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CBS 134

Detection of DEG and EG in syrup products

Featured applications:

  • Tire particles assessment with HPTLC bioassays
  • Machine learning for botanical identification
  • Analysis of Flavonoids and Anthraquinones in Cassia
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CBS ARTICLES IN THIS EDITION

Tire particles assessed with HPTLC bioassays

April 30, 2025
A Swiss research team investigates the chemical substances released from tire wear and their potential impact. Using advanced HPTLC bioassays, they identified compounds that may pose a risk to organisms. Get an inside look at cutting-edge research on tire particle toxicity and environmental safety.
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Detection and limit test of diethylene glycol and ethylene glycol impurities in syrup by HPTLC

April 30, 2025
This optimized HPTLC method enables sensitive and reliable detection of diethylene glycol and ethylene glycol impurities in oral liquid formulations. With a detection limit as low as 21 ng and clear differentiation from other excipients, the method meets and exceeds regulatory safety thresholds, offering a robust tool for pharmaceutical quality control.
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Machine learning for botanical identification

April 30, 2025
A cutting-edge machine learning system analyzes HPTLC fingerprints to accurately distinguish botanical species and common adulterants. By generating synthetic training data and automating image classification, it eliminates subjective manual comparisons – delivering faster, more reliable results for quality control in herbal products.
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Simultaneous determination of flavonoids and anthraquinones in seven Cassia species

April 30, 2025
A newly optimized HPTLC method enables simultaneous resolution of 13 flavonoids and anthraquinones from leaves and flowers of seven Cassia species. Offering high specificity, fluorescence detection, and robust derivatization, this approach supports taxonomic differentiation and quality control in herbal drug analysis.
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