Assessment of haemophilic arthropathy through balance analysis: a promising tool

This is an Author's Accepted Manuscript of an article published in Xavier García-Massó, Yiyao Ye-Lin, Javier Garcia-Casado, Felipe Querol & Luis-Millan Gonzalez (2019) Assessment of haemophilic arthropathy through balance analysis: a promising tool, Computer Methods in Biomechanics and Biomedical Engineering, 22:4, 418-425, DOI: 10.1080/10255842.2018.1561877, available online at: http://doi.org/10.1080/10255842.2018.1561877.[EN] The purpose of this study was to develop a tool able to distinguish between subjects who have haemophilic arthropathy in lower limbs and those who do not by analyzing the centre of pressure displacement. The second objective was to assess the possible different responses of haemophiliacs and healthy subjects by creating a classifier that could distinguish between both groups. Fiftyfour haemophilic patients (28 with and 26 without arthropathy) and 23 healthy subjects took part voluntarily in the study. A force plate was used to measure postural stability. A total of 276 centre of pressure displacement parameters were calculated under different conditions: unipedal/bipedal balance with eyes open/closed. These parameters were used to design a Quadratic Discriminant Analysis classifier. The arthropathy versus non-arthropathy classifier had an overall accuracy of 97.5% when only 10 features were used in its design. Similarly, the haemophiliac versus nonhaemophiliac classifier had an overall accuracy of 97.2% when only 7 features were used. In conclusion, an objective haemophilic arthropathy in lower limbs evaluation system was developed by analyzing centre of pressure displacement signals. The haemophiliac vs. non-haemophiliac classifier designed was also able to corroborate the existing differences in postural control between haemophilic patients (with and without arthropathy) and healthy subjects.García-Massó, X.; Ye Lin, Y.; Garcia-Casado, J.; Querol -Fuentes, F.; Gonzalez, L. (2019). 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Identifying physical activity type in manual wheelchair users with spinal cord injury by means of accelerometers

Objectives: The main objective of this study was to develop and test classification algorithms based on machine learning using accelerometers to identify the activity type performed by manual wheelchair users with spinal cord injury (SCI). Setting: The study was conducted in the Physical Therapy department and the Physical Education and Sports department of the University of Valencia. Methods: A total of 20 volunteers were asked to perform 10 physical activities, lying down, body transfers, moving items, mopping, working on a computer, watching TV, arm-ergometer exercises, passive propulsion, slow propulsion and fast propulsion, while fitted with four accelerometers placed on both wrists, chest and waist. The activities were grouped into five categories: sedentary, locomotion, housework, body transfers and moderate physical activity. Different machine learning algorithms were used to develop individual and group activity classifiers from the acceleration data for different combinations of number and position of the accelerometers. Results: We found that although the accuracy of the classifiers for individual activities was moderate (55-72%), with higher values for a greater number of accelerometers, grouped activities were correctly classified in a high percentage of cases (83.2-93.6%). Conclusions: With only two accelerometers and the quadratic discriminant analysis algorithm we achieved a reasonably accurate group activity recognition system (490%). Such a system with the minimum of intervention would be a valuable tool for studying physical activity in individuals with SCI.X Garcia-Masso gratefully acknowledges the support of the University of Valencia under project UV-INV-PRECOMP13-115364.García-Massó, X.; Serra-Añó P.; Gonzalez, L.; Ye Lin, Y.; Prats-Boluda, G.; Garcia Casado, FJ. (2015). 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Neuronal pentraxin 1 negatively regulates excitatory synapse density and synaptic plasticity

In mature neurons, the number of synapses is determined by a neuronal activity-dependent dynamic equilibrium between positive and negative regulatory factors. We hypothesized that neuronal pentraxin (NP1), a proapoptotic protein induced by low neuronal activity, could be a negative regulator of synapse density because it is found in dystrophic neurites in Alzheimer's disease-affected brains. Here, we report that knockdown of NP1 increases the number of excitatory synapses and neuronal excitability in cultured rat cortical neurons and enhances excitatory drive and long-term potentiation in the hippocampus of behaving mice. Moreover, we found that NP1 regulates the surface expression of the Kv7.2 subunit of the Kv7 family of potassium channels that control neuronal excitability. Furthermore, pharmacological activation of Kv7 channels prevents, whereas inhibition mimics, the increase in synaptic proteins evoked by the knockdown of NP1. These results indicate that NP1 negatively regulates excitatory synapse number by modulating neuronal excitability and show that NP1 restricts excitatory synaptic plasticity

