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Our research project computed the direct health costs of patients with amyotrophic lateral sclerosis (ALS) in a Spanish multidisciplinary unit and explored the main factors associated. Besides analyzing a context with universal health care provision, we used an administrative health care dataset from the most crucial center unit treating ALS in Catalonia (80% of total patients). Our results show that the direct health cost of caring for an ALS patient in our unit was 5,158€per patient/year. This cost was not influenced by the onset of the disease, sex or age, but it increased if the patient lived near our center since this facilitates the frequency of follow-up visits. Finally, the higher the educational level, the lower the direct health costs. [ABSTRACT FROM AUTHOR]

The aim of this study was to analyse differences in velocity, distance travelled and manoeuvres performed by Olympic sailors of the RS:X class using a GPS device. Fifty-three Olympic sailors of the RS:X class (28 males and 25 females) who competed in a World Championship were selected. The sample was divided into tertiles (T1, T2 and T3) according to their classification in the competition. Using a GPS device during the competition, mean velocity (VM), velocity made good (VMG), manoeuvres and distances in three different courses (upwind, reaching and downwind) were assessed during a regatta. Significant differences were found based on performance level in upwind (p < 0.001; η p 2 = 0.288), sailors of T1 covering a shorter distance compared to those of T2 (p < 0.009) and T3 (p < 0.001). Regarding VMG, an effect was observed for performance level in upwind (p < 0.001; η p 2 = 0.718), reaching (p < 0.001; η p 2 = 0.469) and downwind (p < 0.001; η p 2 = 0.575). Females covered a shorter distance compared to the males in upwind (p < 0.001; η p 2 = 0.639) and downwind (p < 0.001; η p 2 = 0.903). Distance and VMG are significant variables for establishing differences in performance level among Olympic sailors of the RS:X class when the wind speed is in a range of 8–21 knots. [ABSTRACT FROM AUTHOR]

Amyotrophic lateral sclerosis (ALS) is a heterogeneous disease, both in its onset phenotype and in its rate of progression. The aim of this study was to establish whether the dysfunction of the blood–brain barrier (BBB) and blood–spinal cord barrier (BSCB) measured through cerebrospinal fluid (CSF) proteins and the albumin-quotient (QAlb) are related to the speed of disease progression. An amount of 246 patients diagnosed with ALS were included. CSF and serum samples were determined biochemically for different parameters. Survival analysis based on phenotype shows higher probability of death for bulbar phenotype compared to spinal phenotype (p-value: 0.0006). For the effect of CSF proteins, data shows an increased risk of death for spinal ALS patients as the value of CSF proteins increases. The same model replicated for CSF albumin yielded similar results. Statistical models determined that the lowest cut-off value for CSF proteins able to differentiate patients with a good prognosis and worse prognosis corresponds to CSF proteins ≥ 0.5 g/L (p-value: 0.0189). For the CSF albumin, the QAlb ≥0.65 is associated with elevated probability of death (p-value: 0.0073). High levels of QAlb are a bad prognostic indicator for the spinal phenotype, in addition to high CSF proteins levels that also act as a marker of poor prognosis. [ABSTRACT FROM AUTHOR]

Background: Fatty acids play prominent roles in brain function as they participate in structural, metabolic and signaling processes. The homeostasis of fatty acids and related pathways is known to be impaired in cognitive decline and dementia, but the relationship between these metabolic disturbances and common risk factors, namely the ɛ4 allele of the apolipoprotein E (ApoE-ɛ4) gene and sex, remains elusive. Methods: In order to investigate early alterations associated with cognitive decline in the fatty acid-related serum metabolome, we here applied targeted metabolomics analysis on a nested case-control study (N=368), part of a prospective population cohort on dementia. Results: When considering the entire study population, circulating levels of free fatty acids, acyl-carnitines and pantothenic acid were found to be increased among those participants who had greater odds of cognitive decline over a 12-year follow-up. Interestingly, stratified analyses indicated that these metabolomic alterations were specific for ApoE-ɛ4 non-carriers and women. Conclusions: Altogether, our results highlight that the regulation of fatty acids and related metabolic pathways during ageing and cognitive decline depends on complex inter-relationships between the ApoE-ε4 genotype and sex. A better understanding of the ApoE-ɛ4 and sex dependent modulation of metabolism is essential to elucidate the individual variability in the onset of cognitive decline, which would help develop personalized therapeutic approaches. [ABSTRACT FROM AUTHOR]

