Acute promyelocytic leukemia associated with the PLZF-RARA fusion gene: two additional cases with clinical and laboratorial peculiar presentations

Acute promyelocytic leukemia (APL) is characterized by the presence of the t(15;17) and PML-RARa rearrangement, with good response to treatment with retinoids. However, few cases of variant APL involving alternative chromosomal aberrations have been reported, including t(11;17)(q23;q21) (Wells et al. in Nat Genet 17:109-113, 1; Arnould et al. in Hum Mol Genet 8:1741-1749, 2) t(5;17)(q35;q12-21), t(11;17)(q13;q21) (Grimwade et al in Blood 96:1297-1308, 3) and der(17) (Rego et al. in Blood (ASH Annual Meeting Abstracts)114:Abstract 6, 4), whereby RARa is fused to the PLZF, NPM, NuMA, and STAT5b genes, respectively, have been described. These cases are characterized by distinct morphology, clinical presentation, and in respect to PLZF, a lack of differentiation response to retinoids leading to the need of different approaches concerning diagnostic methods and therapeutics. This paper describes two cases of APL associated with the PLZF-RARA fusion gene enrolled in the IC-APL trial that is a non-randomized, multicenter study conducted in Brazil, Mexico, Chile and Uruguay with the aim to improve the treatment outcome of APL patients in developing countries. These cases, although rare, offer a challenge to its early recognition and proper conduction.

In vivo consequences of AML1-ETO fusion protein expression for hematopoiesis

The t(8;21) (q22;q22) translocation fusing the ETO (also known as MTG8) gene on human chromosome 8 with the AML1 (also called Runx1 or CBFα) gene on chromosome 21 is one of the most common genetic aberrations found in acute myeloid leukemia (AML). This chromosomal translocation occurs in 12 % of de novo AML cases and in up to 40 % of the AML-M2 subtype of the French-American-British classification. To date, the in vivo function of aberrant AML1-ETO fusion protein expression has been investigated by several groups. However, in these studies, controversial results were reported and some key issues remain unknown. Importantly, the consequences of aberrant AML1-ETO expression for self-renewing hematopoietic stem cells (HSCs), multipotent hematopoietic progenitors (MPPs) and lineage-restricted precursors are not known. rn The aim of this thesis was to develop a novel experimental AML1-ETO in vivo model that (i) overcomes the current lack of insight into the pre-leukemic condition of t(8;21)-associated AML, (ii) clarifies the in vivo consequences of AML1-ETO for HSCs, MPPs, progenitors and more mature blood cells and (iii) generates an improved mouse model suitable for mirroring the human condition. For this purpose, a conditional tet on/off mouse model expressing the AML1-ETO fusion protein from the ROSA26 (R26) locus was generated. rn Aberrant AML1-ETO activation in compound ROSA26/tetOAML1-ETO (R26/AE) mice caused high rates of mortality, an overall disruption of hematopoietic organs and a profound alteration of hematopoiesis. However, since the generalized activity of the R26 locus did not recapitulate the leukemic condition found in human patients, it was important to restrict AML1-ETO expression to blood cell lineages. Therefore, bone marrow cells from non-induced R26/AE mice were adoptively transplanted into sublethal irradiated RAG2-/- recipient mice. First signs of phenotypical differences between AML1-ETO-expressing and control mice were observed after eight to nine months of transgene induction. AML1-ETO-expressing mice showed profound changes in hematopoietic organs accompanied by manifest extramedullary hematopoiesis. In addition, a block in early erythropoiesis, B- and T-cell maturation was observed and granulopoiesis was significantly enhanced. Most interestingly, conditional activation of AML1-ETO in chimeric mice did not increase HSCs, MPPs, common lymphoid precursors (CLPs), common myeloid progenitors (CMPs) and megakaryocyte-erythrocyte progenitors (MEPs) but promoted the selective amplification of granulocyte-macrophage progenitors (GMPs). rn The results of this thesis provide clear experimental evidence how aberrant AML1-ETO modulates the developmental properties of normal hematopoiesis and establishes for the first time that AML1-ETO does not increase HSCs, MPPs and common lineage-restricted progenitor pools but specifically amplifies GMPs. The here presented mouse model not only clarifies the role of aberrant AML1-ETO for shaping hematopoietic development but in addition has strong implications for future therapeutic strategies and will be an excellent pre-clinical tool for developing and testing new approaches to treat and eventually cure AML.rn

