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Background: Systemic mastocytosis (SM) is a heterogeneous disease characterized by an expansion of KIT‐mutated mast cells (MC). KIT‐mutated MC display activated features and release MC mediators that might act on the tumour microenvironment and other immune cells. Here, we investigated the distribution of lymphocyte subsets in blood of patients with distinct subtypes of SM and determined its association with other disease features. Methods: We studied the distribution of TCD4+ and TCD4− cytotoxic cells and their subsets, as well as total NK‐ and B cells, in blood of 115 SM patients—38 bone marrow mastocytosis (BMM), 67 indolent SM (ISM), 10 aggressive SM (ASM)‐ and 83 age‐matched healthy donors (HD), using spectral flow cytometry and the EuroFlow Immunomonitoring panel, and correlated it with multilineage KITD816V, the alpha‐tryptasemia genotype (HαT) and the clinical manifestations of the disease. Results: SM patients showed decreased counts (vs. HD) of TCD4− cytotoxic cells, NK cells and several functional subsets of TCD4+ cells (total Th1, Th2‐effector memory, Th22‐terminal effector and Th1‐like Tregs), together with increased T‐follicular‐helper and Th1/Th17‐like Treg counts, associated with different immune profiles per diagnostic subtype of SM, in multilineal versus MC‐restricted KITD816V and in cases with a HαT+ versus HαT− genotype. Unique immune profiles were found among BMM and ISM patients with MC‐restricted KITD816V who displayed HαT, anaphylaxis, hymenoptera venom allergy, bone disease, pruritus, flushing and GI symptoms. Conclusion: Our results reveal altered T‐ and NK‐cell immune profiles in blood of SM, which vary per disease subtype, the pattern of involvement of haematopoiesis by KITD816V, the HαT genotype and specific clinical manifestations of the disease. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method that selects a subset of the training data points to update LVQ prototypes. The main goal is to conduct the prototypes to converge at a more convenient location, diminishing misclassification errors. The method selects an update set composed by a subset of points considered to be at the risk of being captured by another class prototype. We associate the proposed methodology to a weighted norm, instead of the Euclidean, in order to establish different levels of relevance for the input attributes. The technique was implemented on a controlled experiment and on Web available data sets. Index Terms--Learning vector quantization LVQ, pattern classification, clustering, data selection, neural networks.

Flow cytometric immunophenotyping has become essential for accurate diagnosis, classification, and disease monitoring in hemato-oncology. The EuroFlow Consortium has established a fully standardized 'all-in-one' pipeline consisting of standardized instrument settings, reagent panels, and sample preparation protocols and software for data analysis and disease classification. For its reproducible implementation, parallel development of a quality assurance (QA) program was required. Here, we report on the results of four consecutive annual rounds of the novel external QA EuroFlow program. The novel QA scheme aimed at monitoring the whole flow cytometric analysis process (cytometer setting, sample preparation, acquisition and analysis) by reading the median fluorescence intensities (MedFI) of defined lymphocytes' subsets. Each QA participant applied the predefined reagents' panel on blood cells of local healthy donors. A uniform gating strategy was applied to define lymphocyte subsets and to read MedFI values per marker. The MedFI values were compared with reference data and deviations from reference values were quantified using performance score metrics. In four annual QA rounds, we analyzed 123 blood samples from local healthy donors on 14 different instruments in 11 laboratories from nine European countries. The immunophenotype of defined cellular subsets appeared sufficiently standardized to permit unified (software) data analysis. The coefficient of variation of MedFI for 7 of 11 markers performed repeatedly below 30%, average MedFI in each QA round ranged from 86 to 125% from overall median. Calculation of performance scores was instrumental to pinpoint standardization failures and their causes. Overall, the new EuroFlow QA system for the first time allowed to quantify the technical variation that is introduced in the measurement of fluorescence intensities in a multicentric setting over an extended period of time. EuroFlow QA is a proficiency test specific for laboratories that use standardized EuroFlow protocols. It may be used to complement, but not replace, established proficiency tests. © 2014 International Society for Advancement of Cytometry [ABSTRACT FROM AUTHOR]

Acute megakaryoblastic leukemia (AMKL) is a rare and heterogeneous subtype of acute myeloid leukemia (AML). We evaluated the immunophenotypic profile of 72 AMKL and 114 non-AMKL AML patients using the EuroFlow AML panel. Univariate and multivariate/multidimensional analyses were performed to identify most relevant markers contributing to the diagnosis of AMKL. AMKL patients were subdivided into transient abnormal myelopoiesis (TAM), myeloid leukemia associated with Down syndrome (ML-DS), AML-not otherwise specified with megakaryocytic differentiation (NOS-AMKL), and AMKL-other patients (AML patients with other WHO classification but with flowcytometric features of megakaryocytic differentiation). Flowcytometric analysis showed good discrimination between AMKL and non-AMKL patients based on differential expression of, in particular, CD42a.CD61, CD41, CD42b, HLADR, CD15 and CD13. Combining CD42a.CD61 (positive) and CD13 (negative) resulted in a sensitivity of 71% and a specificity of 99%. Within AMKL patients, TAM and ML-DS patients showed higher frequencies of immature CD34+/CD117+ leukemic cells as compared to NOS-AMKL and AMKL-Other patients. In addition, ML-DS patients showed a significantly higher expression of CD33, CD11b, CD38 and CD7 as compared to the other three subgroups, allowing for good distinction of these patients. Overall, our data show that the EuroFlow AML panel allows for straightforward diagnosis of AMKL and that ML-DS is associated with a unique immunophenotypic profile.

