9 research outputs found

    Flowchart of selection and follow-up of the Study Population from the Primary Target Sample.

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    <p>A total of 3,060 children, 9–12 months-old were elected for an epidemiological studies reported elsewhere <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0049828#pone.0049828-Collaborative1" target="_blank">[14]</a> and referred as “Primary Target Sample”. The Clinical Trial design is highlighted by dashed format. The study population enrolled in the present investigation was selected from the “Primary Target Sample” according to the PRNT results and comprise 30 PV-PRNT<sup>+</sup> and 10 PV-PRNT<sup>−</sup> individuals on each experimental arm (17DD and 17D-213/77), reaching a total of 80 volunteers. The current Immunological Study design is highlighted by solid format.</p

    Comparative analysis of the cytokine signatures of innate and adaptive immunity triggered by the YF-17DD and YF-17D-213/77 substrains upon the <i>in vitro</i> recall of whole blood leukocytes from seroconverter children (PV-PRNT<sup>+</sup>) with specific YF-Ag.

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    <p>The diagrams highlight each leukocyte subsets with distinct tags as they display low (white rectangle) or high (black rectangle = inflammatory, gray rectangle = regulatory) cytokine producers (top panel). The ascendant frequency of volunteers with high cytokine indexes of the innate and adaptive immunity was assembled for each experimental arm and is demonstrated by bar graphs (medium panel). Comparative analysis of the overall cytokine patterns of YF-17DD (lines with black or gray triangles) and YF-17D-213/77 (lines with black or gray squares) vaccinees were further compared by overlapping the ascendant cytokine curves (bottom panel). Dotted lines highlight the 25<sup>th</sup> and 50<sup>th</sup> percentiles used as reference for comparative analysis. *Differences were considered relevant when the frequency for a given cytokine emerged outside the 50<sup>th</sup> percentile as compared to the reference cytokine pattern or signature.</p

    Impact of serum titers of anti-YF neutralizing antibodies on the cytokine-mediated immune response triggered by the YF-17DD and YF-17D-213/77 substrains upon <i>in vitro</i> recall of whole blood leukocytes from seroconverter children (PV-PRNT<sup>+</sup>) with specific YF-Ag.

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    <p>The PRNT<sup>+</sup> groups from each experimental arm were first categorized into two subgroups referred to as PV-PRNT<sup>MEDIUM+</sup> (2.5≤ serum titers ≤3.5 log<sub>10</sub> mIU/mL) and PV-PRNT<sup>HIGH+</sup> (serum titers >3.5 log<sub>10</sub> mIU/mL). The cytokine profile of the PV-PRNT<sup>MEDIUM+</sup> and PV-PRNT<sup>HIGH+</sup> subgroups were evaluated, considering relevant the percentages of a given inflammatory cytokine that emerged higher than the 50<sup>th</sup> percentile, as indicate by an upward arrow (↑).</p

    Comparative inflammatory and regulatory cytokine signatures triggered by the YF-17DD and YF-17D-213/77 substrains upon the <i>in vitro</i> recall of whole blood leukocytes from (A) seroconverter (PV-PRNT<sup>+</sup>) and nonseroconverter primary vaccinees (PV-PRNT<sup>−</sup>) as well as (B) seroconverter revaccinees (RV-PRNT<sup>+</sup>) with specific YF-Ag.

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    <p>The ascendant frequency of volunteers with high inflammatory and regulatory cytokine indexes was assembled for each experimental arm and demonstrated by bar graphs. Comparative analysis between PV-PRNT<sup>+</sup>, PV-PRNT<sup>−</sup>, and RV-PRNT<sup>+</sup> within the same experimental arm was performed taking the ascendant cytokine curve of the YF-17DD (lines with black or gray triangles) or YF-17D-213/77 (lines with black or gray squares) groups as reference. #Differences were considered relevant when the percentage of a given cytokine emerged below the quartile of the reference cytokine signatures.</p

    Multi-parameter approach to evaluate the timing of memory status after 17DD-YF primary vaccination

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    <div><p>In this investigation, machine-enhanced techniques were applied to bring about scientific insights to identify a minimum set of phenotypic/functional memory-related biomarkers for post-vaccination follow-up upon yellow fever (YF) vaccination. For this purpose, memory status of circulating T-cells (Naïve/early-effector/Central-Memory/Effector-Memory) and B-cells (Naïve/non-Classical-Memory/Classical-Memory) along with the cytokine profile (IFN/TNF/IL-5/IL-10) were monitored before-NV(day0) and at distinct time-points after 17DD-YF primary vaccination—PV(day30-45); PV(year1-9) and PV(year10-11). A set of biomarkers (eEfCD4; EMCD4; CMCD19; EMCD8; IFNCD4; IL-5CD8; TNFCD4; IFNCD8; TNFCD8; IL-5CD19; IL-5CD4) were observed in PV(day30-45), but not in NV(day0), with most of them still observed in PV(year1-9). Deficiencies of phenotypic/functional biomarkers were observed in NV(day0), while total lack of memory-related attributes was observed in PV(year10-11), regardless of the age at primary vaccination. Venn-diagram analysis pre-selected 10 attributes (eEfCD4, EMCD4, CMCD19, EMCD8, IFNCD4, IL-5CD8, TNFCD4, IFNCD8, TNFCD8 and IL-5CD4), of which the overall mean presented moderate accuracy to discriminate PV(day30-45)&PV(year1-9) from NV(day0)&PV(year10-11). Multi-parameter approaches and decision-tree algorithms defined the EMCD8 and IL-5CD4 attributes as the top-two predictors with moderated performance. Together with the PRNT titers, the top-two biomarkers led to a resultant memory status observed in 80% and 51% of volunteers in PV(day30-45) and PV(year1-9), contrasting with 0% and 29% found in NV(day0) and PV(year10-11), respectively. The deficiency of memory-related attributes observed at PV(year10-11) underscores the conspicuous time-dependent decrease of resultant memory following17DD-YF primary vaccination that could be useful to monitor potential correlates of protection in areas under risk of YF transmission.</p></div

    Overall 17DD-YF memory-related biomarker signatures at distinct time-points after primary vaccination.

