Streaming Support for Data Intensive Cloud-Based Sequence Analysis

Cloud computing provides a promising solution to the genomics data deluge problem resulting from the advent of next-generation sequencing (NGS) technology. Based on the concepts of “resources-on-demand” and “pay-as-you-go”, scientists with no or limited infrastructure can have access to scalable and cost-effective computational resources. However, the large size of NGS data causes a significant data transfer latency from the client’s site to the cloud, which presents a bottleneck for using cloud computing services. In this paper, we provide a streaming-based scheme to overcome this problem, where the NGS data is processed while being transferred to the cloud. Our scheme targets the wide class of NGS data analysis tasks, where the NGS sequences can be processed independently from one another. We also provide the elastream package that supports the use of this scheme with individual analysis programs or with workflow systems. Experiments presented in this paper show that our solution mitigates the effect of data transfer latency and saves both time and cost of computation.

A New Approach for Automatic Removal of Movement Artifacts in Near-Infrared Spectroscopy Time Series by Means of Acceleration Data

Abstract: Near-infrared spectroscopy (NIRS) enables the non-invasive measurement of changes in hemodynamics and oxygenation in tissue. Changes in light-coupling due to movement of the subject can cause movement artifacts (MAs) in the recorded signals. Several methods have been developed so far that facilitate the detection and reduction of MAs in the data. However, due to fixed parameter values (e.g., global threshold) none of these methods are perfectly suitable for long-term (i.e., hours) recordings or were not time-effective when applied to large datasets. We aimed to overcome these limitations by automation, i.e., data adaptive thresholding specifically designed for long-term measurements, and by introducing a stable long-term signal reconstruction. Our new technique (“acceleration-based movement artifact reduction algorithm”, AMARA) is based on combining two methods: the “movement artifact reduction algorithm” (MARA, Scholkmann et al. Phys. Meas. 2010, 31, 649–662), and the “accelerometer-based motion artifact removal” (ABAMAR, Virtanen et al. J. Biomed. Opt. 2011, 16, 087005). We describe AMARA in detail and report about successful validation of the algorithm using empirical NIRS data, measured over the prefrontal cortex in adolescents during sleep. In addition, we compared the performance of AMARA to that of MARA and ABAMAR based on validation data.

The updated European Consensus 2009 on the use of Botulinum toxin for children with cerebral palsy

An interdisciplinary European group of clinical experts in the field of movement disorders and experienced Botulinum toxin users has updated the consensus for the use of Botulinum toxin in the treatment of children with cerebral palsy (CP). A problem-orientated approach was used focussing on both published and practice-based evidence. In part I of the consensus the authors have tabulated the supporting evidence to produce a concise but comprehensive information base, pooling data and experience from 36 institutions in 9 European countries which involves more than 10,000 patients and over 45,000 treatment sessions during a period of more than 280 treatment years. In part II of the consensus the Gross Motor Function Measure (GMFM) and Gross Motor Function Classification System (GMFCS) based Motor Development Curves have been expanded to provide a graphical framework on how to treat the motor disorders in children with CP. This graph is named "CP(Graph) Treatment Modalities - Gross Motor Function" and is intended to facilitate communication between parents, therapists and medical doctors concerning (1) achievable motor function, (2) realistic goal-setting and (3) treatment perspectives for children with CP. The updated European consensus 2009 summarises the current understanding regarding an integrated, multidisciplinary treatment approach using Botulinum toxin for the treatment of children with CP.

Automated detection of fiducial screws from CT/DVT volume data for image-guided ENT surgery

This paper presents an automated solution for precise detection of fiducial screws from three-dimensional (3D) Computerized Tomography (CT)/Digital Volume Tomography (DVT) data for image-guided ENT surgery. Unlike previously published solutions, we regard the detection of the fiducial screws from the CT/DVT volume data as a pose estimation problem. We thus developed a model-based solution. Starting from a user-supplied initialization, our solution detects the fiducial screws by iteratively matching a computer aided design (CAD) model of the fiducial screw to features extracted from the CT/DVT data. We validated our solution on one conventional CT dataset and on five DVT volume datasets, resulting in a total detection of 24 fiducial screws. Our experimental results indicate that the proposed solution achieves much higher reproducibility and precision than the manual detection. Further comparison shows that the proposed solution produces better results on the DVT dataset than on the conventional CT dataset.

Evaluating Code Duplication to Identify Rich Business Objects from Data Transfer Objects

Java Enterprise Applications (JEAs) are complex software systems written using multiple technologies. Moreover they are usually distributed systems and use a database to deal with persistence. A particular problem that appears in the design of these systems is the lack of a rich business model. In this paper we propose a technique to support the recovery of such rich business objects starting from anemic Data Transfer Objects (DTOs). Exposing the code duplications in the application's elements using the DTOs we suggest which business logic can be moved into the DTOs from the other classes.

