Composite lymphoma of concurrent T zone lymphoma and large cell B cell lymphoma in a dog.

BackgroundEvolution of indolent to aggressive lymphoma has been described in dogs but is difficult to distinguish from the de novo development of a second, clonally distinct lymphoma. Differentiation of these scenarios can be aided by next generation sequencing (NGS)-based assessment of clonality of lymphocyte antigen receptor genes.Case presentationAn 8-year-old male intact Mastiff presented with generalized lymphadenomegaly was diagnosed with nodal T zone lymphoma (TZL) based on cytology, histopathology, immunohistochemistry and flow cytometry. Thirteen months later, the dog re-presented with progressive lymphadenomegaly, and based on cytology and flow cytometry, a large B cell lymphoma (LBCL) was diagnosed. Sequencing-based clonality testing confirmed the de novo development of a LBCL and the persistence of a TZL.ConclusionsThe occurrence of two distinct lymphoid neoplasms should be considered if patient features and tumor cytomorphology or immunophenotype differ among sequential samples. Sequencing-based clonality testing may provide conclusive evidence of two concurrent and distinct clonal lymphocyte populations, termed most appropriately "composite lymphoma"

Quantitative-Morphological and Cytological Analyses in Leukemia

Leukemia, a blood cancer originating in the bone marrow, presents as a heterogeneous disease with highly variable survival rates. Leukemia is classified into major types based on the rate of cancerous cell growth and cell lineage: chronic or acute and myeloid or lymphoid leukemia. Histological and cytological analysis of the peripheral blood and the bone marrow can classify these major leukemia categories. However, histological analyses of patient biopsies and cytological microscopic assessment of blood and bone marrow smears are insufficient to diagnose leukemia subtypes and to direct therapy. Hence, more expensive and time-consuming diagnostic tools routinely complement histological-cytological analysis during a patient’s diagnosis. To extract more accurate and detailed information from patient tissue samples, digital pathology is emerging as a powerful tool to enhance biopsy- and smear-based decisions. Furthermore, digital pathology methods integrated with advances in machine learning enable new diagnostic features from leukemia patients’ histological and cytological slides and optimize patient classification, thus providing a cheaper, more robust, and faster diagnostic tool than current standards. This review summarizes emerging approaches to automatically diagnose leukemia from morphological and cytological-histological analyses

Optimizing morphology through blood cell image analysis

Introduction Morphological review of the peripheral blood smear is still a crucial diagnostic aid as it provides relevant information related to the diagnosis and is important for selection of additional techniques. Nevertheless, the distinctive cytological characteristics of the blood cells are subjective and influenced by the reviewer's interpretation and, because of that, translating subjective morphological examination into objective parameters is a challenge. Methods The use of digital microscopy systems has been extended in the clinical laboratories. As automatic analyzers have some limitations for abnormal or neoplastic cell detection, it is interesting to identify quantitative features through digital image analysis for morphological characteristics of different cells. Result Three main classes of features are used as follows: geometric, color, and texture. Geometric parameters (nucleus/cytoplasmic ratio, cellular area, nucleus perimeter, cytoplasmic profile, RBC proximity, and others) are familiar to pathologists, as they are related to the visual cell patterns. Different color spaces can be used to investigate the rich amount of information that color may offer to describe abnormal lymphoid or blast cells. Texture is related to spatial patterns of color or intensities, which can be visually detected and quantitatively represented using statistical tools. Conclusion This study reviews current and new quantitative features, which can contribute to optimize morphology through blood cell digital image processing techniques.Peer ReviewedPostprint (published version

USSR Space Life Sciences Digest, Issue 18

This is the 18th issue of NASA's USSR Life Sciences Digest. It contains abstracts of 50 papers published in Russian language periodicals or presented at conferences and of 8 new Soviet monographs. Selected abstracts are illustrated with figures and tables from the original. A review of a recent Aviation Medicine Handbook is also included. The abstracts in this issue have been identified as relevant to 37 areas of space biology and medicine. These areas are: adaptation, aviation medicine, biological rhythms, biospherics, body fluids, cardiovascular and respiratory systems, cytology, developmental biology, endocrinology, enzymology, equipment and instrumentation, exobiology, gastrointestinal system, genetics, gravitational biology, group dynamics, habitability and environmental effects, hematology, human performance, immunology, life support systems, man-machine systems, mathematical modeling, metabolism, microbiology, musculoskeletal system, neurophysiology, nutrition, operational medicine, perception, personnel selection, psychology, radiobiology, reproductive biology, space biology and medicine, and space industrialization

