Evaluation of Body Composition in CrossFit® Athletes and the Relation with Their Results in Official Training

CrossFit® is a high-intensity sport that combines weightlifting, gymnastic skills, and cardiovascular exercises. To find the anthropometric references that define the optimal body composition, it is essential to first find an optimal body composition for one’s physical preparation. The objective of this study is to describe the anthropometric characteristics of 27 Spanish CrossFit® athletes, 19 males aged 39 years old (24–44) and 8 females aged 28 years old (23–40), and how these characteristics influenced their performance. The athletes performed the Fran, Cindy, and Kelly workouts, establishing minimum marks, and the CrossFit Total workout to assess maximum strength. Significant differences were not found in time and repetitions between sexes in skill training, although there was a positive correlation r = 0.876 (p < 0.001) between muscle mass and the Total CrossFit result. We can conclude that the CrossFit® athlete has a low amount of fat mass and a small relative size, which is an advantage when training with bodyweight exercises, and a high muscle mass that provide benefits when strength training. In addition, despite executing movements from a multitude of disciplines, the physical demands for lifting heavy loads resulted in the anthropometric values of athletes being more similar to elite weightlifting athletes than in other sports

Funciones de estimación de la biomasa aérea de varias especies del matorral mediterráneo del centro de la península Ibérica

Se calculan las funciones adecuadas para evaluar la biomasa aérea de 17 especies típicas del matorral mediterráneo del centro de la península Ibérica. Se usan y discuten diferentes métodos existentes en la literatura. La relación entre el peso y un parámetro estructural sencillo para estas especies -cobertura, altura, biovolumen aparente- suele ser alométrica -expresable como una potencia de alguno de estos parámetros-. La función de alometria calculada directamente, sin transformaciones previas de los datos originales, se ha revelado como la de mayor utilidad en el caso considerado.A set of functions for the estimation of aerial biomass have been calculated on data from 17 Mediterranean shrub species. Together with the methods here used, those applied in the relevant literature are discussed. Simple structural parameters like cover, height and biovolume proved to scale allometrically with weight. Models based on raw untransformated data rendered the best results

Using ensembles for accurate modelling of manufacturing processes in an IoT data-acquisition solution

The development of complex real-time platforms for the Internet of Things (IoT) opens up a promising future for the diagnosis and the optimization of machining processes. Many issues have still to be solved before IoT platforms can be profitable for small workshops with very flexible workloads and workflows. The main obstacles refer to sensor implementation, IoT architecture, and data processing, and analysis. In this research, the use of different machine-learning techniques is proposed, for the extraction of different information from an IoT platform connected to a machining center, working under real industrial conditions in a workshop. The aim is to evaluate which algorithmic technique might be the best to build accurate prediction models for one of the main demands of workshops: the optimization of machining processes. This evaluation, completed under real industrial conditions, includes very limited information on the machining workload of the machining center and unbalanced datasets. The strategy is validated for the classification of the state of a machining center, its working mode, and the prediction of the thermal evolution of the main machine-tool motors: the axis motors and the milling head motor. The results show the superiority of the ensembles for both classification problems under analysis and all four regression problems. In particular, Rotation Forest-based ensembles turned out to have the best performance in the experiments for all the metrics under study. The models are accurate enough to provide useful conclusions applicable to current industrial practice, such as improvements in machine programming to avoid cutting conditions that might greatly reduce tool lifetime and damage machine components.Projects TIN2015-67534-P (MINECO/FEDER, UE) of the Ministerio de Economía Competitividad of the Spanish Government and projects CCTT1/17/BU/0003 and BU085P17 (JCyL/FEDER, UE) of the Junta de Castilla y León, all of them co-financed through European-Union FEDER funds

Mapping the scientific structure of organization and management of enterprises using complex networks

Understanding the scientific and social structure of a discipline is a fundamental aspect for scientific evaluation processes, identifying trends and niches, and balancing the trade-off between exploitation and exploration in research. In the present contribution, the production of doctoral theses is used as a proxy to analyze the scientific structure of the knowledge area of business organization in Spain. To that end, a complex networks approach is selected, and two different networks are built: (i) the social network of co-participation in thesis examining committees and thesis supervision, and (ii) a bipartite network of theses and thesis descriptors. The former has a modular structure that is partially explained by thematic specialization in different subdisciplines. The latter serves to assess the interdisciplinary structure of the discipline, as it enables the characterization of affinity levels between fields, research poles and thematic clusters. Our results have implications for the scientific evaluation and formal definition of related fields.Spanish Ministry of Science, Innovation and Universities (RED2018-102518-T), the Spanish State Research Agency (PID2020-118906GB-I00 and PID2020-119894GB-I00 via AEI/10.13039/501100011033), the Junta de Castilla y León – Consejería de Educación (BU055P20), Fundación La Caixa (2020/00062/001) and from NVIDIA Corporation and its donation of the TITAN Xp GPUs that facilitated this research. This work was partially supported by the European Social Fund, as the authors José Miguel Ramírez-Sanz, José Luis Garrido-Labrador and Alicia Olivares-Gil are the recipient of a predoctoral grant from the Department of Education of Junta de Castilla y León (VA) (ORDEN EDU/875/2021). In addition, this work was also partially supported by the Generalitat Valenciana via its Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, as Adrián Arnaiz is recipicient of a predoctoral grant