Metabolomics and proteomics, like other omics domains, usually face a data mining challenge in providing an understandable output to advance in biomarker discovery and precision medicine. Often, statistical analysis is one of the most difficult challenges and it is critical in the subsequent biological interpretation of the results. Because of this, combined with the computational programming skills needed for this type of analysis, several bioinformatic tools aimed at simplifying metabolomics and proteomics data analysis have emerged. However, sometimes the analysis is still limited to a few hidebound statistical methods and to data sets with limited flexibility. POMAShiny is a web-based tool that provides a structured, flexible and user-friendly workflow for the visualization, exploration and statistical analysis of metabolomics and proteomics data. This tool integrates several statistical methods, some of them widely used in other types of omics, and it is based on the POMA R/Bioconductor package, which increases the reproducibility and flexibility of analyses outside the web environment. POMAShiny and POMA are both freely available at https://github.com/nutrimetabolomics/POMAShiny and https://github.com/nutrimetabolomics/POMA, respectively. Author summary: Metabolomics and proteomics are two growing areas in human health and personalized medicine fields. Often, one of the main applications of metabolomics and proteomics is the discovery of novel biomarkers and new therapeutic targets in these areas. However, these data are extremely complex and hard to analyse, since they have a large number of features, several missing values, and often important clinical variables to consider in the analyses. Therefore, powerful and versatile tools are needed to provide efficient methods for data visualization and exploration, as well as a wide range of robust statistical methods to meet all data and users requirements. Although powerful tools do exist for the analysis of these data, many of them are still limiting the analyses in terms of visualization and statistical analysis. To address this limitation and complement the existing tools, we have developed a web-based application, named POMAShiny, for the data analysis of metabolomics and proteomics. This novel and versatile tool offers a wholly interactive and easy-to-use environment for the analysis of these data, including numerous methods for preprocessing, data visualization and statistical analysis. The POMAShiny open-source tool is extremely flexible and portable, as it can be installed locally and freely accessed online at https://webapps.nutrimetabolomics.com/POMAShiny. [ABSTRACT FROM AUTHOR]

Background: Autoimmune diseases are heterogeneous pathologies with difficult diagnosis and few therapeutic options. In the last decade, several omics studies have provided significant insights into the molecular mechanisms of these diseases. Nevertheless, data from different cohorts and pathologies are stored independently in public repositories and a unified resource is imperative to assist researchers in this field. Results: Here, we present Autoimmune Diseases Explorer (https://adex.genyo.es), a database that integrates 82 curated transcriptomics and methylation studies covering 5609 samples for some of the most common autoimmune diseases. The database provides, in an easy-to-use environment, advanced data analysis and statistical methods for exploring omics datasets, including meta-analysis, differential expression or pathway analysis. Conclusions: This is the first omics database focused on autoimmune diseases. This resource incorporates homogeneously processed data to facilitate integrative analyses among studies. [ABSTRACT FROM AUTHOR]

Hippocampal neurogenesis (HN) occurs throughout the life course and is important for memory and mood. Declining with age, HN plays a pivotal role in cognitive decline (CD), dementia, and late-life depression, such that altered HN could represent a neurobiological susceptibility to these conditions. Pertinently, dietary patterns (e.g. Mediterranean diet) and/or individual nutrients (e.g. vitamin D, omega 3) can modify HN, but also modify risk for CD, dementia, and depression. Therefore, the interaction between diet/nutrition and HN may alter risk trajectories for these ageing-related brain conditions. Using a subsample (n  = 371) of the Three-City cohort—where older adults provided information on diet and blood biobanking at baseline and were assessed for CD, dementia, and depressive symptomatology across 12 years—we tested for interactions between food consumption, nutrient intake, and nutritional biomarker concentrations and neurogenesis-centred susceptibility status (defined by baseline readouts of hippocampal progenitor cell integrity, cell death, and differentiation) on CD, Alzheimer's disease (AD), vascular and other dementias (VoD), and depressive symptomatology, using multivariable-adjusted logistic regression models. Increased plasma lycopene concentrations (OR [95% CI]  =  1.07 [1.01, 1.14]), higher red meat (OR [95% CI]  =  1.10 [1.03, 1.19]), and lower poultry consumption (OR [95% CI]  =  0.93 [0.87, 0.99]) were associated with an increased risk for AD in individuals with a neurogenesis-centred susceptibility. Increased vitamin D consumption (OR [95% CI]  =  1.05 [1.01, 1.11]) and plasma γ-tocopherol concentrations (OR [95% CI]  =  1.08 [1.01, 1.18]) were associated with increased risk for VoD and depressive symptomatology, respectively, but only in susceptible individuals. This research highlights an important role for diet/nutrition in modifying dementia and depression risk in individuals with a neurogenesis-centred susceptibility. [ABSTRACT FROM AUTHOR]

Metabolomics has proven great potential to unravel the molecular basis of diseases. However, most attempts aimed at identifying reliable metabolomics-based biomarkers for diagnosis, prediction, and prognosis of diseases have repeatedly failed because of inconsistent results and unsatisfactory replication in independent cohorts. This review article explores the possible causes behind this reproducibility crisis, with special focus on the role that inter-individual variability factors play in modulating the susceptibility to disease development. Furthermore, we provide future perspectives on the applicability of metabolomics in biomedical research and its translatability into clinical practice. [ABSTRACT FROM AUTHOR]

