Volumetric analysis of lung nodules in computed tomography (CT): comparison of two different segmentation algorithm softwares and two different reconstruction filters on automated volume calculation.

BACKGROUND A precise detection of volume change allows for better estimating the biological behavior of the lung nodules. Postprocessing tools with automated detection, segmentation, and volumetric analysis of lung nodules may expedite radiological processes and give additional confidence to the radiologists. PURPOSE To compare two different postprocessing software algorithms (LMS Lung, Median Technologies; LungCARE®, Siemens) in CT volumetric measurement and to analyze the effect of soft (B30) and hard reconstruction filter (B70) on automated volume measurement. MATERIAL AND METHODS Between January 2010 and April 2010, 45 patients with a total of 113 pulmonary nodules were included. The CT exam was performed on a 64-row multidetector CT scanner (Somatom Sensation, Siemens, Erlangen, Germany) with the following parameters: collimation, 24x1.2 mm; pitch, 1.15; voltage, 120 kVp; reference tube current-time, 100 mAs. Automated volumetric measurement of each lung nodule was performed with the two different postprocessing algorithms based on two reconstruction filters (B30 and B70). The average relative volume measurement difference (VME%) and the limits of agreement between two methods were used for comparison. RESULTS At soft reconstruction filters the LMS system produced mean nodule volumes that were 34.1% (P < 0.0001) larger than those by LungCARE® system. The VME% was 42.2% with a limit of agreement between -53.9% and 138.4%.The volume measurement with soft filters (B30) was significantly larger than with hard filters (B70); 11.2% for LMS and 1.6% for LungCARE®, respectively (both with P < 0.05). LMS measured greater volumes with both filters, 13.6% for soft and 3.8% for hard filters, respectively (P < 0.01 and P > 0.05). CONCLUSION There is a substantial inter-software (LMS/LungCARE®) as well as intra-software variability (B30/B70) in lung nodule volume measurement; therefore, it is mandatory to use the same equipment with the same reconstruction filter for the follow-up of lung nodule volume.

A Quantitative Analysis of Developer Information Needs in Software Ecosystems

We present the results of an investigation into the nature of information needs of software developers who work in projects that are part of larger ecosystems. This work is based on a quantitative survey of 75 professional software developers. We corroborate the results identified in the sur- vey with needs and motivations proposed in a previous sur- vey and discover that tool support for developers working in an ecosystem context is even more meager than we thought: mailing lists and internet search are the most popular tools developers use to satisfy their ecosystem-related information needs.

Charge density analysis for crystal engineering

This review reports on the application of charge density analysis in the field of crystal engineering, which is one of the most growing and productive areas of the entire field of crystallography. While methods to calculate or measure electron density are not discussed in detail, the derived quantities and tools, useful for crystal engineering analyses, are presented and their applications in the recent literature are illustrated. Potential developments and future perspectives are also highlighted and critically discussed.

Assessing the Potential of Multiple Imputation in Sequence Analysis

Sequence analysis and optimal matching are useful heuristic tools for the descriptive analysis of heterogeneous individual pathways such as educational careers, job sequences or patterns of family formation. However, to date it remains unclear how to handle the inevitable problems caused by missing values with regard to such analysis. Multiple Imputation (MI) offers a possible solution for this problem but it has not been tested in the context of sequence analysis. Against this background, we contribute to the literature by assessing the potential of MI in the context of sequence analyses using an empirical example. Methodologically, we draw upon the work of Brendan Halpin and extend it to additional types of missing value patterns. Our empirical case is a sequence analysis of panel data with substantial attrition that examines the typical patterns and the persistence of sex segregation in school-to-work transitions in Switzerland. The preliminary results indicate that MI is a valuable methodology for handling missing values due to panel mortality in the context of sequence analysis. MI is especially useful in facilitating a sound interpretation of the resulting sequence types.

Modern tools to study nuclear pore complexes and nucleocytoplasmic transport in Caenorhabditis elegans.

