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Chemokine

Chemokines are a family of small cytokuines that play a crucial role in immune system function and inflammation.
They are involved in the recruitment and activation of various immune cells, including leukocytes, to sites of infection or tissue damage.
Chemokines exert their effects by binding to specific G protein-coupled receptors, triggering signaling cascades that regulate cell migration, adhesion, and activation.
This diverse class of signaling molecules is important for maintaining homeostasis, orchestrating immune responses, and contributing to the pathogenesis of numerous diseases.
Understanding the complex chemokine network is essential for developing targeted therapies for conditions such as autoimmune disorders, cancer, and infectious diseases.

Most cited protocols related to «Chemokine»

1
Comprehensive Tumor Immune Profile Analysis
Cited 212 times
Multivariate Cox regression, log-rank test and Kaplan–Meier estimators were implemented using the R package survival. The association between CD8 T-cell abundance and tumor status was evaluated using logistic regression corrected for age and clinical stage and was implemented using the R package glm. The same analysis was performed for neutrophil abundance and gender associations, corrected for age and smoking history. Partial correlations of immune cell abundance and gene expression of chemokines and receptors, somatic mutation counts, CT gene expression, as well as immunosuppressive molecule expression were calculated using the R package ppcor. Multiple test correction was performed using the R package qvalue [39 ] and FDR thresholds are applied based on the abundance of signals in the data. In this study, we applied the Pearson correlation to purity and gene expression because it is reasonable to expect that the expression level is linearly associated with tumor purity. For others, we used the Spearman correlation. We applied partial correlation analysis to remove the influence of tumor purity on the involved variables. All other analyses, including linear regression, Fisher’s exact test, Wilcoxon rank sum test, Spearman’s correlation, and hierarchical clustering, were performed using R [40 ]. Of note, in Figs. 2b and 3b, we used the 20 percentile as a cutoff only to help visualize the association of immune infiltration with outcomes and the statistical significance was determined by multivariate Cox regression (Fig. 3a) including all the samples. Our results on survival analysis, neoantigen association, tumor recurrence, and association of checkpoint blockade inhibitory molecules with immune cells are available in Additional file 10: Table S8.
Li B., Severson E., Pignon J.C., Zhao H., Li T., Novak J., Jiang P., Shen H., Aster J.C., Rodig S., Signoretti S., Liu J.S, & Liu X.S. (2016). Comprehensive analyses of tumor immunity: implications for cancer immunotherapy. Genome Biology, 17, 174.
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Publication 2016
CD8-Positive T-Lymphocytes Cells Chemokine Diploid Cell Gender Gene Expression Immunosuppressive Agents Inhibitory Checkpoint Molecules Mutation Neoplasms Neutrophil Recurrence
2
Standardized Immunology Data Annotation
Cited 119 times
ImmPort data is annotated with terms from several ontologies including Cell Ontology23 (link), Disease Ontology (disease-ontology.org), Ontology for Biomedical Investigations (OBI; obi-ontology.org), Protein Ontology24 (link), and Vaccine Ontology25 (link). MedDRA (www.meddra.org) is used for adverse event terms and the NCI Thesaurus supplies terms from a variety of sources (e.g., CDISC). The Antibody Ontology (AntiO) is a new resource developed from data curated in ImmPort to provide standardized representation of monoclonal antibodies used in immunology research26 (link). Along with updates to OBI, it exemplifies the ongoing development of data standardization facilitated by ImmPort. An analogous problem arises in the case of cytokines, where no public domain registry has thus far been available. To fill this gap, a registry of cytokines, chemokines and their receptors was compiled (http://www.immport.org/immport-open/public/reference/cytokineRegistry) for the purpose of collecting, integrating, and mapping between entity names and synonyms. The cytokine registry draws on resources such NCBI Gene, HGNC, MGI, Protein Ontology, and UniProt. ImmPort engages with several data standards communities such as the Human Immune Phenotyping Consortium (HIPC) Standards Working Group18 (link), BioSharing (fairsharing.org), the Patient Derived Tumor Xenograft Minimal Information (PDX-MI) working group27 (link) and the NIH Big Data to Knowledge (BD2K) initiative (datascience.nih.gov/bd2k/about) through its collaboration with CEDAR (http://metadatacenter.org).
Bhattacharya S., Dunn P., Thomas C.G., Smith B., Schaefer H., Chen J., Hu Z., Zalocusky K.A., Shankar R.D., Shen-Orr S.S., Thomson E., Wiser J, & Butte A.J. (2018). ImmPort, toward repurposing of open access immunological assay data for translational and clinical research. Scientific Data, 5, 180015.
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Publication 2018
Cells Chemokine Cytokine Genes Homo sapiens Immunoglobulins Monoclonal Antibodies Neoplasms Patients Proteins Public Domain Vaccines Xenografting
3
Evaluating Tumor Immune Microenvironment in Bladder Cancer
Cited 62 times