Summary: Trace elements and heavy metals play pivotal roles in health status by regulating a myriad of vital biological functions. Abnormal metal homeostasis has been linked to a constellation of pathogenic complications, including oxidative stress, inflammatory processes, dyslipidemia, and impaired insulin‐mediated metabolism of carbohydrates, thereby increasing the odds of developing childhood obesity and related comorbidities. Herein, we provide a comprehensive revision of recent literature on the association between childhood obesity, trace elements, and heavy metals. Further, we emphasize on the crucial importance of addressing the influence that interindividual variability factors (e.g., sex, age, genetic determinants, concomitance of comorbidities, and environmental factors) may have in modulating the susceptibility to disease development. Altogether, this review article represents a concise guide to better understand the involvement of metals in childhood obesity pathogenesis and discusses future needs with the aim of establishing robust biomarkers in the context of precision medicine. [ABSTRACT FROM AUTHOR]

Nutrition research can be conducted by using two complementary approaches: (i) traditional self-reporting methods or (ii) via metabolomics techniques to analyze food intake biomarkers in biofluids. However, the complexity and heterogeneity of these two very different types of data often hinder their analysis and integration. To manage this challenge, we have developed a novel ontology that describes food and their associated metabolite entities in a hierarchical way. This ontology uses a formal naming system, category definitions, properties and relations between both types of data. The ontology presented is called FOBI (Food-Biomarker Ontology) and it is composed of two interconnected sub-ontologies. One is a 'Food Ontology' consisting of raw foods and 'multi-component foods' while the second is a 'Biomarker Ontology' containing food intake biomarkers classified by their chemical classes. These two sub-ontologies are conceptually independent but interconnected by different properties. This allows data and information regarding foods and food biomarkers to be visualized in a bidirectional way, going from metabolomics to nutritional data or vice versa. Potential applications of this ontology include the annotation of foods and biomarkers using a well-defined and consistent nomenclature, the standardized reporting of metabolomics workflows (e.g. metabolite identification, experimental design) or the application of different enrichment analysis approaches to analyze nutrimetabolomic data. Availability : FOBI is freely available in both OWL (Web Ontology Language) and OBO (Open Biomedical Ontologies) formats at the project's Github repository (https://github.com/pcastellanoescuder/FoodBiomarkerOntology) and FOBI visualization tool is available in https://polcastellano.shinyapps.io/FOBI_Visualization_Tool/. [ABSTRACT FROM AUTHOR]

There is a great need for having accurate analytical methods able to guarantee the authenticity and traceability of foods, especially for those of high quality and economic value such as extra-virgin olive oil. In the present work, we assessed the potential of combining traditional analytical techniques, based on the characterization of the unsaponifiable fraction, together with novel nuclear magnetic resonance fingerprinting with the aim to investigate the effect of variety and geographical origin on olive oils collected from different locations across the province of Huelva (Spain). Various complementary supervised pattern recognition procedures and machine learning algorithms were then applied to build classification and predictive models. Extra-virgin olive oils were characterized by high concentrations of apparent β-sitosterol (93% of total sterol content), α-tocopherol (representing almost 91% of the total tocopherol fraction), squalene (90% of the total hydrocarbon content), heptacosanol and eicosane (the most abundant aliphatic alcohol and n-alkane, respectively). Furthermore, olive oil classes could be clearly differentiated on the basis of a characteristic chemical pattern, comprising tocopherols, squalene, sterols (campesterol, stigmasterol, β-sitosterol), aliphatic alcohols (heptacosanol, octacosanol) and some nuclear magnetic resonances related to fatty acid chains. Image 1 • 1H NMR and UF profiling were applied for EVOO traceability. • UF discriminant variables were tocopherols, squalene, sterols and alcohols. • NMR signals related to fatty acids classify EVOOs according to origin and variety. • Predictive models were built by using different machine learning tools. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10–25 years before the onset of clinical symptoms. As multiple functionally interconnected molecular/cellular pathways appear disrupted in AD, the exploitation of high-throughput unbiased omics sciences is critical to elucidating the precise pathogenesis of AD. Among different omics, metabolomics is a fast-growing discipline allowing for the simultaneous detection and quantification of hundreds/thousands of perturbed metabolites in tissues or biofluids, reproducing the fluctuations of multiple networks affected by a disease. Here, we seek to critically depict the main metabolomics methodologies with the aim of identifying new potential AD biomarkers and further elucidating AD pathophysiological mechanisms. From a systems biology perspective, as metabolic alterations can occur before the development of clinical signs, metabolomics – coupled with existing accessible biomarkers used for AD screening and diagnosis – can support early disease diagnosis and help develop individualized treatment plans. Presently, the majority of metabolomic analyses emphasized that lipid metabolism is the most consistently altered pathway in AD pathogenesis. The possibility that metabolomics may reveal crucial steps in AD pathogenesis is undermined by the difficulty in discriminating between the causal or epiphenomenal or compensatory nature of metabolic findings. • Exploring metabolomic biomarker profiles shows the complexity of AD pathophysiology. • Metabolomics helps disclose candidate blood-based biomarker signatures. • Lipid metabolism is the most consistently dysregulated pathway in AD pathogenesis. • Metabolomics aids to optimize AD diagnosis, prognosis, and targeted therapies. • Metabolomics/lipidomics data can provide a holistic depiction of AD pathophysiology. [ABSTRACT FROM AUTHOR]

