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Th17 Cells

Th17 cells are a subset of T helper cells that play a key role in immune responses and inflammatory processes.
These cells are characterized by their production of the cytokine interleukin-17 (IL-17) and express the transcription factor RORγt.
Th17 cells are involved in the defense against extracellular pathogens and have been implicated in the pathogenesis of autoimmune diseases and chronic inflammation.
Optimizing Th17 cell research is crucial for understanding their biological functions and developing targeted therapeutics.
PubCompare.ai, an AI-powered platform, can enhance the reproducibility and accuracy of Th17 cell studies by helping researchers easily locate relevant protocols from literature, preprints, and patents, while using AI-driven comparisons to identify the best protocols and prodcuts.
Improve your Th17 cell research with the power of PubCompare.ai.

Most cited protocols related to «Th17 Cells»

A custom signature matrix can be created using data from purified cell populations. While the process to generate a custom matrix from expression profiles is straightforward, the performance of a custom matrix will depend on the quality of the data used to generate it. Immunophenotyping of leukocytes is a dynamic field with new immune populations continuing to be identified. Care should be taken in determining which immune “cell types” should be included in the signature matrix and which canonical markers should be used to isolate these populations. For example, it is clear that the population of “CD4-expressing T lymphocytes” encompasses heterogeneous populations with diverse functional phenotypes including naïve, memory, Th1, Th2, Th17, T-regulatory cells and T follicular helper cells. Replicates for each purified immune cell type are required to gauge variance in the expression profile (see 5.4 for further details). The platform and methods used to generate data for the signature matrix ideally should be identical to that applied to analysis of the mixture samples. While SVR is robust to unknown cell populations, performance can be adversely affected by genes that are highly expressed in a relevant unknown cell population (e.g., in the malignant cells) but not by any immune components present in the signature matrix. A simple option implemented in CIBERSORT to limit this effect is to remove genes highly expressed in non-hematopoietic cells or tumor cells. If expression data is available from purified tumor cells for the malignancy to be studied, this can be used as a guideline to filter other confounding genes from the signature matrix.
Publication 2018
Cells Genes Hematopoietic System Leukocytes Malignant Neoplasms Memory Neoplasms Phenotype T Follicular Helper Cells Th17 Cells

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Publication 2012
CD4 Positive T Lymphocytes Cells DNA Chips Mus Nodes, Lymph Spleen Th17 Cells
TIMER is a comprehensive resource for systematic analysis of immune infiltrates across diverse cancer types (https://cistrome.shinyapps.io/timer/) (23 (link)). TIMER applies a deconvolution previously published statistical method (24 (link)) to infer the abundance of tumor-infiltrating immune cells (TIICs) from gene expression profiles. The TIMER database includes 10,897 samples across 32 cancer types from The Cancer Genome Atlas (TCGA) to estimate the abundance of immune infiltrates. We analyzed LAYN expression in different types of cancer and the correlation of LAYN expression with the abundance of immune infiltrates, including B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells, via gene modules. Gene expression levels against tumor purity is displayed on the left-most panel (25 (link)). In addition, correlations between LAYN expression and gene markers of tumor-infiltrating immune cells were explored via correlation modules. The gene markers of tumor-infiltrating immune cells included markers of CD8+ T cells, T cells (general), B cells, monocytes, TAMs, M1 macrophages, M2 macrophages, neutrophils, natural killer (NK) cells, dendritic cells (DCs), T-helper 1 (Th1) cells, T-helper 2 (Th2) cells, follicular helper T (Tfh) cells, T-helper 17 (Th17) cells, Tregs, and exhausted T cells. These gene markers are referenced in prior studies (26 (link)–28 (link)). The correlation module generated the expression scatter plots between a pair of user-defined genes in a given cancer type, together with the Spearman's correlation and the estimated statistical significance. LAYN was used for the x-axis with gene symbols, and related marker genes are represented on the y-axis as gene symbols. The gene expression level was displayed with log2 RSEM.
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Publication 2019
B-Lymphocytes CD4 Positive T Lymphocytes CD8-Positive T-Lymphocytes Cells Dendritic Cells Epistropheus Gene Expression Gene Modules Genes Genes, Neoplasm Genetic Markers Genome Macrophage Malignant Neoplasms Monocytes Myeloproliferative Syndrome, Transient Natural Killer Cells Neoplasms Neutrophil System, Immune T-Lymphocyte Th17 Cells Type-2 Helper T Cell Type 1 Helper T Cells

