Multi-Proteomic Analysis Reveals the Effect of Protein Lactylation on Matrix and Cholesterol Metabolism in Tendinopathy.

Tendinopathy is a disease with surging prevalence. Lacking understanding of molecular mechanisms impedes the development of therapeutic approaches and agents. Lysine lactylation (Kla) is a newly discovered post-translational modification related to glycolysis. It has long been noted that manipulation of glycolysis metabolism could affect tendon cell function, tendon homeostasis, and healing process of tendon. However, protein lactylation sites in tendinopathy remain unexplored. Here, we conducted the first proteome-wide Kla analysis in tendon samples harvested from patients with rotator cuff tendinopathy (RCT), which identified 872 Kla sites across 284 proteins. Compared with normal counterparts, 136 Kla sites on 77 proteins were identified as upregulated in the pathological tendon, while 56 sites on 32 proteins were downregulated. Function enrichment analysis demonstrated that the majority of proteins with upregulated Kla levels functioned in organization of the tendon matrix and cholesterol metabolism, accompanied by lower expression levels which meant impaired cholesterol metabolism and degeneration of the tendon matrix, indicating potential cross-talk between protein lactylation and expression levels. At last, by western blotting and immunofluorescence, we verified the correlation between high lactylation and the downregulation of matrix and cholesterol-related proteins including BGN, MYL3, TPM3, and APOC3. ProteomeXchange: PXD033146.

Vanilla pompona Leaves and Stems as New Sources of Bioactive Compounds: The Therapeutic Potential for Skin Senescence.

A large variety of natural plants are widely produced and utilised because of their remarkable pharmacological effects. In this study, two phenolic glycosides were isolated for the first time from Vanilla pompona Schiede (Orchidaceae) from Kyushu, Japan: bis [4-(ß-D - O-glucopyranosyloxy)-benzyl] (S)-2-isopropylmalate (1: ) and bis 4-[ß-D-O-glucopyranosyloxy)-benzyl]-(2R,3S)-2-isopropyl tartrate (2: ). We have discovered that the crude extract of V. pompona leaves and stems and its two phenolic glycosides (compounds 1:  - 2: ) are highly effective in reversing skin senescence. V. pompona and compounds 1:  - 2: were found to promote the synthesis of collagen, hyaluronic acid, and elastin in skin fibroblasts in a normal skin cell model; in a replicative senescence model, V. pompona and compounds 1:  - 2: significantly reduced the ageing phenotype in skin fibroblasts. These compounds also demonstrated a significant protective effect in a UV-induced photo-senescence model; the possible mechanisms of this effect were investigated in this study. To the best of our knowledge, this study is the first to develop V. pompona leaves and stems as new sources of bioactive compounds and to examine their therapeutic potential for skin senescence. The development potential of V. pompona leaves and stems for use in the cosmetics, cosmeceutical, and pharmaceutical industries remains to be investigated.

The effect of talus osteochondral defects of different area size on ankle joint stability: a finite element analysis.

BACKGROUND: Osteochondral lesion of the talus (OLT) is one of the most common ankle injuries, which will lead to biomechanical changes in the ankle joint and ultimately affect ankle function. Finite element analysis (FEA) is used to clarify the effect of talus osteochondral defects on the stability of the ankle joint at different depths. However, no research has been conducted on talus osteochondral defect areas that require prompt intervention. In this research, FEA was used to simulate the effect of the area size of talus osteochondral defect on the stress and stability of the ankle joint under a specific depth defect. METHODS: Different area sizes (normal, 2 mm* 2 mm, 4 mm* 4 mm, 6 mm* 6 mm, 8 mm* 8 mm, 10 mm* 10 mm, and 12 mm* 12 mm) of the three-dimensional finite element model of osteochondral defects were established. The model was used to simulate and calculate joint stress and displacement of the articular surface of the distal tibia and the proximal talus when the ankle joint was in the heel-strike, midstance, and push-off phases. RESULTS: When OLT occurred, the contact pressure of the articular surface, the equivalent stress of the proximal talus, the tibial cartilage, and the talus cartilage did not change significantly with an increase in the size of the osteochondral defect area when the heel-strike phase was below 6 mm * 6 mm. Gradual increases started at 6 mm * 6 mm in the midstance and push-off phases. Maximum changes were reached when the defect area size was 12 mm * 12 mm. The same patterns were observed in the talus displacement. CONCLUSIONS: The effect of the defect area of the ankle talus cartilage on the ankle biomechanics is evident in the midstance and push-off phases. When the size of the defect reaches 6 mm * 6 mm, the most apparent change in the stability of the ankle joint occurs, and the effect does not increase linearly with the increase in the size of the defect.

