Tokai National Higher Education and Research System

Insights from epidemiological, clinical and basic research are illuminating the interplay between metabolic disorders, cardiovascular disease (CVD) and kidney dysfunction, termed cardio-renal-metabolic (CRM) disease. Broadly defined, CRM disease involves multidirectional interactions between metabolic diseases such as type 2 diabetes (T2D), various types of CVD and chronic kidney disease (CKD). T2D confers increased risk for heart failure, which-although well known-has only recently come into focus for treatment, and may differ by ethnicity, whereas atherosclerotic heart disease is a well-established complication of T2D. Many people with T2D also have CKD, with a higher risk in Asians than their Western counterparts. Furthermore, CVD increases the risk of CKD and vice versa, with heart failure, notably, present in approximately half of CKD patients. Molecular mechanisms involved in CRM disease include hyperglycaemia, insulin resistance, hyperactivity of the renin-angiotensin-aldosterone system, production of advanced glycation end-products, oxidative stress, lipotoxicity, endoplasmic reticulum stress, calcium-handling abnormalities, mitochondrial malfunction and deficient energy production, and chronic inflammation. Pathophysiological manifestations of these processes include diabetic cardiomyopathy, vascular endothelial dysfunction, cardiac and renal fibrosis, glomerular hyperfiltration, renal hypoperfusion and venous congestion, reduced exercise tolerance leading to metabolic dysfunction, and calcification of atherosclerotic plaque. Importantly, recognition of the interaction between CRM diseases would enable a more holistic approach to CRM care, rather than isolated treatment of individual conditions, which may improve patient outcomes. Finally, aspects of CRM diseases may differ between Western and East Asian countries such as Japan, a super-ageing country, with potential differences in epidemiology, complications and prognosis that represent an important avenue for future research.

Transglutaminase 2 (TG2) is a ubiquitously expressed enzyme catalyzing the crosslinking between Gln and Lys residues and involved in various pathophysiological events. Besides this crosslinking activity, TG2 functions as a deamidase, GTPase, isopeptidase, adapter/scaffold, protein disulfide isomerase, and kinase. It also plays a role in the regulation of hypusination and serotonylation. Through these activities, TG2 is involved in cell growth, differentiation, cell death, inflammation, tissue repair, and fibrosis. Depending on the cell type and stimulus, TG2 changes its subcellular localization and biological activity, leading to cell death or survival. In normal unstressed cells, intracellular TG2 exhibits a GTP-bound closed conformation, exerting prosurvival functions. However, upon cell stimulation with Ca2+ or other factors, TG2 adopts a Ca2+-bound open conformation, demonstrating a transamidase activity involved in cell death or survival. These functional discrepancies of TG2 open form might be caused by its multifunctional nature, the existence of splicing variants, the cell type and stimulus, and the genetic backgrounds and variations of the mouse models used. TG2 is also involved in the phagocytosis of dead cells by macrophages and in fibrosis during tissue repair. Here, we summarize and discuss the multifunctional and controversial roles of TG2, focusing on cell death/survival and fibrosis.

It is necessary to accurately identify dental implant brands and the stage of treatment to ensure efficient care. Thus, the purpose of this study was to use multi-task deep learning to investigate a classifier that categorizes implant brands and treatment stages from dental panoramic radiographic images. For objective labeling, 9767 dental implant images of 12 implant brands and treatment stages were obtained from the digital panoramic radiographs of patients who underwent procedures at Kagawa Prefectural Central Hospital, Japan, between 2005 and 2020. Five deep convolutional neural network (CNN) models (ResNet18, 34, 50, 101 and 152) were evaluated. The accuracy, precision, recall, specificity, F1 score, and area under the curve score were calculated for each CNN. We also compared the multi-task and single-task accuracies of brand classification and implant treatment stage classification. Our analysis revealed that the larger the number of parameters and the deeper the network, the better the performance for both classifications. Multi-tasking significantly improved brand classification on all performance indicators, except recall, and significantly improved all metrics in treatment phase classification. Using CNNs conferred high validity in the classification of dental implant brands and treatment stages. Furthermore, multi-task learning facilitated analysis accuracy.

