T-cell immune profile in blood of systemic mastocytosis: Association with disease features.

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.

Automated identification of leukocyte subsets improves standardization of database-guided expert-supervised diagnostic orientation in acute leukemia: a EuroFlow study.

Precise classification of acute leukemia (AL) is crucial for adequate treatment. EuroFlow has previously designed an AL orientation tube (ALOT) to guide toward the relevant classification panel and final diagnosis. In this study, we designed and validated an algorithm for automated (database-supported) gating and identification (AGI tool) of cell subsets within samples stained with ALOT. A reference database of normal peripheral blood (PB, n = 41) and bone marrow (BM; n = 45) samples analyzed with the ALOT was constructed, and served as a reference for the AGI tool to automatically identify normal cells. Populations not unequivocally identified as normal cells were labeled as checks and were classified by an expert. Additional normal BM (n = 25) and PB (n = 43) and leukemic samples (n = 109), analyzed in parallel by experts and the AGI tool, were used to evaluate the AGI tool. Analysis of normal PB and BM samples showed low percentages of checks (<3% in PB, <10% in BM), with variations between different laboratories. Manual analysis and AGI analysis of normal and leukemic samples showed high levels of correlation between cell numbers (r2 > 0.95 for all cell types in PB and r2 > 0.75 in BM) and resulted in highly concordant classification of leukemic cells by our previously published automated database-guided expert-supervised orientation tool for immunophenotypic diagnosis and classification of acute leukemia (Compass tool). Similar data were obtained using alternative, commercially available tubes, confirming the robustness of the developed tools. The AGI tool represents an innovative step in minimizing human intervention and requirements in expertise, toward a "sample-in and result-out" approach which may result in more objective and reproducible data analysis and diagnostics. The AGI tool may improve quality of immunophenotyping in individual laboratories, since high percentages of checks in normal samples are an alert on the quality of the internal procedures.

The Exact VC Dimension of the WiSARD n -Tuple Classifier.

The Wilkie, Stonham, and Aleksander recognition device (WiSARD) n -tuple classifier is a multiclass weightless neural network capable of learning a given pattern in a single step. Its architecture is determined by the number of classes it should discriminate. A target class is represented by a structure called a discriminator, which is composed of N RAM nodes, each of them addressed by an n -tuple. Previous studies were carried out in order to mitigate an important problem of the WiSARD n -tuple classifier: having its RAM nodes saturated when trained by a large data set. Finding the VC dimension of the WiSARD n -tuple classifier was one of those studies. Although no exact value was found, tight bounds were discovered. Later, the bleaching technique was proposed as a means to avoid saturation. Recent empirical results with the bleaching extension showed that the WiSARD n -tuple classifier can achieve high accuracies with low variance in a great range of tasks. Theoretical studies had not been conducted with that extension previously. This work presents the exact VC dimension of the basic two-class WiSARD n -tuple classifier, which is linearly proportional to the number of RAM nodes belonging to a discriminator, and exponentially to their addressing tuple length, precisely N(2n-1)+1 . The exact VC dimension of the bleaching extension to the WiSARD n -tuple classifier, whose value is the same as that of the basic model, is also produced. Such a result confirms that the bleaching technique is indeed an enhancement to the basic WiSARD n -tuple classifier as it does no harm to the generalization capability of the original paradigm.

Low-count monoclonal B-cell lymphocytosis persists after seven years of follow up and is associated with a poorer outcome.

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.

Maturation-associated gene expression profiles along normal human bone marrow monopoiesis.

Human monopoiesis is a tightly coordinated process which starts in the bone marrow (BM) haematopoietic stem cell (HSC) compartment and leads to the production of circulating blood mature monocytes. Although mature monocytes/macrophages have been extensively studied in both normal or inflammatory conditions, monopoiesis has only been assessed in vitro and in vivo animal models, due to low frequency of the monocytic precursors in the normal human BM. Here we investigated the transcriptional profile along normal human BM monopoiesis. Five distinct maturation-associated stages of monocytic precursors were identified and isolated from (fresh) normal human BM through fluorescence-activated cell sorting, and the gene expression profile (GEP) of each monocytic precursor subset was analysed by DNA-oligonucleotide microarrays. Overall, >6000 genes (18% of the genes investigated) were expressed in ≥1 stage of BM monopoiesis at stable or variable amounts, showing early decrease in cell proliferation with increased levels of expression of genes linked with cell differentiation. The here-defined GEP of normal human BM monopoiesis might contribute to better understand monocytic differentiation and the identification of novel monocytic candidate markers, while also providing a frame of reference for the study of monocytic maturation in both neoplastic and non-neoplastic disease conditions involving monocytic precursor cells.

