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A Randomized Controlled Trial of the Effectiveness of Computer-Assisted Cognitive Remediation (CACR) in Adolescents with Psychosis or at High Risk of Psychosis.

Background: Computer assisted cognitive remediation (CACR) was demonstrated to be efficient in improving cognitive deficits in adults with psychosis. However, scarce studies explored the outcome of CACR in adolescents with psychosis or at high risk. Aims: To investigate the effectiveness of a computer-assisted cognitive remediation (CACR) program in adolescents with psychosis or at high risk. Method: Intention to treat analyses included 32 adolescents who participated in a blinded 8-week randomized controlled trial of CACR treatment compared to computer games (CG). Cognitive abilities, symptoms and psychosocial functioning were assessed at baseline and posttreatment. Results: Improvement in visuospatial abilities was significantly greater in the CACR group than in CG. Other cognitive functions, psychotic symptoms and psychosocial functioning improved significantly, but at similar rates, in the two groups. Conclusion: CACR can be successfully administered in this population; it proved to be effective over and above CG for the most intensively trained cognitive ability.

Optimization of HS-SPME/GC-MS analysis and its use in the profiling of illicit ecstasy tablets (Part 1)

A headspace solid-phase microextraction procedure (HS-SPME) was developed for the profiling of traces present in 3,4-methylenedioxymethylampethamine (MDMA). Traces were first extracted using HS-SPME and then analyzed by gas chromatography-mass spectroscopy (GC-MS). The HS-SPME conditions were optimized using varying conditions. Optimal results were obtained when 40 mg of crushed MDMA sample was heated at 80 °C for 15 min, followed by extraction at 80 °C for 15 min with a polydimethylsiloxane/divinylbenzene coated fibre. A total of 31 compounds were identified as traces related to MDMA synthesis, namely precursors, intermediates or by-products. In addition some fatty acids used as tabletting materials and caffeine used as adulterant, were also detected. The use of a restricted set of 10 target compounds was also proposed for developing a screening tool for clustering samples having close profile. 114 seizures were analyzed using an SPME auto-sampler (MultiPurpose Samples MPS2), purchased from Gerstel GMBH & Co. (Germany), and coupled to GC-MS. The data was handled using various pre-treatment methods, followed by the study of similarities between sample pairs based on the Pearson correlation. The results show that HS-SPME, coupled with the suitable statistical method is a powerful tool for distinguishing specimens coming from the same seizure and specimens coming from different seizures. This information can be used by law enforcement personnel to visualize the ecstasy distribution network as well as the clandestine tablet manufacturing.

Evaluation of a computer model to simulate water table response to subirrigation

The objective of this work was to evaluate the water flow computer model, WATABLE, using experimental field observations on water table management plots from a site located near Hastings, FL, USA. The experimental field had scale drainage systems with provisions for subirrigation with buried microirrigation and conventional seepage irrigation systems. Potato (Solanum tuberosum L.) growing seasons from years 1996 and 1997 were used to simulate the hydrology of the area. Water table levels, precipitation, irrigation and runoff volumes were continuously monitored. The model simulated the water movement from a buried microirrigation line source and the response of the water table to irrigation, precipitation, evapotranspiration, and deep percolation. The model was calibrated and verified by comparing simulated results with experimental field observations. The model performed very well in simulating seasonal runoff, irrigation volumes, and water table levels during crop growth. The two-dimensional model can be used to investigate different irrigation strategies involving water table management control. Applications of the model include optimization of the water table depth for each growth stage, and duration, frequency, and rate of irrigation.

Computer-Aided Business Model Design

There is a lack of dedicated tools for business model design at a strategic level. However, in today's economic world the need to be able to quickly reinvent a company's business model is essential to stay competitive. This research focused on identifying the functionalities that are necessary in a computer-aided design (CAD) tool for the design of business models in a strategic context. Using design science research methodology a series of techniques and prototypes have been designed and evaluated to offer solutions to the problem. The work is a collection of articles which can be grouped into three parts: First establishing the context of how the Business Model Canvas (BMC) is used to design business models and explore the way in which CAD can contribute to the design activity. The second part extends on this by proposing new technics and tools which support elicitation, evaluation (assessment) and evolution of business models design with CAD. This includes features such as multi-color tagging to easily connect elements, rules to validate coherence of business models and features that are adapted to the correct business model proficiency level of its users. A new way to describe and visualize multiple versions of a business model and thereby help in addressing the business model as a dynamic object was also researched. The third part explores extensions to the business model canvas such as an intermediary model which helps IT alignment by connecting business model and enterprise architecture. And a business model pattern for privacy in a mobile environment, using privacy as a key value proposition. The prototyped techniques and proposition for using CAD tools in business model modeling will allow commercial CAD developers to create tools that are better suited to the needs of practitioners.

