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Characterising intractable high-dimensional random variables is one of the fundamental challenges in stochastic computation. The recent surge of transport maps offers a mathematical foundation and new insights for tackling this challenge by coupling intractable random variables with tractable reference random variables. This paper generalises the functional tensor-train approximation of the inverse Rosenblatt transport recently developed by Dolgov et al. (Stat Comput 30:603-625, 2020) to a wide class of high-dimensional non-negative functions, such as unnormalised probability density functions. First, we extend the inverse Rosenblatt transform to enable the transport to general reference measures other than the uniform measure. We develop an efficient procedure to compute this transport from a squared tensor-train decomposition which preserves the monotonicity. More crucially, we integrate the proposed order-preserving functional tensor-train transport into a nested variable transformation framework inspired by the layered structure of deep neural networks. The resulting deep inverse Rosenblatt transport significantly expands the capability of tensor approximations and transport maps to random variables with complicated nonlinear interactions and concentrated density functions. We demonstrate the efficiency of the proposed approach on a range of applications in statistical learning and uncertainty quantification, including parameter estimation for dynamical systems and inverse problems constrained by partial differential equations., Author(s): Tiangang Cui [sup.1], Sergey Dolgov [sup.2] Author Affiliations: (1) grid.1002.3, 0000 0004 1936 7857, School of Mathematics, , 3800, Monash University, VIC, Australia (2) grid.7340.0, 0000 0001 2162 1699, [...]

The transformation protocol based on the dual selection approach (fluorescent protein and herbicide resistance) has been applied here to produce transgenic plants of two cereal species, emmer wheat and bread wheat, with the goal of activating the synthesis of the stress hormone jasmonates by overexpressing ALLENE OXIDE SYNTHASE from Arabidopsis thaliana (AtAOS) and bread wheat (TaAOS) and OXOPHYTODIENOATE REDUCTASE 3 from A. thaliana (AtOPR3) under the strong constitutive promoter (ZmUbi1), either individually or both genes simultaneously. The delivery of the expression cassette encoding AOS was found to affect morphogenesis in both wheat species negatively. The effect of transgene expression on the accumulation of individual jasmonates in hexaploid and tetraploid wheat was observed. Among the introduced genes, overexpression of TaAOS was the most successful in increasing stress-inducible phytohormone levels in transgenic plants, resulting in higher accumulations of JA and JA-Ile in emmer wheat and 12-OPDA in bread wheat. In general, overexpression of AOS, alone or together with AtOPR3, negatively affected leaf lamina length and grain numbers per spike in both wheat species. Double (AtAOS + AtOPR3) transgenic wheat plants were characterized by significantly reduced plant height and seed numbers, especially in emmer wheat, where several primary plants failed to produce seeds. [ABSTRACT FROM AUTHOR]

We present data on the ability for organogenesis in 22 genotypes of grapevine and developed a direct organogenesis protocol for the cultivar Podarok Magaracha and the rootstock Kober 5BB. The protocol does not require replacement of culture media and growth regulators, and the duration is 11 weeks. The cultivation of explants occurs on modified MS medium with the addition of 2.0 mg L−1 benzyladenine and indole-3-butyric acid (0.15 mg L−1 for the rootstock Kober 5BB or 0.05 mg L−1 for the cultivar Podarok Magaracha). The direct organogenesis protocol consists of three time periods: (1) culturing explants for 2 weeks in dark conditions for meristematic bulk tissue, (2) followed by 4 weeks of cultivation in light conditions for regeneration, and (3) 5 weeks of cultivation in dark conditions for shoot elongation. Based on this protocol, conditions for the Agrobacterium-mediated transformation of the Podarok Magaracha cultivar were developed with an efficiency of 2.0% transgenic plants per 100 explants. Two stably transformed lines with integration into the genome of the pBin35SGFP plasmid construction, confirmed by Southern blotting, were obtained. [ABSTRACT FROM AUTHOR]

WRKYs are a multigenic family of transcription factors that are plant-specific and involved in the regulation of plant development and various stress response processes. However, the evolution of WRKY genes is not fully understood. This family has also been incompletely studied in grapevine, and WRKY genes have been named with different numbers in different studies, leading to great confusion. In this work, 62 Vitis vinifera WRKY genes were identified based on six genomes of different cultivars. All WRKY genes were numbered according to their chromosomal location, and a complete revision of the numbering was performed. Amino acid variability between different cultivars was assessed for the first time and was greater than 5% for some WRKYs. According to the gene structure, all WRKYs could be divided into two groups: more exons/long length and fewer exons/short length. For the first time, some chimeric WRKY genes were found in grapevine, which may play a specific role in the regulation of different processes: VvWRKY17 (an N-terminal signal peptide region followed by a non-cytoplasmic domain) and VvWRKY61 (Frigida-like domain). Five phylogenetic clades A–E were revealed and correlated with the WRKY groups (I, II, III). The evolution of WRKY was studied, and we proposed a WRKY evolution model where there were two dynamic phases of complexity and simplification in the evolution of WRKY. [ABSTRACT FROM AUTHOR]

