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.

Optimizing therapeutic targets for breast cancer using boolean network models.

Studying gene regulatory networks associated with cancer provides valuable insights for therapeutic purposes, given that cancer is fundamentally a genetic disease. However, as the number of genes in the system increases, the complexity arising from the interconnections between network components grows exponentially. In this study, using Boolean logic to adjust the existing relationships between network components has facilitated simplifying the modeling process, enabling the generation of attractors that represent cell phenotypes based on breast cancer RNA-seq data. A key therapeutic objective is to guide cells, through targeted interventions, to transition from the current cancer attractor to a physiologically distinct attractor unrelated to cancer. To achieve this, we developed a computational method that identifies network nodes whose inhibition can facilitate the desired transition from one tumor attractor to another associated with apoptosis, leveraging transcriptomic data from cell lines. To validate the model, we utilized previously published in vitro experiments where the downregulation of specific proteins resulted in cell growth arrest and death of a breast cancer cell line. The method proposed in this manuscript combines diverse data sources, conducts structural network analysis, and incorporates relevant biological knowledge on apoptosis in cancer cells. This comprehensive approach aims to identify potential targets of significance for personalized medicine.

Systematic Evaluation of Antigenic Stimulation in Chronic Lymphocytic Leukemia: Humoral Immunity as Biomarkers for Disease Evolution.

Chronic lymphocytic leukemia (CLL) is the most common leukemia in the Western world. Studies of CLL antibody reactivity have shown differential targets to autoantigens and antimicrobial molecular motifs that support the current hypothesis of CLL pathogenesis. METHODS: In this study, we conducted a quantitative serum analysis of 7 immunoglobulins in CLL and monoclonal B-cell lymphocytosis (MBL) patients (bead-suspension protein arrays) and a serological profile (IgG and IgM) study of autoantibodies and antimicrobial antigens (protein microarrays). RESULTS: Significant differences in the IgA levels were observed according to disease progression and evolution as well as significant alterations in IgG1 according to IGHV mutational status. More representative IgG autoantibodies in the cohort were against nonmutagenic proteins and IgM autoantibodies were against vesicle proteins. Antimicrobial IgG and IgM were detected against microbes associated with respiratory tract infections. CONCLUSIONS: Quantitative differences in immunoglobulin serum levels could be potential biomarkers for disease progression. In the top 5 tumoral antigens, we detected autoantibodies (IgM and IgG) against proteins related to cell homeostasis and metabolism in the studied cohort. The top 5 microbial antigens were associated with respiratory and gastrointestinal infections; moreover, the subsets with better prognostics were characterized by a reactivation of Cytomegalovirus. The viral humoral response could be a potential prognosis biomarker for disease progression.

Unravelling soluble immune checkpoints in chronic lymphocytic leukemia: Physiological immunomodulators or immune dysfunction.

Chronic lymphocytic leukemia (CLL) is a lymphoid neoplasm characterized by the accumulation of mature B cells. The diagnosis is established by the detection of monoclonal B lymphocytes in peripheral blood, even in early stages [monoclonal B-cell lymphocytosis (MBLhi)], and its clinical course is highly heterogeneous. In fact, there are well-characterized multiple prognostic factors that are also related to the observed genetic heterogenicity, such as immunoglobulin heavy chain variable region (IGHV) mutational status, del17p, and TP53 mutations, among others. Moreover, a dysregulation of the immune system (innate and adaptive immunity) has been observed in CLL patients, with strong impact on immune surveillance and consequently on the onset, evolution, and therapy response. In addition, the tumor microenvironment is highly complex and heterogeneous (i.e., matrix, fibroblast, endothelial cells, and immune cells), playing a critical role in the evolution of CLL. In this study, a quantitative profile of 103 proteins (cytokines, chemokines, growth/regulatory factors, immune checkpoints, and soluble receptors) in 67 serum samples (57 CLL and 10 MBLhi) has been systematically evaluated. Also, differential profiles of soluble immune factors that discriminate between MBLhi and CLL (sCD47, sCD27, sTIMD-4, sIL-2R, and sULBP-1), disease progression (sCD48, sCD27, sArginase-1, sLAG-3, IL-4, and sIL-2R), or among profiles correlated with other prognostic factors, such as IGHV mutational status (CXCL11/I-TAC, CXCL10/IP-10, sHEVM, and sLAG-3), were deciphered. These results pave the way to explore the role of soluble immune checkpoints as a promising source of biomarkers in CLL, to provide novel insights into the immune suppression process and/or dysfunction, mostly on T cells, in combination with cellular balance disruption and microenvironment polarization leading to tumor escape.

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.

Deciphering Biomarkers for Leptomeningeal Metastasis in Malignant Hemopathies (Lymphoma/Leukemia) Patients by Comprehensive Multipronged Proteomics Characterization of Cerebrospinal Fluid.

