Novel lncRNAs with diagnostic or prognostic value screened out from breast cancer via bioinformatics analyses.

Background: Recent studies have shown that long non-coding RNAs (lncRNAs) may play key regulatory roles in many malignant tumors. This study investigated the use of novel lncRNA biomarkers in the diagnosis and prognosis of breast cancer. Materials and Methods: The database subsets of The Cancer Genome Atlas (TCGA) by RNA-seq for comparing analysis of tissue samples between breast cancer and normal control groups were downloaded. Additionally, anticoagulant peripheral blood samples were collected and used in this cohort study. The extracellular vesicles (EVs) from the plasma were extracted and sequenced, then analyzed to determine the expressive profiles of the lncRNAs, and the cancer-related differentially expressed lncRNAs were screened out. The expressive profiles and associated downstream-mRNAs were assessed using bioinformatics (such as weighted correlation network analysis (WGCNA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) enrichments, Receiver-Operating Characteristic (ROC) curve and survival analysis, etc.) to investigate the diagnostic and prognostic values of these EV lncRNAs and their effectors. Results: In this study, 41 breast cancer-related lncRNAs were screen out from two datasets of tissue and fresh collected plasma samples of breast cancer via the transcriptomic and bioinformatics techniques. A total of 19 gene modules were identified with WGCNA analysis, of which five modules were significantly correlated with the clinical stage of breast cancer, including 28 lncRNA candidates. The ROC curves of these lncRNAs revealed that the area under the curve (AUC) of all candidates were great than 70%. However, eight lncRNAs had an AUC >70%, indicating that the combined one has a good diagnostic value. In addition, the results of survival analysis suggested that two lncRNAs with low expressive levels may indicate the poor prognosis of breast cancer. By tissue sample verification, C15orf54, AL157935.1, LINC01117, and SNHG3 were determined to have good diagnostic ability in breast cancer lesions, however, there was no significant difference in the plasma EVs of patients. Moreover, survival analysis data also showed that AL355974.2 may serve as an independent prognostic factor and as a protective factor. Conclusion: A total of five lncRNAs found in this study could be developed as biomarkers for breast cancer patients, including four diagnostic markers (C15orf54, AL157935.1, LINC01117, and SNHG3) and a potential prognostic marker (AL355974.2).

Carbon fabric supported 3D cobalt oxides/hydroxide nanosheet network as cathode for flexible all-solid-state asymmetric supercapacitor.

Owing to a lack of electroactive sites and poor conductivity, Co oxides/hydroxides nanosheet network electrodes usually show low experimental capacity, hardly meeting the demand for high energy density needed for an asymmetric supercapacitor. Herein, we demonstrate a surface capacity enhancement of a 3D cobalt oxides/hydroxides nanosheet network cathode through a simple cyclic voltammetry electro-deposition method. By optimizing the electro-deposition parameters, the as-prepared Co oxides/hydroxides nanosheet network electrode delivers a significantly high capacity of 427 C g-1 at the current density of 1 A g-1 and excellent rate ability of 79.8% at the current density of 10 A g-1, as well as outstanding cycling life. A detailed voltammetric analysis using the power-law relationship and Trasatti's method shows that both the large surface area, high pore volume and polycrystalline nature contribute to the enhancement of the surface capacity. In addition, the assembled asymmetric all-solid-state supercapacitor also presents a volume energy density of 2.78 mW h cm-3 at a power density of 14 mW cm-3 and excellent cycling stability. In addition, our prepared asymmetric supercapacitor shows super flexibility and was used to light up a heart-shaped logo. This work may provide valuable insights into the design and fabrication of electrode materials with improved capacity and rate ability.

Impacts of Mn ion in ZnSe passivation on electronic band structure for high efficiency CdS/CdSe quantum dot solar cells.

Surface passivation in quantum dot-sensitized solar cells (QDSSCs) plays a very important role in preventing surface charge recombination and thus enhancing the power conversion efficiency (PCE). ZnSe passivation with dopant in CdS/CdSe co-sensitized QDSSCs has been demonstrated as an effective way to improve the PCE. In the present study, a series of characterizations revealed that a Mn-doped ZnSe passivation layer can not only reduce surface charge recombination, but also enhance light harvesting. By means of density functional theory calculation along with a systematic study of electronic band structure, it has been found that the valence band of ZnSe moves upward on Mn-ion doping which leads to acceleration of charge separation and broader light absorption range. The impact of the Mn ion on charge recombination and light harvesting has been interpreted reasonably and the PCE of CdS/CdSe co-sensitized QDSSCs with Mn-doped ZnSe passivation layer is as high as 6.46%, which is 1.5 times that of the solar cell without the passivation layer.