Antioxidant and Antibacterial Properties of Carbosilane Dendrimers Functionalized with Polyphenolic Moieties

A new family of polyphenolic carbosilane dendrimers functionalized with ferulic, caffeic, and gallic acids has been obtained through a straightforward amidation reaction. Their antioxidant activity has been studied by different techniques such as DPPH (2,2 '-diphenyl-1-picrylhydrazyl) radical scavenging assay, FRAP assay (ferric reducing antioxidant power), and cyclic voltammetry. The antioxidant analysis showed that polyphenolic dendrimers exhibited higher activities than free polyphenols in all cases. The first-generation dendrimer decorated with gallic acid stood out as the best antioxidant compound, displaying a correlation between the number of hydroxyl groups in the polyphenol structure and the antioxidant activity of the compounds. Moreover, the antibacterial capacity of these new systems has been screened against Gram-positive (+) and Gram-negative (-) bacteria, and we observed that polyphenolic dendrimers functionalized with caffeic and gallic acids were capable of decreasing bacterial growth. In contrast, ferulic carbosilane dendrimers and free polyphenols showed no effect, establishing a correlation between antioxidant activity and antibacterial capacity. Finally, a viability assay in human skin fibroblasts cells (HFF-1) allowed for corroborating the nontoxicity of the polyphenolic dendrimers at their active antibacterial concentration.Ministerio de Economía y CompetitividadJunta de Comunidades de Castilla-La ManchaComunidad de Madri

Adopting a multidisciplinary telemedicine intervention for fall prevention in Parkinson’s disease. Protocol for a longitudinal, randomized clinical trial

Approximately 40–70% of people with Parkinson’s disease (PD) fall each year, causing decreased activity levels and quality of life. Current fall-prevention strategies include the use of pharmacological and non-pharmacological therapies. To increase the accessibility of this vulnerable population, we developed a multidisciplinary telemedicine program using an Information and Communication Technology (ICT) platform. We hypothesized that the risk for falling in PD would decrease among participants receiving a multidisciplinary telemedicine intervention program added to standard office-based neurological care.This work was supported by the project PI19/00670 of the Ministerio de Ciencia, Innovacio´n y Universidades, Instituto de Salud Carlos II, Spain. The authors gratefully acknowledge the support of NVIDIA Corporation and its donation of the TITAN Xp GPUs used in this research

A Low-Cost System Using a Big-Data Deep-Learning Framework for Assessing Physical Telerehabilitation: A Proof-of-Concept

The consolidation of telerehabilitation for the treatment of many diseases over the last decades is a consequence of its cost-effective results and its ability to offer access to rehabilitation in remote areas. Telerehabilitation operates over a distance, so vulnerable patients are never exposed to unnecessary risks. Despite its low cost, the need for a professional to assess therapeutic exercises and proper corporal movements online should also be mentioned. The focus of this paper is on a telerehabilitation system for patients suffering from Parkinson’s disease in remote villages and other less accessible locations. A full-stack is presented using big data frameworks that facilitate communication between the patient and the occupational therapist, the recording of each session, and real-time skeleton identification using artificial intelligence techniques. Big data technologies are used to process the numerous videos that are generated during the course of treating simultaneous patients. Moreover, the skeleton of each patient can be estimated using deep neural networks for automated evaluation of corporal exercises, which is of immense help to the therapists in charge of the treatment programs.This work was supported by project PI19/00670 of the Ministerio de Ciencia, Innovación y Universidades, Instituto de Salud Carlos III, Spain. The authors gratefully acknowledge the support of the NVIDIA Corporation and its donation of the TITAN Xp GPU used in this research. In addition, this work was partially supported by the European Social Fund, as the authors José Miguel Ramírez-Sanz, José Luis Garrido-Labrador, and Alicia Olivares-Gil are the recipients of a pre-doctoral grant (EDU/875/2021) from the Conserjería de Educación de la Junta de Castilla y León