In the present work, leptomeningeal disease, a very destructive form of systemic cancer, was characterized from several proteomics points of view. This pathology involves the invasion of the leptomeninges by malignant tumor cells. The tumor spreads to the central nervous system through the cerebrospinal fluid (CSF) and has a very grim prognosis; the average life expectancy of patients who suffer it does not exceed 3 months. The early diagnosis of leptomeningeal disease is a challenge because, in most of the cases, it is an asymptomatic pathology. When the symptoms are clear, the disease is already in the very advanced stages and life expectancy is low. Consequently, there is a pressing need to determine useful CSF proteins to help in the diagnosis and/or prognosis of this disease. For this purpose, a systematic and exhaustive proteomics characterization of CSF by multipronged proteomics approaches was performed to determine different protein profiles as potential biomarkers. Proteins such as PTPRC, SERPINC1, sCD44, sCD14, ANPEP, SPP1, FCGR1A, C9, sCD19, and sCD34, among others, and their functional analysis, reveals that most of them are linked to the pathology and are not detected on normal CSF. Finally, a panel of biomarkers was verified by a prediction model for leptomeningeal disease, showing new insights into the research for potential biomarkers that are easy to translate into the clinic for the diagnosis of this devastating disease.

Microclimate of grass canopies and biomass accumulation are influenced by the use of caged exclosures in grazing research.

Exclosure cages are often used for estimating biomass accumulation on continuously stocked pastures in grazing experiments. The microclimate inside the cages may affect the estimates of biomass accumulation, but this has not been previously identified or quantified. We evaluated how the exclusion from grazing for 21 days in Mulato II brachiariagrass (Brachiaria brizantha × Brachiaria decumbens × Brachiaria ruziziensis) pastures affected canopy air temperature (T) and relative humidity (RH) and how this related to biomass accumulation. We also evaluated the effect of the exclosure cage on wind speed (WS) and incoming solar radiation (SR), and how these impacted evapotranspiration (ET) and estimates of biomass accumulation on grazed canopies maintained at 20- and 30-cm height under continuous stocking. Regardless of canopy height, changes in canopy structure during the exclusion period up to 21 days did not affect T and RH (averages of 24.3 °C and 88.7%, respectively), indicating that the air circulation was not affected by the exclusion. The cage structure reduced SR by 5%, although there were times during clear days when SR was slightly greater inside the cage than outside. The cage also reduced WS by 4.4%. Smaller SR and WS resulted in less ET inside the cages than outside, although with close values (2.9 vs. 3.0 mm day-1; P = 0.0494). The biomass accumulation rate was greater inside than outside the cages for both canopy heights. This overestimation would be 5.8 and 9.7% greater if the structure of the cage did not reduce the SR, WS, and ET.

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.

Low-beta repetitive transcranial magnetic stimulation to human dorsolateral prefrontal cortex during object recognition memory sample presentation, at a task-related frequency observed in local field potentials in homologous macaque cortex, impairs subsequent recollection but not familiarity.

According to dual-process signal-detection (DPSD) theories, short- and long-term recognition memory draws upon both familiarity and recollection. It remains unclear how primate prefrontal cortex (PFC) contributes to these processes, but frequency-specific neuronal activities are considered to play a key role. In Experiment 1, nonhuman primate (NHP) local field potential (LFP) electrophysiological recordings in macaque left dorsolateral PFC (dlPFC) revealed performance-related differences in a low-beta frequency range during the sample presentation phase of a visual object recognition memory task. Experiment 2 employed a similar task in humans and targeted left dlPFC (and vertex as a control) with repetitive transcranial magnetic stimulation (rTMS) at 12.5 Hz during occasional sample presentations. This low-beta frequency rTMS to dlPFC decreased DPSD derived indices of recollection, but not familiarity, in subsequent memory tests of the targeted samples after short delays. The same number of rTMS pulses over the same total duration albeit at a random frequency had no effect on either recollection or familiarity. Neither stimulation protocols had any causal effect upon behaviour when targeted to the control site (vertex). In this study, our hypotheses for our human TMS study were derived from our observations in NHPs; this approach might inspire further translational research through investigation of homologous brain regions and tasks across species using similar neuroscientific methodologies to advance the neural mechanism of recognition memory in primates.

Data-Driven Modeling of Breast Cancer Tumors Using Boolean Networks.