This work explores the potential of multi-element fingerprinting in combination with advanced data mining strategies to assess the geographical origin of extra virgin olive oil samples. For this purpose, the concentrations of 55 elements were determined in 125 oil samples from multiple Spanish geographic areas. Several unsupervised and supervised multivariate statistical techniques were used to build classification models and investigate the relationship between mineral composition of olive oils and their provenance. Results showed that Spanish extra virgin olive oils exhibit characteristic element profiles, which can be differentiated on the basis of their origin in accordance with three geographical areas: Atlantic coast (Huelva province), Mediterranean coast and inland regions. Furthermore, statistical modelling yielded high sensitivity and specificity, principally when random forest and support vector machines were employed, thus demonstrating the utility of these techniques in food traceability and authenticity research. [ABSTRACT FROM AUTHOR]

In resistance training, load intensity is usually calculated as the percentage of a maximum repetition (1RM) or maximum number of possible repetitions ( % of 1RM). Some studies have proposed a lactate threshold (LT) intensity as an optimal approach for concurrent training of cardiorespiratory endurance and muscle strength, as well as an alternative in resistance training. The objective of the present study was to analyze the results obtained in research evaluating the use of LT in resistance training. A keyword and search tree strategy identified 14 relevant articles in the Dialnet, Elsevier, Medline, Pubmed, Scopus and Web of Science databases. Based on the studies analyzed, the conclusion was that the LT in resistance exercises can be determined either by mathematical methods or by visual inspection of graphical plots. Another possibility is to measure the intensity at which LT might coincide with the first ventilatory threshold (VT1). Since performing an exercise session at one's LT intensity has been shown to accelerate the cardiorespiratory response and induce neuromuscular fatigue, this intensity could be used to set the training load in a resistance training program. [ABSTRACT FROM AUTHOR]

The present study aimed to compare two fitness-training methodologies, instability circuit resistance training (ICRT) versus traditional circuit resistance training (TCRT), applying an experimental model of exercise prescription controlling and modulating exercise load using the Borg rating of perceived exertion. Forty-four healthy young adults age (21.6 ± 2.3 years) were randomly assigned to three groups: TCRT (n = 14), ICRT (n = 14) and a control group (n = 16). Strength and cardiorespiratory tests were chosen to evaluate cardiorespiratory and muscular fitness before and after the training program. In cardiorespiratory data, a significant difference was observed for the time effect in VO2max, peak heart rate, peak velocity, and heart rate at anaerobic threshold intensity (p < 0.05) in the experimental groups. In strength variables, a significant Group x Time interaction effect was detected in 1RM, in mean propulsive power, and in peak power (p ≤ 0.01) in the back squat exercise. In the bench press exercise, a significant time effect was detected in 1RM, in mean propulsive power, and in peak power, and a Group x Time interaction in peak power (all p < 0.05). We can conclude that applying an experimental model of exercise prescription using RPE improved cardiorespiratory and muscular fitness in healthy young adults in both experimental groups. [ABSTRACT FROM AUTHOR]

Purpose This study was designed to identify the lactate threshold ( LT) and first ventilatory threshold ( VT1) in a graded resistance half-squat test and determine whether both thresholds are produced at the same workload. A further goal was to compare the visual inspection and algorithm adjustment methods of detecting both thresholds during graded resistance exercise. Methods Twenty-four young men completed two test sessions 48 h apart; (i) the one-repetition maximum (1 RM) was determined, (ii) an incremental load test was performed to locate LT and VT1. VT1 was calculated in three different ways based on pulmonary ventilation, the ventilatory equivalent of oxygen or the end-tidal oxygen pressure (as VT1- VE, VT1- VE· [ABSTRACT FROM AUTHOR]

La fuerza influye directamente en el estado de salud y en la capacidad de fitness, motivo por el que el entrenamiento contra resistencias o resistance training (RT) se incluye dentro de aquellos programas de ejercicio encaminados a mejorar la salud y calidad de vida. Debido a que muchasenfermedades cursan con alteración de la masa y funcionalidad muscular y a que el RT es la principal modalidad de ejercicio encaminada a mejorar la función muscular, el objetivo de la presente revisión bibliográfica ha sido exponer las evidencias actuales sobre las adaptaciones delRT, así como su posible aplicación en patologías como la obesidad, diabetes, dislipemia, hipertensión, cáncer, Parkinson, esclerosis múltiple o fibromialgia. El RT en estas enfermedades puede aumentar los niveles de masa muscular, disminuyendo los niveles de masa grasa, los nivelesde ácidos grasos en sangre y la glucemia, incrementando la sensibilidad a la insulina, y disminuyendo los niveles de citokinas inflamatorias. El RT, además, mejora el gasto cardiaco y la funcionalidad endotelial, regulando la tensión arterial e incrementando el consumo de oxígeno. Las ganancias de fuerza muscular mejoran la funcionalidad y la calidad de vida, especialmente en población con una afectación neuromuscular grave, como pudieran ser los enfermos de esclerosis múltiple, fibromialgia o Parkinson. Por ello, el RT debe ser incorporado como parte del tratamiento en las personas que presentan determinado tipo de patologías. [ABSTRACT FROM AUTHOR]

