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BACKGROUND AND AIM Microbiota have been associated with several diseases including colorectal cancer (CRC). This study aimed to evaluate the microbiota in early/invasive CRC utilizing stool and cytological brushes to determine differences in relative abundance (RA). METHODS Colonoscopy patients referred for endoscopic submucosal dissection or previous to CRC surgery were prospectively enrolled. Stool was collected pre-bowel preparation; and brush samples were taken during colonoscopy (three regions). DNA extraction, 16S rRNA next generation sequencing, and biostatistics (qiime and stamp software packages) followed. Primary outcome was the difference in RA of the Fusobacterium genus between the groups. Secondary outcomes included analyses of other microbiota. RESULTS Twenty-five patients were included, of which 14 had invasive cancer (≥ 1000 mm into the submucosa). The three major genera for invasive cancer were Bacterioides, Oribacterium, and Fusobacterium, whereas for early cancer were Oribacterium, Bacterioides, and Prevotella (decreasing order of RA). There was a significantly higher RA of Fusobacterium in the invasive cancer group (9.65% vs 0.95%, respectively, P

Mucosal healing is the main treatment goal for Crohn’s disease. In this situation, some patients have difficulty with endoscopic evaluation of the entire small intestine. Crohn’s disease is closely associated with the gut microbiota, but the relationship between the microbiome and disease activity in the small intestine remains unclear. We examined the association between the microbiome and endoscopic findings in the small intestine and determined whether the microbiome can predict mucosal healing. The patients with Crohn’s disease who were scheduled for capsule or balloon-assisted endoscopy were included in this prospective study. Patients whose entire small intestine was evaluated were divided into two groups based on ulcerative findings. The microbiomes in the fecal samples were analyzed using 16S rRNA sequencing. The 38 enrolled patients were divided into the ulcer group (24) and mucosal healing group (14). The ulcer group exhibited lower α diversity. Six genera, namely Faecalibacterium (P = 0.008), Lachnospira (P = 0.009), Paraprevotella (P = 0.01), Dialister (P = 0.012), Streptococcus (P = 0.025), and Clostridium (P = 0.028) were enriched in the mucosal healing group. A predictive score for mucosal healing was defined using these six genera. The area under the curve was 0.795 and the sensitivity and specificity for predicting mucosal healing were 0.643 and 0.917, respectively. Fecal microbiome is corelated with disease activity in the entire small intestine in Crohn’s disease patients. The predictive score proposed by microbiota characteristics was a potential biomarker for mucosal healing in the small intestine.

In order to sell items of a genre that each user is not interested in, their latent interests of the genre have to be induced. Therefore, we focus on "Influencer," who is the person that has a large impact on a user's behaviors, and research a recommender system which advertises some items by utilizing influencer's remarks via social media. This paper investigates what kinds of remarks and remarkers would induce users'interests. As the result, we have revealed many findings. One is that "One of the factors that would induce the users' positive interests on the movie, is the positive reputation for the movie that is included in tweets." The other is that "If the user does not like the remarker, the user's negative interests for the items in the remarks of the person would be induced, even though the person has famousness.", INSPEC Accession Number: 18674306

PBLs signifies both problem-based learning and project-based learning; we clearly distinguish between the two types of PBLs. The former PBL involves finding ways to solve problems under unfavorable conditions. In the curriculum at our institute, problem-based learning has been conducted since 2006. By contrast, project-based learning involves a student team undertaking an actual project, devised by a company. We did not adopt project-based learning in our curriculum. In 2016, our institute joined the Education Network for Practical Information Technology project of Japan’s Ministry of Education, Culture, Sports, Science and Technology. In that project, around 40 universities are engaged in developing a cooperative network. Each university develops practical education using PBL; its knowledge and resources obtained are shared among other universities in the network. For our part of the project, we added 3 practical exercises based on project-based learning. By combining the two different types of PBL, our curriculum provides exercises that introduce better problem-solving skills, instill a challenging spirit, and provide practical experience for students. In this paper, we report our exercises and practical results for 2017.

A 44-year-old woman was referred to our hospital because of a cystic lesion in the pancreatic body that was found by computed tomography (CT) as a result of a screening for impaired liver function after the patient presented with a high fever in 2011. Trans-abdominal ultrasonography (US) revealed a 33-mm unilocular cyst within the pancreatic body and a 5-mm hypoechoic mass in the pancreatic neck. Contrast-enhanced CT showed a slight enhancement around the cyst and a mild dilation of the main pancreatic duct, but neither septum nor nodule was detected inside. Contrast-enhanced endoscopic ultrasonography (CE-EUS) revealed a hyperechoic elevated lesion inside the cystic lesion without enhancement in the pancreatic body; CE-EUS also revealed a 5-mm homogeneous hypoechoic mass with a remarkable enhancement in the pancreatic neck with the use of Sonazoid(®) as a contrast medium. These lesions were diagnosed as a pancreatic pseudocyst and a neuroendocrine tumor (NET), respectively, and were followed up with periodic examinations. The cystic lesion showed contraction 6 months after the initial exam. However, US revealed an enlargement of the cystic lesion to 40 mm in diameter 2 years after the initial exam, and EUS showed irregular thickening of the wall with a cyst-in-cyst appearance. The diagnoses of a mucinous cystic neoplasm (MCN) and a concomitant small NET were made after a distal pancreatectomy. We herein report a rare case of MCN that showed various morphological changes over 2 years of observation.

