Integrative Proteomic Characterization of Human Lung Adenocarcinoma.

Genomic studies of lung adenocarcinoma (LUAD) have advanced our understanding of the disease's biology and accelerated targeted therapy. However, the proteomic characteristics of LUAD remain poorly understood. We carried out a comprehensive proteomics analysis of 103 cases of LUAD in Chinese patients. Integrative analysis of proteome, phosphoproteome, transcriptome, and whole-exome sequencing data revealed cancer-associated characteristics, such as tumor-associated protein variants, distinct proteomics features, and clinical outcomes in patients at an early stage or with EGFR and TP53 mutations. Proteome-based stratification of LUAD revealed three subtypes (S-I, S-II, and S-III) related to different clinical and molecular features. Further, we nominated potential drug targets and validated the plasma protein level of HSP 90ß as a potential prognostic biomarker for LUAD in an independent cohort. Our integrative proteomics analysis enables a more comprehensive understanding of the molecular landscape of LUAD and offers an opportunity for more precise diagnosis and treatment.

P300 Interacted With N-Myc and Regulated Its Protein Stability via Altering Its Post-Translational Modifications in Neuroblastoma.

MYCN amplification is an independent risk factor for poor prognosis in neuroblastoma (NB), but its protein product cannot be directly targeted because of protein structure. Thus, this study aimed to explore novel ways to indirectly target N-Myc by regulating its post-translational modifications (PTMs) and therefore protein stability. N-Myc coimmunoprecipitation combined with HPLC-MS/MS identified 16 PTM residues and 114 potential N-Myc-interacting proteins. Notably, both acetylation and ubiquitination were identified on lysine 199 of N-Myc. We then discovered that p300, which can interact with N-Myc, modulated the protein stability of N-Myc in MYCN-amplified NB cell lines and simultaneously regulated the acetylation level and ubiquitination level on lysine-199 of N-Myc protein in vitro. Furthermore, p300 correlated with poor prognosis in NB patients. Taken together, p300 can be considered as a potential therapeutic target to treat MYCN-amplified NB patients, and other identified PTMs and interacting proteins also provide potential targets for further study.

Identification of MYCN non-amplified neuroblastoma subgroups points towards molecular signatures for precision prognosis and therapy stratification.

BACKGROUND: Despite the extensive study of MYCN-amplified neuroblastomas, there is a significant unmet clinical need in MYCN non-amplified cases. In particular, the extent of heterogeneity within the MYCN non-amplified population is unknown. METHODS: A total of 1566 samples from 16 datasets were identified in Gene Expression Omnibus (GEO) and ArrayExpress. Characterisation of the subtypes was analysed by ConsensusClusterPlus. Independent predictors for subgrouping were constructed from the single sample predictor based on the multiclassPairs package. Findings were verified using immunohistochemistry and CIBERSORTx analysis. RESULTS: We demonstrate that MYCN non-amplified neuroblastomas are heterogeneous and can be classified into 3 subgroups based on their transcriptional signatures. Within these groups, subgroup_2 has the worst prognosis and this group shows a 'MYCN' signature that is potentially induced by the overexpression of Aurora Kinase A (AURKA); whilst subgroup_3 is characterised by an 'inflamed' gene signature. The clinical implications of this subtype classification are significant, as each subtype demonstrates a unique prognosis and vulnerability to investigational therapies. A total of 420 genes were identified as independent subgroup predictors with average balanced accuracy of 0.93 and 0.84 for train and test datasets, respectively. CONCLUSION: We propose that transcriptional subtyping may enhance precision prognosis and therapy stratification for patients with MYCN non-amplified neuroblastomas.

ESPDHot: An Effective Machine Learning-Based Approach for Predicting Protein-DNA Interaction Hotspots.

Protein-DNA interactions are pivotal to various cellular processes. Precise identification of the hotspot residues for protein-DNA interactions holds great significance for revealing the intricate mechanisms in protein-DNA recognition and for providing essential guidance for protein engineering. Aiming at protein-DNA interaction hotspots, this work introduces an effective prediction method, ESPDHot based on a stacked ensemble machine learning framework. Here, the interface residue whose mutation leads to a binding free energy change (ΔΔG) exceeding 2 kcal/mol is defined as a hotspot. To tackle the imbalanced data set issue, the adaptive synthetic sampling (ADASYN), an oversampling technique, is adopted to synthetically generate new minority samples, thereby rectifying data imbalance. As for molecular characteristics, besides traditional features, we introduce three new characteristic types including residue interface preference proposed by us, residue fluctuation dynamics characteristics, and coevolutionary features. Combining the Boruta method with our previously developed Random Grouping strategy, we obtained an optimal set of features. Finally, a stacking classifier is constructed to output prediction results, which integrates three classical predictors, Support Vector Machine (SVM), XGBoost, and Artificial Neural Network (ANN) as the first layer, and Logistic Regression (LR) algorithm as the second one. Notably, ESPDHot outperforms the current state-of-the-art predictors, achieving superior performance on the independent test data set, with F1, MCC, and AUC reaching 0.571, 0.516, and 0.870, respectively.

