Real-Time 6D Object Pose Estimation on CPU

We propose a fast and accurate 6D object pose estimation from a RGB-D image. Our proposed method is template matching based and consists of three main technical components, PCOF-MOD (multimodal PCOF), balanced pose tree (BPT) and optimum memory rearrangement for a coarse-to-fine search. Our model templates on densely sampled viewpoints and PCOF-MOD which explicitly handles a certain range of 3D object pose improve the robustness against background clutters. BPT which is an efficient tree-based data structures for a large number of templates and template matching on rearranged feature maps where nearby features are linearly aligned accelerate the pose estimation. The experimental evaluation on tabletop and bin-picking dataset showed that our method achieved higher accuracy and faster speed in comparison with state-of-the-art techniques including recent CNN based approaches. Moreover, our model templates can be trained only from 3D CAD in a few minutes and the pose estimation run in near real-time (23 fps) on CPU. These features are suitable for any real applications.Comment: accepted to IROS 201

Effects of 6-month eicosapentaenoic acid treatment on postprandial hyperglycemia, hyperlipidemia, insulin secretion ability, and concomitant endothelial dysfunction among newly-diagnosed impaired glucose metabolism patients with coronary artery disease. An open label, single blinded, prospective randomized controlled trial

Additional file 2: Table S2. Comparison of cookie meal test data between baseline and 6 months, and comparison of absolute change from baseline among patients with baseline plasma glucose <110 mg/dL

Attention network for predicting T-cell receptor–peptide binding can associate attention with interpretable protein structural properties

Koyama K., Hashimoto K., Nagao C., et al. Attention network for predicting T-cell receptor–peptide binding can associate attention with interpretable protein structural properties. Frontiers in Bioinformatics 3, 1274599 (2023); https://doi.org/10.3389/fbinf.2023.1274599.Understanding how a T-cell receptor (TCR) recognizes its specific ligand peptide is crucial for gaining an insight into biological functions and disease mechanisms. Despite its importance, experimentally determining TCR–peptide–major histocompatibility complex (TCR–pMHC) interactions is expensive and time-consuming. To address this challenge, computational methods have been proposed, but they are typically evaluated by internal retrospective validation only, and few researchers have incorporated and tested an attention layer from language models into structural information. Therefore, in this study, we developed a machine learning model based on a modified version of Transformer, a source–target attention neural network, to predict the TCR–pMHC interaction solely from the amino acid sequences of the TCR complementarity-determining region (CDR) 3 and the peptide. This model achieved competitive performance on a benchmark dataset of the TCR–pMHC interaction, as well as on a truly new external dataset. Additionally, by analyzing the results of binding predictions, we associated the neural network weights with protein structural properties. By classifying the residues into large- and small-attention groups, we identified statistically significant properties associated with the largely attended residues such as hydrogen bonds within CDR3. The dataset that we created and the ability of our model to provide an interpretable prediction of TCR–peptide binding should increase our knowledge about molecular recognition and pave the way for designing new therapeutics

有害作用低減を志向したヒストン脱アセチル化酵素阻害法の開発 [論文要旨及び審査の要旨]

関西大学博士（工学）thesi

有害作用低減を志向したヒストン脱アセチル化酵素阻害法の開発

関西大学博士（工学）doctoral thesi

Porphyromonas gingivalis Clearance by SIgA

Our previous studies showed that a combination of a DNA plasmid encoding Flt3 ligand (pFL) and CpG oligodeoxynucleotides 1826 (CpG ODN) (FL/CpG) as a nasal adjuvant provoked antigen-specific immune responses. In this study, we investigated the efficacy of a nasal vaccine consisting of FimA as the structural subunit of Porphyromonas gingivalis (P. gingivalis) fimbriae and FL/CpG for the induction of FimA-specific antibody (Ab) responses and their protective roles against nasal and lung infection by P. gingivalis, a keystone pathogen in the etiology of periodontal disease. C57BL/6 mice were nasally immunized with recombinant FimA (rFimA) plus FL/CpG three times at weekly intervals. As a control, mice were given nasal rFimA alone. Nasal washes (NWs) and bronchoalveolar lavage fluid (BALF) of mice given nasal rFimA plus FL/CpG resulted in increased levels of rFimA-specific secretory IgA (SIgA) and IgG Ab responses when compared with those in controls. Significantly increased numbers of CD8- or CD11b-expressing mature-type dendritic cells (DCs) were detected in the respiratory inductive and effector tissues of mice given rFimA plus FL/CpG. Additionally, significantly upregulated Th1/Th2-type cytokine responses by rFimA-stimulated CD4+ T cells were noted in the respiratory effector tissues. When mice were challenged with live P. gingivalis via the nasal route, mice immunized nasally with rFimA plus FL/CpG inhibited P. gingivalis colonization in the nasal cavities and lungs. In contrast, controls failed to show protection. Of interest, when IgA-deficient mice given nasal rFimA plus FL/CpG were challenged with nasal P. gingivalis, the inhibition of bacterial colonization in the respiratory tracts was not seen. Taken together, these results show that nasal FL/CpG effectively enhanced DCs and provided balanced Th1- and Th2-type cytokine response-mediated rFimA-specific IgA protective immunity in the respiratory tract against P. gingivalis. A nasal administration with rFimA and FL/CpG could be a candidate for potent mucosal vaccines for the elimination of inhaled P. gingivalis in periodontal patients

A study of live neural cell in cultured neural network by using Raman spectroscopy

関西学院大

Embryonic LTR retrotransposons supply promoter modules to somatic tissues

Long terminal repeat (LTR) retrotransposons are widely distributed across the human genome. They have accumulated through retroviral integration into germline DNA and are latent genetic modules. Active LTR promoters are observed in germline cells; however, little is known about the mechanisms underlying their active transcription in somatic tissues. Here, by integrating our previous transcriptome data set with publicly available data sets, we show that the LTR families MLT2A1 and MLT2A2 are primarily expressed in human four-cell and eight-cell embryos and are also activated in some adult somatic tissues, particularly pineal gland. Three MLT2A elements function as the promoters and first exons of the protein-coding genes ABCE1, COL5A1, and GALNT13 specifically in the pineal gland of humans but not in that of macaques, suggesting that the exaptation of these LTRs as promoters occurred during recent primate evolution. This analysis provides insight into the possible transition from germline insertion to somatic expression of LTR retrotransposons.Peer reviewe