A new information fusion method for land-use classification using high resolution satellite imagery

Satellite image classification involves designing and developing efficient image classifiers. With satellite image data and image analysis methods multiplying rapidly, selecting the right mix of data sources and data analysis approaches has become critical to the generation of quality land-use maps. In this study, a new postprocessing information fusion algorithm for the extraction and representation of land-use information based on high-resolution satellite imagery is presented. This approach can produce land-use maps with sharp interregional boundaries and homogeneous regions. The proposed approach is conducted in five steps. First, a GIS layer - ATKIS data - was used to generate two coarse homogeneous regions, i.e. urban and rural areas. Second, a thematic (class) map was generated by use of a hybrid spectral classifier combining Gaussian Maximum Likelihood algorithm (GML) and ISODATA classifier. Third, a probabilistic relaxation algorithm was performed on the thematic map, resulting in a smoothed thematic map. Fourth, edge detection and edge thinning techniques were used to generate a contour map with pixel-width interclass boundaries. Fifth, the contour map was superimposed on the thematic map by use of a region-growing algorithm with the contour map and the smoothed thematic map as two constraints. For the operation of the proposed method, a software package is developed using programming language C. This software package comprises the GML algorithm, a probabilistic relaxation algorithm, TBL edge detector, an edge thresholding algorithm, a fast parallel thinning algorithm, and a region-growing information fusion algorithm. The county of Landau of the State Rheinland-Pfalz, Germany was selected as a test site. The high-resolution IRS-1C imagery was used as the principal input data.

An Early-Warning System for Hypo-/Hyperglycemic Events Based on Fusion of Adaptive Prediction Models

Introduction: Early warning of future hypoglycemic and hyperglycemic events can improve the safety of type 1 diabetes mellitus (T1DM) patients. The aim of this study is to design and evaluate a hypoglycemia / hyperglycemia early warning system (EWS) for T1DM patients under sensor-augmented pump (SAP) therapy. Methods: The EWS is based on the combination of data-driven online adaptive prediction models and a warning algorithm. Three modeling approaches have been investigated: (i) autoregressive (ARX) models, (ii) auto-regressive with an output correction module (cARX) models, and (iii) recurrent neural network (RNN) models. The warning algorithm performs postprocessing of the models′ outputs and issues alerts if upcoming hypoglycemic/hyperglycemic events are detected. Fusion of the cARX and RNN models, due to their complementary prediction performances, resulted in the hybrid autoregressive with an output correction module/recurrent neural network (cARN)-based EWS. Results: The EWS was evaluated on 23 T1DM patients under SAP therapy. The ARX-based system achieved hypoglycemic (hyperglycemic) event prediction with median values of accuracy of 100.0% (100.0%), detection time of 10.0 (8.0) min, and daily false alarms of 0.7 (0.5). The respective values for the cARX-based system were 100.0% (100.0%), 17.5 (14.8) min, and 1.5 (1.3) and, for the RNN-based system, were 100.0% (92.0%), 8.4 (7.0) min, and 0.1 (0.2). The hybrid cARN-based EWS presented outperforming results with 100.0% (100.0%) prediction accuracy, detection 16.7 (14.7) min in advance, and 0.8 (0.8) daily false alarms. Conclusion: Combined use of cARX and RNN models for the development of an EWS outperformed the single use of each model, achieving accurate and prompt event prediction with few false alarms, thus providing increased safety and comfort.

Multi-Model Data Fusion to Improve an Early Warning System for Hypo-/Hyperglycemic Events

Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.