Strawberry is one of the most economically important and widely cultivated fruit crops across the world, so that there is a growing need to develop new analytical methodologies for the authentication of variety and origin, as well as the assessment of agricultural and processing practices. In this work, an untargeted metabolomic strategy based on gas chromatography mass spectrometry (GC–MS) combined with multivariate statistical techniques was used for the first time to characterize the primary metabolome of different strawberry cultivars and to study metabolite alterations in response to multiple agronomic conditions. For this purpose, we investigated three varieties of strawberries with different sensitivity to environmental stress (Camarosa, Festival and Palomar), cultivated in soilless systems using various electrical conductivities, types of coverage and substrates. Metabolomic analysis revealed significant alterations in primary metabolites between the three strawberry cultivars grown under different crop conditions, including sugars (fructose, glucose), organic acids (malic acid, citric acid) and amino acids (alanine, threonine, aspartic acid), among others. Therefore, it could be concluded that GC–MS based metabolomics is a suitable tool to differentiate strawberry cultivars and characterize metabolomic changes associated with environmental and agronomic conditions. [ABSTRACT FROM AUTHOR]

Inflammation plays a prominent role in the pathogenesis of Alzheimer's disease, affecting both brain and the peripheral system. Thus, modulation of inflammation in animal models of this neurodegenerative disorder may be of great interest to elucidate the pathological mechanisms underlying this inflammatory component. To this end, a metabolomic investigation on a triple transgenic mouse model obtained by crossing the APP/PS1 mice with interleukin-4 knockout mice (a model of impaired immune function) was performed for the first time. Serum samples from transgenic mice and wild type animals were analyzed by direct infusion mass spectrometry followed by multivariate statistics in order to identify altered metabolites. Subsequently, metabolic pathway analysis allowed the elucidation of potential pathological mechanisms associated with the development of Alzheimer-type disorders in response to interleukin-4 deficiency, such as impaired homeostasis of histamine, altered metabolism of amino acids (threonine, aspartate and tyrosine), deregulated urea cycle and increased production of eicosanoids. Therefore, this work demonstrates the potential of this triple transgenic model with modulated immunity for the study of pathological mechanisms associated with inflammation in Alzheimer's disease. [ABSTRACT FROM AUTHOR]

This study was designed to identify the blood lactate threshold (LT2) for the half squat (HS) and to examine cardiorespiratory and metabolic variables during a HS test performed at a work intensity corresponding to the LT2. Twenty-four healthy men completed 3 test sessions. In the first, their one-repetition maximum (1RM) was determined for the HS. In the second session, a resistance HS incremental-load test was performed to determine LT2. Finally, in the third session, subjects performed a constantload HS exercise at the load corresponding to the LT2 (21 sets of 15 repetitions with 1 min of rest between sets). In this last test, blood samples were collected for lactate determination before the test and 30 s after the end of set (S) 3, S6, S9, S12, S15, S18 and S21. During the test, heart rate (HR) was telemetrically monitored and oxygen consumption (VO2), carbon dioxide production (VCO2), minute ventilation (VE), respiratory exchange ratio (RER), ventilatory equivalent for O2 (VE·VO2 -1) and ventilatory equivalent for CO2 (VE·VCO2 -1) were monitored using a breath-by-breath respiratory gas analyzer. The mean LT2 for the participants was 24.8 ± 4.8% 1RM. Blood lactate concentrations showed no significant differences between sets 3 and 21 of exercise (p = 1.000). HR failed to vary between S6 and S21 (p > 1.000). The respiratory variables VO2, VCO2, and VE·VCO2 -1 stabilized from S3 to the end of the constant-load HS test (p = 0.471, p = 0.136, p = 1.000), while VE and VE·VO2 -1 stabilized from S6 to S21. RER did not vary significantly across exercise sets (p = 0.103). The LT2 was readily identified in the incremental HS test. Cardiorespiratory and metabolic variables remained stable during this resistance exercise conducted at an exercise intensity corresponding to the LT2. These responses need to be confirmed for other resistance exercises and adaptations in these responses after a training program also need to be addressed. [ABSTRACT FROM AUTHOR]

Metabolomic analysis of brain tissue from transgenic mouse models of Alzheimer's disease has demonstrated a great potential for the study of pathological mechanisms and the development of new therapies and biomarkers for diagnosis. However, in order to translate these investigations to the clinical practice it is necessary to corroborate these findings in peripheral samples. To this end, this work considers the application of a novel metabolomic platform based on the combination of a two-steps extraction procedure with complementary analysis by direct infusion electrospray mass spectrometry and flow infusion atmospheric pressure photoionization mass spectrometry for a holistic investigation of metabolic abnormalities in serum samples from APP/PS1 mice. A number of metabolites were found to be perturbed in this mouse model, including increased levels of di- and tri-acylglycerols, eicosanoids, inosine, choline and glycerophosphoethanolamine; reduced content of cholesteryl esters, free fatty acids, lysophosphocholines, amino acids, energy-related metabolites, phosphoethanolamine and urea, as well as abnormal distribution of phosphocholines depending on the fatty acid linked to the molecular moiety. This allowed the elucidation of possible pathways disturbed underlying to disease (abnormal homeostasis of phospholipids leading to membrane breakdown, energy-related failures, hyperammonemia and hyperlipidemia, among others), thus demonstrating the utility of peripheral samples to investigate pathology in the APP/PS1 model. [ABSTRACT FROM AUTHOR]

