Tregitope 289
Tregitope 289 is a peptide derived from the Fc region of immunoglobulin G (IgG) and is a highly conserved T cell epitope that stimulates the expansion of natural regulatory T cells. Co-delivery of Tregitope 289 with type 1 diabetes (T1D) antigens delays the development of hyperglycemia and reduces the incidence of diabetes in the NOD mouse model. Tregitope 289 can be used to study T1D and other autoimmune diseases.
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- Formule: C115H173N31O36
- Masse moléculaire:2565.79
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Stockage:
Please store the product under the recommended conditions in the Certificate of Analysis.
Activité biologique
Description
Chemical Information
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Masse moléculaire 2565.79
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Formule C115H173N31O36
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Sequence
Glu-Glu-Gln-Tyr-Asn-Ser-Thr-Tyr-Arg-Val-Val-Ser-Val-Leu-Thr-Val-Leu-His-Gln-Asp-Trp-NH2
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Sequence Shortening
EEQYNSTYRVVSVLTVLHQDW-NH2
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Livraison
Room temperature in continental US; may vary elsewhere.
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Stockage
Please store the product under the recommended conditions in the Certificate of Analysis.
Protocole
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Research Protocol for Metabolic Diseases
AMP-activated protein kinase, AMPK, is a conserved cellular energy sensor that responds to reduced cellular energy status and coordinates metabolism by increasing ATP-generating catabolic pathways while suppressing ATP-consuming anabolic processes. In metabolic disease research, the AMPK pathway is experimentally relevant because it regulates hepatic lipid synthesis, fatty acid oxidation, glucose production, skeletal-muscle glucose disposal, mTORC1-linked biosynthesis, autophagy, mitochondrial homeostasis, and whole-body energy balance. The central pathway logic is that energy stress, metformin, exercise-like stimulation, or direct AMPK activators increase AMPKα Thr172 phosphorylation and downstream substrate phosphorylation, including ACC and RAPTOR. Phosphorylation of ACC suppresses lipogenesis and supports fatty acid oxidation, whereas phosphorylation of RAPTOR suppresses mTORC1 signaling and links cellular energy status to growth and protein synthesis control. The pathway is linked
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Research Protocol for Cancer Immunology
Cancer immunology studies how the immune system recognizes, suppresses, edits, or fails to eliminate malignant cells through tumor antigen release, antigen presentation, T-cell priming, immune trafficking, tumor-cell killing, and feedback inhibition in the tumor microenvironment. The cancer-immunity cycle links tumor antigenicity, dendritic-cell priming, CD8+ T-cell infiltration, cytotoxic function, and immune-checkpoint regulation to tumor rejection or immune escape. Immune-checkpoint pathways such as PD-1/PD-L1 and CTLA-4 suppress antitumor T-cell activity and can be therapeutically blocked, but many tumors remain resistant because of poor antigen presentation, weak T-cell infiltration, suppressive myeloid cells, regulatory T cells, and tumor-intrinsic immune-exclusion programs. Unresolved questions include which immune-cell states predict response, how tumor-intrinsic pathways exclude immune cells, how myeloid suppression limits checkpoint blockade, and which combination strategies
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How to Choose the Right Model Animal
Choosing the right model animal is a validity-driven decision in which the species, strain, sex, age, genetic background, disease-induction method, outcome measures, and welfare burden must match the scientific question rather than laboratory tradition or convenience. A model should be selected by judging face validity, construct validity, and predictive validity: whether it resembles the human phenotype, whether it reproduces relevant mechanisms, and whether results are likely to predict human biology or treatment response. Animal studies often fail to translate because of species differences, weak disease resemblance, poor experimental design, inadequate reporting, publication bias, and underuse of randomization, blinding, and sample-size justification. Unresolved questions include how to rank competing models objectively, how much human-disease complexity must be reproduced for a given objective, and when non-animal systems such as organoids, ex vivo tissue, or computational models
Pureté et documentation
Références
Calculators
Concentration (start) × Volume (start) = Concentration (final) × Volume (final)