Potential of Hibiscus sabdariffa L. and Hibiscus Acid to Reverse Skin Aging.

Hibiscus sabdariffa L. (HS) has a long history of edible and medicinal uses. In this study, the biological activities of the extracts, chromatographic fractions, and hibiscus acid obtained from HS were evaluated for their potential bioactivities. Their ability to promote extracellular matrix synthesis in skin fibroblasts was evaluated by enzyme-linked immunosorbent assays. Their anti-inflammatory activity was evaluated in a nitric oxide (NO)-Griess inflammatory experiment. Furthermore, hibiscus acid was found to have a strong anti-oxidative stress effect through the establishment of an oxidative stress model induced by hydrogen peroxide. Several assays indicated that hibiscus acid treatment can effectively reduce extracellular adenosine triphosphate (ATP) secretion and carbonyl protein production, as well as maintain a high level of reduced/oxidized glutathione (GSH/GSSG) in skin cells, thus providing a possible mechanism by which hibiscus acid can counter antioxidative stress. The present study is the first to explore the reversing skin aging potential and the contributory component of HS.

SVDNVLDA: predicting lncRNA-disease associations by Singular Value Decomposition and node2vec.

BACKGROUND: Numerous studies on discovering the roles of long non-coding RNAs (lncRNAs) in the occurrence, development and prognosis progresses of various human diseases have drawn substantial attentions. Since only a tiny portion of lncRNA-disease associations have been properly annotated, an increasing number of computational methods have been proposed for predicting potential lncRNA-disease associations. However, traditional predicting models lack the ability to precisely extract features of biomolecules, it is urgent to find a model which can identify potential lncRNA-disease associations with both efficiency and accuracy. RESULTS: In this study, we proposed a novel model, SVDNVLDA, which gained the linear and non-linear features of lncRNAs and diseases with Singular Value Decomposition (SVD) and node2vec methods respectively. The integrated features were constructed from connecting the linear and non-linear features of each entity, which could effectively enhance the semantics contained in ultimate representations. And an XGBoost classifier was employed for identifying potential lncRNA-disease associations eventually. CONCLUSIONS: We propose a novel model to predict lncRNA-disease associations. This model is expected to identify potential relationships between lncRNAs and diseases and further explore the disease mechanisms at the lncRNA molecular level.

The factors associated with nosocomial infection in elderly hip fracture patients: gender, age, and comorbidity.

PURPOSE: This is a retrospective case-control study to ascertain the factors influencing nosocomial infection (NI) in elderly patients with hip fractures. METHODS: A total of 80,174 patients (≥ 60 years) who suffered hip fractures between 2006 and 2017 were identified through a national inquiry of 94 hospitals. The patients were divided into an NI group and control group according to the occurrence or lack of occurrence of NI within 48 hours after surgery, respectively. Age, gender, hip fracture pattern, whether to operate, surgical treatments, and comorbidities were recorded as variables. RESULTS: A total of 9806 elderly hip fracture patients (60 years) were included, 1977 of whom were patients diagnosed with NI. The control group consisted of randomly drawn cases from the 9806 patients from different hospitals with a rate of one NI patient: four patients without NI. Patient gender, age, and in particular the number of comorbidities were associated with occurrence of NI. Using regression models to predict infection outcomes based on the number of comorbidities had an area under the curve (AUC) of 0.714, while using the Charlson comorbidity index (CCI) yielded a smaller value of 0.694. The most common comorbidities of this elderly cohort were chronic respiratory disease, hypertension, diabetes mellitus, cerebrovascular disease, and coronary heart disease. CONCLUSIONS: Older age, male gender, and greater number of comorbidities were found to be associated with the occurrence of NI. In particular, the number of comorbidities was the most accurate predictor of NI occurrence, and when used to build a regression model, it had greater predictive capability than CCI to predict NI in elderly hip fracture patients. Additionally, the common diseases of the elderly should be primarily considered when investigating the relationship between comorbidities and NI in older patients.

