Development of an innovative method for evaluating a network of collective defensive interactions in football

Social network analysis (SNA) has been increasingly applied to performance analytics in team sports, seeking to better understand the dynamic properties of competitive interactions. Despite considerable potential to analyze individual (micro) and team (macro) behavioral patterns of play, there are important limitations that can undermine the potential applicability of SNA. One important limitation in existing research is the lack of network analyses of defensive interactions, curtailing understanding of the functionality and adaptability of teams during competitive performance. This study developed an innovative network method for assessing interactions between players in defensive phases of play in football. The networking method was evaluated using a small-sided and conditioned game (SSCG; GK+7v7+GK) of 20 min duration (two halves of 10 min each, interspersed by 5 min intervals of active recovery). The method traced interactions between groups of three players (effective defensive triangulations) as network nodes, weighted according to the number of passes performed by the attacking players. Results showed how this social network analysis method may provide researchers, coaches and performance analysts with relevant information regarding the functional properties of teams in the defensive phase of the game. For instance, coaches and performance analysts can evaluate the geometry of a team’s defense, with players engaged in effective triangular-shaped positioning, that allowed them to provide defensive cover and balance, to protect the goal and recover ball possession

Reuma.pt/vasculitis - the Portuguese vasculitis registry

BACKGROUND: The vasculitides are a group of rare diseases with different manifestations and outcomes. New therapeutic options have led to the need for long-term registries. The Rheumatic Diseases Portuguese Register, Reuma.pt, is a web-based electronic clinical record, created in 2008, which currently includes specific modules for 12 diseases and > 20,000 patients registered from 79 rheumatology centres. On October 2014, a dedicated module for vasculitis was created as part of the European Vasculitis Society collaborative network, enabling prospective collection and central storage of encrypted data from patients with this condition. All Portuguese rheumatology centres were invited to participate. Data regarding demographics, diagnosis, classification criteria, assessment tools, and treatment were collected. We aim to describe the structure of Reuma.pt/vasculitis and characterize the patients registered since its development. RESULTS: A total of 687 patients, with 1945 visits, from 13 centres were registered; mean age was 53.4 ± 19.3 years at last visit and 68.7% were females. The most common diagnoses were Behçet's disease (BD) (42.5%) and giant cell arteritis (GCA) (17.8%). Patients with BD met the International Study Group criteria and the International Criteria for BD in 85.3 and 97.2% of cases, respectively. Within the most common small- and medium-vessel vasculitides registered, median [interquartile range] Birmingham Vasculitis Activity Score (BVAS) at first visit was highest in patients with ANCA-associated vasculitis (AAV) (17.0 [12.0]); there were no differences in the proportion of patients with AAV or polyarteritis nodosa who relapsed (BVAS≥1) or had a major relapse (≥1 major BVAS item) during prospective assessment (p = 1.00, p = 0.479). Biologic treatment was prescribed in 0.8% of patients with GCA, 26.7% of patients with AAV, and 7.6% of patients with BD. There were 34 (4.9%) deaths reported. CONCLUSIONS: Reuma.pt/vasculitis is a bespoke web-based registry adapted for routine care of patients with this form of rare and complex diseases, allowing an efficient data-repository at a national level with the potential to link with other international databases. It facilitates research, trials recruitment, service planning and benchmarking.publishersversionpublishe

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Portable Digital Monitoring System for Sarcopenia Screening and Diagnosis

Sarcopenia is a well-known highly prevalent muscle disease that severely impairs overall physical performance in elders, inducing a massive health-related economic burden. The widespread screening, diagnosis and treatment of sarcopenia are pivotal to restrain the disease progression and constrain its societal impact. Simple-to-use, portable, and reliable methods to evaluate sarcopenia are scarce, and sarcopenia-related assessments are typically done in several time-consuming stages. This study presents a portable digital system that enables a simple and intuitive method to evaluate sarcopenia—based on the European Working Group on Sarcopenia in Older People 2 (EWGSOP2) algorithm—including the four Find-Assess-Confirm-Severity (FACS) steps. The system comprises a mobile application (app); two wireless devices: a dynamometer (Gripwise) and a skinfold caliper (Lipowise); and a back-end website. To find cases, the SARC-F questionnaire is applied. To assess sarcopenia, the handgrip strength and the sit-to-stand tests are performed with the Gripwise and an application-embedded stopwatch, respectively. To confirm cases, anthropometric measures are performed, and muscle quantity is estimated with Lipowise. Finally, to assess severity, the app stopwatch grants the gait speed test application, evaluating physical performance. This step-by-step sarcopenia assessment results in a final grading according to the cut-off points of the EWGSOP2 criteria. All data is automatically encrypted and exported into a GDPR-compliant cloud platform, in which healthcare professionals can access and monitor their patients through the internet

Preventive and Therapeutic Potential of Physical Exercise in Neurodegenerative Diseases

Significance: The prevalence and incidence of age-related neurodegenerative diseases (NDDs) tend to increase along with the enhanced average of the world life expectancy. NDDs are a major cause of morbidity and disability, affecting the health care, social and economic systems with a significant impact. Critical Issues and Recent Advances: Despite the worldwide burden of NDDs and the ongoing research efforts to increase the underlying molecular mechanisms involved in NDD pathophysiologies, pharmacological therapies have been presenting merely narrow benefits. On the contrary, absent of detrimental side effects but growing merits, regular physical exercise (PE) has been considered a prone pleiotropic nonpharmacological alternative able to modulate brain structure and function, thereby stimulating a healthier and "fitness" neurological phenotype. Future Directions: This review summarizes the state of the art of some peripheral and central-related mechanisms that underlie the impact of PE on brain plasticity as well as its relevance for the prevention and/or treatment of NDDs. Nevertheless, further studies are needed to better clarify the molecular signaling pathways associated with muscle contractions-related myokines release and its plausible positive effects in the brain. In addition, particular focus of research should address the role of PE in the modulation of mitochondrial metabolism and oxidative stress in the context of NDDs

Intracyclic velocity variation and arm coordination assessment in swimmers with down syndrome

This study examined the differences in intracycle velocity variation and arm coordination in front crawl in swimmers with Down syndrome in three breathing conditions. International swimmers with Down syndrome (N = 16) performed 3 × 20 m front crawl at 50 m race speed: without breathing, breathing to the preferred side, and breathing to the nonpreferred side. A two dimensional video movement analysis was performed using the APASystem. Breathing conditions were compared using Repeated Measures ANOVA. Swimming velocity was higher without breathing and intracyclic velocity variation was higher while breathing. Swimmers tended to a catch up arm coordination mode for both breathing conditions and a superposition mode when not breathing. These data reflect arm coordination compromising swimming performance, particularly when comparing with non disabled swimmers in literature. The physical and perhaps cognitive impairment associated with Down syndrome may result in a disadvantage in both propulsion and drag, more evident when breathing.status: publishe