Quality assessment program for EuroFlow protocols: summary results of four-year (2010-2013) quality assurance rounds.

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.

Gene expression profile of highly purified bone marrow mast cells in systemic mastocytosis.

BACKGROUND: Despite the fact that a great majority (>90%) of patients with systemic mastocytosis (SM) carry a common genetic lesion, the D816V KIT mutation, little is known regarding the molecular and biological pathways underlying the clinical heterogeneity of the disease. OBJECTIVE: We sought to analyze the gene expression profile (GEP) of bone marrow mast cells (BMMCs) in patients with SM and its association with distinct clinical variants of the disease. METHODS: GEP analyses were performed by using DNA-oligonucleotide microarrays in highly purified BMMCs from patients with SM carrying the D816V KIT mutation (n=26) classified according to the diagnostic subtype of SM versus normal/reactive BMMCs (n=7). Validation of GEP results was performed with flow cytometry in the same set of samples and in an independent cohort of 176 subjects. RESULTS: Overall, 758 transcripts were significantly deregulated in patients with SM, with a common GEP (n=398 genes) for all subvariants of SM analyzed. These were characterized by upregulation of genes involved in the innate and inflammatory immune response, including interferon-induced genes and genes involved in cellular responses to viral antigens, together with complement inhibitory molecules and genes involved in lipid metabolism and protein processing. Interestingly, aggressive SM additionally showed deregulation of apoptosis and cell cycle-related genes, whereas patients with indolent SM displayed increased expression of adhesion-related molecules. CONCLUSION: BMMCs from patients with different clinical subtypes of SM display distinct GEPs, which might reflect new targetable pathways involved in the pathogenesis of the disease.

Altered innate immune profile in blood of systemic mastocytosis patients.

Background: Mast cells (MC) from systemic mastocytosis (SM) patients release MC mediators that lead to an altered microenvironment with potential consequences on innate immune cells, such as monocytes and dendritic cells (DC). Here we investigated the distribution and functional behaviour of different populations of blood monocytes and DC among distinct diagnostic subtypes of SM. Methods: Overall, we studied 115 SM patients - 45 bone marrow mastocytosis (BMM), 61 indolent SM (ISM), 9 aggressive SM (ASM)- and 32 healthy donors (HD). Spontaneous and in vitro-stimulated cytokine production by blood monocytes, and their plasma levels, together with the distribution of different subsets of blood monocytes and DCs, were investigated. Results: SM patients showed increased plasma levels and spontaneous production by blood monocytes of IL1ß, IL6, IL8, TNFα and IL10, associated with an exhausted ability of LPS + IFNγ-stimulated blood monocytes to produce IL1ß and TGFß. SM (particularly ISM) patients also showed decreased counts of total monocytes, at the expense of intermediate monocytes and non-classical monocytes. Interestingly, while ISM and ASM patients had decreased numbers of plasmacytoid DC and myeloid DC (and their major subsets) in blood, an expansion of AXL+ DC was specifically encountered in BMM cases. Conclusion: These results demonstrate an altered distribution of blood monocytes and DC subsets in SM associated with constitutive activation of functionally impaired blood monocytes and increased plasma levels of a wide variety of inflammatory cytokines, reflecting broad activation of the innate immune response in mastocytosis.

Immunophenotypic Analysis of Acute Megakaryoblastic Leukemia: A EuroFlow Study.

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.

Expert-independent classification of mature B-cell neoplasms using standardized flow cytometry: a multicentric study.

Reproducible expert-independent flow-cytometric criteria for the differential diagnoses between mature B-cell neoplasms are lacking. We developed an algorithm-driven classification for these lymphomas by flow cytometry and compared it to the WHO gold standard diagnosis. Overall, 662 samples from 662 patients representing 9 disease categories were analyzed at 9 laboratories using the previously published EuroFlow 5-tube-8-color B-cell chronic lymphoproliferative disease antibody panel. Expression levels of all 26 markers from the panel were plotted by B-cell entity to construct a univariate, fully standardized diagnostic reference library. For multivariate data analysis, we subsequently used canonical correlation analysis of 176 training cases to project the multidimensional space of all 26 immunophenotypic parameters into 36 2-dimensional plots for each possible pairwise differential diagnosis. Diagnostic boundaries were fitted according to the distribution of the immunophenotypes of a given differential diagnosis. A diagnostic algorithm based on these projections was developed and subsequently validated using 486 independent cases. Negative predictive values exceeding 92.1% were observed for all disease categories except for follicular lymphoma. Particularly high positive predictive values were returned in chronic lymphocytic leukemia (99.1%), hairy cell leukemia (97.2%), follicular lymphoma (97.2%), and mantle cell lymphoma (95.4%). Burkitt and CD10+ diffuse large B-cell lymphomas were difficult to distinguish by the algorithm. A similar ambiguity was observed between marginal zone, lymphoplasmacytic, and CD10- diffuse large B-cell lymphomas. The specificity of the approach exceeded 98% for all entities. The univariate immunophenotypic library and the multivariate expert-independent diagnostic algorithm might contribute to increased reproducibility of future diagnostics in mature B-cell neoplasms.

