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Background and AimsAutism spectrum disorder (ASD) is a neurodevelopmental disorder with a higher likelihood of being diagnosed in preterm populations. Likewise, low birthweight has also been connected with an increased likelihood of ASD. The objectives were to study the frequency and define the relationship between ASD, gestational age, birthweight, and growth percentiles for preterm children. MethodsA sample of preterm children with very low birthweight was selected from the Spanish population at 7-10 years old. Families were contacted from the hospital, and they were offered an appointment to conduct a neuropsychological assessment. The children who showed signs of ASD were referred to the diagnostic unit for differential diagnosis. ResultsA total of 57 children completed full assessments, with 4 confirmed ASD diagnoses. The estimated prevalence was 7.02%. There were statistically significant weak correlations between ASD and gestational age (tau b = -0.23), and birthweight (tau b = -0.25), suggesting there is a higher likelihood of developing ASD for those born smaller or earlier in their gestation. ConclusionThese results could improve ASD detection and outcomes for this vulnerable population while also supporting and enhancing previous findings.

Contains fulltext : 244575.pdf (Publisher’s version ) (Open Access) Within pregnancies occurring between 1986 and 2017 in Dutch kidney transplant recipients (KTR), we retrospectively compared short-term maternal and foetal outcomes between patients on calcineurin inhibitor (CNI) based (CNI+) and CNI-free immunosuppression (CNI-). We identified 129 CNI+ and 125 CNI- pregnancies in 177 KTR. Demographics differed with CNI+ having higher body mass index (P = 0.045), shorter transplant-pregnancy interval (P

Objectives This study investigated severe medication errors (MEs) reported to the National Supervisory Authority for Welfare and Health (Valvira) in Finland and evaluated how the incident documentation applies to learning from errors. Methods This study was a retrospective document analysis consisting of medication-related complaints and authoritative statements investigated by Valvira in 2013 to 2017 (n = 58). Results Medication errors caused death or severe harm in 52% (n = 30) of the cases (n = 58). The majority (83%; n = 48) of the incidents concerned patients older than 60 years. Most likely, the errors occurred in prescribing (n = 38; 47%), followed by administration (n = 15; 19%) and monitoring (n = 14; 17%). The error process often included many failures (n = 24; 41%) or more than one health professional (n = 16; 28%). Antithrombotic agents (n = 17; 13%), opioids (n = 10; 8%), and antipsychotics (n = 10; 8%) were the therapeutic groups most commonly involved in the errors. Almost all error cases (91%; n = 53) were assessed as likely or potentially preventable. In 60% (n = 35) of the cases, the organization reported actions taken to improve medication safety after the occurrence of the investigated incident. Conclusions Medication errors reported to the national health care supervisory authority provide a valuable source of risk information and should be used for learning from severe errors at the level of health care systems. High age remains a key risk factor to severe MEs, which may be associated with a wide range of medications including those not typically perceived as high-alert medications or high-risk administration routes. Despite being complex processes, the severe MEs have a great potential to lead to developing systems, processes, resources, and competencies of health care organizations.

The effect of solvent has been investigated for the synthesis of bismuth gallate compounds, of which the water-based bismuth subgallate has been used as an active pharmaceutical ingredient (API) for over a century. Using methanol as a solvent, two new bismuth gallates were acquired: first a flexible 3-periodic metal-organic framework (MOF) forms, which transforms upon extended synthesis times into a layered 2-periodic coordination polymer of the same bismuth-to-gallate ratio. The structures were determined by three-dimensional electron diffraction. Synthesis in ethanol resulted in the formation of the MOF phase, but not the layered phase. The layered material of the methanol-based synthesis was used as a Lewis acid catalyst due to its higher stability, showing a comparatively quick and regiospecific conversion of styrene oxide to 2-methoxy-2-phenylethanol, indicating the presence of open metal sites in the material. The acquisition of bismuth gallate structures of varying periodicity highlights the prospect of acquiring novel MOFs and coordination polymers from the same components of APIs. ispartof: DALTON TRANSACTIONS vol:51 issue:37 pages:14221-14227 ispartof: location:England status: published