Low-count monoclonal B-cell lymphocytosis is defined by the presence of very low numbers of circulating clonal B cells, usually phenotypically similar to chronic lymphocytic leukemia cells, whose biological and clinical significance remains elusive. Herein, we re-evaluated 65/91 low-count monoclonal B-cell lymphocytosis cases (54 chronic lymphocytic leukemia-like and 11 non-chronic lymphocytic leukemia-like) followed-up for a median of seven years, using high-sensitivity flow cytometry and interphase fluorescence in situ hybridization. Overall, the clone size significantly increased in 69% of low-count monoclonal B-cell lymphocytosis cases, but only one subject progressed to high-count monoclonal B-cell lymphocytosis. In parallel, the frequency of cytogenetic alterations increased over time (32% vs 61% of cases, respectively). The absolute number of the major T-cell and natural killer cell populations also increased, but only among chronic lymphocytic leukemia-like cases with increased clone size vs age- and sex-matched controls. Although progression to chronic lymphocytic leukemia was not observed, the overall survival of low-count monoclonal B-cell lymphocytosis individuals was significantly reduced vs non-monoclonal B-cell lymphocytosis controls ( P =0.03) plus the general population from the same region ( P ≤0.001), particularly among females ( P =0.01); infection and cancer were the main causes of death in low-count monoclonal B-cell lymphocytosis. In summary, despite the fact that mid-term progression from low-count monoclonal B-cell lymphocytosis to high-count monoclonal B-cell lymphocytosis and chronic lymphocytic leukemia appears to be unlikely, these clones persist at increased numbers, usually carrying more genetic alterations, and might thus be a marker of an impaired immune system indirectly associated with a poorer outcome, particularly among females., (Copyright© 2018 Ferrata Storti Foundation.)

Flow cytometric immunophenotyping has become essential for accurate diagnosis, classification, and disease monitoring in hemato-oncology. The EuroFlow Consortium has established a fully standardized "all-in-one" pipeline consisting of standardized instrument settings, reagent panels, and sample preparation protocols and software for data analysis and disease classification. For its reproducible implementation, parallel development of a quality assurance (QA) program was required. Here, we report on the results of four consecutive annual rounds of the novel external QA EuroFlow program. The novel QA scheme aimed at monitoring the whole flow cytometric analysis process (cytometer setting, sample preparation, acquisition and analysis) by reading the median fluorescence intensities (MedFI) of defined lymphocytes' subsets. Each QA participant applied the predefined reagents' panel on blood cells of local healthy donors. A uniform gating strategy was applied to define lymphocyte subsets and to read MedFI values per marker. The MedFI values were compared with reference data and deviations from reference values were quantified using performance score metrics. In four annual QA rounds, we analyzed 123 blood samples from local healthy donors on 14 different instruments in 11 laboratories from nine European countries. The immunophenotype of defined cellular subsets appeared sufficiently standardized to permit unified (software) data analysis. The coefficient of variation of MedFI for 7 of 11 markers performed repeatedly below 30%, average MedFI in each QA round ranged from 86 to 125% from overall median. Calculation of performance scores was instrumental to pinpoint standardization failures and their causes. Overall, the new EuroFlow QA system for the first time allowed to quantify the technical variation that is introduced in the measurement of fluorescence intensities in a multicentric setting over an extended period of time. EuroFlow QA is a proficiency test specific for laboratories that use standardized EuroFlow protocols. It may be used to complement, but not replace, established proficiency tests. © 2014 International Society for Advancement of Cytometry., (© 2014 International Society for Advancement of Cytometry.)

Protein function prediction is one of the most challenging problems in the post-genomic era. The number of newly identified proteins has been exponentially increasing with the advances of the high-throughput techniques. However, the functional characterization of these new proteins was not incremented in the same proportion. To fill this gap, a large number of computational methods have been proposed in the literature. Early approaches have explored homology relationships to associate known functions to the newly discovered proteins. Nevertheless, these approaches tend to fail when a new protein is considerably different (divergent) from previously known ones. Accordingly, more accurate approaches, that use expressive data representation and explore sophisticate computational techniques are required. Regarding these points, this review provides a comprehensible description of machine learning approaches that are currently applied to protein function prediction problems. We start by defining several problems enrolled in understanding protein function aspects, and describing how machine learning can be applied to these problems. We aim to expose, in a systematical framework, the role of these techniques in protein function inference, sometimes difficult to follow up due to the rapid evolvement of the field. With this purpose in mind, we highlight the most representative contributions, the recent advancements, and provide an insightful categorization and classification of machine learning methods in functional proteomics.