Tengyue Li

CellMarker 2.0 (http://bio-bigdata.hrbmu.edu.cn/CellMarker or http://117.50.127.228/CellMarker/) is an updated database that provides a manually curated collection of experimentally supported markers of various cell types in different tissues of human and mouse. In addition, web tools for analyzing single cell sequencing data are described. We have updated CellMarker 2.0 with more data and several new features, including (i) Appending 36 300 tissue-cell type-maker entries, 474 tissues, 1901 cell types and 4566 markers over the previous version. The current release recruits 26 915 cell markers, 2578 cell types and 656 tissues, resulting in a total of 83 361 tissue-cell type-maker entries. (ii) There is new marker information from 48 sequencing technology sources, including 10X Chromium, Smart-Seq2 and Drop-seq, etc. (iii) Adding 29 types of cell markers, including protein-coding gene lncRNA and processed pseudogene, etc. Additionally, six flexible web tools, including cell annotation, cell clustering, cell malignancy, cell differentiation, cell feature and cell communication, were developed to analysis and visualization of single cell sequencing data. CellMarker 2.0 is a valuable resource for exploring markers of various cell types in different tissues of human and mouse.

Long non-coding RNAs (lncRNAs) are associated with human diseases. Although lncRNA-disease associations have received significant attention, no online repository is available to collect lncRNA-mediated regulatory mechanisms, key downstream targets, and important biological functions driven by disease-related lncRNAs in human diseases. We thus developed LncTarD (http://biocc.hrbmu.edu.cn/LncTarD/ or http://bio-bigdata.hrbmu.edu.cn/LncTarD), a manually-curated database that provides a comprehensive resource of key lncRNA-target regulations, lncRNA-influenced functions, and lncRNA-mediated regulatory mechanisms in human diseases. LncTarD offers (i) 2822 key lncRNA-target regulations involving 475 lncRNAs and 1039 targets associated with 177 human diseases; (ii) 1613 experimentally-supported functional regulations and 1209 expression associations in human diseases; (iii) important biological functions driven by disease-related lncRNAs in human diseases; (iv) lncRNA-target regulations responsible for drug resistance or sensitivity in human diseases and (v) lncRNA microarray, lncRNA sequence data and transcriptome data of an 11 373 pan-cancer patient cohort from TCGA to help characterize the functional dynamics of these lncRNA-target regulations. LncTarD also provides a user-friendly interface to conveniently browse, search, and download data. LncTarD will be a useful resource platform for the further understanding of functions and molecular mechanisms of lncRNA deregulation in human disease, which will help to identify novel and sensitive biomarkers and therapeutic targets.

Aberrant expression of long non-coding RNAs (lncRNA) is associated with altered DNA methylation and histone modifications during carcinogenesis. However, identifying epigenetically dysregulated lncRNAs and characterizing their functional mechanisms in different cancer subtypes are still major challenges for cancer studies. In this study, we systematically analyzed the epigenetic alterations of lncRNAs at important regulatory elements in three breast cancer subtypes. We identified 87, 691, and 1,197 epigenetically dysregulated lncRNAs in luminal, basal, and claudin-low subtypes of breast cancer, respectively. The landscape of epigenetically dysregulated lncRNAs at enhancer elements revealed that epigenetic changes of the majority of lncRNAs occurred in a subtype-specific manner and contributed to subtype-specific biological functions. We identified six acetylation of lysine 27 on histone H3 (H3K27ac)-dysregulated lncRNAs and three DNA methylation-dysregulated lncRNAs (CTC-303L1.2, RP11-738B7.1, and SLC26A4-AS1) as prognostic biomarkers of basal subtype. These lncRNAs were involved in immune response-related biological functions. Treatment of the basal breast cancer cell line MDA-MB-468 with CREBBP/EP300 bromodomain inhibitors downregulated H3K27 acetylation levels and caused a decrease in the expression of five H3K27ac-dysregulated lncRNAs (LINC00393, KB-1836B5.1, RP1-140K8.5, AC005162.1, and AC020916.2) and inhibition of the growth of breast cancer cells. One epigenetically dysregulated lncRNA (LINC01983) and four lncRNA regulators (UCA1, RP11-221J22.2, RP11-221J22.1, and RP1-212P9.3) were identified as prognostic biomarkers of the luminal molecular subtype of breast cancer by controlling the tumor necrosis factor (TNF) signaling pathway, T helper (Th)17 cell differentiation, and T cell migration. Finally, our results highlighted a profound role of enhancer-related H3K27ac-dysregulated lncRNAs, DNA methylation-dysregulated lncRNAs, and lncRNA regulators in breast cancer subtype carcinogenesis and their potential prognostic value.

Abstract One of the most important issues of the organic light‐emitting diode (OLED) is the highly efficient blue‐emissive material, which demands both excellent photoluminescent quantum yield (PLQY) and balanced carrier mobilities. Herein, a series of blue‐emissive donor–π–acceptor (D–π–A) materials with fluorene π‐bridge and their D–A analogues are synthesized and discovered with a theoretical combined experimental method. Based on the excellent electron mobility of the oxadiazole (OXZ) acceptor, it is further proven that the insertion of the fluorene π‐bridge can not only contribute to the formation of hybrid local and charge‐transfer excited state with high PLQY, but also give rise to the hole mobilities by enhanced intermolecular face‐to‐face stacking. As a result, the non‐doped OLED of TPACFOXZ exhibits a high maximum external quantum efficiency approaching 10% with boosted and balanced hole and electron mobilities of 5.60 × 10 −5 and 6.60 × 10 −5 cm 2 V −1 s −1 , respectively, which are among the best results of the non‐doped blue fluorescent OLEDs.

Underwater images captured by optical cameras can be degraded by light attenuation and scattering, which leads to deteriorated visual image quality. The technique of underwater image enhancement plays an important role in a wide range of subsequent applications such as image segmentation and object detection. To address this issue, we propose an underwater image enhancement framework which consists of an adaptive color restoration module and a haze-line based dehazing module. First, we employ an adaptive color restoration method to compensate the deteriorated color channels and restore the colors. The color restoration module consists of three steps: background light estimation, color recognition, and color compensation. The background light estimation determines the image is blueish or greenish, and the compensation is applied in red-green or red-blue channels. Second, the haze-line technique is employed to remove the haze and enhance the image details. Experimental results show that the proposed method can restore the color and remove the haze at the same time, and it also outperforms several state-of-the-art methods on three publicly available datasets. Moreover, experiments on an underwater object detection dataset show that the proposed underwater image enhancement method is able to improve the accuracy of the subsequent underwater object detection framework.