Evaluation of the WHO criteria for the classification of patients with mastocytosis.

Diagnosis and classification of mastocytosis is currently based on the World Health Organization (WHO) criteria. Here, we evaluate the utility of the WHO criteria for the diagnosis and classification of a large series of mastocytosis patients (n=133), and propose a new algorithm that could be routinely applied for refined diagnosis and classification of the disease. Our results confirm the utility of the WHO criteria and provide evidence for the need of additional information for (1) a more precise diagnosis of mastocytosis, (2) specific identification of new forms of the disease, (3) the differential diagnosis between cutaneous mastocytosis vs systemic mastocytosis, and (4) improved distinction between indolent systemic mastocytosis and aggressive systemic mastocytosis. Based on our results, a new algorithm is proposed for a better diagnostic definition and prognostic classification of mastocytosis, as confirmed prospectively in an independent validation series of 117 mastocytosis patients.

Birth weight patterns by gestational age in Brazil.

BACKGROUND AND OBJECTIVES: We present an updated birth weight-for-gestational-age portrait, based on nearly 8 million observations of an ethnic-mixed population. It comprises the first comprehensive charts with Brazilian data. This contribution intends to assist clinicians in classifying fetal growth, to provide a reference for investigations of predictors and to show the consequences of small and large patterns for gestational age delivery. Most of the reference data for assessing birth weight for gestational age deal with insufficient sample size, especially at low gestational age. Population-based studies with considerably large sample size refer to data collected more than 15 years ago. METHODS: We accomplished a population-based study on births in all the Brazilian states from 2003 to 2005. Results were based on 7,993,166 singletons. We constructed the 3(rd), 5(th), 10(th), 25(th), 50(th), 90(th), 95(th) and 97(th) smoothed percentiles curves and gender-specific tables from 22 to 43 completed weeks. RESULTS: The resulting tables and graphical representation provide a gender-specific reference to access the birth weights distribution according to the gestational age in the Brazilian population. CONCLUSIONS: This is the first population-based reference constructed on a developing country data. These charts could provide an important tool to improve clinical assessment of growth in newborns.

Maturation-associated gene expression profiles during normal human bone marrow erythropoiesis.

Erythropoiesis has been extensively studied using in vitro and in vivo animal models. Despite this, there is still limited data about the gene expression profiles (GEP) of primary (ex vivo) normal human bone marrow (BM) erythroid maturation. We investigated the GEP of nucleated red blood cell (NRBC) precursors during normal human BM erythropoiesis. Three maturation-associated populations of NRBC were identified and purified from (fresh) normal human BM by flow cytometry and the GEP of each purified cell population directly analyzed using DNA-oligonucleotide microarrays. Overall, 6569 genes (19% of the genes investigated) were expressed in ≥1 stage of BM erythropoiesis at stable (e.g., genes involved in DNA process, cell signaling, protein organization and hemoglobin production) or variable amounts (e.g., genes related to cell differentiation, apoptosis, metabolism), the latter showing a tendency to either decrease from stage 1 to 3 (genes associated with regulation of erythroid differentiation and survival, e.g., SPI1, STAT5A) or increase from stage 2 to stage 3 (genes associated with autophagy, erythroid functions such as heme production, e.g., ALAS1, ALAS2), iron metabolism (e.g., ISCA1, SLC11A2), protection from oxidative stress (e.g., UCP2, PARK7), and NRBC enucleation (e.g., ID2, RB1). Interestingly, genes involved in apoptosis (e.g., CASP8, P2RX1) and immune response (e.g., FOXO3, TRAF6) were also upregulated in the last stage (stage 3) of maturation of NRBC precursors. Our results confirm and extend on previous observations and providing a frame of reference for better understanding the critical steps of human erythroid maturation and its potential alteration in patients with different clonal and non-clonal erythropoietic disorders.

Lot-to-lot stability of antibody reagents for flow cytometry.