Assistive Devices for Personal Mobility in Parkinson's Disease: A Systematic Review of the Literature

Artículo de revisiónGait abnormalities are a hallmark of Parkinson’s disease and contribute to falling risk. As disease symptoms progress, assistive devices are often prescribed. However, there are no guidelines for choosing appropriate ambulatory devices for gait impairment.This work was supported by the project PI19/00670 of the Ministerio de Ciencia, Innovación y Universidades, Instituto de Salud Carlos III, Spain. The authors declare that there are no additional disclosures to report relevant to this work

Follow-Up Study Confirms the Presence of Gastric Cancer DNA Methylation Hallmarks in High-Risk Precursor Lesions

Intestinal metaplasia confers an increased risk of progression to gastric cancer. However, some intestinal metaplasia patients do not develop cancer. The development of robust molecular biomarkers to stratify patients with advanced gastric precursor lesions at risk of cancer progression will contribute to guiding programs for prevention. Starting from a genome-wide methylation study, we have simplified the detection method regarding candidate-methylation tests to improve their applicability in the clinical environment. We identified CpG methylation at the ZNF793 and RPRM promoters as a common event in intestinal metaplasia and intestinal forms of gastric cancer. Furthermore, we also showed that Helicobacter pylori infection influences DNA methylation in early precursor lesions but not in intestinal metaplasia, suggesting that therapeutic strategies to prevent epigenome reprogramming toward a cancer signature need to be adopted early in the precursor cascade. To adopt prevention strategies in gastric cancer, it is imperative to develop robust biomarkers with acceptable costs and feasibility in clinical practice to stratified populations according to risk scores. With this aim, we applied an unbiased genome-wide CpG methylation approach to a discovery cohort composed of gastric cancer (n = 24), and non-malignant precursor lesions (n = 64). Then, candidate-methylation approaches were performed in a validation cohort of precursor lesions obtained from an observational longitudinal study (n = 264), with a 12-year follow-up to identify repression or progression cases. H. pylori stratification and histology were considered to determine their influence on the methylation dynamics. As a result, we ascertained that intestinal metaplasia partially recapitulates patterns of aberrant methylation of intestinal type of gastric cancer, independently of the H. pylori status. Two epigenetically regulated genes in cancer, RPRM and ZNF793, consistently showed increased methylation in intestinal metaplasia with respect to earlier precursor lesions. In summary, our result supports the need to investigate the practical utilities of the quantification of DNA methylation in candidate genes as a marker for disease progression. In addition, the H. pylori-dependent methylation in intestinal metaplasia suggests that pharmacological treatments aimed at H. pylori eradication in the late stages of precursor lesions do not prevent epigenome reprogramming toward a cancer signature

Overproduction of a Trichoderma harzianum chitinase and analysis of its biotechnological potential to produce chitooligosaccharides

Trabajo presentado en la 7ª ed. del congreso internacional "FEMS" organizado por la Sociedad Española de Microbiología y la Federación Europea de Sociedades Microbiológicas en el Centro de Convenciones Feria Valencia (Valencia, España) durante los días 9 al 13 de julio de 2017.BACKGROUNDS: Chitooligosaccharides (COS) are β-(1,4)-linked oligomers of N-acetyl-glucosamine (GlcNAc) and glucosamine (GlcN) formed by chemical or enzymatic hydrolysis of chitosan or chitin. The growing biotechnological interest of COS in fields such as food or health increases the demand of the producing enzymes as well as their characterization and functional improvement. | OBJETIVES: Express a chitinase of 42 kDa from Trichoderma harzianum in a heterologous system, obtain protein levels compatible with its crystallization for the future protein structural resolution and evaluate the ability of the recombinant protein to produce COS. | METHODS: The chitinase gene cDNA from T. harzianum was expressed in Pichia pastoris using a restriction-free cloning strategy, production of heterologous protein was analysed and escalated up to a 5 L fermenter level. Recombinant protein was purified and some crystals were obtained which allows undertake the protein structural resolution. Synthesis of oligosaccharides from different substrates were evaluated and optimized using the recombinant enzyme. HPAEC-PAD on a Dionex ICS3000 system and Mass Spectrometry were used in the reaction studies and product characterization. | CONCLUSIONS: A chitinase of 42 kDa from T. harzianum was overexpressed in P. pastoris, the recombinant protein was purified, characterized and crystallized for the protein structural resolution. Production of COS mediated by this enzyme was evaluated and some of the molecules formed were characterized.N