Gas chromatography coupled to mass spectrometry is the most frequent tool for metabolomic profiling of low molecular weight metabolites. Its suitability in health survey is beyond doubt, given that primary metabolites involved in central pathways of metabolism are usually altered in diseases. The objective of this work is to investigate metabolic differences in serum between Alzheimer's disease patients and healthy controls in order to elucidate pathological mechanisms underlying to disease. Alterations in levels of 23 metabolites were detected, including increased lactic acid, α-ketoglutarate, isocitric acid, glucose, oleic acid, adenosine and cholesterol, as well as decreased urea, valine, aspartic acid, pyroglutamate, glutamine, phenylalanine, asparagine, ornithine, pipecolic acid, histidine, tyrosine, palmitic and uric acid, tryptophan, stearic acid and cystine. Metabolic pathway analysis revealed the involvement of multiple affected pathways, such as energy deficiencies, oxidative stress, hyperammonemia, and others. Moreover, it is noteworthy that some of these compounds have not been previously described in AD research, such as α-ketoglutarate, isocitrate pipecolic acid, pyroglutamate and adenosine, confirming the potential of this metabolomic approach in the search of novel potential markers for early detection of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

The transgenic mouse APP/PS1 is widely employed by neuroscientists because reproduces well some of the neuropathological and cognitive deficits observed in human Alzheimer's disease. In this study, serum samples from APP/PS1 mice (n = 30) and wild-type controls (n = 30) were analyzed using a metabolomic multiplatform based on the combination of gas chromatography-mass spectrometry and ultra-high performance liquid chromatography-mass spectrometry, in order to obtain wide information about serum metabolome. Metabolic profiles showed significant differences between the groups of study, and numerous metabolites were identified as potential players in the development of Alzheimer-type disorders in this transgenic model. Pathway analysis revealed the involvement of multiple metabolic networks in the underlying pathology, such as deficiencies in energy metabolism, altered amino acid homeostasis, abnormal membrane lipid metabolism, and other impairments related to the integrity of the central nervous system. It is noteworthy that some of these metabolomic markers are in accordance with pathological alterations observed in human Alzheimer's disease, while others have not been previously described. Therefore, these results demonstrate the potential of metabolomics and the use of transgenic animal models to understand the pathogenesis of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

The identification of pathological mechanisms underlying to Alzheimer's disease is of great importance for the discovery of potential markers for diagnosis and disease monitoring. In this study, we investigated regional metabolic alterations in brain from the APP/PS1 mice, a transgenic model that reproduces well some of the neuropathological and cognitive deficits observed in human Alzheimer's disease. For this purpose, hippocampus, cortex, cerebellum and olfactory bulbs were analyzed using a high-throughput metabolomic approach based on direct infusion mass spectrometry. Metabolic fingerprints showed significant differences between transgenic and wild-type mice in all brain tissues, being hippocampus and cortex the most affected regions. Alterations in numerous metabolites were detected including phospholipids, fatty acids, purine and pyrimidine metabolites, acylcarnitines, sterols and amino acids, among others. Furthermore, metabolic pathway analysis revealed important alterations in homeostasis of lipids, energy management, and metabolism of amino acids and nucleotides. Therefore, these findings demonstrate the potential of metabolomic screening and the use of transgenic models for understanding pathogenesis of Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Carnosine, dipeptide formed by amino acids ß-alanine and L-histidine, has important physiological functions among which its antioxidant and related memory and learning. However, in connection with the exercise, the most important functions would be associated with muscle contractility, improving calcium sensitivity in muscle fibers, and the regulatory function of pH. Thus, it is proposed that carnosine is the major intracellular buffer, but could contribute to 7-10% in buffer or buffer capacity. Since carnosine synthesis seems to be limited by the availability of ß-alanine supplementation with this compound has been gaining increasing popularity among the athlete population. Therefore, the objective of this study literature review was to examine all those research works have shown the effect of ß-alanine supplementation on athletic performance. Moreover, it also has attempted to establish a specific dosage that maximizing the potential benefits, minimize paresthesia, the main side effect presented in response to supplementation. [ABSTRACT FROM AUTHOR]

