TNF-α Promotes IFN-γ-Induced CD40 Expression and Antigen Process in Myb-Transformed Hematological Cells

Tumour necrosis factor-α, interferon-γ and interleukin-4 are critical cytokines in regulating the immune responses against infections and tumours. In this study, we investigated the effects of three cytokines on CD40 expression in Myb-transformed hematological cells and their regulatory roles in promoting these cells into dendritic cells. We observed that both interleukin-4 and interferon-γ increased CD40 expression in these hematological cells in a dose-dependent manner, although the concentration required for interleukin-4 was significantly higher than that for interferon-γ. We found that tumour necrosis factor-α promoted CD40 expression induced by interferon-γ, but not by interleukin-4. Our data showed that tumour necrosis factor-α plus interferon-γ-treated Myb-transformed hematological cells had the greatest ability to take up and process the model antigen DQ-Ovalbumin. Tumour necrosis factor-α also increased the ability of interferon-γ to produce the mixed lymphocyte reaction to allogenic T cells. Furthermore, only cotreatment with tumour necrosis factor-α and interferon-γ induced Myb-transformed hematological cells to express interleukin-6. These results suggest that tumour necrosis factor-α plays a key regulatory role in the development of dendritic cells from hematological progenitor cells induced by interferon-γ

A Novel Joint Gene Set Analysis Framework Improves Identification of Enriched Pathways in Cross Disease Transcriptomic Analysis

Motivation: Gene set enrichment analysis is a widely accepted expression analysis tool which aims at detecting coordinated expression change within a pre-defined gene sets rather than individual genes. The benefit of gene set analysis over individual differentially expressed (DE) gene analysis includes more reproducible and interpretable results and detecting small but consistent change among gene set which could not be detected by DE gene analysis. There have been many successful gene set analysis applications in human diseases. However, when the sample size of a disease study is small and no other public data sets of the same disease are available, it will lead to lack of power to detect pathways of importance to the disease.Results: We have developed a novel joint gene set analysis statistical framework which aims at improving the power of identifying enriched gene sets through integrating multiple similar disease data sets. Through comprehensive simulation studies, we demonstrated that our proposed frameworks obtained much better AUC scores than single data set analysis and another meta-analysis method in identification of enriched pathways. When applied to two real data sets, the proposed framework could retain the enriched gene sets identified by single data set analysis and exclusively obtained up to 200% more disease-related gene sets demonstrating the improved identification power through information shared between similar diseases. We expect that the proposed framework would enable researchers to better explore public data sets when the sample size of their study is limited

Single image super resolution based on multi-scale structure and non-local smoothing

In this paper, we propose a hybrid super-resolution method by combining global and local dictionary training in the sparse domain. In order to present and differentiate the feature mapping in different scales, a global dictionary set is trained in multiple structure scales, and a non-linear function is used to choose the appropriate dictionary to initially reconstruct the HR image. In addition, we introduce the Gaussian blur to the LR images to eliminate a widely used but inappropriate assumption that the low resolution (LR) images are generated by bicubic interpolation from high-resolution (HR) images. In order to deal with Gaussian blur, a local dictionary is generated and iteratively updated by K-means principal component analysis (K-PCA) and gradient decent (GD) to model the blur effect during the down-sampling. Compared with the state-of-the-art SR algorithms, the experimental results reveal that the proposed method can produce sharper boundaries and suppress undesired artifacts with the present of Gaussian blur. It implies that our method could be more effect in real applications and that the HR-LR mapping relation is more complicated than bicubic interpolation

tRNASer(CGA) differentially regulates expression of wild-type and codon-modified papillomavirus L1 genes