The genetic engineering of plants often relies on the use of antibiotic or herbicide resistance genes for the initial selection of primary transgenic events. Nevertheless, the commercial release of genetically modified crops containing any marker gene encounters several challenges stemming from the lack of consumer acceptance. The development of strategies enabling the generation of marker-free transgenic plants presents an alternative to address public concerns regarding the safety of biotech crops. This study examined the capabilities of highly regenerative potato cultivars to develop transgenic plants without the presence of selective substances in their media. Internodal segments of in vitro potato plants were inoculated with the Agrobacterium strain AGL0 carrying plasmids, which contained the GFP or RFP gene driven by the CaMV 35S promoter to monitor the transformation process by observing in vivo green or red fluorescence. Despite the absence of selective pressure, inoculated explants demonstrated comparable or even higher transient expression compared to experiments based on antibiotic assistant selection. Consequently, under non-selective conditions, non-transgenic, chimeric, and fully fluorescent potato plantlets were concurrently developed. Among the five tested cultivars, the regeneration efficiency of non-chimeric transgenic plants varied from 0.9 ('Chicago') to 2.7 (#12-36-42) plants per 100 detached plantlets. Depending on the regenerative characteristics of potato varieties (early, intermediate, or late), a specific time interval can be determined when a blind collection of transgenic plantlets is more successful, streamlining the transformation procedure. The results indicate that the outlined procedure is simple and reproducible, consistently achieving the transformation efficiency of 7.3–12.0% (per 100 inoculated explants) in potato cultivars without selective pressure. The described transformation procedure holds the potential for obtaining cisgenic or intragenic potato plants with new valuable traits that do not carry marker genes. [ABSTRACT FROM AUTHOR]

The tomato is a convenient object for studying reproductive processes, which has become a classic. Such complex processes as flowering and fruit setting require an understanding of the fundamental principles of molecular interaction, the structures of genes and proteins, the construction of signaling pathways for transcription regulation, including the synchronous actions of cis-regulatory elements (promoter and enhancer), trans-regulatory elements (transcription factors and regulatory RNAs), and transposable elements and epigenetic regulators (DNA methylation and acetylation, chromatin structure). Here, we discuss the current state of research on tomatoes (2017–2023) devoted to studying the function of genes that regulate flowering and signal regulation systems using genome-editing technologies, RNA interference gene silencing, and gene overexpression, including heterologous expression. Although the central candidate genes for these regulatory components have been identified, a complete picture of their relationship has yet to be formed. Therefore, this review summarizes the latest achievements related to studying the processes of flowering and fruit set. This work attempts to display the gene interaction scheme to better understand the events under consideration. [ABSTRACT FROM AUTHOR]

We propose a deep importance sampling method that is suitable for estimating rare event probabilities in high-dimensional problems. We approximate the optimal importance distribution in a general importance sampling problem as the pushforward of a reference distribution under a composition of order-preserving transformations, in which each transformation is formed by a squared tensor-train decomposition. The squared tensor-train decomposition provides a scalable ansatz for building order-preserving high-dimensional transformations via density approximations. The use of a composition of maps moving along a sequence of bridging densities alleviates the difficulty of directly approximating concentrated density functions. To compute expectations over unnormalized probability distributions, we design a ratio estimator that estimates the normalizing constant using a separate importance distribution, again constructed via a composition of transformations in tensor-train format. This offers better theoretical variance reduction compared to self-normalized importance sampling and thus opens the door to efficient computation of rare event probabilities in Bayesian inference problems. Numerical experiments on problems constrained by differential equations show little to no increase in the computational complexity of the estimator when the event probability goes to zero, enabling us to compute hitherto unattainable estimates of rare event probabilities for complex, high-dimensional posterior densities. [ABSTRACT FROM AUTHOR]

