Chlorophenyl-benzoxime inhibits pancreatic cancer cell proliferation, invasion and migration by down-regulating the expressions of interleukin-8 and cyclooxygenase-2

Purpose: To investigate the effects of chlorophenyl-benzoxime (CPBZX) on pancreatic cancer (PC) cell proliferation, invasion and migration, and the underlying mechanism of action. Methods: Pancreatic carcinoma cell lines (HuP-T4, HuP-T3 and BxPC-3) were cultured in Dulbecco's Modified Eagle medium (DMEM) containing 10 % fetal bovine serum (FBS), penicillin (100 U/mL) and streptomycin (10 μg/mL) at 37 ˚C in a humidified atmosphere containing 5 % CO2 and 95 % air. Cell proliferation was assessed using MTT assay. Real-time quantitative polymerase chain reaction (qRTPCR) and Western blotting were employed for the determination of changes in the levels of expression of carcinoembryonic antigen (CEA), interleukin-8 (IL-8) and cyclooxygenase-2 (COX 2). Cell invasion and migration were determined using Transwell and wound healing assays, respectively. Results: The results of MTT assay showed that CPBZX significantly and dose-dependently inhibited the proliferation of PC cells (p < 0.05). Incubation of HuP-T4 cells with CPBZX significantly and dosedependently reduced the invasive ability of the cells (p < 0.05). The migratory ability of HuP-T4 cells was also significantly and dose-dependently inhibited by CPBZX (p < 0.05). The results of Western blotting and qRT PCR showed that CPBZX treatment significantly and dose-dependently upregulated CEA mRNA expression (p < 0.05). On the other hand, the expressions of IL-8 and COX-2 were significantly and dose-dependently down-regulated by CPBZX. Treatment of pancreatic tumor mice with CPBZX significantly decreased tumor growth and metastasis of tumor cells to the pulmonary tissues, liver and lymph nodes (p < 0.05). Conclusion: The results of this study suggest that CPBZX inhibits the development and metastasis of PC via the down-regulation of IL-8 and COX 2 expressions, and therefore may find application in pancreatic cancer therapy

User-centered design approaches to integrating intellectual property information into early design processes with a design patent retrieval application

The relationship between intellectual property rights (IPRs) and the development of creativity is always a controversial topic. However, it has seldom been explored from the user-centered design (UCD) perspective. This paper describes how the UCD approach has been employed to develop Design Patent Retrieval Application (acronym: DsPLAi), a mobile app aimed to integrate IPRs related information into early design processes to enhance designers’ IP practice and to facilitate the creative process. Interview studies were first conducted to identify end-users’ understanding of IPRs and related practices. Next, participatory design workshops with designers and IP processionals were organized to understand the interaction between the two parties and their needs, thereby deriving requirements for DsPLAi. A prototype of the app was developed and evaluated with ten industrial designers. The prototype received positive feedback in the usability evaluation. The empirical results showed that the provision of IPRs related information at an early stage could be helpful to the design process and that the designers were positive about the use of DsPLAi in their daily design routines

Exploring personalised autonomous vehicles to influence user trust

Trust is a major determinant of acceptance of an autonomous vehicle (AV), and a lack of appropriate trust could prevent drivers and society in general from taking advantage of such technology. This paper makes a new attempt to explore the effects of personalised AVs as a novel approach to the cognitive underpinnings of drivers’ trust in AVs. The personalised AV system is able to identify the driving behaviours of users and thus adapt the driving style of the AV accordingly. A prototype of a personalised AV was designed and evaluated in a lab-based experimental study of 36 human drivers, which investigated the impact of the personalised AV on user trust when compared with manual human driving and non-personalised AVs. The findings show that a personalised AV appears to be significantly more reliable through accepting and understanding each driver’s behaviour, which could thereby increase a user’s willingness to trust the system. Furthermore, a personalised AV brings a sense of familiarity by making the system more recognisable and easier for users to estimate the quality of the automated system. Personalisation parameters were also explored and discussed to support the design of AV systems to be more socially acceptable and trustworthy