Sensitive gene expression profiling of human T cell subsets reveals parallel post-thymic differentiation for CD4+ and CD8+ lineages.

The differentiation of CD4(+) or CD8(+) T cells following priming of naive cells is central in the establishment of the immune response against pathogens or tumors. However, our understanding of this complex process and the significance of the multiple subsets of differentiation remains controversial. Gene expression profiling has opened new directions of investigation in immunobiology. Nonetheless, the need for substantial amount of biological material often limits its application range. In this study, we have developed procedures to perform microarray analysis on amplified cDNA from low numbers of cells, including primary T lymphocytes, and applied this technology to the study of CD4 and CD8 lineage differentiation. Gene expression profiling was performed on samples of 1000 cells from 10 different subpopulations, defining the major stages of post-thymic CD4(+) or CD8(+) T cell differentiation. Surprisingly, our data revealed that while CD4(+) and CD8(+) T cell gene expression programs diverge at early stages of differentiation, they become increasingly similar as cells reach a late differentiation stage. This suggests that functional heterogeneity between Ag experienced CD4(+) and CD8(+) T cells is more likely to be located early during post-thymic differentiation, and that late stages of differentiation may represent a common end in the development of T-lymphocytes.

Paper 5: Surveillance of multiple congenital anomalies: implementation of a computer algorithm in European registers for classification of cases.

BACKGROUND: Surveillance of multiple congenital anomalies is considered to be more sensitive for the detection of new teratogens than surveillance of all or isolated congenital anomalies. Current literature proposes the manual review of all cases for classification into isolated or multiple congenital anomalies. METHODS: Multiple anomalies were defined as two or more major congenital anomalies, excluding sequences and syndromes. A computer algorithm for classification of major congenital anomaly cases in the EUROCAT database according to International Classification of Diseases (ICD)v10 codes was programmed, further developed, and implemented for 1 year's data (2004) from 25 registries. The group of cases classified with potential multiple congenital anomalies were manually reviewed by three geneticists to reach a final agreement of classification as "multiple congenital anomaly" cases. RESULTS: A total of 17,733 cases with major congenital anomalies were reported giving an overall prevalence of major congenital anomalies at 2.17%. The computer algorithm classified 10.5% of all cases as "potentially multiple congenital anomalies". After manual review of these cases, 7% were agreed to have true multiple congenital anomalies. Furthermore, the algorithm classified 15% of all cases as having chromosomal anomalies, 2% as monogenic syndromes, and 76% as isolated congenital anomalies. The proportion of multiple anomalies varies by congenital anomaly subgroup with up to 35% of cases with bilateral renal agenesis. CONCLUSIONS: The implementation of the EUROCAT computer algorithm is a feasible, efficient, and transparent way to improve classification of congenital anomalies for surveillance and research.

Gene expression profiling in human pathogenic dermatophytes in vitro and in vivo

Objectives: Dermatophytes are highly specialized fungi which are the most common agents of superficial mycoses in humans and animals. The particular ability of these microorganisms to invade and multiply within keratinized host structures is presumably linked to their secreted keratinolytic activity, which is therefore a major putative virulence attribute of these fungi. The overall adaptation and transcriptional response of dermatophytes during protein degradation and/or infection is largely unknown. Methods: A Trichophyton rubrum cDNA microarray was developed and used for the transcriptional analysis of T. rubrum and Arthroderma benhamiae cells during growth on protein substrates. Moreover, the gene expression profile in A. benhamiae cells was monitored during infection of guinea pigs. Results: T. rubrum and A. benhamiae cells activate a large set of genes encoding secreted endo- and exoproteases during growth on soy and keratin. In addition, other specifically induced factors with potential implication in protein utilization were identified, e.g. multiple transporters, metabolic enzymes, transcription factors and hypothetical proteins with unknown function. Notably however, the protease gene expression profile in the fungal cells during infection was significantly different from the pattern elicited during in vitro growth on keratin. Conclusions: Our results suggest specific functions of individual proteases during infection, which may not be restricted to the degradation of keratin. This first, broad in vivo transcriptional profiling approach in dermatophytes gives new molecular insights into pathogenicity associated adaptation mechanisms that make these microorganisms the most successful causitive agents of superficial mycoses.

CleanEx: a database of heterogeneous gene expression data based on a consistent gene nomenclature.

