Examination of DNAm PhenoAge as an epigenetic biomarker for perioperative risk in adult spinal deformity surgeries - Michael P. Kelly; Jeffrey Hills; Justin S. Smith; Lawrence G. Lenke; Han Jo Kim; Shay Bess; Breton Line; Virginie Lafage; Renaud Lafage; Eric Klineberg; Ferran Pellise; Khaled Kebaish; et al. (GeroScience, 2026)

Data quality control considerations in multivariate environmental monitoring: experience of the French coastal network SOMLIT - Elsa Breton; Nicolas Savoye; Peggy Rimmelin-Maury; Benoit Sautour; Eric Goberville; Arnaud Lheureux; Thierry Cariou; Sophie Ferreira; Hélène Agogué; Samir Alliouane; Fabien Aubert; Sébastien Aubin; et al. (Frontiers in Marine Science, 2023)
Introduction While crucial to ensuring the production of accurate and high-quality data—and to avoid erroneous conclusions—data quality control (QC) in environmental monitoring datasets is still poorly documented. Methods With a focus on annual inter-laboratory comparison (ILC) exercises performed in the context of the French coastal monitoring SOMLIT network, we share here a pragmatic approach to QC, which allows the calculation of systematic and random errors, measurement uncertainty, and individual performance. After an overview of the different QC actions applied to fulfill requirements for quality and competence, we report equipment, accommodation, design of the ILC exercises, and statistical methodology specially adapted to small environmental networks (<20 laboratories) and multivariate datasets. Finally, the expanded uncertainty of measurement for 20 environmental variables routinely measured by SOMLIT from discrete sampling—including Essential Ocean Variables—is provided. Results, Discussion, Conclusion The examination of the temporal variations (2001–2021) in the repeatability, reproducibility, and trueness of the SOMLIT network over time confirms the essential role of ILC exercises as a tool for the continuous improvement of data quality in environmental monitoring datasets.