Messenger RNAs (mRNAs) with phosphorothioate modification (PS-mRNA) to the phosphate site of A, G, C, and U with all 16 possible combinations were prepared, and the translation reaction was evaluated using an E. coli cell-free translation system. Protein synthesis from PS-mRNA increased in 12 of 15 patterns when compared with that of unmodified mRNA. The protein yield increased 22-fold when the phosphorothioate modification at A/C sites was introduced into the region from the 5'-end to the initiation codon. Single-turnover analysis of PS-mRNA translation showed that phosphorothioate modification increases the number of translating ribosomes, thus suggesting that the rate of translation initiation (rate of ribosome complex formation) is positively affected by the modification. The method provides a new strategy for improving translation by using non-natural mRNA.

Pell and Gregory, and Winter's classifications are frequently implemented to classify the mandibular third molars and are crucial for safe tooth extraction. This study aimed to evaluate the classification accuracy of convolutional neural network (CNN) deep learning models using cropped panoramic radiographs based on these classifications. We compared the diagnostic accuracy of single-task and multi-task learning after labeling 1330 images of mandibular third molars from digital radiographs taken at the Department of Oral and Maxillofacial Surgery at a general hospital (2014-2021). The mandibular third molar classifications were analyzed using a VGG 16 model of a CNN. We statistically evaluated performance metrics [accuracy, precision, recall, F1 score, and area under the curve (AUC)] for each prediction. We found that single-task learning was superior to multi-task learning (all p < 0.05) for all metrics, with large effect sizes and low p-values. Recall and F1 scores for position classification showed medium effect sizes in single and multi-task learning. To our knowledge, this is the first deep learning study to examine single-task and multi-task learning for the classification of mandibular third molars. Our results demonstrated the efficacy of implementing Pell and Gregory, and Winter's classifications for specific respective tasks.

BACKGROUND: Contrast-enhanced endoscopic ultrasound (CE-EUS) is useful for the differentiation of pancreatic tumors. Using deep learning for the segmentation and classification of pancreatic tumors might further improve the diagnostic capability of CE-EUS. AIMS: The aim of this study was to evaluate the capability of deep learning for the automatic segmentation of pancreatic tumors on CE-EUS video images and possible factors affecting the automatic segmentation. METHODS: This retrospective study included 100 patients who underwent CE-EUS for pancreatic tumors. The CE-EUS video images were converted from the originals to 90-s segments with six frames per second. Manual segmentation of pancreatic tumors from B-mode images was performed as ground truth. Automatic segmentation was performed using U-Net with 100 epochs and was evaluated with 4-fold cross-validation. The degree of respiratory movement (RM) and tumor boundary (TB) were divided into 3-degree intervals in each patient and evaluated as possible factors affecting the segmentation. The concordance rate was calculated using the intersection over union (IoU). RESULTS: < 0.01). However, there was no significant difference between the degrees of RM. CONCLUSIONS: Automatic segmentation of pancreatic tumors using U-Net on CE-EUS video images showed a decent concordance rate. The concordance rate was lowered by an unclear TB but was not affected by RM.

and identified His-535 in the SH3 domain as the critical residue for enzymatic activity of FUT8. Furthermore, we found that although FUT8 is mainly localized to the Golgi, it also partially localizes to the cell surface in an SH3-dependent manner, indicating that the SH3 domain is also involved in FUT8 trafficking. Finally, we identified ribophorin I (RPN1), a subunit of the oligosaccharyltransferase complex, as an SH3-dependent binding protein of FUT8. RPN1 knockdown decreased both FUT8 activity and core fucose levels, indicating that RPN1 stimulates FUT8 activity. Our findings indicate that the SH3 domain critically controls FUT8 catalytic activity and localization and is required for binding by RPN1, which promotes FUT8 activity and core fucosylation.