The main goal of CleanEx is to provide access to public gene expression data via unique gene names. A second objective is to represent heterogeneous expression data produced by different technologies in a way that facilitates joint analysis and cross-data set comparisons. A consistent and up-to-date gene nomenclature is achieved by associating each single experiment with a permanent target identifier consisting of a physical description of the targeted RNA population or the hybridization reagent used. These targets are then mapped at regular intervals to the growing and evolving catalogues of human genes and genes from model organisms. The completely automatic mapping procedure relies partly on external genome information resources such as UniGene and RefSeq. The central part of CleanEx is a weekly built gene index containing cross-references to all public expression data already incorporated into the system. In addition, the expression target database of CleanEx provides gene mapping and quality control information for various types of experimental resource, such as cDNA clones or Affymetrix probe sets. The web-based query interfaces offer access to individual entries via text string searches or quantitative expression criteria. CleanEx is accessible at: http://www.cleanex.isb-sib.ch/.

The Learning Affect Monitor (LAM) - A computer-based system integrating quantitative and qualitative assessment of affective states in daily life.

The Learning Affect Monitor (LAM) is a new computer-based assessment system integrating basic dimensional evaluation and discrete description of affective states in daily life, based on an autonomous adapting system. Subjects evaluate their affective states according to a tridimensional space (valence and activation circumplex as well as global intensity) and then qualify it using up to 30 adjective descriptors chosen from a list. The system gradually adapts to the user, enabling the affect descriptors it presents to be increasingly relevant. An initial study with 51 subjects, using a 1 week time-sampling with 8 to 10 randomized signals per day, produced n = 2,813 records with good reliability measures (e.g., response rate of 88.8%, mean split-half reliability of .86), user acceptance, and usability. Multilevel analyses show circadian and hebdomadal patterns, and significant individual and situational variance components of the basic dimension evaluations. Validity analyses indicate sound assignment of qualitative affect descriptors in the bidimensional semantic space according to the circumplex model of basic affect dimensions. The LAM assessment module can be implemented on different platforms (palm, desk, mobile phone) and provides very rapid and meaningful data collection, preserving complex and interindividually comparable information in the domain of emotion and well-being.

Gene expression profiling of rat spermatogonia and Sertoli cells reveals signaling pathways from stem cells to niche and testicular cancer cells to surrounding stroma.

Background: Stem cells and their niches are studied in many systems, but mammalian germ stem cells (GSC) and their niches are still poorly understood. In rat testis, spermatogonia and undifferentiated Sertoli cells proliferate before puberty, but at puberty most spermatogonia enter spermatogenesis, and Sertoli cells differentiate to support this program. Thus, pre-pubertal spermatogonia might possess GSC potential and pre-pubertal Sertoli cells niche functions. We hypothesized that the different stem cell pools at pre-puberty and maturity provide a model for the identification of stem cell and niche-specific genes. We compared the transcript profiles of spermatogonia and Sertoli cells from pre-pubertal and pubertal rats and examined how these related to genes expressed in testicular cancers, which might originate from inappropriate communication between GSCs and Sertoli cells. Results: The pre-pubertal spermatogonia-specific gene set comprised known stem cell and spermatogonial stem cell (SSC) markers. Similarly, the pre-pubertal Sertoli cell-specific gene set comprised known niche gene transcripts. A large fraction of these specifically enriched transcripts encoded trans-membrane, extra-cellular, and secreted proteins highlighting stem cell to niche communication. Comparing selective gene sets established in this study with published gene expression data of testicular cancers and their stroma, we identified sets expressed genes shared between testicular tumors and pre-pubertal spermatogonia, and tumor stroma and pre-pubertal Sertoli cells with statistic significance. Conclusions: Our data suggest that SSC and their niche specifically express complementary factors for cell communication and that the same factors might be implicated in the communication between tumor cells and their micro-enviroment in testicular cancer.

Road Profile Adjustment Computer Program, HR-143, 1969

A computer program to adjust roadway profiles has been developed to serve as an aid to the county engineers of the State of Iowa. Many hours are spent reducing field notes and calculating adjusted roadway profiles to prepare an existing roadway for paving that will produce a high quality ride and be as maintenance free as possible. Since the computer is very well adapted to performing long tedious tasks; programming this work for a computer would result in freeing the engineer of these tasks. Freed from manual calculations, the engineer is able to spend more time in solving engineering problems. The type of roadway that this computer program is designed to adjust is a road that at sometime. in its history was graded to a finished subgrade. After a period of time, this road is to receive a finished paved surface. The problem then arises whether to bring the existing roadway up to the de signed grade or to make profile adjustments and comprise between the existing and the design profiles. In order to achieve the latter condition using this program, the engineer needs to give the computer only a minimum amount of information.