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Researchers evaluated the flavor quality of milk processed with alternating-current high electric field (AC-HEF) pasteurization compared to conventional ultrahigh temperature (UHT) treatment, which is known for producing undesirable "cooked" flavors. To analyze the differences, the team profiled volatile compounds using solid-phase microextraction gas chromatography-mass spectrometry (GC-MS) and utilized gas chromatography-sulfur chemiluminescence detection (GC-SCD) specifically for sulfur-containing volatiles. The robust chromatographic analysis revealed that AC-HEF effectively suppresses the formation of off-flavors while maintaining favorable aromatic compounds, suggesting it is a promising alternative for producing shelf-stable milk with an improved flavor profile.

Researchers have optimized a headspace sorptive extraction (HSSE) method coupled with gas chromatography-mass spectrometry (GC-MS) to analyze human scent traces left on clothing. By extracting volatile and semi-volatile organic compounds and applying supervised machine learning algorithms, such as support vector machines (SVM) and partial least squares-discriminant analysis (PLS-DA), to the GC-MS data, the team achieved 100% accuracy in gender discrimination. This combination of optimized extraction, GC-MS analysis, and machine learning provides a rapid and automated forensic screening technique to help narrow down suspect or victim profiles based on trace evidence.

Researchers successfully employed high-performance liquid chromatography with fluorescence detection (HPLC-FLD) to analyze atmospheric polycyclic aromatic hydrocarbons (PAHs) across Quebec using Pleurozium schreberi moss. The chromatographic analysis targeted 10 PAHs to establish a rigorous spatial baseline of pollution and 15 PAHs to measure the environmental impact of the severe 2023 Canadian wildfires. The HPLC-FLD data revealed that while the wildfires did not increase total PAH concentrations, they caused distinct compositional shifts, proving the effectiveness of this analytical method in detecting regional pollution gradients and temporal source changes.

A worldwide study involving 12 research groups has confirmed that capillary zone electrophoresis combined with mass spectrometry (CZE-MS) is a highly reproducible and sensitivealternative to traditional methods for analyzing proteoforms, offering a way to separate these critical protein variations based on their charge-to-size ratio. LCGC International spoke to Kevin Jooß of the Vrije Universiteit Amsterdam, one of the authors of a paper outlining the study, about this work.

Headspace solid-phase microextraction-gas chromatography–mass spectrometry (HS-SPME/GC-MS) and high-performance liquid chromatography with diode-array detection (HPLC-DAD) were used to evaluate 45 Brazilian artisanal chocolates, identifying 72 volatile compounds and quantifying methylxanthines. Results demonstrated that theobromine and caffeine concentrations strongly correlate with declared cocoa content, proving these chromatographic methods provide a reliable workflow for quality control, traceability, and fraud prevention in chocolate manufacturing.

Headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry HS-SPME-GC-MS was used by researchers to analyze volatile organic compounds (VOCs) during goat cheese ripening over 150 days. They identified 68 VOCs and found that 2-butanone and 2-butanol serve as potential markers for the final maturation stage, offering a simple, low-cost method for early monitoring of cheese ripening.

Researchers utilized gas chromatography (GC) to evaluate and compare the fatty acid compositions of plant-based meat substitutes and traditional ground beef available on the market. Following homogenization and lipid extraction, the GC data revealed distinct fatty acid profiles between the two groups. The analysis demonstrated that most plant-based alternatives exhibited higher polyunsaturated fatty acid levels and more favorable nutritional indices—such as the unsaturation and hypocholesterolemic indices—compared to beef, though the researchers noted that the specific health implications rely heavily on the diverse types of oils used in each plant-based product.

Advances in liquid chromatography (LC) address the growing need to analyze complex analytes with higher sensitivity and efficiency. Application-specific column chemistries, optimized system configurations, and improved consumables help mitigate PFAS contamination, metal-sensitive analytes, and solvent-related artifacts. Emerging injection strategies and smart instrumentation aim to enhance data quality and laboratory productivity, demonstrating that optimizing LC methods goes beyond column selection alone.

Gas chromatography-mass spectrometry (GC-MS) and orthogonal partial least squares (OPLS) regression to analyze both volatile and non-volatile compounds in five strawberry cultivars. The study successfully correlated specific compounds with sensory profiles like sweetness and flavor, offering valuable insights to improve predictive models and guide future strawberry breeding programs.

Antibody–oligonucleotide conjugates (AOCs) represent a promising new biotherapeutic modality that combines the cell‑targeting specificity of antibodies with the gene‑modulating power of oligonucleotides. Designed to overcome long‑standing delivery barriers in nucleic acid therapeutics, AOCs enable targeted delivery beyond the liver to tissues such as skeletal muscle, heart, and the central nervous system. Their unique dual therapeutic behavior and large oligonucleotide payload introduce analytical challenges distinct from antibody‑drug conjugates (ADCs), requiring approaches such as size-exclusion chromatography–mass spectrometry (SEC–MS) and ion‑exchange methods. As analytical science advances, AOCs are poised to expand therapeutic possibilities and drive innovation in precision and personalized medicine.

Researchers investigated the effects of electron beam irradiation on cold fresh rainbow trout using GC×GC-MS and lipidomics. The chromatographic analysis revealed that while low doses preserve quality, doses of 3 kGy or higher accelerate lipid oxidation, significantly increasing volatile flavor compounds and causing unwanted irradiation odors that lower sensory acceptability.

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Field-flow fractionation (FFF), and, in particular, asymmetrical flow field-flow fractionation (AF4), is transitioning from a specialized separation technique into an application-driven analytical platform. From the perspective of the Young Scientists of FFF, we describe how advances in inline detection, data analysis, and validation are expanding AF4’s capacity to deliver size-resolved structural and compositional insights into complex systems. We highlight how this evolution enables more reliable characterization of heterogeneous and dynamically assembled materials across disciplines. We argue that realizing this potential will require deliberate choices (by the community, instrument developers, and end users) to move AF4 from niche expert knowledge to broadly trusted analytical practice.

Gas chromatography coupled with quadrupole mass spectrometry (GC-qMS) and high-performance liquid chromatography equipped with diode-array and refractive index detectors (HPLC-DAD/RI) to analyze the chemical and aromatic profiles of kombucha fermented with pineapple, fennel, and carrot by-products. The chromatographic data revealed how specific microbial communities interact with these plant residues to produce unique volatile organic compounds, demonstrating a sustainable approach for value-added beverage production.

Μetabolomics enables the comprehensive profiling of small molecules in medicine, plant science, and systems biology. Its true value depends not on the number of detected features but on the reliability of metabolite identification and pathway analysis. Despite well-established guidelines, annotation and definitive identification are often conflated in practice. Simple matches in mass databases are frequently reported as identities, without comparison to standards or chromatographic evidence. This overstatement of confidence compromises validity and risks propagating errors into databases, pathway analyses, and AI-driven workflows. Mass spectrometry (MS) alone is rarely sufficient for identification and orthogonal evidence is essential. Chromatographic retention time is an underused but powerful descriptor reflecting molecular properties. When combined with MS it can provide plausibility checks and form the basis of Level 1 identification. Regulatory frameworks already require such combined criteria in targeted analysis. Systematic use of retention order, retention indices, and prediction models can filter implausible candidates and strengthen identification.