Identification of cancer hallmark‐associated gene and lncRNA cooperative regulation pairs and dictate lncRNA roles in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is the most common malignant tumour in the oral and maxillofacial region. Numerous cancers share ten common traits (“hallmarks”) that govern the transformation of normal cells into cancer cells. Long non‐coding RNAs (lncRNAs) are important factors that contribute to tumorigenesis. However, very little is known about the cooperative relationships between lncRNAs and cancer hallmark‐associated genes in OSCC. Through integrative analysis of cancer hallmarks, somatic mutations, copy number variants (CNVs) and expression, some OSCC‐specific cancer hallmark‐associated genes and lncRNAs are identified. A computational framework to identify gene and lncRNA cooperative regulation pairs (GLCRPs) associated with different cancer hallmarks is developed based on the co‐expression and co‐occurrence of mutations. The distinct and common features of ten cancer hallmarks based on GLCRPs are characterized in OSCC. Cancer hallmark insensitivity to antigrowth signals and self‐sufficiency in growth signals are shared by most GLCRPs in OSCC. Some key GLCRPs participate in many cancer hallmarks in OSCC. Cancer hallmark‐associated GLCRP networks have complex patterns and specific functions in OSCC. Specially, some key GLCRPs are associated with the prognosis of OSCC patients. In summary, we generate a comprehensive landscape of cancer hallmark‐associated GLCRPs that can act as a starting point for future functional explorations, the identification of biomarkers and lncRNA‐based targeted therapy in OSCC.     

LNRLMI: Linear neighbour representation for predicting lncRNA‐miRNA interactions

LncRNA and miRNA are key molecules in mechanism of competing endogenous RNAs(ceRNA), and their interactions have been discovered with important roles in gene regulation. As supplementary to the identification of lncRNA‐miRNA interactions from CLIP‐seq experiments, in silico prediction can select the most potential candidates for experimental validation. Although developing computational tool for predicting lncRNA‐miRNA interaction is of great importance for deciphering the ceRNA mechanism, little effort has been made towards this direction. In this paper, we propose an approach based on linear neighbour representation to predict lncRNA‐miRNA interactions (LNRLMI). Specifically, we first constructed a bipartite network by combining the known interaction network and similarities based on expression profiles of lncRNAs and miRNAs. Based on such a data integration, linear neighbour representation method was introduced to construct a prediction model. To evaluate the prediction performance of the proposed model, k‐fold cross validations were implemented. As a result, LNRLMI yielded the average AUCs of 0.8475 ± 0.0032, 0.8960 ± 0.0015 and 0.9069 ± 0.0014 on 2‐fold, 5‐fold and 10‐fold cross validation, respectively. A series of comparison experiments with other methods were also conducted, and the results showed that our method was feasible and effective to predict lncRNA‐miRNA interactions via a combination of different types of useful side information. It is anticipated that LNRLMI could be a useful tool for predicting non‐coding RNA regulation network that lncRNA and miRNA are involved in.     

An Antiaging Electrolyte Additive for High‐Energy‐Density Lithium‐Ion Batteries

High‐capacity Li‐rich layered oxide cathodes along with Si‐incorporated graphite anodes have high reversible capacity, outperforming the electrode materials used in existing commercial products. Hence, they are potential candidates for the development of high‐energy‐density lithium‐ion batteries (LIBs). However, structural degradation induced by loss of interfacial stability is a roadblock to their practical use. Here, the use of malonic acid‐decorated fullerene (MA‐C₆₀) with superoxide dismutase activity and water scavenging capability as an electrolyte additive to overcome the structural instability of high‐capacity electrodes that hampers the battery quality is reported. Deactivation of PF₅ by water scavenging leads to the long‐term stability of the interfacial structures of electrodes. Moreover, an MA‐C₆₀‐added electrolyte deactivates the reactive oxygen species and constructs an electrochemically robust cathode‐electrolyte interface for Li‐rich cathodes. This work paves the way for new possibilities in the design of electrolyte additives by eliminating undesirable reactive substances and tuning the interfacial structures of high‐capacity electrodes in LIBs.     