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Publication 2018
CD274 protein, human CTLA4 protein, human DNA Damage Immunotherapy Neoplasms Th17 Cells Wolves X-Ray Photoelectron Spectroscopy
The severity and clinical course of EAU induced by active immunization (CFA-EAU) with peptide 161–180 in B10.RIII mice is typically monophasic, resembling the Lewis rat, and lasts for 2–3 weeks. High intensity immunization results in an acute form of disease with onset as early as day 8 or 9 and widespread photo-receptor damage, whereas lower intensity of immunization will result in milder disease with progressively later onset (24 (link)). In other strains (e.g., B10.A) it is possible to observe relapsing disease after a low to intermediate intensity protocol (56 (link)). As in the Lewis, the rapid onset and acute course of EAU induced with peptide 161–180 in B10.RIII mice makes it difficult to evaluate therapeutic intervention during active disease. Alternatively, to look at efferent-stage disease, begin intervention 7 days after immunization, when immune lymphocytes are already present, or to use an adoptive transfer system.
Interestingly, the DC-EAU model exhibits unique clinical manifestations and inflammatory characteristics when compared to traditional CFA-induced EAU. DC-EAU is less severe, of shorter duration, and is characterized by focal infiltrates and short linear lesions. While the cellular infiltrate of CFA-EAU is composed of monocytes and lymphocytes, DC-EAU is largely granulocytic with a small population of eosinophils. Intraocularly, IFNγ predominates in DC-EAU with little or no detectable IL-17, i.e., a dominant Th1 response. In contrast, the eye milieu of CFA-EAU consists of a combination of IFNγ, IL-17, and IL-18, i.e., a mixed Th1/Th17 response. The differences observed in these two EAU models highlights the variability of clinical and immunological outcomes when the same antigen is processed in the context of distinct innate stimuli. The DC-EAU induction system can offer the investigator an opportunity to choose a disease model that is devoid of IL-17 influence, has a milder outcome, and is free of prolonged innate stimulation generated by the Ag/CFA depot.
Publication 2012
Acute Disease Adoptive Transfer Antigens Eosinophil Granulocyte IL17A protein, human Immunization Inflammation Interferon Type II interleukin 18 protein, human Lymphocyte Monocytes Mus Peptides Strains Th17 Cells Therapeutics Vaccination

Most recents protocols related to «Th17 Cells»

The experimental operations were carried out following the instructions of the Cytometric Beads Array (CBA) kit (Cat: 560485, BD biosciences, USA). First, the standard samples were diluted. Then, 50 μL of a mixture of capture beads was added to the standard tubes and sample tubes and mixed well, followed by 50 μL Th1/Th2/Th17 PE detection reagent being added to each tube. The tubes were incubated in the dark at room temperature for 2 h. After washing, the precipitates were resuspended and detected by the FACS Calibur (LSRFortessa SORP, BD biosciences, USA), followed by analyzation using FCAP Array software (Cat: 652099, BD biosciences, USA).
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Publication 2023
Th17 Cells

