Proceedings of the 8th Python in Science conference

International audienceThe SciPy conference provides a unique opportunity to learn and affect what is happening in the realm of scientific computing with Python. Attendees have the opportunity to review the available tools and how they apply to specific problems. By providing a forum for developers to share their Python expertise with the wider commercial, academic, and research communities, this conference fosters collaboration and facilitates the sharing of software components, techniques and a vision for high level language use in scientific computing

Evaluating the accuracy of diffusion MRI models in white matter

Models of diffusion MRI within a voxel are useful for making inferences about the properties of the tissue and inferring fiber orientation distribution used by tractography algorithms. A useful model must fit the data accurately. However, evaluations of model-accuracy of some of the models that are commonly used in analyzing human white matter have not been published before. Here, we evaluate model-accuracy of the two main classes of diffusion MRI models. The diffusion tensor model (DTM) summarizes diffusion as a 3-dimensional Gaussian distribution. Sparse fascicle models (SFM) summarize the signal as a linear sum of signals originating from a collection of fascicles oriented in different directions. We use cross-validation to assess model-accuracy at different gradient amplitudes (b-values) throughout the white matter. Specifically, we fit each model to all the white matter voxels in one data set and then use the model to predict a second, independent data set. This is the first evaluation of model-accuracy of these models. In most of the white matter the DTM predicts the data more accurately than test-retest reliability; SFM model-accuracy is higher than test-retest reliability and also higher than the DTM, particularly for measurements with (a) a b-value above 1000 in locations containing fiber crossings, and (b) in the regions of the brain surrounding the optic radiations. The SFM also has better parameter-validity: it more accurately estimates the fiber orientation distribution function (fODF) in each voxel, which is useful for fiber tracking

The NumPy array: a structure for efficient numerical computation

International audienceIn the Python world, NumPy arrays are the standard representation for numerical data. Here, we show how these arrays enable efficient implementation of numerical computations in a high-level language. Overall, three techniques are applied to improve performance: vectorizing calculations, avoiding copying data in memory, and minimizing operation counts. We first present the NumPy array structure, then show how to use it for efficient computation, and finally how to share array data with other libraries

Lack of association between stavudine exposure and lipoatrophy, dysglycaemia, hyperlactataemia and hypertriglyceridaemia: a prospective cross sectional study

<p>Abstract</p> <p>Background</p> <p>Stavudine continues to be widely used in resource poor settings despite its toxicity. Our objective was to determine association between plasma stavudine concentrations and lipoatrophy, concentrations of glucose, lactate and triglycerides.</p> <p>Methods</p> <p>Participants were enrolled in a cross-sectional study with lipoatrophy assessment, oral glucose tolerance test, fasting triglycerides, finger prick lactate, and stavudine concentrations. Individual predictions of the area under the concentration curve (AUC) were obtained using a population pharmacokinetic approach. Logistic regression models were fitted to assess the association between stavudine geometric mean ratio > 1 and impaired fasting glucose, impaired glucose tolerance, hyperlactataemia, hypertriglyceridaemia, and lipoatrophy.</p> <p>Results</p> <p>There were 47 study participants with a median age of 34 years and 83% were women. The median body mass index and waist:hip ratio was 24.5 kg/m²and 0.85 respectively. The median duration on stavudine treatment was 14.5 months. The prevalence of lipoatrophy, impaired fasting glucose, impaired glucose tolerance, hyperlactataemia, and hypertriglyceridaemia were 34%, 19%, 4%, 32%, and 23% respectively. Estimated median (interquartile range) stavudine AUC was 2191 (1957 to 2712) ng*h/mL. Twenty two participants had stavudine geometric mean ratio >1. Univariate logistic regression analysis showed no association between stavudine geometric mean ratio >1 and impaired fasting glucose (odds ratio (OR) 2.00, 95% CI 0.44 to 9.19), impaired glucose tolerance (OR 1.14, 95% CI 0.07 to 19.42), hyperlactataemia (OR 2.19, 95%CI 0.63 to 7.66), hypertriglyceridaemia (OR 1.75, 95%CI 0.44 to 7.04), and lipoatrophy (OR 0.83, 95% CI 0.25 to 2.79).</p> <p>Conclusions</p> <p>There was a high prevalence of metabolic complications of stavudine, but these were not associated with plasma stavudine concentrations. Until there is universal access to safer antiretroviral drugs, there is a need for further studies examining the pathogenesis of stavudine-associated toxicities.</p

