An Association of Multiple Well Differentiated Liposarcomas, Lipomatous Tissue and Hereditary Retinoblastoma

Well differentiated liposarcoma (atypical lipomatous tumour) is a low grade tumour, with no metastatic potential unless dedifferentiation supervenes. When superficial, it recurs locally only occasionally after marginal excision. We present a patient in whom bilateral childhood retinoblastoma was followed by later development of massive confluent areas of low grade liposarcoma and lipomatous tissue affecting the upper extremities and trunk. We discuss the role of mutations in the retinoblastoma gene (RB1) in linking these conditions and demonstrate the surgical management of an extremely unusual and challenging case

Validating the model of predictors of academic self-handicapping behavior

The main aim of the present study is to validate the model of predictors of self-handicapping behavior (POASH) on the data derived from undergraduate students in an ongoing co-curriculum compulsory course. The study adapted and extended the original theory of reciprocal interaction of emotion, cognition and behavior by adding self-handicapping behavior component. In so doing, this study assessed the direct and indirect effects of emotion, cognition and behavior via student engagement on self-handicapping behavior. The second purpose of the study is to evaluate gender and nationality status invariants of the causal structure of POASH. This cross-validation procedure determined whether gender and nationality status moderated the causal structure of the model, and thus the generality of POASH. The data was collected from two self-reported questionnaires administered to 790 undergraduates of an International Islamic University in Malaysia. A confirmatory three-step approach theory testing and development using Maximum Likelihood method was applied. The results of structured equation modeling supported the adequacy of POASH and the causal structure of POASH proved to be applicable to both genders and nationality statuses

Evaluation of prototype risk prediction tools for clinicians and people living with type 2 diabetes in North West London using the think aloud method

The prevalence of type 2 diabetes in North West London (NWL) is relatively high compared to other parts of the United Kingdom with outcomes suboptimal. This presents a need for more effective strategies to identify people living with type 2 diabetes who need additional support. An emerging subset of web-based interventions for diabetes self-management and population management have used artificial intelligence and machine learning models to stratify the risk of complications from diabetes and identify patients in need of immediate support. In this study, two prototype risk prediction tools on the MyWay Diabetes and MyWay Clinical platforms were evaluated with six clinicians and six people living with type 2 diabetes in North West London using the think aloud method. The results of the sessions with people living with type 2 diabetes showed that the concept of the tool was intuitive, however more instruction on how to correctly use the risk prediction tool would be valuable. The feedback from the sessions with clinicians was that the data presented in the tool aligned with the key diabetes targets in NWL, and that this would be particularly useful for identifying and inviting patients to the practice who are overdue for tests and at-risk of complications. The findings of the evaluation have been used to support the development of the prototype risk predictions tools. This study demonstrates the value of conducting usability and user experience testing on web-based interventions designed to support for supporting the targeted management of type 2 diabetes in local communities