Corrigendum: Single nucleotide polymorphisms of porcine lncMGPF regulate meat production traits by affecting RNA stability.

[This corrects the article DOI: 10.3389/fcell.2021.

SYISL Knockout Promotes Embryonic Muscle Development of Offspring by Modulating Maternal Gut Microbiota and Fetal Myogenic Cell Dynamics.

Embryonic muscle fiber formation determines post-birth muscle fiber totals. The previous research shows SYISL knockout significantly increases muscle fiber numbers and mass in mice, but the mechanism remains unclear. This study confirms that the SYISL gene, maternal gut microbiota, and their interaction significantly affect the number of muscle fibers in mouse embryos through distinct mechanisms, as SYISL knockout alters maternal gut microbiota composition and boosts butyrate levels in embryonic serum.

Functional SNPs in SYISL promoter significantly affect muscle fiber density and muscle traits in pigs.

Our previous studies showed that SYISL is a negative regulator of muscle growth and regeneration in mice, pigs and humans. SYISL knockout resulted in an increase in the density of muscle fibers and muscle growth. However, it is unclear whether there are natural mutations in pig SYNPO2 intron sense-overlapping lncRNA (pSYISL) that affect the expression of pSYISL and muscle growth traits.

Efficient Robust Watermarking Based on Structure-Preserving Quaternion Singular Value Decomposition.

Quaternion singular value decomposition (QSVD) is a robust technique of digital watermarking that extracts high quality watermarks from watermarked images with low distortion. However, the existing QSVD-based watermarking schemes face the obstacle of "explosion of complexity" and have much room for improvement in terms of real-time, invisibility, and robustness. In this paper, we overcome such obstacle by introducing a new real structure-preserving QSVD algorithm and propose a novel QSVD-based watermarking scheme with high efficiency.

Distributional generative adversarial imitation learning with reproducing kernel generalization.

Generative adversarial imitation learning (GAIL) regards imitation learning (IL) as a distribution matching problem between the state-action distributions of the expert policy and the learned policy. In this paper, we focus on the generalization and computational properties of policy classes. We prove that the generalization can be guaranteed in GAIL when the class of policies is well controlled.

FHL3 promotes the formation of fast glycolytic muscle fibers by interacting with YY1 and muscle glycolytic metabolism.

The proportions of the various muscle fiber types are important in the regulation of skeletal muscle metabolism, as well as animal meat production. Four-and-a-half LIM domain protein 3 (FHL3) is highly expressed in fast glycolytic muscle fibers and differentially regulates the expression of myosin heavy chain (MyHC) isoforms at the cellular level. Whether FHL3 regulates the transformation of muscle fiber types in vivo and the regulatory mechanism is unclear.

Long noncoding RNA lncMREF promotes myogenic differentiation and muscle regeneration by interacting with the Smarca5/p300 complex.

Long noncoding RNAs (lncRNAs) play important roles in the spatial and temporal regulation of muscle development and regeneration. Nevertheless, the determination of their biological functions and mechanisms underlying muscle regeneration remains challenging. Here, we identified a lncRNA named lncMREF (lncRNA muscle regeneration enhancement factor) as a conserved positive regulator of muscle regeneration among mice, pigs and humans.

Conservative analysis of Synaptopodin-2 intron sense-overlapping lncRNA reveals its novel function in promoting muscle atrophy.

Background: Dissection of the regulatory pathways that control skeletal muscle development and atrophy is important for the treatment of muscle wasting. Long noncoding RNA (lncRNA) play important roles in various stages of muscle development. We previously reported that Synaptopodin-2 (SYNPO2) intron sense-overlapping lncRNA (SYISL) regulates myogenesis through an interaction with enhancer of zeste homologue 2 (EZH2).

SAB Net: A Semantic Attention Boosting Framework for Semantic Segmentation.

