Panoramic Image-to-Image Translation

In this paper, we tackle the challenging task of Panoramic Image-to-Image translation (Pano-I2I) for the first time. This task is difficult due to the geometric distortion of panoramic images and the lack of a panoramic image dataset with diverse conditions, like weather or time. To address these challenges, we propose a panoramic distortion-aware I2I model that preserves the structure of the panoramic images while consistently translating their global style referenced from a pinhole image. To mitigate the distortion issue in naive 360 panorama translation, we adopt spherical positional embedding to our transformer encoders, introduce a distortion-free discriminator, and apply sphere-based rotation for augmentation and its ensemble. We also design a content encoder and a style encoder to be deformation-aware to deal with a large domain gap between panoramas and pinhole images, enabling us to work on diverse conditions of pinhole images. In addition, considering the large discrepancy between panoramas and pinhole images, our framework decouples the learning procedure of the panoramic reconstruction stage from the translation stage. We show distinct improvements over existing I2I models in translating the StreetLearn dataset in the daytime into diverse conditions. The code will be publicly available online for our community

Role of kif2c, A Gene Related to ALL Relapse, in Embryonic Hematopoiesis in Zebrafish

Relapse of acute lymphoblastic leukemia (ALL) is dangerous and it worsens the prognosis of patients; however, prognostic markers or therapeutic targets for ALL remain unknown. In the present study, using databases such as TARGET, GSE60926 and GSE28460, we determined that KIF2C and its binding partner, KIF18B are overexpressed in patients with relapsed ALL compared to that in patients diagnosed with ALL for the first time. As 50% of the residues are exactly the same and the signature domain of KIF2C is highly conserved between human and zebrafish, we used zebrafish embryos as a model to investigate the function of kif2c in vivo. We determined that kif2c is necessary for lymphopoiesis in zebrafish embryos. Additionally, we observed that kif2c is not related to differentiation of HSCs; however, it is important for the maintenance of HSCs as it provides survival signals to HSCs. These results imply that the ALL relapse-related gene KIF2C is linked to the survival of HSCs. In conclusion, we suggest that KIF2C can serve as a novel therapeutic target for relapsed ALL

Copper-Mediated Amination of Aryl C-H Bonds with the Direct Use of Aqueous Ammonia via a Disproportionation Pathway

The direct amination of C-H bonds with ammonia is a challenge in synthetic chemistry. Herein, we present a copper-mediated approach that enables a chelation-assisted aromatic C-H bond amination using aqueous ammonia. A key strategy was to use soft low-valent Cu(I) species to avoid the strong coordination of ammonia. Mechanistic investigations suggest that the catalysis is initiated by a facile deprotonation of bound ammonia, and the C-N coupling is achieved by subsequent reductive elimination of the resultant copper-amido intermediate from a Cu(III) intermediate that is readily generated by disproportionation of low-valent copper analogues. This mechanistic postulate was supported by a preliminary kinetic isotope effect study and computations. This new chelation-assisted, copper-mediated C-H bond amination with aqueous ammonia was successfully applied to a broad range of substrates to deliver primary anilines. Moreover, the mild conditions required for this transformation allowed the reaction to operate even under substoichiometric conditions to enable a late-stage application for the preparation of pharmaceutical agents. © 2018 American Chemical Societ

High-precision 3D Bio-dot Printing to Improve Paracrine Interaction Between Multiple Types of Cell Spheroids

Cell-cell interaction accounts for one of the most influential factors affecting the viability and functionality of cell-based tissue models. In this respect, various methods capable of producing micro-patterns with cell spheroids are introduced to simultaneously improve contact-dependent and -independent cell-cell interactions. However, no method has yet been designed to effectively generate precise 3D patterns with multiple spheroid types. In this study, a new high-precision and convenient 3D spheroid printing technology is developed, designated as 3D bio-dot printing. This new technique is designed to produce cell-laden, non-adhesive micro-pores within 3D structures to allow cell spheroids to be induced at printed sites. Experimental results show that various cell types, including hepatocytes, pancreatic beta-cells, and breast cancer cells, can be employed for the in situ formation of cell spheroids, and 3D freeform structures with multiple spheroid types can be printed. Moreover, this novel technology can also be used for performing 3D invasion assays. More importantly, it ensures that the precise control of spheroid size and position is achieved at micrometer scale. Finally, the usefulness of this novel technology is demonstrated by producing multicellular micro-patterns with primary hepatocyte spheroids and endothelial cells, that exhibit significantly improved long-term hepatic function and drug metabolism

