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 study generated a dataset of 420 sgRNAs targeting promoters, exons, and introns of 137 tomato genes in protoplasts, linking editing efficiency to chromatin accessibility, genomic context, and sequence features. Open chromatin sites showed higher editing rates, while transcriptional activity had little effect, and a subset of guides produced near‑complete editing with microhomology‑mediated deletions. Human‑trained prediction models performed poorly, highlighting the need for plant‑specific guide design tools.

The study identifies the extended NT‑C2 domain of Plastid Movement Impaired 1 (PMI1) as the main membrane‑binding module that interacts with PI4P and PI(4,5)P2, requiring basic residues for plasma‑membrane association. Calcium binding by the NT‑C2 domain modulates its phosphoinositide preference, and cytosolic Ca2+ depletion blocks blue‑light‑induced PMI1 redistribution, indicating that both the NT‑C2 domain and adjacent intrinsically disordered regions are essential for PMI1’s role in chloroplast movement.

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 study reveals that rice perceives Xanthomonas oryzae pv. oryzae outer membrane vesicles through a rapid calcium signal that triggers plasma‑membrane nanodomain formation and the re‑organisation of defence‑related proteins, establishing an early immune response. Without this Ca2+ signal, OMVs are not recognized and immunity is weakened.

Using a microfluidic valve rootchip, the study simultaneously tracked ROS and calcium dynamics in compressed roots and found three kinetic phases linking mechanosensitive channel activity, NADPH oxidase‑dependent ROS accumulation, and secondary calcium influx. Pharmacological inhibition revealed that a fast calcium response is mediated by plasma‑membrane mechanosensitive channels, while a slower calcium increase is driven by ROS production.

The study uses an optogenetic ChannelRhodopsin 2 variant (XXM2.0) to generate defined cytosolic Ca²⁺ transients in Arabidopsis root cells, revealing that these Ca²⁺ signatures suppress auxin‑induced membrane depolarization, Ca²⁺ spikes, and auxin‑responsive transcription, leading to reversible inhibition of cell division and elongation. This demonstrates that optogenetically imposed Ca²⁺ signals act as dynamic regulators of auxin sensitivity in roots.

The study demonstrates that jasmonate (JA) enhances Arabidopsis thaliana responses to extracellular ATP (eATP) by upregulating the eATP receptor P2K1 and amplifying eATP‑induced cytosolic Ca²⁺ spikes and transcriptional reprogramming in a COI1‑dependent manner, whereas salicylic acid pretreatment suppresses these responses. These findings reveal a JA‑mediated priming mechanism that potentiates eATP signaling during stress.

The study characterizes a plasma membrane-localized, calcium‑permeable force‑gated channel named Rapid Mechanically Activated (RMA) in plants, using patch‑clamp and pressure‑clamp to elucidate its rapid activation, inactivation, and irreversible adaptation upon repeated mechanical stimulation. Kinetic modeling shows the channel functions as a pass‑band filter for frequencies between 10 Hz and 1 kHz, supporting its role in transducing high‑frequency mechano‑stimuli such as insect vibrations.

The study integrates genome, transcriptome, and chromatin accessibility data from 380 soybean accessions to dissect the genetic and regulatory basis of symbiotic nitrogen fixation (SNF). Using GWAS, TWAS, eQTL mapping, and ATAC-seq, the authors identify key loci, co‑expression modules, and regulatory elements, and validate the circadian clock gene GmLHY1b as a negative regulator of nodulation via CRISPR and CUT&Tag. These resources illuminate SNF networks and provide a foundation for soybean improvement.