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Publication 2023
Anti-Antibodies Antibodies, Anti-Idiotypic CD4 Positive T Lymphocytes Cells CY5.5 cyanine dye Cytokine Fluorescein-5-isothiocyanate Fluorescent Antibody Technique Helper-Inducer T-Lymphocyte IFNG protein, mouse IL2RA protein, human Ionomycin ITGAM protein, human Mus Proteins Protoplasm Regulatory T-Lymphocytes Tetradecanoylphorbol Acetate Th17 Cells Type-2 Helper T Cell
The gene sets of 28 immune cells and four classes of immune factors were downloaded from TISIDB database.3 The following 28 types of immune cells were obtained: central memory CD4+ T cells (CD4+ Tcm), central memory CD8+ T cells (CD8+ Tcm), type-2 T helper cells (Th2), CD56dim natural killer cells (CD56− NK), activated CD8+ T cells (CD8+ Ta), activated CD4+ T cells (CD4+ Ta), activated B cells (Ba), effector memory CD8+ T cells (CD8+ Tem), effector memory CD4+ T cells (CD4+ Tem), macrophages, eosinophils, memory B cells (Bm), immature dendritic cells (DCi), gamma delta T cells (γδT), CD56bright natural killer cells (CD56+ NK), monocytes, mast cells, natural killer cells (NK), immature B cells (Bi), type-1 T helper cells (Th1), neutrophils, plasmacytoid dendritic cells (DCp), natural killer T cells (NK T), type-17 T helper cells (Th17), follicular helper T cells (Tfh), regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSC), and activated dendritic cells (DCa). The four classes of immune factors include 41 chemokines, 24 immunosuppressive factors, 46 immunostimulatory factors, and 18 immune receptors.
The ssGSEA algorithm, which classifies gene sets with common biological functions, physiological regulation, and chromosomal localization, was employed via R packages (GSVA 1.42.0) to comprehensively assess the immunologic characteristics of each sample included in the analyses (Hänzelmann et al., 2013 (link)). Normalized data of gene expression profiles were compared with the gene sets to demonstrate the enrichment of immune cells in each AD brain samples. Then, ANOVA was adopted to identify immune cell types with significant differences between the groups with longer lifespan and shorter lifespan. Pearson correlations between the gene expression level of each hub gene and the concentrations of immune cells were carried out using cor.test in R software (version: 4.0.3). The hub genes were identified in 2.4.
The correlations between the gene expression levels of each hub gene and the gene sets of immune factors were also calculated, respectively. Then, the pairs of hub genes and immune-related molecules with |cor| > 0.6 & p value<0.05 were selected to generate a circos plot via Cytoscape.
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Publication 2023
B-Lymphocytes Biological Processes Brain CD4 Positive T Lymphocytes CD8-Positive T-Lymphocytes Central Memory T Cells Chemokine Chromosomes Dendritic Cells Effector Memory T Cells Eosinophil Gene Expression Genes Helper-Inducer T-Lymphocyte Immature B-Lymphocyte Immunization Immunologic Factors Immunosuppressive Agents Intraepithelial Lymphocytes Macrophage Mast Cell Memory B Cells Monocytes Myeloid-Derived Suppressor Cells Natural Killer Cells Natural Killer T-Cells neuro-oncological ventral antigen 2, human Neutrophil physiology Plasmacytoid Dendritic Cells Receptors, Immunologic Regulatory T-Lymphocytes Th17 Cells Type-2 Helper T Cell Type 1 Helper T Cells
Fluorochrome-conjugated anti-mouse CD4 (RM4-5), CD8a (53-6.7), CD11b (M1/70), CD11c (N418), CD45.1 (A20), CD45.2 (104), CD80 (16-10A1), CD86 (GL1), I-A/E (M5/114.15.2), IFN-γ (XMG1.2), and IL-17A (eBio17B7), and CD135 (A2F10) were obtained from eBioscience and CD115 (T38-320) was obtained from BD Biosciences. All antibody dilutions were 1:200. Cell death and apoptosis were analyzed using an Annexin V/Propidium iodide (PI) staining kit (eBioscience, 88-8007-74) according to the manufacturer’s protocol. Cell proliferation was determined using CFSE staining (Molecular Probes, C1157). Aldehyde dehydrogenase (ALDH) activity was measured in the BMDCs using an ALDEFLUOR Kit (STEMCELL Technologies, 01700) according to the manufacturer’s protocol. For the intracellular detection of IFN-γ and IL-17A, cells were fixed and permeabilized with Foxp3/Transcription Factor Staining Buffer Set (eBioscience, 00-5523-00) and incubated for 30 min on ice with the relevant antibodies diluted in Permeabilization buffer (eBioscience). Cytokines secreted into culture media were quantified using the CBA Mouse Inflammation Kit (BD Biosciences, 552364) and the CBA Mouse Th1/Th2/Th17 Cytokine Kit (BD Biosciences, 560485). Stained cells or samples were analyzed using flow cytometry with the FACSVerse system (BD Biosciences) and a FACS LSR Fortessa flow cytometer (BD Biosciences). All flow cytometry data collected by FACSuite (BD Biosciences) and FACSDiva (BD Biosciences) were analyzed using the FlowJo software (Treestar). CBA data were analyzed using FCAP Array software (BD Biosciences). Three biological replicates were performed for each condition.
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Publication 2023
5-(6)-carboxyfluorescein diacetate succinimidyl ester Annexin A5 Antibodies Apoptosis Biopharmaceuticals Buffers Cell Death Cell Proliferation Cells Culture Media Cytokine Dehydrogenase, Aldehyde Flow Cytometry Fluorescent Dyes Immunoglobulins Inflammation Interferon Type II Interleukin-17A ITGAM protein, human Mice, Inbred CBA Molecular Probes Mus Propidium Iodide Protoplasm Stem Cells Technique, Dilution Th17 Cells Transcription Factor
CD4+ T cell in vitro differentiation with BMDCs was performed as previously described49 (link). In brief, CD4+ naive T cells were isolated from the spleen of C57BL6 mice using the MagniSort Mouse CD4+ Naïve T cell Enrichment Kit (eBioscience, 8804-6824-74). Naive CD4+ T cells (1 × 105 cells/well) and CD11c+ BMDCs (1 × 104 cells/well) were co-cultured in the presence of soluble anti-CD3ε (0.15 μg/mL; BioLegend, 100331) for 4 days. For Th1 differentiation, BMDCs were treated with LPS (100 ng/mL). For Th17 differentiation, BMDCs were stimulated with LPS (100 ng/mL) and TGF-β (3 ng/mL; Peprotech, 100-21 C). In vitro differentiated CD4+ T cells were incubated with 50 μg/mL PMA (Sigma, P1585) and 1 μg/mL ionomycin (Sigma, I3909) in the presence of brefeldin A (eBioscience, B6542) for 4 h before intracellular cytokine staining analysis. Three biological replicates were performed for each condition.
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Publication 2023
Biopharmaceuticals Brefeldin A CD3E protein, human CD4 Positive T Lymphocytes Cells Cytokine Ionomycin Mus Protoplasm Spleen Th17 Cells Transforming Growth Factor beta