Acetylation of FOXO1 activates Bim expression involved in CVB3 induced cardiomyocyte apoptosis.

Viral myocarditis (VMC) is the major reason for sudden cardiac death among both children and young adults. Of these, coxsackievirus B3 (CVB3) is the most common causative agent of myocarditis. Recently, the role of signaling pathways in the pathogenesis of VMC has been evaluated in several studies, which has provided a new perspective on identifying potential therapeutic targets for this hitherto incurable disease. In the present study, in vivo and in vitro experiments showed that CVB3 infection leads to increased Bim expression and triggers apoptosis. In addition, by knocking down Bim using RNAi, we further confirmed the biological function of Bim in apoptosis induced by CVB3 infection. We additionally found that Bim and forkhead box O1 class (FOXO1) inhibition significantly increased the viability of CVB3-infected cells while blocking viral replication and viral release. Moreover, CVB3-induced Bim expression was directly dependent on FOXO1 acetylation, which is catalyzed by the co-regulation of CBP and SirTs. Furthermore, the acetylation of FOXO1 was an important step in Bim activation and apoptosis induced by CVB3 infection. The findings of this study suggest that CVB3 infection induces apoptosis through the FOXO1 acetylation-Bim pathway, thus providing new insights for developing potential therapeutic targets for enteroviral myocarditis.

Fractal two-scale method for calculating the laser scattering distribution of asphalt pavement.

The laser scattering characteristic of pavement is one of the important factors that affect the detection performance of optical sensors such as lidars. Because the wavelength of laser does not match the roughness of the asphalt pavement, the common analytical approximation model of electromagnetic scattering is not applicable in this case, so it is difficult to calculate the laser scattering distribution of the pavement accurately and effectively. According to the self-similarity of the asphalt pavement profile, a fractal two-scale method (FTSM) based on fractal structure is proposed in this paper. We used the Monte Carlo method to obtain the bidirectional scattering intensity distribution (SID) and the back SID of the laser on the asphalt pavement with different roughness. Then we designed a laser scattering measurement system to verify the simulation results. We calculated and measured the SIDs of s-light and p-light of three asphalt pavements with different roughness (σ=0.34 mm; 1.74 mm; 3.08 mm). The results show that, compared with the traditional analytical approximation methods, the results of FTSM are closer to the experimental results. Compared with the single-scale model based on the Kirchhoff approximation, FTSM has a significant improvement in computational accuracy and speed.

Dynamic Insights into the Self-Activation Pathway and Allosteric Regulation of the Orphan G-Protein-Coupled Receptor GPR52.

Within over 800 members of G-protein-coupled receptors, there are numerous orphan receptors whose endogenous ligands are largely unknown, providing many opportunities for novel drug discovery. However, the lack of an in-depth understanding of the intrinsic working mechanism for orphan receptors severely limits the related rational drug design. The G-protein-coupled receptor 52 (GPR52) is a unique orphan receptor that constitutively increases cellular 5'-cyclic adenosine monophosphate (cAMP) levels without binding any exogenous agonists and has been identified as a promising therapeutic target for central nervous system disorders. Although recent structural biology studies have provided snapshots of both active and inactive states of GPR52, the mechanism of the conformational transition between these states remains unclear. Here, an acceptable self-activation pathway for GPR52 was proposed through 6 µs Gaussian accelerated molecular dynamics (GaMD) simulations, in which the receptor spontaneously transitions from the active state to that matching the inactive crystal structure. According to the three intermediate states of the receptor obtained by constructing a reweighted potential of mean force, how the allosteric regulation occurs between the extracellular orthosteric binding pocket and the intracellular G-protein-binding site is revealed. Combined with the independent gradient model, several important microswitch residues and the allosteric communication pathway that directly links the two regions are both identified. Transfer entropy calculations not only reveal the complex allosteric signaling within GPR52 but also confirm the unique role of ECL2 in allosteric regulation, which is mutually validated with the results of GaMD simulations. Overall, this work elucidates the allosteric mechanism of GPR52 at the atomic level, providing the most detailed information to date on the self-activation of the orphan receptor.

