SatSel: A Satellite Selection Algorithm to reduce delivery time in DTN-Nanosatellite Networks for Internet Access in Rural Areas.

There are some different ways to connect rural areas to the Internet. One of these provides the use of a nanosatellite constellation. This type of network allows people in rural areas to enjoy all services the Internet can offer keeping low the cost of Internet access. One of the critical aspect is related to the delivery time, because LEO satellite links are not always up. This means that the system must be able to deal with periodic disruptions and high delays in the path from the source to the destination, considering that data could be stored in nanosatellite, Internet gateway (also called hot spot), and rural gateway (also called cold spot) buffers also for several seconds or minutes waiting to be forwarded. In the path from rural areas to the Internet, it is possible to reduce data delivery time acting on rural gateways. We propose SatSel: a selection algorithm which allows the cold spots to choose the nanosatellite to whom upload data in order to reduce the data delivery tim

Edelfosine impact on HLA-DR/DP/DQ expression on human T cells.

<p>(A) Gating strategy to identify viable CD4⁺ and CD8⁺ T cells and their naïve (CD27⁺CD45RA⁺) and memory (CD27⁺CD45RA⁻) subsets after the incubation of PBMCs for 24 h in the absence of edelfosine or in the presence of 3.3 µg/ml and 10 µg/ml edelfosine, respectively. (B) Representative histograms of one donor display the considerably low expression of HLA-DR/DP/DQ on the previously described T cell subsets. (C) Summary of MedFI values determined for each treatment within each T cell subset (n = 3 donors (represented by symbols •, ▪, ▴), + edelfosine added as indicated, − no edelfosine added). For CD27⁺CD45RA⁺ and CD27⁺CD45RA⁻ populations of CD4⁺ and CD8⁺ T cells no significant reduction of HLA-DR/DP/DQ expression was observed after Bonferroni post-hoc analysis (depicted P-value: as determined by repeated measures ANOVA). Histogram legends for B: no edelfosine (black line), 3.3 µg/ml edelfosine (green line), 10 µg/ml edelfosine (red line), isotype control (blue line).</p

Edelfosine impact on T cell viability.

<p>(A) Gating strategy to determine frequencies of annexin V⁺ and/or PI⁺ CD4⁺ as well as CD8⁺ T cells. Dot plots for annexin V and PI gating of approaches in absence of edelfosine, with 10 µg/ml edelfosine, or 33.3 µg/ml edelfosine. (B) With regard to CD4⁺ T cells just 10 µg/ml edelfosine led to a decrease in annexin V⁻PI⁻ frequencies accompanied by a remarkable increase in annexin V⁺PI⁺CD4⁺ T cell frequencies. In the case of CD8⁺ T cells a marked decrease in annexin V⁻PI⁻ cells was only observed with 33.3 µg/ml edelfosine which resulted in comparable frequencies of annexin V⁺PI⁻ as well as annexin V⁺PI⁺ cells. PBMCs of a donor were seeded in triplicates and pooled before analysis.</p

Human T cell proliferation was affected by edelfosine.

<p>(A) Reduced PBMC proliferation upon addition of edelfosine on cell seeding was independent of the addition of PHA. Notably, PHA-activated cells appeared to be susceptible to edelfosine at 10-fold lower concentrations. (B) The inhibitory effect of edelfosine was observed if the drug was added to already activated, proliferating T cells, i.e. two days after cell seeding and PHA addition. Here, a significant reduction of proliferation in unstimulated cells was only detectable with 33.3 µg/ml edelfosine. (C) Preincubation of PBMCs with at least 3.3 µg/ml edelfosine interfered with the cells' capacity to proliferate upon PHA stimulation. No effect was detected in preconditioned, but unstimulated cells (experiments A, B, C: sample size n = 3 donors, each approach was seeded in triplicates and means for each donor are represented by symbols •, ▪, ▴). (D) 1 µg/ml edelfosine or higher concentrations profoundly diminished proliferation in MBP_(83–99)-specific TCLs. One representative TCL of two is shown. Cells were incubated in quadruplicates. • stimulated, ▪ unstimulated (E) PBMCs of one donor were cultured without addition of a stimulus. Proliferation was detectable after seven days. The presence of anti-HLA-DR- and anti-MHC class I-blocking antibodies or 3.3 µg/ml edelfosine inhibited cellular proliferation (• untreated, ▪ blocking antibodies added, ▴ 3.3 µg/ml edelfosine-treated). Bars represent mean values ± SEM, *P<0.05, **P<0.01 and ***P<0.001 after repeated measures ANOVA succeeded by Bonferroni post-hoc analysis.</p

Modulated gene expression in CD4⁺ T cells upon culture with edelfosine.

<p>Numbers of differentially up- or downregulated genes after incubation with edelfosine are shown.</p

Cytokine secretion was modulated in activated CD4⁺ T cells by edelfosine.