Semantic segmentation has achieved great progress by effectively fusing features of contextual information. In this article, we propose an end-to-end semantic attention boosting (SAB) framework to adaptively fuse the contextual information iteratively across layers with semantic regularization. Specifically, we first propose a pixelwise semantic attention (SAP) block, with a semantic metric representing the pixelwise category relationship, to aggregate the nonlocal contextual information.

Targeted overexpression of PPARγ in skeletal muscle by random insertion and CRISPR/Cas9 transgenic pig cloning enhances oxidative fiber formation and intramuscular fat deposition.

Peroxisome proliferator-activated receptor gamma (PPARγ) is a master regulator of adipogenesis and lipogenesis. To understand its roles in fiber formation and fat deposition in skeletal muscle, we successfully generated muscle-specific overexpression of PPARγ in two pig models by random insertion and CRISPR/Cas9 transgenic cloning procedures. The content of intramuscular fat was significantly increased in PPARγ pigs while had no changes on lean meat ratio.

Lipidomic analyses reveal enhanced lipolysis in planthoppers feeding on resistant host plants.

The brown planthopper (BPH) (Nilaparvata lugens Stål) is a highly destructive pest that seriously damages rice (Oryza sativa L.) and causes severe yield losses. To better understand the physiological and metabolic mechanisms through which BPHs respond to resistant rice, we combined mass-spectrometry-based lipidomics with transcriptomic analysis and gene knockdown techniques to compare the lipidomes of BPHs feeding on either of the two resistant (NIL-Bph6 and NIL-Bph9) plants or a wild-type, BPH susceptible (9311) plant.

Salivary Protein 1 of Brown Planthopper Is Required for Survival and Induces Immunity Response in Plants.

The brown planthopper (BPH), Stål, is one of the major pests of rice. It uses its stylet to penetrate rice phloem, feeding on rice sap and causing direct damage to rice or even plant death. During the feeding process, BPHs secrete saliva into plant tissues, which plays crucial roles in the plant-insect interactions.

CAB U-Net: An end-to-end category attention boosting algorithm for segmentation.

With the development of machine learning and artificial intelligence, many convolutional neural networks (CNNs) based segmentation methods have been proposed for 3D cardiac segmentation. In this paper, we propose the category attention boosting (CAB) module, which combines the deep network calculation graph with the boosting method. On the one hand, we add the attention mechanism into the gradient boosting process, which enhances the information of coarse segmentation without high computation cost.

Large-Scale Place Recognition Based on Camera-LiDAR Fused Descriptor.

In the field of autonomous driving, carriers are equipped with a variety of sensors, including cameras and LiDARs. However, the camera suffers from problems of illumination and occlusion, and the LiDAR encounters motion distortion, degenerate environment and limited ranging distance. Therefore, fusing the information from these two sensors deserves to be explored.

Nonlinear Semi-Supervised Metric Learning Via Multiple Kernels and Local Topology.

Changing the metric on the data may change the data distribution, hence a good distance metric can promote the performance of learning algorithm. In this paper, we address the semi-supervised distance metric learning (ML) problem to obtain the best nonlinear metric for the data. First, we describe the nonlinear metric by the multiple kernel representation.

Manifold Preserving: An Intrinsic Approach for Semisupervised Distance Metric Learning.

In this paper, we address the semisupervised distance metric learning problem and its applications in classification and image retrieval. First, we formulate a semisupervised distance metric learning model by considering the metric information of inner classes and interclasses. In this model, an adaptive parameter is designed to balance the inner metrics and intermetrics by using data structure.

Nonlinear image registration with bidirectional metric and reciprocal regularization.

Nonlinear registration is an important technique to align two different images and widely applied in medical image analysis. In this paper, we develop a novel nonlinear registration framework based on the diffeomorphic demons, where a reciprocal regularizer is introduced to assume that the deformation between two images is an exact diffeomorphism. In detail, first, we adopt a bidirectional metric to improve the symmetry of the energy functional, whose variables are two reciprocal deformations.