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Liquid chromatography-mass spectrometry (LC-MS) profiling reveals chemical diversity across grapevine varieties.

Liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) link perinatal factors to infant urinary metabolite changes.

This LCGC Blog installment explains how NIST categorizes and certifies reference materials, and why they underpin reliable results in science and medicine.

Comparing manual and automated N-glycan profiling of a trastuzumab biosimilar, researchers found that both workflows detected the same glycan types, but automation gave more reproducible results (mean CV of about 5.7% vs. 7.95%), making it better suited to high-throughput analysis in biopharmaceutical development.

How can analysts resolve impurities that differ by a single mass unit? Experts discuss deamidation, racemization, HRMS, and 2D-LC for GLP-1 peptides.

"LC Troubleshooting" explores why phosphorothioate oligonucleotides (ONs) diastereomers challenge liquid chromatography.

This new high-performance liquid chromatography (HPLC) method reliably measures cholesterol adsorption in artichoke fiber.

The panel walks through confirming peptide identity–from HRMS and LC–MS/MS sequencing to amino acid analysis and D/L-isomer verification.

Malte Hübschen of the University of Duisburg-Essen (Germany) discusses an automated gas chromatography-tandem mass spectrometry (GC-MS/MS) workflow that improves phthalate detection in tricky oils with LCGC International.

Liquid chromatography–ion mobility spectrometry–high-resolution mass spectrometry (LC–IMS–HRMS) shows elephant seal pups carry more PFAS than their mothers do.

Gas chromatography–mass spectrometry (GC–MS) and omics profiling distinguish duck and goose foie gras composition.

This week's Chromatography Online highlights include olive waste antioxidant recovery, food and tea analysis, EV isolation, mRNA vaccine purification, perfusion chromatography for oligonucleotides, mass spectrometry in teaching and career advice from “Women in Chromatography.”

Kinjal Bhatt and Ina Varfaj call AI a chromatography equalizer only if training and access keep pace, framing the risk as implementation, not technology.