Specific recognition between YTHDF3 and m6 A-modified RNA: An all-atom molecular dynamics simulation study.

The YTH domain of YTHDF3 belongs to a class of protein "readers" recognizing the N6-methyladenosine (m6 A) modification in mRNA. Although static crystal structure reveals m6 A recognition by a conserved aromatic cage, the dynamic process in recognition and importance of aromatic cage residues are not completely clear. Here, molecular dynamics (MD) simulations are performed to explore the issues and negative selectivity of YTHDF3 toward unmethylated substrate. Our results reveal that there exist conformation selectivity and induced-fit in YTHDF3 binding with m6 A-modified RNA, where recognition loop and loop6 play important roles in the specific recognition. m6 A modification enhances the stability of YTHDF3 in complex with RNA. The methyl group of m6 A, like a warhead, enters into the aromatic cage of YTHDF3, where Trp492 anchors the methyl group and constraints m6 A, making m6 A further stabilized by π-π stacking interactions from Trp438 and Trp497. In addition, the methylation enhances the hydrophobicity of adenosine, facilitating water molecules excluded out of the aromatic cage, which is another reason for the specific recognition and stronger intermolecular interaction. Finally, the comparative analyses of hydrogen bonds and binding free energy between the methylated and unmethylated complexes reveal the physical basis for the preferred recognition of m6 A-modified RNA by YTHDF3. This study sheds light on the mechanism by which YTHDF3 specifically recognizes m6 A-modified RNA and can provide important information for structure-based drug design.

Phyllosphere fungal communities of rubber trees exhibited biogeographical patterns, but not bacteria.

Phyllosphere microbiomes play an essential role in maintaining host health and productivity. Still, the diversity patterns and the drivers for the phyllosphere microbial community of the tropical cash crop Rubber tree (Hevea brasiliensis) - are poorly understood. We sampled the phyllosphere of field-grown rubber trees in South China. We examined the phyllosphere bacterial and fungal composition, diversity and main drivers of these microbes using the Illumina® sequencing and assembly. Fungal communities were distinctly different in different climatic regions (i.e. Xishuangbanna and Hainan Island) and climatic factors, especially mean annual temperature, and they were the main driving factors of foliar fungal communities, indicating fungal communities showed a geographical pattern. Significant differences of phyllosphere bacterial communities were detected in different habitats (i.e. endophytic and epiphytic). Most of the differences in taxa composition came from Firmicutes spp., which have been assigned as nitrogen-fixing bacteria. Since these bacteria cannot penetrate the cuticle like fungi, the abundant epiphytic Firmicutes spp. may supplement the deficiency of nitrogen acquisition. And the main factor influencing endophytic bacteria were internal factors, such as total nitrogen, total phosphorus and water content of leaves. External factors (i.e. climate) were the main driving force for epiphytic bacteria community assembly. Our work provides empirical evidence that the assembly of phyllosphere bacterial and fungal differed, which creates a precedent for preventing and controlling rubber tree diseases and pests and rubber tree yield improvement.

The Expression and Role of microRNA-133a in Plasma of Patients with Kawasaki Disease.

Kawasaki disease (KD)), also known as mucocutaneous lymph node syndrome (MCLS), is an autoimmune and systemic vasculitis syndrome. Its etiology and pathogenesis are still unclear. microRNAs (miRNA), a novel class of small non-coding RNAs, regulate the expression of multiple protein-encoding genes at the post-transcriptional level. We intend to study the change of miRNA-133a in the plasma of patients with KD, explore the role of miRNA-133a on HUVEC and define the pathogenesis of vascular dysfunction in KD. miRNA-133a expression and the mRNA and protein expression of protein phosphatase 2 catalytic subunit alpha (PPP2CA) were assessed by RT-qPCR and Western blot, respectively. The PPP2CA mRNA 3'UTR was predicted to be the potential target of miRNA-133a by using the miRNA databases and verified by the luciferase assay. The plasmids of miRNA-133a mimics and inhibitors were transfected into HUVEC cells. The plasma soluble vascular endothelial cadherin (sVE-cadherin, the excised extracellular part of VE-cadherin) levels were investigated by ELISA. The results suggested that miRNA-133a was increased by 3.8 times in the acute KD group and by 2.7 times in the convalescent KD group compared with the control group (both P = .000). PPP2CA is the target gene of miRNA-133a and its expression was inhibited by miRNA-133a acting on PPP2CA mRNA 3'UTR (P = .013). The plasma sVE-cadherin levels in the acute KD groups were increased compared with the control group (P = .024). The ROC curve analysis showed that the expression of miRNA-133a segregate acute KD patients from convalescent KD patients and healthy children. Our results suggest that miRNA-133a might be a new biomarker for KD.

