Rasch analysis of the Patient and Observer Scar Assessment Scale (POSAS) in burn scars

The Patient and Observer Scar Assessment Scale (POSAS) is a questionnaire that was developed to assess scar quality. It consists of two separate six-item scales (Observer Scale and Patient Scale), both of which are scored on a 10-point rating scale. After many years of experience with this scale in burn scar assessment, it is appropriate to examine its psychometric properties using Rasch analysis. Cross-sectional data collection from seven clinical trials resulted in a data set of 1,629 observer scores and 1,427 patient scores of burn scars. We examined the person-item map, item fit statistics, reliability, response category ordering, and dimensionality of the POSAS. The POSAS showed an adequate fit to the Rasch model, except for the item surface area. Person reliability of the Observer Scale and Patient Scale was 0.82 and 0.77, respectively. Dimensionality analysis revealed that the unexplained variance by the first contrast of both scales was 1.7 units. Spearman correlation between the Observer Scale Rasch measure and the overall opinion of the clinician was 0.75. The Rasch model demonstrated that the POSAS is a reliable and valid scale that measures the single-construct scar qualit

Clinical development of new drug-radiotherapy combinations.

In countries with the best cancer outcomes, approximately 60% of patients receive radiotherapy as part of their treatment, which is one of the most cost-effective cancer treatments. Notably, around 40% of cancer cures include the use of radiotherapy, either as a single modality or combined with other treatments. Radiotherapy can provide enormous benefit to patients with cancer. In the past decade, significant technical advances, such as image-guided radiotherapy, intensity-modulated radiotherapy, stereotactic radiotherapy, and proton therapy enable higher doses of radiotherapy to be delivered to the tumour with significantly lower doses to normal surrounding tissues. However, apart from the combination of traditional cytotoxic chemotherapy with radiotherapy, little progress has been made in identifying and defining optimal targeted therapy and radiotherapy combinations to improve the efficacy of cancer treatment. The National Cancer Research Institute Clinical and Translational Radiotherapy Research Working Group (CTRad) formed a Joint Working Group with representatives from academia, industry, patient groups and regulatory bodies to address this lack of progress and to publish recommendations for future clinical research. Herein, we highlight the Working Group's consensus recommendations to increase the number of novel drugs being successfully registered in combination with radiotherapy to improve clinical outcomes for patients with cancer.National Institute for Health ResearchThis is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/nrclinonc.2016.7

Supraorbital morphology and social dynamics in human evolution

Uniquely, with respect to Middle Pleistocene hominins, anatomically modern humans do not possess marked browridges, and have a more vertical forehead with mobile eyebrows that play a key role in social signalling and communication. The presence and variability of browridges in archaic Homo and their absence in ourselves have led to debate concerning their morphogenesis and function, with two main hypotheses being put forward; that browridge morphology is the result of the spatial relationship between the orbits and the braincase, and that browridge morphology is significantly impacted by biting mechanics. Here we virtually manipulate browridge morphology of an archaic hominin (Kabwe 1), showing that it is much larger than the minimum required to fulfil spatial demands and that browridge size has little impact on mechanical performance during biting. Since browridge morphology in this fossil is not driven by spatial and mechanical requirements alone, the role of the supraorbital region in social communication is a potentially significant factor. We propose that conversion of the large browridges of our immediate ancestors to a more vertical frontal in modern humans allowed highly mobile eyebrows to display subtle affiliative emotions

Does corporate reputation matter? Role of social media in consumer intention to purchase innovative food product

The exponential growth of the corporate reputation in food industry has resulted in innovations in every link of its supply chain. There have been studies that have characterized innovation in various industries from the perspective of technology, but far fewer in the area of corporate reputation, consumer perception, and intention towards innovations in food products. This research analyses the innovations in the food industry from the perspective of the consumer and provides a conceptual framework of food innovation stages. The study also investigates the relationship between corporate reputation and intention towards food innovation along with the other components of TPB model with an extension of social media engagement. The results from India and US samples confirm that social media engagement have a significant role to play in creating intention to purchase innovative food products. The study compares the US and Indian samples and identifies differences in subjective norms and perceived behavioural control

Identification of structured LTI MIMO state-space models

The identification of structured state-space model has been intensively studied for a long time but still has not been adequately addressed. The main challenge is that the involved estimation problem is a non-convex (or bilinear) optimization problem. This paper is devoted to developing an identificationmethod which aims to find the global optimal solution under mild computational burden. Key to the developed identification algorithm is to transform a bilinear estimation to a rank constrained optimization problem and further a difference of convex programming (DCP) problem. The initial conditionfor the DCP problem is obtained by solving its convex part of the optimization problem which happens to be a nuclear norm regularized optimization problem. Since the nuclear norm regularized optimization is the closest convex form of the low-rank constrained estimation problem, the obtained initialcondition is always of high quality which provides the DCP problem a good starting point. The DCP problem is then solved by the sequential convex programming method. Finally, numerical examples are included to show the effectiveness of the developed identification algorithm