78 resultados para Minimal-complexity classifier

em Université de Lausanne, Switzerland


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Many assays to evaluate the nature, breadth, and quality of antigen-specific T cell responses are currently applied in human medicine. In most cases, assay-related protocols are developed on an individual laboratory basis, resulting in a large number of different protocols being applied worldwide. Together with the inherent complexity of cellular assays, this leads to unnecessary limitations in the ability to compare results generated across institutions. Over the past few years a number of critical assay parameters have been identified which influence test performance irrespective of protocol, material, and reagents used. Describing these critical factors as an integral part of any published report will both facilitate the comparison of data generated across institutions and lead to improvements in the assays themselves. To this end, the Minimal Information About T Cell Assays (MIATA) project was initiated. The objective of MIATA is to achieve a broad consensus on which T cell assay parameters should be reported in scientific publications and to propose a mechanism for reporting these in a systematic manner. To add maximum value for the scientific community, a step-wise, open, and field-spanning approach has been taken to achieve technical precision, user-friendliness, adequate incorporation of concerns, and high acceptance among peers. Here, we describe the past, present, and future perspectives of the MIATA project. We suggest that the approach taken can be generically applied to projects in which a broad consensus has to be reached among scientists working in fragmented fields, such as immunology. An additional objective of this undertaking is to engage the broader scientific community to comment on MIATA and to become an active participant in the project.

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Operative treatment of coronoid fracture often requires a large dissection of soft tissue, resulting in elbow stiffness and functional limitation. The authors present a minimal invasive, safe technique, useful in the case of isolated coronoid fracture associated with elbow dislocation. This technique does not require soft tissue dissection and allows an early unlimited resumption of sports activities.

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Neuroblastoma (NB) is a neural crest-derived childhood tumor characterized by a remarkable phenotypic diversity, ranging from spontaneous regression to fatal metastatic disease. Although the cancer stem cell (CSC) model provides a trail to characterize the cells responsible for tumor onset, the NB tumor-initiating cell (TIC) has not been identified. In this study, the relevance of the CSC model in NB was investigated by taking advantage of typical functional stem cell characteristics. A predictive association was established between self-renewal, as assessed by serial sphere formation, and clinical aggressiveness in primary tumors. Moreover, cell subsets gradually selected during serial sphere culture harbored increased in vivo tumorigenicity, only highlighted in an orthotopic microenvironment. A microarray time course analysis of serial spheres passages from metastatic cells allowed us to specifically "profile" the NB stem cell-like phenotype and to identify CD133, ABC transporter, and WNT and NOTCH genes as spheres markers. On the basis of combined sphere markers expression, at least two distinct tumorigenic cell subpopulations were identified, also shown to preexist in primary NB. However, sphere markers-mediated cell sorting of parental tumor failed to recapitulate the TIC phenotype in the orthotopic model, highlighting the complexity of the CSC model. Our data support the NB stem-like cells as a dynamic and heterogeneous cell population strongly dependent on microenvironmental signals and add novel candidate genes as potential therapeutic targets in the control of high-risk NB.

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Immunotherapy, especially therapeutic vaccination, has a great deal of potential in the treatment of cancer and certain infectious diseases such as HIV (Allison et al., 2006; Fauci et al., 2008; Feldmann and Steinman, 2005). Numerous vaccine candidates have been tested in patients with a variety of tumor types and chronic viral diseases. Often, the best way to assess the clinical potential of these vaccines is to monitor the induced T cell response, and yet there are currently no standards for reporting these results. This letter is an effort to address this problem.

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OBJECTIVES: To document biopsychosocial profiles of patients with rheumatoid arthritis (RA) by means of the INTERMED and to correlate the results with conventional methods of disease assessment and health care utilization. METHODS: Patients with RA (n = 75) were evaluated with the INTERMED, an instrument for assessing case complexity and care needs. Based on their INTERMED scores, patients were compared with regard to severity of illness, functional status, and health care utilization. RESULTS: In cluster analysis, a 2-cluster solution emerged, with about half of the patients characterized as complex. Complex patients scoring especially high in the psychosocial domain of the INTERMED were disabled significantly more often and took more psychotropic drugs. Although the 2 patient groups did not differ in severity of illness and functional status, complex patients rated their illness as more severe on subjective measures and on most items of the Medical Outcomes Study Short Form 36. Complex patients showed increased health care utilization despite a similar biologic profile. CONCLUSIONS: The INTERMED identified complex patients with increased health care utilization, provided meaningful and comprehensive patient information, and proved to be easy to implement and advantageous compared with conventional methods of disease assessment. Intervention studies will have to demonstrate whether management strategies based on INTERMED profiles can improve treatment response and outcome of complex patients.

