A survey of transposable element classification systems--a call for a fundamental update to meet the challenge of their diversity and complexity.

The increase of publicly available sequencing data has allowed for rapid progress in our understanding of genome composition. As new information becomes available we should constantly be updating and reanalyzing existing and newly acquired data. In this report we focus on transposable elements (TEs) which make up a significant portion of nearly all sequenced genomes. Our ability to accurately identify and classify these sequences is critical to understanding their impact on host genomes. At the same time, as we demonstrate in this report, problems with existing classification schemes have led to significant misunderstandings of the evolution of both TE sequences and their host genomes. In a pioneering publication Finnegan (1989) proposed classifying all TE sequences into two classes based on transposition mechanisms and structural features: the retrotransposons (class I) and the DNA transposons (class II). We have retraced how ideas regarding TE classification and annotation in both prokaryotic and eukaryotic scientific communities have changed over time. This has led us to observe that: (1) a number of TEs have convergent structural features and/or transposition mechanisms that have led to misleading conclusions regarding their classification, (2) the evolution of TEs is similar to that of viruses by having several unrelated origins, (3) there might be at least 8 classes and 12 orders of TEs including 10 novel orders. In an effort to address these classification issues we propose: (1) the outline of a universal TE classification, (2) a set of methods and classification rules that could be used by all scientific communities involved in the study of TEs, and (3) a 5-year schedule for the establishment of an International Committee for Taxonomy of Transposable Elements (ICTTE).

History of offending behavior in first episode psychosis patients : a marker of specific clinical needs and a call for early detection strategies among young offenders

Plusieurs études suggèrent que les patients qui présentent un premier épisode psychotique et un passé délictueux présenteraient une clinique spécifique et nécessiteraient une prise en charge adaptée. A partir d'une cohorte de patients suivis pour un premier épisode psychotique dans la région de Melbourne {The Early Psychosis Prevention and Intervention Centre), nous avons analysé la prévalence d'actes délictueux dans leur passé (1), les caractéristiques cliniques à leur admission (2), l'évolution à court terme des patients ayant commis des délits par rapport aux autres patients (3). Nous avons également cherché à déterminer si des délits plus graves (atteinte à l'intégrité d'une personne) étaient corrélés à des caractéristiques cliniques particulières. Sur les 649 patients dont les données ont pu être analysées entre 1998 et 2000, 29% avaient un passé délictueux. Ils étaient en majorité des hommes et présentaient des difficultés sociales et scolaires plus importantes que les autres patients. Ils avaient également recours de manière plus régulière à des substances illicites et commis plus souvent des tentatives de suicide. Le tableau clinique qu'ils présentaient à leur admission dans le programme de soins était plus complexe et l'évolution globalement plus défavorable après 18 mois de traitement. Nous avons relevé aussi que la durée de psychose non traitée était plus longue que celle des autres patients. Enfin, les délits avec atteinte à l'intégrité d'une autre personne étaient plus fréquents en présence d'un insight faible et nécessitaient un plus grand nombre d'hospitalisation. Ces résultats confirment le besoin d'une recherche approfondie dans ce champ de la clinique et de stratégies de prévention et de soins plus spécifiques. Une détection précoce chez les jeunes hommes qui commettent des actes délictueux serait particulièrement importante puisque notre étude suggère que certains d'entre eux seraient dans une phase débutante et non reconnue d'un épisode psychotique. Une intervention plus rapide et adaptée pourrait avoir des conséquences positives à plusieurs niveaux.

Call for uniform neuropsychological assessment after aneurysmal subarachnoid hemorrhage: Swiss recommendations.

BACKGROUND: In a high proportion of patients with favorable outcome after aneurysmal subarachnoid hemorrhage (aSAH), neuropsychological deficits, depression, anxiety, and fatigue are responsible for the inability to return to their regular premorbid life and pursue their professional careers. These problems often remain unrecognized, as no recommendations concerning a standardized comprehensive assessment have yet found entry into clinical routines. METHODS: To establish a nationwide standard concerning a comprehensive assessment after aSAH, representatives of all neuropsychological and neurosurgical departments of those eight Swiss centers treating acute aSAH have agreed on a common protocol. In addition, a battery of questionnaires and neuropsychological tests was selected, optimally suited to the deficits found most prevalent in aSAH patients that was available in different languages and standardized. RESULTS: We propose a baseline inpatient neuropsychological screening using the Montreal Cognitive Assessment (MoCA) between days 14 and 28 after aSAH. In an outpatient setting at 3 and 12 months after bleeding, we recommend a neuropsychological examination, testing all relevant domains including attention, speed of information processing, executive functions, verbal and visual learning/memory, language, visuo-perceptual abilities, and premorbid intelligence. In addition, a detailed assessment capturing anxiety, depression, fatigue, symptoms of frontal lobe affection, and quality of life should be performed. CONCLUSIONS: This standardized neuropsychological assessment will lead to a more comprehensive assessment of the patient, facilitate the detection and subsequent treatment of previously unrecognized but relevant impairments, and help to determine the incidence, characteristics, modifiable risk factors, and the clinical course of these impairments after aSAH.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units.

PURPOSE: According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction. METHOD: About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART). RESULTS: The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty. CONCLUSION: Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.

CT attenuation values of blood and myocardium: rationale for accurate coronary artery calcifications detection with multi-detector CT.

OBJECTIVES: To determine inter-session and intra/inter-individual variations of the attenuations of aortic blood/myocardium with MDCT in the context of calcium scoring. To evaluate whether these variations are dependent on patients' characteristics. METHODS: Fifty-four volunteers were evaluated with calcium scoring non-enhanced CT. We measured attenuations (inter-individual variation) and standard deviations (SD, intra-individual variation) of the blood in the ascending aorta and of the myocardium of left ventricle. Every volunteer was examined twice to study the inter-session variation. The fat pad thickness at the sternum and noise (SD of air) were measured too. These values were correlated with the measured aortic/ventricular attenuations and their SDs (Pearson). Historically fixed thresholds (90 and 130 HU) were tested against different models based on attenuations of blood/ventricle. RESULTS: The mean attenuation was 46 HU (range, 17-84 HU) with mean SD 23 HU for the blood, and 39 HU (10-82 HU) with mean SD 18 HU for the myocardium. The attenuation/SD of the blood were significantly higher than those of the myocardium (p < 0.01). The inter-session variation was not significant. There was a poor correlation between SD of aortic blood/ventricle with fat thickness/noise. Based on existing models, 90 HU threshold offers a confidence interval of approximately 95% and 130 HU more than 99%. CONCLUSIONS: Historical thresholds offer high confidence intervals for exclusion of aortic blood/myocardium and by the way for detecting calcifications. Nevertheless, considering the large variations of blood/myocardium CT values and the influence of patient's characteristics, a better approach might be an adaptive threshold.

Automatic Brain Extraction in Fetal MRI using Multi-Atlas-based Segmentation

In fetal brain MRI, most of the high-resolution reconstruction algorithms rely on brain segmentation as a preprocessing step. Manual brain segmentation is however highly time-consuming and therefore not a realistic solution. In this work, we assess on a large dataset the performance of Multiple Atlas Fusion (MAF) strategies to automatically address this problem. Firstly, we show that MAF significantly increase the accuracy of brain segmentation as regards single-atlas strategy. Secondly, we show that MAF compares favorably with the most recent approach (Dice above 0.90). Finally, we show that MAF could in turn provide an enhancement in terms of reconstruction quality.