DPIF-Net: a dual path network for rural road extraction based on the fusion of global and local information.

Background: Automatic extraction of roads from remote sensing images can facilitate many practical applications. However, thus far, thousands of kilometers or more of roads worldwide have not been recorded, especially low-grade roads in rural areas. Moreover, rural roads have different shapes and are influenced by complex environments and other interference factors, which has led to a scarcity of dedicated low level category road datasets. Methods: To address these issues, based on convolutional neural networks (CNNs) and tranformers, this article proposes the Dual Path Information Fusion Network (DPIF-Net). In addition, given the severe lack of low-grade road datasets, we constructed the GaoFen-2 (GF-2) rural road dataset to address this challenge, which spans three regions in China and covers an area of over 2,300 km, almost entirely composed of low-grade roads. To comprehensively test the low-grade road extraction performance and generalization ability of the model, comparative experiments are carried out on the DeepGlobe, and Massachusetts regular road datasets. Results: The results show that DPIF-Net achieves the highest IoU and F1 score on three datasets compared with methods such as U-Net, SegNet, DeepLabv3+, and D-LinkNet, with notable performance on the GF-2 dataset, reaching 0.6104 and 0.7608, respectively. Furthermore, multiple validation experiments demonstrate that DPIF-Net effectively preserves improved connectivity in low-grade road extraction with a modest parameter count of 63.9 MB. The constructed low-grade road dataset and proposed methods will facilitate further research on rural roads, which holds promise for assisting governmental authorities in making informed decisions and strategies to enhance rural road infrastructure.

GROWTH REGULATING FACTOR 7-mediated arbutin metabolism enhances rice salt tolerance.

Salt stress is an environmental factor that limits plant growth and crop production. With the rapid expansion of salinized arable land worldwide, investigating the molecular mechanisms underlying the salt stress response in plants is urgently needed. Here, we report that GROWTH REGULATING FACTOR 7 (OsGRF7) promotes salt tolerance by regulating arbutin (hydroquinone-ß-D-glucopyranoside) metabolism in rice (Oryza sativa). Overexpression of OsGRF7 increased arbutin content, and exogenous arbutin application rescued the salt-sensitive phenotype of OsGRF7 knockdown and knockout plants. OsGRF7 directly promoted the expression of the arbutin biosynthesis genes URIDINE DIPHOSPHATE GLYCOSYLTRANSFERASE 1 (OsUGT1) and OsUGT5, and knockout of OsUGT1 or OsUGT5 reduced rice arbutin content, salt tolerance, and grain size. Furthermore, OsGRF7 degradation through its interaction with F-BOX AND OTHER DOMAINS CONTAINING PROTEIN 13 (OsFBO13) reduced rice salinity tolerance and grain size. These findings highlight an underexplored role of OsGRF7 in modulating rice arbutin metabolism, salt stress response, and grain size, as well as its broad potential use in rice breeding.

Three-Dimensional Chiral Morphogenesis of Active Fluids.

Chirality is an essential nature of biological systems. However, it remains obscure how the handedness at the microscale is translated into chiral morphogenesis at the tissue level. Here, we investigate three-dimensional (3D) tissue morphogenesis using an active fluid theory invoking chirality. We show that the coordination of achiral and chiral stresses, arising from microscopic interactions and energy input of individual cells, can engender the self-organization of 3D papillary and helical structures. The achiral active stress drives the nucleation of asterlike topological defects, which initiate 3D out-of-plane budding, followed by rodlike elongation. The chiral active stress excites vortexlike topological defects, which favor the tip spheroidization and twisting of the elongated rod. These results unravel the chiral morphogenesis observed in our experiments of 3D organoids generated by human embryonic stem cells.

RPL22L1, a novel candidate oncogene promotes temozolomide resistance by activating STAT3 in glioblastoma.