The use of atmospheric pressure photoionization is not widespread in metabolomics, despite its considerable potential for the simultaneous analysis of compounds with diverse polarities. This work considers the development of a novel analytical approach based on flow injection analysis and atmospheric pressure photoionization mass spectrometry for rapid metabolic screening of serum samples. Several experimental parameters were optimized, such as type of dopant, flow injection solvent, and their flows, given that a careful selection of these variables is mandatory for a comprehensive analysis of metabolites. Toluene and methanol were the most suitable dopant and flow injection solvent, respectively. Moreover, analysis in negative mode required higher solvent and dopant flows (100 µl min −1 and 40 µl min −1 , respectively) compared to positive mode (50 µl min −1 and 20 µl min −1 ). Then, the optimized approach was used to elucidate metabolic alterations associated with Alzheimer׳s disease. Thereby, results confirm the increase of diacylglycerols, ceramides, ceramide-1-phosphate and free fatty acids, indicating membrane destabilization processes, and reduction of fatty acid amides and several neurotransmitters related to impairments in neuronal transmission, among others. Therefore, it could be concluded that this metabolomic tool presents a great potential for analysis of biological samples, considering its high-throughput screening capability, fast analysis and comprehensive metabolite coverage. [ABSTRACT FROM AUTHOR]

The role of iron in the human body is essential, and athletes must always try to keep an adequate iron status. Hepcidin is proposed as the main hormone responsible for the control of iron reserves in the body, given its ability to induce degradation of ferroportin. The action of hepcidin on ferroportin leads to a decreased dietary iron absorption, as well as to a decrease in macrophages. Several factors such as the iron status, the amount of dietary iron, the inflammation, the hypoxia, the testosterone and the physical exercise have been pointed out as affecting the synthesis of hepcidin. This study has aimed at analysing the researches on hepcidin response to exercise, as well as designing a specific strategy to prevent a potential ferropenic status in athletes. The main findings are an association between exercise at an intensity over 65% VO2max and transient increases in the synthesis of hepcidin, and a possible regulatory effect of intermittent hypoxic stimuli in the early post-exercise recovery. Other factors such as the training volume, sex, kind of exercise or the type of surface where the training takes place do not seem to affect the response of hepcidin to exercise. [ABSTRACT FROM AUTHOR]

The analysis of urine by direct infusion mass spectrometry suffers from ion suppression due to its high salt content and inter-sample variability caused by the differences in urine volume between persons. Thus, urine metabolomics requires a careful selection of the sample preparation procedure and a normalization strategy to deal with these problems. Several approaches were tested for metabolomic analysis of urine samples by direct infusion electrospray mass spectrometry (DI–ESI–MS), including solid phase extraction, liquid–liquid extraction, and sample dilution. In addition, normalization of results based on conductivity values and statistical treatment was performed to minimize sample variability. Both urine dilution and solid phase extraction with mixed mode sorbent considerably reduced the salt content in urine, providing comprehensive metabolomic fingerprints. Moreover, statistical data normalization enabled the correction of inter-sample physiological variability, improving the quality of results obtained. Therefore, high-throughput DI–ESI–MS fingerprinting of urine samples can be achieved with simple pretreatment procedures allowing the use of this noninvasive sampling in metabolomics. Finally, the optimized approach was tested in a pilot metabolomic investigation of urine samples from transgenic mice models of Alzheimer’s disease (APP/PS1) in order to illustrate the potential of the methodology. [ABSTRACT FROM AUTHOR]

Given the multiple functions of iron in the body, any state of iron deficiency will induce a series of secondary effects that could compromise sports performance. Low serum iron levels are commonly observed in athletes during the course of a training period, especially in those performing aerobic exercises and resistance training. Sometimes, body iron levels will even fall below those detected in sedentary individuals, and we could go as far as to say that iron deficiency is the most frequently observed nutrition disorder among athletes of any sport. Hepcidin, a hormone secreted by hepatocytes whose principal mechanism of action is the degradation of ferroportin (the main iron exporter from macrophages and the basolateral membrane of duodenal enterocytes), has been proposed as the main regulator of the body's iron reserves. Thus, elevated serum hepcidin levels lead to diminished iron absorption and recycling, while lower levels of the hormone will cause greater iron absorption. Among the factors that affect the hepcidin response produced, we should highlight an individual's total iron levels, erythropoietic demands, state of hypoxia, dietary iron, inflammation and physical exercise. Given the important role played by iron regulatory mechanisms in physical performance, this report reviews our current understanding of the physiological response of hepcidin to different sports intensities and modalities. [ABSTRACT FROM AUTHOR]

Abstract: Alzheimer's disease is closely related to abnormal metabolism of phospholipids from neural membranes, so that the study of their dyshomeostasis could be of great interest for the discovery of potential biomarkers for diagnosis and disease monitoring. In this work, it has been developed a metabolomic multi-platform for the characterization of phospholipid alterations occurring in serum from Alzheimer's disease patients. For this purpose, we performed a metabolomic screening by direct infusion mass spectrometry and profiling analysis by reversed phase ultra-high performance liquid chromatography with complementary detection by molecular and atomic mass spectrometry, which allowed combining the high-throughput capability of shotgun metabolomics and the targeted character of profiling approaches. Thus significant changes were detected in the levels of several molecular species of phosphatidylcholines, phosphatidylethanolamines, plasmenylcholines, plasmenylethanolamines and different classes of lysophospholipids, which provided a global vision of the possible factors triggering membrane breakdown. In this sense, alterations of phospholipids metabolism appears to have a multifactorial origin involving overactivation of phospholipases, increased anabolism of lysophospholipids, peroxisomal dysfunction, imbalances in the levels of saturated/unsaturated fatty acids contained in the structure of phospholipids and oxidative stress. Biological significance: This work represents the first comprehensive characterization of serum phospholipids alterations in relation to Alzheimer's disease, by combining shotgun metabolomics and phospholipids profiling through different analytical approaches.This article is part of a Special Issue entitled: Environmental and structural proteomics. [Copyright &y& Elsevier]

