Journal: Nutrients

Article Title: Investigation of Antibacterial and Antiinflammatory Activities of Proanthocyanidins from Pelargonium sidoides DC Root Extract

doi: 10.3390/nu11112829

Figure Lengend Snippet: The effect of Pelargonium sidoides root extract (PSRE) and proanthocyanidins from PSRE (PACN) on ( a ) interleukin-8 (IL-8) and ( b ) prostaglandin E2 (PGE2) secretion from gingival fibroblasts, and ( c ) interleukin-6 (IL-6) secretion from peripheral blood mononuclear cells after LPS treatment. Fifty and 100 represent the concentrations (μg/mL). The data are presented as means and standard deviations of seven experiments. *—significant difference compared to untreated control, #—significant difference compared to LPS only treatment and &—significant difference compared to LPS plus a 50 μg/mL PSRE treatment, p < 0.05.

Article Snippet: Human peripheral blood mononuclear cells (PBMCs) were purchased from ATCC (ATCC ® PCS-800-011TM, Manassas, VA, USA).

Techniques: Control

Journal: Nutrients

Article Title: Investigation of Antibacterial and Antiinflammatory Activities of Proanthocyanidins from Pelargonium sidoides DC Root Extract

doi: 10.3390/nu11112829

Figure Lengend Snippet: The effect of Pelargonium sidoides root extract (PSRE) and proanthocyanidins from PSRE (PACN) on proinflammatory gene expression in bone marrow-derived macrophages ( a – c ) and peripheral blood mononuclear cells ( d – f ) after LPS or LPS and IFN- stimulation. ( a , d ) IL-1β ( a , b ) iNOS, ( c , f ) TNF- and ( e ) COX-2. The data are expressed as a fold change of glucose-6-phosphate isomerase gene transcription and presented as mean ± SD of three independent measurements. *—significantly different from the LPS-treated samples (ANOVA followed by a Tukey’s multiple comparison test, p < 0.05).

Article Snippet: Human peripheral blood mononuclear cells (PBMCs) were purchased from ATCC (ATCC ® PCS-800-011TM, Manassas, VA, USA).

Techniques: Gene Expression, Derivative Assay, Comparison

Journal: Future Science OA

Article Title: Promising approach for targeting ROBO1 with CAR NK cells to combat ovarian cancer primary tumor cells and organoids

doi: 10.2144/fsoa-2023-0135

Figure Lengend Snippet: Strategy and materials in this study. (A) Diagram of the procedure in the study. The primary tumor cells and tumor organoids were generated from patients' tumor tissues and ROBO1-NK were constructed from patients' PBMCs. (B) IHC of ovarian tumor tissues. Negative control was used irrelevant IgG replacing primary antibody for incubating. Strong positive of ROBO1 expression on cell membrane was marked by red circles. (C) ROBO1 positively expressed in tumor tissues of the clinical ovarian cancer patient #01, #02, #03 and #04.

Article Snippet: In brief, PBMCs were isolated from the patient's peripheral blood using the MACSprepTM PBMC Isolation Kit (130-115-169, Miltenyi Biotec, Bergisch Gladbach, GER) employing the density gradient centrifugation method.

Techniques: Generated, Construct, Negative Control, Expressing, Membrane

Journal: Future Science OA

Article Title: Promising approach for targeting ROBO1 with CAR NK cells to combat ovarian cancer primary tumor cells and organoids

doi: 10.2144/fsoa-2023-0135

Figure Lengend Snippet: Characters of ROBO1-NK cells. (A) Morphology comparison of PBMCs (upper panel), PBMC-NK cells (mid panel) and ROBO1-NK cells (bottom panel) under bright field. (B) Biomarkers determination of ROBO1-NK cells by flow cytometry. For the biomarkers CD34, CD45, CD3, CD56 and CD16, negative controls were used irrelevant IgG replacing primary antibody for incubating, presented as red peaks. For the ROBO1-CAR detection, negative control was used PBMC-NK incubating with anti-CAR antibody, presented as red peak. Samples in detection were presented as blue peaks.

Article Snippet: In brief, PBMCs were isolated from the patient's peripheral blood using the MACSprepTM PBMC Isolation Kit (130-115-169, Miltenyi Biotec, Bergisch Gladbach, GER) employing the density gradient centrifugation method.