Display Visibility Improvement Through Content and Ambient Light-Adaptive Image Enhancement

An image in a display device under strong illuminance can be perceived as darker than the original due to the nature of the human visual system (HVS). In order to alleviate this degradation in terms of software, existing schemes employ global luminance compensation or tone mapping. However, since such approaches focus on restoring luminance only, it has a fundamental drawback that chrominance cannot be sufficiently restored. Also, the previous approaches seldom provide acceptable visibility because it does not consider the content of an input image. Furthermore, because they focus mainly on global image quality, they may show unsatisfactory image quality for certain local areas. This paper introduces VisibilityNet, a neural network model designed to restore both chrominance and luminance. By leveraging VisibilityNet, we generate an optimally enhanced dataset tailored to the ambient light conditions. Furthermore, employing the generated dataset and a convolutional neural network (CNN), we estimate weighted piece-wise linear enhancement curves (WPLECs) that take into account both ambient light and image content. These WPLECs effectively enhance global contrast by addressing both luminance and chrominance aspects. Ultimately, through the utilization of a salient object detection algorithm that emulates the HVS, visibility enhancement is achieved not only for the overall region but also for visually salient areas. We verified the performance of the proposed method by comparing it with five existing approaches in terms of two quantitative metrics for a dataset we built ourselves. Experimental findings substantiate that the proposed method surpasses alternative approaches by significantly improving visibility

Substrate-Dependent Growth Mode Control of MoS2 Monolayers: Implications for Hydrogen Evolution and Field-Effect Transistor

The control of domain sizes provides a powerful means to engineer the characteristics of monolayer (ML) MoS2films for specific applications including catalysts for hydrogen evolution and thin-film transistors. Here, we report an efficient way to control domain structures of MoS2by substrate-dependent growth mode control. Deterministic control of growth modes, associated with catalytic intermediates, is introduced by utilizing different growth substrates in metal-organic chemical vapor deposition (MOCVD) of ML MoS2. Na-Mo-O eutectic alloys formed by a soda lime (SL) substrate dominate the growth based on a vapor-liquid-solid (VLS) process, resulting in large-crystalline domains of MoS2with a reduced density of liquid nuclei. On the other hand, MoO3-xseeds formed from an alkali aluminosilicate (AA) substrate accelerate nucleation via a vapor-solid-solid (VSS) process for nanocrystalline domains. ML MoS2of nanocrystalline domains resulted in efficient hydrogen evolution reactions (HERs), while large-domain films showed better electron conductivity. © 2022 American Chemical Society. All rights reserved.11Nsciescopu

FRZB as a key molecule in abdominal aortic aneurysm progression affecting vascular integrity

Abdominal aortic aneurysm (AAA), when ruptured, results in high mortality. The identification of molecular pathways involved in AAA progression is required to improve AAA prognosis. The aim of the present study was to assess the key genes for the progression of AAA and their functional role. Genomic and clinical data of three independent cohorts were a downloaded from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) (GSE57691, GSE7084, and GSE98278). To develop AAA diagnosis and progression-related differentially expressed genes (DEGs), we used a significance analysis of microarray (SAM). Spearman correlation test and gene set analysis were performed to identify potential enriched pathways for DEGs. Only the Frizzled-related protein (FRZB) gene and chromosome 1 open reading frame 24 (C1orf24) exhibited significant down-regulation in a all analyses. With FRZB, the pathways were associated with RHO GTPase and elastin fiber formation. With C1orf24, the pathways were elastic fiber formation, extracellular matrix organization, and cell-cell communication. Since only FRZB was evolutionally conserved in the vertebrates, function of FRZB was validated using zebrafish embryos. Knockdown of frzb remarkably reduced vascular integrity in zebrafish embryos. We believe that FRZB is a a key gene involved in AAA initiation and progression affecting vascular integrity