Asymptotically optimal strategy-proof mechanisms for two-facility games

ABSTRACT We consider the problem of locating facilities in a metric space to serve a set of selfish agents. The cost of an agent is the distance between her own location and the nearest facility. The social cost is the total cost of the agents. We are interested in designing strategy-proof mechanisms without payment that have a small approximation ratio for social cost. A mechanism is a (possibly randomized) algorithm which maps the locations reported by the agents to the locations of the facilities. A mechanism is strategy-proof if no agent can benefit from misreporting her location in any configuration. This setting was first studied by Procaccia and Tennenholtz We first prove an Ω(n) lower bound of the social cost approximation ratio for deterministic strategy-proof mechanisms. Our lower bound even holds for the line metric space. This significantly improves the previous constant lower bound

Federated and distributed learning applications for electronic health records and structured medical data: A scoping review

Federated learning (FL) has gained popularity in clinical research in recent years to facilitate privacy-preserving collaboration. Structured data, one of the most prevalent forms of clinical data, has experienced significant growth in volume concurrently, notably with the widespread adoption of electronic health records in clinical practice. This review examines FL applications on structured medical data, identifies contemporary limitations and discusses potential innovations. We searched five databases, SCOPUS, MEDLINE, Web of Science, Embase, and CINAHL, to identify articles that applied FL to structured medical data and reported results following the PRISMA guidelines. Each selected publication was evaluated from three primary perspectives, including data quality, modeling strategies, and FL frameworks. Out of the 1160 papers screened, 34 met the inclusion criteria, with each article consisting of one or more studies that used FL to handle structured clinical/medical data. Of these, 24 utilized data acquired from electronic health records, with clinical predictions and association studies being the most common clinical research tasks that FL was applied to. Only one article exclusively explored the vertical FL setting, while the remaining 33 explored the horizontal FL setting, with only 14 discussing comparisons between single-site (local) and FL (global) analysis. The existing FL applications on structured medical data lack sufficient evaluations of clinically meaningful benefits, particularly when compared to single-site analyses. Therefore, it is crucial for future FL applications to prioritize clinical motivations and develop designs and methodologies that can effectively support and aid clinical practice and research

Asymptotically optimal strategy-proof mechanisms for twofacility games

We consider the problem of locating facilities in a metric space to serve a set of selfish agents. The cost of an agent is the distance between her own location and the nearest facility. The social cost is the total cost of the agents. We are interested in designing strategy-proof mechanisms without payment that have a small approximation ratio for social cost. A mechanism is a (possibly randomized) algorithm which maps the locations reported by the agents to the locations of the facilities. A mechanism is strategy-proof if no agent can benefit from misreporting her location in any configuration. This setting was first studied by Procaccia and Tennenholtz [21]. They focused on the facility game where agents and facilities are located on the real line. Alon et al. studied the mechanisms for the facility games in a general metric space [1]. However, they focused on the games with only one facility. In this paper, we study the two-facility game in a general metric space, which extends both previous models. We first prove an Ω(n) lower bound of the social cost approximation ratio for deterministic strategy-proof mechanisms. Our lower bound even holds for the line metric space. This significantly improves the previous constant lower bounds [21, 17]. Notice that there is a matching linear upper bound in the line metric space [21]. Next, we provide the first randomized strategy-proof mechanism with a constant approximation ratio of 4. Our mechanism works in general metric spaces. For randomized strategy-proof mechanisms, the previous best upper bound is O(n) which works only in the line metric space. This work was done when the two authors were visitin

Asymptotically optimal strategy-proof mechanisms for two-facility games

Abstract We consider the problem of locating facilities in a metric space to serve a set of selfish agents. The cost of an agent is the distance between her own location and the nearest facility. The social cost is the total cost of the agents. We are interested in designing strategy-proof mechanisms without payment that have a small approximation ratio for social cost. A mechanism is a (possibly randomized) algorithm which maps the locations reported by the agents to the locations of the facilities. A mechanism is strategy-proof if no agent can benefit from misreporting her location in any configuration. This setting was first studied by Procaccia and Tennenholtz We first prove an Ω(n) lower bound of the social cost approximation ratio for deterministic strategyproof mechanisms. Our lower bound even holds for the line metric space. This significantly improves the previous constant lower bound

Frontiers in Algorithmics and Algorithmic Aspects in Information and ManagementJoint International Conference, FAW-AAIM 2012, Beijing, China, May 14-16, 2012. Proceedings /

XVII, 370 p. 77 illus.online resource