Aggressiveness and drug resistance are major challenges in the clinical treatment of glioblastoma (GBM). Our previously research reported a novel candidate oncogene ribosomal protein L22 like 1 (RPL22L1). The aim of this study was to elucidate the potential role and mechanism of RPL22L1 in progression and temozolomide (TMZ) resistance of GBM. Online database, tissue microarrays and clinical tissue specimens were used to evaluate the expression and clinical implication of RPL22L1 in GBM. We performed cell function assays, orthotopic and subcutaneous xenograft tumor models to evaluate the effects and molecular mechanisms of RPL22L1 on GBM. RPL22L1 expression was significantly upregulated in GBM and associated with poorer prognosis. RPL22L1 overexpression enhanced GBM cell proliferation, migration, invasion, TMZ resistance and tumorigenicity, which could be reduced by RPL22L1 knockdown. Further, we found RPL22L1 promoted mesenchymal phenotype of GBM and the impact of these effects was closely related to EGFR/STAT3 pathway. Importantly, we observed that STAT3 specific inhibitor (Stattic) significantly inhibited the malignant functions of RPL22L1, especially on TMZ resistance. RPL22L1 overexpressed increased combination drug sensitive of Stattic and TMZ both in vitro and in vivo. Moreover, Stattic effectively restored the sensitive of RPL22L1 induced TMZ resistance in vitro and in vivo. Our study identified a novel candidate oncogene RPL22L1 which promoted the GBM malignancy through STAT3 pathway. And we highlighted that Stattic combined with TMZ therapy might be an effective treatment strategy in RPL22L1 high-expressed GBM patients.

Substrate nesting guides cyst morphogenesis of human pluripotent stem cells without 3D extracellular matrix overlay.

Understanding the principles underlying the self-organization of stem cells into tissues is fundamental for deciphering human embryo development. Here, we report that, without three-dimensional (3D) extracellular matrix (ECM) overlay, human pluripotent stem cells (hPSCs) cultured on two-dimensional soft elastic substrates can self-organize into 3D cysts resembling the human epiblast sac in a stiffness-dependent manner. Our theoretical modeling predicts that this cyst organization is facilitated and guided by the spontaneous nesting of the soft substrate, which results from the adhesion-dependent mechanical interaction between cells and substrate. Such substrate nesting is sufficient for the 3D assembly and polarization of hPSCs required for cyst organization, even without 3D ECM overlay. Furthermore, we identify that the reversible substrate nesting and cyst morphogenesis also require appropriate activation of ROCK-Myosin II pathway. This indicates a unique set of tissue morphomechanical signaling mechanisms that clearly differ from the canonical cystogenic mechanism previously reported in 3D ECM. Our findings highlight an unanticipated synergy between mechanical microenvironment and mechanotransduction in controlling tissue morphogenesis and suggest a mechanics-based strategy for generation of hPSCs-derived models for early human embryogenesis. STATEMENT OF SIGNIFICANCE: Soft substrates can induce the self-organization of human pluripotent stem cells (hPSCs) into cysts without three-dimensional (3D) extracellular matrix (ECM) overlay. However, the underlying mechanisms by which soft substrate guides cystogenesis are largely unknown. This study shows that substrate nesting, resulting from cell-substrate interaction, plays an important role in cyst organization, including 3D assembly and apical-basal polarization. Additionally, actomyosin contractility mediated by the ROCK-Myosin II pathway also contributes to the substrate deformation and cyst morphology. These findings demonstrate the interplay between the mechanical microenvironment and cells in tissue morphogenesis, suggesting a mechanics-based strategy in building hPSC-derived models for early human embryo development.

A Preliminary Study on Sympathetic Skin Response in Acute Ischemic Cerebrovascular Disease.