In the Web world, one user creates and uploads a Web document about a phenomenon or event in the physical world, while another user retrieves and consumes Web documents by submitting a Web query. There have been many researches to mine Web documents in the exploding Web world, especially User Generated Content such as weblogs and microblogs, for knowledge about various phenomena and events in the physical world, and also Web services with the Web-mined knowledge have been made available for the public. However, there are few detailed investigations on how accurately Web-mined data reflect physical-world data. It must be socially-problematic to immoderately utilize the Web-mined data in public Web services without ensuring their accuracy sufficiently. Therefore, the previous papers introduced various Web Sensors to extract spatiotemporal data about a target phenomenon from Web documents searched by keyword(s) representing the target phenomenon, and tried to validate the potential and reliability of the Web-sensed spatiotemporal data. Moreover, this paper compares spatio-temporal Web Sensors analyzing Web queries and/or Web documents. 

To enable us to select the only scenes that we want to watch in a baseball video and personalize its highlights subvideo, we require an Automatic Baseball Video Tagging system that divides a baseball video into multiple sub-videos per at-bat scene automatically and also appends tag information relevant to at-bat scenes. The previous paper proposed several Tagging algorithms using ball-by-ball textual report and voice recognition. To improve our system, this paper introduces a more refined model for baseball games, and performs comparative experiments on models with regard to their recall, precision, and F-measure.

The Gipie/GRP78 interaction serves as a molecular switch for the regulation of the apoptotic signaling pathway, which appears to contribute to the protection of endothelial cells from endoplasmic reticulum stress-induced apoptosis., Continued exposure of endothelial cells to mechanical/shear stress elicits the unfolded protein response (UPR), which enhances intracellular homeostasis and protect cells against the accumulation of improperly folded proteins. Cells commit to apoptosis when subjected to continuous and high endoplasmic reticulum (ER) stress unless homeostasis is maintained. It is unknown how endothelial cells differentially regulate the UPR. Here we show that a novel Girdin family protein, Gipie (78 kDa glucose-regulated protein [GRP78]-interacting protein induced by ER stress), is expressed in endothelial cells, where it interacts with GRP78, a master regulator of the UPR. Gipie stabilizes the interaction between GRP78 and the ER stress sensor inositol-requiring protein 1 (IRE1) at the ER, leading to the attenuation of IRE1-induced c-Jun N-terminal kinase (JNK) activation. Gipie expression is induced upon ER stress and suppresses the IRE1-JNK pathway and ER stress-induced apoptosis. Furthermore we found that Gipie expression is up-regulated in the neointima of carotid arteries after balloon injury in a rat model that is known to result in the induction of the UPR. Thus our data indicate that Gipie/GRP78 interaction controls the IRE1-JNK signaling pathway. That interaction appears to protect endothelial cells against ER stress-induced apoptosis in pathological contexts such as atherosclerosis and vascular endothelial dysfunction.

This paper introduces the concept of Secure Spaces, one step ahead of Smart Spaces, on information security. We define Secure Spaces as physically isolated environments in which any resource is completely protected from its unauthorized objects with respect to information security. In other words, only if inside them, any information resource is completely protected from being accessed by its unauthorized visitors, and any visitor is completely protected from being exposed to her unwanted information resources. To build such a secure Smart Space, we propose a formalized model and architecture for space entry control based on its dynamically changing contents such as its visitors, physical information resources, and virtual information resources via its embedded output devices.

We experience or forecast various phenomena (e.g., rain, snow, earthquake) in the physical world, while we carry out various actions (e.g., blogging, searching, e-shopping) in the Web world. There have been many researches to mine the exploding Web world for knowledge about various phenomena and events in the physical world, and also Web services with the Web-mined knowledge have been made available for the public. However, there are few detailed investigations on how accurately Web-mined data reflect physical-world data. It must be socially-problematic to idolatrously utilize the Web-mined data in public Web services without ensuring their accuracy sufficiently. This paper introduces temporally-shifted Web Sensors with a temporal shift parameter δ to extract spatiotemporal numerical value about a physical phenomenon from Web documents searched by linguistic keyword(s) representing the physical phenomenon, and analyzes the spatiotemporal dependency of the temporal shift parameter δ with respect to their coefficient correlation with Japan Meteorological Agency's spatiotemporal statistics.