STUDY QUESTION Can consensus definitions for the core outcome set for infertility be identified in order to recommend a standardized approach to reporting? SUMMARY ANSWER Consensus definitions for individual core outcomes, contextual statements and a standardized reporting table have been developed. WHAT IS KNOWN ALREADY Different definitions exist for individual core outcomes for infertility. This variation increases the opportunities for researchers to engage with selective outcome reporting, which undermines secondary research and compromises clinical practice guideline development. STUDY DESIGN, SIZE, DURATION Potential definitions were identified by a systematic review of definition development initiatives and clinical practice guidelines and by reviewing Cochrane Gynaecology and Fertility Group guidelines. These definitions were discussed in a face-to-face consensus development meeting, which agreed consensus definitions. A standardized approach to reporting was also developed as part of the process. PARTICIPANTS/MATERIALS, SETTING, METHODS Healthcare professionals, researchers and people with fertility problems were brought together in an open and transparent process using formal consensus development methods. MAIN RESULTS AND THE ROLE OF CHANCE Forty-four potential definitions were inventoried across four definition development initiatives, including the Harbin Consensus Conference Workshop Group and International Committee for Monitoring Assisted Reproductive Technologies, 12 clinical practice guidelines and Cochrane Gynaecology and Fertility Group guidelines. Twenty-seven participants, from 11 countries, contributed to the consensus development meeting. Consensus definitions were successfully developed for all core outcomes. Specific recommendations were made to improve reporting. LIMITATIONS, REASONS FOR CAUTION We used consensus development methods, which have inherent limitations. There was limited representation from low- and middle-income countries. WIDER IMPLICATIONS OF THE FINDINGS A minimum data set should assist researchers in populating protocols, case report forms and other data collection tools. The generic reporting table should provide clear guidance to researchers and improve the reporting of their results within journal publications and conference presentations. Research funding bodies, the Standard Protocol Items: Recommendations for Interventional Trials statement, and over 80 specialty journals have committed to implementing this core outcome set. STUDY FUNDING/COMPETING INTEREST(S) This research was funded by the Catalyst Fund, Royal Society of New Zealand, Auckland Medical Research Fund and Maurice and Phyllis Paykel Trust. Siladitya Bhattacharya reports being the Editor-in-Chief of Human Reproduction Open and an editor of the Cochrane Gynaecology and Fertility Group. J.L.H.E. reports being the Editor Emeritus of Human Reproduction. R.S.L. reports consultancy fees from Abbvie, Bayer, Ferring, Fractyl, Insud Pharma and Kindex and research sponsorship from Guerbet and Hass Avocado Board. B.W.M. reports consultancy fees from Guerbet, iGenomix, Merck, Merck KGaA and ObsEva. C.N. reports being the Editor-in-Chief of Fertility and Sterility and Section Editor of the Journal of Urology, research sponsorship from Ferring, and a financial interest in NexHand. E.H.Y.N. reports research sponsorship from Merck. A.S. reports consultancy fees from Guerbet. J.W. reports being a statistical editor for the Cochrane Gynaecology and Fertility Group. A.V. reports that he is a Statistical Editor of the Cochrane Gynaecology & Fertility Review Group and of the journal Reproduction. His employing institution has received payment from Human Fertilisation and Embryology Authority for his advice on review of research evidence to inform their ‘traffic light’ system for infertility treatment ‘add-ons’. N.L.V. reports consultancy and conference fees from Ferring, Merck and Merck Sharp and Dohme. The remaining authors declare no competing interests in relation to the work presented. All authors have completed the disclosure form. TRIAL REGISTRATION NUMBER Core Outcome Measures in Effectiveness Trials Initiative: 1023.

Numerous discussions have advocated the presence of a so called rabbit-hole (RH) phenomenon on social media, interested in advanced personalization to their users. This phenomenon is loosely understood as a collapse of mainstream recommendations, in favor of ultra personalized ones that lock users into narrow and specialized feeds. Yet quantitative studies are often ignoring personalization, are of limited scale, and rely on manual tagging to track this collapse. This precludes a precise understanding of the phenomenon based on reproducible observations, and thus the continuous audits of platforms. In this paper, we first tackle the scale issue by proposing a user-sided bot-centric approach that enables large scale data collection, through autoplay walks on recommendations. We then propose a simple theory that explains the appearance of these RHs. While this theory is a simplifying viewpoint on a complex and planet-wide phenomenon, it carries multiple advantages: it can be analytically modeled, and provides a general yet rigorous definition of RHs. We define them as an interplay between i) user interaction with personalization and ii) the attraction strength of certain video categories, which cause users to quickly step apart of mainstream recommendations made to fresh user profiles. We illustrate these concepts by highlighting some RHs found after collecting more than 16 million personalized recommendations on YouTube. A final validation step compares our automatically-identified RHs against manually-identified RHs from a previous research work. Together, those results pave the way for large scale and automated audits of the RH effect in recommendation systems., To appear in Social Network Analysis and Mining (Springer)

[EN] Wireless sensor networks (WSNs) are becoming one of the demanding platforms, where sensor nodes are sensing and monitoring the physical or environmental conditions and transmit the data to the base station via multihop routing. Agriculture sector also adopted these networks to promote innovations for environmental friendly farming methods, lower the management cost, and achieve scientific cultivation. Due to limited capabilities, the sensor nodes have suffered with energy issues and complex routing processes and lead to data transmission failure and delay in the sensor-based agriculture fields. Due to these limitations, the sensor nodes near the base station are always relaying on it and cause extra burden on base station or going into useless state. To address these issues, this study proposes a Gateway Clustering Energy-Efficient Centroid- (GCEEC-) based routing protocol where cluster head is selected from the centroid position and gateway nodes are selected from each cluster. Gateway node reduces the data load from cluster head nodes and forwards the data towards the base station. Simulation has performed to evaluate the proposed protocol with state-of-the-art protocols. The experimental results indicated the better performance of proposed protocol and provide more feasible WSN-based monitoring for temperature, humidity, and illumination in agriculture sector., This work has also been partially supported by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) project ERANETMED3-227 SMARTWATIR.

Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis proximity to where data are captured based on artificial intelligence. Edge intelligence aims at enhancing data processing and protects the privacy and security of the data and users. Although recently emerged, spanning the period from 2011 to now, this field of research has shown explosive growth over the past five years. In this article, we present a thorough and comprehensive survey of the literature surrounding edge intelligence. We first identify four fundamental components of edge intelligence, i.e., edge caching, edge training, edge inference, and edge offloading based on theoretical and practical results pertaining to proposed and deployed systems. We then aim for a systematic classification of the state of the solutions by examining research results and observations for each of the four components and present a taxonomy that includes practical problems, adopted techniques, and application goals. For each category, we elaborate, compare, and analyze the literature from the perspectives of adopted techniques, objectives, performance, advantages and drawbacks, and so on. This article provides a comprehensive survey of edge intelligence and its application areas. In addition, we summarize the development of the emerging research fields and the current state of the art and discuss the important open issues and possible theoretical and technical directions.

Even though flooding is a threat to rural communities in plains drained by ephemeral rivers, the magnitude of its impact, coping/prevention mechanisms, and the implications for river management are not well known. In this study, data were collected using a phenomenological‐based research design. Field observations, a questionnaire (n = 440), key informant interviews (10), and one focus group discussion (with seven discussants) were used to collect the desired data from flood‐prone farmers. As the results show, 42% of the respondents believe that flooding has become stronger over the past 20 years, whereas 38% believe there has been no change. As mitigation measures, 52% of the respondents suggested evacuating to neighbouring villages as the best option. Most of the damage was experienced in farmlands (including crops, either harvested or standing) and settlements. As coping mechanisms, 31% of the respondents were displaced, whereas an additional 40% were forced to construct new houses for their settlement. Chi‐square testing showed that the farmers’ responses statistically varied among different groups (p

Background While the methods for conducting health economics research in general are improving, current guidelines provide limited guidance regarding resource use measurement (RUM). Consequently, a variety of methods exists, yet there is no overview of aspects to consider when deciding on the most appropriate RUM methodology. Therefore, this study aims to (1) identify and categorize existing knowledge regarding aspects of RUM, and (2) develop a framework that provides a comprehensive overview of methodological aspects regarding RUM. Methods Relevant articles were identified by enrolling a search string in six databases and handsearching the DIRUM database. Included articles were descriptively reviewed and served as input for a comprehensive framework. Health economics experts were involved during the process to establish the framework’s face validity. Results Forty articles were included in the scoping review. The RUM framework consists of four methodological RUM domains: ‘Whom to measure’, addressing whom to ask and whom to measure; ‘How to measure’, addressing the different approaches of measurement; ‘How often to measure’, addressing recall period and measurement patterns; and ‘Additional considerations’, which covers additional aspects that are essential for further refining the methodologies for measurement. Evidence retrieved from the scoping review was categorized according to these domains. Conclusion This study clustered the aspects of RUM methodology in health economics into a comprehensive framework. The results may guide health economists in their decision making regarding the selection of appropriate RUM methods and developing instruments for RUM. Furthermore, policy makers may use these findings to review study results from an evidence-based perspective. Supplementary Information The online version contains supplementary material available at 10.1007/s40273-021-01048-z.

International audience; The availability of genomic data from extinct homini such as Neanderthals has caused a revolution in palaeontology allowing the identification of modern human-specific protein substitutions. Currently, little is known as to how these substitutions alter the proteins on a molecular level. Here, we investigate adenylosuccinate lyase, a conserved enzyme involved in purine metabolism for which several substitutions in the modern human protein (hADSL) have been described to affect intelligence and behaviour. During evolution, modern humans acquired a specific substitution (Ala429Val) in ADSL distinguishing it from the ancestral variant present in Neanderthals (nADSL). We show here that despite this conservative substitution being solvent exposed and located distant from the active site, there is a difference in thermal stability, but not enzymology or ligand binding between nADSL and hADSL. Substitutions near residue 429 which do not profoundly affect enzymology were previously reported to cause neurological symptoms in humans. This study also reveals that ADSL undergoes conformational changes during catalysis which, together with the crystal structure of a hitherto undetermined product bound conformation, explains the molecular origin of disease for several modern human ADSL mutants.