Immunological characteristics of the TME in BLCA include the expression of immunomodulators, activity of the cancer immunity cycle, infiltration level of TIICs, and the expression of inhibitory immune checkpoints. We first collected information on 122 immunomodulators including MHC, receptors, chemokines, and immune stimulators from the study of Charoentong et al. (Table S2) 28 (link). The cancer immunity cycle reflects the anticancer immune response and comprises seven steps: release of cancer cell antigens (Step 1), cancer antigen presentation (Step 2), priming and activation (Step 3), trafficking of immune cells to tumors (Step 4), infiltration of immune cells into tumors (Step 5), recognition of cancer cells by T cells (Step 6), and killing of cancer cells (Step 7) (Table S3) 29 (link). The activities of these steps determine the fate of the tumor cells. Xu et al. evaluated the activities of these steps using a single sample gene set enrichment analysis (ssGSEA) based on the gene expression of individual samples 30 (link). Thereafter, several algorithms were developed to calculate the infiltration level of TIICs in TME using bulk RNA-seq data. Different algorithms and marker gene sets of TIICs initiate calculation errors. To avoid these errors, we comprehensively calculated the infiltration level of TIICs using seven independent algorithms: Cibersort-ABS, MCP-counter, quanTIseq, TIMER, xCell, TIP, and TISIDB (Table S4) 30 (link)-36 (link). We also identified the effector genes of TIICs from previous studies (Table S5). Finally, we collected 22 inhibitory immune checkpoints with therapeutic potential from Auslander's study (Table S6) 37 (link).
Ayers et al. developed and validated a pan-cancer T cell-inflamed score, which could define pre-existing cancer immunity, as well as predict the clinical response of ICB 38 (link). The eighteen genes included in the T cell-inflamed score algorithm and their coefficients are shown in Table S7. Here, we computed the T cell inflamed score as a weighted linear combination of the scores from the 18 genes. Hyperprogression is an adverse event associated with ICB. We summarized several predictors of hyperprogression (Table S8) 39 -41 . The amplification and high mRNA expression of MDM2, MDM4, DNMT3A, CCND1, FGF19, FGF4, and FGF3 are positively correlated with hyperprogression. In addition, the deletion and low mRNA expression of CDKN2A and CDKN2B are also positively correlated with hyperprogression.
To confirm the role of Siglec15 in modulating cancer immunity in BLCA, we analyzed the correlation between Siglec15 and the immunological characteristics of TME with respect to the above aspects. The findings from this study were validated in three independent external cohorts, including GSE31684, GSE32894, and IMvigor210.
Hu J., Yu A., Othmane B., Qiu D., Li H., Li C., Liu P., Ren W., Chen M., Gong G., Guo X., Zhang H., Chen J, & Zu X. (2021). Siglec15 shapes a non-inflamed tumor microenvironment and predicts the molecular subtype in bladder cancer. Theranostics, 11(7), 3089-3108.
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Publication 2021
Antigen Presentation Antigens Biological Response Modifiers CCND1 protein, human CDKN2A Gene Chemokine Deletion Mutation Dietary Fiber FGF4 protein, human Gene Expression Genes Immune Checkpoint Blockade Malignant Neoplasms MDM2 protein, human Neoplasms Response, Immune RNA, Messenger RNA-Seq T-Lymphocyte Therapeutics
4
CellChatDB: Comprehensive Ligand-Receptor Interactions
Cited 44 times
To construct a database of ligand-receptor interactions that comprehensively represents the current state of knowledge, we manually reviewed other publicly available signaling pathway databases, as well as peer-reviewed literature and developed CellChatDB. CellChatDB is a database of literature-supported ligand-receptor interactions in both mouse and human. The majority of ligand–receptor interactions in CellChatDB were manually curated on the basis of KEGG (Kyoto Encyclopedia of Genes and Genomes) signaling pathway database (https://www.genome.jp/kegg/pathway.html). Additional signaling molecular interactions were gathered from recent peer-reviewed experimental studies. We took into account not only the structural composition of ligand-receptor interactions, that often involve multimeric receptors, but also cofactor molecules, including soluble agonists and antagonists, as well as co-stimulatory and co-inhibitory membrane-bound receptors that can prominently modulate ligand-receptor mediated signaling events. The detailed steps for how CellChatDB was built and how to update CellChatDB by adding user-defined ligand-receptor pairs were provided in Supplementary Note 1. To further analyze cell–cell communication in a more biologically meaningful way, we grouped all of the interactions into 229 signaling pathway families, such as WNT, ncWNT, TGFβ, BMP, Nodal, Activin, EGF, NRG, TGFα, FGF, PDGF, VEGF, IGF, chemokine and cytokine signaling pathways (CCL, CXCL, CX3C, XC, IL, IFN), Notch and TNF. The supportive evidences for each signaling interaction is included within the database.
Jin S., Guerrero-Juarez C.F., Zhang L., Chang I., Ramos R., Kuan C.H., Myung P., Plikus M.V, & Nie Q. (2021). Inference and analysis of cell-cell communication using CellChat. Nature Communications, 12, 1088.
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Publication 2021
Activins agonists antagonists Cell Communication Chemokine Cytokine Genes Genome Homo sapiens Ligands Mus Platelet-Derived Growth Factor Psychological Inhibition Signal Transduction Pathways TGFA protein, human Tissue, Membrane Transforming Growth Factor beta Vascular Endothelial Growth Factors
5
Cytokine and Chemokine Profiles in ICU Care
Cited 28 times