Ultra-processed foods consumption as a promoting factor of greenhouse gas emissions, water, energy, and land use: A longitudinal assessment

Background: Dietary patterns can produce an environmental impact. Changes in people's diet, such as the increased consumption of ultra-processed food (UPF) can not only influence human health but also environment sustainability. Objectives: Assessment of the impact of 2-year changes in UPF consumption on greenhouse gas emissions and water, energy and land use. Design: A 2-year longitudinal study after a dietary intervention including 5879 participants from a Southern European population between the ages of 55-75 years with metabolic syndrome. Methods: Food intake was assessed using a validated 143-item food frequency questionnaire, which allowed classifying foods according to the NOVA system. In addition, sociodemographic data, Mediterranean diet adherence, and physical activity were obtained from validated questionnaires. Greenhouse gas emissions, water, energy and land use were calculated by means of the Agribalyse® 3.0.1 database of environmental impact indicators for food items. Changes in UPF consumption during a 2-year period were analyzed. Statistical analyses were conducted using computed General Linear Models. Results: Participants with major reductions in their UPF consumption reduced their impact by -0.6 kg of CO2eq and -5.3 MJ of energy. Water use was the only factor that increased as the percentage of UPF was reduced. Conclusions: Low consumption of ultra-processed foods may contribute to environmental sustainability. The processing level of the consumed food should be considered not only for nutritional advice on health but also for environmental protection

The effect of 26 versus 29-inch wheel diameter in the transmission of vibrations in cross-country mountain biking

Vibrations experienced by cyclists can a ect their performance and health. We analysed the vibrations transmitted by mountain bike (26 or 29-inch wheels), in a 2,110 m circuit with a sample of 55 cyclists. The results indicate that the 29'-wheel increases speed (p < 0.001) and thus performance but it also increases exposure to vibrations as the root mean square (RMS) indicate (p = 0.001). The wheel diameter signi cantly a ected the accelerometer-related dependent variables (p < 0.01), speci cally seen in the RMS variable (p < 0.01). Regarding vibration transmission variables, it was found that the LW/FH, RW/FH, LA/RH, and RA/RH ratios were higher in the 29' bicycle than in 26' one. Average heart rate (p = 0.01) and maximum heart rate (p < 0.01) values were higher for the 29' bike with no signi cant di erences in the average power values recorded. In conclusion, bicycles with 29' wheels transmit higher levels of vibration to riders

Analyzing Spatial Behavior of Backcountry Skiers in Mountain Protected Areas Combining GPS Tracking and Graph Theory

Mountain protected areas (PAs) aim to preserve vulnerable environments and at the same time encourage numerous outdoor leisure activities. Understanding the way people use natural environments is crucial to balance the needs of visitors and site capacities. This study aims to develop an approach to evaluate the structure and use of designated skiing zones in PAs combining Global Positioning System (GPS) tracking and analytical methods based on graph theory. The study is based on empirical data (n = 609 GPS tracks of backcountry skiers) collected in Tatra National Park (TNP), Poland. The physical structure of the entire skiing zones system has been simplified into a graph structure (structural network; undirected graph). In a second step, the actual use of the area by skiers (functional network; directed graph) was analyzed using a graph-theoretic approach. Network coherence (connectivity indices: β, γ, α), movement directions at path segments, and relative importance of network nodes (node centrality measures: degree, betweenness, closeness, and proximity prestige) were calculated. The system of designated backcountry skiing zones was not evenly used by the visitors. Therefore, the calculated parameters differ significantly between the structural and the functional network. In particular, measures related to the actually used trails are of high importance from the management point of view. Information about the most important node locations can be used for planning sign-posts, on-site maps, interpretative boards, or other tourist infrastructure