Purpose: The study aims to identify the characteristics of SSR in patients with AICVD and their correlation with clinical presentations. Methods: SSR of the upper limbs, the National Institute of Health stroke scale (NIHSS), the Barthel index (BI), the Essen stroke risk score (ESRS), and imaging examinations, was evaluated in 30 healthy subjects and 66 patients with AICVD. All results were recorded and analyzed via Statistical Package for the Social Sciences (SPSS 22.0) software. t-test and Spearman rank correlation were used. Results: Compared to the control group, SSR of upper limbs in patients with AICVD showed prolonged latency, reduced amplitude, and disappeared waveform (p=0.000, p=0.015, p=0.004), No statistically significant difference was observed between the affected side and the healthy side (p=0.068, p=0.661). In the case group, the higher the abnormal rate of SSR, the more severe the neurological impairment (NIHSS and ADL scores) and the worse the long-term prognosis. Specific results are as follows: Firstly, the total abnormality rate of SSR, prolonged SSR latency were positively related to the NIHSS, also the ESRS (r=0.347, p=0.004; r=0.437, p<0.001), (r=0.371, p=0.005; r=0.433, p=0.001), the reduced amplitude was positively related to the NIHSS (r=0.341, p=0.012) while the disappeared waveform was positively related to the ESRS (r=0.299, p=0.015); Secondly, the total abnormality rate of SSR, prolonged SSR latency and reduced amplitude were negatively related to the BI (r=-0.346, p=0.004) (r=-0.426, p=0.001) (r=-0.316, p=0.020). Conclusion: There may be inhibition of sympathetic reflex activity in patients with AICVD, SSR abnormality rate in patients with AICVD may be correlated with the degree of neurological impairment and long-term prognosis.

Selective kernel convolution deep residual network based on channel-spatial attention mechanism and feature fusion for mechanical fault diagnosis.

This paper proposes a selective kernel convolution deep residual network based on the channel-spatial attention mechanism and feature fusion for mechanical fault diagnosis. First, adjacent channel attention modules are connected with the spatial attention mechanism module, then all channel features and spatial features are fused and a channel-spatial attention mechanism is constructed to form the feature enhancement module. Second, the feature enhancement module is embedded in a series model based on selective kernel convolution and deep residual network and combined with multi-layer feature fusion information. The model can more effectively extract fault features from the vibration signal, compared with traditional deep learning methods, and the fault recognition efficiency is improved. Finally, the proposed method was used to experimentally diagnose bearing and gear faults, and identification accuracies of 99.87% and 97.77%, respectively, were achieved. Compared with similar algorithms, the proposed method has higher fault identification ability, thereby demonstrating the advantages of the channel-spatial attention mechanism network. In addition, the accuracy and robustness of the model were verified.

A three-player game model for promoting enterprise green technology innovation from the perspective of media coverage.

Objective: The objective of this study was to explore the game relationship among enterprise, the government, and the public under the new media environment, so as to provide decision-making reference for improving enterprise green technology innovation and promoting economy high-quality development with new media participation. Methods: This study constructs a three-subject evolutionary game model of enterprise, government, and public based on multi-agent relationship analysis and evolutionary game theory. In addition, the derivation of an evolutionary equilibrium strategy and numerical simulation analysis is carried out to comprehensively explore the evolution trajectory of green technology innovation system under the new media environment. Findings: (1) The system may have four stable evolutionary strategies: (1,0,0), (0,0,1), (1,0,1), and (1,1,1). (2) The initial strategy probability of various actors would affect the system evolution speed but not the evolution result, and the authenticity of new media reports is an important factor determining the system evolution of green technology innovation. (3) Numerical simulation results show that a fair and just new media environment can effectively constrain the traditional production behavior of enterprise, actively guide the public to participate in supervision, and play an alternative role to government regulation to a certain extent. Value: This study explores the evolutionary balance strategy of green technology innovation system under the new media environment, which not only enriches relevant theories of media environment governance but also has important reference value for promoting enterprises' green technology innovation and establishing an environmental governance system jointly governed by government, enterprise, public, and media.

A Novel Defined RAS-Related Gene Signature for Predicting the Prognosis and Characterization of Biological Function in Osteosarcoma.