Serena Oliveri,1 Lucilla Lanzoni,1 Serena Petrocchi,1 Rosanne Janssens,2 Elise Schoefs,2 Isabelle Huys,2 Meredith Y Smith,3,4 Ian P Smith,5 Jorien Veldwijk,5,6 G Ardine de Wit,5 Gabriella Pravettoni1 1Applied Research Division for Cognitive and Psychological Science, IEO, European Institute of Oncology IRCCS, Milan, Italy; 2Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium; 3Alexion Pharmaceuticals, Inc., Boston, MA, USA; 4University of Southern California School of Pharmacy, Los Angeles, CA, USA; 5Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands; 6School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, NetherlandsCorrespondence: Lucilla LanzoniEuropean Institute of Oncology IRCCS, Applied Research Division for Cognitive and Psychological Science, Via Giuseppe Ripamonti, 435, Milano, 20141, ItalyTel +39 294 372054Email lucilla.lanzoni@ieo.itAbstract: The application of web-based and remotely administered surveys is becoming increasingly popular due to the fact that it offers numerous advantages over traditional paper-based or computer-based surveys completed in the presence of the researcher. However, it is unclear whether complex preference elicitation tasks administered online in highly vulnerable patient populations are also feasible. This commentary discusses opportunities and challenges of conducting quantitative patient preference studies in lung cancer patients using web-based modes of data collection. We refer to our recent experience in the context of the Patient Preference in Benefit-Risk Assessments during the Drug Life Cycle (PREFER) project. Among the main advantages were the possibility of reaching a wider and geographically distant population in a shorter timeframe while reducing the financial costs of testing, the greater flexibility offered and the reduced burden on the patients. Some limitations were also identified and should be the object of further research, including the potential lack of inclusiveness of the research, the lack of control over who is completing the survey, a poor comprehension of the study material, and ultimately a lower level of engagement with the study. Despite these limitations, experience from the PREFER project suggests that online quantitative methods for data collection may provide a valuable method to explore preferences in vulnerable patient populations beyond the COVID-19 pandemic.Keywords: discrete choice experiment, swing weighting, web-based survey, educational tool, online data collection, lung cancer

Protein splicing catalyzed by inteins utilizes many different combinations of amino-acid types at active sites. Inteins have been classified into three classes based on their characteristic sequences. We investigated the structural basis of the protein splicing mechanism of class 3 inteins by determining crystal structures of variants of a class 3 intein from Mycobacterium chimaera and molecular dynamics simulations, which suggested that the class 3 intein utilizes a different splicing mechanism from that of class 1 and 2 inteins. The class 3 intein uses a bond cleavage strategy reminiscent of proteases but share the same Hedgehog/INTein (HINT) fold of other intein classes. Engineering of class 3 inteins from a class 1 intein indicated that a class 3 intein would unlikely evolve directly from a class 1 or 2 intein. The HINT fold appears as structural and functional solution for trans-peptidyl and trans-esterification reactions commonly exploited by diverse mechanisms using different combinations of amino-acid types for the active-site residues.

Structural studies of challenging targets such as G protein-coupled receptors (GPCRs) have accelerated during the last several years due to the development of new approaches, including small-wedge and serial crystallography. Here, we describe the deposition of seven datasets consisting of X-ray diffraction images acquired from lipidic cubic phase (LCP) grown microcrystals of two human GPCRs, Cysteinyl leukotriene receptors 1 and 2 (CysLT1R and CysLT2R), in complex with various antagonists. Five datasets were collected using small-wedge synchrotron crystallography (SWSX) at the European Synchrotron Radiation Facility with multiple crystals under cryo-conditions. Two datasets were collected using X-ray free electron laser (XFEL) serial femtosecond crystallography (SFX) at the Linac Coherent Light Source, with microcrystals delivered at room temperature into the beam within LCP matrix by a viscous media microextrusion injector. All seven datasets have been deposited in the open-access databases Zenodo and CXIDB. Here, we describe sample preparation and annotate crystallization conditions for each partial and full datasets. We also document full processing pipelines and provide wrapper scripts for SWSX and SFX data processing., Measurement(s) X-ray diffraction data • protein complex • protein structure data • protein crystallization Technology Type(s) small-wedge synchrotron crystallography • x-ray crystallography assay • X-ray free electron laser serial femtosecond crystallography Factor Type(s) type of G-protein-coupled receptor • type of antagonist Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13128758