Broadband devices for a polarization converter based on optical metasurfaces.

Devices employed for optical polarization conversion are widely used in the areas of optical focusing, optical imaging, and microscopy. To circumvent the problems of traditional optical polarization conversion devices, such as a narrow bandwidth, bulky size, and integration difficulties, a linear-radial polarization converter (LRPC) method based on optical metasurfaces is proposed. For a visible wavelength, i.e., λ=632.8nm, an all-dielectric half-wave plate and a LRPC with a size of 40λ (25.312 µm) are designed. The simulated results demonstrate that the LRPC creates a radially polarized wave from a linearly polarized wave in the wavelength range of 620-680 nm. In addition, a cylindrical vectorial wave with different polarizations can be generated via an adjustment of the polarization direction of the incident wave. These types of polarization converters have the important advantage of high transmittance, while also being ultra-thin and easy to integrate. They are expected to be suitable for miniaturized and integrated optical devices.

MCM6 indicates adverse tumor features and poor outcomes and promotes G1/S cell cycle progression in neuroblastoma.

BACKGROUND: Minichromosome maintenance complex component 6 (MCM6), as an important replication permission factor, is involved in the pathogenesis of various tumors. Here we studied the expression of MCM6 in neuroblastoma and its influence on tumor characteristics and prognosis. METHODS: Publicly available datasets were used to explore the influence of the differential expression of MCM6 on neuroblastoma tumor stage, risk and prognosis. In cell experiments, human neuroblastoma cell lines SK-N-SH and SK-N-BE [ (2)] were utilized to verify the ability of MCM6 to promote cell proliferation, migration and invasion. We further explored the possible molecular mechanism of MCM6 affecting the phenotype of neuroblastoma cells by mutual verification of RNA-seq and western blotting, and flow cytometry to inquire about its potential specific roles in the cell cycle. RESULTS: Through multiple datasets mining, we found that high expression of MCM6 was positively correlated with elevated tumor stage, high risk and poor prognosis in neuroblastoma. At the cellular level, neuroblastoma cell proliferation, migration and invasion were significantly inhibited after MCM6 was interfered by siRNA. Mutual verification of RNA-seq and western blotting suggested that the downstream cell cycle-related genes were differentially expressed after MCM6 interference. Flow cytometric analysis revealed that neuroblastoma cells were blocked in G1/S phase after MCM6 interference. CONCLUSION: MCM6 is considered to be the driving force of G1/S cell cycle progression, and it is also a prognostic marker and a potential novel therapeutic target in neuroblastoma.

KP-10/Gpr54 attenuates rheumatic arthritis through inactivating NF-κB and MAPK signaling in macrophages.

Rheumatoid arthritis (RA) is an autoimmune disease mainly characterized as chronic inflammation of joint. Both genetic and environmental factors play important roles in RA progression. G protein-coupled receptor 54 (GPR54) and Kisspeptins (KPs), the natural GRP54 ligands encoded by Kiss-1 gene are known to play important roles in immune regulation but the precise role of KP-10/GPR54 in RA remains elusive. Kiss1/Gpr54 expression was determined by immunohistochemistry on protein and real-time PCR on RNA from isolated RA-patient synovial tissue and PBMC. Collagen-induced arthritis (CIA) mouse models were used to investigate the effect of KP-10/Gpr54 on the rheumatic arthritis severity in the mice. The signaling pathway involved in KP-10/GPR54 was assessed by western blot and immunofluorescence.In the present study, we demonstrated that GPR54 upregulation in bone marrow-derived macrophages (BMDM) was associated with the severity of RA. In addition, Gpr54-/- increased the inflammatory cytokines induced by lipopolysaccharide (LPS) in BMDM and diseased severity of CIA (n = 10), while KP-10 reduced the LPS-induced inflammatory cytokines in vitro and ameliorated the CIA symptoms in vivo. Furthermore, we demonstrated that KP-10/GPR54 binds to PP2A-C to suppressed LPS induced NF-κB and MAPK signaling in BMDM. All these findings suggest that KP-10/GPR54 may be a novel therapeutic target for the diagnosis and treatment of RA.