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Publication 2020
Chemokine Cytokine Plasma

Most recents protocols related to «Chemokine»

1
Engineered Tregs for Autoimmune Therapy
Not available on PMC !

Example 2

CD4+/CD45RA+ T-cells are transduced with a lentivirus having nucleic acid sequences encoding a FOXP3 polypeptide having mutations as described herein, a receptor polypeptide, and a therapeutic gene product (FIG. 2). Here, a CD4+/CD45RA+ T-cell is transformed with a nucleic acid sequence encoding a FOXP3 polypeptide, a nucleic acid sequence encoding a CXCR3 chemokine receptor polypeptide, and is also transformed with a nucleic acid sequence encoding a scFv antigen-binding fragment that is capable of binding to an IL-6R antigen expressed on a cell associated with an autoimmune disease. The binding of the scFV to an epitope of IL-6R blocks the binding of IL-6R to IL-6. An antibody used in this example includes Tocilizumab, which is a humanized anti-IL-6R antibody. The variable light and heavy chain domains of Tocilizumab (See, U.S. Pat. No. 5,795,965) are provided to the cells using nucleic acid sequence encoding a scFv linked to a secretion signal and operably linked by a constitutive promoter such as EF-1α. Mutations are introduced into the amino acid sequence of Tocilizumab that render the heavy and light chains more favorable binding properties to the IL-6R (See, U.S. Pat. No. 8,562,991). Tregs are not known to naturally produce IL-6 blocking mediators (e.g., antibody or antigen-binding fragments to IL-6R). Therefore, expression of such blockers transformed into a CD4+/CD45RA+ T-cell along with an a nucleic acid sequence encoding a FOXP3 polypeptide will render the T-cells more effective in inflammatory environments than T-cells not transformed with the nucleic acid sequences described herein. The binding of the scFv to IL-6R+ is confirmed by flow cytometry. Secretion of the scFv is verified by ELISA, and the biological activity is confirmed by inhibition of IL-6 signaling in a reporter cell assay (e.g., IL-6 Luciferase stable reporter cell line from Novus Biologicals).

US11879003B2. Methods for increasing T-cell function (2024-01-23). Kyverna Therapeutics, Inc. [US]. Inventors: John Lee [US], Erin O'Brien [US], Jordan Tsai [US], Lih-Yun Hsu [US], Faye Wu [US].
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Patent 2024
Amino Acid Sequence Antibodies, Anti-Idiotypic Antigens Autoimmune Diseases Base Sequence Biological Assay Biological Factors Biopharmaceuticals CD4 Positive T Lymphocytes Cell Lines Cells Chemokine Chemokine Receptor CXCR3 protein, human CXCR3 Receptors Enzyme-Linked Immunosorbent Assay Epitopes Flow Cytometry IL6R protein, human Immunoglobulins Immunoglobulins, Fab Inflammation Lentivirus Light Luciferases Mutation Novus Polypeptides Proteins Psychological Inhibition secretion T-Lymphocyte Therapeutics tocilizumab
2
Generating CXCR3+ Regulatory T-cells
Not available on PMC !