Techniques: Comparison, Flow Cytometry, Negative Control

Journal: Future Science OA

Article Title: Promising approach for targeting ROBO1 with CAR NK cells to combat ovarian cancer primary tumor cells and organoids

doi: 10.2144/fsoa-2023-0135

Figure Lengend Snippet: ROBO1-NK lyse ovarian cancer cell line and primary cancer cells. (A) Positive expression of ROBO1 on SKOV-3 cells. (B) Rate of SKOV-3 cell lysis with different E-T ratio. E: number of effective cells; T: number of target cells. (C) Time curve of different NK cells, including Mock-CAR-NK (blue), PBMC-NK (green), ROBO1-NK (red) and control (medium, black), lysing SKOV-3 cells. (D) Lysis rate of primary ovarian tumor cells from patient #01, #02, #03 and #04 by PBMC-NK and ROBO1-NK after 24 h, detected with CCK-8 assay. (E) Photograph of PBMC-NK and ROBO1-NK lysing efficacy on primary ovarian tumor cells after 48 h co-culturing. The primary cells were presented as spindle-like form while NK cells were spherical form with clusters.

Article Snippet: In brief, PBMCs were isolated from the patient's peripheral blood using the MACSprepTM PBMC Isolation Kit (130-115-169, Miltenyi Biotec, Bergisch Gladbach, GER) employing the density gradient centrifugation method.

Techniques: Expressing, Lysis, Control, CCK-8 Assay

Journal: Nature Communications

Article Title: Determining sequencing depth in a single-cell RNA-seq experiment

doi: 10.1038/s41467-020-14482-y

Figure Lengend Snippet: a Description of the sequencing budget allocation problem. Consider estimating the underlying gene distribution (top) from the noisy read counts obtained via sequencing (bottom). With a fixed number of reads to be sequenced, deep sequencing of a few cells accurately estimates each individual cell but lacks coverage of the entire distribution (left), whereas a shallow sequencing of many cells covers the entire population but introduces a lot of noise (right). b Optimal tradeoff. The memory T-cell marker gene S100A4 has 41.7k reads in the pbmc_4k dataset. For estimating the underlying gamma distribution \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${X}_{g} \sim {\rm{Gamma}}({r}_{g},{\theta }_{g})$$\end{document} X g ~ Gamma ( r g , θ g ) , the relative error is plotted as a function of the sequencing depth, where the optimal error is obtained at a depth of one read per cell (orange star) and is two times smaller than that at the current depth of pbmc_4k (red triangle). c Experimental design. To determine the sequencing depth for an experiment, first the relative gene expression level can be obtained via pilot experiments or previous studies (top left). Then the researcher can select a set of genes of interest (i.e., some marker genes highlighted as black dots), of which the smallest relative expression level \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${p}^{* }$$\end{document} p * ( MS4A1 ) defines the reliable detection limit. Finally, the optimal sequencing depth is determined as \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${n}_{{\rm{reads}}}^{* }=1/{p}^{* }$$\end{document} n reads * = 1 ∕ p * (top right). The errors under different tradeoffs are visualized as a function of the genes ordered from the most expressed to the least (bottom). The optimal sequencing budget allocation (orange) minimizes the worst-case error over all the genes of interest (left of the red dashed line), whereas both the deeper sequencing (green) and the shallower sequencing (blue) yield worse results.

Article Snippet: They are publicly available and can be downloaded via the following links: pbmc_4k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/pbmc4k pbmc_8k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/pbmc8k brain_1k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/neurons_900 brain_2k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/neurons_2000 brain_9k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/neuron_9k brain_1.3m: https://support.10xgenomics.com/single-cell-gene-expression/datasets/1.3.0/1M_neurons 293T_1k, 3T3_1k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/hgmm_1k 293T_6k, 3T3_6k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/hgmm_6k 293T_12k, 3T3_12k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/hgmm_12k We note that pbmc_4k and pbmc_8k are from the same donor; brain_1k and brain_9k are also from the same donor.

Techniques: Sequencing, Marker, Expressing

Journal: Nature Communications

Article Title: Determining sequencing depth in a single-cell RNA-seq experiment

doi: 10.1038/s41467-020-14482-y

Figure Lengend Snippet: a Top: for estimating the coefficient of variation (CV), the plug-in estimates become more inflated as the sequencing depth becomes shallower (from right to left along the x axis), whereas the EB estimates are consistent. 3-std confidence intervals are provided for this panel. Middle: both brain_1k and brain_1.3m are from the mouse brain, and hence each gene should have a similar CV value between the two datasets. This is indeed the case for the EB estimator (right), which is adaptive to different sequencing depths. However, as brain_1k is twice deeper than brain_1.3m, the plug-in estimates are biased that most points are above the 45-degree line (red). Bottom: distribution recovery for the gene GZMA from a dataset that is subsampled to be five times shallower (left). The EB estimator provides a reasonable estimation for both the zero proportion and the tail shape, resulting in a small total variation error (right). b Feature selection and PCA. The task is to first select features (genes) based on CV, and then perform PCA on the selected features. The results on the full data (pbmc_4k) and a subsampled (three times shallower) are compared. EB estimates are more consistent between the full data and the subsampled data for both the CV ranks (top) and the PCA plots (bottom).