Potential common radiation problems for components and diagnostics in future magnetic and inertial confinement fusion devices

This work aims at identifying commonpotentialproblems that futurefusiondevices will encounter for both magnetic and inertialconfinement approaches in order to promote joint efforts and to avoid duplication of research. Firstly, a comparison of radiation environments found in both fusion reaction chambers will be presented. Then, wall materials, optical components, cables and electronics will be discussed, pointing to possible future areas of common research. Finally, a brief discussion of experimental techniques available to simulate the radiation effect on materials is included

The technofusion project for fusion technology development: opportunities for the inertial community

Technofusion will be the new Spanish singular scientific-technical installation for fusion research. The research activities will be focused on seven areas of materials research considered the most relevant ones for further technological developments of fusion energy. In principle, most of the infrastructure in Technofusion will be useful for both, magnetic (MC) and inertial (IC) confinement fusion communities and most of the research and developments carried out for one of the fusion concepts will be valid and transferable to the other. However, some aspects related to first wall materials strongly differ in MC and IC approaches. This is due to the very different typical ion energy and deposited powers in both cases.

Plasma facing materials for fusion reactor applications

The lack of plasma facing materials (PFM) able to withstand the severe magnetiicffusiion radiation conditions expected in fusion reactors is the actual bottle In both fusions approaches energy is released in the form of kinetic energy of neck for fusion to becomes a reality.

Structural Insights into Viral Membrane Fusion Machinery via Cryo-Electron Tomography: Influenza Virus and Human Parainfluenza Virus

Thesis (Ph.D.)--University of Washington, 2016-06

High level data fusion

We address the question of how to obtain effective fusion of identification information such that it is robust to the quality of this information. As well as technical issues data fusion is encumbered with a collection of (potentially confusing) practical considerations. These considerations are described during the early chapters in which a framework for data fusion is developed. Following this process of diversification it becomes clear that the original question is not well posed and requires more precise specification. We use the framework to focus on some of the technical issues relevant to the question being addressed. We show that fusion of hard decisions through use of an adaptive version of the maximum a posteriori decision rule yields acceptable performance. Better performance is possible using probability level fusion as long as the probabilities are accurate. Of particular interest is the prevalence of overconfidence and the effect it has on fused performance. The production of accurate probabilities from poor quality data forms the latter part of the thesis. Two approaches are taken. Firstly the probabilities may be moderated at source (either analytically or numerically). Secondly, the probabilities may be transformed at the fusion centre. In each case an improvement in fused performance is demonstrated. We therefore conclude that in order to obtain robust fusion care should be taken to model the probabilities accurately; either at the source or centrally.

Multi-scale score level fusion of local descriptors for gender classification in the wild

The 2015 FRVT gender classification (GC) report evidences the problems that current approaches tackle in situations with large variations in pose, illumination, background and facial expression. The report suggests that both commercial and research solutions are hardly able to reach an accuracy over 90% for The Images of Groups dataset, a proven scenario exhibiting unrestricted or in the wild conditions. In this paper, we focus on this challenging dataset, stepping forward in GC performance by observing: 1) recent literature results combining multiple local descriptors, and 2) the psychophysics evidences of the greater importance of the ocular and mouth areas to solve this task...

Truncation identities for the small polaron fusion hierarchy

We study a one-dimensional lattice model of interacting spinless fermions. This model is integrable for both periodic and open boundary conditions; the latter case includes the presence of Grassmann valued non-diagonal boundary fields breaking the bulk U(1) symmetry of the model. Starting from the embedding of this model into a graded Yang-Baxter algebra, an infinite hierarchy of commuting transfer matrices is constructed by means of a fusion procedure. For certain values of the coupling constant related to anisotropies of the underlying vertex model taken at roots of unity, this hierarchy is shown to truncate giving a finite set of functional equations for the spectrum of the transfer matrices. For generic coupling constants, the spectral problem is formulated in terms of a functional (or TQ-)equation which can be solved by Bethe ansatz methods for periodic and diagonal open boundary conditions. Possible approaches for the solution of the model with generic non-diagonal boundary fields are discussed.