BRAND / VENDOR: Agilent

Agilent, GS24-CU, GlykoPrep cleanup module, 24-ct

CATALOG NUMBER: GS24-CU

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Product Description

GlykoPrep cleanup module, 24-ct. GlykoPrep N-glycan sample preparation is a cartridge based workflow. Module for cleanup of glycans from aqueous solution. Compatible with microplate liquid handling platforms. Designed for cleanup with the InstantDye labeling modules.

Specifications:
Count: 24
Equipment & Reagents Provided by User: Acetonitrile (ACN, 100%, HPLC-grade)AssayMAP Labware (AM200)Centrifuge (capable of 50 - 1000 x g) and deep microplate rotor with clearance of minimum 44 mm heightFormic acid (HPLC-grade)Heater and incubation blocks, capable of 50–100°C, available from Agilent (GS150)Ultrapure, deionized water
Kit Configuration: Sample Prep Module
Protein Load Range: 1-30 µg

**********The following product description is generated by AI and is for reference only. If you have any questions, please contact customer service.**********
Designed for reliable and streamlined sample preparation, this cleanup module enables efficient purification of glycans from a variety of biological samples. The kit includes 24 pre-formulated units, ensuring consistency and reproducibility across multiple experiments. Optimized for use in workflows requiring high-throughput glycan analysis, it supports research applications such as glycoprotein profiling, biopharmaceutical characterization, and biomarker discovery. Each unit is suitable for the removal of impurities and contaminants prior to downstream analytical techniques, including mass spectrometry and HPLC.

This module integrates seamlessly with the Agilent GlykoPrep system and related Agilent analytical platforms. It is particularly valuable in laboratories focused on studying glycosylation patterns, method development, and quality control processes. Compatible with a wide range of glycoprotein samples, it enhances the accuracy and reliability of glycan quantitation and structural elucidation. The included components are designed for straightforward handling, reducing total sample preparation time. Researchers benefit from improved sample purity, reduced variability, and enhanced method robustness. It is suitable for both small-scale exploratory studies and larger, routine sample processing in regulated environments.

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Collaboration

Tony Tang

Email: Tony.Tang@iright.com

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