Methodological issues in quantifying the magnitude of the tuberculosis problem in a prison population

SETTING: Correctional settings and remand prisons. OBJECTIVE: To critically discuss calculations for epidemiological indicators of the tuberculosis (TB) burden in prisons and to provide recommendations to improve study comparability. METHODS: A hypothetical data set illustrates issues in determining incidence and prevalence. The appropriate calculation of the incidence rate is presented and problems arising from cross-sectional surveys are clarifi ed. RESULTS: Cases recognized during the fi rst 3 months should be classifi ed as prevalent at entry and excluded from any incidence rate calculation. The numerator for the incidence rate includes persons detected as having developed TB during a specifi ed period of time subsequent to the initial 3 months. The denominator is persontime at risk from 3 months onward to the end point (TB or end of the observation period). Preferably, entry time, exit time and event time are known for each inmate to determine person-time at risk. Failing that, an approximation consists of the sum of monthly head counts, excluding prevalent cases and those persons no longer at risk from both the numerator and the denominator. CONCLUSIONS: The varying durations of inmate incarceration in prisons pose challenges for quantifying the magnitude of the TB problem in the inmate population. Recommendations are made to measure incidence and prevalence.

Dystonic movement disorders and spinal degenerative disease

The occurrence of degenerative spinal disease subsequent to dystonic movement disorders has been neglected and has received more attention only recently. Spinal surgery is challenging with regard to continuous mechanical stress when treatment of the underlying movement disorder is insufficient. To characterize better the particular features of degenerative spinal disease in patients with dystonia and to analyze operative strategies, we reviewed the available published data. Epidemiologic studies reveal that degenerative spinal disorders in patients with dystonia and choreoathetosis occur much earlier than in the physiological aging process. Dystonic movement disorders more often affect the spine at higher cervical levels (C(2-5)), in contrast to spinal degeneration with age which manifests more frequently at the middle and lower cervical spine (C(5-7)). Degenerative changes of the cervical spine are more likely to occur on the side where the chin is rotated or tilted to. Various operative approaches for treatment of spinal pathologies have been advocated in patients with dystonic movement disorders. The available data do not allow making firm statements regarding the superiority of one approach over the other. Posterior approaches were first used for decompression, but additional anterior fusion became necessary in many instances. Anterior approaches with or without instrumented fusion yielded more favorable results, but drawbacks are pseudarthrosis and adjacent-level disease. Parallel to the development of posterior fusion techniques, circumferential surgery was suggested to provide a maximum degree of cord decompression and a higher fusion rate. Perioperative local injections of botulinum toxin were used initially to enhance patient comfort with halo immobilization, but they are also applied in patients without external fixation nowadays. Treatment algorithms directed at the underlying movement disorder itself, taking advantage of new techniques of functional neurosurgery, combined with spinal surgery have recently been introduced and show promising results.

[Herd problem: udder health. Retrospective study of farms assessed by the Swiss Bovine Health Service (BHS) from 1999 to 2004]

Data from 59 farms with complaints of udder health problems and insufficient quality of delivered milk that had been assessed by the Swiss Bovine Health Service (BHS) between 1999 and 2004 were retrospectively analysed. Data evaluated included farm characteristics such as farm size, herd size, average milk yield, milking system and housing system, deficits of the milking equipment and the milking practices, and bacteriological results of milk samples from all cows in lactation. The average size of the farms assessed by the BHS was larger than the size of the were evaluated, 42 showed obvious failures which the farm managers could have noticed. Only 5 of the 57 milkers carried out their work according to the generally valid guidelines of the National Mastitis Council. More than 2 basic mistakes were observed in the milking practices of 36 milkers. In 51 farms, mixed infections with several problem bacteria (those present in at least 20 % of the tested cows on a farm) were found. Staphylococcus aureus proved to be the most common problem germ. As the bacteria responsible for the herd problem (the sole problem bacteria detectable on a particular farm) Staphylococcus aureus was detected in 4 farms. The current study revealed that education in the area of milking techniques and milking practices of farmers should be improved in order to reduce the incidence of udder health problems on herd level. Staphylococcus aureus is the most important problem bacteria involved in herds with udder health problems in Switzerland. Staphylococcus aureus might be used in practice as the indicator germ for early recognition of management problems in dairy farms.

Virtopsy - the concept of a centralized database in forensic medicine for analysis and comparison of radiological and autopsy data

Recent developments in clinical radiology have resulted in additional developments in the field of forensic radiology. After implementation of cross-sectional radiology and optical surface documentation in forensic medicine, difficulties in the validation and analysis of the acquired data was experienced. To address this problem and for the comparison of autopsy and radiological data a centralized database with internet technology for forensic cases was created. The main goals of the database are (1) creation of a digital and standardized documentation tool for forensic-radiological and pathological findings; (2) establishing a basis for validation of forensic cross-sectional radiology as a non-invasive examination method in forensic medicine that means comparing and evaluating the radiological and autopsy data and analyzing the accuracy of such data; and (3) providing a conduit for continuing research and education in forensic medicine. Considering the infrequent availability of CT or MRI for forensic institutions and the heterogeneous nature of case material in forensic medicine an evaluation of benefits and limitations of cross-sectional imaging concerning certain forensic features by a single institution may be of limited value. A centralized database permitting international forensic and cross disciplinary collaborations may provide important support for forensic-radiological casework and research.