The Identification of Lymphocyte-Like Cells and Lymphoid-Related Genes in Amphioxus Indicates the Twilight for the Emergency of Adaptive Immune System

To seek evidence of a primitive adaptive immune system (AIS) before vertebrate, we examined whether lymphocytes or lymphocyte-like cells and the related molecules participating in the lymphocyte function existed in amphioxus. Anatomical analysis by electron microscopy revealed the presence of lymphocyte-like cells in gills, and these cells underwent morphological changes in response to microbial pathogens that are reminiscent of those of mammalian lymphocytes executing immune response to microbial challenge. In addition, a systematic comparative analysis of our cDNA database of amphioxus identified a large number of genes whose vertebrate counterparts are involved in lymphocyte function. Among these genes, several genes were found to be expressed in the vicinity of the lymphocyte-like cells by in situ hybridization and up-regulated after exposure to microbial pathogens. Our findings in the amphioxus indicate the twilight for the emergency of AIS before the invertebrate-vertebrate transition during evolution

Isoform-specific potentiation of stem and progenitor cell engraftment by AML1/RUNX1

Background: AML1/RUNX1 is the most frequently mutated gene in leukaemia and is central to the normal biology of hematopoietic stem and progenitor cells. However, the role of different AML1 isoforms within these primitive compartments is unclear. Here we investigate whether altering relative expression of AML1 isoforms impacts the balance between cell self-renewal and differentiation in vitro and in vivo. Methods and Findings: The human AML1a isoform encodes a truncated molecule with DNA-binding but no transactivation capacity. We used a retrovirus-based approach to transduce AML1a into primitive haematopoietic cells isolated from the mouse. We observed that enforced AML1a expression increased the competitive engraftment potential of murine long-term reconstituting stem cells with the proportion of AML1a-expressing cells increasing over time in both primary and secondary recipients. Furthermore, AML1a expression dramatically increased primitive and committed progenitor activity in engrafted animals as assessed by long-term culture, cobblestone formation, and colony assays. In contrast, expression of the full-length isoform AML1b abrogated engraftment potential. In vitro, AML1b promoted differentiation while AML1a promoted proliferation of progenitors capable of short-term lymphomyeloid engraftment. Consistent with these findings, the relative abundance of AML1a was highest in the primitive stem/progenitor compartment of human cord blood, and forced expression of AML1a in these cells enhanced maintenance of primitive potential both in vitro and in vivo. Conclusions: These data demonstrate that the "a" isoform of AML1 has the capacity to potentiate stem and progenitor cell engraftment, both of which are required for successful clinical transplantation. This activity is consistent with its expression pattern in both normal and leukaemic cells. Manipulating the balance of AML1 isoform expression may offer novel therapeutic strategies, exploitable in the contexts of leukaemia and also in cord blood transplantation in adults, in whom stem and progenitor cell numbers are often limiting. © 2007 Tsuzuki et al

Robust Automated Tumour Segmentation on Histological and Immunohistochemical Tissue Images

Tissue microarray (TMA) is a high throughput analysis tool to identify new diagnostic and prognostic markers in human cancers. However, standard automated method in tumour detection on both routine histochemical and immunohistochemistry (IHC) images is under developed. This paper presents a robust automated tumour cell segmentation model which can be applied to both routine histochemical tissue slides and IHC slides and deal with finer pixel-based segmentation in comparison with blob or area based segmentation by existing approaches. The presented technique greatly improves the process of TMA construction and plays an important role in automated IHC quantification in biomarker analysis where excluding stroma areas is critical. With the finest pixel-based evaluation (instead of area-based or object-based), the experimental results show that the proposed method is able to achieve 80% accuracy and 78% accuracy in two different types of pathological virtual slides, i.e., routine histochemical H&E and IHC images, respectively. The presented technique greatly reduces labor-intensive workloads for pathologists and highly speeds up the process of TMA construction and provides a possibility for fully automated IHC quantification