Falls not only present a considerable health threat, but the resulting treatment and loss of working days also place a heavy economic burden on society. Gait instability is a major fall risk factor, particularly in geriatric patients, and walking is one of the most frequent dynamic activities of daily living. To allow preventive strategies to become effective, it is therefore imperative to identify individuals with an unstable gait. Assessment of dynamic stability and gait variability via biomechanical measures of foot kinematics provides a viable option for quantitative evaluation of gait stability, but the ability of these methods to predict falls has generally not been assessed. Although various methods for assessing gait stability exist, their sensitivity and applicability in a clinical setting, as well as their cost-effectiveness, need verification. The objective of this systematic review was therefore to evaluate the sensitivity of biomechanical measures that quantify gait stability among elderly individuals and to evaluate the cost of measurement instrumentation required for application in a clinical setting. To assess gait stability, a comparative effect size (Cohen's d ) analysis of variability and dynamic stability of foot trajectories during level walking was performed on 29 of an initial yield of 9889 articles from four electronic databases. The results of this survey demonstrate that linear variability of temporal measures of swing and stance was most capable of distinguishing between fallers and non-fallers, whereas step width and stride velocity prove more capable of discriminating between old versus young (OY) adults. In addition, while orbital stability measures (Floquet multipliers) applied to gait have been shown to distinguish between both elderly fallers and non-fallers as well as between young and old adults, local stability measures (ls) have been able to distinguish between young and old adults. Both linear and nonlinear measures of foot time series during gait seem to hold predictive ability in distinguishing healthy from fall-prone elderly adults. In conclusion, biomechanical measurements offer promise for identifying individuals at risk of falling and can be obtained with relatively low-cost tools. Incorporation of the most promising measures in combined retrospective and prospective studies for understanding fall risk and designing preventive strategies is warranted.

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There is growing evidence that adaptive immunity contributes to endogenous regeneration processes: For example, endogenous bone fracture repair is modulated by T cells even in the absence of infection. Because delayed or incomplete fracture healing is associated with poor long-term outcomes and high socioeconomic costs, we investigated the relationship between an individual's immune reactivity and healing outcome. Our study revealed that delayed fracture healing significantly correlated with enhanced levels of terminally differentiated CD8(+) effector memory T (TEMRA) cells (CD3(+)CD8(+)CD11a(++)CD28(-)CD57(+) T cells) in peripheral blood. This difference was long lasting, reflecting rather the individual's immune profile in response to lifelong antigen exposure than a post-fracture reaction. Moreover, CD8(+) TEMRA cells were enriched in fracture hematoma; these cells were the major producers of interferon-γ/tumor necrosis factor-α, which inhibit osteogenic differentiation and survival of human mesenchymal stromal cells. Accordingly, depletion of CD8(+) T cells in a mouse osteotomy model resulted in enhanced endogenous fracture regeneration, whereas a transfer of CD8(+) T cells impaired the healing process. Our data demonstrate the high impact of the individual adaptive immune profile on endogenous bone regeneration. Quantification of CD8(+) TEMRA cells represents a potential marker for the prognosis of the healing outcome and opens new opportunities for early and targeted intervention strategies.

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Accurate measurement of underlying bone positions is important for the understanding of normal movement and function, as well as for addressing clinical musculoskeletal or post-injury problems. Non-invasive measurement techniques are limited by the analysis technique and movement of peripheral soft tissues that can introduce significant measurement errors in reproducing the kinematics of the underlying bones when using external skin markers. Reflective markers, skeletally mounted to the right hind limb of three Merino-mix sheep were measured simultaneously with markers attached to the skin of each segment, during repetitions of gait trials. The movement of the skin markers relative to the underlying bone positions was then assessed using the Point Cluster Technique (PCT), raw averaging and the Optimal Common Shape Technique (OCST), a new approach presented in this manuscript.Errors in the position of the proximal joint centre, predicted from the corresponding skin markers, were shown to be phasic and strongly associated with the amount soft tissue coverage, averaging 8.5 mm for the femur, 2.8 for the tibia and 2.0 for the metatarsus. Although the results show a better prediction of bone kinematics associated with the Optimal Common Shape Technique, these errors were large for all three assessment techniques and much greater than the differences between the various techniques. Whilst individual markers moved up to 4 mm from the optimal marker set configuration, average peak errors of up to 16,s and 3 mm (hip, knee and tibio-metatarsal joints respectively) were observed, suggesting that a large amount of kinematic noise is produced from the synchronous shifting of marker sets, potentially as a result of underlying muscle firing and the inertial effects of heel impact. Current techniques are therefore limited in their ability to determine the kinematics of underlying bones based on skin markers, particularly in segments with more pronounced soft tissue coverage.

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