Best of the Week: Metal Speciation with Liquid Chromatography, Assisted Active Learning

This past week, LCGC International published a variety of articles on hot topics in separation science. We published a new LCGC Blog that covered the current challenges in metal speciation in biological systems and explored what assisted active learning (AAL) is and how it can improve liquid chromatography (LC) method development. Also, Pittcon and Analytica are coming up in March, and these in-person conferences will allow for in-person networking and collaboration like no other.

This is the Best of the Week.

The LCGC Blog: No Column to Rule Them All — Making Sense of Metal Speciation with Liquid Chromatography

In this LCGC blog post, Hayley Brawley, a senior research scientist at COSMIC, and Alexia Kreinbrink, a postdoctoral research associate at Texas A&M University, examine the analytical challenges of metal speciation in biological systems. Traditional elemental techniques like atomic absorption spectroscopy (AAS) and inductively coupled plasma–mass spectrometry (ICP-MS) quantify total metal content but miss biologically critical chemical forms.¹ Chromatography paired with elemental or molecular MS enables speciation but introduces trade-offs. Size-exclusion chromatography (SEC) distinguishes large metalloproteins from small complexes yet suffers from ligand exchange and limited resolution.¹ The authors emphasized in their blog multidimensional liquid chromatography–mass spectrometry (LC–MS) workflows and gentle sample handling as the future of metallomics.¹

AI/ML in Practice: Emery Bosten Explores Assisted Active Learning (AAL)

In this interview, Emery Bosten discussed AAL, which is a machine-learning (ML) framework designed to accelerate LC method development. Traditional LC optimization relies on trial-and-error exploration of interacting parameters.² AAL improves efficiency by combining active learning, sequentially selecting the most informative experiments, with prior knowledge from historical data and analyte properties using Bayesian statistics.² This enables faster convergence toward optimal separations with fewer runs, sometimes only three. Case studies showed comparable performance to conventional methods with far fewer experiments.² Challenges include data quality, automation integration, and user confidence, but AAL offers a path toward autonomous, closed-loop LC systems.²

Comprehensive GC–MS/MS Quantification of Gut Microbiota–Derived Metabolites Across Intestinal and Systemic Tissues

Researchers at the European Molecular Biology Laboratory developed and validated a targeted gas chromatography–tandem mass spectrometry (GC–MS/MS) method to quantify 120 gut microbiota–derived metabolites across diverse biological matrices, as discussed by Nikita Denisov and Michael Zimmermann. Gas chromatography with derivatization enables sensitive separation of small, volatile metabolites, while multiple-reaction monitoring and 52 isotopically labeled standards ensure specificity and quantitative accuracy.³ The method addresses matrix effects, stabilization buffers, and normalization challenges, and distinguishes microbiota-dependent metabolites using germ-free models.³ By linking quantitative metabolite data with sequencing, the approach advances mechanistic understanding of host–microbiota metabolic interactions and supports translational microbiome research.³

Advancing Separation Science: The Power of In‑Person Chromatography Conferences

As chromatography advances through AI, digitalization, and sustainability demands, in-person conferences remain vital for staying current. In this article, associate editorial director Kate Jones highlights Pittcon 2026 and Analytica 2026 as key global gatherings. Pittcon offers hands-on instrument access, broad analytical coverage, and strong networking in San Antonio.⁴ Analytica provides a comprehensive view of laboratory technologies, with emphasis on AI-driven automation and green lab practices.⁴ Both events foster collaboration, practical learning, and exposure to emerging chromatographic innovations essential for scientists navigating 2026’s evolving analytical landscape.

UHPLC-HRMS Suspect Screening Reveals 153 Pharmaceutical Contaminants in Tagus River Basin Ecosystems

A study by the Centre for Energy, Environmental and Technological Research applied ultrahigh-pressure liquid chromatography–high-resolution mass spectrometry (UHPLC-HRMS) suspect screening to assess pharmaceutical contamination across the Tagus River basin. Analyzing water, sediment, fish, wastewater, and sludge samples (2020–2022), researchers identified 153 pharmaceutically active compounds, dominated by cardiovascular, psychotropic, and analgesic drugs.⁵ Surface waters and effluents showed the highest diversity, while sediments and sludge accumulated hydrophobic compounds.⁵ This study demonstrates HRMS screening’s ability to detect diverse pharmaceuticals without standards, supporting contaminant prioritization, environmental monitoring, and regulatory decisions, and guiding ecotoxicological research and mitigation strategies.

References

1. Brawley, H.; Kreinbrink, A. The LCGC Blog: No Column to Rule Them All — Making Sense of Metal Speciation with Liquid Chromatography. LCGC International. Available at: https://www.chromatographyonline.com/view/the-lcgc-blog-no-column-to-rule-them-all-making-sense-of-metal-speciation-with-liquid-chromatography (accessed 2026-02-20).
2. Bosten, E.; Matheson, A. AI/ML in Practice: Emery Bosten Explores Assisted Active Learning (AAL). LCGC International. Available at: https://www.chromatographyonline.com/view/ai-ml-in-practice-emery-bosten-explores-assisted-active-learning-aal- (accessed 2026-02-20).
3. Denisov, N.; Zimmermann, M.; Chasse, J. Comprehensive GC–MS/MS Quantification of Gut Microbiota–Derived Metabolites Across Intestinal and Systemic Tissues. LCGC International. Available at: https://www.chromatographyonline.com/view/comprehensive-gc-ms-ms-quantification-of-gut-microbiota-derived-metabolites-across-intestinal-and-systemic-tissues (accessed 2026-02-20).
4. Jones, K. Advancing Separation Science: The Power of In‑Person Chromatography Conferences. LCGC International. Available at: https://www.chromatographyonline.com/view/advancing-separation-science-the-power-of-in-person-chromatography-conferences (accessed 2026-02-20).
5. Chasse, J. UHPLC-HRMS Suspect Screening Reveals 153 Pharmaceutical Contaminants in Tagus River Basin Ecosystems. LCGC International. Available at: https://www.chromatographyonline.com/view/uplc-hrms-suspect-screening-reveals-153-pharmaceutical-contaminants-in-tagus-river-basin-ecosystems (accessed 2026-02-20).