The nematode Caenorhabditis elegans is characterized by many features that make it highly attractive to study nuclear pore complexes (NPCs) and nucleocytoplasmic transport. NPC composition and structure are highly conserved in nematodes and being amenable to a variety of genetic manipulations, key aspects of nuclear envelope dynamics can be observed in great details during breakdown, reassembly, and interphase. In this chapter, we provide an overview of some of the most relevant modern techniques that allow researchers unfamiliar with C. elegans to embark on studies of nucleoporins in an intact organism through its development from zygote to aging adult. We focus on methods relevant to generate loss-of-function phenotypes and their analysis by advanced microscopy. Extensive references to available reagents, such as mutants, transgenic strains, and antibodies are equally useful to scientists with or without prior C. elegans or nucleoporin experience.

Multi-Environment Model Estimation for Motility Analysis of Caernorhabditis elegans

The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them quantitatively. Over the past years, C. elegans' motility has been studied across a wide range of environments, including crawling on substrates, swimming in fluids, and locomoting through microfluidic substrates. However, each environment often requires customized image processing tools relying on heuristic parameter tuning. In the present study, we propose a novel Multi-Environment Model Estimation (MEME) framework for automated image segmentation that is versatile across various environments. The MEME platform is constructed around the concept of Mixture of Gaussian (MOG) models, where statistical models for both the background environment and the nematode appearance are explicitly learned and used to accurately segment a target nematode. Our method is designed to simplify the burden often imposed on users; here, only a single image which includes a nematode in its environment must be provided for model learning. In addition, our platform enables the extraction of nematode ‘skeletons’ for straightforward motility quantification. We test our algorithm on various locomotive environments and compare performances with an intensity-based thresholding method. Overall, MEME outperforms the threshold-based approach for the overwhelming majority of cases examined. Ultimately, MEME provides researchers with an attractive platform for C. elegans' segmentation and ‘skeletonizing’ across a wide range of motility assays.

Development of small molecular tools for the cellular study of adenosine receptors

The adenosine receptors are members of the G-protein coupled receptor (GPCR) family which represents the largest class of cell-surface proteins mediating cellular communication. As a result, GPCRs are formidable drug targets and it is estimated that approximately 30% of the marketed drugs act through members of this receptor class. There are four known subtypes of adenosine receptors: A1, A2A, A2B and A3. The adenosine A1 receptor, which is the subject of this presentation, mediates the physiological effects of adenosine in various tissues including the brain, heart, kidney and adipocytes. In the brain for instance, its role in epilepsy and ischemia has been the focus of many studies. Previous attempts to study the biosynthesis, trafficking and agonist-induced internalisation of the adenosine A1 receptor in neurons using fluorescent protein-receptor fusion constructs have been hampered by the sheer size of the fluorescent protein (GFP) that ultimately affected the function of the receptor. We have therefore initiated a research programme to develop small molecule fluorescent agonists that selectively activate the adenosine A1 receptor. Our probe design is based on the endogenous ligand adenosine and the known unselective adenosine receptor agonist NECA. We have synthesised a small library of non-fluorescent adenosine derivatives that have different cyclic and bicyclic moieties at the 6 position of the purine ring and have evaluated the pharmacology of these compounds using a yeast-based assay. This analysis revealed compounds with interesting behaviour, i.e. exhibiting subtype-selectivity and biased signalling, that can be potentially used as tool compounds in their own right for cellular studies of the adenosine A1 receptor. Furthermore, we have also linked fluorescent dyes to the purine ring and discovered fluorescent compounds that can activate the adenosine A1 receptor.