Article Snippet: They are publicly available and can be downloaded via the following links: pbmc_4k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/pbmc4k pbmc_8k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/pbmc8k brain_1k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/neurons_900 brain_2k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/neurons_2000 brain_9k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/neuron_9k brain_1.3m: https://support.10xgenomics.com/single-cell-gene-expression/datasets/1.3.0/1M_neurons 293T_1k, 3T3_1k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/hgmm_1k 293T_6k, 3T3_6k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/hgmm_6k 293T_12k, 3T3_12k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/hgmm_12k We note that pbmc_4k and pbmc_8k are from the same donor; brain_1k and brain_9k are also from the same donor.

Techniques: Sequencing, Selection

Journal: Nature Communications

Article Title: Determining sequencing depth in a single-cell RNA-seq experiment

doi: 10.1038/s41467-020-14482-y

Figure Lengend Snippet: a Top: the EB-estimated Pearson correlation for some marker genes in pbmc_4k are visualized, ordered by different cell populations (top). The clear block-diagonal structure implies that the EB estimator is capable of capturing the gene functional groups. As a comparison, the plug-in estimator also recovers those modules but with a weaker contrast (bottom left panel, plug-in with 100%). Bottom: a subsample experiment further shows that the EB estimator can recover the module with 5% of the data. For the plug-in estimator, the first block (T cells) is blurred with 25% of the data, and the entire structure vanishes with 10% of the data. b Gene network based on the EB-estimated Pearson correlation using the pbmc_4k dataset. Most gene modules correspond to important cell types or functions, including T cells, B cells, NK-cells, myeloid-derived cells, megakaryocytes/platelets, ribosomal protein genes, and mitochondrially encoded protein-coding genes. c Left: the estimated Pearson correlations between all genes and LCK (1st panel) and CD3D (2nd panel), two known T-cell markers. There are three modes for the EB-estimated values, where the positive mode, the zero mode, and the negative mode correspond to genes in the same module, different modules, and irrelevant genes, respectively. The plug-in estimated values are nonetheless much closer to zero even for the truly correlated ones, indicating an artificial shrinkage of the estimated values. Right: two instances where the EB estimates are significantly different from the plug-in estimates. The axes represent read counts, and the color codes the number of cells. Both gene pairs are biologically validated (see Gene network analysis in Methods). See also Supplementary Figs. – for more examples.

Article Snippet: They are publicly available and can be downloaded via the following links: pbmc_4k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/pbmc4k pbmc_8k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/pbmc8k brain_1k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/neurons_900 brain_2k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/neurons_2000 brain_9k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/neuron_9k brain_1.3m: https://support.10xgenomics.com/single-cell-gene-expression/datasets/1.3.0/1M_neurons 293T_1k, 3T3_1k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/hgmm_1k 293T_6k, 3T3_6k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/hgmm_6k 293T_12k, 3T3_12k: https://support.10xgenomics.com/single-cell-gene-expression/datasets/2.1.0/hgmm_12k We note that pbmc_4k and pbmc_8k are from the same donor; brain_1k and brain_9k are also from the same donor.

Techniques: Marker, Blocking Assay, Functional Assay, Derivative Assay

Journal: International Journal of Nanomedicine

Article Title: Cathepsin B-Activatable Bioactive Peptide Nanocarrier for High-Efficiency Immunotherapy of Asthma

doi: 10.2147/IJN.S455633

Figure Lengend Snippet: Effect of PEG-Liker (PEG-IALLIPF), Trp, or MPP-Trp on the production of NO and Pro-inflammatory cytokines. ( A ) In Control-PBMCs, Asthma-PBMCs, Asthma-PBMCs + PEG-Liker, Asthma-PBMCs + Trp and Asthma-PBMCs + MPP-Trp group, NO production were examined by NO assay kit. Pro-inflammatory cytokines ( B ) TNF-α, ( C ) IL-1β, and ( D ) IL-6 contents in all groups were examined by ELISA assay. Data were presented as mean ± SD of three independent experiments. * P <0.05, ** P <0.01, *** P <0.001 vs Asthma-PBMCs group.