A 45-year-old woman visited our hospital due to upper left quadrant pain and melena. Colonoscopy revealed longitudinal ulcers in the transverse colon. The endoscopic findings and pathological examination of a biopsy specimen led to diagnosis of Crohn disease, and mesalazine was administered. Although the colorectal lesions showed improvement with mesalazine, a blood test revealed elevation of biliary enzymes. Endoscopic retrograde cholangiopancreatography showed diffuse narrowing of the main pancreatic duct and smooth stricture of the distal bile duct. Steroid therapy improved the pancreatic lesion, which was diagnosed as type 2 autoimmune pancreatitis.

In recent years, many researches to mine the exploding Web world, especially User Generated Content (UGC) such as weblogs, for knowledge about various phenomena and events in the physical world have been done actively, and also Web services with the Web-mined knowledge have begun to be developed for the public. However, there are few detailed investigations on how accurately Web-mined data reflect physical-world data. It must be problematic to idolatrously utilize the Web-mined data in public Web services without ensuring their accuracy sufficiently. Therefore, this paper introduces the simplest Web Sensor and spatiotemporallynormalized Web Sensor to extract spatiotemporal data about a target phenomenon from weblogs searched by keyword(s) representing the target phenomenon, and tries to validate the potential and reliability of the Web-sensed spatiotemporal data by four kinds of granularity analyses of coefficient correlation with temperature, rainfall, snowfall, and earthquake statistics per day by region of Japan Meteorological Agency as physical-world data: spatial granularity (region-s population density), temporal granularity (time period, e.g., per day vs. per week), representation granularity (e.g., "rain" vs. "heavy rain"), and media granularity (weblogs vs. microblogs such as Tweets).

As next steps of Image Retrieval, it is very important to discriminate between “Typical Images” and “Peculiar Images” in the acceptable images, and moreover, to collect many different kinds of peculiar images exhaustively. As a solution to the 1st next step, my previous work has proposed a novel method to more precisely search the Web for peculiar images of a target object by its peculiar appearance descriptions (e.g., color-names) extracted from the Web and/or its peculiar image features (e.g., color-features) converted from them. This paper proposes a refined method equipped with cross-language (translation between Japanese and English) functions and validates its retrieval precision.

Most researches on Image Retrieval (IR) have aimed at clearing away noisy images and allowing users to search only acceptable images for a target object specified by its object-name. We have become able to get enough acceptable images of a target object just by submitting its object-name to a conventional keyword-based Web image search engine. However, because the search results rarely include its uncommon images, we can often get only its common images and cannot easily get exhaustive knowledge about its appearance (look and feel). As next steps of IR, it is very important to discriminate between “Typical Images” and “Peculiar Images” in the acceptable images, and moreover, to collect many different kinds of peculiar images exhaustively. This paper proposes a method to search the Web for peculiar images by expanding or modifying a target object-name (as an original query) with its hyponyms based on hand-made concept hierarchies such as WordNet and Wikipedia.

This paper discusses PBL for first year software education, paying attention to aspects of holistic learning, and also proposes a new PLB course based on the discussion. The PBL course was given to high school students to confirm fundamental validity. The questionnaire method suggested that PBL might be fundamentally useful to learn holistically.

Automatic knowledge extraction from such a very large document corpus as the Web is one of the hottest research topics in the domain of Artificial Intelligence and Database technologies. This chapter introduces my object-oriented and the existing methods to extract semantic (e.g., hyponymy and meronymy) and sensory (e.g., visual and aural) knowledge from the Web, and compares them by showing several experimental results. My object-oriented semantic knowledge extraction is based on property inheritance(s) and property aggregation, and repeatedly improves the extracted results of both hyponymy and meronymy relations. Meanwhile, my object-oriented sensory knowledge extraction is improved by utilizing the extracted hyponymy and meronymy relations. Finally, this chapter introduces my Sense-based Object-name Search (SOS) to enable users to identify the concrete name of a target object which they do not know only by inputting its hyponym (class-name) and some sensory descriptions, as an application system to utilize the Web-extracted semantic and sensory knowledge.

Concept hierarchies, such as hyponymy and meronymy relations, are very important for various natural language processing systems. Many researchers have tackled how to mine very large corpora of documents such as the Web for them not manually but automatically. However, their methods are mostly based on lexico-syntactic patterns as not necessary but sufficient conditions of concept hierarchies, so they can achieve high precision but low recall when using stricter patterns or they can achieve high recall but low precision when using looser patterns. In this paper, property inheritance from a concept to its hyponyms is assumed to be necessary and sufficient conditions of hyponymy relations to achieve high recall and not low precision, and we propose a method to acquire hyponymy relations from the Web based on property inheritance.

This paper presents a method to extract appearance descriptions for a given set of objects. Conversion between an object name and its appearance descriptions is useful for various applications, such as searching for an unknown object, memory recall support, and car/walk navigation. The method is based on text mining applied to Web search results. Using a manually constructed dictionary of visual modifiers, our system obtains a set of pairs of a visual modifier and a component/class for a given name of object, which best describe its appearance. The experimental results have demonstrated the effectiveness of our method in discovering appearance descriptions of various types of objects.