LBX2-AS1 promotes ovarian cancer progression by facilitating E2F2 gene expression via miR-455-5p and miR-491-5p sponging

LBX2-AS1 is a long non-coding RNA that facilitates the development of gastrointestinal cancers and lung cancer, but its participation in ovarian cancer development remained uninvestigated. Clinical data retrieved from TCGA ovarian cancer database and the clinography of 60 ovarian cancer patients who received anti-cancer treatment in our facility were analysed. The overall cell growth, colony formation, migration, invasion, apoptosis and tumour formation on nude mice of ovarian cancer cells were evaluated before and after lentiviral-based LBX2-AS1 knockdown. ENCORI platform was used to explore LBX2-AS1-interacting microRNAs and target genes of the candidate microRNAs. Luciferase reporter gene assay and RNA pulldown assay were used to verify the putative miRNA-RNA interactions. Ovarian cancer tissue specimens showed significant higher LBX2-AS1 expression levels that non-cancerous counterparts. High expression level of LBX2-AS1 was significantly associated with reduced overall survival of patients. LBX2-AS1 knockdown significantly down-regulated the cell growth, colony formation, migration, invasion and tumour formation capacity of ovarian cancer cells and increased their apoptosis in vitro. LBX2-AS1 interacts with and thus inhibits the function of miR-455-5p and miR-491-5p, both of which restrained the expression of E2F2 gene in ovarian cancer cells via mRNA targeting. Transfection of miRNA inhibitors of these two miRNAs or forced expression of E2F2 counteracted the effect of LBX2-AS1 knockdown on ovarian cancer cells. LBX2-AS1 was a novel cancer-promoting lncRNA in ovarian cancer. This lncRNA increased the cell growth, survival, migration, invasion and tumour formation of ovarian cancer cells by inhibiting miR-455-5p and miR-491-5p, thus liberating the expression of E2F2 cancer-promoting gene.     

Construction of a robust prognostic model for adult adrenocortical carcinoma: Results from bioinformatics and real-world data

This study aims to construct a robust prognostic model for adult adrenocortical carcinoma (ACC) by large-scale multiomics analysis and real-world data. The RPPA data, gene expression profiles and clinical information of adult ACC patients were obtained from The Cancer Proteome Atlas (TCPA), Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Integrated prognosis-related proteins (IPRPs) model was constructed. Immunohistochemistry was used to validate the prognostic value of the IPRPs model in Fudan University Shanghai Cancer Center (FUSCC) cohort. 76 ACC cases from TCGA and 22 ACC cases from GSE10927 in NCBI’s GEO database with full data for clinical information and gene expression were utilized to validate the effectiveness of the IPRPs model. Higher FASN (P = .039), FIBRONECTIN (P < .001), TFRC (P < .001), TSC1 (P < .001) expression indicated significantly worse overall survival for adult ACC patients. Risk assessment suggested significantly a strong predictive capacity of IPRPs model for poor overall survival (P < .05). IPRPs model showed a little stronger ability for predicting prognosis than Ki-67 protein in FUSCC cohort (P = .003, HR = 3.947; P = .005, HR = 3.787). In external validation of IPRPs model using gene expression data, IPRPs model showed strong ability for predicting prognosis in TCGA cohort (P = .005, HR = 3.061) and it exhibited best ability for predicting prognosis in GSE10927 cohort (P = .0898, HR = 2.318). This research constructed IPRPs model for predicting adult ACC patients’ prognosis using proteomic data, gene expression data and real-world data and this prognostic model showed stronger predictive value than other biomarkers (Ki-67, Beta-catenin, etc) in multi-cohorts.     

Metabolomics and lipid profile analysis of Coccomyxa melkonianii SCCA 048

Extremophiles - With an unsupervised GC–MS metabolomics approach, polar metabolite changes of the microalgae Coccomyxa melkonianii SCCA 048 grown under standard conditions for seven weeks...     

