64 research outputs found
Impact of Cytomegalovirus and Grafts versus Host Disease on the Dynamics of CD57+CD28−CD8+ T Cells After Bone Marrow Transplant
OBJECTIVES: The present study aimed to evaluate the dynamics of CD28 and CD57 expression in CD8+ T lymphocytes during cytomegalovirus viremia in bone marrow transplant recipients. METHODS: In a prospective study, blood samples were obtained once weekly once from 33 healthy volunteers and weekly from 33 patients. To evaluate the expression of CD57 and CD28 on CD8+ T lymphocytes, flow cytometry analysis was performed on blood samples for four months after bone marrow transplant, together with cytomegalovirus antigenemia assays. RESULTS: Compared to cytomegalovirus-seronegative healthy subjects, seropositive healthy subjects demonstrated a higher percentage of CD57+ and a lower percentage of CD28+ cells (p<0.05). A linear regression model demonstrated a continuous decrease in CD28+ expression and a continuous increase in CD57+ expression after bone marrow transplant. The occurrence of cytomegalovirus antigenemia was associated with a steep drop in the percentage of CD28+ cells (5.94%, p<0.01) and an increase in CD57+ lymphocytes (5.60%, p<0.01). This cytomegalovirus-dependent effect was for the most part concentrated in the allogeneic bone marrow transplant patients. The development of acute graft versus host disease, which occurred at an earlier time than antigenemia (day 26 vs. day 56 post- bone marrow transplant), also had an impact on the CD57+ subset, triggering an increase of 4.9% in CD57+ lymphocytes (p<0.05). CONCLUSION: We found continuous relative changes in the CD28+ and CD57+ subsets during the first 120 days post- bone marrow transplant, as part of immune system reconstitution and maturation. A clear correlation was observed between the expansion of the CD57+CD28-CD8+ T lymphocyte subpopulation and the occurrence of graft versus host disease and cytomegalovirus viremia
The sample processing time interval as an influential factor in flow cytometry analysis of lymphocyte subsets
Validation of a yellow fever vaccine model using data from primary vaccination in children and adults, re-vaccination and dose-response in adults and studies with immunocompromised individuals
Background: An effective yellow fever (YF) vaccine has been available since 1937. Nevertheless, questions regarding its use remain poorly understood, such as the ideal dose to confer immunity against the disease, the need for a booster dose, the optimal immunisation schedule for immunocompetent, immunosuppressed, and pediatric populations, among other issues. This work aims to demonstrate that computational tools can be used to simulate different scenarios regarding YF vaccination and the immune response of individuals to this vaccine, thus assisting the response of some of these open questions.
Results: This work presents the computational results obtained by a mathematical model of the human immune response to vaccination against YF. Five scenarios were simulated: primovaccination in adults and children, booster dose in adult individuals, vaccination of individuals with autoimmune diseases under immunomodulatory therapy, and the immune response to different vaccine doses. Where data were available, the model was able to quantitatively replicate the levels of antibodies obtained experimentally. In addition, for those scenarios where data were not available, it was possible to qualitatively reproduce the immune response behaviours described in the literature.
Conclusions: Our simulations show that the minimum dose to confer immunity against YF is half of the reference dose. The results also suggest that immunological immaturity in children limits the induction and persistence of long-lived plasma cells are related to the antibody decay observed experimentally. Finally, the decay observed in the antibody level after ten years suggests that a booster dose is necessary to keep immunity against YF
Viscerotropic disease: case definition and guidelines for collection, analysis, and presentation of immunization safety data
Viscerotropic disease (VTD) is defined as acute multiple organ system dysfunction that occurs following vaccination. The severity of VTD ranges from relatively mild multisystem disease to severe multiple organ system failure and death. The term VTD was first used shortly after the initial published reports in 2001 of febrile multiple organ system failure following yellow fever (YF) vaccination. To date, VTD has been reported only in association with YF vaccine and has been thus referred to as YF vaccine-associated viscerotropic disease (YEL-AVD)
Immune response to the mumps component of the MMR vaccine in the routine of immunisation services in the Brazilian National Immunisation Program
Neonatal infections: Case definition and guidelines for data collection, analysis, and presentation of immunisation safety data.
Maternal vaccination is an important area of research and requires appropriate and internationally comparable definitions and safety standards. The GAIA group, part of the Brighton Collaboration was created with the mandate of proposing standardised definitions applicable to maternal vaccine research. This study proposes international definitions for neonatal infections. The neonatal infections GAIA working group performed a literature review using Medline, EMBASE and the Cochrane collaboration and collected definitions in use in neonatal and public health networks. The common criteria derived from the extensive search formed the basis for a consensus process that resulted in three separate definitions for neonatal blood stream infections (BSI), meningitis and lower respiratory tract infections (LRTI). For each definition three levels of evidence are proposed to ensure the applicability of the definitions to different settings. Recommendations about data collection, analysis and presentation are presented and harmonized with the Brighton Collaboration and GAIA format and other existing international standards for study reporting
Historical review of clinical vaccine studies at Oswaldo Cruz Institute and Oswaldo Cruz Foundation - technological development issues
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
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