Parks and other green spaces are an important part of sustainable, healthy and socially equal urban environment. Urban planning and green space management benefit from information about green space use and values, but such data are often scarce and laborious to collect. Temporally dynamic geographic information generated by different mobile devices and social media platforms are a promising source of data for studying green spaces. User-generated data have, however, platform specific characteristics that limit their potential use. In this article, we compare the ability of different user-generated data sets to provide information on where, when and how people use and value urban green spaces. We compare four types of data: social media, sports tracking, mobile phone operator and public participation geographic information systems (PPGIS) data in a case study from Helsinki, Finland. Our results show that user-generated geographic information sources provide useful insights about being in, moving through and perceiving urban green spaces, as long as evident limitations and sample biases are acknowledged. Social media data highlight patterns of leisure time activities and allow further content analysis. Sports tracking data and mobile phone data capture green space use at different times of the day, including commuting through the parks. PPGIS studies allow asking specific questions from active participants, but might be limited in spatial and temporal extent. Combining information from multiple user-generated data sets complements traditional data sources and provides a more comprehensive understanding of green space use and preferences.

Modern urban-transport planning requires evidence-based insights into current transport flows to better understand the needs and impacts of policymaking. Urban transport includes passenger and freight vehicles, which have different behavior, and the need for such a separation is often ignored in research and practice [1]. New digital data sources provide an opportunity to better understand urban transport and identify where policy interventions are required. We review the literature on digital counting techniques to monitor transport flows, including loops, Automatic-Number Plate Recognition (ANPR) cameras and floating car data. We further investigate the potential of ANPR cameras, which are widely deployed, and which can be augmented with vehicle category information. This article presents the methodology that we follow for transforming raw augmented ANPR camera data into practical knowledge for city planners. Our is aim is to provide a better understanding of passenger and freight vehicle movements and stops, identifying similarities and differences between vehicle categories. We demonstrate our methodology on a case study for the Mechelen-Willebroek district in Belgium, encompassing augmented data from 122 ANPR cameras for a period of two weeks. Additionally, we also look at the car-reduced zone and how time restrictions affect the different vehicle categories’ actions. The findings are validated with GPS data from heavy-good vehicles in the same period. The potential of augmented ANPR camera data and promising themes and applications of this data source are illustrated through the case study.

ObjectivesTo determine the incidence and characteristics of hockey (‘field hockey’) injuries over the course of one outdoor and indoor season. Comparisons of female versus male players, outdoor versus indoor season and match versus practice were performed.MethodsFemale and male teams of the first, second, third, regional and youth divisions were recruited among a local hockey association in Northern Germany, and followed over an indoor and an outdoor season. Exposure times and location, type, severity and cause of injuries during practice and matches were documented by the coaches or medical staff and collected weekly. Prevalence and incidence rates were calculated.ResultsOf the 232 players (mean±SD age 20.7±4.7 years, 68.1% male, 31.9% first division), 84 players (36.2%) suffered 108 new injuries during the season. The overall incidence rate was 3.7 injuries per 1000 player hours (95% CI 3.0 to 4.4). The injury incidence was lower in practice (2.7 per 1000 player practice hours, 95% CI 2.0 to 3.3) than in matches (9.7 per 1000 player match hours, 95% CI 6.8 to 12.7), and was similar for female and male players as well as during the outdoor and the indoor season. Most injuries affected the lower limb (thigh, knee and ankle) and occurred without contact (58.3%). Severe injuries (n=34; 31.5%) were predominantly located at the knee and hand/finger.ConclusionHockey players have a high prevalence and incidence of injuries, especially at the lower limb.

