Water fluxes pattern growth and identity in shoot meristems.

In multicellular organisms, tissue outgrowth creates a new water sink, modifying local hydraulic patterns. Although water fluxes are often considered passive by-products of development, their contribution to morphogenesis remains largely unexplored. Here, we mapped cell volumetric growth across the shoot apex in Arabidopsis thaliana.

A quantitative gibberellin signaling biosensor reveals a role for gibberellins in internode specification at the shoot apical meristem.

Growth at the shoot apical meristem (SAM) is essential for shoot architecture construction. The phytohormones gibberellins (GA) play a pivotal role in coordinating plant growth, but their role in the SAM remains mostly unknown. Here, we developed a ratiometric GA signaling biosensor by engineering one of the DELLA proteins, to suppress its master regulatory function in GA transcriptional responses while preserving its degradation upon GA sensing.

bHLH heterodimer complex variations regulate cell proliferation activity in the meristems of .

Root, shoot, and lateral meristems are the main regions of cell proliferation in plants. It has been proposed that meristems might have evolved dedicated transcriptional networks to balance cell proliferation. Here, we show that basic helix-loop-helix (bHLH) transcription factor heterodimers formed by members of the TARGET OF MONOPTEROS5 (TMO5) and LONESOME HIGHWAY (LHW) subclades are general regulators of cell proliferation in all meristems.

Benchmarking of deep learning algorithms for 3D instance segmentation of confocal image datasets.

Segmenting three-dimensional (3D) microscopy images is essential for understanding phenomena like morphogenesis, cell division, cellular growth, and genetic expression patterns. Recently, deep learning (DL) pipelines have been developed, which claim to provide high accuracy segmentation of cellular images and are increasingly considered as the state of the art for image segmentation problems. However, it remains difficult to define their relative performances as the concurrent diversity and lack of uniform evaluation strategies makes it difficult to know how their results compare.

Temporal integration of auxin information for the regulation of patterning.

Positional information is essential for coordinating the development of multicellular organisms. In plants, positional information provided by the hormone auxin regulates rhythmic organ production at the shoot apex, but the spatio-temporal dynamics of auxin gradients is unknown. We used quantitative imaging to demonstrate that auxin carries high-definition graded information not only in space but also in time.

An Image Analysis Pipeline to Quantify Emerging Cracks in Materials or Adhesion Defects in Living Tissues.

Microcracks in materials reflect their mechanical properties. The quantification of the number or orientation of such cracks is thus essential in many fields, including engineering and geology. In biology, cracks in soft tissues can reflect adhesion defects, and the analysis of their pattern can help to deduce the magnitude and orientation of tensions in organs and tissues.

DRACO-STEM: An Automatic Tool to Generate High-Quality 3D Meshes of Shoot Apical Meristem Tissue at Cell Resolution.

The shoot apical meristem (SAM), origin of all aerial organs of the plant, is a restricted niche of stem cells whose growth is regulated by a complex network of genetic, hormonal and mechanical interactions. Studying the development of this area at cell level using 3D microscopy time-lapse imaging is a newly emerging key to understand the processes controlling plant morphogenesis. Computational models have been proposed to simulate those mechanisms, however their validation on real-life data is an essential step that requires an adequate representation of the growing tissue to be carried out.

Tree leaves extraction in natural images: comparative study of preprocessing tools and segmentation methods.

In this paper, we propose a comparative study of various segmentation methods applied to the extraction of tree leaves from natural images. This study follows the design of a mobile application, developed by Cerutti et al. (published in ReVeS Participation--Tree Species Classification Using Random Forests and Botanical Features.