DOTA-NHS-ester is a linker for affibody molecules and is applied in small animals PET, SPECT, and CT. DOTA-NHS-ester can be used to label radiotherapeutic agents or imaging probes for the detection of tumors.
Storage Temp
Store at -20°C,Desiccated
Shipped In
Ice chest + Ice pads
This product requires cold chain shipping. Ground and other economy services are not available.
Product Description
DOTA-NHS-ester is a linker for affibody molecules and is applied in small animals PET, SPECT, and CT. DOTA-NHS-ester can be used to label radiotherapeutic agents or imaging probes for the detection of tumors.
In Vitro
DOTA-NHS-ester can be used to modify human serum albumin (HSA) to produce DOTA-HSA. And DOTA-HSA is furtherly modified by Sulfo-SMCC to obtain DOTA-HSA-SMCC. DOTA-HSA-SMCC is conjugated to ZHER2:342 and the final product is DOTA-HSA-Z HER2 :342. In a cell uptake assay, DOTA-HSA-Z HER2 :342 is labeled by 64 Cu, 64 Cu-DOTA-HSA-Z HER2 :342 (0.5-2 hours) slowly accumulates in the SKOV3 cells and reaches 0.71% of the applied activity at 0.5 h and the uptake increased to 1.58% at 2 h. MCE has not independently confirmed the accuracy of these methods. They are for reference only.
In Vivo
In a microPET images of a mouse bearing SKOV3 tumor, 64 Cu-DOTA-HSA-Z HER2 :342 is injected to the mouse tail. microPET images of a mouse bearing SKOV3 tumor at 1, 4, 24 and 48 h after tail vein injection. The SKOV3 tumor is visible with a low tumor-to-background contrast at 1 h post-injection (p.i.), but with a very good tumor-to-background contrast at 4 and 24 h p.i. Quantification analysis reveals that the SKOV3 tumor uptake values increases with time and are found to be 5.63%, 9.98%, 14.34% and 14.12% ID/g at 1, 4, 24, and 48 h, respectively . MCE has not independently confirmed the accuracy of these methods. They are for reference only.
This compound belongs to the class of organic compounds known as tetracarboxylic acids and derivatives. These are carboxylic acids containing exactly four carboxyl groups.
External Descriptors
Not available
1. Djoumbou Feunang Y, Eisner R, Knox C, Chepelev L, Hastings J, Owen G, Fahy E, Steinbeck C, Subramanian S, Bolton E, Greiner R, and Wishart DS. ClassyFire: Automated Chemical Classification With A Comprehensive, Computable Taxonomy. Journal of Cheminformatics, 2016, 8:61.
F2523388