15,16-dihydrotanshinone I inhibits EOMA cells proliferation by interfering in posttranscriptional processing of hypoxia-inducible factor 1.

Infantile hemangioma (IH), which threatens the physical and mental health of patients, is the most common benign tumor in infants. Previously, we found that 15,16-dihydrotanshinone I (DHTS) was significantly more effective at inhibiting hemangioma proliferation in vitro and in vivo than the first-line treatment propranolol. To investigate the underlying mechanism of DHTS, we used EOMA cells as a model to study the effect of DHTS. We compared the transcriptomes of control and DHTS-treated EOMA cells. In total, 2462 differentially expressed genes were detected between the groups. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed downregulated activity of the hypoxia-inducible factor 1 alpha (HIF-1α) signaling pathway in EOMA cells following treatment with DHTS. Thus, we investigated HIF-1α expression at protein and mRNA levels. Our results revealed that DHTS downregulated HIF-1α expression by interfering in its posttranscriptional processing, and the RNA-binding protein HuR participated in this mechanism. Our findings provide a basis for clinical transformation of DHTS and insight into pathogenic mechanisms involved in IH.

Power and Thermal Efficiency Optimization of an Irreversible Steady-Flow Lenoir Cycle.

Using finite time thermodynamic theory, an irreversible steady-flow Lenoir cycle model is established, and expressions of power output and thermal efficiency for the model are derived. Through numerical calculations, with the different fixed total heat conductances (UT) of two heat exchangers, the maximum powers (Pmax), the maximum thermal efficiencies (ηmax), and the corresponding optimal heat conductance distribution ratios (uLP(opt)) and (uLη(opt)) are obtained. The effects of the internal irreversibility are analyzed. The results show that, when the heat conductances of the hot- and cold-side heat exchangers are constants, the corresponding power output and thermal efficiency are constant values. When the heat source temperature ratio (τ) and the effectivenesses of the heat exchangers increase, the corresponding power output and thermal efficiency increase. When the heat conductance distributions are the optimal values, the characteristic relationships of P-uL and η-uL are parabolic-like ones. When UT is given, with the increase in τ, the Pmax, ηmax, uLP(opt), and uLη(opt) increase. When τ is given, with the increase in UT, Pmax and ηmax increase, while uLP(opt) and uLη(opt) decrease.

Generation of subdiffraction longitudinal bifoci by shaping a radially polarized wave.

Lenses with two or more foci along the longitudinal direction exhibit immense potential in several optical applications. In this study, we propose an approach for generating subdiffraction longitudinal bifoci by binary-phase bifocal super-oscillatory lenses (SOLs), which are realized by simple AND operation between two single-foci SOLs with different focal lengths. Three bifocal SOLs with radiusRlens=70λ are designed at an operating wavelength of λ=118.8µm. Simulation results demonstrate that the minimum full width at half maximum (FWHM) is 0.397λ, and the maximum FWHM is 0.449λ, which is still smaller than the Abbe diffraction limit of 0.510λ, while all the sidelobe ratios are small (<15.1%). By properly choosing the focal length of the single-foci SOLs in the design process, the distance between the two foci can be easily controlled. Significantly, the generated bifoci with relatively uniform intensity contain a strong longitudinal electric field, which indicates their excellent prospects in optical imaging, particle acceleration, and other optical applications. In addition, the proposed bifoci-SOLs are based on the binary phase modulation, which facilitates easy fabrication compared with other approaches. These outstanding properties indicate the wide application prospects of bifocal SOLs.

Arabidopsis SH3P2 is an ubiquitin-binding protein that functions together with ESCRT-I and the deubiquitylating enzyme AMSH3.

Clathrin-mediated endocytosis of plasma membrane proteins is an essential regulatory process that controls plasma membrane protein abundance and is therefore important for many signaling pathways, such as hormone signaling and biotic and abiotic stress responses. On endosomal sorting, plasma membrane proteins maybe recycled or targeted for vacuolar degradation, which is dependent on ubiquitin modification of the cargos and is driven by the endosomal sorting complexes required for transport (ESCRTs). Components of the ESCRT machinery are highly conserved among eukaryotes, but homologs of ESCRT-0 that are responsible for recognition and concentration of ubiquitylated proteins are absent in plants. Recently several ubiquitin-binding proteins have been identified that serve in place of ESCRT-0; however, their function in ubiquitin recognition and endosomal trafficking is not well understood yet. In this study, we identified Src homology-3 (SH3) domain-containing protein 2 (SH3P2) as a ubiquitin- and ESCRT-I-binding protein that functions in intracellular trafficking. SH3P2 colocalized with clathrin light chain-labeled punctate structures and interacted with clathrin heavy chain in planta, indicating a role for SH3P2 in clathrin-mediated endocytosis. Furthermore, SH3P2 cofractionates with clathrin-coated vesicles (CCVs), suggesting that it associates with CCVs in planta Mutants of SH3P2 and VPS23 genetically interact, suggesting that they could function in the same pathway. Based on these results, we suggest a role of SH3P2 as an ubiquitin-binding protein that binds and transfers ubiquitylated proteins to the ESCRT machinery.