Cancer is a genomic disease involving various intertwined pathways with complex cross-communication links. Conceptually, this complex interconnected system forms a network, which allows one to model the dynamic behavior of the elements that characterize it to describe the entire system's development in its various evolutionary stages of carcinogenesis. Knowing the activation or inhibition status of the genes that make up the network during its temporal evolution is necessary for the rational intervention on the critical factors for controlling the system's dynamic evolution. In this report, we proposed a methodology for building data-driven boolean networks that model breast cancer tumors. We defined the network components and topology based on gene expression data from RNA-seq of breast cancer cell lines. We used a Boolean logic formalism to describe the network dynamics. The combination of single-cell RNA-seq and interactome data enabled us to study the dynamics of malignant subnetworks of up-regulated genes. First, we used the same Boolean function construction scheme for each network node, based on canalyzing functions. Using single-cell breast cancer datasets from The Cancer Genome Atlas, we applied a binarization algorithm. The binarized version of scRNA-seq data allowed identifying attractors specific to patients and critical genes related to each breast cancer subtype. The model proposed in this report may serve as a basis for a methodology to detect critical genes involved in malignant attractor stability, whose inhibition could have potential applications in cancer theranostics.

Flow Cytometry Immunophenotyping for Diagnostic Orientation and Classification of Pediatric Cancer Based on the EuroFlow Solid Tumor Orientation Tube (STOT).

Early diagnosis of pediatric cancer is key for adequate patient management and improved outcome. Although multiparameter flow cytometry (MFC) has proven of great utility in the diagnosis and classification of hematologic malignancies, its application to non-hematopoietic pediatric tumors remains limited. Here we designed and prospectively validated a new single eight-color antibody combination-solid tumor orientation tube, STOT-for diagnostic screening of pediatric cancer by MFC. A total of 476 samples (139 tumor mass, 138 bone marrow, 86 lymph node, 58 peripheral blood, and 55 other body fluid samples) from 296 patients with diagnostic suspicion of pediatric cancer were analyzed by MFC vs. conventional diagnostic procedures. STOT was designed after several design-test-evaluate-redesign cycles based on a large panel of monoclonal antibody combinations tested on 301 samples. In its final version, STOT consists of a single 8-color/12-marker antibody combination (CD99-CD8/numyogenin/CD4-EpCAM/CD56/GD2/smCD3-CD19/cyCD3-CD271/CD45). Prospective validation of STOT in 149 samples showed concordant results with the patient WHO/ICCC-3 diagnosis in 138/149 cases (92.6%). These included: 63/63 (100%) reactive/disease-free samples, 43/44 (98%) malignant and 4/4 (100%) benign non-hematopoietic tumors together with 28/38 (74%) leukemia/lymphoma cases; the only exception was Hodgkin lymphoma that required additional markers to be stained. In addition, STOT allowed accurate discrimination among the four most common subtypes of malignant CD45- CD56++ non-hematopoietic solid tumors: 13/13 (GD2++ numyogenin- CD271-/+ nuMyoD1- CD99- EpCAM-) neuroblastoma samples, 5/5 (GD2- numyogenin++ CD271++ nuMyoD1++ CD99-/+ EpCAM-) rhabdomyosarcomas, 2/2 (GD2-/+ numyogenin- CD271+ nuMyoD1- CD99+ EpCAM-) Ewing sarcoma family of tumors, and 7/7 (GD2- numyogenin- CD271+ nuMyoD1- CD99- EpCAM+) Wilms tumors. In summary, here we designed and validated a new standardized antibody combination and MFC assay for diagnostic screening of pediatric solid tumors that might contribute to fast and accurate diagnostic orientation and classification of pediatric cancer in routine clinical practice.

Tracking the Antibody Immunome in Sporadic Colorectal Cancer by Using Antigen Self-Assembled Protein Arrays.

Sporadic Colorectal Cancer (sCRC) is the third leading cause of cancer death in the Western world, and the sCRC patients presenting with synchronic metastasis have the poorest prognosis. Genetic alterations accumulated in sCRC tumor cells translate into mutated proteins and/or abnormal protein expression levels, which contribute to the development of sCRC. Then, the tumor-associated proteins (TAAs) might induce the production of auto-antibodies (aAb) via humoral immune response. Here, Nucleic Acid Programmable Protein Arrays (NAPPArray) are employed to identify aAb in plasma samples from a set of 50 sCRC patients compared to seven healthy donors. Our goal was to establish a systematic workflow based on NAPPArray to define differential aAb profiles between healthy individuals and sCRC patients as well as between non-metastatic (n = 38) and metastatic (n = 12) sCRC, in order to gain insight into the role of the humoral immune system in controlling the development and progression of sCRC. Our results showed aAb profile based on 141 TAA including TAAs associated with biological cellular processes altered in genesis and progress of sCRC (e.g., FSCN1, VTI2 and RPS28) that discriminated healthy donors vs. sCRC patients. In addition, the potential capacity of discrimination (between non-metastatic vs. metastatic sCRC) of 7 TAAs (USP5, ML4, MARCKSL1, CKMT1B, HMOX2, VTI2, TP53) have been analyzed individually in an independent cohort of sCRC patients, where two of them (VTI2 and TP53) were validated (AUC ~75%). In turn, these findings provided novel insights into the immunome of sCRC, in combination with transcriptomics profiles and protein antigenicity characterizations, wich might lead to the identification of novel sCRC biomarkers that might be of clinical utility for early diagnosis of the tumor. These results explore the immunomic analysis as potent source for biomarkers with diagnostic and prognostic value in CRC. Additional prospective studies in larger series of patients are required to confirm the clinical utility of these novel sCRC immunomic biomarkers.