MiR-467a-5p aggravates myocardial infarction by modulating ZEB1 expression in mice

Journal of Molecular Histology - Myocardial infarction (MI) is a great threat to patients all over the word. MicroRNAs (miRNAs) are a group of non-coding RNAs and can regulate initiation and...     

传粉昆虫下降背景下的授粉生态弹性: 内涵、机制和展望

全球传粉昆虫多样性正在下降, 如何保障农林生态系统传粉功能是当前研究的热点。理论上说, 传粉功能不仅与生态系统的传粉昆虫多样性相关, 还与生态系统的调节能力有关。近年来, 学者们逐渐认识到授粉生态弹性对传粉功能的影响。本文在回顾已有研究的基础之上, 总结传粉昆虫授粉生态弹性的内涵, 厘清授粉生态弹性与工程弹性、稳定性和抗性的异同。目前, 学者对授粉生态弹性形成机制开展广泛探讨, 提出功能冗余假说、密度补偿假说、响应多样性假说、连接周转假说和跨尺度弹性假说, 但这5个假说间的关系仍不清楚, 存在一词多义、词意混淆等现象。我们依次阐述功能冗余假说、密度补偿假说、响应多样性假说、连接周转假说和跨尺度弹性假说, 介绍不同假说中授粉生态弹性形成过程、研究热点和发展动态。通过解析授粉生态弹性的形成机制可知, 5个假说在内涵上存在紧密联系, 它们从不同空间尺度和研究对象下解释传粉昆虫授粉生态弹性的形成机制。未来授粉生态弹性研究将整合传粉昆虫群落动态和传粉功能动态的量化方法, 通过实验验证5个假说的合理性, 并揭示不同假说间的联系, 由此阐明授粉生态弹性的发生条件、形成阈值和动态规律。随着研究的深入, 授粉生态弹性理论有望用于指导农林生态系统传粉功能的经营管理。     

Restoration of circPSMC3 sensitizes gefitinib-resistant esophageal squamous cell carcinoma cells to gefitinib by regulating miR-10a-5p/PTEN axis

Circular RNAs (circRNAs) has been shown to play an important role in the progression of various cancers. However, the function and underlying mechanisms of circRNAs affecting chemotherapy resistance in esophageal squamous cell carcinoma (ESCC) remain largely unknown. In this study, we used gefitinib-resistant (GR) ESCC cells to investigate the function of circPSMC3 and clarify the underlying mechanism in chemotherapy resistance in ESCC. The results suggested that circPSMC3 expression was downregulated, but miR-10a-5p was upregulated in ESCC tissues and cells, as well as in GR ESCC cells. CircPSMC3 overexpression increased the sensitivity of ESCC cells to gefitinib, as indicated by reduced half maximal inhibitory concentration value, increased apoptosis rate and cleaved caspase-3 protein expression. CircPSMC3 directly interacted with miR-10a-5p and inhibited the expression of miR-10a-5p. Phosphatase and tensin homolog (PTEN) was a direct target of miR-10a-5p and circPSMC3 promoted PTEN expression via decreasing miR-10a-5p level. Moreover, the effect of circPSMC3 on resistance of GR ESCC cells to gefitinib was remarkably reduced by restoration of miR-10a-5p and downregultion of PTEN. Taken together, these observations suggested that upregulation of circPSMC3 overcame resistance of GR ESCC cells to gefitinib by modulating the miR-10a-5p/PTEN axis, which provide a new therapeutic strategy for overcoming gefitinib resistance in ESCC.     