Capacity building in the use of geospatial tools for natural resource management in Tajikistan: Final Report

The Swiss Swiss Consultant Trust Fund (CTF) support covered the period from July to December 2007 and comprised four main tasks: (1) Analysis of historic land degradation trends in the four watersheds of Zerafshan, Surkhob, Toirsu, and Vanj; (2) Translation of standard CDE GIS training materials into Russian and Tajik to enable local government staff and other specialists to use geospatial data and tools; (3) Demonstration of geospatial tools that show land degradation trends associated with land use and vegetative cover data in the project areas, (4) Preliminary training of government staff in using appropriate data, including existing information, global datasets, inexpensive satellite imagery and other datasets and webbased visualization tools like spatial data viewers, etc. The project allowed building of local awareness of, and skills in, up-to-date, inexpensive, easy-to-use GIS technologies, data sources, and applications relevant to natural resource management and especially to sustainable land management. In addition to supporting the implementation of the World Bank technical assistance activity to build capacity in the use of geospatial tools for natural resource management, the Swiss CTF support also aimed at complementing the Bank supervision work on the ongoing Community Agriculture and Watershed Management Project (CAWMP).

Capacity building in the use of geospatial tools for natural resource management in Tajikistan: Inception report BNWPP project

The Centre for Development and Environment (CDE) has been contracted by the World Bank Group to conduct a program on capacity development in use of geospatial tools for natural resource management in Tajikistan. The program aimed to help improving natural resource management by fostering the use of geospatial tools among governmental and non-governmental institutions in Tajikistan. For this purpose a database including a Geographic Information System (GIS) has been prepared, which combines spatial data on various sectors for case study analysis related to the Community Agriculture and Watershed Management Project (CAWMP). The inception report is based on the findings resulting from the Swiss Consultant Trust Fund (CTF) financed project, specifically on the experiences from the awareness creation and training workshop conducted in Dushanbe in November 2007 and the analysis of historical land degradation trends carried out for the four CAWMP watersheds. Furthermore, also recommendations from the inception mission of CDE to Tajikistan (5-20 August 2007) and the inception report for the Swiss CTF support were considered. The inception report for the BNWPP project (The Bank-Netherlands Water Partnership Program) discusses the following project relevant issues: (1) Preliminary list of additional data layers, types of data analysis, and audiences to be covered by BNWPP grant (2) Assessing skills and equipment already available within Tajikistan, and implications for training program and specific equipment procurement plans (3) Updated detailed schedule and plans for all activities to be financed by BNWPP grant, and (4) Proposed list of contents for the final report and web-based presentations.

Towards a spatial understanding of trade-offs in sustainable development: A meso-scale analysis of the nexus between land use, poverty, and environment in the Lao PDR

In land systems, equitably managing trade-offs between planetary boundaries and human development needs represents a grand challenge in sustainability oriented initiatives. Informing such initiatives requires knowledge about the nexus between land use, poverty, and environment. This paper presents results from Lao PDR, where we combined nationwide spatial data on land use types and the environmental state of landscapes with village-level poverty indicators. Our analysis reveals two general but contrasting trends. First, landscapes with paddy or permanent agriculture allow a greater number of people to live in less poverty but come at the price of a decrease in natural vegetation cover. Second, people practising extensive swidden agriculture and living in intact environments are often better off than people in degraded paddy or permanent agriculture. As poverty rates within different landscape types vary more than between landscape types, we cannot stipulate a land use–poverty–environment nexus. However, the distinct spatial patterns or configurations of these rates point to other important factors at play. Drawing on ethnicity as a proximate factor for endogenous development potentials and accessibility as a proximate factor for external influences, we further explore these linkages. Ethnicity is strongly related to poverty in all land use types almost independently of accessibility, implying that social distance outweighs geographic or physical distance. In turn, accessibility, almost a precondition for poverty alleviation, is mainly beneficial to ethnic majority groups and people living in paddy or permanent agriculture. These groups are able to translate improved accessibility into poverty alleviation. Our results show that the concurrence of external influences with local—highly contextual—development potentials is key to shaping outcomes of the land use–poverty–environment nexus. By addressing such leverage points, these findings help guide more effective development interventions. At the same time, they point to the need in land change science to better integrate the understanding of place-based land indicators with process-based drivers of land use change.

