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Quantitative Human DAT (Glycosylated) Sandwich ELISA Kit

CAT#: GLJF-0525-HX516

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Specifications
Product Description
The quantitative human DAT (glycosylated) sandwich ELISA kit is designed to detect human dopamine transporter (DAT) levels. DAT is a membrane protein that plays a critical role in regulating dopamine neurotransmission. DAT is located on the presynaptic neuron and functions to remove dopamine from the synaptic cleft, the space between neurons. This reuptake process terminates dopamine signaling and allows for its recycling. The kit is suitable for various biological samples such as tissue homogenates, cell lysates. Its sensitivity is 0.083 ng/mL, which can accurately detect low concentrations of DAT in the sample.
Target
DAT
Kit Components
Pre-coated ELISA plate; Lyophilized standard; Biotin-labeled antibody; HRP-avidin; Various diluents; Wash buffer; TMB chromogenic substrate; Stop solution
Sample Types
Tissue homogenates, cell lysates
Sample Volume
100 μL
Sensitivity
0.083 ng/mL
Detection Principle
Quantitative sandwich ELISA
Detection Range
1 ng/mL-10 ng/mL
Detection Time
1 h-5 h
Detection Wavelength
450 nm
Storage
Store at 2-8°C for long term storage.
Target Information
Species
Human
Full Name
Dopamine transporter
Alternate Names
DAT; Dopamine transporter; SLC6A3; DAT1; Sodium-dependent dopamine transporter; Dopamine active transporter
Uniprot No.
N-Glycosylation Site
181, 188, 205
Application Notes
Application
The quantitative human DAT (glycosylated) sandwich ELISA kit is a valuable tool for neuroscience research, particularly in studies of dopamine signaling and related disorders. Researchers use it to measure DAT levels in brain tissue and other biological samples. The kit has applications in studies of Parkinson's disease, addiction, and attention deficit hyperactivity disorder (ADHD).
Precision
Intra-Assay: n=20, CV <8%;
Inter-Assay: n=20, CV <10%;
Recovery
Serum sample: n=5, 80-95%;
Plasma sample: n=4, 90-110%;
Standard Curve

The standard curve is for reference only, and a new standard curve should be generated for each set of samples tested.
For Research Use Only.
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