STUDY QUESTION: Does Day-3 cleavage-stage PGS affect neurodevelopment of 9-year-old IVF offspring?SUMMARY ANSWER: We did not find evidence of adverse consequences of Day-3 cleavage-stage PGS on neurodevelopment of 9-year-old IVF offspring, although children born after IVF with or without PGS often had a non-optimal neurological condition.WHAT IS KNOWN ALREADY: Knowledge on long-term sequelae for development and health of children born following PGS is lacking. This is striking as evidence accumulates that IVF itself is associated with increased risk for impaired health and development in the offspring.STUDY DESIGN SIZE, DURATION: This prospective, assessor-blinded, multicentre, follow-up study evaluated development and health of 9-year-old IVF children born to women who were randomly assigned to IVF with PGS (PGS group) or without PGS (control group). The follow-up examination at 9 years took place between March 2014 and May 2016.PARTICIPANTS/MATERIALS, SETTING, METHODS: In total, 408 women were included and randomly assigned to IVF with or without Day-3 cleavage-stage PGS. This resulted in 52 ongoing pregnancies in the PGS group and 74 in the control group. In the PGS group, 59 children were born alive; in the control group, 85 children were born alive. At the age of 9 years, 43 children born after PGS and 56 control children participated in the study. Our primary outcome was the neurological optimality score, a sensitive measure of neurological condition assessed with a standardized, age-specific test (Touwen test). Secondary outcomes were adverse neurological condition (neurologically abnormal and the complex form of minor neurological dysfunction), cognitive development (intelligence quotient and specific domains), behaviour (parental and teacher's questionnaires), blood pressure and anthropometrics.MAIN RESULTS AND THE ROLE OF CHANCE: Neurodevelopmental outcome of PGS children did not differ from that of controls; the neurological optimality scores (mean values [(95% CI]: PGS children 51.5 [49.3; 53.7], control children 53.1 [50.5; 55.7]) were not significantly different. The prevalences of adverse neurological outcome (in all but one child implying the presence of the complex form of minor neurological dysfunction) did not differ between the groups (PGS group 17/43 [40%], control group 19/56 [34%]), although the prevalence of complex minor neurological dysfunction in both groups was rather high. Also intelligence quotient scores of the two groups were not significantly different (PGS group 114 [108; 120]); control group 117 [109; 125]), and the behaviour, blood pressure and anthropometrics of both groups did not differ. Mean blood pressures of both groups were above the 60th percentile.LIMITATIONS REASONS FOR CAUTION: The power analysis of the study was not based on the number of children needed for the follow-up study, but on the number of women who were needed to detect an increase in ongoing pregnancy rates after PGS. In addition, our study evaluated embryo biopsy in the form of PGS at cleavage stage (Day-3 embryo biopsy), while currently PGS at blastocyst stage (Day-5 embryo biopsy) is recommended and increasingly being used.WIDER IMPLICATIONS OF THE FINDINGS: Our findings indicate that PGS in cleavage stage embryos is not associated with adverse effects on neurological, cognitive and behavioural development, blood pressure and anthropometrics of offspring at 9 years. This is a reassuring finding as embryo biopsy in the forms of PGS and PGD is increasingly applied. However, both groups of IVF offspring showed high prevalences of the clinically relevant form of minor neurological dysfunction, which is a point of concern for the IVF community. In addition, our study confirms findings of others that IVF offspring may be at risk of an unfavourable cardiovascular outcome. These findings are alarming and highlight the importance of research on the underlying mechanisms of unfavourable neurodevelopmental and cardiovascular outcomes in IVF offspring.STUDY FUNDING/COMPETING INTEREST(S): The randomized controlled trial was financially supported by the Organization for Health Research and Development (ZonMw), The Netherlands (Grant number 945-03-013). The follow-up was financially supported by the University Medical Center Groningen (Grant number: 754510), the Cornelia Foundation, and the graduate schools BCN and Share, Groningen, The Netherlands. The sponsors of the study had no role in study design, data collection, data analysis, data interpretation or writing of the report. There are no conflicts of interest.TRIAL REGISTRATION NUMBER: ISRCTN76355836.

International audience; The number of Life Cycle Assessment (LCA) studies on foods and diets steadily increases. However, due to lack of data on food products as well as time and resource constraints, many of these studies ignore part of the system (e.g. cooking and waste in the household), which may lead to underestimating impacts greatly. This LCA study compared diets using six methods with different system boundaries; three of these are simplified methods we developed. The aim was to identify which method best optimizes data collection for life cycle inventories from cradle to human mouth of food products and diets. The principle behind the three simplified methods was that, for many foods and impact categories, the farm (or fishery) is the life cycle stage that contributes most to impacts. One average, one healthy and one vegetarian diet, each composed of up to 105 foods, were assessed. Climate change, cumulative energy demand, eutrophication, acidification and land occupation impacts were estimated. Recommendations are given on which methods, depending on study goals, offer the best trade-off among available resources (time, money, and knowledge), while providing the required robustness of results. Compared to a full LCA, simplified LCA methods can yield more accurate results at a lower cost of data collection.

Firms operating multiple channels as parallel routes to market face intense pressure to ensure superior customer satisfaction in their entire channel system. Relying on the structural alignment framework, the authors argue that to address this challenge, providers of concurrent channels should give priority to alignable channel attributes—attributes that have corresponding or “mirror” attributes in the other channels. These features are more salient to customers than nonalignable features and likely represent the origin of satisfaction evaluations in concurrent channel environments. Applying multigroup nested models using data from off-line and online shoppers, the authors empirically validate choice (assortment breadth and depth), charge (availability of fair prices), convenience (efficiency of the purchase process), confidence (security of transactions), and care (assurance of promised quality) as alignable channel facets. The resulting 5C model is superior to existing models in that it enables the unified capture of both off-line and online satisfaction, allowing a meaningful comparison across formats. Using alignable satisfaction facets enables managers to trace true differences in the satisfaction levels between channels. In particular, a channel’s share of investment should match its share of unexploited satisfaction potential. The 5C model also supports within-channel decisions by revealing the impact of the five facets on overall satisfaction with each format.

Background: People living with HIV (PLWH) experience a higher cardiovascular disease (CVD) risk. Yet, traditional algorithms are often used to estimate CVD risk. We evaluated the performance of 4 commonly used algorithms.Setting: The Netherlands.Methods: We used data from 16,070 PLWH aged > 18 years, who were in care between 2000 and 2016, had no pre-existing CVD, had initiated first combination antiretroviral therapy >1 year ago, and had available data on CD4 count, smoking status, cholesterol, and blood pressure. Predictive performance of 4 algorithms [Data Collection on Adverse Effects of Anti-HIV Drugs Study (D: A: D); Systematic COronary Risk Evaluation adjusted for national data (SCORE-NL); Framingham CVD Risk Score (FRS); and American College of Cardiology and American Heart Association Pooled Cohort Equations (PCE)] was evaluated using a Kaplan-Meier approach. Model discrimination was assessed using Harrell's C-statistic. Calibration was assessed using observed-versusexpected ratios, calibration plots, and Greenwood-Nam-D'Agostino goodness-of-fit tests.Results: All algorithms showed acceptable discrimination (Harrell's C-statistic 0.73-0.79). On a population level, D: A: D, SCORE-NL, and PCE slightly underestimated, whereas FRS slightly overestimated CVD risk (observed-versus-expected ratios 1.35, 1.38, 1.14, and 0.92, respectively). D: A: D, FRS, and PCE best fitted our data but still yielded a statistically significant lack of fit (Greenwood-Nam-D'Agostino chi(2) ranged from 24.57 to 34.22, P Conclusions: All algorithms perform reasonably well in PLWH, with SCORE-NL performing poorest. Prediction algorithms are useful for clinical practice, but clinicians should be aware of their limitations (ie, lack of fit and slight underestimation of CVD risk in low-risk groups).

Background The Epi-Info software suite, built and maintained by the Centers for Disease Control and Prevention (CDC), is widely used by epidemiologists and public health researchers to collect and analyze public health data, especially in the event of outbreaks such as Ebola and Zika. As it exists today, Epi-Info Desktop runs only on the Windows platform, and the larger Epi-Info Suite of products consists of separate codebases for several different devices and use-cases. Software portability has become increasingly important over the past few years as it offers a number of obvious benefits. These include reduced development time, reduced cost, and simplified system architecture. Thus, there is a blatant need for continued research. Specifically, it is critical to fully understand any underlying negative performance issues which arise from platform-agnostic systems. Such understanding should allow for improved design, and thus result in substantial mitigation of reduced performance. In this paper, we present a viable cross-platform architecture for Epi-Info which solves many of these problems. Results We have successfully generated executables for Linux, Mac, and Windows from a single code-base, and we have shown that performance need not be completely sacrificed when building a cross-platform application. This has been accomplished by using Electron as a wrapper for an AngularJS app, a Python analytics module, and a local, browser-based NoSQL database. Conclusions Promising results warrant future research. Specifically, the design allows for cross-platform form-design, data-collection, offline/online modes, scalable storage, automatic local-to-remote data sync, and fast analytics which rival more traditional approaches.

International audience; Battery lifetime is a key impediment to long-lasting low power sensor nodes and networks thereof. Energy harvesting—conversion of ambient energy into electrical energy—has emerged as a viable alternative to battery power. Indeed, the harvested energy mitigates the dependency on battery power and can be used to transmit data. However, unfair data delivery delay and energy expenditure among sensors remain important issues for such networks. We study performance of sensor networks with mobile sinks: a mobile sink moves towards the transmission range of the different static sensor nodes to collect their data. We propose and analyse a Markovian queueing system to study the impact of uncertainty in energy harvesting, energy expenditure, data acquisition and data transmission. In particular, the energy harvesting sensor node is described by a system with two queues, one queue corresponding to the battery and the other to the data buffer. We illustrate our approach by numerical examples which show that energy harvesting correlation considerably affects performance measures like the mean data delay and the effective data collection rate.

Objective: The objectives of this article are first to give an overview of the risks of bias in trial-based economic evaluations and, second, to identify how key sources for bias can be revealed and overcome (i.e. what bias-reducing strategies might be employed) in future trial-based economic evaluations in the field of health psychology. Design: Narrative review discussing sources of bias in trial-based economic evaluations and bias-reducing strategies. Results: We identified 11 biases and assigned them to a particular trial phase. A distinction is made between pre-trial biases, biases during the trial and biases that are relevant after the actual trial. All potential forms of bias are discussed in detail and strategies are shown to detect and overcome these biases. Conclusion: In order to avoid bias in trial-based economic evaluations, one has to be aware of all the possible forms of bias. All stakeholders have to examine trial-based economic evaluations in a rigorous and stringent manner. This article can be helpful in this examination as it gives an overview of the possible biases which researchers should take into account.

