Journal: Viruses

Article Title: Characterization of Natural Killer Cell Profile in a Cohort of Infected Pregnant Women and Their Babies and Its Relation to CMV Transmission

doi: 10.3390/v16050780

Figure Lengend Snippet: Comparative analysis of NK cell profile in CMV-transmitting vs. non-transmitting mothers. ( A,B ) Scatter plots with bar (mean ± SD) depict frequency distribution, as in B,C. Unpaired t test and Mann–Whitney test were used to assess differences in cell frequencies between transmitting (red dots, n = 8) and non-transmitting (blue dots, n = 9) mothers. Significance was set at p < 0.05. ( C ) tSNE algorithm was configured to distribute data combined from transmitting and non-transmitting mothers’ samples according to the expression of NK cell markers CD56, CD16, NKG2C, NKG2A, CD57, NKG2D, DNAM-1, KIRs, and PD-1. Multigraph histogram overlays with geomean values were generated in a combined FCS file obtained by concatenating 2000 events in NK cell down-sample (identified as CD3-CD19-CD14- live lymphocytes) of transmitting (red, n = 7) and non-transmitting (blue, n = 8) mothers. ( D ) By using the same combined FCS file, single parameter heatmaps were obtained for transmitting (upper panels) and non-transmitting (lower panels) groups. Outline population (black circle) is specific to non-transmitting mothers and only the expressed markers are reported. TD NK: terminally differentiated NK; ML NK: memory-like NK.

Article Snippet: The “DownSample” FlowJo plugin was run on NK cells in order to reduce and make uniform the population sizes for the further concatenation of samples from different groups into a single FCS file. tSNE was performed on the concatenated file using the “TSNE” plugin and the maps generated using data from the following compensated parameters as inputs: CD56, CD16, NKG2C, NKG2A, NKG2D, DNAM-1, CD57, KIR2DL1/S1/S3/S5, KIR2DL2/L3, and PD-1 for the phenotype analysis and CD56, CD16, NKG2C, DNAM-1, CD57, NKp46, PD-1, and CD107a for the degranulation analysis; under the following tSNE settings: iteration 1000, perplexity 30, learning rate (Eta) 910–2100, the ANNOY algorithm as the k nearest neighbors (KNN) algorithm and the fast Fourier transform (FTT) interpolation as the gradient algorithm, resulting in tSNE plots with less than 5 million events ( ).

Techniques: MANN-WHITNEY, Expressing, Generated

Journal: Viruses

Article Title: Characterization of Natural Killer Cell Profile in a Cohort of Infected Pregnant Women and Their Babies and Its Relation to CMV Transmission

doi: 10.3390/v16050780

Figure Lengend Snippet: Comparative analysis of NK cell profile in newborns with or without CMV congenital infection. ( A , B ) Scatter plots with bar (mean ± SD) depict frequency distribution, as in B,C. Mann–Whitney test was used to assess differences in cell frequencies between congenital (purple dots, n = 12) and non-congenital (pink dots, n = 5) newborns. Significance was set at p < 0.05. ( C ) tSNE algorithm was configured to distribute data combined from congenital and non-congenital children’s samples according to C. Multigraph histogram overlays with geomean values were generated in a combined FCS file obtained by concatenating 1880 events in NK cell down-sample of congenital (purple, n = 11) and non-congenital (pink, n = 5) children. ( D ) By using the same combined FCS file, single parameter heatmaps were obtained for congenital (upper panels) and non-congenital (lower panels) groups. Outline population (black circle) is specific to congenital children and only the expressed markers are reported. TD NK: terminally differentiated NK; ML NK: memory-like NK.

Article Snippet: The “DownSample” FlowJo plugin was run on NK cells in order to reduce and make uniform the population sizes for the further concatenation of samples from different groups into a single FCS file. tSNE was performed on the concatenated file using the “TSNE” plugin and the maps generated using data from the following compensated parameters as inputs: CD56, CD16, NKG2C, NKG2A, NKG2D, DNAM-1, CD57, KIR2DL1/S1/S3/S5, KIR2DL2/L3, and PD-1 for the phenotype analysis and CD56, CD16, NKG2C, DNAM-1, CD57, NKp46, PD-1, and CD107a for the degranulation analysis; under the following tSNE settings: iteration 1000, perplexity 30, learning rate (Eta) 910–2100, the ANNOY algorithm as the k nearest neighbors (KNN) algorithm and the fast Fourier transform (FTT) interpolation as the gradient algorithm, resulting in tSNE plots with less than 5 million events ( ).

Techniques: Infection, MANN-WHITNEY, Generated

Journal: Viruses

Article Title: Characterization of Natural Killer Cell Profile in a Cohort of Infected Pregnant Women and Their Babies and Its Relation to CMV Transmission

doi: 10.3390/v16050780

Figure Lengend Snippet: NK cell degranulation ( A ) tSNE algorithm was generated for CD107a+ NK cells and configured to distribute data combined from study cohorts of stimulated samples according to the expression of NK cell markers CD56, CD16, CD107a, NKG2C, CD57, NKp46, DNAM-1, and PD-1. Multigraph histogram overlays with geomean values were generated in two combined FCS files. One was obtained by concatenating 1000 events in NK cell down-sample of either CMV-infected (orange, n = 9) and uninfected (green, n = 4) pregnant women or transmitting (red, n = 5) and non-transmitting (blue, n = 4) mothers. The other one was obtained by concatenating 1180 events in the NK cell down-sample of congenital (purple, n = 7) and non-congenital (pink, n = 5) children. ( B ) By using the same combined FCS files, single parameter heatmaps were obtained for each study group. Outline populations (black circles) are specific to infected pregnant women and congenital children, and only the expressed markers are reported.

Article Snippet: The “DownSample” FlowJo plugin was run on NK cells in order to reduce and make uniform the population sizes for the further concatenation of samples from different groups into a single FCS file. tSNE was performed on the concatenated file using the “TSNE” plugin and the maps generated using data from the following compensated parameters as inputs: CD56, CD16, NKG2C, NKG2A, NKG2D, DNAM-1, CD57, KIR2DL1/S1/S3/S5, KIR2DL2/L3, and PD-1 for the phenotype analysis and CD56, CD16, NKG2C, DNAM-1, CD57, NKp46, PD-1, and CD107a for the degranulation analysis; under the following tSNE settings: iteration 1000, perplexity 30, learning rate (Eta) 910–2100, the ANNOY algorithm as the k nearest neighbors (KNN) algorithm and the fast Fourier transform (FTT) interpolation as the gradient algorithm, resulting in tSNE plots with less than 5 million events ( ).

Techniques: Generated, Expressing, Infection