Macrophages are important components in modulating homeostatic and inflammatory responses and are generally categorized into two broad but distinct subsets: classical activated (M1) and alternatively activated (M2) depending on the microenvironment. Fibrosis is a chronic inflammatory disease exacerbated by M2 macrophages, although the detailed mechanism by which M2 macrophage polarization is regulated remains unclear. These polarization mechanisms have little in common between mice and humans, making it difficult to adapt research results obtained in mice to human diseases. Tissue transglutaminase (TG2) is a known marker common to mouse and human M2 macrophages and is a multifunctional enzyme responsible for crosslinking reactions. Here we sought to identify the role of TG2 in macrophage polarization and fibrosis. In IL-4-treated macrophages derived from mouse bone marrow and human monocyte cells, the expression of TG2 was increased with enhancement of M2 macrophage markers, whereas knockout or inhibitor treatment of TG2 markedly suppressed M2 macrophage polarization. In the renal fibrosis model, accumulation of M2 macrophages in fibrotic kidney was significantly reduced in TG2 knockout or inhibitor-administrated mice, along with the resolution of fibrosis. Bone marrow transplantation using TG2-knockout mice revealed that TG2 is involved in M2 polarization of infiltrating macrophages derived from circulating monocytes and exacerbates renal fibrosis. Furthermore, the suppression of renal fibrosis in TG2-knockout mice was abolished by transplantation of wild-type bone marrow or by renal subcapsular injection of IL4-treated macrophages derived from bone marrow of wild-type, but not TG2 knockout. Transcriptome analysis of downstream targets involved in M2 macrophages polarization revealed that ALOX15 expression was enhanced by TG2 activation and promoted M2 macrophage polarization. Furthermore, the increase in the abundance of ALOX15-expressing macrophages in fibrotic kidney was dramatically suppressed in TG2-knockout mice. These findings demonstrated that TG2 activity exacerbates renal fibrosis by polarization of M2 macrophages from monocytes via ALOX15.

Abstract Since their early stages of development, micro-electro-mechanical systems (MEMS) have shown potential for breakthroughs in the fabrication of medical tools. The miniaturization of various devices using MEMS technology has enabled minimally invasive treatments and in situ measurements. In this paper, we introduce two advancements in MEMS applications in the medical field: (1) microneedle devices for brain activity evaluation, a transdermal drug delivery system, and biological fluid sampling; and (2) miniaturized MEMS sensors for monitoring the conditions inside blood vessels and respiratory organs. In addition, we provide a summary of MEMS sensors used in developing new drugs, detecting vital signs, and other applications.

AIMS/INTRODUCTION: Glucagon is secreted from pancreatic α-cells and plays an important role in amino acid metabolism in liver. Various animal models deficient in glucagon action show hyper-amino acidemia and α-cell hyperplasia, indicating that glucagon contributes to feedback regulation between the liver and the α-cells. In addition, both insulin and various amino acids, including branched-chain amino acids and alanine, participate in protein synthesis in skeletal muscle. However, the effect of hyperaminoacidemia on skeletal muscle has not been investigated. In the present study, we examined the effect of blockade of glucagon action on skeletal muscle using mice deficient in proglucagon-derived peptides (GCGKO mice). MATERIALS AND METHODS: Muscles isolated from GCGKO and control mice were analyzed for their morphology, gene expression and metabolites. RESULTS: GCGKO mice showed muscle fiber hypertrophy, and a decreased ratio of type IIA and an increased ratio of type IIB fibers in the tibialis anterior. The expression levels of myosin heavy chain (Myh) 7, 2, 1 and myoglobin messenger ribonucleic acid were significantly lower in GCGKO mice than those in control mice in the tibialis anterior. GCGKO mice showed a significantly higher concentration of arginine, asparagine, serine and threonine in the quadriceps femoris muscles, and also alanine, aspartic acid, cysteine, glutamine, glycine and lysine, as well as four amino acids in gastrocnemius muscles. CONCLUSIONS: These results show that hyperaminoacidemia induced by blockade of glucagon action in mice increases skeletal muscle weight and stimulates slow-to-fast transition in type II fibers of skeletal muscle, mimicking the phenotype of a high-protein diet.

