The study introduces a hybrid modeling framework that integrates a logistic ordinary differential equation with a Long Short-Term Memory neural network to form a Physics-Informed Neural Network (PINN) for predicting wheat plant height. Using only time and temperature as inputs, the PINN outperformed other longitudinal growth models, achieving the lowest average RMSE and reduced variability across multiple random initializations. The results suggest that embedding biological growth constraints within data‑driven models can substantially improve prediction accuracy for plant traits.

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.

The authors compiled and standardized published data on Rubisco dark inhibition for 157 flowering plant species, categorizing them into four inhibition levels and analyzing phylogenetic trends. Their meta‑analysis reveals a complex, uneven distribution of inhibition across taxa, suggesting underlying chloroplast microenvironment drivers and providing a new resource for future photosynthesis improvement efforts.

The study investigates how cortical microtubule orientations are coordinated across tissues, testing the hypothesis that they sense mechanical stress. By quantifying microtubule behavior on different cell faces and edges, the authors find that tissue-level biases arise from cell‑geometric factors and edge‑specific mechanisms rather than direct stress sensing, and they develop a combinatorial model incorporating face‑specific and edge‑specific microtubule dynamics to explain the observed coordination.

The study isolated the Plant Cysteine Oxidase/Ethylene Response Factor VII oxygen‑sensing circuit from Arabidopsis thaliana and reconstituted it in Saccharomyces cerevisiae, using a reporter to compare hypoxia‑induced transcriptional dynamics in yeast and plants. Both systems showed rapid ERFVII stabilization, but plants exhibited a larger response, which could be enhanced in yeast by adding a hypoxia‑inducible feedback loop. Computational modeling identified promoter competition and hypoxia‑inducible PCOs as key determinants of early hypoxia responses.

The study investigates the altered timing of the core circadian oscillator gene ELF3 in wheat compared to Arabidopsis, revealing that dawn-specific expression in wheat arises from repression by TOC1. An optimized computational model integrating experimental expression data and promoter architecture predicts that wheat’s circadian oscillator remains robust despite this shift, indicating flexibility in plant circadian network design.