Papillary Thyroid Carcinoma of a Diffuse Sclerosing Variant: Ultrasonographic Monitoring from a Normal Thyroid Gland to Mass Formation

A diffuse sclerosing variant of papillary thyroid carcinoma is uncommon and has a tendency for rapid growth and a higher incidence of cervical lymph node metastases. We experienced a case of a diffuse sclerosing variant of papillary thyroid carcinoma in a 48-year-old man. This case showed benign features on initial ultrasonography and positron emission tomography (PET) scan. A new nodule was detected on follow-up ultrasonography that showed rapid enlargement. This case was confirmed by surgical excision. We herein describe the initial and follow-up ultrasonographic findings of a diffuse sclerosing variant of papillary thyroid carcinoma

Establishment of Efficacy and Safety Assessment of Human Adipose Tissue-Derived Mesenchymal Stem Cells (hATMSCs) in a Nude Rat Femoral Segmental Defect Model

Human adipose tissue-derived mesenchymal stem cell (hATMSC) have emerged as a potentially powerful tool for bone repair, but an appropriate evaluation system has not been established. The purpose of this study was to establish a preclinical assessment system to evaluate the efficacy and safety of cell therapies in a nude rat bone defect model. Segmental defects (5 mm) were created in the femoral diaphyses and transplanted with cell media (control), hydroxyapatite/tricalcium phosphate scaffolds (HA/TCP, Group I), hATMSCs (Group II), or three cell-loading density of hATMSC-loaded HA/TCP (Group III-V). Healing response was evaluated by serial radiography, micro-computed tomography and histology at 16 weeks. To address safety-concerns, we conducted a GLP-compliant toxicity study. Scanning electron microscopy studies showed that hATMSCs filled the pores/surfaces of scaffolds in a cell-loading density-dependent manner. We detected significant increases in bone formation in the hATMSC-loaded HA/TCP groups compared with other groups. The amount of new bone formation increased with increases in loaded cell number. In a toxicity study, no significant hATMSC-related changes were found in body weights, clinical signs, hematological/biochemical values, organ weights, or histopathological findings. In conclusion, hATMSCs loaded on HA/TCP enhance the repair of bone defects and was found to be safe under our preclinical efficacy/safety hybrid assessment system

Examining the hierarchy of destination brands and the chain of effects between brand equity dimensions

ABSTRACT: This paper focuses on the customer-based brand equity for a tourist destination, and develops a model including the dimensions of this construct (i.e. awareness, image, perceived quality and loyalty). Accordingly, loyalty is considered the main dependent variable in the model developed here. A major contribution of this paper is that it takes into account the hierarchy of destination brands and analyzes not only the chain of effects between the dimensions of brand equity for a regional destination but also the influence of the country destination image (i.e. the country is considered to be an umbrella brand) on the perceived image of one of its regional destinations. Another significant contribution is made by examining the moderating effect of country familiarity on the relationship with both types of image. The empirical evidence obtained from a sample of 253 international tourists visiting a regional destination in Spain supports the hypothesis that loyalty towards a destination is positively influenced by the perceived quality of the destination, which in turn is directly influenced by the image and awareness of that destination. Additionally, the results support the idea that perceptions of a regional destination are positively influenced by the perceptions of the country destination in which the region is located. However, a moderating effect of country familiarity on the relationship with either type of image was not supported in this research. This could be because in a country where there are a lot of destination brands, being more familiar with the country does not necessarily imply a more accurate knowledge of its regional destinations

Position Prediction in Space System for Vehicles Using Artificial Intelligence

This paper deals with the prediction of the future location of vehicles, which is attracting attention in the era of the fourth industrial revolution and is required in various fields, such as autonomous vehicles and smart city traffic management systems. Currently, vehicle traffic prediction models and accident prediction models are being tested in various places, and considerable progress is being made. However, there are always errors in positioning when using wireless sensors due to various variables, such as the appearance of various substances (water, metal) that occur in the space where radio waves exist. There have been various attempts to reduce the positioning error in such an Internet of Things environment, but there is no definitive method with confirmed performance. Of course, location prediction is also not accurate. In particular, since a vehicle moves rapidly in space, it is increasingly affected by changes in the environment. Firstly, it was necessary to develop a spatial positioning algorithm that can improve the positioning accuracy. Secondly, for the data generated by the positioning algorithm, a machine learning method suitable for position prediction was developed. Based on the above two developed algorithms, through experiments, we found a means to reduce the error of positioning through radio waves and to increase the accuracy of positioning. We started with the idea of changing the positioning space itself from a three-dimensional space into a two-dimensional one. With changes in the time and space of radio wave measurement, the location was measured by transforming the spatial dimension to cope with environmental changes. This is a technology that predicts a location through machine learning on time series data using a direction angle classification technique. An experiment was conducted to verify the performance of the proposed technology. As a result, the accuracy of positioning was improved, and the accuracy of location prediction increased in proportion to the learning time. It was possible to confirm the prediction accuracy increase of up to 80% with changes. Considering that the accuracy result for location prediction presented by other researchers is 70%, through this study, the result was improved by 10% compared to the existing vehicle location prediction accuracy. In conclusion, this paper presents a positioning algorithm and machine learning methodology for vehicle positioning. By proving its usefulness through experiments, this study provides other researchers with a new definition of space for predicting the location of a vehicle, and a machine learning method using direction angles

Indian monsoon variability in the Mahanadi Basin over the last two glacial cycles and its implications on the Indonesian throughflow

The orbital-scale variability of the Indian summer monsoon (ISM) has been influenced by multiple factors, such as atmospheric CO2 concentration, global ice volume, and insolation. Proxies for weathering activity and paleo-productivity provide potential insights into the driving forces of its variability. We documented multi-proxy data at IODP Site U1445, located in the Mahanadi Basin of the northwestern Bay of Bengal, to find out ISM variability over the last 200 ka. The proxy records, such as Nd/Sr isotopes of detrital particles, clay mineral compositions of the fine-grained sediments, biogenic opal and CaCO3, organic carbon contents, and carbon isotopes of organic matter, represent sediment sources, weathering patterns, and paleo-productivity related to the ISM variability. Detrital Nd/Sr isotope data and clay mineral compositions suggest that the sediments at Site U1445 originated mainly from the Ganges, Brahmaputra, and Meghna rivers without dramatic provenance change between the glacial and interglacial periods. The weathering activity inferred from clay mineral compositions and the paleo-productivity shift reconstructed by biogenic opal and CaCO3 contents suggest that the land-sea interactions were closely linked to the ISM precipitation between the glacial and interglacial periods. High precipitation by the strong ISM resulted in intense chemical weathering and dominant biogenic opal deposition during the interglacial periods. In contrast, low precipitation by the weak ISM led to reduced chemical weathering and predominant CaCO3 deposition during the glacial periods. Further, the ISM variability driving the land-sea interactions in the Mahanadi Basin was modulated by the Indonesian throughflow (ITF). Our study emphasizes the role of low-latitude forcing of climatic changes in the strong relationship between the ISM and ITF over orbital periods, providing a base for future investigations