Article Snippet: The total peripheral blood mononuclear cells (PBMCs) were isolated from the whole blood samples of control group and asthma group by mouse peripheral blood mononuclear cell isolation kit (P6340; Solarbio, Beijing, China) according to the manufacturer's protocol.

Techniques: Control, Enzyme-linked Immunosorbent Assay

Journal: International Journal of Nanomedicine

Article Title: Cathepsin B-Activatable Bioactive Peptide Nanocarrier for High-Efficiency Immunotherapy of Asthma

doi: 10.2147/IJN.S455633

Figure Lengend Snippet: MPP-Trp was closely correlated with the balanced Th1/Th2 level and Th1/Th2-type cytokine production. ( A ) In Control-PBMCs, Asthma-PBMCs, Asthma-PBMCs + PEG-Liker, Asthma-PBMCs + Trp and Asthma-PBMCs + MPP-Trp group, Th1 population (CD4+IFN-γ+) and Th2 population (CD4+IL-4+) were selected by flow cytometry assay. ( B ) Relative mRNA expressions of IFN-γ, IL-4, IL-13, and IL-5 in all groups were assessed by qRT-PCR. ( C ) The IFN-γ, IL-4, IL-13, and IL-5 contents in all groups were examined by ELISA assay. Data were presented as mean ± SD of three independent experiments. * P <0.05, ** P <0.01, *** P <0.001 vs Asthma-PBMCs group.

Article Snippet: The total peripheral blood mononuclear cells (PBMCs) were isolated from the whole blood samples of control group and asthma group by mouse peripheral blood mononuclear cell isolation kit (P6340; Solarbio, Beijing, China) according to the manufacturer's protocol.

Techniques: Control, Flow Cytometry, Quantitative RT-PCR, Enzyme-linked Immunosorbent Assay

Journal: International Journal of Nanomedicine

Article Title: Cathepsin B-Activatable Bioactive Peptide Nanocarrier for High-Efficiency Immunotherapy of Asthma

doi: 10.2147/IJN.S455633

Figure Lengend Snippet: MPP-Trp altered cytokine gene expression and production in a concentration-dependent way. In Control-PBMCs, Asthma-PBMCs, and Asthma-PBMCs + MPP-Trp (10, 50, 100 and 200 μg/mL) group, ( A ) Th1/Th2 cytokine gene expressions (IFN-γ, IL-4, IL-13, and IL-5) were determined by RT-qPCR. ( B ) The cytokines (IFN-γ, IL-4, IL-13, and IL-5) levels in all groups were detected by ELISA. Data were presented as mean ± SD of three independent experiments. ** P <0.01, *** P <0.001 vs Control-PBMCs group; # P <0.05, ## P <0.01, ### P <0.001 vs Asthma-PBMCs group.

Article Snippet: The total peripheral blood mononuclear cells (PBMCs) were isolated from the whole blood samples of control group and asthma group by mouse peripheral blood mononuclear cell isolation kit (P6340; Solarbio, Beijing, China) according to the manufacturer's protocol.

Techniques: Gene Expression, Concentration Assay, Control, Quantitative RT-PCR, Enzyme-linked Immunosorbent Assay

Journal: International Journal of Nanomedicine

Article Title: Cathepsin B-Activatable Bioactive Peptide Nanocarrier for High-Efficiency Immunotherapy of Asthma

doi: 10.2147/IJN.S455633

Figure Lengend Snippet: MPP-Trp altered cytokine gene expression and production in a time-dependent way. ( A ) In Control-PBMCs, Asthma-PBMCs, and 100 μg/mL Asthma-PBMCs + MPP-Trp (6, 12, 24, and 48 h) group, IFN-γ, IL-4, IL-13, and IL-5 mRNA levels were determined by RT-qPCR. ( B ) The Th1/Th2-type cytokines (IFN-γ, IL-4, IL-13, and IL-5) productions in all group were examined by ELISA. Data were presented as mean ± SD of three independent experiments. *** P <0.001 vs Control-PBMCs group; # P <0.05; ## P <0.01; ### P <0.001 vs Asthma-PBMCs group.

Article Snippet: The total peripheral blood mononuclear cells (PBMCs) were isolated from the whole blood samples of control group and asthma group by mouse peripheral blood mononuclear cell isolation kit (P6340; Solarbio, Beijing, China) according to the manufacturer's protocol.

