Traffic Incident Database with Multiple Labels Including Various Perspective Environmental Information

A large dataset of annotated traffic accidents is necessary to improve the accuracy of traffic accident recognition using deep learning models. Conventional traffic accident datasets provide annotations on traffic accidents and other teacher labels, improving traffic accident recognition performance. However, the labels annotated in conventional datasets need to be more comprehensive to describe traffic accidents in detail. Therefore, we propose V-TIDB, a large-scale traffic accident recognition dataset annotated with various environmental information as multi-labels. Our proposed dataset aims to improve the performance of traffic accident recognition by annotating ten types of environmental information as teacher labels in addition to the presence or absence of traffic accidents. V-TIDB is constructed by collecting many videos from the Internet and annotating them with appropriate environmental information. In our experiments, we compare the performance of traffic accident recognition when only labels related to the presence or absence of traffic accidents are trained and when environmental information is added as a multi-label. In the second experiment, we compare the performance of the training with only contact level, which represents the severity of the traffic accident, and the performance with environmental information added as a multi-label. The results showed that 6 out of 10 environmental information labels improved the performance of recognizing the presence or absence of traffic accidents. In the experiment on the degree of recognition of traffic accidents, the performance of recognition of car wrecks and contacts was improved for all environmental information. These experiments show that V-TIDB can be used to learn traffic accident recognition models that take environmental information into account in detail and can be used for appropriate traffic accident analysis.Comment: Conference paper accepted to IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023 Reason for revision: Corrected due to a missing space between sentences in the preview's abstract, which led to an unintended URL interpretatio

Correlations of Vascular Architecture and Angiogenesis with Pituitary Adenoma Histotype

Vascular endothelial growth factor (VEGF) is a potent angiogenic factor in solid tumors. However, its role in angiogenesis in pituitary adenoma is controversial. Angiogenesis in solid tumors including pituitary adenoma is commonly evaluated by microvascular density (MVD). Here, we evaluated MVD and the role of VEGF in vascular architecture in 51 pituitary adenomas (24 nonfunctioning, 13 prolactin-secreting, 10 growth hormone-secreting, 3 adrenocorticotropic hormone-secreting, and 1 thyroid-stimulating hormone-secreting). Paraffin sections were stained with CD34 and VEGF. MVD and vascular architecture parameters (vessel area, diameter, perimeter, and roundness) were evaluated in CD34-stained sections. Immunohistochemistry showed 27/51 tumors (53%) were VEGF-positive. There were no significant differences in MVD, any vascular parameter, or adenoma volume between VEGF-positive and VEGF-negative tumors. VEGF mRNA expression was significantly higher in VEGF-positive tumors. There were no significant correlations between VEGF mRNA expression and MVD or vascular parameters. However, vessel diameter and perimeter were significantly larger in prolactin-secreting than nonfunctioning and growth hormone-secreting macroadenomas. The difference in vessel diameter was observed among both VEGF-positive and all adenomas (micro- and macroadenoma). Thus, VEGF may have limited roles in the development of vascular architecture and tumor angiogenesis in pituitary adenomas, but the differences in vessel architecture by histotype (i.e., larger vessel diameter and perimeter in prolactin-secreting adenomas) suggest the hormonal regulation of vessel architecture rather than angiogenesi

Multiscale structural control of linked metal–organic polyhedra gel by aging-induced linkage-reorganization

Assembly of permanently porous metal–organic polyhedra/cages (MOPs) with bifunctional linkers leads to soft supramolecular networks featuring both porosity and processability. However, the amorphous nature of such soft materials complicates their characterization and thus limits rational structural control. Here we demonstrate that aging is an effective strategy to control the hierarchical network of supramolecular gels, which are assembled from organic ligands as linkers and MOPs as junctions. Normally, the initial gel formation by rapid gelation leads to a kinetically trapped structure with low controllability. Through a controlled post-synthetic aging process, we show that it is possible to tune the network of the linked MOP gel over multiple length scales. This process allows control on the molecular-scale rearrangement of interlinking MOPs, mesoscale fusion of colloidal particles and macroscale densification of the whole colloidal network. In this work we elucidate the relationships between the gel properties, such as porosity and rheology, and their hierarchical structures, which suggest that porosity measurement of the dried gels can be used as a powerful tool to characterize the microscale structural transition of their corresponding gels. This aging strategy can be applied in other supramolecular polymer systems particularly containing kinetically controlled structures and shows an opportunity to engineer the structure and the permanent porosity of amorphous materials for further applications

Preparation of Mouse Monoclonal Antibody for RB1CC1 and Its Clinical Application

RB1-inducible coiled-coil 1 (RB1CC1; also known as FIP200) plays important roles in several biological pathways such as cell proliferation and autophagy. Evaluation of RB1CC1 expression can provide useful clinical information on various cancers and neurodegenerative diseases. In order to realize the clinical applications, it is necessary to establish a stable supply of antibody and reproducible procedures for the laboratory examinations. In the present study, we have generated mouse monoclonal antibodies for RB1CC1, and four kinds of antibodies (N1-8, N1-216, N3-2, and N3-42) were found to be optimal for clinical applications such as ELISA and immunoblots and work as well as the pre-existing polyclonal antibodies. N1-8 monoclonal antibody provided the best recognition of RB1CC1 in the clinico-pathological examination of formalin-fixed paraffin-embedded tissues. These monoclonal antibodies will help to generate new opportunities in scientific examinations in biology and clinical medicine

Hematopoietic cell-derived IL-15 supports NK cell development in scattered and clustered localization within the bone marrow

骨髄のNK細胞の分化に造血細胞が産生するIL-15が必須である --2種類の局在を示すNK細胞の新規分化モデル--. 京都大学プレスリリース. 2023-09-20.Natural killer (NK) cells are innate immune cells critical for protective immune responses against infection and cancer. Although NK cells differentiate in the bone marrow (BM) in an interleukin-15 (IL-15)-dependent manner, the cellular source of IL-15 remains elusive. Using NK cell reporter mice, we show that NK cells are localized in the BM in scattered and clustered manners. NK cell clusters overlap with monocyte and dendritic cell accumulations, whereas scattered NK cells require CXCR4 signaling. Using cell-specific IL-15-deficient mice, we show that hematopoietic cells, but not stromal cells, support NK cell development in the BM through IL-15. In particular, IL-15 produced by monocytes and dendritic cells appears to contribute to NK cell development. These results demonstrate that hematopoietic cells are the IL-15 niche for NK cell development in the BM and that BM NK cells are present in scattered and clustered compartments by different mechanisms, suggesting their distinct functions in the immune response