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For reconstructing large tomographic datasets fast, filtered backprojection-type or Fourier-based algorithms are still the method of choice, as they have been for decades. These robust and computationally efficient algorithms have been integrated in a broad range of software packages. The continuous mathematical formulas used for image reconstruction in such algorithms are unambiguous. However, variations in discretization and interpolation result in quantitative differences between reconstructed images, and corresponding segmentations, obtained from different software. This hinders reproducibility of experimental results, making it difficult to ensure that results and conclusions from experiments can be reproduced at different facilities or using different software. In this paper, a way to reduce such differences by optimizing the filter used in analytical algorithms is proposed. These filters can be computed using a wrapper routine around a black-box implementation of a reconstruction algorithm, and lead to quantitatively similar reconstructions. Use cases for this approach are demonstrated by computing implementation-adapted filters for several open-source implementations and applying them to simulated phantoms and real-world data acquired at the synchrotron. Our contribution to a reproducible reconstruction step forms a building block towards a fully reproducible synchrotron tomography data processing pipeline., (open access.)

The reconstruction of computed tomography (CT) images is an active area of research. Following the rise of deep learning methods, many data-driven models have been proposed in recent years. In this work, we present the results of a data challenge that we organized, bringing together algorithm experts from different institutes to jointly work on quantitative evaluation of several data-driven methods on two large, public datasets during a ten day sprint. We focus on two applications of CT, namely, low-dose CT and sparse-angle CT. This enables us to fairly compare different methods using standardized settings. As a general result, we observe that the deep learning-based methods are able to improve the reconstruction quality metrics in both CT applications while the top performing methods show only minor differences in terms of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). We further discuss a number of other important criteria that should be taken into account when selecting a method, such as the availability of training data, the knowledge of the physical measurement model and the reconstruction speed.

Background: Although many studies have provided evidence for all-cause mortality attributed to extreme temperature across India, few studies have provided a systematic analysis of the association between all-cause mortality and temperature., Objective: To estimate the risk associated with heat waves during two major heat waves of Nagpur occurred in 2010 and 2014., Methods: The association between temperature and mortality was measured using a distributed lag non-linear model (DLNM) and the attributable deaths associated with the heat waves with forward perspective in the DLNM framework., Results: From the ecological analysis, we found 580 and 306 additional deaths in 2010 and 2014, respectively. Moving average results also gave similar findings. DLNM results showed that the relative risk was 1.5 for the temperature above 45 °C; forward perspective analysis revealed that the attributable deaths during 2010 and 2014 were 505 and 376, respectively. Results from different methods showed that heat waves in different years had variable impacts for various reasons. However, all the results were consistent during 2010 and 2014; there were 30% and 14% extra-mortalities due to heat comparing to non-heat wave years., Conclusion: We strongly recommend the city Government to implement the action plans based on this research outcome to reduce the risk from the heat wave in future.

Weak management is widely recognised as a key impediment to scaling-up coverage of health interventions and ensuring health systems are responsive to population needs. Yet there is scant evidence linking management practices in the public administration to effective health service delivery. We report on the development of a tool to measure management practices in India's district health bureaucracy. We first developed a conceptual framework based on a review of the literature and qualitative interviews with district public health managers. Across 16 management practices, we then drafted and piloted questions to be used with a scoring grid to evaluate process-orientated management practices. We implemented the tool in 34 districts of Maharashtra between April and July 2016, interviewing up to three district public health managers per district (n = 99). Using rigorous psychometric methods, we assessed the acceptability, reliability and validity of the tool. We present three key findings. First, the tool was feasible to implement, response rates were high, and there were no missing data. Second, internal consistency of the tool was high and test-retest reliability was comparable with other management tools used in the literature. Third, there was evidence of validity. The number of staff with a management qualification was positively associated with better management practices. Factor analysis showed that one principal component loaded positively on all the management practices although there was little support for management sub-scales. These findings provide novel evidence on the psychometric properties of a tool designed to measure management practices in the public administration of a developing country. Our framework and tool provide the basis to examine associations between district health management practices and health service delivery, and test the effectiveness of management strengthening interventions in India's public health sector., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