Background: Osteosarcoma (OS) is the most common primary bone malignancy in children and adolescents with a high incidence and poor prognosis. Activation of the RAS pathway promotes progression and metastasis of osteosarcoma. RAS has been studied in many different tumors; however, the prognostic value of RAS-associated genes in OS remains unclear. On this basis, we investigated the RAS-related gene signature and explored the intrinsic biological features of OS. Methods: We obtained RNA transcriptome sequencing data and clinical information of osteosarcoma patients from the TARGET database. RAS pathway-related genes were obtained from the KEGG pathway database. Molecular subgroups and risk models were developed using consensus clustering and least absolute shrinkage and selection operator (LASSO) regression, respectively. ESTIMATE algorithm and ssGSEA analysis were used to assess the tumor microenvironment and immune penetrance between the two groups. A comprehensive review of gene ontology (GO) and KEGG analyses revealed inherent biological functional differences between the two groups. Results: The consistent clustering showed stratification of osteosarcoma patients into two subtypes based on RAS-associated genes and provided a robust prediction of prognosis. A risk model further confirmed that RAS-related genes are the best prognostic indicators for OS patients. GO analysis showed that GDP/GTP binding, focal adhesion, cytoskeletal motor activity, and cell-matrix junctions were associated with the RAS-related model group. Furthermore, RAS signaling in osteosarcoma based on KEGG analysis was significantly associated with cancer progression, with immune function and tumor microenvironment particularly affected. Conclusion: We constructed a prognostic model founded on RAS-related gene and demonstrated its predictive ability. Then, furtherly exploration of the molecular mechanisms and immune characteristics proved the role of RAS-related gene in the dysregulation in OS.

Measuring Endogenous GA and IAA.

Plant hormones regulate many physiological processes that largely influence growth, differentiation, and development. Contents of phytohormones were analyzed using a liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) system. This protocol describes a detailed procedure to extract and quantify indole-3-acetic acid (IAA) and gibberellin acid (GA) in rice (Oryza sativa) tissues using high-performance liquid chromatography (HPLC)-based method.

Stem Cell-Based Embryo Models: En Route to a Programmable Future.

Early-stage human embryogenesis, such as implantation, gastrulation, and neurulation, are critical for successful pregnancy. For decades, our knowledge about these stages has been limited by the inaccessibility to such embryo specimens in vivo and the difficulty in rebuilding them in vitro. Although human embryos could be cultured in vitro beyond implantation, it remains challenging for the cultured embryos to recapitulate the continuous, coordinated morphogenesis and cytodifferentiation as seen in vivo. Stem cell-based embryo models, mainly derived from human pluripotent stem cells, are organized structures mimicking essential developmental processes in the early-stage human embryos. Despite their invaluable potentials, most embryo models are based on the self-organization of human pluripotent stem cells, which are limited in controllability, reproducibility, and developmental fidelity. Recently, the integration of bioengineered tools and stem cell biology has fueled a technological transformation towards programmable, highly complex, high-fidelity stem cell-based embryo models. Given its scientific and clinical significance, we present an overview of recent paradigm-shifting advances as well as historical perspectives regarding the past, present, and future of synthetic human embryology. Following the developmental roadmap of human embryogenesis, we critically review existing stem cell-based models for implantation, gastrulation, and neurulation, respectively. We highlight the limitations encountered by autonomous self-organization strategy and discuss the concept and application of guided cell organization as a game-changer for innovating next-generation embryo models. Future endeavors in synthetic human embryology should rationally leverage both the self-organizing power and programmable microenvironmental guidance to secure faithful reconstructions of the hierarchical orders of human embryogenesis in vitro.

Genic male sterility increases rice drought tolerance.

