An Active and Soft Hydrogel Actuator to Stimulate Live Cell Clusters by Self-folding

The hydrogels are widely used in various applications, and their successful uses depend on controlling the mechanical properties. In this study, we present an advanced strategy to develop hydrogel actuator designed to stimulate live cell clusters by self-folding. The hydrogel actuator consisting of two layers with different expansion ratios were fabricated to have various curvatures in self-folding. The expansion ratio of the hydrogel tuned with the molecular weight and concentration of gel-forming polymers, and temperature-sensitive molecules in a controlled manner. As a result, the hydrogel actuator could stimulate live cell clusters by compression and tension repeatedly, in response to temperature. The cell clusters were compressed in the 0.7-fold decreases of the radius of curvature with 1.0 mm in room temperature, as compared to that of 1.4 mm in 37 degrees C. Interestingly, the vascular endothelial growth factor (VEGF) and insulin-like growth factor-binding protein-2 (IGFBP-2) in MCF-7 tumor cells exposed by mechanical stimulation was expressed more than in those without stimulation. Overall, this new strategy to prepare the active and soft hydrogel actuator would be actively used in tissue engineering, drug delivery, and micro-scale actuators

MPSeg : Multi-Phase strategy for coronary artery Segmentation

Accurate segmentation of coronary arteries is a pivotal process in assessing cardiovascular diseases. However, the intricate structure of the cardiovascular system presents significant challenges for automatic segmentation, especially when utilizing methodologies like the SYNTAX Score, which relies extensively on detailed structural information for precise risk stratification. To address these difficulties and cater to this need, we present MPSeg, an innovative multi-phase strategy designed for coronary artery segmentation. Our approach specifically accommodates these structural complexities and adheres to the principles of the SYNTAX Score. Initially, our method segregates vessels into two categories based on their unique morphological characteristics: Left Coronary Artery (LCA) and Right Coronary Artery (RCA). Specialized ensemble models are then deployed for each category to execute the challenging segmentation task. Due to LCA's higher complexity over RCA, a refinement model is utilized to scrutinize and correct initial class predictions on segmented areas. Notably, our approach demonstrated exceptional effectiveness when evaluated in the Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs (ARCADE) Segmentation Detection Algorithm challenge at MICCAI 2023.Comment: MICCAI 2023 Conference ARCADE Challeng

SSASS: Semi-Supervised Approach for Stenosis Segmentation

Coronary artery stenosis is a critical health risk, and its precise identification in Coronary Angiography (CAG) can significantly aid medical practitioners in accurately evaluating the severity of a patient's condition. The complexity of coronary artery structures combined with the inherent noise in X-ray images poses a considerable challenge to this task. To tackle these obstacles, we introduce a semi-supervised approach for cardiovascular stenosis segmentation. Our strategy begins with data augmentation, specifically tailored to replicate the structural characteristics of coronary arteries. We then apply a pseudo-label-based semi-supervised learning technique that leverages the data generated through our augmentation process. Impressively, our approach demonstrated an exceptional performance in the Automatic Region-based Coronary Artery Disease diagnostics using x-ray angiography imagEs (ARCADE) Stenosis Detection Algorithm challenge by utilizing a single model instead of relying on an ensemble of multiple models. This success emphasizes our method's capability and efficiency in providing an automated solution for accurately assessing stenosis severity from medical imaging data.Comment: MICCAI 2023 Conference ARCADE Challeng

Small-cell neuroendocrine carcinoma of the breast

A small-cell carcinoma is one of the histologic subtypes of primary neuroendocrine carcinomas of the breast. A small-cell carcinoma is a rare entity of the breast and exhibits similar morphologic features as neuroendocrine tumors of the gastrointestinal tract and lung. We present the imaging and pathologic findings of a primary small-cell neuroendocrine carcinoma of the breast. This is the first report of a primary small-cell carcinoma arising from the breast in Korea

A Novel Selective Sphingosine Kinase 2 Inhibitor, HWG-35D, Ameliorates the Severity of Imiquimod-Induced Psoriasis Model by Blocking Th17 Differentiation of Naïve CD4 T Lymphocytes

Sphingosine kinases (SK) catalyze the phosphorylation of sphingosine to generate sphingosine-1-phosphate. Two isoforms of SK (SK1 and SK2) exist in mammals. Previously, we showed the beneficial effects of SK2 inhibition, using ABC294640, in a psoriasis mouse model. However, ABC294640 also induces the degradation of SK1 and dihydroceramide desaturase 1 (DES1). Considering these additional effects of ABC294640, we re-examined the efficacy of SK2 inhibition in an IMQ-induced psoriasis mouse model using a novel SK2 inhibitor, HWG-35D, which exhibits nM potency and 100-fold selectivity for SK2 over SK1. Topical application of HWG-35D ameliorated IMQ-induced skin lesions and normalized the serum interleukin-17A levels elevated by IMQ. Application of HWG-35D also decreased skin mRNA levels of interleukin-17A, K6 and K16 genes induced by IMQ. Consistent with the previous data using ABC294640, HWG-35D also blocked T helper type 17 differentiation of naive CD4+ T cells with concomitant reduction of SOCS1. Importantly, HWG-35D did not affect SK1 or DES1 expression levels. These results reaffirm an important role of SK2 in the T helper type 17 response and suggest that highly selective and potent SK2 inhibitors such as HWG-35D might be of therapeutic use for the treatment of psoriasis

Combined Effects of Surface Morphology and Mechanical Straining Magnitudes on the Differentiation of Mesenchymal Stem Cells without Using Biochemical Reagents

Existing studies examining the control of mesenchymal stem cell (MSC) differentiation into desired cell types have used a variety of biochemical reagents such as growth factors despite possible side effects. Recently, the roles of biomimetic microphysical environments have drawn much attention in this field. We studied MSC differentiation and changes in gene expression in relation to osteoblast-like cell and smooth muscle-like cell type resulting from various microphysical environments, including differing magnitudes of tensile strain and substrate geometries for 8 days. In addition, we also investigated the residual effects of those selected microphysical environment factors on the differentiation by ceasing those factors for 3 days. The results of this study showed the effects of the strain magnitudes and surface geometries. However, the genes which are related to the same cell type showed different responses depending on the changes in strain magnitude and surface geometry. Also, different responses were observed three days after the straining was stopped. These data confirm that controlling microenvironments so that they mimic those in vivo contributes to the differentiation of MSCs into specific cell types. And duration of straining engagement was also found to play important roles along with surface geometry

ArmA and RmtB Were the Predominant 16S RMTase Genes Responsible for Aminoglycoside-resistant Isolates in Korea

Pathogenic gram-negatives that produce 16S ribosomal RNA methyltransferases (16S RMTases) have already been distributed all over the world. To investigate the predominance of aminoglycoside resistance associated with 16S RMTases in Korea, we collected a total of 222 amikacin resistant Gram-negative clinical isolates from patient specimens between 1999 and 2015 from three hospital banks across Korea. ArmA and nntB were the predominant 16S RMTase genes responsible for aminoglycoside-resistant isolates circulating in Korean community settings although only one rmtA-producing isolate was detected in 2006.1

Lepidopterous Insect Fauna of Gyeongju National Park in Korea

AbstractLepidopterous insect fauna of Gyeongju National Park, was investigated during 25-28 April and 10-11 August 2007, especially in Mt. Namsan Zone. In total, 150 species of 21 families belonging to Lepidoptera were identified through this study. Therefore, a total of 183 species under 25 families are recorded from Gyeongju National Park, including the previous studies