New semiquantitative ultrasonographic score for peripheral arterial disease assessment and its association with cardiovascular risk factors

The data concerning the distribution, extent and progression of peripheral arterial disease (PAD), as well as its association with traditional cardiovascular (CV) risk factors, have generally been obtained from studies of patients in advanced stages of the disease undergoing surgical or endovascular treatment. In this study, we have introduced a new semiquantitative ultrasonographic score (ultrasonographic lower limb atherosclerosis (ULLA) score) that is able to categorize lower limb atherosclerotic lesions at all stages of PAD. We then associated these ultrasonographic categories with a CV risk profile. We enrolled 320 consecutive subjects with symptoms suggestive of PAD or with known CV risk factors referring to our angiology unit between 1 July 2014 and 30 June 2015 for ultrasonographic evaluation of the lower limb arteries. Femoropopliteal and run-off segments were categorized together and separately based on their ultrasonographic characteristics. In univariate and multivariate analyses, the ULLA scores were significantly associated with the main CV risk factors, that is, age, male gender, cigarette smoking, arterial hypertension, diabetes, dyslipidemia, sedentary lifestyle, previous CV events and family history of CV disease, and also confirming the specific association of single risk factors with different segments of lower limb arteries. The proposed ULLA score enables a complete evaluation of the entire lower limb atherosclerotic burden, extending the results concerning the association of PAD with CV risk factors to all stages of the disease, including the early stages. It can be feasible that this new score will facilitate better evaluation of the progression of PAD and its prospective role in CV risk stratification

Trends in template/fragment-free protein structure prediction

Predicting the structure of a protein from its amino acid sequence is a long-standing unsolved problem in computational biology. Its solution would be of both fundamental and practical importance as the gap between the number of known sequences and the number of experimentally solved structures widens rapidly. Currently, the most successful approaches are based on fragment/template reassembly. Lacking progress in template-free structure prediction calls for novel ideas and approaches. This article reviews trends in the development of physical and specific knowledge-based energy functions as well as sampling techniques for fragment-free structure prediction. Recent physical- and knowledge-based studies demonstrated that it is possible to sample and predict highly accurate protein structures without borrowing native fragments from known protein structures. These emerging approaches with fully flexible sampling have the potential to move the field forward

Bioreactor for microalgal cultivation systems: strategy and development

Microalgae are important natural resources that can provide food, medicine, energy and various bioproducts for nutraceutical, cosmeceutical and aquaculture industries. Their production rates are superior compared to those of terrestrial crops. However, microalgae biomass production on a large scale is still a challenging problem in terms of economic and ecological viability. Microalgal cultivation system should be designed to maximize production with the least cost. Energy efficient approaches of using light, dynamic mixing to maximize use of carbon dioxide (CO2) and nutrients and selection of highly productive species are the main considerations in designing an efficient photobioreactor. In general, optimized culture conditions and biological responses are the two overarching attributes to be considered for photobioreactor design strategies. Thus, fundamental aspects of microalgae growth, such as availability of suitable light, CO2 and nutrients to each growing cell, suitable environmental parameters (including temperature and pH) and efficient removal of oxygen which otherwise would negatively impact the algal growth, should be integrated into the photobioreactor design and function. Innovations should be strategized to fully exploit the wastewaters, flue-gas, waves or solar energy to drive large outdoor microalgae cultivation systems. Cultured species should be carefully selected to match the most suitable growth parameters in different reactor systems. Factors that would decrease production such as photoinhibition, self-shading and phosphate flocculation should be nullified using appropriate technical approaches such as flashing light innovation, selective light spectrum, light-CO2 synergy and mixing dynamics. Use of predictive mathematical modelling and adoption of new technologies in novel photobioreactor design will not only increase the photosynthetic and growth rates but will also enhance the quality of microalgae composition. Optimizing the use of natural resources and industrial wastes that would otherwise harm the environment should be given emphasis in strategizing the photobioreactor mass production. To date, more research and innovation are needed since scalability and economics of microalgae cultivation using photobioreactors remain the challenges to be overcome for large-scale microalgae production

Unplanned medication discontinuation as a potential pharmacovigilance signal : a nested young person cohort study

Because of relatively small treatment numbers together with low adverse drug reaction (ADR) reporting rates the timely identification of ADRs affecting children and young people is problematic. The primary objective of this study was to assess the utility of unplanned medication discontinuation as a signal for possible ADRs in children and young people. Using orlistat as an exemplar, all orlistat prescriptions issued to patients up to 18 years of age together with patient characteristics, prescription duration, co-prescribed medicines and recorded clinical (Read) codes were identified from the Primary Care Informatics Unit database between 1st Jan 2006-30th Nov 2009. Binary logistic regression was used to assess association between characteristics and discontinuation. During the study period, 79 patients were prescribed orlistat (81% female, median age 17 years). Unplanned medication discontinuation rates for orlistat were 52% and 77% at 1 and 3-months. Almost 20% of patients were co-prescribed an anti-depressant. One month unplanned medication discontinuation was significantly lower in the least deprived group (SIMD 1-2 compared to SIMD 9-10 OR 0.09 (95% CI0.01 - 0.83)) and those co-prescribed at least one other medication. At 3 months, discontinuation was higher in young people (≥17 yr versus, OR 3.07 (95% CI1.03 - 9.14)). Read codes were recorded for digestive, respiratory and urinary symptoms around the time of discontinuation for 24% of patients. Urinary retention was reported for 7.6% of patients. Identification of unplanned medication discontinuation using large primary care datasets may be a useful tool for pharmacovigilance signal generation and detection of potential ADRs in children and young people