Dipy, a library for the analysis of diffusion MRI data

Diffusion Imaging in Python (Dipy) is a free and open source software projectfor the analysis of data from diffusion magnetic resonance imaging (dMRI)experiments. dMRI is an application of MRI that can be used to measurestructural features of brain white matter. Many methods have been developed touse dMRI data to model the local configuration of white matter nerve fiberbundles and infer the trajectory of bundles connecting different parts of thebrain.Dipy gathers implementations of many different methods in dMRI, including:diffusion signal pre-processing; reconstruction of diffusion distributions inindividual voxels; fiber tractography and fiber track post-processing, analysisand visualization. Dipy aims to provide transparent implementations forall the different steps of dMRI analysis with a uniform programming interface.We have implemented classical signal reconstruction techniques, such as thediffusion tensor model and deterministic fiber tractography. In addition,cutting edge novel reconstruction techniques are implemented, such asconstrained spherical deconvolution and diffusion spectrum imaging withdeconvolution, as well as methods for probabilistic tracking and originalmethods for tractography clustering. Many additional utility functions areprovided to calculate various statistics, informative visualizations, as wellas file-handling routines to assist in the development and use of noveltechniques.In contrast to many other scientific software projects, Dipy is not beingdeveloped by a single research group. Rather, it is an open project thatencourages contributions from any scientist/developer through GitHub and opendiscussions on the project mailing list. Consequently, Dipy today has aninternational team of contributors, spanning seven different academic institutionsin five countries and three continents, which is still growing

Japanese subpopulation analysis of MONARCH 2: phase 3 study of abemaciclib plus fulvestrant for treatment of hormone receptor-positive, human epidermal growth factor receptor 2-negative breast cancer that progressed on endocrine therapy

BACKGROUND: This was a Japanese subpopulation analysis of MONARCH 2, a double-blind, randomized, placebo-controlled, phase 3 study of abemaciclib plus fulvestrant in patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative advanced breast cancer (ABC). METHODS: Eligible women had progressed on (neo)adjuvant endocrine therapy (ET),  ≤ 12 months from end of adjuvant ET, or on first-line ET for ABC, and had not received chemotherapy for ABC. Patients were randomized 2:1 to receive abemaciclib or placebo plus fulvestrant. The primary endpoint was progression-free survival (PFS). Secondary endpoints included overall survival (OS), pharmacokinetics (PK), health-related quality of life (HRQoL), and safety. RESULTS: In Japan, 95 patients were randomized (abemaciclib, n = 64; placebo, n = 31). At final PFS analysis (February 14, 2017), median PFS was 21.2 and 14.3 months, respectively, in the abemaciclib and placebo groups (hazard ratio: 0.672; 95% confidence interval: 0.380-1.189). Abemaciclib had a higher objective response rate (37.5%) than placebo (12.9%). PK and safety profiles for Japanese patients were consistent with those of the overall population, without clinically meaningful differences across most HRQoL dimensions evaluated. The most frequent adverse events in the abemaciclib versus placebo groups were diarrhea (95.2 versus 25.8%), neutropenia (79.4 versus 0%), and leukopenia (66.7 versus 0%). At a second data cutoff (June 20, 2019), median OS was not reached with abemaciclib and 47.3 months with placebo (hazard ratio: 0.755; 95% confidence interval: 0.390-1.463). CONCLUSIONS: Results of the Japanese subpopulation were consistent with the improved clinical outcomes and manageable safety profile observed in the overall population. CLINICAL TRIAL REGISTRATION: NCT02107703; U.S. National Library of Medicine: https://clinicaltrials.gov/ct2/show/NCT02107703

Lung Volume, Breathing Pattern and Ventilation Inhomogeneity in Preterm and Term Infants

BACKGROUND: Morphological changes in preterm infants with bronchopulmonary dysplasia (BPD) have functional consequences on lung volume, ventilation inhomogeneity and respiratory mechanics. Although some studies have shown lower lung volumes and increased ventilation inhomogeneity in BPD infants, conflicting results exist possibly due to differences in sedation and measurement techniques. METHODOLOGY/PRINCIPAL FINDINGS: We studied 127 infants with BPD, 58 preterm infants without BPD and 239 healthy term-born infants, at a matched post-conceptional age of 44 weeks during quiet natural sleep according to ATS/ERS standards. Lung function parameters measured were functional residual capacity (FRC) and ventilation inhomogeneity by multiple breath washout as well as tidal breathing parameters. Preterm infants with BPD had only marginally lower FRC (21.4 mL/kg) than preterm infants without BPD (23.4 mL/kg) and term-born infants (22.6 mL/kg), though there was no trend with disease severity. They also showed higher respiratory rates and lower ratios of time to peak expiratory flow and expiratory time (t(PTEF)/t(E)) than healthy preterm and term controls. These changes were related to disease severity. No differences were found for ventilation inhomogeneity. CONCLUSIONS: Our results suggest that preterm infants with BPD have a high capacity to maintain functional lung volume during natural sleep. The alterations in breathing pattern with disease severity may reflect presence of adaptive mechanisms to cope with the disease process