Plant fertility and resistance to stress environments are antagonistic to each other. At booting stage, fertility is often sacrificed for survive in rice under abiotic stress. However, the relationship between fertility and resistance at molecular level remains elusive. Here, we identified a transcription factor, OsAlfin like 5, which regulates the OsTMS5 and links both the drought stress response and thermosensitive genic male sterility. The OsAL5 overexpression plants (OE-OsAL5) became sensitive to temperature owning to the OsTMS5 that the OE-OsAL5 plants were fertile under low temperature (23 °C) and sterile under high temperature (28 °C). Significantly, the survival rate of OE-OsAL5 lines was higher than that of the wide-type (WT) under drought stress. Further experiments confirmed that the OsAL5 regulated both of the OsTMS5 and the down-stream drought-related genes by binding to the 'GTGGAG' element in vivo, revealing that the OsAL5 participated both in the drought stress response and thermosensitive genic male sterility in rice. These findings open up the possibility of breeding elite TGMS lines with strong drought tolerance by manipulating the expression of OsAL5.

The metabolomic landscape of rice heterosis highlights pathway biomarkers for predicting complex phenotypes.

Understanding the molecular mechanisms underlying complex phenotypes requires systematic analyses of complicated metabolic networks and contributes to improvements in the breeding efficiency of staple cereal crops and diagnostic accuracy for human diseases. Here, we selected rice (Oryza sativa) heterosis as a complex phenotype and investigated the mechanisms of both vegetative and reproductive traits using an untargeted metabolomics strategy. Heterosis-associated analytes were identified, and the overlapping analytes were shown to underlie the association patterns for six agronomic traits. The heterosis-associated analytes of four yield components and plant height collectively contributed to yield heterosis, and the degree of contribution differed among the five traits. We performed dysregulated network analyses of the high- and low-better parent heterosis hybrids and found multiple types of metabolic pathways involved in heterosis. The metabolite levels of the significantly enriched pathways (especially those from amino acid and carbohydrate metabolism) were predictive of yield heterosis (area under the curve = 0.907 with 10 features), and the predictability of these pathway biomarkers was validated with hybrids across environments and populations. Our findings elucidate the metabolomic landscape of rice heterosis and highlight the potential application of pathway biomarkers in achieving accurate predictions of complex phenotypes.

Extracellular Matrix Stiffness Regulates DNA Methylation by PKCα-Dependent Nuclear Transport of DNMT3L.

Extracellular matrix (ECM) stiffness has profound effects on the regulation of cell functions. DNA methylation is an important epigenetic modification governing gene expression. However, the effects of ECM stiffness on DNA methylation remain elusive. Here, it is reported that DNA methylation is sensitive to ECM stiffness, with a global hypermethylation under stiff ECM condition in mouse embryonic stem cells (mESCs) and embryonic fibroblasts compared with soft ECM. Stiff ECM enhances DNA methylation of both promoters and gene bodies, especially the 5' promoter regions of pluripotent genes. The enhanced DNA methylation is functionally required for the loss of pluripotent gene expression in mESCs grown on stiff ECM. Further experiments reveal that the nuclear transport of DNA methyltransferase 3-like (DNMT3L) is promoted by stiff ECM in a protein kinase C α (PKCα)-dependent manner and DNMT3L can be binding to Nanog promoter regions during cell-ECM interactions. These findings unveil DNA methylation as a novel target for the mechanical sensing mechanism of ECM stiffness, which provides a conserved mechanism for gene expression regulation during cell-ECM interactions.

Role of Tumor-Derived Extracellular Vesicles in Glioblastoma.

Glioblastoma (GBM) is the most common primary central nervous system tumor and one of the most lethal cancers worldwide, with morbidity of 5.26 per 100,000 population per year. These tumors are often associated with poor prognosis and terrible quality of life. Extracellular vesicles (EVs) are membrane-bound nanoparticles secreted by cells and contain lipid, protein, DNA, mRNA, miRNA and other bioactive substances. EVs perform biological functions by binding or horizontal transfer of bioactive substances to target cell receptors. In recent years, EVs have been considered as possible targets for GBM therapy. A great many types of research demonstrated that EVs played a vital role in the GBM microenvironment, development, progression, angiogenesis, invasion, and even the diagnosis of GBM. Nevertheless, the exact molecular mechanisms and roles of EVs in these processes are unclear. It can provide the basis for GBM treatment in the future that clarifying the regulatory mechanism and related signal pathways of EVs derived from GBM and their clinical value in GBM diagnosis and treatment. In this paper, the research progress and clinical application prospects of GBM-derived EVs are reviewed and discussed.

