Physical consequences of falls in the elderly: a literature review from 1995 to 2010

In the last decade, population ageing has been registered as a global phenomenon. A relation exists between falling and ageing, since falling frequency increases significantly with age. In fact, one in three older adult falls annually. Although ageing is generically associated with decrease and degeneration of psychological and physical functions, it is still not common for the correct identification of risk factors to lead to a clinical prognosis of the elder being in risk of falling. Therefore, the goal of this review article is to identify, categorise and analyse typical ageing and fall factors mentioned in the literature as well as to quantify the number of times they were referenced. The research considered hundreds of publications, but analysis was then restricted to the 87 most pertinent articles written in English and published in journals or scientific magazines between 1995 and 2010. We concluded that falls among older adults can be characterised by the following: anatomic characteristics and physiological consequences of ageing; the pathologies that induce falls, which can be neurological, musculoskeletal, cardiovascular and other diseases; causes and risk factors of falls that can be behavioural, biological, environmental or socio-economic; type of physical consequences of falls, including fractures, bruises, injuries or other physical consequences; and strategies to prevent, mitigate or rehabilitate, which can be of a physical, environmental or behavioural nature.

Physical consequences of falls in the elderly: a literature review from 1995 to 2010

In the last decade, population ageing has been registered as a global phenomenon. A relation exists between falling and ageing, since falling frequency increases significantly with age. In fact, one in three older adult falls annually. Although ageing is generically associated with decrease and degeneration of psychological and physical functions, it is still not common for the correct identification of risk factors to lead to a clinical prognosis of the elder being in risk of falling. Therefore, the goal of this review article is to identify, categorise and analyse typical ageing and fall factors mentioned in the literature as well as to quantify the number of times they were referenced. The research considered hundreds of publications, but analysis was then restricted to the 87 most pertinent articles written in English and published in journals or scientific magazines between 1995 and 2010. We concluded that falls among older adults can be characterised by the following: anatomic characteristics and physiological consequences of ageing; the pathologies that induce falls, which can be neurological, musculoskeletal, cardiovascular and other diseases; causes and risk factors of falls that can be behavioural, biological, environmental or socio-economic; type of physical consequences of falls, including fractures, bruises, injuries or other physical consequences; and strategies to prevent, mitigate or rehabilitate, which can be of a physical, environmental or behavioural nature.

An image processing application for quantification of protein aggregates in Caenorhabditis elegans

Protein aggregation became a widely accepted marker of many polyQ disorders, including Machado-Joseph disease (MJD), and is often used as readout for disease progression and development of therapeutic strategies. The lack of good platforms to rapidly quantify protein aggregates in a wide range of disease animal models prompted us to generate a novel image processing application that automatically identifies and quantifies the aggregates in a standardized and operator-independent manner. We propose here a novel image processing tool to quantify the protein aggregates in a Caenorhabditis elegans (C. elegans) model of MJD. Confocal mi-croscopy images were obtained from animals of different genetic conditions. The image processing application was developed using MeVisLab as a platform to pro-cess, analyse and visualize the images obtained from those animals. All segmenta-tion algorithms were based on intensity pixel levels.The quantification of area or numbers of aggregates per total body area, as well as the number of aggregates per animal were shown to be reliable and reproducible measures of protein aggrega-tion in C. elegans. The results obtained were consistent with the levels of aggrega-tion observed in the images. In conclusion, this novel imaging processing applica-tion allows the non-biased, reliable and high throughput quantification of protein aggregates in a C. elegans model of MJD, which may contribute to a significant improvement on the prognosis of treatment effectiveness for this group of disor-ders