Example 3

CD4+CD45RA+ T-cells are transduced with a lentivirus having nucleic acid sequences encoding a CXCR3 polypeptide and a nucleic acid sequence encoding a FOXP3 polypeptide (FIG. 3). Following transformation, the cells are expanded in the presence of high dose rIL-2 and purified based on low expression of CD127 (IL7 receptor). Other means of purifying the cells as described herein or known in the art can also be used to purify the T-cell. CXCR3 expression is confirmed by flow cytometric analysis using an antibody against the CXCR3 polypeptide (e.g., anti-human CD183 (CXCR3) Biolegend Cat. No. RU0353707). CXCR3 function is also confirmed by an in vitro chemotaxis assay (e.g., transwell migration assay). Briefly, transduced cells are placed in a transwell system with a CXCR3 ligand (e.g., 50-300 ng/mL CXCL10 (human rCXCL10 from R&D Systems Cat No. 266-IP-010)) or a control chemokine present on the side of the membrane opposite the transduced cells. Migration of cells across the membrane is evaluated by flow cytometry using an antibody against CXCR3. Specificity is further confirmed by blocking migration with anti-CXCR3 blocking antibody.

US11879003B2. Methods for increasing T-cell function (2024-01-23). Kyverna Therapeutics, Inc. [US]. Inventors: John Lee [US], Erin O'Brien [US], Jordan Tsai [US], Lih-Yun Hsu [US], Faye Wu [US].
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Patent 2024
Antibodies, Anti-Idiotypic Base Sequence Biological Assay Cardiac Arrest Cell Migration Assays Cells Chemokine Chemokine Receptor Chemotaxis CXCR3 protein, human Flow Cytometry Homo sapiens Immunoglobulins Interleukin 7 Receptor Lentivirus Ligands Migration, Cell Polypeptides T-Lymphocyte Tissue, Membrane Tissues
3
PBMC Cytokine Response to RNA Agonists
Buffy coats, the fraction of an anti-coagulated blood sample that contains most of the white blood cells and platelets after the centrifugation of the blood (500 mL blood in 70 mL citrate phosphate dextrose coagulant), from five healthy human (consensual) blood donors, were obtained from Sanquin Blood Supply in Rotterdam, the Netherlands. PBMCs were isolated from each buffy coat within 24 h after blood collection, aliquoted, and cryopreserved. PBMCs were stimulated for 48 h with QR-1011 candidates AON32, AON44, AON59, or AON60 at a concentration of 1 μM and 10 μM; positive control R848 (1 μM); or PBS (vehicle control) at 37°C under a 5% CO2 atmosphere. For every donor, all conditions were tested in triplicate in 96-well round-bottom microtiter plates. The total number of viable PBMCs per well was 3 × 105. R848 (Resiquimod [tlrl-r848]; InvivoGen, San Diego, CA, USA), a potent Toll-like receptor (TLR)7/8 agonist, was selected as a positive control for its strong and robust immune-activating properties, inducing the production of pro-inflammatory cytokines. Also, R848 acts on the TLRs that are most likely to be involved in recognition of single-strand RNA, arguably making it the most relevant positive control for this purpose. After incubation, cell culture supernatant was isolated following centrifugation (300 relative centrifugal force for 5 min at room temperature). The viability of PBMCs after exposure to test items was assessed by resazurin reduction assay (CellTiter-Blue Reagent; Promega, Madison, WI, USA). Cytotoxicity was assessed by measurement of lactate dehydrogenase in the cell culture supernatant (CyQUANT LDH Cytotoxicity Assay; Thermo Fisher Scientific). Readout of viability and cytotoxicity assays was performed on a SpectraMax M5 Microplate reader. Cytokine levels in PBMC culture supernatants were measured using the MILLIPLEX MAP Human Cytokine/Chemokine Magnetic Bead Panel-Custom 6 Plex-Immunology Multiplex Assay (Merck KGaA, Darmstadt, Germany). Analytes included IFN-α2, IL-6, IP-10, MIP-1α, MIP-1β, and tumor necrosis factor-α. Assay plates were read on the Luminex MAGPIX platform (Luminex, San Francisco, CA, USA). Analysis of the Luminex data was performed in Bio-Plex Manager 6.1 software (Bio-Rad). Standard curves were fitted using five-parameter logistic regression. Cytokine concentrations that were outside of the detectable range of the assay were imputed for the purpose of calculation and statistical analysis. Values below the limit of detection (LOD), rendered “out of range <” by the analysis software, were imputed with a concentration value of ½ × LOD. The LOD values, which were empirically determined by the manufacturer of the Luminex kit, were derived from the technical data sheet. Conversely, cytokine concentrations that were above the upper limit of quantification, rendered “out of range >” by the analysis software, were imputed with a concentration value of two times the concentration of the highest calibrator.