<p>(A) By ELISA, a significant reduction of IFN-γ-secretion was monitored upon edelfosine treatment. (B) This result was confirmed by a human 13plex kit which allowed the detection of not only reduced concentrations of IFN-γ in supernatants of edelfosine-treated cells, but also reduced concentrations of the Th1-associated cytokines IL-2 and TNF-α as well as the Th17-associated cytokines IL-17A, IL-22 and IL-6. Cells of four individuals (age-matched, two males and two females) were used, error bars indicate SEM of respective means (*P<0.05 after paired t-tests).</p

Clustering of up- or downregulated genes to determine biological pathways affected by edelfosine in human CD4⁺ T cells after gene expression analysis.

<p>(A) The incubation of unstimulated cells with 10 µg/ml edelfosine resulted in the upregulation of apoptosis- and cell death-associated genes. Genes involved in immune response and antigen processing and presentation were downregulated. (B) In the case of stimulated cells which were cultured in presence of 3.3 µg/ml edelfosine the downmodulation of cell cycle progression-related genes was found. Additionally, edelfosine resulted in the upregulation of genes assigned to immune response- and virus response-pathways characterized by type I IFN-regulated genes.</p

Edelfosine impact on HLA-DR/DP/DQ expression on human B cells.

<p>(A) Gating strategy to identify viable CD19⁺ B cells and their IgD⁺CD27⁻, IgD⁺CD27⁺ and IgD⁻ CD27⁺ subsets after the incubation of PBMCs for 24 h in the absence of edelfosine or in the presence of 3.3 µg/ml and 10 µg/ml edelfosine, respectively. (B) Histograms, exemplary of one donor, display the edelfosine-induced downmodulation of HLA-DR/DP/DQ on the previously described B cell subsets in comparison to the respective untreated control approach. (C) Summary of MedFI values determined for each treatment within each B cell subset (n = 3 donors (represented by symbols •, ▪, ▴), + edelfosine added as indicated, − no edelfosine added). For CD19⁺, IgD⁺CD27⁻ and IgD⁺CD27⁺ populations significant reductions of HLA-DR/DP/DQ expression were observed (*P<0.05, **P<0.01, ***P<0.001 after repeated measures ANOVA and Bonferroni post-hoc analysis). Histogram legends for B: no edelfosine (black line), 3.3 µg/ml edelfosine (green line), 10 µg/ml edelfosine (red line), isotype control (blue line).</p

T cell activation alters mRNA expression of specific ion channel subunits.

<p>A, B, Bar diagram summarizing n-fold increase or decrease in intensity of hybridization signals obtained by probing oligonucleotide-based arrays with Cy3 and Cy5 labeled cDNA derived from mRNA isolated from non-activated and PHA-L activated PBMCs, respectively. Gray bars – custom-made array (n = 14) (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0104692#pone.0104692.s002" target="_blank">Tables S1</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0104692#pone.0104692.s003" target="_blank">S2</a>); black bars – Affimetrix array (human U133A 2.0; n = 6). Error bars are SEM. Channel subunit genes are indicated on the left. Nomenclature is from <a href="http://www.ncbi.nlm.nih.gov/omim" target="_blank">http://www.ncbi.nlm.nih.gov/omim</a>. Brackets - selectivity of corresponding ion channel. cat – cation; n.p. – not present in array; n.d. – not determined. CD25 (IL2RA) served as control. C, Bar diagram summarizing qPCR results for changes in mRNA expression of purified CD4⁺ and CD8⁺ T cells activated with anti-CD3/CD28 antibody-coated beads (n = 5–8). D, qPCR analysis of P2RX5 mRNA expression in activated CD4⁺ T cells in absence (▴) or presence (□) of cycloheximide (n = 3). Error bars are SEM.</p

Presentation_1.PDF

<p>The antigen-specific activation of pathogenic T cells is considered essential in the initiation and maintenance of multiple sclerosis (MS). The site of activation, the differential involvement of CD4+, and CD8+ T cells, their functional phenotype, and specificity, are important aspects to understand MS pathogenesis. The analysis of clonal expansions of brain-infiltrating T cells may reveal local antigen-driven activation or specific brain homing and allow the identification of putatively pathogenic T cells. We used high-throughput T cell receptor β-chain variable gene (TRBV) sequencing (-seq) of genomic (g)DNA, which reflects the quantity and diversity of the TRBV repertoire, to characterize three white matter demyelinating lesions with different location and inflammatory activity, and paired peripheral blood memory CD4+ and CD8+ T cell pools from a secondary progressive (SP)MS patient. Our results revealed an important sharing of clonally expanded T cells with identical TRBV sequence (clonotypes) across MS lesions independently of their proximity or inflammatory activity. Comparison with circulating T cells showed that the most frequent brain-infiltrating CD8+, but not CD4+ clonotypes were also those with highest frequency in the peripheral blood, indicating clonal expansion inside the brain or specific brain homing of CD4+ but not CD8+ T cells. Parallel TRBV-seq of complementary (c)DNA that reflects the activation status of the cells, revealed differences between lesions regarding inflammatory activity and appears to facilitate the identification of putatively pathogenic T cells in active lesions. Approaches to identify pathogenic T cells in brain lesions using TRBV-seq may benefit from focusing on lesions with high inflammatory activity and from combining gDNA and cDNA sequencing.</p