anti cd4  (fluidigm)

Journal: iScience

Article Title: T cells with increased responsiveness cause obesity in mice without diet intervention

doi: 10.1016/j.isci.2024.109471

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Article Snippet: Anti-CD4 , Standard BioTools , Cat# 3172003B; RRID:AB_2811242.

Techniques: Recombinant, Lysis, Red Blood Cell Lysis, Staining, Blocking Assay, Cell Isolation, Labeling, Sequencing, Software, Flow Cytometry, Cytometry

Journal: Cell reports

Article Title: AXL-initiated paracrine activation of pSTAT3 enhances mesenchymal and vasculogenic supportive features of tumor-associated macrophages

doi: 10.1016/j.celrep.2023.113067

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Article Snippet: Anti-Mouse CD4 172Yb , Fluidigm , Cat#3172003B; RRID: AB_2811242.

Techniques: Recombinant, Reverse Transcription, Cell Viability Assay, In Situ, SYBR Green Assay, RNA Sequencing, Quantitative RT-PCR, Luciferase, Software

Journal: iScience

Article Title: From pseudo to real-time dynamics of T cell thymic differentiation.

doi: 10.1016/j.isci.2022.105826

Figure Lengend Snippet: Figure 1. Dimensionality reduction and segmentation (A) Cell differentiation in the thymus. Scatterplot of cells in representative mouse (yellow) depicts a snapshot of the maturation process, with naive cells entering the thymus in the double-negative state (DN, CD4CD8), sequentially differentiating into double-positive cells (DP, CD4+CD8+), and finally acquiring one of the single-positive fates (SP, CD4+/ CD8/+). Arcsine transformation was used here and for gating purposes (see STAR Methods). (B) Five simulated markers. Profiles are shown without adding noise. Each time step (dt = 0.01), 100 new cells were added and assigned with t = 0. Initial marker values for each cell were chosen from a normal distribution centered at the values plotted at t = 0, with a SD of 0.1. Noise was also added to the cycle time length of each cell (after which the cell was removed) which was chosen from a normal distribution centered at T = 1 with a SD of 0.1. Division and apoptosis were not implemented in these simulations, which were run until reaching the steady state. (C) Trajectory course calculated upon density plot of two markers in B. Starting and ending points are predetermined (upper and lower crosses respectively). Anchors (corresponding symbols) are placed in positions of local maxima. The trajectory (red circles) travels upon the crest connecting path edges and anchors. Panel to the right magnifies the last position obtained and illustrates how new position coordinates are chosen; new coordinates are chosen from nearest neighbors surrounding the previous position on a grid, where progression in the direction of the previous position is forbidden (optional new coordinates are surrounded by black circles). Default choice is for the neighbor in the direction aligned toward the next anchor (moment). Deviation is permitted only if the difference in densities between the default neighbor and some other permitted neighbor exceeds a predetermined value, thereby justifying a detour. See methods for more details. (D) Trajectory calculation in five dimensions. The principle is similar to calculation in two dimensions (see text), allowing for trajectory dynamics in any region where at least one of the markers changes. The calculated trajectory is projected here upon a two-dimensional density plot, with anchors and crosses representing landmarks as in C. Note that anchors are placed near, but not in the exact position, of the global maxima in two dimensions (see methods for superfluous anchor removal in higher dimensions).

Article Snippet: Anti-Mouse CD4 (RM4-5)-172 Yb FLUIDIGM RRID:AB_2924892.

Techniques: Cell Differentiation, Transformation Assay, Marker

Journal: iScience

Article Title: From pseudo to real-time dynamics of T cell thymic differentiation.

doi: 10.1016/j.isci.2022.105826

Figure Lengend Snippet: Figure 4. A two-step segmentation process (A and B) Since one-step segmentation in higher dimensions can lead to significant dispersal of cells along the projected trajectory in CD4/CD8 space (e.g. assigning DN cells to points far along the trajectory, supplemental information Figure S4), segmentation was first performed in 2D. Panel in A shows the trajectory upon the density plot in CD4/CD8 space, leading from DN to DP, and splitting toward SP states. The time equation was solved separately for the DN + DP phase and each SP phase. Sequentially, each segment was sub-segmented using more markers (8 dimensions) as illustrated in B. A zoomed portion of the trajectory calculated in A is shown, with cells between two pairs of points colored differently (green and pink). The grid size for sub-segmentation was proportionally chosen with respect to the relative time spent in the original segment (Dt), potentially resulting in the addition of more or less time points.

Article Snippet: Anti-Mouse CD4 (RM4-5)-172 Yb FLUIDIGM RRID:AB_2924892.

Techniques:

Journal: iScience

Article Title: From pseudo to real-time dynamics of T cell thymic differentiation.

doi: 10.1016/j.isci.2022.105826

Figure Lengend Snippet: Figure 5. Real-time axis validation (A) In-vivo validation was performed by intrathymic, adoptive transfer of DN1-3 (CD4CD8CD44+/CD25+/) cells from CD45.1 mice (B6SJL) into CD45.2 (C57BL) mice (left and center panel). Thymi were harvested 1, 3, 10, 14, 21, and 28 days post-transfer and stained with antibodies against CD45.1, CD45.2, CD8, CD4, and other developmental markers (center). Further analysis was performed by gating the CD45.1+/CD45.2- cells. Each time point presents Thymi from two mice, and the experiment was repeated twice. (B) CD8 (Black) and CD4 (Red) expression levels were calculated by tracking the CD45.1+/CD45.2- gated cells. The expression levels for CD4 and CD8 were separately normalized to the median fluorescence of all the cells from all the time points. Black broken vertical lines separate here (and in later figures) between the DN, DP, and SP phases as indicated on top. (C) CD4 and CD8 profiles as constructed by our method for real-time axis inference averaged across 12 mice. (D) Wishbone pseud-temporal ordering captures the major stages in T cell development but scales differently than the real-time axis.

Article Snippet: Anti-Mouse CD4 (RM4-5)-172 Yb FLUIDIGM RRID:AB_2924892.

Techniques: Biomarker Discovery, In Vivo, Adoptive Transfer Assay, Staining, Expressing, Construct

Journal: iScience

Article Title: From pseudo to real-time dynamics of T cell thymic differentiation.

doi: 10.1016/j.isci.2022.105826

Figure Lengend Snippet: Figure 6. The real-time axis is able to unfold regions of biological significance (A-C) CD69, IDU, and cPARP real-time trajectory profiles along the CD4 SP and CD8 SP paths (left and center panels respectively, averging data from 12 mice.), and along Wishbone pseudotime trajectory (right, one mouse). Black broken vertical lines separate between DN, DP, and SP phases as in Figure 5. Black arrows in A indicate the second elevation in CD69 expression which is spread over several days along the real-time axis as opposed to the relative condensed portion it occupies in the Wishbone trajectory.

Article Snippet: Anti-Mouse CD4 (RM4-5)-172 Yb FLUIDIGM RRID:AB_2924892.

Techniques: Expressing