NonLoss: a novel analytical method for differential biological module identification from single-cell transcriptome.

BACKGROUND: The identification of disease-related biological modules plays an important role in our understanding of the process of diseases. Although single-cell RNA sequencing (scRNA-seq) provides high-resolution transcriptome data that can potentially characterize subtle gene expression changes within cells, the susceptibility of the gene expression information to the influence of individual genes also makes it difficult to distinguish the biological module. METHODS: To quantify gene expression information for biological function modules, we adopted the method based on Shannon's entropy and Spearman rank correlation analysis. The ingenious combination of these two methods enables the variation analysis of the former and the consistency analysis of the latter to make a more robust biological function analysis tool. RESULTS: We developed a computational analytical method and desktop application called NonLoss to analyze scRNA-seq data more robustly and to extract real biological differences between cell populations. The method derives its power by handling expression level data from all genes annotated to a specific function module, both for dimensionality reduction and reliability of function identification, avoiding random disturbance of individual genes. NonLoss can in principle be used to assess changes of function modules and identify vital functions simultaneously. Furthermore, specific genes contributing to important functions, even those with subtle expression changes, can be identified. The results demonstrated that NonLoss yields biologically significant insights into 3 different applications. CONCLUSIONS: NonLoss was developed with a user-friendly graphical user interface, and it could identify the module of biologically relevant expression changes at a single-cell resolution.

Inhibition of lncRNA Gm15834 Attenuates Autophagy-Mediated Myocardial Hypertrophy via the miR-30b-3p/ULK1 Axis in Mice.

Emerging evidence reveals that autophagy plays crucial roles in cardiac hypertrophy. Long noncoding RNAs (lncRNAs) are novel transcripts that function as gene regulators. However, it is unclear whether lncRNAs regulate autophagy in cardiac hypertrophy. Here, we identified a novel transcript named lncRNA Gm15834, which was upregulated in the transverse aortic constriction (TAC) model in vivo and the angiotensin-II (Ang-II)-induced cardiac hypertrophy model in vitro and was regulated by nuclear factor kappa B (NF-κB). Importantly, forced expression of lncRNA Gm15834 enhanced autophagic activity of cardiomyocytes and promoted myocardial hypertrophy, whereas silencing of lncRNA Gm15834 attenuated autophagy-induced myocardial hypertrophy. Mechanistically, we found that lncRNA Gm15834 could function as an endogenous sponge RNA of microRNA (miR)-30b-3p, which was downregulated in cardiac hypertrophy. Inhibition of miR-30b-3p enhanced cardiomyocyte autophagic activity and aggravated myocardial hypertrophy, whereas overexpression of miR-30b-3p suppressed autophagy-induced myocardial hypertrophy by targeting the downstream autophagy factor of unc-51-like kinase 1 (ULK1). Moreover, inhibition of lncRNA Gm15834 by adeno-associated virus carrying short hairpin RNA (shRNA) suppressed cardiomyocyte autophagic activity, improved cardiac function, and mitigated cardiac hypertrophy. Taken together, our study identified a novel regulatory axis encompassing lncRNA Gm15834/miR-30b-3p/ULK1/autophagy in cardiac hypertrophy, which may provide a potential therapy target for cardiac hypertrophy.

Rice GROWTH-REGULATING FACTOR 7 controls tiller number by regulating strigolactone synthesis.