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    <p>The phenotypic/functional biomarker signatures were built taking the proportion of subjects above the cut-off edges defined for each attribute, calculated as the median index value (17DD-YF/Control) for the study population. Diagrams were constructed for all study groups to calculate the proportion (%) of volunteers above the median cut-off indices for each biomarker (gray-shaded spots). (A) The PV(day30-45) group was used to construct the memory-related phenotypic and functional biomarker signatures and draw the reference curves, used for comparative analysis amongst the study groups, (B) NV(day0), (C) PV(year1-9) and (D) PV(year10-11). Hatched cells represent unavailable results. Data mining was carried out as proposed previously by Luiza-Silva et al., (2011), selecting from the PV(day30-45) reference curves, those biomarkers with more than 50% of volunteers above the cut-off index (surrounded by dashed rectangles). Comparative analysis amongst the study groups were carried out considering only the selected set of relevant biomarkers from the phenotypic and functional reference curves. Substantial change in the set of relevant biomarkers were highlighted by (*) when the proportion of subjects above the cut-off fell below 50%. The common set of relevant biomarkers on each study group was underscored in bold font.</p

    Changes in neutralizing antibody titers and phenotypic/functional memory-related biomarkers at distinct time-points after primary 17DD-YF vaccination.

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    <p>Correlation analyses were performed to validate the time-dependent decline in (A) neutralizing antibody titers and 17DD-YF Memory-related (B) phenotypic and (C) functional features. Data are expressed as scattering distribution of individual values along distinct time-points after 17DD-YF primary vaccination against neutralizing antibody titers (PRNT) as well as phenotypic and functional features (YF-Ag/CC Index). Spearman’s correlation test was applied to identify significant time-dependent loss of memory-related biomarkers. Correlation indices (p and r) along with the 95% confidence band of the best-fit line are provided in the figure. Attributes with higher correlation indices (r values) are highlighted with gray background.</p

    Major phenotypic/functional biomarkers useful to monitor the memory status following primary 17DD-YF vaccination.

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    <p>(A) Decision tree analysis was carried out to identify root attributes [Ellipses] for phenotypic/functional (P&F) biomarkers amongst NV(day0)&PV(year10-11) [white rectangle] and PV(day30-45)&PV(year1-9) [black rectangle], considered biomarkers to discriminate unprotected from protected subjects. Leave-one-out-cross-validation analysis (LOOCV) was employed to minimize biased performance estimates by using all data set for decision tree model fitting. EMCD8 and IL-5CD4 were selected as major phenotypic and functional 17DD-YF Memory-related biomarkers, respectively. (B) Heatmaps were built, taking the mean index of the top-two phenotypic/functional biomarkers (EMCD8 & IL-5CD4) and demonstrating the proportion (%) of volunteers ranging from low (White) to high (Gray) YF-Ag/CC index. A scatter plot was constructed to show the sensitivity (Gray Circle) and specificity (White Circle) of the top-two biomarkers, employing the cut-off edge (Mean Index = 1.3) provided by the ROC curve analysis. (C) Resultant memory status was defined for each subject, considering the top-two biomarkers (Mean Index >1.3) and PRNT (>2.9 Log mIU/mL, according to Simões et al., 2012). Column statistics were used to calculate the proportion of subjects displaying differing categories of resultant memory, referred as none, top-two biomarkers—P&F, PRNT and both. (D) Pie charts illustrated the overall resultant memory status within each category, as determined by the top-two biomarkers and PRNT. Significant differences at p<0.05 (Chi-square test) of resultant memory status amongst study groups were represented by letters “a”, b”, “c” and “d” in comparison to NV(day0), PV(day30-45), PV(year1-9) and PV(year10-11), respectively.</p

    17DD-YF memory-related biomarker signatures according to the age at primary vaccination.

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    <p>The memory-related biomarker signatures were constructed using the proportion of subjects above the cut-off edges defined for each attribute, calculated as the median index value (17DD-YF/Control) for the study population. The signatures were constructed for phenotypic/functional biomarkers, compiling the proportion (%) of volunteer above the median cut-off indices. The memory-related biomarker signatures, constructed for the PV(day30-45) group, were used as the reference curves for comparative analysis amongst the PV(year10-11) subgroups, categorized according to the age at primary vaccination, including (A) 20–30 years old, (B) 31–40 years old and (C) 41–74 years old. Comparative analysis were carried out considering only the set of relevant biomarkers pre-selected from the phenotypic/functional reference curves (surrounded by dashed rectangles), including those biomarkers with more than 50% of volunteers above the cut-off index in the PV(day30-45) reference curves (surrounded by dashed rectangles). Substantial changes in the set of relevant biomarkers were underscored by (*) when the proportion of subjects above the cut-off fell below 50%. The common set of relevant biomarkers on each study group was underscored in bold font.</p
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