Inspired by recent industrial efforts towards high altitude flying wireless access points powered by renewable energy, an online resource allocation problem for a mobile access point travelling at high altitude is formulated. The access point allocates its resources (available energy) to maximise the total utility (reward) provided to a sequentially observed set of users demanding service. The problem is formulated as a 0/1 dynamic knapsack problem with incremental capacity over a finite time horizon, and the solution of which is quite open in the literature. We address the problem through deterministic and stochastic formulations followed by a model where the statistics of the underlying processes are not known and learned through rule-based and neural network approaches. For the deterministic problem, several online approximations including optimisation via genetic algorithm and rule-based approach are proposed based on an instantaneous threshold that can adapt to short-time-scale dynamics. For the stochastic model, after showing the optimality of a threshold-based solution on a dynamic programming formulation, an approximate threshold-based policy is obtained. The performances of proposed policies are compared with that of the optimal solution obtained through dynamic programming. Copyright (C) 2016 John Wiley & Sons, Ltd., E. Uysal-Biyikoglu was supported by a Science Academy BAGEP award and in part through the E-CROPS project funded by TUBITAK.

Ultrafast pump-probe X-ray crystallography has now been established at X-ray free electron lasers that operate at hard X-ray energies. We discuss the performance and development of current applications in terms of the available data quality and sensitivity to detect and analyse structural dynamics. A discussion of technical capabilities expected at future high repetition rate applications as well as future non-collinear multi-pulse schemes focuses on the possibility to advance the technique to the practical application of the X-ray crystallographic equivalent of an impulse time-domain Raman measurement of vibrational coherence. Furthermore, we present calculations of the magnitude of population differences and distributions prepared with ultrafast optical pumping of single crystals in the typical serial femtosecond crystallography geometry, which are developed for the general uniaxial and biaxial cases. The results present opportunities for polarization resolved anisotropic X-ray diffraction analysis of photochemical populations for the ultrafast time domain. This article is part of the theme issue ‘Measurement of ultrafast electronic and structural dynamics with X-rays’.

For more than 20 years, the development community has claimed that monitoring and evaluation helps projects achieve their objectives. This study uses data from 1,300 World Bank projects evaluated between 2008 and 2014 to investigate this suggested link between the quality of monitoring and evaluation and project performance. The propensity score matching results indicate that the quality of monitoring and evaluation is significantly and positively associated with project outcome as institutionally measured at the World Bank. This positive relationship holds when controlling for project manager identity, and is robust to various specification choices. Through a systematic text analysis of the narrative produced by the Independent Evaluation Group to justify its monitoring and evaluation quality rating, the study shows that there are common markers of good quality monitoring and evaluation, such as: clear institutional setup and division of labor around monitoring and evaluation activities; simple monitoring and evaluation framework that is well aligned with clients' existing monitoring and evaluation systems; good integration with operational tasks; and a system that can generate regular and timely reporting, and that is used during and after lending.

©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The vision of the Internet of Things (IoT) to interconnect and Internet-connect everyday people, objects, and machines poses new challenges in the design of wireless communication networks. The design of medium access control (MAC) protocols has been traditionally an intense area of research due to their high impact on the overall performance of wireless communications. The majority of research activities in this field deal with different variations of protocols somehow based on ALOHA, either with or without listen before talk, i.e., carrier sensing multiple access. These protocols operate well under low traffic loads and low number of simultaneous devices. However, they suffer from congestion as the traffic load and the number of devices increase. For this reason, unless revisited, the MAC layer can become a bottleneck for the success of the IoT. In this paper, we provide an overview of the existing MAC solutions for the IoT, describing current limitations and envisioned challenges for the near future. Motivated by those, we identify a family of simple algorithms based on distributed queueing (DQ), which can operate for an infinite number of devices generating any traffic load and pattern. A description of the DQ mechanism is provided and most relevant existing studies of DQ applied in different scenarios are described in this paper. In addition, we provide a novel performance evaluation of DQ when applied for the IoT. Finally, a description of the very first demo of DQ for its use in the IoT is also included in this paper.

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There is accumulating evidence that reaction times (RTs) can be used to detect recognition of critical (e.g., crime) information. A limitation of this research base is its reliance upon small samples (average n = 24), and indications of publication bias. To advance RT-based memory detection, we report upon the development of the first web-based memory detection test. Participants in this research (Study1: n = 255; Study2: n = 262) tried to hide 2 high salient (birthday, country of origin) and 2 low salient (favourite colour, favourite animal) autobiographical details. RTs allowed to detect concealed autobiographical information, and this, as predicted, more successfully so than error rates, and for high salient than for low salient items. While much remains to be learned, memory detection 2.0 seems to offer an interesting new platform to efficiently and validly conduct RT-based memory detection research.