BACKGROUND: Continued expansion of indications for sodium-glucose cotransporter-2 inhibitors increases importance of evaluating cardiovascular and kidney efficacy and safety of empagliflozin in patients with type 2 diabetes compared to similar therapies. METHODS: The EMPRISE Europe and Asia study is a non-interventional cohort study using data from 2014-2019 in seven European (Denmark, Finland, Germany, Norway, Spain, Sweden, United Kingdom) and four Asian (Israel, Japan, South Korea, Taiwan) countries. Patients with type 2 diabetes initiating empagliflozin were 1:1 propensity score matched to patients initiating dipeptidyl peptidase-4 inhibitors. Primary endpoints included hospitalization for heart failure, all-cause mortality, myocardial infarction and stroke. Other cardiovascular, renal, and safety outcomes were examined. FINDINGS: Among 83,946 matched patient pairs, (0·7 years overall mean follow-up time), initiation of empagliflozin was associated with lower risk of hospitalization for heart failure compared to dipeptidyl peptidase-4 inhibitors (Hazard Ratio 0·70; 95% CI 0.60 to 0.83). Risks of all-cause mortality (0·55; 0·48 to 0·63), stroke (0·82; 0·71 to 0·96), and end-stage renal disease (0·43; 0·30 to 0·63) were lower and risk for myocardial infarction, bone fracture, severe hypoglycemia, and lower-limb amputation were similar between initiators of empagliflozin and dipeptidyl peptidase-4 inhibitors. Initiation of empagliflozin was associated with higher risk for diabetic ketoacidosis (1·97; 1·28 to 3·03) compared to dipeptidyl peptidase-4 inhibitors. Results were consistent across continents and regions. INTERPRETATION: Results from this EMPRISE Europe and Asia study complements previous clinical trials and real-world studies by providing further evidence of the beneficial cardiorenal effects and overall safety of empagliflozin compared to dipeptidyl peptidase-4 inhibitors.

Attention mechanism, which is a means of determining which part of the forced data is emphasized, has attracted attention in various fields of deep learning in recent years. The purpose of this study was to evaluate the performance of the attention branch network (ABN) for implant classification using convolutional neural networks (CNNs). The data consisted of 10191 dental implant images from 13 implant brands that cropped the site, including dental implants as pretreatment, from digital panoramic radiographs of patients who underwent surgery at Kagawa Prefectural Central Hospital between 2005 and 2021. ResNet 18, 50, and 152 were evaluated as CNN models that were compared with and without the ABN. We used accuracy, precision, recall, specificity, F1 score, and area under the receiver operating characteristics curve as performance metrics. We also performed statistical and effect size evaluations of the 30-time performance metrics of the simple CNNs and the ABN model. ResNet18 with ABN significantly improved the dental implant classification performance for all the performance metrics. Effect sizes were equivalent to "Huge" for all performance metrics. In contrast, the classification performance of ResNet50 and 152 deteriorated by adding the attention mechanism. ResNet18 showed considerably high compatibility with the ABN model in dental implant classification (AUC = 0.9993) despite the small number of parameters. The limitation of this study is that only ResNet was verified as a CNN; further studies are required for other CNN models.

