability to classify autism effectively and quickly requires careful design of assessment and diagnostic tools. Given the brevity, accuracy and quantitative nature of the classifier, results from this study may prove valuable in the development of mobile tools for preliminary evaluation and clinical prioritization—in particular those focused on assessment of short home videos of children—that speed the pace of initial evaluation and broaden the reach to a significantly larger percentage of the population at risk

Exceptionally Preserved Jellyfishes from the Middle Cambrian

Cnidarians represent an early diverging animal group and thus insight into their origin and diversification is key to understanding metazoan evolution. Further, cnidarian jellyfish comprise an important component of modern marine planktonic ecosystems. Here we report on exceptionally preserved cnidarian jellyfish fossils from the Middle Cambrian (∼505 million years old) Marjum Formation of Utah. These are the first described Cambrian jellyfish fossils to display exquisite preservation of soft part anatomy including detailed features of structures interpreted as trailing tentacles and subumbrellar and exumbrellar surfaces. If the interpretation of these preserved characters is correct, their presence is diagnostic of modern jellyfish taxa. These new discoveries may provide insight into the scope of cnidarian diversity shortly after the Cambrian radiation, and would reinforce the notion that important taxonomic components of the modern planktonic realm were in place by the Cambrian period

SOSORT consensus paper: school screening for scoliosis. Where are we today?

This report is the SOSORT Consensus Paper on School Screening for Scoliosis discussed at the 4th International Conference on Conservative Management of Spinal Deformities, presented by SOSORT, on May 2007. The objectives were numerous, 1) the inclusion of the existing information on the issue, 2) the analysis and discussion of the responses by the meeting attendees to the twenty six questions of the questionnaire, 3) the impact of screening on frequency of surgical treatment and of its discontinuation, 4) the reasons why these programs must be continued, 5) the evolving aim of School Screening for Scoliosis and 6) recommendations for improvement of the procedure

Eastern Mediterranean sapropels: chemical structure, deposition and relation to oil-shales

Ten sapropels, deposited in three different basins of the eastern Mediterranean since the Miocene and selected from cores of the Deep Sea Drilling Programme have been characterised by elemental analysis; fluorescence, infra-red and NMR spectrometry, by pyrolysis-gas chromatography/mass spectrometry and by catalytic hydrogenation at moderately high pressure. The sapropels are Types I-II kerogens, which have been oxidised, probably by a front experienced, since their deposition. Only one, from the Cretan basin, contained structures from lignin. The others, typical of a marine deposition, possessed aromaticities of about 0.2. Their detailed organic structures are described

Black Sea sapropels: relationship to kerogens and fossil fuel precursors

The organic structures in sapropels sampled from two cores obtained at known locations beneath the southern Black Sea have been characterised. Fluorescence petrography shows the sapropels to occur as layers of impure alginite, similar to 50 mu m thick, within Unit 2 of the sediments. Solid state C-13 NMR indicates the bulk chemical structures to be very similar to those in an immature Type 1 kerogen (lamosite) oil shale with an aromaticity of similar to 0.2. Consistent with the immaturity of the sapropels, which are between 3000 and 7000 years old, temperature programmed reduction showed aliphatic and aromatic sulphides to be the major organic sulphur forms. Alkanes formed from phytoplankton lipids, alkyl benzenes, alkyl naphthalenes and some phenols dominated the mix of volatile compounds identified by pyrolysis-gas chromatography/mass spectrometry. About half of the sapropels remained as an involatile, tarry residue after pyrolysis. The structure of the sapropels is consistent with their formation resulting from marine phytoplankton with only small terrigeneous inputs. Future catagenesis may be expected to decarboxylate the lipids, increase the aromaticity and to dry and compress the muds to form a source rock