In light of recent climate change, with its rising temperatures and precipitation changes, we are facing the need to increase the valuable crop's tolerance against unfavorable environmental conditions. Emmer wheat is a cereal crop with high nutritional value. We investigated the possibility of improving the stress tolerance of emmer wheat by activating the synthesis of the stress hormone jasmonate by overexpressing two genes of the jasmonate biosynthetic pathway from Arabidopsis thaliana, ALLENE OXIDE SYNTHASE (AtAOS) and OXOPHYTODIENOATE REDUCTASE 3 (AtOPR3). Analyses of jasmonates in intact and mechanically wounded leaves of non-transgenic and transgenic plants showed that the overexpression of each of the two genes resulted in increased wounding-induced levels of jasmonic acid and jasmonate-isoleucine. Against all expectations, the overexpression of AtAOS, encoding a chloroplast-localized enzyme, does not lead to an increased level of the chloroplast-formed 12-oxo-phytodienoic acid (OPDA), suggesting an effective conversion of OPDA to downstream products in wounded emmer wheat leaves. Transgenic plants overexpressing AtAOS or AtOPR3 with increased jasmonate levels show a similar phenotype, manifested by shortening of the first and second leaves and elongation of the fourth leaf, as well as increased tolerance to osmotic stress induced by the presence of the polyethylene glycol (PEG) 6000. [ABSTRACT FROM AUTHOR]

A gradient-enhanced functional tensor train cross approximation method for the resolution of the Hamilton-Jacobi-Bellman (HJB) equations associated with optimal feedback control of nonlinear dynamics is presented. The procedure uses samples of both the solution of the HJB equation and its gradient to obtain a tensor train approximation of the value function. The collection of the data for the algorithm is based on two possible techniques: Pontryagin Maximum Principle and State-Dependent Riccati Equations. Several numerical tests are presented in low and high dimension showing the effectiveness of the proposed method and its robustness with respect to inexact data evaluations, provided by the gradient information. The resulting tensor train approximation paves the way towards fast synthesis of the control signal in real-time applications. [ABSTRACT FROM AUTHOR]

The removal of biogenic substances (mineral nitrogen and phosphorus) from river catchments and its modern aspects of formation are considered. A rough estimate of the annual water-biogenic balance for the Linda and Kudma river catchments, which are the tributaries of the Cheboksary reservoir, and the river catchments of the Kursk region is presented. It is shown that the diffuse removal of biogens from river catchments exceeds their removal into water bodies with wastewater. Not only anthropogenic, but also natural factors play an important role in the biogens export to the rivers and waterbodies. Resent changes in biogens removal from catchments are assessed.

12-Oxophytodienoate reductase is the enzyme involved in the biosynthesis of phytohormone jasmonates, which are considered to be the major regulators of plant tolerance to biotic challenges, especially necrotrophic pathogens. However, we observe compromised tolerance to the necrotrophic fungal pathogen Botrytis cinerea in transgenic hexaploid bread wheat and tetraploid emmer wheat plants overexpressing 12-OXOPHYTODIENOATE REDUCTASE-3 gene from Arabidopsis thaliana, while in Arabidopsis plants themselves, endogenously produced and exogenously applied jasmonates exert a strong protective effect against B. cinerea. Exogenous application of methyl jasmonate on hexaploid and tetraploid wheat leaves suppresses tolerance to B. cinerea and induces the formation of chlorotic damages. Exogenous treatment with methyl jasmonate in concentrations of 100 µM and higher causes leaf yellowing even in the absence of the pathogen, in agreement with findings on the role of jasmonates in the regulation of leaf senescence. Thereby, the present study demonstrates the negative role of the jasmonate system in hexaploid and tetraploid wheat tolerance to B. cinerea and reveals previously unknown jasmonate-mediated responses. [ABSTRACT FROM AUTHOR]

This article develops a new algorithm named TTRISK to solve high‐dimensional risk‐averse optimization problems governed by differential equations (ODEs and/or partial differential equations [PDEs]) under uncertainty. As an example, we focus on the so‐called Conditional Value at Risk (CVaR), but the approach is equally applicable to other coherent risk measures. Both the full and reduced space formulations are considered. The algorithm is based on low rank tensor approximations of random fields discretized using stochastic collocation. To avoid nonsmoothness of the objective function underpinning the CVaR, we propose an adaptive strategy to select the width parameter of the smoothed CVaR to balance the smoothing and tensor approximation errors. Moreover, unbiased Monte Carlo CVaR estimate can be computed by using the smoothed CVaR as a control variate. To accelerate the computations, we introduce an efficient preconditioner for the Karush–Kuhn–Tucker (KKT) system in the full space formulation.The numerical experiments demonstrate that the proposed method enables accurate CVaR optimization constrained by large‐scale discretized systems. In particular, the first example consists of an elliptic PDE with random coefficients as constraints. The second example is motivated by a realistic application to devise a lockdown plan for United Kingdom under COVID‐19. The results indicate that the risk‐averse framework is feasible with the tensor approximations under tens of random variables. [ABSTRACT FROM AUTHOR]