Kaltak M., de Bruijn P., Piccolo D., Lee S.E., Dulla K., Hoogenboezem T., Beumer W., Webster A.R., Collin R.W., Cheetham M.E., Platenburg G, & Swildens J. (2023). Antisense oligonucleotide therapy corrects splicing in the common Stargardt disease type 1-causing variant ABCA4 c.5461-10T>C. Molecular Therapy. Nucleic Acids, 31, 674-688.
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Publication 2023
Atmosphere Biological Assay BLOOD Blood Platelets Cell Culture Techniques Centrifugation Chemokine citrate phosphate dextrose Coagulants Cytokine Cytotoxin Donor, Blood Homo sapiens Inflammation Lactate Dehydrogenase Leukocytes Promega resazurin resiquimod SERPINA3 protein, human Tissue Donors TLR8 protein, human Tumor Necrosis Factor-alpha
4
Expansion and Characterization of Allogeneic Tr1 Cells
FACS-sorter Allogenic Tr1 (Allo Tr1) cells (20x103/well) were cultured for 4 days (37°C/5% of CO2) in Expansion culture medium supplemented with 10% AB-HS and stimulated with anti-CD3/CD28-coated beads at a 1:5 ratio (Beads : Tr1) plus rhIL-10 (10 ng/mL) and rhIL-2 (250 U/mL) (expansion period). After 4 days of stimulation, the anti-CD3/CD28-coated beads were removed using the DynaMag and Allo Tr1 cells (50x103) were rested for 3 days in Expansion culture medium supplemented with 10% AB-HS and rhIL-2 (50 U/mL) (resting period). Three consecutive rounds of stimulation/resting (4 days of expansion and 3 days of resting each) were performed. A schematic representation of protocol is shown in Figure 1.
As a control group, allospecific CD4+ T conv cells (20x103/well) were polyclonally-expanded in parallel cultures with anti-CD3/anti-CD28 coated beads at 1:5 ratio (Beads:T conv) and rhIL-2 (100 U/mL) with the same rounds of stimulation/resting used for Allo Tr1 cells.
Throughout the ex vivo expansion protocol, IL-10 production of T cells was evaluated using IL-10 secretion assay and CytoStim™ kits (Miltenyi Biotec); next, the cells were stained with anti-CD4, anti-CD49b, anti-LAG-3, anti-TIM-3, anti-TIGIT, anti-PD1, anti-CTLA-4, anti-CD39 and Zombie Aqua™ for 30 min at 37°C in the dark and washed once with FACS buffer. The chemokine profile was evaluated with anti-CD4, anti-CD49b, anti-LAG-3, anti-CCR2, anti-CCR5, anti-CCR4, anti-CCR7, anti-CXCR3, and Zombie NIR™ and the samples were stained for 20 min at room temperature in the dark and washed once with FACS buffer. Sample acquisitions were performed in an Attune NxT cytometer (Thermo Scientific) and data were analyzed with FlowJo v10.8 software (BD Biosciences, CA, USA).
Arteaga-Cruz S., Cortés-Hernández A., Alvarez-Salazar E.K., Rosas-Cortina K., Aguilera-Sandoval C., Morales-Buenrostro L.E., Alberú-Gómez J.M, & Soldevila G. (2023). Highly purified and functionally stable in vitro expanded allospecific Tr1 cells expressing immunosuppressive graft-homing receptors as new candidates for cell therapy in solid organ transplantation. Frontiers in Immunology, 14, 1062456.
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Publication 2023
Biological Assay Buffers CCR5 protein, human CD4 Positive T Lymphocytes Cells Chemokine Culture Media CXCR3 protein, human Cytotoxic T-Lymphocyte Antigen 4 HAVCR2 protein, human Interleukin-10 Muromonab-CD3 secretion T-Lymphocyte TIGIT protein, human Tr1 Cells
5
Comprehensive Analysis of Chemokine Profiles
The aim of the present study was a comprehensive analysis of chemokines regarding their temporal patterns and correlations with clinical parameters. To that purpose the 20 chemokines included in the panel were isolated and further analyzed. In detail, twelve members of the “C-C family”, i.e., CCL2, CCL3, CCL4, CCL7, CCL8, CCL11, CCL13, CCL19, CCL20, CL23, CCL25 and CCL28; seven members of the “C-X-C family”, i.e., CXCL1, CXCL5, CXCL6, CXCL8, CXCL9, CXCL10 and CXCL11; and finally, the only member of the “C-X3-C” family CX3CL1. Notably, on the Olink Proteomics web site some of the included chemokines are listed with an alternative first name, i.e., CCL2 as MCP1, CCL7 as MCP3, CCL8 as MCP2, CCL11 as Eotaxin, CCL13 as MCP4, CXCL8 as IL-8 and CX3CL1 as Fractalkine.
Vlachogiannis P., Hillered L., Enblad P, & Ronne-Engström E. (2023). Elevated levels of several chemokines in the cerebrospinal fluid of patients with subarachnoid hemorrhage are associated with worse clinical outcome. PLOS ONE, 18(3), e0282424.
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Publication 2023
CCL2 protein, human CCL3 protein, human CCL4 protein, human CCL7 protein, human CCL8 protein, human CCL19 protein, human CCL20 protein, human CCL25 protein, human Chemokine CX3CL1 protein, human CXCL1 protein, human CXCL5 protein, human CXCL6 protein, human CXCL9 protein, human CXCL11 protein, human Eotaxin-1 Family Member MCP-4 protein, human

