Causes and consequences of infant neuromotor development: The Generation R Study

Due to the complexity of the brain, and the many genetic and environmental determinants, there are endless ways in which the brain can develop, leading to at least as many possibilities in the expression of these variations in behaviours or cognitive functioning. Although the study of the brain is as old as science itself, it is just until recently that we have begun to understand more about how the brain works. Historically, scientists who dedicated their work to understanding the central nervous system came from different disciplines: medicine, biology, psychology, physics, chemistry, mathematics. However, the study of the brain has been revolutionized when an interdisciplinary approach was taken, yielding a new synthesized perspective. Similarly, existing knowledge on infant neurological development has increased during the past decades. It is based on insights generated by paediatrics (developmental neurology), movement science and neuropsychology. Currently, neuromotor development is an accepted means of measuring the maturity and intactness of an infant’s central nervous system. Impaired development of the central nervous system in the first year of life is mainly expressed in deviances in neuromotor development

Screening for autism spectrum disorders with the brief infant-toddler social and emotional assessment

Objective: Using parent-completed questionnaires in (preventive) child health care can facilitate the early detection of psychosocial problems and psychopathology, including autism spectrum disorders (ASD). A promising questionnaire for this purpose is the Brief Infant-Toddler Social and Emotional Assessment (BITSEA). The screening accuracy with regard to ASD of the BITSEA Problem and Competence scales and a newly calculated Autism score were evaluated. Method: Data, that was collected between April 2010 and April 2011, from a community sample of 2-year-olds (N = 3127), was combined with a sample of preschool children diagnosed with ASD (N = 159). For the total population and for subgroups by child's gender, area under the Receiver Operating Characteristic (ROC) curve was examined, and across a range of BITSEA Problem, Competence and Autism scores, sensitivity, specificity, positive and negative likelihood ratio's, diagnostic odds ratio and Youden's index were reported. Results: The area under the ROC curve (95% confidence interval, [95%CI]) of the Problem scale was 0.90(0.87-0.92), of the Competence scale 0.93(0.91-0.95), and of the Autism score 0.95(0.93-0.97). For the total population, the screening accuracy of the Autism score was significantly better, compared to the Problem scale. The screening accuracy of the Competence scale was significantly better for girls (AUC = 0.97; 95%CI = 0.95-0.98) than for boys (AUC = 0.91; 95%CI = 0.88-0.94). Conclusion: The results indicate that the BITSEA scales and newly calculated Autism score have good discriminative power to differentiate children with and without ASD. Therefore, the BITSEA may be helpful in the early detection of ASD, which could have beneficial effects on the child's development

The PeptideAtlas project

The completion of the sequencing of the human genome and the concurrent, rapid development of high-throughput proteomic methods have resulted in an increasing need for automated approaches to archive proteomic data in a repository that enables the exchange of data among researchers and also accurate integration with genomic data. PeptideAtlas (http://www.peptideatlas.org/) addresses these needs by identifying peptides by tandem mass spectrometry (MS/MS), statistically validating those identifications and then mapping identified sequences to the genomes of eukaryotic organisms. A meaningful comparison of data across different experiments generated by different groups using different types of instruments is enabled by the implementation of a uniform analytic process. This uniform statistical validation ensures a consistent and high-quality set of peptide and protein identifications. The raw data from many diverse proteomic experiments are made available in the associated PeptideAtlas repository in several formats. Here we present a summary of our process and details about the Human, Drosophila and Yeast PeptideAtlas build

Product-service Systems as a Promising Approach to Sustainability: Exploring the Sustainable Aspects of a PSS in Brazil

AbstractProduct-Service Systems (PSS) represent a business proposition with potential to provide a wide range of economic, environmental, and social benefits, allowing achievingthe sustainability. However, PSS does not necessarily lead to sustainable solutions and this potential must be assessed in each case. In this sense, the aim of this paper is to investigate sustainable aspects of a ‘result oriented PSS’(a reverse osmosis water filter system) available in Brazil and compares it with the conventional product, the bottled water. Some aspects from the literature, mentioned as important in each sustainability dimension, were selected to analyze the PSS under study. A qualitative analysis was performed and demonstrates that in comparison with bottled water, the water filter PSS is competitive, satisfy customer needs, and has a relatively lower environmental impact. However, besides conceiving sustainable solutions, is necessary to identify which factors drive the implementation and diffusion of PSS. Some findings of this study suggest that the effects caused by unexpected consumer behavior and incorrect PSS application may compromise PSS sustainable performance during operational phase. An analysis of these effects during transition process is essential to successful sustainable strategies. The study aimed to contribute to the PSS empirical knowledge and to assist building a theoretical basis regarding PSS and sustainability