Genistein-3′-sodium sulfonate Attenuates Neuroinflammation in Stroke Rats by Down-Regulating Microglial M1 Polarization through α7nAChR-NF-κB Signaling Pathway

Microglial M1 depolarization mediated prolonged inflammation contributing to brain injury in ischemic stroke. Our previous study revealed that Genistein-3′-sodium sulfonate (GSS) exerted neuroprotective effects in ischemic stroke. This study aimed to explore whether GSS protected against brain injury in ischemic stroke by regulating microglial M1 depolarization and its underlying mechanisms. We established transient middle cerebral artery occlusion and reperfusion (tMCAO) model in rats and used lipopolysaccharide (LPS)-stimulated BV2 microglial cells as in vitro model. Our results showed that GSS treatment significantly reduced the brain infarcted volume and improved the neurological function in tMCAO rats. Meanwhile, GSS treatment also dramatically reduced microglia M1 depolarization and IL-1β level, reversed α7nAChR expression, and inhibited the activation of NF-κB signaling in the ischemic penumbra brain regions. These effects of GSS were further verified in LPS-induced M1 depolarization of BV2 cells. Furthermore, pretreatment of α7nAChR inhibitor (α-BTX) significantly restrained the neuroprotective effect of GSS treatment in tMCAO rats. α-BTX also blunted the regulating effects of GSS on neuroinflammation, M1 depolarization and NF-κB signaling activation. This study demonstrates that GSS protects against brain injury in ischemic stroke by reducing microglia M1 depolarization to suppress neuroinflammation in peri-infarcted brain regions through upregulating α7nAChR and thereby inhibition of NF-κB signaling. Our findings uncover a potential molecular mechanism for GSS treatment in ischemic stroke.     

Modeling vegetation greenness and its climate sensitivity with deep‐learning technology

Climate sensitivity of vegetation has long been explored using statistical or process‐based models. However, great uncertainties still remain due to the methodologies’ deficiency in capturing the complex interactions between climate and vegetation. Here, we developed global gridded climate–vegetation models based on long short‐term memory (LSTM) network, which is a powerful deep‐learning algorithm for long‐time series modeling, to achieve accurate vegetation monitoring and investigate the complex relationship between climate and vegetation. We selected the normalized difference vegetation index (NDVI) that represents vegetation greenness as model outputs. The climate data (monthly temperature and precipitation) were used as inputs. We trained the networks with data from 1982 to 2003, and the data from 2004 to 2015 were used to validate the models. Error analysis and sensitivity analysis were performed to assess the model errors and investigate the sensitivity of global vegetation to climate change. Results show that models based on deep learning are very effective in simulating and predicting the vegetation greenness dynamics. For models training, the root mean square error (RMSE) is <0.01. Model validation also assure the accuracy of our models. Furthermore, sensitivity analysis of models revealed a spatial pattern of global vegetation to climate, which provides us a new way to investigate the climate sensitivity of vegetation. Our study suggests that it is a good way to integrate deep‐learning method to monitor the vegetation change under global change. In the future, we can explore more complex climatic and ecological systems with deep learning and coupling with certain physical process to better understand the nature.     

Toxicity of gold nanoparticles (AuNPs): A review

Gold nanoparticles are a kind of nanomaterials that have received great interest in field of biomedicine due to their electrical, mechanical, thermal, chemical and optical properties. With these great potentials came the consequence of their interaction with biological tissues and molecules which presents the possibility of toxicity. This paper aims to consolidate and bring forward the studies performed that evaluate the toxicological aspect of AuNPs which were categorized into in vivo and in vitro studies. Both indicate to some extent oxidative damage to tissues and cell lines used in vivo and in vitro respectively with the liver, spleen and kidney most affected. The outcome of these review showed small controversy but however, the primary toxicity and its extent is collectively determined by the characteristics, preparations and physicochemical properties of the NPs. Some studies have shown that AuNPs are not toxic, though many other studies contradict this statement. In order to have a holistic inference, more studies are required that will focus on characterization of NPs and changes of physical properties before and after treatment with biological media. So also, they should incorporate controlled experiment which includes supernatant control Since most studies dwell on citrate or CTAB-capped AuNPs, there is the need to evaluate the toxicity and pharmacokinetics of functionalized AuNPs with their surface composition which in turn affects their toxicity. Functionalizing the NPs surface with more peculiar ligands would however help regulate and detoxify the uptake of these NPs.