Accurate and robust reconstruction of proximal femur from sparse intraoperative data and dense point distribution model for surgical navigation

Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

The exchange of radiotherapy data as part of an electronic patient-referral system

PURPOSE: To describe the implementation and use of an electronic patient-referral system as an aid to the efficient referral of patients to a remote and specialized treatment center. METHODS AND MATERIALS: A system for the exchange of radiotherapy data between different commercial planning systems and a specially developed planning system for proton therapy has been developed through the use of the PAPYRUS diagnostic image standard as an intermediate format. To ensure the cooperation of the different TPS manufacturers, the number of data sets defined for transfer has been restricted to the three core data sets of CT, VOIs, and three-dimensional dose distributions. As a complement to the exchange of data, network-wide application-sharing (video-conferencing) technologies have been adopted to provide methods for the interactive discussion and assessment of treatments plans with one or more partner clinics. RESULTS: Through the use of evaluation plans based on the exchanged data, referring clinics can accurately assess the advantages offered by proton therapy on a patient-by-patient basis, while the practicality or otherwise of the proposed treatments can simultaneously be assessed by the proton therapy center. Such a system, along with the interactive capabilities provided by video-conferencing methods, has been found to be an efficient solution to the problem of patient assessment and selection at a specialized treatment center, and is a necessary first step toward the full electronic integration of such centers with their remotely situated referral centers.

Hermitian curve interpolation for CT-data re-sampling

Purpose: Development of an interpolation algorithm for re‐sampling spatially distributed CT‐data with the following features: global and local integral conservation, avoidance of negative interpolation values for positively defined datasets and the ability to control re‐sampling artifacts. Method and Materials: The interpolation can be separated into two steps: first, the discrete CT‐data has to be continuously distributed by an analytic function considering the boundary conditions. Generally, this function is determined by piecewise interpolation. Instead of using linear or high order polynomialinterpolations, which do not fulfill all the above mentioned features, a special form of Hermitian curve interpolation is used to solve the interpolation problem with respect to the required boundary conditions. A single parameter is determined, by which the behavior of the interpolation function is controlled. Second, the interpolated data have to be re‐distributed with respect to the requested grid. Results: The new algorithm was compared with commonly used interpolation functions based on linear and second order polynomial. It is demonstrated that these interpolation functions may over‐ or underestimate the source data by about 10%–20% while the parameter of the new algorithm can be adjusted in order to significantly reduce these interpolation errors. Finally, the performance and accuracy of the algorithm was tested by re‐gridding a series of X‐ray CT‐images. Conclusion: Inaccurate sampling values may occur due to the lack of integral conservation. Re‐sampling algorithms using high order polynomialinterpolation functions may result in significant artifacts of the re‐sampled data. Such artifacts can be avoided by using the new algorithm based on Hermitian curve interpolation

Movement control of manipulative tasks in patients with Gilles de la Tourette syndrome

When a hand-held object is moved, grip and load force are accurately coordinated for establishing grasp stability. In the present work, the question was raised whether patients with Gilles de la Tourette syndrome (TS), who show tic-like movements, are impaired in grip-load force control when executing a manipulative task. To this end, we assessed force regulation during action patterns that required rhythmical unimanual or bimanual (iso-directional/anti-directional) movements. Results showed that the profile of grip-load force ratio was characterized by maxima and minima that were realized at upward and downward hand positions, respectively. TS patients showed increased force ratios during unimanual and bimanual movements, compared with control subjects, indicative of an inaccurate specification of the precision grip. Functional imaging data complemented the behavioural results and revealed that secondary motor areas showed no (or greatly reduced) activation in TS patients when executing the movement tasks as compared with baseline conditions. This indicates that the metabolic level in the secondary motor areas was equal during rest and task performance. At the neuronal level, this observation suggests that these cortical areas were continuously involved in movement preparation. Based on these data, we conclude that the ongoing activation of secondary motor areas may be explained by the TS patients' involuntary urges to move. Accordingly, interference will prevent an accurate planning of voluntary behaviour. Together, these findings reveal modulations in movement organization in patients with TS and exemplify degrading consequences for manual function.

Data-driven estimates of the number of clusters in multivariate time series

An important problem in unsupervised data clustering is how to determine the number of clusters. Here we investigate how this can be achieved in an automated way by using interrelation matrices of multivariate time series. Two nonparametric and purely data driven algorithms are expounded and compared. The first exploits the eigenvalue spectra of surrogate data, while the second employs the eigenvector components of the interrelation matrix. Compared to the first algorithm, the second approach is computationally faster and not limited to linear interrelation measures.