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Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. Includes self-contained introductions to probability and decision theory. Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. Features implementation of the methodology with reference to commercial and academically available software. Presents standard networks and their extensions that can be easily implemented and that can assist in the reader's own analysis of real cases. Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

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Eusociality is taxonomically rare, yet associated with great ecological success. Surprisingly, studies of environmental conditions favouring eusociality are often contradictory. Harsh conditions associated with increasing altitude and latitude seem to favour increased sociality in bumblebees and ants, but the reverse pattern is found in halictid bees and polistine wasps. Here, we compare the life histories and distributions of populations of 176 species of Hymenoptera from the Swiss Alps. We show that differences in altitudinal distributions and development times among social forms can explain these contrasting patterns: highly social taxa develop more quickly than intermediate social taxa, and are thus able to complete the reproductive cycle in shorter seasons at higher elevations. This dual impact of altitude and development time on sociality illustrates that ecological constraints can elicit dynamic shifts in behaviour, and helps explain the complex distribution of sociality across ecological gradients.

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Human perception of bitterness displays pronounced interindividual variation. This phenotypic variation is mirrored by equally pronounced genetic variation in the family of bitter taste receptor genes. To better understand the effects of common genetic variations on human bitter taste perception, we conducted a genome-wide association study on a discovery panel of 504 subjects and a validation panel of 104 subjects from the general population of São Paulo in Brazil. Correction for general taste-sensitivity allowed us to identify a SNP in the cluster of bitter taste receptors on chr12 (10.88- 11.24 Mb, build 36.1) significantly associated (best SNP: rs2708377, P = 5.31 × 10(-13), r(2) = 8.9%, β = -0.12, s.e. = 0.016) with the perceived bitterness of caffeine. This association overlaps with-but is statistically distinct from-the previously identified SNP rs10772420 influencing the perception of quinine bitterness that falls in the same bitter taste cluster. We replicated this association to quinine perception (P = 4.97 × 10(-37), r(2) = 23.2%, β = 0.25, s.e. = 0.020) and additionally found the effect of this genetic locus to be concentration specific with a strong impact on the perception of low, but no impact on the perception of high concentrations of quinine. Our study, thus, furthers our understanding of the complex genetic architecture of bitter taste perception.

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Objective: The aim of this study was to determine the smallest changes in health-related quality of life (HRQOL) scores in the European Organization for Research and Treatment of Cancer quality of life questionnaire (EORTC QLQ-C30) and the EORTC Brain Cancer Module (QLQ-BN20), which could be considered as clinically meaningful in brain cancer patients. Methods: World Health Organization (WHO) performance status (PS) and the Mini Mental State Examination (MMSE) were used as clinical anchors to determine minimal clinically important differences (MCID) in HRQOL change scores (range 0 - 100) in the EORTC QLQ-C30 and QLQ-BN20. Anchor-based MCID estimates less than 0.2SD (small effect) were not recommended for interpretation. Other selected distribution-based methods were also used for comparison purposes. Results: Based on WHO PS, our findings support the following whole number estimates of the MCID for improvement and deterioration respectively: physical functioning (6, 9), role functioning (14, 12), cognitive functioning (8, 8), global health status (7, 4*), fatigue (12, 9) and motor dysfunction (4*, 5). Anchoring with MMSE, cognitive functioning MCID estimates for improvement and deterioration were (11, 2*) and those for communication deficit were (9, 7). The estimates with asterisks were less that the set 0.2 SD threshold and are therefore not recommended for interpretation. Our MCID estimates therefore range from 5-14. Conclusion: These estimates can help clinicians to evaluate changes in HRQOL over time and, in conjunction with other measures of efficacy, help to assess the value of a health care intervention or to compare treatments. Furthermore, the estimates can be useful in determining sample sizes in the design of future clinical trials.

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Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence-environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence-environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building 'under fit' models, having insufficient flexibility to describe observed occurrence-environment relationships, we risk misunderstanding the factors shaping species distributions. By building 'over fit' models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.

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Vitamin K deficiency bleeding within the first 24 h of life is caused in most cases by maternal drug intake (e.g. coumarins, anticonvulsants, tuberculostatics) during pregnancy. Haemorrhage is often life-threatening and usually not prevented by vitamin K prophylaxis at birth. We report a case of severe intracranial bleeding at birth secondary to phenobarbital-induced vitamin K deficiency and traumatic delivery. Burr hole trepanations of the skull were performed and the subdural haematoma was evacuated. Despite the severe prognosis, the infant showed an unexpected good recovery. At the age of 3 years, neurological examinations were normal as was the EEG at the age of 9 months. CT showed close to normal intracranial structures. CONCLUSION: This case report stresses the importance of antenatal vitamin K prophylaxis and the consideration of a primary Caesarean section in maternal vitamin K deficiency states and demonstrates the successful management of massive subdural haemorrhage by a limited surgical approach.