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More about "Th17 Cells"

Th17 Cells: Crucial Players in Immune Response and Inflammation Th17 cells, a specialized subset of T helper cells, play a pivotal role in the immune system's defense against extracellular pathogens.
These cells are characterized by their production of the cytokine interleukin-17 (IL-17) and the expression of the transcription factor RORγt.
Th17 cells are involved in a wide range of biological processes, from immune responses to inflammatory conditions.
They are crucial in fighting off infections caused by bacteria, fungi, and certain viruses.
However, dysregulation of Th17 cells has been implicated in the pathogenesis of autoimmune diseases and chronic inflammation.
To better understand the functions and therapeutic potential of Th17 cells, researchers often utilize various tools and techniques.
Common methods include cell culture with Ionomycin and PMA, flow cytometry analysis using FACSCanto II or FACSCalibur instruments, and cytokine measurements with techniques like ELISA and FCAP Array software.
Optimizing Th17 cell research is crucial for developing targeted therapies.
Researchers can leverage platforms like PubCompare.ai to easily locate relevant protocols from literature, preprints, and patents, while utilizing AI-driven comparisons to identify the best protocols and products.
This can enhance the reproducibility and accuracy of Th17 cell studies, ultimately leading to a better understanding of these important immune cells and their role in health and disease.
By incorporating synonyms, related terms, and key subtopics, this comprehensive overview provides a deeper dive into the world of Th17 cells, empowering researchers to advance their investigations and unlock new insights.