Matrine inhibits the growth and induces apoptosis of osteosarcoma cells in vitro by inactivating the Akt pathway.

Matrine, a natural product, has been demonstrated to be a promising chemotherapeutic drug for some cancers. Using flow cytometric analysis of the cell cycle and apoptosis, we found that matrine inhibited the proliferation and induced apoptosis in the human osteosarcoma (OS) cell lines MG63, HOS, U2OS, and SAOS2 in vitro in a dose-dependent manner. We therefore assessed the role of the serine/threonine kinase Akt in the regulation of matrine-mediated cell growth inhibition and apoptosis induction in human OS cell lines. After treatment for 48 h, matrine induced G0/G1-stage cell cycle arrest in MG63, U2OS, and SAOS2 cells associated with an increase in the expression of p27(Kip1) and a decrease in the expression of Akt, glycogen synthase kinase 3 (GSK3)-ß (Ser9), and cyclin D1. Furthermore, the pro-apoptotic factor Bax was upregulated. Overall, our findings suggest that matrine may be an effective anti-osteosarcoma drug due to its ability to inhibit proliferation and induce apoptosis in OS cells, possibly through the involvement of Akt signaling.

Comparison of the effects of heparin and the direct factor Xa inhibitor, rivaroxaban, on bone microstructure and metabolism in adult rats.

AIM: Deep venous thrombosis is a significant complication following surgery, and is associated with high morbidity and mortality in adults. The direct factor Xa inhibitor, rivaroxaban, is used to prevent venous thromboembolism in patients suffering from trauma and joint arthroplasty. The present study compared the effects of rivaroxaban and heparin on bone microstructure and metabolism in adult rats. MATERIALS AND METHODS: Twenty-four Wistar rats were divided into sham, rivaroxaban and heparin groups. Rivaroxaban (1.5 mg·kg(-1)·d(-1)) and heparin (2 IU·g(-1)·d(-1)) were administered for 4 weeks. To assess changes in bone metabolism, serum calcium and phosphorus levels, and bone formation and resorption markers were examined. Micro-CT analysis was used to examine the microstructure of both trabecular and cortical bone. Dual energy X-ray absorptiometry was employed to detect bone mineral density (BMD). RESULTS: Serum phosphorus levels were significantly lower in both rivaroxaban (1.33 ± 0.07 mmol/L) and heparin (1.33 ± 0.21 mmol/L) rats than in sham rats (1.71 ± 0.14 mmol/L). Activity and levels of bone formation markers, bone-specific alkaline phosphatase (BAP) and type I procollagen N-terminal pro-peptide (PINP), were 32.4 and 38.2% lower in heparin-treated rats than in sham rats. Bone resorption markers, pyridinoline (PYD) and deoxypyridinoline (DPD), were 20.1 and 34.3% higher in heparin-treated rats than in sham rats, respectively. By contrast, rivaroxaban only resulted in a decrease PINP levels. Bone volume fraction (BV/TV) decreased by 23.5 and 20.5% from those in sham rats, while trabecular separation (Tb.Sp) increased by 28.2 and 16.3% in trabecular bone of heparin- and rivaroxaban-treated rats, [corrected] respectively. Moreover, the microstructure of cortical bone and BMD were negatively affected by heparin but not by rivaroxaban. CONCLUSION: Rivaroxaban leads to fewer adverse effects on bone microstructure than heparin.

