The transcription factors, STOP1 and TCP20, are required for root system architecture alterations in response to nitrate deficiency

Nitrate distribution in soils is often heterogeneous. Plants have adapted to this by modifying their root system architecture (RSA). Previous studies showed that NITRATE-TRANSPORTER1.1 (NRT1.1), which also transports auxin, helps inhibit lateral root primordia (LRP) emergence in nitrate-poor patches, by preferentially transporting auxin away from the LRP. In this study, we identified the regulatory system for this response involving the transcription factor (TF), SENSITIVE-TO-PROTON-RHIZOTOXICITY1 (STOP1), which is accumulated in the nuclei of LRP cells under nitrate deficiency and directly regulates Arabidopsis NRT1.1 expression. Mutations in STOP1 mimic the root phenotype of the loss-of-function NRT1.1 mutant under nitrate deficiency, compared to wild-type plants, including increased LR growth and higher DR5promoter activity (i.e., higher LRP auxin signaling/activity). Nitrate deficiency-induced LR growth inhibition was almost completely reversed when STOP1 and the TF, TEOSINTE-BRANCHED1,-CYCLOIDEA,-PCF-DOMAIN-FAMILY-PROTEIN20 (TCP20), a known activator of NRT1.1 expression, were both mutated. Thus, the STOP1-TCP20 system is required for activation of NRT1.1 expression under nitrate deficiency, leading to reduced LR growth in nitrate-poor regions. We found this STOP1-mediated system is more active as growth media becomes more acidic, which correlates with reductions in soil nitrate as the soil pH becomes more acidic. STOP1 has been shown to be involved in RSA modifications in response to phosphate deficiency and increased potassium uptake, hence, our findings indicate that root growth regulation in response to low availability of the major fertilizer nutrients, nitrogen, phosphorus and potassium, all involve STOP1, which may allow plants to maintain appropriate root growth under the complex and varying soil distribution of nutrients.

High affinity promoter binding of STOP1 is essential for early expression of novel aluminum-induced resistance genes GDH1 and GDH2 in Arabidopsis

Malate efflux from roots, which is regulated by the transcription factor STOP1 (SENSITIVE-TO-PROTON-RHIZOTOXICITY1) and mediates aluminum-induced expression of ALUMINUM-ACTIVATED-MALATE-TRANSPORTER1 (AtALMT1), is critical for aluminum resistance in Arabidopsis thaliana. Several studies showed that AtALMT1 expression in roots is rapidly observed in response to aluminum; this early induction is an important mechanism to immediately protect roots from aluminum toxicity. Identifying the molecular mechanisms that underlie rapid aluminum resistance responses should lead to a better understanding of plant aluminum sensing and signal transduction mechanisms. In this study, we observed that GFP-tagged STOP1 proteins accumulated in the nucleus soon after aluminum treatment. The rapid aluminum-induced STOP1-nuclear localization and AtALMT1 induction were detected in the presence of a protein synthesis inhibitor, suggesting that post-translational regulation is involved in these events. STOP1 also regulated rapid aluminum-induced expression for other genes that carry a functional/high-affinity STOP1-binding site in their promoter, including STOP2, GLUTAMATE-DEHYDROGENASE1 and 2 (GDH1 and 2). However STOP1 did not regulate Al resistance genes which have no functional STOP1-binding site such as ALUMINUM-SENSITIVE3, suggesting that the binding of STOP1 in the promoter is essential for early induction. Finally, we report that GDH1 and 2 which are targets of STOP1, are novel aluminum-resistance genes in Arabidopsis.

Data-Driven Computational Simulation in Bone Mechanics

The data-driven approach was formally introduced in the field of computational mechanics just a few years ago, but it has gained increasing interest and application as disruptive technology in many other fields of physics and engineering. Although the fundamental bases of the method have been already settled, there are still many challenges to solve, which are often inherently linked to the problem at hand. In this paper, the data-driven methodology is applied to a particular problem in tissue biomechanics, a context where this approach is particularly suitable due to the difficulty in establishing accurate and general constitutive models, due to the intrinsic intra and inter-individual variability of the microstructure and associated mechanical properties of biological tissues. The problem addressed here corresponds to the characterization and mechanical simulation of a piece of cortical bone tissue. Cortical horse bone tissue was mechanically tested using a biaxial machine. The displacement field was obtained by means of digital image correlation and then transformed into strains by approximating the displacement derivatives in the bone virtual geometric image. These results, together with the approximated stress state, assumed as uniform in the small pieces tested, were used as input in the flowchart of the data-driven methodology to solve several numerical examples, which were compared with the corresponding classical model-based fitted solution. From these results, we conclude that the data-driven methodology is a useful tool to directly simulate problems of biomechanical interest without the imposition (model-free) of complex spatial and individually-varying constitutive laws. The presented data-driven approach recovers the natural spatial variation of the solution, resulting from the complex structure of bone tissue, i.e. heterogeneity, microstructural hierarchy and multifactorial architecture, making it possible to add the intrinsic stochasticity of biological tissues into the data set and into the numerical approach.

Biomechanical design of less invasive stabilization system femoral plates: computational evaluation of the fracture environment

Less Invasive Stabilization System femoral plates are currently accepted as a suitable fixation technique for supra-intercondylar femoral fractures. However, general agreement does not exist regarding the optimum design of this fixator type. Therefore, the aim of this article is to reduce the intrinsic Less Invasive Stabilization System complications by clarifying, from a biomechanical point of view, how the number of screws, the screw connection type (unicortical or bicortical), or the structured position of the screws can influence the outcome of the fracture site. These studies include a specific finite element analysis that determines how several biomechanical variables, such as the movement at the fracture site, are influenced by the preconditions of bone healing. The results of this study show that the screw type affects the mechanical stabilization of the femur to a greater extent than the material type of the Less Invasive Stabilization System femoral plates. The most significant differences among all the analyzed configurations are observed in the shear interfragmentary strain between screw types. Values are approximately 50% higher with unicortical screws than with bicortical ones.