RSI-CB: A Large-Scale Remote Sensing Image Classification Benchmark Using Crowdsourced Data.

Image classification is a fundamental task in remote sensing image processing. In recent years, deep convolutional neural networks (DCNNs) have experienced significant breakthroughs in natural image recognition. The remote sensing field, however, is still lacking a large-scale benchmark similar to ImageNet. In this paper, we propose a remote sensing image classification benchmark (RSI-CB) based on massive, scalable, and diverse crowdsourced data. Using crowdsourced data, such as Open Street Map (OSM) data, ground objects in remote sensing images can be annotated effectively using points of interest, vector data from OSM, or other crowdsourced data. These annotated images can, then, be used in remote sensing image classification tasks. Based on this method, we construct a worldwide large-scale benchmark for remote sensing image classification. This benchmark has large-scale geographical distribution and large total image number. It contains six categories with 35 sub-classes of more than 24,000 images of size 256 × 256 pixels. This classification system of ground objects is defined according to the national standard of land-use classification in China and is inspired by the hierarchy mechanism of ImageNet. Finally, we conduct numerous experiments to compare RSI-CB with the SAT-4, SAT-6, and UC-Merced data sets. The experiments show that RSI-CB is more suitable as a benchmark for remote sensing image classification tasks than other benchmarks in the big data era and has many potential applications.

Performance Optimization of a Condenser in Ocean Thermal Energy Conversion (OTEC) System Based on Constructal Theory and a Multi-Objective Genetic Algorithm.

Constructal optimization of a plate condenser with fixed heat transfer rate and effective volume in ocean thermal energy conversion (OTEC) system is performed based on constructal theory. Optimizations of entropy generation rate ( S ˙ g ) in heat transfer process and total pumping power ( P sum ) due to friction loss are two conflicting objectives for a plate condenser. With the conventional optimization method, the plate condenser is designed by taking a composite function (CF) considering both S ˙ g and P sum as optimization objectives, and employing effective length, width, and effective number of heat transfer plates as design variables. Effects of structural parameters of the plate condenser and weighting coefficient of CF on design results are investigated. With a multi-objective genetic algorithm, the plate condenser is designed by simultaneously optimizing S ˙ g and P sum , and the Pareto optimal set is obtained. The results demonstrate that CFs after primary and twice-constructal optimizations are respectively reduced by 7.8% and 9.9% compared with the initial CF, and the effective volume of the plate condenser has a positive impact on the twice minimum CF. Furthermore, the Pareto optimal set can provide better selections for performance optimizations of plate condensers.

A novel long noncoding RNA AK016739 inhibits osteoblast differentiation and bone formation.

The incidence of postmenopausal osteoporosis research 50% in middle-aged and older women, however, effects of existing therapy are not ideal. Emerging evidence have proved that long noncoding RNAs (lncRNAs) was correlated with multiple physiological and pathology processes including development, carcinogenesis, and osteogenesis. However, reports on lncRNAs regulating bone formation were relatively limited. In this study, we screened osteogenic lncRNAs through mRNA/lncRNA microarray combined with gene coexpression analysis. The biological function of the screened lncRNA was assessed both in vitro and in vivo. The effects of the lncRNA on osteogenic transcription factors were also evaluated. We identified AK016739, which was correlated with osteogenic differentiation and enriched in skeletal tissues of mice. The expression levels of AK016739 in bone-derived mesenchymal stem cells were increased with age and negatively correlated with osteogenic differentiation marker genes. Experiments showed that AK016739 inhibited osteoblast differentiation, and in vivo inhibition of AK016739 by its small interfering RNA would rescue bone formation in ovariectomized osteoporosis mice model. In addition, AK016739 suppressed both expression levels and activities of osteogenic transcription factors. This newly identified lncRNA AK016739 has revealed a new mechanism of osteogenic differentiation and provided new targets for treatment of skeletal disorders.