The influence of Type I and III collagen on the proliferation, migration and differentiation of myoblasts.

Myoblast is a kind of activated muscle stem cell. Its biological activities, such as proliferation, migration, differentiation, and fusion, play a crucial role in maintaining the integrity of the skeletal muscle system. These activities of myoblasts can be significantly influenced by the extracellular matrix. Collagen, being a principal constituent of the extracellular matrix, substantially influences these biological activities. In skeletal muscle, collagen I and III are two kinds of primary collagen types. Their influence on myoblasts and the difference between them remain ambiguous. The purpose of this study is to discover the influence of collagen I and III on biological function of myoblasts and compare their differences. We used C2C12 cell line and primary myoblasts to discover the effect of collagen I and III on proliferation, migration and differentiation of myoblasts and then performed the transcriptome sequencing and analysis. The results showed that both collagen I and III enhanced the proliferation of myoblasts, with no statistical difference between them. Similarly, collagen I and III enhanced the migration of myoblasts, with collagen I was more pronounced in Transwell assay. On the contrary, collagen I and III inhibited myoblasts differentiation, with collagen III was more pronounced at gene expression level. The transcriptome sequencing identified DEGs and enrichment analysis elucidated different terms between Type I and III collagen. Collectively, our research preliminarily elucidated the influence of collagen I and III on myoblasts and their difference and provided the preliminary experimental foundation for subsequent research.

Histone deacetylase inhibition enhances extracellular vesicles from muscle to promote osteogenesis via miR-873-3p.

Regular physical activity is widely recognized for reducing the risk of various disorders, with skeletal muscles playing a key role by releasing biomolecules that benefit multiple organs and tissues. However, many individuals, particularly the elderly and those with clinical conditions, are unable to engage in physical exercise, necessitating alternative strategies to stimulate muscle cells to secrete beneficial biomolecules. Histone acetylation and deacetylation significantly influence exercise-induced gene expression, suggesting that targeting histone deacetylases (HDACs) could mimic some exercise responses. In this study, we explored the effects of the HDAC inhibitor Trichostatin A (TSA) on human skeletal muscle myoblasts (HSMMs). Our findings showed that TSA-induced hyperacetylation enhanced myotube fusion and increased the secretion of extracellular vesicles (EVs) enriched with miR-873-3p. These TSA-EVs promoted osteogenic differentiation in human bone marrow mesenchymal stem cells (hBMSCs) by targeting H2 calponin (CNN2). In vivo, systemic administration of TSA-EVs to osteoporosis mice resulted in significant improvements in bone mass. Moreover, TSA-EVs mimicked the osteogenic benefits of exercise-induced EVs, suggesting that HDAC inhibition can replicate exercise-induced bone health benefits. These results demonstrate the potential of TSA-induced muscle-derived EVs as a therapeutic strategy to enhance bone formation and prevent osteoporosis, particularly for individuals unable to exercise. Given the FDA-approved status of various HDAC inhibitors, this approach holds significant promise for rapid clinical translation in osteoporosis treatment.

HEGANLDA: A Computational Model for Predicting Potential Lncrna-Disease Associations Based On Multiple Heterogeneous Networks.

Long non-coding RNAs (lncRNAs) play vital regulatory roles in many human complex diseases, however, the number of validated lncRNA-disease associations is notable rare so far. How to predict potential lncRNA-disease associations precisely through computational methods remains challenging. In this study, we proposed a novel method, LDVCHN (LncRNA-Disease Vector Calculation Heterogeneous Networks), and also developed the corresponding model, HEGANLDA (Heterogeneous Embedding Generative Adversarial Networks LncRNA-Disease Association), for predicting potential lncRNA-disease associations. In HEGANLDA, the graph embedding algorithm (HeGAN) was introduced for mapping all nodes in the lncRNA-miRNA-disease heterogeneous network into the low-dimensional vectors which severed as the inputs of LDVCHN. HEGANLDA effectively adopted the XGBoost (eXtreme Gradient Boosting) classifier, which was trained by the low-dimensional vectors, to predict potential lncRNA-disease associations. The 10-fold cross-validation method was utilized to evaluate the performance of our model, our model finally achieved an area under the ROC curve of 0.983. According to the experiment results, HEGANLDA outperformed any one of five current state-of-the-art methods. To further evaluate the effectiveness of HEGANLDA in predicting potential lncRNA-disease associations, both case studies and robustness tests were performed and the results confirmed its effectiveness and robustness. The source code and data of HEGANLDA are available at https://github.com/HEGANLDA/HEGANLDA.