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The Bio-Plex 200 system is a multiplex immunoassay platform that allows for the simultaneous detection and quantification of multiple analytes in a single sample. The system utilizes fluorescently-labeled magnetic beads and a dual-laser detection system to perform high-throughput, multiplexed analyses.
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Rneasy mini kit by Qiagen
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The RNeasy Mini Kit is a laboratory equipment designed for the purification of total RNA from a variety of sample types, including animal cells, tissues, and other biological materials. The kit utilizes a silica-based membrane technology to selectively bind and isolate RNA molecules, allowing for efficient extraction and recovery of high-quality RNA.
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TRIzol reagent is a monophasic solution of phenol, guanidine isothiocyanate, and other proprietary components designed for the isolation of total RNA, DNA, and proteins from a variety of biological samples. The reagent maintains the integrity of the RNA while disrupting cells and dissolving cell components.
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Milliplex map mouse cytokine chemokine magnetic bead panel by Merck Group
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More about "Chemokine"

Chemokines are a family of small signaling proteins, also known as cytokines, that play a crucial role in the immune system and inflammation.
These chemoattractant proteins are responsible for recruiting and activating various immune cells, including leukocytes, to sites of infection or tissue damage.
Chemokines exert their effects by binding to specific G protein-coupled receptors, triggering signaling cascades that regulate cell migration, adhesion, and activation.
This diverse class of signaling molecules is essential for maintaining homeostasis, orchestrating immune responses, and contributing to the pathogenesis of numerous diseases, such as autoimmune disorders, cancer, and infectious diseases.
The chemokine network is a complex system, and understanding its intricacies is crucial for developing targeted therapies.
Researchers can leverage advanced tools and technologies to optimize their chemokine research protocols and enhance the reproducibility of their findings.
For instance, the Bio-Plex 200 system, a multiplex assay platform, can be used to simultaneously measure the levels of multiple chemokines and other cytokines in a single sample.
The RNeasy Mini Kit, on the other hand, can be used to extract high-quality RNA from cells and tissues, enabling the analysis of chemokine gene expression.
Additionally, the Milliplex Map Kit, a multiplexed assay, allows for the simultaneous quantification of multiple chemokines and other immune-related proteins.
The Bio-Plex Manager software can be utilized to analyze the data generated by these multiplex assays, providing researchers with valuable insights into the chemokine signaling pathways and their involvement in various disease states.
By leveraging these advanced tools and technologies, researchers can optimize their chemokine research protocols, enhance the reliability of their findings, and unlock new insights into the complex chemokine network.
This knowledge can then be applied to the development of targeted therapies for a wide range of conditions, from autoimmune disorders to cancer and infectious diseases.