Capacity Building in the Use of Geospatial Tools for Natural Resource Management in Tajikistan: Inception report

The sustainable management of natural resources is a key issue for sustainable development of a poor, mountainous country such as Tajikistan. In order to strengthen its agricultural and infrastructural development efforts and alleviate poverty in rural areas, spatial information and analysis are of crucial importance to improve priority setting and decision making efficiency. However, poor access to geospatial data and tools, and limited capacity in their use has greatly constrained the ability of governmental institutions to effectively assess, plan, and monitor natural resources management. The Centre for Development and Environment (CDE) has thus been mandated by the World Bank Group to provide adequate technical support to the Community Agriculture and Watershed Management Project (CAWMP). This support consists of a spatial database on soil degradation trends in 4 watersheds, capacity development in and awareness creation about geographic information technology and a spatial data exchange hub for natural resources management in Tajikistan. CDE’s support has started in July 2007 and will last until December 2007 with a possible extension in 2008.

Analysis of Phenotypic Variation in Childhood Wheezing Disorders

Recurrent wheezing or asthma is a common problem in children that has increased considerably in prevalence in the past few decades. The causes and underlying mechanisms are poorly understood and it is thought that a numb er of distinct diseases causing similar symptoms are involved. Due to the lack of a biologically founded classification system, children are classified according to their observed disease related features (symptoms, signs, measurements) into phenotypes. The objectives of this PhD project were a) to develop tools for analysing phenotypic variation of a disease, and b) to examine phenotypic variability of wheezing among children by applying these tools to existing epidemiological data. A combination of graphical methods (multivariate co rrespondence analysis) and statistical models (latent variables models) was used. In a first phase, a model for discrete variability (latent class model) was applied to data on symptoms and measurements from an epidemiological study to identify distinct phenotypes of wheezing. In a second phase, the modelling framework was expanded to include continuous variability (e.g. along a severity gradient) and combinations of discrete and continuo us variability (factor models and factor mixture models). The third phase focused on validating the methods using simulation studies. The main body of this thesis consists of 5 articles (3 published, 1 submitted and 1 to be submitted) including applications, methodological contributions and a review. The main findings and contributions were: 1) The application of a latent class model to epidemiological data (symptoms and physiological measurements) yielded plausible pheno types of wheezing with distinguishing characteristics that have previously been used as phenotype defining characteristics. 2) A method was proposed for including responses to conditional questions (e.g. questions on severity or triggers of wheezing are asked only to children with wheeze) in multivariate modelling.ii 3) A panel of clinicians was set up to agree on a plausible model for wheezing diseases. The model can be used to generate datasets for testing the modelling approach. 4) A critical review of methods for defining and validating phenotypes of wheeze in children was conducted. 5) The simulation studies showed that a parsimonious parameterisation of the models is required to identify the true underlying structure of the data. The developed approach can deal with some challenges of real-life cohort data such as variables of mixed mode (continuous and categorical), missing data and conditional questions. If carefully applied, the approach can be used to identify whether the underlying phenotypic variation is discrete (classes), continuous (factors) or a combination of these. These methods could help improve precision of research into causes and mechanisms and contribute to the development of a new classification of wheezing disorders in children and other diseases which are difficult to classify.

Decision-Support tools for assessing land degradation and realising sustainable land management, Study Case of El Mkhachbiya Catchment, Northwest of Tunisia

