The authors used a bottom‑up thermodynamic modelling framework to investigate how plants decode calcium signals, starting from Ca2+ binding to EF‑hand proteins and extending to higher‑order decoding modules. They identified six universal Ca2+-decoding modules that can explain variations in calcium sensitivity among kinases and provide a theoretical basis for interpreting calcium signal amplitude and frequency in plant cells.

Four barley genotypes were examined under simultaneous Fusarium culmorum infection and drought, revealing genotype-dependent Fusarium Head Blight severity and largely additive transcriptomic responses dominated by drought. Co‑expression and hormone profiling linked ABA and auxin to stress‑specific gene modules, and a multiple linear regression model accurately predicted combined‑stress gene expression from single‑stress data, suggesting modular regulation.

The study generated comprehensive hormonal profiles of hazelnut catkins across the dormancy period, revealing that abscisic acid declines while gibberellins rise, resulting in a decreasing ABA/GA ratio that correlates with dormancy release. Cytokinins unexpectedly increased throughout dormancy, auxin conjugates and ethylene precursors showed distinct patterns between early and late blooming accessions, suggesting hormone manipulation could delay bloom.

The study benchmarked several sampling approaches for simultaneous profiling of root exudates and rhizosphere microbiota in soil-grown barley, revealing consistent exudate chemistry across methods but variation in root morphology and nitrogen exudation. High‑throughput amplicon sequencing and quantitative PCR showed protocol‑specific impacts on microbial composition, yet most rhizosphere-enriched microbes were captured by all approaches. The authors conclude that different protocols provide comparable integrated data, though methodological differences must be aligned with experimental objectives.