Quality assessment of a large multi-center flow cytometric dataset of acute myeloid leukemia patients—A EuroFlow study

Flowcytometric analysis allows for detailed identification and characterization of large numbers of cells in blood, bone marrow, and other body fluids and tissue samples and therefore contributes to the diagnostics of hematological malignancies. Novel data analysis tools allow for multidimensional analysis and comparison of patient samples with reference databases of normal, reactive, and/or leukemia/lymphoma patient samples. Building such reference databases requires strict quality assessment (QA) procedures. Here, we compiled a dataset and developed a QA methodology of the EuroFlow Acute Myeloid Leukemia (AML) database, based on the eight-color EuroFlow AML panel consisting of six different antibody combinations, including four backbone markers. In total, 1142 AML cases and 42 normal bone marrow samples were included in this analysis. QA was performed on 803 AML cases using multidimensional analysis of backbone markers, as well as tube-specific markers, and data were compared using classical analysis employing median and peak expression values. Validation of the QA procedure was performed by re-analysis of >300 cases and by running an independent cohort of 339 AML cases. Initial evaluation of the final cohort confirmed specific immunophenotypic patterns in AML subgroups; the dataset therefore can reliably be used for more detailed exploration of the immunophenotypic variability of AML. Our data show the potential pitfalls and provide possible solutions for constructing large flowcytometric databases. In addition, the provided approach may facilitate the building of other databases and thereby support the development of novel tools for (semi)automated QA and subsequent data analysis.The EuroFlow Consortium received support from the FP6-2004-LIFESCIHEALTH-5 program of the European Commission (grant LSHB-CT-2006-018708) as a Specific Targeted Research Project (STREP). The EuroFlow Consortium is part of the European Scientific Foundation for Hemato Oncology (ESLHO), a Scientific Working Group (SWG) of the European Hematology Association (EHA). S.M. was supported by Acción Estratégica en Salud (AES) (Grant PI21_01115) and the grant of CIBERONC of the Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación, Madrid, Spain and FONDOS FEDER (no. CB16/12/00400)

Impactos na saúde mental de indivíduos hospitalizados após infecção por SARS-CoV-2: cuidado integral que se constrói em rede

ABSTRACT: Introduction: Covid-19 in hospitalized patients has had an intensified impact on mental health, leading to different psychological repercussions. Objective: to identify symptoms of depression, anxiety and stress in hospitalized patients affected by moderate Covid-19. Method: a cross-sectional study that evaluated patients diagnosed with SARS-CoV-2 infection admitted to a teaching hospital in the countryside of Rio Grande do Sul - RS. The assessment of symptoms of anxiety, depression and stress was performed using the Depression, Anxiety and Stress Scale (DASS-21) and investigated by an educated and qualified professional. Results: sample (n = 44; male: n = 28, 63.60%) with a mean age of 55.11 ± 11.32 years, with 79.50% showing symptoms of anxiety. Conclusion: the anxiety symptom observed in hospitalized patients infected with the SARS-CoV-2 virus highlights the importance of the psychological impacts of Covid-19, which highlights the need for interventions with a preventive approach, considering the epidemiological bases of the different levels of prevention. in public health. Keywords: Depression; Anxiety; Stress; Mental health; Coronavirus infections.  RESUMO: Introdução: a Covid-19 em pacientes internados gerou um impacto sobre a saúde mental de modo intensificado levando a ocasionar distintas repercussões psicológicas. Objetivo: identificar os sintomas de depressão, ansiedade e estresse em pacientes hospitalizados acometidos pela Covid-19 moderada. Método: estudo transversal que avaliou pacientes com diagnóstico da infecção pelo SARS-CoV-2 admitidos em um hospital de ensino do interior do Rio Grande do Sul - RS. A avaliação dos sintomas de ansiedade, depressão e estresse foi realizada por meio da escala Depression, Anxiety and Stress Scale (DASS-21) e investigada por um profissional instruído e qualificado. Resultados: amostra (n= 44; sexo masculino: n= 28, 63,60%) com média de idade de 55,11±11,32 anos, tendo 79,50% apresentado sintomas de ansiedade. Conclusão: o sintoma de ansiedade observado em pacientes hospitalizados infectados pelo vírus SARS-CoV-2 ressalta a importância dos impactos psicológicos da Covid-19, o que evidencia a necessidade de intervenções com enfoque preventivo, considerando as bases epidemiológicas dos diferentes níveis de prevenção em saúde pública. Palavras-Chave: Depressão; Ansiedade; Estresse; Saúde mental; Infecção pelo coronavírus

