5\u27-Terminal nucleotide variations in human cytoplasmic tRNAHisGUG and its 5\u27-halves.

Transfer RNAs (tRNAs) are fundamental adapter components of translational machinery. tRNAs can further serve as a source of tRNA-derived noncoding RNAs that play important roles in various biological processes beyond translation. Among all species of tRNAs, tRNA(HisGUG) has been known to uniquely contain an additional guanosine residue at the -1 position (G-1) of its 5\u27-end. To analyze this -1 nucleotide in detail, we developed a TaqMan qRT-PCR method that can distinctively quantify human mature cytoplasmic tRNA(HisGUG) containing G-1, U-1, A-1, or C-1 or lacking the -1 nucleotide (starting from G1). Application of this method to the mature tRNA fraction of BT-474 breast cancer cells revealed the presence of tRNA(HisGUG) containing U-1 as well as the one containing G-1 Moreover, tRNA lacking the -1 nucleotide was also detected, thus indicating the heterogeneous expression of 5\u27-tRNA(HisGUG) variants. A sequence library of sex hormone-induced 5\u27-tRNA halves (5\u27-SHOT-RNAs), identified via cP-RNA-seq of a BT-474 small RNA fraction, also demonstrated the expression of 5\u27-tRNA(HisGUG) halves containing G-1, U-1, or G1 as 5\u27-terminal nucleotides. Although the detected 5\u27-nucleotide species were identical, the relative abundances differed widely between mature tRNA and 5\u27-half from the same BT-474 cells. The majority of mature tRNAs contained the -1 nucleotide, whereas the majority of 5\u27-halves lacked this nucleotide, which was biochemically confirmed using a primer extension assay. These results reveal the novel identities of tRNA(HisGUG) molecules and provide insights into tRNA(HisGUG) maturation and the regulation of tRNA half production

Learning RGB-D Salient Object Detection using background enclosure, depth contrast, and top-down features

Recently, deep Convolutional Neural Networks (CNN) have demonstrated strong performance on RGB salient object detection. Although, depth information can help improve detection results, the exploration of CNNs for RGB-D salient object detection remains limited. Here we propose a novel deep CNN architecture for RGB-D salient object detection that exploits high-level, mid-level, and low level features. Further, we present novel depth features that capture the ideas of background enclosure and depth contrast that are suitable for a learned approach. We show improved results compared to state-of-the-art RGB-D salient object detection methods. We also show that the low-level and mid-level depth features both contribute to improvements in the results. Especially, F-Score of our method is 0.848 on RGBD1000 dataset, which is 10.7% better than the second place

A Qualitative Study On The Meaning Of Having A Child For Mothers Who Were Abused In Their Childhood

The purpose of this research is to understand what having a child means for mothers who experienced child abuse, how their children affected the motherhood positively, and how the mothers tried to overcome their child abuse experiences. Three mothers were found as participants for the study. The data were collected by qualitative, open-ended interviews. Each of the mothers had one interview that lasted around 1-1.5 hours. The mothers\u27 lived-experiences are portrayed with analysis and in-depth interpretation. The study shows how child abuse experiences impacted the participants\u27 lives and parenting, how the participants made progress in their experiences growing up, and how raising their children had a positive effect on their lives. All the mothers faced and analyzed their present parenting. This research develops a fuller understanding of the brightness of their motherhood. These results will help and inspire other professionals, such as social workers, to understand people who have had similar experiences

デフォーの自伝フィクションにおけるオーセンティシティと自己の創造 : 回想物語の意識描写

広島大学(Hiroshima University)博士(文学)Doctor of Philosophydoctora

YAMAT-seq: an efficient method for high-throughput sequencing of mature transfer RNAs.

Besides translation, transfer RNAs (tRNAs) play many non-canonical roles in various biological pathways and exhibit highly variable expression profiles. To unravel the emerging complexities of tRNA biology and molecular mechanisms underlying them, an efficient tRNA sequencing method is required. However, the rigid structure of tRNA has been presenting a challenge to the development of such methods. We report the development of Y-shaped Adapter-ligated MAture TRNA sequencing (YAMAT-seq), an efficient and convenient method for high-throughput sequencing of mature tRNAs. YAMAT-seq circumvents the issue of inefficient adapter ligation, a characteristic of conventional RNA sequencing methods for mature tRNAs, by employing the efficient and specific ligation of Y-shaped adapter to mature tRNAs using T4 RNA Ligase 2. Subsequent cDNA amplification and next-generation sequencing successfully yield numerous mature tRNA sequences. YAMAT-seq has high specificity for mature tRNAs and high sensitivity to detect most isoacceptors from minute amount of total RNA. Moreover, YAMAT-seq shows quantitative capability to estimate expression levels of mature tRNAs, and has high reproducibility and broad applicability for various cell lines. YAMAT-seq thus provides high-throughput technique for identifying tRNA profiles and their regulations in various transcriptomes, which could play important regulatory roles in translation and other biological processes