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.

Age Distribution of Multiple Functionally Relevant Subsets of CD4+ T Cells in Human Blood Using a Standardized and Validated 14-Color EuroFlow Immune Monitoring Tube.

CD4+ T cells comprise multiple functionally distinct cell populations that play a key role in immunity. Despite blood monitoring of CD4+ T-cell subsets is of potential clinical utility, no standardized and validated approaches have been proposed so far. The aim of this study was to design and validate a single 14-color antibody combination for sensitive and reproducible flow cytometry monitoring of CD4+ T-cell populations in human blood to establish normal age-related reference values and evaluate the presence of potentially altered profiles in three distinct disease models-monoclonal B-cell lymphocytosis (MBL), systemic mastocytosis (SM), and common variable immunodeficiency (CVID). Overall, 145 blood samples from healthy donors were used to design and validate a 14-color antibody combination based on extensive reagent testing in multiple cycles of design-testing-evaluation-redesign, combined with in vitro functional studies, gene expression profiling, and multicentric evaluation of manual vs. automated gating. Fifteen cord blood and 98 blood samples from healthy donors (aged 0-89 years) were used to establish reference values, and another 25 blood samples were evaluated for detecting potentially altered CD4 T-cell subset profiles in MBL (n = 8), SM (n = 7), and CVID (n = 10). The 14-color tube can identify ≥89 different CD4+ T-cell populations in blood, as validated with high multicenter reproducibility, particularly when software-guided automated (vs. manual expert-based) gating was used. Furthermore, age-related reference values were established, which reflect different kinetics for distinct subsets: progressive increase of naïve T cells, T-helper (Th)1, Th17, follicular helper T (TFH) cells, and regulatory T cells (Tregs) from birth until 2 years, followed by a decrease of naïve T cells, Th2, and Tregs in older children and a subsequent increase in multiple Th-cell subsets toward late adulthood. Altered and unique CD4+ T-cell subset profiles were detected in two of the three disease models evaluated (SM and CVID). In summary, the EuroFlow immune monitoring TCD4 tube allows fast, automated, and reproducible identification of ≥89 subsets of CD4+ blood T cells, with different kinetics throughout life. These results set the basis for in-depth T-cell monitoring in different disease and therapeutic conditions.

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.

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.

BOLD mapping of human epileptic spikes recorded during simultaneous intracranial EEG-fMRI: The impact of automated spike classification.

OBJECTIVES: Simultaneous intracranial EEG and functional MRI (icEEG-fMRI) can be used to map the haemodynamic (BOLD) changes associated with the generation of IEDs. Unlike scalp EEG-fMRI, in most patients who undergo icEEG-fMRI, IEDs recorded intracranially are numerous and show variability in terms of field amplitude and morphology. Therefore, visual marking can be highly subjective and time consuming. In this study, we applied an automated spike classification algorithm, Wave_clus (WC), to IEDs marked visually on icEEG data acquired during simultaneous fMRI acquisition. The motivation of this work is to determine whether using a potentially more consistent and unbiased automated approach can produce more biologically meaningful BOLD patterns compared to the BOLD patterns obtained based on the conventional, visual classification. METHODS: We analysed simultaneous icEEG-fMRI data from eight patients with severe drug resistant epilepsy, and who subsequently underwent resective surgery that resulted in a good outcome: confirmed epileptogenic zone (EZ). For each patient two fMRI analyses were performed: one based on the conventional visual IED classification and the other based on the automated classification. We used the concordance of the IED-related BOLD maps with the confirmed EZ as an indication of their biological meaning, which we compared for the automated and visual classifications for all IED originating in the EZ. RESULTS: Across the group, the visual and automated classifications resulted in 32 and 24 EZ IED classes respectively, for which 75% vs 83% of the corresponding BOLD maps were concordant. At the single-subject level, the BOLD maps for the automated approach had greater concordance in four patients, and less concordance in one patient, compared to those obtained using the conventional visual classification, and equal concordance for three remaining patients. These differences did not reach statistical significance. CONCLUSION: We found automated IED classification on icEEG data recorded during fMRI to be feasible and to result in IED-related BOLD maps that may contain similar or greater biological meaning compared to the conventional approach in the majority of the cases studied. We anticipate that this approach will help to gain significant new insights into the brain networks associated with IEDs and in relation to postsurgical outcome.

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.