Non-Negligible Role of Trace Elements in Influenza Virus Infection.

Influenza virus has continuously spread around the globe for more than 100 years since the first influenza epidemic in 1918. The rapid and unpredictable gene variation of the influenza virus could possibly bring about another pandemic in future, which might threaten to overwhelm us without adequate preparation. Consequently, it is extremely urgent to identify effective broad-spectrum antiviral treatments for a variety of influenza virus variants. As essential body components, trace elements are great potential candidates with an as yet poorly understood ability to protect the host from influenza infection. Herein, we have summarized the present state of knowledge concerning the function of trace elements in influenza virus replication along with an analysis of their potential molecular mechanisms. Modulation of host immune responses to the influenza virus is one of the most common modes to achieve the anti-influenza activity of trace elements, such as selenium and zinc. Simultaneously, some antioxidant and antiviral signal pathways can be altered with the participation of trace elements. More interestingly, some micro-elements including selenium, zinc, copper and manganese, directly target viral proteins and regulate their stability and activity to influence the life cycle of the influenza virus. Further verification of the antiviral effect and the mechanism will promote the application of trace elements as adjuvants in the clinic.

Identification of telomere-related genes associated with aging-related molecular clusters and the construction of a diagnostic model in Alzheimer's disease based on a bioinformatic analysis.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disease that is strongly associated with aging. Telomeres are DNA sequences that protect chromosomes from damage and shorten with age. Telomere-related genes (TRGs) may play a role in AD's pathogenesis. OBJECTIVES: To identify TRGs related to aging clusters in AD patients, explore their immunological characteristics, and build a TRG-based prediction model for AD and AD subtypes. METHODS: We analyzed the gene expression profiles of 97 AD samples from the GSE132903 dataset, using aging-related genes (ARGs) as clustering variables. We also assessed immune-cell infiltration in each cluster. We performed a weighted gene co-expression network analysis to identify cluster-specific differentially expressed TRGs. We compared four machine-learning models (random forest, generalized linear model [GLM], gradient boosting model, and support vector machine) for predicting AD and AD subtypes based on TRGs and validated TRGs by conducting an artificial neural network (ANN) analysis and a nomogram model. RESULTS: We identified two aging clusters in AD patients with distinct immunological features: Cluster A had higher immune scores than Cluster B. Cluster A and the immune system are intimately associated, and this association could affect immunological function and result in AD via the digestive system. The GLM predicted AD and AD subtypes most accurately and was validated by the ANN analysis and nomogram model. CONCLUSION: Our analyses revealed novel TRGs associated with aging clusters in AD patients and their immunological characteristics. We also developed a promising prediction model based on TRGs for assessing AD risk.

Delayed denervation-induced muscle atrophy in Opg knockout mice.

Recent evidence has shown a crucial role for the osteoprotegerin/receptor activator of nuclear factor κ-B ligand/RANK (OPG/RANKL/RANK) signaling axis not only in bone but also in muscle tissue; however, there is still a lack of understanding of its effects on muscle atrophy. Here, we found that denervated Opg knockout mice displayed better functional recovery and delayed muscle atrophy, especially in a specific type IIB fiber. Moreover, OPG deficiency promoted milder activation of the ubiquitin-proteasome pathway, which further verified the protective role of Opg knockout in denervated muscle damage. Furthermore, transcriptome sequencing indicated that Opg knockout upregulated the expression of Inpp5k, Rbm3, and Tet2 and downregulated that of Deptor in denervated muscle. In vitro experiments revealed that satellite cells derived from Opg knockout mice displayed a better differentiation ability than those acquired from wild-type littermates. Higher expression levels of Tet2 were also observed in satellite cells derived from Opg knockout mice, which provided a possible mechanistic basis for the protective effects of Opg knockout on muscle atrophy. Taken together, our findings uncover the novel role of Opg in muscle atrophy process and extend the current understanding in the OPG/RANKL/RANK signaling axis.

Application of next-generation sequencing to identify different pathogens.

Early and precise detection and identification of various pathogens are essential for epidemiological monitoring, disease management, and reducing the prevalence of clinical infectious diseases. Traditional pathogen detection techniques, which include mass spectrometry, biochemical tests, molecular testing, and culture-based methods, are limited in application and are time-consuming. Next generation sequencing (NGS) has emerged as an essential technology for identifying pathogens. NGS is a cutting-edge sequencing method with high throughput that can create massive volumes of sequences with a broad application prospects in the field of pathogen identification and diagnosis. In this review, we introduce NGS technology in detail, summarizes the application of NGS in that identification of different pathogens, including bacteria, fungi, and viruses, and analyze the challenges and outlook for using NGS to identify clinical pathogens. Thus, this work provides a theoretical basis for NGS studies and provides evidence to support the application of NGS in distinguishing various clinical pathogens.

Biological and genomic analysis of a symbiotic nitrogen fixation defective mutant in Medicago truncatula.

Medicago truncatula has been selected as one of the model legume species for gene functional studies. To elucidate the functions of the very large number of genes present in plant genomes, genetic mutant resources are very useful and necessary tools. Fast Neutron (FN) mutagenesis is effective in inducing deletion mutations in genomes of diverse species. Through this method, we have generated a large mutant resource in M. truncatula. This mutant resources have been used to screen for different mutant using a forward genetics methods. We have isolated and identified a large amount of symbiotic nitrogen fixation (SNF) deficiency mutants. Here, we describe the detail procedures that are being used to characterize symbiotic mutants in M. truncatula. In recent years, whole genome sequencing has been used to speed up and scale up the deletion identification in the mutant. Using this method, we have successfully isolated a SNF defective mutant FN007 and identified that it has a large segment deletion on chromosome 3. The causal deletion in the mutant was confirmed by tail PCR amplication and sequencing. Our results illustrate the utility of whole genome sequencing analysis in the characterization of FN induced deletion mutants for gene discovery and functional studies in the M. truncatula. It is expected to improve our understanding of molecular mechanisms underlying symbiotic nitrogen fixation in legume plants to a great extent.

Frailty Factors and Outcomes in Patients Undergoing Orthopedic Surgery: Protocol for a Systematic Review and Meta-analysis.

BACKGROUND: Frailty is an aggregate expression of susceptibility to adverse health outcomes because of age- and disease-related deficits that accumulate across multiple domains. Previous studies have found the presence of preoperative frailty is associated with an increased risk of adverse outcomes. The number of older adults undergoing orthopedic surgery is rapidly increasing. However, there has been no evidence-based study on the relationship between frailty and outcomes in patients undergoing orthopedic surgery. OBJECTIVE: The aims of this study are to investigate the association between frailty and outcomes in patients who underwent orthopedic surgery as well as patient factors associated with frailty. METHODS: The methods to be used for this systematic review are reported according to the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-analysis Protocols) 2015 checklist. An extensive search will be conducted in PubMed, Embase, the Cochrane Library, and other mainstream databases. Any study where patients undergoing orthopedic surgery were assessed using a defined or validated measure of frailty and the association of frailty with patient factors and/or outcomes was reported will be included. A total of 2 researchers will independently screen articles for inclusion, with disagreements resolved by a third reviewer. We will perform a narrative synthesis of the factors associated with frailty, prevalence of frailty, effect of frailty on patient outcomes, and interventions for patients who are frail. A meta-analysis focusing on individual factors associated with frailty and the effect of frailty on patient outcomes will be performed, if applicable. The risk of bias will be evaluated. A subgroup analysis and sensitivity analysis will be performed. RESULTS: Literature searches were conducted in September 2021 and the review is anticipated to be completed by the end of July 2022. CONCLUSIONS: This systematic review and meta-analysis will provide an overview of frailty and investigate the relationship between frailty and patient outcomes as well as the relationship between patient factors and frailty in patients undergoing orthopedic surgery. This study could potentially increase patients' awareness of the outcomes associated with frailty, compel clinical specialties to further acknowledge the concept of frailty, and enhance the development of assessment instruments and tools for frailty. TRIAL REGISTRATION: PROSPERO CRD42020181846; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=181846. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/28338.

Mechanisms of estrogen deficiency-induced osteoporosis based on transcriptome and DNA methylation.

Osteoporosis is a disease that impacts the elderly. Low estrogen is related to changes in DNA methylation and consequent alterations in gene expression, leading to a new direction in research related to the pathophysiology of osteoporosis. We constructed an Ovariectomized (OVX) mouse model in our study, and the mouse models had osteoporosis based on the phenotype and methylation levels in the mouse's bone. Furthermore, the methylation level of the OVX mice was significantly changed compared to that of SHAM mice. Therefore, we performed genome-level analysis on the mouse model using transcriptome and Whole Genome Bisulfite Sequencing (WGBS) by combining the data of two omics and discovered that the changes in gene expression level caused by osteoporosis primarily focused on the decrease of bone and muscle development and the activation of the immune system. According to intersection analysis of methylation and transcriptome data, the differentially expressed genes and pathways are consistent with the differentially expressed methylation locations and regions. Further, the differentially expressed methylation sites were mainly concentrated in promoters, exons, and other critical functional regions of essential differentially expressed genes. This is also the primary cause of gene differential expression variations, indicating that estrogen deficiency might regulate gene expression by altering methylation modification, leading to osteoporosis. We demonstrated the clinical value of methylation modification research, and these findings would improve the current understanding of underlying molecular mechanisms of osteoporosis incidence and development and provide new ideas for early detection and treatment of osteoporosis.

WAFNRLTG: A Novel Model for Predicting LncRNA Target Genes Based on Weighted Average Fusion Network Representation Learning Method.

Long non-coding RNAs (lncRNAs) do not encode proteins, yet they have been well established to be involved in complex regulatory functions, and lncRNA regulatory dysfunction can lead to a variety of human complex diseases. LncRNAs mostly exert their functions by regulating the expressions of target genes, and accurate prediction of potential lncRNA target genes would be helpful to further understanding the functional annotations of lncRNAs. Considering the limitations in traditional computational methods for predicting lncRNA target genes, a novel model which was named Weighted Average Fusion Network Representation learning for predicting LncRNA Target Genes (WAFNRLTG) was proposed. First, a novel heterogeneous network was constructed by integrating lncRNA sequence similarity network, mRNA sequence similarity network, lncRNA-mRNA interaction network, lncRNA-miRNA interaction network and mRNA-miRNA interaction network. Next, four popular network representation learning methods were utilized to gain the representation vectors of lncRNA and mRNA nodes. Then, the representations of lncRNAs and target genes in the heterogeneous network were obtained with the weighted average fusion network representation learning method. Finally, we merged the representations of lncRNAs and related target genes to form lncRNA-gene pairs, trained the XGBoost classifier and predicted potential lncRNA target genes. In five-cross validations on the training and independent datasets, the experimental results demonstrated that WAFNRLTG obtained better AUC scores (0.9410, 0.9350) and AUPR scores (0.9391, 0.9350). Moreover, case studies of three common lncRNAs were performed for predicting their potential lncRNA target genes and the results confirmed the effectiveness of WAFNRLTG. The source codes and all data of WAFNRLTG can be freely downloaded at https://github.com/HGDYZW/WAFNRLTG.