SISTER OF TM3 activates FRUITFULL1 to regulate inflorescence branching in tomato

Selection for favorable inflorescence architecture to improve yield is one of the crucial targets in crop breeding. Different tomato varieties require distinct inflorescence-branching structures to enhance productivity. While a few important genes for tomato inflorescence-branching development have been identified, the regulatory mechanism underlying inflorescence branching is still unclear. Here, we confirmed that SISTER OF TM3 (STM3), a homolog of Arabidopsis SOC1, is a major positive regulatory factor of tomato inflorescence architecture by map-based cloning. High expression levels of STM3 underlie the highly inflorescence-branching phenotype in ST024. STM3 is expressed in both vegetative and reproductive meristematic tissues and in leaf primordia and leaves, indicative of its function in flowering time and inflorescence-branching development. Transcriptome analysis shows that several floral development-related genes are affected by STM3 mutation. Among them, FRUITFULL1 (FUL1) is downregulated in stm3cr mutants, and its promoter is bound by STM3 by ChIP-qPCR analysis. EMSA and dual-luciferase reporter assays further confirmed that STM3 could directly bind the promoter region to activate FUL1 expression. Mutation of FUL1 could partially restore inflorescence-branching phenotypes caused by high STM3 expression in ST024. Our findings provide insights into the molecular and genetic mechanisms underlying inflorescence development in tomato.

A Form-Finding Method for Branching Structures Based on Dynamic Relaxation

Branching structure is often used as a supporting structure of the grid shell due to its geometrical and force-transferring features, and the rationality of its shape is very important. The “physical” and “numerical” hanging models can be used for the joint form-finding of the branching structure and free-form grid shell. However, slack elements may exist in the equilibrium model which corresponds to the inefficient members in the form-found branching structure. To solve this problem, a form-finding method of branching structure based on dynamic relaxation is proposed in this study. The proposed method clusters the elements of the branching model and equalizes the axial forces of the elements in the same cluster, in other words, there are no slack elements in the equilibrium branching model. This method overcomes the defect that the equilibrium branching model may have slack elements and needs many manual adjustments during the procedure of determining the rational shape of a branching structure, and effectively prevents the inefficient members existing in the form-found structure. Numerical examples are provided to demonstrate the characteristics of the proposed method and its effectiveness is verified as well.

Credible Futures

This paper articulates in formal terms a crucial distinction concerning future contingents, the distinction between what is true about the future and what is reasonable to believe about the future. Its key idea is that the branching structures that have been used so far to model truth can be employed to define an epistemic property, credibility, which we take to be closely related to knowledge and assertibility, and which is ultimately reducible to probability. As a result, two kinds of claims about future contingents—one concerning truth, the other concerning credibility—can be smoothly handled within a single semantic framework.

Edible Mushrooms and Beta-Glucans: Impact on Human Health

Mushroom cell walls are rich in β-glucans, long or short-chain polymers of glucose subunits with β-1,3 and β-1,6 linkages, that are responsible for the linear and branching structures, respectively. β-glucans from cereals, at variance, have no 1,6 linkages nor branching structures. Both immunomodulatory and anti-inflammatory effects of mushrooms have been described using purified β-glucans or fungi extracts on cellular and experimental models; their potential clinical use has been tested in different conditions, such as recurrent infections of the respiratory tract or complications of major surgery. Another promising application of β-glucans is on cancer, as adjuvant of conventional chemotherapy. β-glucans may protect the cardiovascular system, ameliorating glucose, lipid metabolism, and blood pressure: these activities, observed for oat and barley β-glucans, require confirmation in human studies with mushroom β-glucans. On the other hand, mushrooms may also protect the cardiovascular system via a number of other components, such as bioactive phenolic compounds, vitamins, and mineral elements. The growing knowledge on the mechanism(s) and health benefits of mushrooms is encouraging the development of a potential clinical use of β-glucans, and also to further document their role in preserving health and prevent disease in the context of healthy lifestyles.

High-Resolution Remote Sensing Image Segmentation Framework Based on Attention Mechanism and Adaptive Weighting

Semantic segmentation has been widely used in the basic task of extracting information from images. Despite this progress, there are still two challenges: (1) it is difficult for a single-size receptive field to acquire sufficiently strong representational features, and (2) the traditional encoder-decoder structure directly integrates the shallow features with the deep features. However, due to the small number of network layers that shallow features pass through, the feature representation ability is weak, and noise information will be introduced to affect the segmentation performance. In this paper, an Adaptive Multi-Scale Module (AMSM) and Adaptive Fuse Module (AFM) are proposed to solve these two problems. AMSM adopts the idea of channel and spatial attention and adaptively fuses three-channel branches by setting branching structures with different void rates, and flexibly generates weights according to the content of the image. AFM uses deep feature maps to filter shallow feature maps and obtains the weight of deep and shallow feature maps to filter noise information in shallow feature maps effectively. Based on these two symmetrical modules, we have carried out extensive experiments. On the ISPRS Vaihingen dataset, the F1-score and Overall Accuracy (OA) reached 86.79% and 88.35%, respectively.

Testing methods of linguistic homeland detection using synthetic data

Two families of quantitative methods have been used to infer geographical homelands of language families: Bayesian phylogeography and the ‘diversity method'. Bayesian methods model how populations may have moved using a phylogenetic tree as a backbone, while the diversity method assumes that the geographical area where linguistic diversity is highest likely corresponds to the homeland. No systematic tests of the performances of the different methods in a linguistic context have so far been published. Here, we carry out performance testing by simulating language families, including branching structures and word lists, along with speaker populations moving in space. We test six different methods: two versions of BayesTraits; the relaxed random walk model of BEAST 2; our own RevBayes implementations of a fixed rate and a variable rates random walk model; and the diversity method. As a result of the tests, we propose a hierarchy of performance of the different methods. Factors such as geographical idiosyncrasies, incomplete sampling, tree imbalance and small family sizes all have a negative impact on performance, but mostly across the board, the performance hierarchy generally being impervious to such factors. This article is part of the theme issue ‘Reconstructing prehistoric languages'.

Connecting the Dots: Discovering the “Shape” of Data

Scientists use a mathematical subject called topology to study the shapes of objects. An important part of topology is counting the number of pieces and the number of holes in an object, and researchers use this information to group objects into different types. For example, a doughnut has the same number of holes and the same number of pieces as a teacup with one handle, but it is different from a ball. In studies that resemble activities like “connect-the-dots,” scientists use ideas from topology to study the “shape” of data. Ideas and methods from topology have been used to study the branching structures of veins in leaves, voting in elections, flight patterns in models of bird flocking, and more.