Techniques: Gene Expression, Control, Quantitative RT-PCR, Enzyme-linked Immunosorbent Assay

Journal: Poultry Science

Article Title: Engineered Salmonella Enteritidis vector targeting innate immune molecules provides protection against Salmonella Enteritidis and Salmonella Typhimurium

doi: 10.1016/j.psj.2025.105724

Figure Lengend Snippet: Specific cellular immune responses induced by SIRV in chickens. (A-C) Lymphocyte proliferation. PBMCs are stimulated with SE ( C50041 )-OMPs (A), SE (CVCC3949)-OMPs (B), and ST-OMPs (C), and proliferation is measured using the CCK-8 assay. (D-F) Cytokine production upon in vitro stimulation of lymphocytes. PBMCS are stimulated with SE ( C50041 )-OMPs (D), SE (CVCC3949)-OMPs (E), and ST-OMPs (F). mRNA expression levels of IFN‐γ and IL‐4 are quantified by qRT-PCR. Data are expressed as the mean ± SD of three chickens. Ns, not significant, *, P < 0.05, **, P < 0.01, ***, P < 0.001.

Article Snippet: Peripheral blood mononuclear cells (PBMCs) were isolated 1 week post-vaccination using the chicken PBMC isolation kit (Solarbio).

Techniques: CCK-8 Assay, In Vitro, Expressing, Quantitative RT-PCR

Journal: Viruses

Article Title: The Mechanism of PEDV-Carrying CD3 + T Cells Migrate into the Intestinal Mucosa of Neonatal Piglets

doi: 10.3390/v13030469

Figure Lengend Snippet: Blood-derived CD3 + T cells could be hijacked by PEDV in vitro. Blood-derived CD3 + T cells were infected with PEDV at different times. The viral loads in blood-derived CD3 + T cells were detected by Western blotting ( a ), plaque assay ( b ), and FACS ( c ). At least three independent experiments were performed. PBMC: Peripheral blood monoculear cell; FACS: Fluorescence Activated Cell Sorte.

Article Snippet: Porcine PBMCs (Peripheral blood mononuclear cells) were isolated from the blood of neonatal piglets by density centrifugation using a porcine peripheral blood lymphocyte separation kit (Solarbio, Beijing, China).

Techniques: Derivative Assay, In Vitro, Infection, Western Blot, Plaque Assay, Fluorescence

Journal: Circulation research

Article Title: Ponatinib Drives Cardiotoxicity by S100A8/A9-NLRP3-IL-1β Mediated Inflammation

doi: 10.1161/CIRCRESAHA.122.321504

Figure Lengend Snippet: ( A ) Gating strategy for sorting CD11b + cells from mouse splenocytes. ( B ) CFSE stained CD11b + cells were cultured and treated with combination of antagonists and ponatinib for 72 hours (DMSO as control, LPS, Ponatinib 100nM, Ponatinib 100nM+ TLR4 inhibitor, Ponatinib 100nM+ CY09, Ponatinib 100nM+ Paquinimod). Histograms representing the percentage of diluted CFSE-stained CD11b + cells. ( C ) Quantification of CD11b + proliferation (percentage of CFSE low CD11b + cells). Experiment was repeated three times (N= 3). Data were analyzed by using ordinary one way ANOVA followed by Tukey’s multiple comparisions test and represented as mean±SEM. ( D ) Human CML cells K562 were treated with ponatinib (100nM) for 72 hours. Next, cells were stained with Annexin V and 7AAD, and flow cytometry was performed. ( E ) Violin plot showing the percentage of dead K562 cells after ponatinib treatment. ( F ) Human K562 CML cells and PBMCs were co-cultured (1:5) and treated with ponatinib. Representative flow cytometry figures show gating strategy to measure dead cells in co-culture. ( G-H ) Data represents the quantitation of the percent of K562 dead cells and PBMCs. ( I ) Human PBMCs were treated with ponatinib (100nM) for 72 hours and BrdU was incorporated to culture 24 hours prior to flow cytometry analysis. ( J ) Violin plot shows the percent of proliferating immune cells (CD45 + Brdu + ). ( K-L ) Data represents a proliferation of immune cells in co-culture of human PBMCs and K562 cells post ponatinib treatment (100nM, 72 hours). Experiment was repeated three times (N= 3). Data (E, G, H, J, and L) were analyzed using the unpaired t test and represented as mean±SEM.

Article Snippet: We performed similar experiments with human peripheral blood mononuclear cells (PBMCs) (iXCells Biotechnology).

Techniques: Staining, Cell Culture, Control, Flow Cytometry, Co-Culture Assay, Quantitation Assay