Land degradation is intrinsically complex and involves decisions by many agencies and individuals, land degradation map- ping should be used as a learning tool through which managers, experts and stakeholders can re-examine their views within a wider semantic context. In this paper, we introduce an analytical framework for mapping land degradation, developed by World Overview for Conservation Approaches and technologies (WOCAT) programs, which aims to develop some thematic maps that serve as an useful tool and including effective information on land degradation and conservation status. Consequently, this methodology would provide an important background for decision-making in order to launch rehabilitation/remediation actions in high-priority intervention areas. As land degradation mapping is a problem-solving task that aims to provide clear information, this study entails the implementation of WOCAT mapping tool, which integrate a set of indicators to appraise the severity of land degradation across a representative watershed. So this work focuses on the use of the most relevant indicators for measuring impacts of different degradation processes in El Mkhachbiya catchment, situated in Northwest of Tunisia and those actions taken to deal with them based on the analysis of operating modes and issues of degradation in different land use systems. This study aims to provide a database for surveillance and monitoring of land degradation, in order to support stakeholders in making appropriate choices and judge guidelines and possible suitable recommendations to remedy the situation in order to promote sustainable development. The approach is illustrated through a case study of an urban watershed in Northwest of Tunisia. Results showed that the main land degradation drivers in the study area were related to natural processes, which were exacerbated by human activities. So the output of this analytical framework enabled a better communication of land degradation issues and concerns in a way relevant for policymakers.

Time-varying signal analysis to detect high-altitude periodic breathing in climbers ascending to extreme altitude.

This work investigates the performance of cardiorespiratory analysis detecting periodic breathing (PB) in chest wall recordings in mountaineers climbing to extreme altitude. The breathing patterns of 34 mountaineers were monitored unobtrusively by inductance plethysmography, ECG and pulse oximetry using a portable recorder during climbs at altitudes between 4497 and 7546 m on Mt. Muztagh Ata. The minute ventilation (VE) and heart rate (HR) signals were studied, to identify visually scored PB, applying time-varying spectral, coherence and entropy analysis. In 411 climbing periods, 30-120 min in duration, high values of mean power (MP(VE)) and slope (MSlope(VE)) of the modulation frequency band of VE, accurately identified PB, with an area under the ROC curve of 88 and 89%, respectively. Prolonged stay at altitude was associated with an increase in PB. During PB episodes, higher peak power of ventilatory (MP(VE)) and cardiac (MP(LF)(HR) ) oscillations and cardiorespiratory coherence (MP(LF)(Coher)), but reduced ventilation entropy (SampEn(VE)), was observed. Therefore, the characterization of cardiorespiratory dynamics by the analysis of VE and HR signals accurately identifies PB and effects of altitude acclimatization, providing promising tools for investigating physiologic effects of environmental exposures and diseases.

At risk or not at risk? A meta-analysis of the prognostic accuracy of psychometric interviews for psychosis prediction

An accurate detection of individuals at clinical high risk (CHR) for psychosis is a prerequisite for effective preventive interventions. Several psychometric interviews are available, but their prognostic accuracy is unknown. We conducted a prognostic accuracy meta-analysis of psychometric interviews used to examine referrals to high risk services. The index test was an established CHR psychometric instrument used to identify subjects with and without CHR (CHR+ and CHR-). The reference index was psychosis onset over time in both CHR+ and CHR- subjects. Data were analyzed with MIDAS (STATA13). Area under the curve (AUC), summary receiver operating characteristic curves, quality assessment, likelihood ratios, Fagan's nomogram and probability modified plots were computed. Eleven independent studies were included, with a total of 2,519 help-seeking, predominately adult subjects (CHR+: N=1,359; CHR-: N=1,160) referred to high risk services. The mean follow-up duration was 38 months. The AUC was excellent (0.90; 95% CI: 0.87-0.93), and comparable to other tests in preventive medicine, suggesting clinical utility in subjects referred to high risk services. Meta-regression analyses revealed an effect for exposure to antipsychotics and no effects for type of instrument, age, gender, follow-up time, sample size, quality assessment, proportion of CHR+ subjects in the total sample. Fagan's nomogram indicated a low positive predictive value (5.74%) in the general non-help-seeking population. Albeit the clear need to further improve prediction of psychosis, these findings support the use of psychometric prognostic interviews for CHR as clinical tools for an indicated prevention in subjects seeking help at high risk services worldwide.