As an important transcription factor family, GROWTH-REGULATING FACTORs (GRFs) are involved in central development processes, including growth regulation, insect and disease resistance, and stress response. The OsGRF7 has recently been shown involving in modulating leaf angle through regulating GA and IAA metabolism. Interestingly, we found that OsGRF7 negatively regulates the tiller number. However, the detailed molecular mechanisms of OsGRF7 underlying the tiller number determination are still not understood. Here, we report that OsGRF7 directly targets the promoter of the NODULATION SIGNALING PATHWAY2 (OsNSP2), a key factor involving in the strigolactone synthesis. Correspondingly, OsGRF7 alters the expression level of OsNSP2 and the endogenous strigolactone content, which rendered repression of the outgrowth of the axillary buds. These findings unveil a novel function of OsGRF7 in rice tillering determination.

Long Non-Coding RNA (lncRNA) Small Nucleolar RNA Host Gene 15 (SNHG15) Alleviates Osteoarthritis Progression by Regulation of Extracellular Matrix Homeostasis.

BACKGROUND Growing evidence suggests that long non-coding RNAs (lncRNAs), as decoys of microRNAs (miRNAs), are involved in osteoarthritis (OA) progression, but the potential mechanism of lncRNA SNHG15 in OA remains unknown. Thus, the present study explored the molecular mechanism of SNHG15 in OA progression. MATERIAL AND METHODS OA chondrocytes were created by 20 ng/ml IL-1ß stimulation, and the experimental OA model was created by destabilization of the medial meniscus (DMM) surgery. Cartilage histomorphology was observed by safranin and fast green double dyeing. The relationships between SNHG15 and miR-7, KLF4, and miR-7 were determined by dual-luciferase assay or RNA immunoprecipitation (RIP). Immunofluorescence was used to detect the expressions of Ki67, collagen II, and Aggrecan. Moreover, SNHG15, miR-7, KLF4, MMP3, ADAMTS5, COL2A1, Aggrecan, and ß-catenin expressions were assessed by qRT-PCR or Western blot. The methylation status of SNHG15 promoter was evaluated by MS-PCR. RESULTS Underexpression of KLF4 and SHNG15 and overexpression of miR-7 were found in human OA knee cartilage tissues and IL-1ß-stimulated OA chondrocytes. SHNG15 overexpression significantly inhibited ECM degradation and promoted chondrocyte formation of OA chondrocytes. Furthermore, SNHG15 regulated KLF4 expression by sponging miR-7. Further analysis found that SNHG15 significantly inhibited b-catenin in OA chondrocytes. SNHG15 had a higher level of methylation in human OA tissues than in normal cartilage tissues. CONCLUSIONS Our results revealed that SNHG15 alleviated OA progression by regulating ECM homeostasis, which provides a promising target for OA therapy.

Deciphering the Genetic Basis of Lodging Resistance in Wild Rice Oryza longistaminata.

The abuse of fertilizer results in tall rice plants that are susceptible to lodging and reduced plant yield. Hence, it is important to identify and utilize the quantitative trait loci (QTLs)/genes for lodging resistance breeding. Oryza longistaminata exhibits a strong stem and high biomass productivity, which could be a candidate gene pool for cultivars lodging resistance improvement. Here, a set of 152 BC2F20 lines derived from a cross between a cultivated line 93-11 and O. longistaminata was evaluated for lodging resistance. QTL mapping analysis combined with single-nucleotide polymorphism (SNP) marker derived from high-throughput sequencing identified 12 QTLs for stem diameter (SD), 11 QTLs for stem length (SL), and 3 QTLs for breaking strength (BS). Of which, 14 QTLs were first identified from O. longistaminata. A major QTL, qLR1, which was delimited to a region ∼80 kb on chromosome 1, increased stem diameter, stem length, and breaking strength. Another major QTL, qLR8, that was delimited in an interval ∼120 kb on chromosome 8, significantly enhanced the breaking strength. These results provide evidence that O. longistaminata can be exploited to develop lodging-resistant rice lines.