Rational Design of Core@shell Structured CoSx@Cu2MoS4 Hybridized MoS2/N,S‐Codoped Graphene as Advanced Electrocatalyst for Water Splitting and Zn‐Air Battery

A novel hybrid of small core@shell structured CoS_x@Cu₂MoS₄ uniformly hybridizing with a molybdenum dichalcogenide/N,S‐codoped graphene hetero‐network (CoS_x@Cu₂MoS₄‐MoS₂/NSG) is prepared by a facile route. It shows excellent performance toward the oxygen reduction reaction (ORR), oxygen evolution reaction (OER), and hydrogen evolution reaction (HER) in alkaline medium. The hybrid exhibits rapid kinetics for ORR with high electron transfer number of ≈3.97 and exciting durability superior to commercial Pt/C. It also demonstrates great potential with remarkable stability for HER and OER, requiring low overpotential of 118.1 and 351.4 mV, respectively, to reach a current density of 10 mA cm^?2. An electrolyzer based on CoS_x@Cu₂MoS₄‐MoS₂/NSG produces low cell voltage of 1.60 V and long‐term stability, surpassing a device of Pt/C + RuO₂/C. In addition, a Zn‐air battery using cathodic CoS_x@Cu₂MoS₄‐MoS₂/NSG catalyst delivers a high cell voltage of ≈1.44 V and a power density of 40 mW cm^?2 at 58 mA cm^?2, better than the state‐of‐the‐art Pt/C catalyst. These achievements are due to the rational combination of highly active core@shell CoS_x@Cu₂MoS₄ with large‐area and high‐porosity MoS₂/NSG to produce unique physicochemical properties with multi‐integrated active centers and synergistic effects. The outperformances of such catalyst suggest an advanced candidate for multielectrocatalysis applications in metal‐air batteries and hydrogen production.     

New Class of Ni‐Rich Cathode Materials Li[NixCoyB1−x−y]O2 for Next Lithium Batteries

A new class of layered cathodes, Li[Ni_xCo_yB_1?x?y]O₂ (NCB), is synthesized. The proposed NCB cathodes have a unique microstructure in which elongated primary particles are tightly packed into spherical secondary particles. The cathodes also exhibit a strong crystallographic texture in which the a–b layer planes are aligned along the radial direction, facilitating Li migration. The microstructure, which effectively suppresses the formation of microcracks, improves the cycling stability of the NCB cathodes. The NCB cathode with 1.5 mol% B delivers a discharge capacity of 234 mAh g^?1 at 0.1 C and retains 91.2% of its initial capacity after 100 cycles (compared to values of 229 mAh g^?1 at 0.1 C and 78.8% for pristine Li[Ni_0.9Co_0.1]O₂). This study shows the importance of controlling the microstructure to obtain the required cycling stability, especially for Ni‐rich layered cathodes, where the main cause of capacity fading is related to mechanical strain in their charged state.     

不同病理分期肺腺癌患者血清代谢组学研究

肺癌是当今世界最常见的恶性肿瘤之一,其新发率和死亡率多年来都居于各类癌症之首,其中85%的肺癌都是非小细胞癌,而腺癌又是最常见的非小细胞癌。肺癌的高隐匿性是造成其高死亡率的最主要原因,因此为肺癌的早期诊断和病理分期寻求高效可靠的方法是十分必要的。代谢组学揭示了小分子代谢物的一系列变化,反映了生命活动的最终状态,因此也能直接反映疾病不同发展阶段的病理生理变化。本研究利用核磁共振氢谱(1H-NMR),对在我院就诊的27例不同病理分期的肺腺癌患者和13例健康志愿者进行了血清代谢物分析,运用正交偏最小二乘判别分析(OPLS-DA)对1H-NMR数据进行建模,单变量统计分析对模型进行评价。结果表明肺腺癌患者组的血清中有14种代谢物出现明显差异,其中丙酮酸、丙氨酸、NAC1、乳酸、GPC和甘氨酸比起对照组来有显著上升,而葡萄糖、谷氨酰胺、亮氨酸、异亮氨酸、缬氨酸、丙酮、乙酰乙酸和苏氨酸则显著下降。而在不同分期肺腺癌患者间进行比较后发现,异亮氨酸、乙酰乙酸、NAC1和乳酸的变化与肺腺癌的发展有相关性,可能是肺腺癌早期诊断和分期的潜在生物标志物。