One of the most concerning environmental effects of climate change is rising levels of extreme heat, which already poses serious risks in many parts of the world. In June and July 2015, we collected weekly heat exposure data using area and personal temperature monitoring in Ahmedabad, Gujarat. The study was conducted at four different traffic junctions with a cohort of 16 traffic police. For information on health effects, we administered a baseline survey at the start of the study and prospectively followed up with the officers on prevalence of heat-related symptoms. Wet bulb globe temperature (WBGT) levels ranged from 28.2°C to 36.1°C during the study period. Traffic police workers who participated in this study were exposed to WBGT levels higher than the recommended threshold limit value as per American Conference of Governmental Industrial Hygienists guidelines even beyond the hottest months of the season. Our findings suggest that airport measurements by the Indian Meteorological Department may not accurately capture heat exposures among individuals who work in and alongside high-density traffic junctions. Based on our temperature estimates, traffic police are at risk for heat stress. India is likely to experience warmer temperatures and increased heat waves in the coming decades, fueled by climate change. Therefore, it is important to reduce current and future heat-related risks for traffic police workers and similar occupational risk groups by establishing protection strategies. The protocol established in this study for occupational heat exposure assessment could be applied to a larger cohort., Competing Interests: There are no conflicts of interest.

Indian cities struggle with some of the highest ambient air pollution levels in the world. While national efforts are building momentum towards concerted action to reduce air pollution, individual cities are taking action on this challenge to protect communities from the many health problems caused by this harmful environmental exposure. In 2017, the city of Ahmedabad launched a regional air pollution monitoring and risk communication project, the Air Information and Response (AIR) Plan. The centerpiece of the plan is an air quality index developed by the Indian Institute of Tropical Meteorology’s System for Air Quality and Weather Forecasting and Research program that summarizes information from 10 new continuous air pollution monitoring stations in the region, each reporting data that can help people avoid harmful exposures and inform policy strategies to achieve cleaner air. This paper focuses on the motivation, development, and implementation of Ahmedabad’s AIR Plan. The project is discussed in terms of its collaborative roots, public health purpose in addressing the grave threat of air pollution (particularly to vulnerable groups), technical aspects in deploying air monitoring technology, and broader goals for the dissemination of an air quality index linked to specific health messages and suggested actions to reduce harmful exposures. The city of Ahmedabad is among the first cities in India where city leaders, state government, and civil society are proactively working together to address the country’s air pollution challenge with a focus on public health. The lessons learned from the development of the AIR Plan serve as a template for other cities aiming to address the heavy burden of air pollution on public health. Effective working relationships are vital since they form the foundation for long-term success and useful knowledge sharing beyond a single city.

Epithelial tissues can elongate in two dimensions by polarized cell intercalation, oriented cell division, or cell shape change, owing to local or global actomyosin contractile forces acting in the plane of the tissue. In addition, epithelia can undergo morphogenetic change in three dimensions. We show that elongation of the wings and legs of Drosophila involves a columnar-to-cuboidal cell shape change that reduces cell height and expands cell width. Remodeling of the apical extracellular matrix by the Stubble protease and basal matrix by MMP1/2 proteases induces wing and leg elongation. Matrix remodeling does not occur in the haltere, a limb that fails to elongate. Limb elongation is made anisotropic by planar polarized Myosin-II, which drives convergent extension along the proximal-distal axis. Subsequently, Myosin-II relocalizes to lateral membranes to accelerate columnar-to-cuboidal transition and isotropic tissue expansion. Thus, matrix remodeling induces dynamic changes in actomyosin contractility to drive epithelial morphogenesis in three dimensions., (Copyright © 2018 Elsevier Inc. All rights reserved.)