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.The EuroFlow Consortium received support from the FP6-2004-LIFESCIHEALTH-5 program of the European Commission (grant LSHB-CT-2006-018708) as Specific Targeted Research Project (STREP). The EuroFlow Consortium is part of the European Scientific Foundation for HematoOncology (ESLHO), a Scientific Working Group (SWG) of the European Hematology Association (EHA). The work of C.E.P. and E.S.C. was partially supported by FAPERJ (Grant E26/200.840/2021- CNE; E26/210.379/2018 and E26/110.105/2014); CAPES-PROEX; and CNPq (Grant 306258/2019-6 and 303765/2018-6). M.N. and E.M. were supported by the Ministry of Health of the Czech Republic, grant number NU20J-07-00028. S.M. was supported by Acción Estratégica en Salud (AES) (Grant PI21_01115) and the grant of CIBERONC of the Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación, Madrid, Spain and FONDOS FEDER (no. CB16/12/00400)

Convalescent plasma for COVID-19 in hospitalised patients : an open-label, randomised clinical trial

Background: The effects of convalescent plasma (CP) therapy in hospitalised patients with coronavirus disease 2019 (COVID-19) remain uncertain. This study investigates the effect of CP on clinical improvement in these patients. Methods: This is an investigator-initiated, randomised, parallel arm, open-label, superiority clinical trial. Patients were randomly (1:1) assigned to two infusions of CP plus standard of care (SOC) or SOC alone. The primary outcome was the proportion of patients with clinical improvement 28 days after enrolment. Results: A total of 160 (80 in each arm) patients (66.3% critically ill, 33.7% severely ill) completed the trial. The median (interquartile range (IQR)) age was 60.5 (48–68) years; 58.1% were male and the median (IQR) time from symptom onset to randomisation was 10 (8–12) days. Neutralising antibody titres >1:80 were present in 133 (83.1%) patients at baseline. The proportion of patients with clinical improvement on day 28 was 61.3% in the CP+SOC group and 65.0% in the SOC group (difference −3.7%, 95% CI −18.8–11.3%). The results were similar in the severe and critically ill subgroups. There was no significant difference between CP+SOC and SOC groups in pre-specified secondary outcomes, including 28-day mortality, days alive and free of respiratory support and duration of invasive ventilatory support. Inflammatory and other laboratory marker values on days 3, 7 and 14 were similar between groups. Conclusions: CP+SOC did not result in a higher proportion of clinical improvement on day 28 in hospitalised patients with COVID-19 compared to SOC alone

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Educomunicação e suas áreas de intervenção: Novos paradigmas para o diálogo intercultural

oai:omp.abpeducom.org.br:publicationFormat/1O material aqui divulgado representa, em essência, a contribuição do VII Encontro Brasileiro de Educomunicação ao V Global MIL Week, da UNESCO, ocorrido na ECA/USP, entre 3 e 5 de novembro de 2016. Estamos diante de um conjunto de 104 papers executivos, com uma média de entre 7 e 10 páginas, cada um. Com este rico e abundante material, chegamos ao sétimo e-book publicado pela ABPEducom, em seus seis primeiros anos de existência. A especificidade desta obra é a de trazer as “Áreas de Intervenção” do campo da Educomunicação, colocando-as a serviço de uma meta essencial ao agir educomunicativo: o diálogo intercultural, trabalhado na linha do tema geral do evento internacional: Media and Information Literacy: New Paradigms for Intercultural Dialogue

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost