LncSEA: a platform for long non-coding RNA related sets and enrichment analysis.

Long non-coding RNAs (lncRNAs) have been proven to play important roles in transcriptional processes and various biological functions. Establishing a comprehensive collection of human lncRNA sets is urgent work at present. Using reference lncRNA sets, enrichment analyses will be useful for analyzing lncRNA lists of interest submitted by users. Therefore, we developed a human lncRNA sets database, called LncSEA, which aimed to document a large number of available resources for human lncRNA sets and provide annotation and enrichment analyses for lncRNAs. LncSEA supports >40 000 lncRNA reference sets across 18 categories and 66 sub-categories, and covers over 50 000 lncRNAs. We not only collected lncRNA sets based on downstream regulatory data sources, but also identified a large number of lncRNA sets regulated by upstream transcription factors (TFs) and DNA regulatory elements by integrating TF ChIP-seq, DNase-seq, ATAC-seq and H3K27ac ChIP-seq data. Importantly, LncSEA provides annotation and enrichment analyses of lncRNA sets associated with upstream regulators and downstream targets. In summary, LncSEA is a powerful platform that provides a variety of types of lncRNA sets for users, and supports lncRNA annotations and enrichment analyses. The LncSEA database is freely accessible at http://bio.liclab.net/LncSEA/index.php.

HiFreSP: A novel high-frequency sub-pathway mining approach to identify robust prognostic gene signatures.

With the increasing awareness of heterogeneity in cancers, better prediction of cancer prognosis is much needed for more personalized treatment. Recently, extensive efforts have been made to explore the variations in gene expression for better prognosis. However, the prognostic gene signatures predicted by most existing methods have little robustness among different datasets of the same cancer. To improve the robustness of the gene signatures, we propose a novel high-frequency sub-pathways mining approach (HiFreSP), integrating a randomization strategy with gene interaction pathways. We identified a six-gene signature (CCND1, CSF3R, E2F2, JUP, RARA and TCF7) in esophageal squamous cell carcinoma (ESCC) by HiFreSP. This signature displayed a strong ability to predict the clinical outcome of ESCC patients in two independent datasets (log-rank test, P = 0.0045 and 0.0087). To further show the predictive performance of HiFreSP, we applied it to two other cancers: pancreatic adenocarcinoma and breast cancer. The identified signatures show high predictive power in all testing datasets of the two cancers. Furthermore, compared with the two popular prognosis signature predicting methods, the least absolute shrinkage and selection operator penalized Cox proportional hazards model and the random survival forest, HiFreSP showed better predictive accuracy and generalization across all testing datasets of the above three cancers. Lastly, we applied HiFreSP to 8137 patients involving 20 cancer types in the TCGA database and found high-frequency prognosis-associated pathways in many cancers. Taken together, HiFreSP shows higher prognostic capability and greater robustness, and the identified signatures provide clinical guidance for cancer prognosis. HiFreSP is freely available via GitHub: https://github.com/chunquanlipathway/HiFreSP.

KnockTF: a comprehensive human gene expression profile database with knockdown/knockout of transcription factors.

Transcription factors (TFs) and their target genes have important functions in human diseases and biological processes. Gene expression profile analysis before and after knockdown or knockout is one of the most important strategies for obtaining target genes of TFs and exploring TF functions. Human gene expression profile datasets with TF knockdown and knockout are accumulating rapidly. Based on the urgent need to comprehensively and effectively collect and process these data, we developed KnockTF (http://www.licpathway.net/KnockTF/index.html), a comprehensive human gene expression profile database of TF knockdown and knockout. KnockTF provides a number of resources for human gene expression profile datasets associated with TF knockdown and knockout and annotates TFs and their target genes in a tissue/cell type-specific manner. The current version of KnockTF has 570 manually curated RNA-seq and microarray datasets associated with 308 TFs disrupted by different knockdown and knockout techniques and across multiple tissue/cell types. KnockTF collects upstream pathway information of TFs and functional annotation results of downstream target genes. It provides details about TFs binding to promoters, super-enhancers and typical enhancers of target genes. KnockTF constructs a TF-differentially expressed gene network and performs network analyses for genes of interest. KnockTF will help elucidate TF-related functions and potential biological effects.

ce-Subpathway: Identification of ceRNA-mediated subpathways via joint power of ceRNAs and pathway topologies.

Competing endogenous RNAs (ceRNAs) represent a novel mechanism of gene regulation that may mediate key subpathway regions and contribute to the altered activities of pathways. However, the classical methods used to identify pathways fail to specifically consider ceRNAs within the pathways and key regions impacted by them. We proposed a powerful strategy named ce-Subpathway for the identification of ceRNA-mediated functional subpathways. It provided an effective level of pathway analysis via integrating ceRNAs, differentially expressed (DE) genes and their key regions within the given pathways. We respectively analysed one pulmonary arterial hypertension (PAH) and one myocardial infarction (MI) data sets and demonstrated that ce-Subpathway could identify many subpathways whose corresponding entire pathways were ignored by those non-ceRNA-mediated pathway identification methods. And these pathways have been well reported to be associated with PAH/MI-related cardiovascular diseases. Further evidence showed reliability of ceRNA interactions and robustness/reproducibility of the ce-Subpathway strategy by several data sets of different cancers, including breast cancer, oesophageal cancer and colon cancer. Survival analysis was finally applied to illustrate the clinical application value of the ceRNA-mediated functional subpathways using another data sets of pancreatic cancer. Comprehensive analyses have shown the power of a joint ceRNAs/DE genes and subpathway strategy based on their topologies.

Effect of biodegradable PBAT microplastics on the C and N accumulation of functional organic pools in tropical latosol.

Microplastics (MPs) pollution is becoming an emerging global stressor for soil ecosystems. However, studies on the impacts of biodegradable MPs on soil C sequestration have been mainly based on bulk C quantity, without considering the storage form of C, its persistency and N demand. To address this issue, the common poly (butylene adipate-co-terephthalate) (PBAT) was used as the model, and its effects on soil functional organic pools, including mineral-associated (MAOM), particulate (POM) and dissolved organic matter (DOM), were investigated from the novel coupled perspective of C and N stocks. After adding PBAT-MPs, the contents of soil POM-C, DOM-C, and MAOM-C were increased by 546.9 %-697.8 %, 54.2 %-90.3 %, and 13.7 %-18.9 %, respectively. Accordingly, the total C increased by 116.0 %-191.1 %. Structural equation modeling showed that soil C pools were regulated by PBAT input and microbial metabolism associated with C and N enzymes. Specifically, PBAT debris could be disguised as soil C to promote POM formation, which was the main pathway for C accumulation. Inversely, the MAOM-C and DOM-C formation was attributed to the PBAT microbial product and the selective consumption in DOM-N. Random forest model confirmed that N-activated (e.g., Nitrospirae) and PBAT-degrading bacteria (e.g., Gemmatinadetes) were important taxa for soil C accumulation, and the key enzymes were rhizopus oryzae lipas, invertase, and ammonia monooxygenase. The soil N accumulation was mainly related to the oligotrophic taxa (e.g., Chloroflexi and Ascomycota) associated with aggregate formation, decreasing the DOM-N by 46.9 %-84.3 %, but did not significantly change the total N storage and other N pools. Collectively, the findings highlight the urgency to control the nutrient imbalance risk of labile N loss and recalcitrant C enrichment in POM to avoid the depressed turnover rate of organic matter in MPs-polluted soil.

Molecular insights into effects of PBAT microplastics on latosol microbial diversity and DOM chemodiversity.

The impact of biodegradable microplastics on the microbial community and dissolved organic matter (DOM) in latosol has not been well reported. In this study, an incubation experiment at 25 ºC for 120 days using latosol amended with low (5%) and high (10%) concentrations of polybutylene adipate terephthalate (PBAT) microplastics was carried out to explore the impacts of PBAT microplastics on soil microbial communities and DOM chemodiversity, and the intrinsic interactions between their shifts. The main bacterial and fungal phyla in soil, namely Chloroflexi, Actinobacteria, Chytridiomycota, and Rozellomycota showed a nonlinear relationship with PBAT concentration and played a pivotal role in shaping DOM chemodiversity. A higher decreased levels of lignin-like compounds and increased levels of protein-like and condensed aromatic compounds in the 5% treatment were observed than that in the 10% treatment. Furthermore, a higher increase relative abundance of CHO compounds in the 5% treatment than in the 10% treatment was ascribed to its higher oxidation degree. Co-occurrence network analysis suggested that bacteria formed more complex relationships with DOM molecules than fungi did, indicating their critical roles in DOM transformation. Our study has important implications for understanding the potential influence of biodegradable microplastics on carbon biogeochemical roles in soil.

Maintaining Breastfeeding During the Treatment of Breast Abscesses Is Not Contraindicated.

Background: World Health Organization guidelines recommend maintaining breastfeeding if a woman develops breast abscess, because of benefits to her recovery and the infant's health. However, clinical staff recommend weaning to promote faster recovery from the abscess. The purpose of this study was to determine whether maintaining breastfeeding after development of a breast abscess has any influence on the resolution of the breast abscess. Methods: The records of 212 patients who were breastfeeding and developed breast abscess treated at Guangzhou Women and Children's Medical Center from January 2018 to December 2019 were retrospectively reviewed. Patients were divided into two groups: those who maintained breastfeeding (study group) and those who stopped breastfeeding (control group). Results: There were 139 patients in study group and 73 patients in the control group. Baseline characteristics were similar between the two groups. The time to cure in the study group and in the control group was 7.20 ± 2.21 days and 7.01 ± 2.39 days, respectively (t = 0.579, p = 0.563). Common complications were milk fistula and galactocele, and the frequency of both was similar between the two groups (milk fistula: 7.9% versus 8.2%, respectively; χ2 = 0.006, p = 0.938; galactocele: 8.6% versus 9.6%, respectively; χ2 = 0.054, p = 0.817). There was no significant difference in the recurrence rates between the two groups (5.0% versus 2.7%; χ2 = 0.184, p = 0.668). Conclusion: Maintaining breastfeeding during treatment of breast abscess does not affect the outcome of treatment provided, on condition that the abscess is treated appropriately.

Identification of miRNA-Mediated Subpathways as Prostate Cancer Biomarkers Based on Topological Inference in a Machine Learning Process Using Integrated Gene and miRNA Expression Data.

Accurately identifying classification biomarkers for distinguishing between normal and cancer samples is challenging. Additionally, the reproducibility of single-molecule biomarkers is limited by the existence of heterogeneous patient subgroups and differences in the sequencing techniques used to collect patient data. In this study, we developed a method to identify robust biomarkers (i.e., miRNA-mediated subpathways) associated with prostate cancer based on normal prostate samples and cancer samples from a dataset from The Cancer Genome Atlas (TCGA; n = 546) and datasets from the Gene Expression Omnibus (GEO) database (n = 139 and n = 90, with the latter being a cell line dataset). We also obtained 10 other cancer datasets to evaluate the performance of the method. We propose a multi-omics data integration strategy for identifying classification biomarkers using a machine learning method that involves reassigning topological weights to the genes using a directed random walk (DRW)-based method. A global directed pathway network (GDPN) was constructed based on the significantly differentially expressed target genes of the significantly differentially expressed miRNAs, which allowed us to identify the robust biomarkers in the form of miRNA-mediated subpathways (miRNAs). The activity value of each miRNA-mediated subpathway was calculated by integrating multiple types of data, which included the expression of the miRNA and the miRNAs' target genes and GDPN topological information. Finally, we identified the high-frequency miRNA-mediated subpathways involved in prostate cancer using a support vector machine (SVM) model. The results demonstrated that we obtained robust biomarkers of prostate cancer, which could classify prostate cancer and normal samples. Our method outperformed seven other methods, and many of the identified biomarkers were associated with known clinical treatments.

Topologically inferring active miRNA-mediated subpathways toward precise cancer classification by directed random walk.

Accurate predictions of classification biomarkers and disease status are indispensable for clinical cancer diagnosis and research. However, the robustness of conventional gene biomarkers is limited by issues with reproducibility across different measurement platforms and cohorts of patients. In this study, we collected 4775 samples from 12 different cancer datasets, which contained 4636 TCGA samples and 139 GEO samples. A new method was developed to detect miRNA-mediated subpathway activities by using directed random walk (miDRW). To calculate the activity of each miRNA-mediated subpathway, we constructed a global directed pathway network (GDPN) with genes as nodes. We then identified miRNAs with expression levels which were strongly inversely correlated with differentially expressed target genes in the GDPN. Finally, each miRNA-mediated subpathway activity was integrated with the topological information, differential levels of miRNAs and genes, expression levels of genes, and target relationships between miRNAs and genes. The results showed that the proposed method yielded a more robust and accurate overall performance compared with other existing pathway-based, miRNA-based, and gene-based classification methods. The high-frequency miRNA-mediated subpathways are more reliable in classifying samples and for selecting therapeutic strategies.

Precisely Controlled Delivery of Abaloparatide through Injectable Hydrogel to Promote Bone Regeneration.

Side-effects from allograft, limited bone stock, and site morbidity from autograft are the major challenges to traditional bone defect treatments. With the advance of tissue engineering, hydrogel injection therapy is introduced as an alternative treatment. Therapeutic drugs and growth factors can be carried by hydrogels and delivered to patients. Abaloparatide, as an analog of human recombinant parathyroid hormone protein (PTHrp) and an alternative to teriparatide, has been considered as a drug for treating postmenopausal osteoporosis since 2017. Since only limited cases of receiving abaloparatide with polymeric scaffolds have been reported, the effects of abaloparatide on pre-osteoblast MC3T3-E1 are investigated in this study. It is found that in vitro abaloparatide treatment can promote pre-osteoblast MC3T3-E1 cells' viability, differentiation, and mineralization significantly. For the drug delivery system, 3D porous structure of the methacrylated gelatin (GelMA) hydrogel is found effective for prolonging the release of abaloparatide (more than 10 days). Therefore, injectable photo-crosslinked GelMA hydrogel is used in this study to prolong the release of abaloparatide and to promote healing of defected bones in rats. Overall, data collected in this study show no contradiction and imply that Abaloparatide-loaded GelMA hydrogel is effective in stimulating bone regeneration.

Strontium inhibits osteoclastogenesis by enhancing LRP6 and ß-catenin-mediated OPG targeted by miR-181d-5p.

Strontium is a drug with the bone formation and anti-resorption effects on bone. The underlying mechanisms for the dual effect of strontium on bone metabolism, especially for the anti-resorption effects remain unknown. Thus, we aim to investigate the mechanisms of effects of strontium on osteoclastogenesis. Firstly, we found that strontium decreased the levels of important biomarkers of receptor activator of nuclear factor kappa-B ligand (RANKL) which induced osteoclast differentiation, indicating that strontium might directly inhibit osteoclast differentiation. Next, we revealed that strontium enhanced Low Density Lipoprotein Receptor-Related Protein 6 (LRP6)/ß-catenin/osteoprotegerin (OPG) signaling pathway in MC3T3-E1 cells. The signaling pathway may negatively regulate osteoclastogenesis. Thus, strontium indirectly inhibited RANKL induced osteoclast differentiation. Finally, we revealed that OPG was targeted by miR-181d-5p as determined by luciferase reporter assay and downregulated by miR-181d-5p at both mRNA and protein levels as determined by western blot.

Transfer of Extracellular Vesicle-Associated-RNAs Induces Drug Resistance in ALK-Translocated Lung Adenocarcinoma.

Anaplastic lymphoma kinase (ALK) translocation is an actionable mutation in lung adenocarcinoma. Nonetheless tumour consists of heterogeneous cell subpopulations with diverse phenotypes and genotypes, and cancer cells can actively release extracellular vesicles (EVs) to modulate the phenotype of other cells in the tumour microenvironment. We hypothesized that EVs derived from a drug-resistant subpopulation of cells could induce drug resistance in recipient cells. We have established ALK-translocated lung adenocarcinoma cell lines and subclones. The subclones have been characterized and the expression of EV-RNAs determined by quantitative polymerase chain reaction. The effects of EV transfer on drug resistance were examined in vitro. Serum EV-RNA was assayed serially in two patients prescribed ALK-tyrosine kinase inhibitor (ALK-TKI) treatment. We demonstrated that the EVs from an ALK-TKI-resistant subclone could induce drug resistance in the originally sensitive subclone. EV-RNA profiling revealed that miRNAs miR-21-5p and miR-486-3p, and lncRNAs MEG3 and XIST were differentially expressed in the EVs secreted by the resistant subclones. These circulating EV-RNA levels have been found to correlate with disease progression of EML4-ALK-translocated lung adenocarcinoma in patients prescribed ALK-TKI treatment. The results from this study suggest that EVs released by a drug-resistant subpopulation can induce drug resistance in other subpopulations and may sustain intratumoural heterogeneity.

miR-375-3p negatively regulates osteogenesis by targeting and decreasing the expression levels of LRP5 and ß-catenin.

Wnt signaling pathways are essential for bone formation. Previous studies showed that Wnt signaling pathways were regulated by miR-375. Thus, we aim to explore whether miR-375 could affect osteogenesis. In the present study, we investigated the roles of miR-375 and its downstream targets. Firstly, we revealed that miR-375-3p negatively modulated osteogenesis by suppressing positive regulators of osteogenesis and promoting negative regulators of osteogenesis. In addition, the results of TUNEL cell apoptosis assay showed that miR-375-3p induced MC3T3-E1 cell apoptosis. Secondly, miR-375-3p targeted low-density lipoprotein receptor-related protein 5 (LRP5), a co-receptor of the Wnt signaling pathways, and ß-catenin as determined by luciferase activity assay, and it decreased the expression levels of LRP5 and ß-catenin. Thirdly, the decline of protein levels of ß-catenin was determined by immunocytochemistry and immunofluorescence. Finally, silence of LRP5 in osteoblast precursor cells resulted in diminished cell viability and cell proliferation as detected by WST-1-based colorimetric assay. Additionally, all the parameters including the relative bone volume from µCT measurement suggested that LRP5 knockout in mice resulted in a looser and worse-connected trabeculae. The mRNA levels of important negative modulators relating to osteogenesis increased after the functions of LRP5 were blocked in mice. Last but not least, the expression levels of LRP5 increased during the osteogenesis of MC3T3-E1, while the levels of ß-catenin decreased in bone tissues from osteoporotic patients with vertebral compression fractures. In conclusion, we revealed miR-375-3p negatively regulated osteogenesis by targeting LRP5 and ß-catenin. In addition, loss of functions of LRP5 damaged bone formation in vivo. Clinically, miR-375-3p and its targets might be used as diagnostic biomarkers for osteoporosis and might be also as novel therapeutic agents in osteoporosis treatment. The relevant products of miR-375-3p might be developed into molecular drugs in the future. These molecules could be used in translational medicine.