The fluorescence detected using fluorochrome-labelled monoclonal antibodies depends not only on the abundance of the target antigen, but amongst many other factors also on the effective fluorochrome-to-antibody ratio. The diagnostic approach of the EuroFlow consortium relies on reproducible fluorescence intensities over time. A capture bead system for mouse immunoglobulin light chains was utilized to compare the mean fluorescence intensity of 1323 consecutive antibody lots to the currently used lot of the same monoclonal antibody. In total, 157 different monoclonal antibodies were assessed over seven years. Median relative difference between consecutive lots was 3.8% (range: 0.01% to 164.7%, interquartile range: 1.3% to 10.1%). The relative difference exceeded 20% in 8.8% of all comparisons. FITC labelled monoclonal antibodies (median relative difference: 2.1%) showed a significantly smaller variation between lots than antibodies conjugated to PE (3.5%), PECy7 (3.9%), PerCPCy5.5 (5.8%), APC (5.8%), APCH7 (7.4%), and APCC750 (14.5%). Reagents labelled with Pacific Blue (1.4%), Pacific Orange (2.4%), HV450 (0.7%), and HV500 (1.7%) demonstrated more consistent results compared to conjugates of BV421 (4.1%) and BV510 (16.2%). Additionally, significant differences in lot-to-lot fluorescence stability amongst antibodies labelled with the same fluorochrome were observed between manufacturers. These observations might guide future quality recommendations for the production and application of fluorescence-labelled monoclonal antibodies in multicolor flow cytometry.

Generation of flow cytometry data files with a potentially infinite number of dimensions.

Immunophenotypic characterization of B-cell chronic lymphoproliferative disorders (B-CLPD) is associated with the use of increasingly larger panels of multiple combinations of 3 to > or =6 monoclonal antibodies (Mab), data analysis being separately performed for each of the different stained sample aliquots. Here, we describe and validate an automated method for calculation of flow cytometric data from several multicolor stainings of the same cell sample--i.e., the merging of data from different aliquots stained with partially overlapping combinations of Mab reagents (focusing on > or =1 cell populations)--into one data file as if it concerned a single "super" multicolor staining. Evaluation of the performance of the method described was done in a group of 60 B-CLPD studied at diagnosis with 18 different reagents in a panel containing six different 3- and 4-color stainings, which systematically contained CD19 for the identification of B-cells. Our results show a high degree of correlation and agreement between originally measured and calculated data about cell surface stainings, providing a basis for the use of this approach for the generation of flow cytometric data files containing information about a virtually infinite number of stainings for each individual cellular event measured in a sample, using a limited number of fluorochrome stainings.

A universal multilingual weightless neural network tagger via quantitative linguistics.

In the last decade, given the availability of corpora in several distinct languages, research on multilingual part-of-speech tagging started to grow. Amongst the novelties there is mWANN-Tagger (multilingual weightless artificial neural network tagger), a weightless neural part-of-speech tagger capable of being used for mostly-suffix-oriented languages. The tagger was subjected to corpora in eight languages of quite distinct natures and had a remarkable accuracy with very low sample deviation in every one of them, indicating the robustness of weightless neural systems for part-of-speech tagging tasks. However, mWANN-Tagger needed to be tuned for every new corpus, since each one required a different parameter configuration. For mWANN-Tagger to be truly multilingual, it should be usable for any new language with no need of parameter tuning. This article proposes a study that aims to find a relation between the lexical diversity of a language and the parameter configuration that would produce the best performing mWANN-Tagger instance. Preliminary analyses suggested that a single parameter configuration may be applied to the eight aforementioned languages. The mWANN-Tagger instance produced by this configuration was as accurate as the language-dependent ones obtained through tuning. Afterwards, the weightless neural tagger was further subjected to new corpora in languages that range from very isolating to polysynthetic ones. The best performing instances of mWANN-Tagger are again the ones produced by the universal parameter configuration. Hence, mWANN-Tagger can be applied to new corpora with no need of parameter tuning, making it a universal multilingual part-of-speech tagger. Further experiments with Universal Dependencies treebanks reveal that mWANN-Tagger may be extended and that it has potential to outperform most state-of-the-art part-of-speech taggers if better word representations are provided.

Learning vector quantization with training data selection.

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.

A review of protein function prediction under machine learning perspective.

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.

Overview of clinical flow cytometry data analysis: recent advances and future challenges.

Major technological advances in flow cytometry (FC), both for instrumentation and reagents, have emerged over the past few decades. These advances facilitate simultaneous evaluation of more parameters in single cells analyzed at higher speed. Consequently, larger and more complex data files that contain information about tens of parameters for millions of cells are generated. This increasing complexity has challenged pre-existing data analysis tools and promoted the development of new algorithms and tools for data analysis and visualization. Here, we review the currently available (conventional and newly developed) data analysis and visualization strategies that aim for easier, more objective, and robust interpretation of FC data both in biomedical research and clinical diagnostic laboratories.