The PeptideAtlas project

The completion of the sequencing of the human genome and the concurrent, rapid development of high-throughput proteomic methods have resulted in an increasing need for automated approaches to archive proteomic data in a repository that enables the exchange of data among researchers and also accurate integration with genomic data. PeptideAtlas () addresses these needs by identifying peptides by tandem mass spectrometry (MS/MS), statistically validating those identifications and then mapping identified sequences to the genomes of eukaryotic organisms. A meaningful comparison of data across different experiments generated by different groups using different types of instruments is enabled by the implementation of a uniform analytic process. This uniform statistical validation ensures a consistent and high-quality set of peptide and protein identifications. The raw data from many diverse proteomic experiments are made available in the associated PeptideAtlas repository in several formats. Here we present a summary of our process and details about the Human, Drosophila and Yeast PeptideAtlas builds

Development of an instrument to analyze organizational characteristics in multidisciplinary care pathways:the case of colorectal cancer

Background: To analyze the organization of multidisciplinary care pathways such as colorectal cancer care, an instrument was developed based on a recently published framework that was earlier used in analyzing (monodisciplinary) specialist cataract care from a lean perspective. Methods: The instrument was constructed using semi-structured interviews and direct observation of the colorectal care process based on a Rapid Plant Assessment. Six lean aspects that were earlier established that highly impact process design, were investigated: operational focus, autonomous work cell, physical lay-out of resources, multi-skilled team, pull planning and non-value adding activities. To test reliability, clarity and face validity of the instrument, a pilot study was performed in eight Dutch hospitals.ResultsIn the pilot it proved feasible to apply the instrument and generate the intended information. The instrument consisted of 83 quantitative and 24 qualitative items. Examples of results show differences in operational focus, number of patient visits needed for diagnosis, numbers of staff involved with treatment, the implementation of protocols and utilization of one-stop-shops. Identification of waste and non-value adding activities may need further attention. Based on feedback from involved clinicians the face validity was acceptable and the results provided useful feedback- and benchmark data. The instrument proved to be reliable and valid for broader implementation in Dutch health care. The limited number of cases made statistical analysis not possible and further validation studies may shed better light on variation. Conclusions: This paper demonstrates the use of an instrument to analyze organizational characteristics in colorectal cancer care from a lean perspective. Wider use might help to identify best organizational practices for colorectal surgery. In larger series the instrument might be used for in-depth research into the relation between organization and patient outcomes.Although we found no reason to adapt the underlying framework, recommendations were made for further development to enable use in different tumor- and treatment modalities and in larger (international) samples that allow for more advanced statistical analysis. Waste from defective care or from wasted human potential will need further elaboration of the instrumen

Corra: Computational framework and tools for LC-MS discovery and targeted mass spectrometry-based proteomics

BACKGROUND: Quantitative proteomics holds great promise for identifying proteins that are differentially abundant between populations representing different physiological or disease states. A range of computational tools is now available for both isotopically labeled and label-free liquid chromatography mass spectrometry (LC-MS) based quantitative proteomics. However, they are generally not comparable to each other in terms of functionality, user interfaces, information input/output, and do not readily facilitate appropriate statistical data analysis. These limitations, along with the array of choices, present a daunting prospect for biologists, and other researchers not trained in bioinformatics, who wish to use LC-MS-based quantitative proteomics. RESULTS: We have developed Corra, a computational framework and tools for discovery-based LC-MS proteomics. Corra extends and adapts existing algorithms used for LC-MS-based proteomics, and statistical algorithms, originally developed for microarray data analyses, appropriate for LC-MS data analysis. Corra also adapts software engineering technologies (e.g. Google Web Toolkit, distributed processing) so that computationally intense data processing and statistical analyses can run on a remote server, while the user controls and manages the process from their own computer via a simple web interface. Corra also allows the user to output significantly differentially abundant LC-MS-detected peptide features in a form compatible with subsequent sequence identification via tandem mass spectrometry (MS/MS). We present two case studies to illustrate the application of Corra to commonly performed LC-MS-based biological workflows: a pilot biomarker discovery study of glycoproteins isolated from human plasma samples relevant to type 2 diabetes, and a study in yeast to identify in vivo targets of the protein kinase Ark1 via phosphopeptide profiling. CONCLUSION: The Corra computational framework leverages computational innovation to enable biologists or other researchers to process, analyze and visualize LC-MS data with what would otherwise be a complex and not user-friendly suite of tools. Corra enables appropriate statistical analyses, with controlled false-discovery rates, ultimately to inform subsequent targeted identification of differentially abundant peptides by MS/MS. For the user not trained in bioinformatics, Corra represents a complete, customizable, free and open source computational platform enabling LC-MS-based proteomic workflows, and as such, addresses an unmet need in the LC-MS proteomics field