Atypical eye gaze is an established clinical sign in the diagnosis of autism spectrum disorder (ASD). We propose a computerized diagnostic algorithm for ASD, applicable to children and adolescents aged between 5 and 17 years using Gazefinder, a system where a set of devices to capture eye gaze patterns and stimulus movie clips are equipped in a personal computer with a monitor. We enrolled 222 individuals aged 5-17 years at seven research facilities in Japan. Among them, we extracted 39 individuals with ASD without any comorbid neurodevelopmental abnormalities (ASD group), 102 typically developing individuals (TD group), and an independent sample of 24 individuals (the second control group). All participants underwent psychoneurological and diagnostic assessments, including the Autism Diagnostic Observation Schedule, second edition, and an examination with Gazefinder (2 min). To enhance the predictive validity, a best-fit diagnostic algorithm of computationally selected attributes originally extracted from Gazefinder was proposed. The inputs were classified automatically into either ASD or TD groups, based on the attribute values. We cross-validated the algorithm using the leave-one-out method in the ASD and TD groups and tested the predictability in the second control group. The best-fit algorithm showed an area under curve (AUC) of 0.84, and the sensitivity, specificity, and accuracy were 74, 80, and 78%, respectively. The AUC for the cross-validation was 0.74 and that for validation in the second control group was 0.91. We confirmed that the diagnostic performance of the best-fit algorithm is comparable to the diagnostic assessment tools for ASD.

Oncogene-induced DNA replication stress (RS) and consequent pathogenic R-loop formation are known to impede S phase progression. Nonetheless, cancer cells continuously proliferate under such high-stressed conditions through incompletely understood mechanisms. Here, we report taurine upregulated gene 1 (TUG1) long noncoding RNA (lncRNA), which is highly expressed in many types of cancers, as an important regulator of intrinsic R-loop in cancer cells. Under RS conditions, TUG1 is rapidly upregulated via activation of the ATR-CHK1 signaling pathway, interacts with RPA and DHX9, and engages in resolving R-loops at certain loci, particularly at the CA repeat microsatellite loci. Depletion of TUG1 leads to overabundant R-loops and enhanced RS, leading to substantial inhibition of tumor growth. Our data reveal a role of TUG1 as molecule important for resolving R-loop accumulation in cancer cells and suggest targeting TUG1 as a potent therapeutic approach for cancer treatment.

A complex containing a V–Al bond is described. This species can be prepared by either transmetalation of a previously disclosed alumanylpotassium with Cp2VCl or photolytic oxidative alumination of Cp2V using the corresponding dialumane. Reaction of the resulting V–Al complex with H2 gave a Cp2V-dihydridoaluminate complex. These complexes were studied with X-ray crystallography, vanadium K-edge XANES spectroscopy, and DFT calculations. Finally, the reactivity of these molecules was studied opening the way to a catalytic C–H alumanylation of alkenes.

The photocatalytic activity of titanium dioxide is widely utilized in science and technology. In the biological field, titanium dioxide is believed to be a disinfectant because it produces reactive oxygen species (ROS). However, there are multiple types of ROS such as hydroxyl radicals, superoxide anions, singlet oxygen, and hydrogen peroxide. In this study, we attempted to characterize the various mechanisms and roles of ROS in disinfection. Surprisingly, we found that titanium dioxide protected yeast cells from ultraviolet irradiation. We characterized the ROS produced under these conditions. The production of hydroxyl radicals and superoxide anions was confirmed; however, glucose in the yeast medium scavenged hydroxyl radicals. The photocatalytic activity of titanium dioxide produced oxidative products and reductive products, as oxidation and reduction occurred simultaneously. Once hydroxyl radicals are scavenged, the photocatalytic activity of titanium dioxide produces a reductive environment for fermenting yeast cells and protects them from oxidative stress by ultraviolet irradiation.