Exogenous transfer RNAs (tRNAs) favor translation of bovine papillomavirus 1 wild-type (wt) L1 mRNA in in vitro translation systems (Zhou et al. 1999, J. Virol., 73, 4972-4982). We, therefore, investigated whether papillomavirus (PV) wt L1 protein expression could be enhanced in eukaryotic cells following exogenous tRNA supplementation. Both Chinese hamster ovary (CHO) and Cos1 cells, transfected with PV1 wt L1 genes, effectively transcribed the genes but did not translate them. However, L1 protein translation was demonstrated following co-transfection with the L1 gene and a gene expressing tRNA(Ser)(CGA). Cell lines, stably transfected with a bovine papillomavirus 1 (BPV1) wt L1 expression construct, produced L1 protein after the transfection of the tRNA(Ser)(CGA) gene, but not following the transfection with basal vectors, suggesting that tRNA(Ser)(CGA) gene enhanced wt L1 translation as a result of endogenous tRNA alterations and phosphorylation of translation initiation factors elF4E and elF2alpha in the tRNA(Ser)(CGA) transfected L1 cell lines. The tRNA(Ser)(CGA) gene expression significantly reduced translation of L1 proteins expressed from codon-modified (HB) PV L1 genes utilizing mammalian preferred codons, but had variable effects on translation of green fluorescent proteins (GFPs) expressed from six serine GFP variants. The changes of tRNA pools appear to match the codon composition of PV wt and HB L1 genes and serine GFP variants to regulate translation of their mRNAs. These findings demonstrate for the first time in eukaryotic cells that translation of the target genes can be differentially influenced by the provision of a single tRNA expression construct

RAI-Net: Range-Adaptive LiDAR Point Cloud Frame Interpolation Network

LiDAR point cloud frame interpolation, which synthesizes the intermediate frame between the captured frames, has emerged as an important issue for many applications. Especially for reducing the amounts of point cloud transmission, it is by predicting the intermediate frame based on the reference frames to upsample data to high frame rate ones. However, due to high-dimensional and sparse characteristics of point clouds, it is more difficult to predict the intermediate frame for LiDAR point clouds than videos. In this paper, we propose a novel LiDAR point cloud frame interpolation method, which exploits range images (RIs) as an intermediate representation with CNNs to conduct the frame interpolation process. Considering the inherited characteristics of RIs differ from that of color images, we introduce spatially adaptive convolutions to extract range features adaptively, while a high-efficient flow estimation method is presented to generate optical flows. The proposed model then warps the input frames and range features, based on the optical flows to synthesize the interpolated frame. Extensive experiments on the KITTI dataset have clearly demonstrated that our method consistently achieves superior frame interpolation results with better perceptual quality to that of using state-of-the-art video frame interpolation methods. The proposed method could be integrated into any LiDAR point cloud compression systems for inter prediction.Comment: Accepted by the IEEE International Symposium on Broadband Multimedia Systems and Broadcasting 202

Generalized substitution of isoencoding codons shortens the duration of papillomavirus L1 protein expression in transiently gene-transfected keratinocytes due to cell differentiation

Recently we reported that gene codon composition determines differentiation-dependent expression of the PV L1 genes in mouse primary keratinocytes (KCs) in vitro and in vivo (Zhao et al. 2005, Mol. Cell Biol. 25:8643–8655). Here, we investigated whether generalized substitution of isoencoding codons affects the duration of expression of PV L1 genes in mouse and human KCs in day 1 culture transiently transfected with native (Nat) and codon modified (Mod) L1 genes. Following transient transfection, KC continuously transcribed both Nat and Mod PV L1 genes for at least 12 days, with the levels of L1 mRNAs from the Mod L1 genes significantly higher than those from the Nat L1 genes. However, continuous L1 protein expression at day 9 post-transfection was observed for both mouse and human KCs transfected with the Nat L1 genes only. Further, aa-tRNAs prepared from D8 KC cultures enhanced translation of two PV Nat L1 DNAs in RRL lysate and PV Nat L1 mRNAs in D0 cell-free lysate, whereas aa-tRNAs from D0 KCs enhanced translation of PV Mod L1 mRNAs in D8 cell-free lysate. It appears that aa-tRNAs in less-differentiated and differentiated KCs differentially match the PV Nat and Mod L1 mRNAs to regulate their translations in vitro