Instruction of haematopoietic lineage choices, evolution of transcriptional landscapes and cancer stem cell hierarchies derived from an AML1-ETO mouse model.

The t(8;21) chromosomal translocation activates aberrant expression of the AML1-ETO (AE) fusion protein and is commonly associated with core binding factor acute myeloid leukaemia (CBF AML). Combining a conditional mouse model that closely resembles the slow evolution and the mosaic AE expression pattern of human t(8;21) CBF AML with global transcriptome sequencing, we find that disease progression was characterized by two principal pathogenic mechanisms. Initially, AE expression modified the lineage potential of haematopoietic stem cells (HSCs), resulting in the selective expansion of the myeloid compartment at the expense of normal erythro- and lymphopoiesis. This lineage skewing was followed by a second substantial rewiring of transcriptional networks occurring in the trajectory to manifest leukaemia. We also find that both HSC and lineage-restricted granulocyte macrophage progenitors (GMPs) acquired leukaemic stem cell (LSC) potential being capable of initiating and maintaining the disease. Finally, our data demonstrate that long-term expression of AE induces an indolent myeloproliferative disease (MPD)-like myeloid leukaemia phenotype with complete penetrance and that acute inactivation of AE function is a potential novel therapeutic option.

Reconstruction of metal pollution and recent sedimentation processes in Havana Bay (Cuba): A tool for coastal ecosystem management.

Since 1998 the highly polluted Havana Bay ecosystem has been the subject of a mitigation program. In order to determine whether pollution-reduction strategies were effective, we have evaluated the historical trends of pollution recorded in sediments of the Bay. A sediment core was dated radiometrically using natural and artificial fallout radionuclides. An irregularity in the (210)Pb record was caused by an episode of accelerated sedimentation. This episode was dated to occur in 1982, a year coincident with the heaviest rains reported in Havana over the XX century. Peaks of mass accumulation rates (MAR) were associated with hurricanes and intensive rains. In the past 60 years, these maxima are related to strong El Niño periods, which are known to increase rainfall in the north Caribbean region. We observed a steady increase of pollution (mainly Pb, Zn, Sn, and Hg) since the beginning of the century to the mid 90s, with enrichment factors as high as 6. MAR and pollution decreased rapidly after the mid 90s, although some trace metal levels remain high. This reduction was due to the integrated coastal zone management program introduced in the late 90s, which dismissed catchment erosion and pollution.

In vivo fate mapping with SCL regulatory elements identifies progenitors for primitive and definitive hematopoiesis in mice.

One of the principal issues facing biomedical research is to elucidate developmental pathways and to establish the fate of stem and progenitor cells in vivo. Hematopoiesis, the process of blood cell formation, provides a powerful experimental system for investigating this process. Here, we employ transcriptional regulatory elements from the stem cell leukemia (SCL) gene to selectively label primitive and definitive hematopoiesis. We report that SCL-labelled cells arising in the mid to late streak embryo give rise to primitive red blood cells but fail to contribute to the vascular system of the developing embryo. Restricting SCL-marking to different stages of foetal development, we identify a second population of multilineage progenitors, proficient in contributing to adult erythroid, myeloid and lymphoid cells. The distinct lineage-restricted potential of SCL-labelled early progenitors demonstrates that primitive erythroid cell fate specification is initiated during mid gastrulation. Our data also suggest that the transition from a hemangioblastic precursors with endothelial and blood forming potential to a committed hematopoietic progenitor must have occurred prior to SCL-marking of definitive multilineage blood precursors.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

A review of atlas-based segmentation for magnetic resonance brain images.

Normal and abnormal brains can be segmented by registering the target image with an atlas. Here, an atlas is defined as the combination of an intensity image (template) and its segmented image (the atlas labels). After registering the atlas template and the target image, the atlas labels are propagated to the target image. We define this process as atlas-based segmentation. In recent years, researchers have investigated registration algorithms to match atlases to query subjects and also strategies for atlas construction. In this paper we present a review of the automated approaches for atlas-based segmentation of magnetic resonance brain images. We aim to point out the strengths and weaknesses of atlas-based methods and suggest new research directions. We use two different criteria to present the methods. First, we refer to the algorithms according to their atlas-based strategy: label propagation, multi-atlas methods, and probabilistic techniques. Subsequently, we classify the methods according to their medical target: the brain and its internal structures, tissue segmentation in healthy subjects, tissue segmentation in fetus, neonates and elderly subjects, and segmentation of damaged brains. A quantitative comparison of the results reported in the literature is also presented.