Lactobacillus plantarum, a lactic acid bacterium, produces organic acids, fatty acids, ammonia, hydrogen peroxide, diacetyl, and bacteriocin to survive in an unfavorable environment. Plantaricin, a class II bacteriocin produced by L. plantarum, is reported to be heterologous, and its ability to inhibit or kill pathogenic bacteria is very broad, with potential application as a bio-preservative. Plantaricin production is regulated by genetically organized operons, which also encode structural genes, immunity proteins, and secretion genes in plasmids or chromosomes. The mechanism of action against pathogenic bacteria depends on the characteristics of plantaricin. The most common bactericidal mechanisms are disruption of the cell wall integrity and inhibition of protein or nucleic acid synthesis. This review focuses on characterization of the heterologous mechanisms of plantaricin to inhibit and kill pathogenic bacteria and the future role of plantaricin for food preservation. With this review, we hope to contribute to innovation in food preservation, by promoting a better understanding of this natural resource.

Idiopathic pulmonary fibrosis (IPF) is characterized by the invariably progressive deposition of fibrotic tissue in the lungs and overall poor prognosis. TG2 (transglutaminase 2) is an enzyme that crosslinks glutamine and lysine residues and is involved in IPF pathogenesis. Despite the accumulating evidence implicating TG2 as a critical enzyme, the causative function and direct target of TG2 relating to this pathogenesis remain unelucidated. Here, we clarified the distributions of TG2 protein/activity and conducted quantitative proteomics analyses of possible substrates crosslinked by TG2 on unfixed lung sections in a mouse pulmonary fibrosis model. We identified 126 possible substrates as markedly TG2-dependently increased in fibrotic lung. Gene ontology analysis revealed that these identified proteins were mostly enriched in the lipid metabolic process, immune system process, and protein transport. In addition, these proteins were enriched in 21 pathways, including phagosome, lipid metabolism, several immune responses, and protein processing in endoplasmic reticulum. Furthermore, the network analyses screened out the six clusters and top 20 hub proteins with higher scores, which are related to endoplasmic reticulum stress and peroxisome proliferator-activated receptor signals. Several enriched pathways and categories were identified, some of which were the same terms based on transcription analysis in IPF. Our results provide novel pathological molecular networks driven by protein crosslinking via TG2, which can lead to the development of new therapeutic targets for IPF.

This article sought to address issues related to human-robot cooperation tasks focusing especially on robotic operation using bio-signals. In particular, we propose to develop a control scheme for a robot arm based on electromyography (EMG) signal that allows a cooperative task between humans and robots that would enable teleoperations. A basic framework for achieving the task and conducting EMG signals analysis of the motion of upper limb muscles for mapping the hand motion is presented. The objective of this work is to investigate the application of a wearable EMG device to control a robot arm in real-time. Three EMG sensors are attached to the brachioradialis, biceps brachii, and anterior deltoid muscles as targeted muscles. Three motions were conducted by moving the arm about the elbow joint, shoulder joint, and a combination of the two joints giving a two degree of freedom. Five subjects were used for the experiments. The results indicated that the performance of the system had an overall accuracy varying from 50% to 100% for the three motions for all subjects. This study has further shown that upper-limb motion discrimination can be used to control the robotic manipulator arm with its simplicity and low computational cost.

During wound regeneration, both cell adhesion and adhesion-inhibitory functions must be controlled in parallel. We developed a membrane with dual surfaces by merging the properties of carboxymethyl cellulose (CMC) and collagen using vitrification. A rigid membrane was formed by vitrification of a bi-layered CMC and collagen hydrogel without using cross-linking reagents, thus providing dual functions, strong cell adhesion-inhibition with the CMC layer, and cell adhesion with the collagen layer. We referred to this bi-layered CMC-collagen vitrigel membrane as "Bi-C-CVM" and optimized the process and materials. The introduction of the CMC layer conferred a "tough but stably wet" property to Bi-C-CVM. This enables Bi-C-CVM to cover wet tissue and make the membrane non-detachable while preventing tissue adhesion on the other side. The bi-layered vitrification procedure can expand the customizability of collagen vitrigel devices for wider medical applications.