Light Detection and Ranging (LIDAR) sensors are commonly used in perception for autonomous vehicles because of their high accuracy, speed, and range. These characteristics make the sensor suitable for integration into the perception layer of controllers which have the capacity to avoid collisions with unpredicted obstacles. The objective of this work was to design a robust and efficient algorithm to acquire useful knowledge from LIDAR scans, and to test its performance in real road situations. The method is based on the construction of an Occupancy Grid based on the Transferable Belief Model, which has proved promising in other studies. Two clear advantages of this method are the reduction of the problem complexity in the phases of segmentation, occlusion detection and tracking, and its ease of integration with other sensors to allow the overall system to evolve towards reliable and complete perception. [ABSTRACT FROM AUTHOR]

Abstract: Aim: To evaluate the cognitive performance of a homogeneous population of Alzheimer''s disease (AD), non-demented Type 2 Diabetes Mellitus (DIAB), demented with concomitant diseases (AD+DIAB) and healthy control subjects. AD is a progressive dementia disorder characterized clinically by impairment of memory, cognition and behavior. Recently, a major research interest in AD has been placed on early evaluation. Diabetes is one of the clinical conditions that represent the greatest risk of developing oxidative stress and dementia. Glucose overload, leading to the development of impaired-induced insulin secretion in DIAB and has been suggested to slow or deter AD pathogenesis. Methods: The degree of cognitive impairment was determined on the Alzheimer Disease Assessment Scale-Cognitive (ADAS-Cog) and the Folstein''s Mini Mental State Examination (MMSE); the severity of dementia was quantified applying the Clinical Dementia Rating (CDR) test; the Hamilton test was employed to evaluate depressive conditions; the final population studied was 101 subjects. Results: The cognitive deterioration is statistically significantly lower (p <0.05) in AD+DIAB patients as compared with AD patients. Conclusions: In this longitudinal study the superimposed diabetic condition was associated with a lower rate of cognitive decline, while diabetic non-demented patients and controls present normal scores. [Copyright &y& Elsevier]

Markers of oxidative stress were measured in blood samples of 338 subjects (965 observations): Alzheimer’s, vascular dementia, diabetes (type II) superimposed to dementias, Parkinson’s disease and controls. Patients showed increased thiobarbituric acid reactive substances (+21%; P < 0.05), copper-zinc superoxide dismutase (+64%; P < 0.001) and decreased antioxidant capacity (−28%; P < 0.001); pairs of variables resulted linearly related across groups ( P < 0.001). Catalase and glutathione peroxidase, involved in discrimination between diseases, resulted non-significant. When diabetes is superimposed with dementias, changes resulted less marked but significant. Also, superoxide dismutase resulted not linearly correlated with any other variable or age-related (pure Alzheimer’s peaks at 70 years, P < 0.001). Systemic oxidative stress was significantly associated ( P ≪ 0.001) with all diseases indicating a disbalance in peripheral/adaptive responses to oxidative disorders through different free radical metabolic pathways. While other changes—methionine cycle, insulin correlation—are also associated with dementias, the responses presented here show a simple linear relation between prooxidants and antioxidant defenses. [ABSTRACT FROM AUTHOR]

OBJECTIVES: To adapt and validate a Spanish-language version (SV) of the National institutes of Health Stroke Scale (NIHSS) to facilitate its use in Spanish-speaking contexts. PATIENTS AND METHODS: The methods recommended by the international Quality of Life Assessment Project were followed Two forward translations and 1 back translation of the NIHSS were developed to ensure lingual and cultural equivalence. A final revised SV-NIHSS was administered by 8 physicians to patients with stroke in 3 clinics in Buenos Aires, Argentina, from September 2003 to December 2003. RESULTS: The study included 102 patients (mean ± SD age, 73.3±6.5 years; 56% women) with stroke (86% ischemic). The SV-NIHSS mean baseline score was 9.78±704 interrater reliability was independently evaluated for 98 patients, showing a high agreement: κ, 0.77 to 0.99 for the 15 items; interrater correlation coefficient, 0.991 (95% confidence interval, 0.987-0.994). intrarater reliability was excellent: κ, 0.86 to 1.00 for the 15 items; mean Intrarater correlation coefficient, 0.994 (95% confidence interval, 0.991-0.996). Construct validity was also adequate; the SV-NIHSS had a negative correlation with baseline Glasgow Coma Scale (Spearman coefficient = -.0574, P < .001) and with Barthel index at 3 months (Spearman coefficient = -0.658, P < 001). Patients with different Rankin scores at 3 months also had significantly different baseline SV-NIHSS scores, from a mean of 4.29 ± 2.21 for Rankin score of 0 to a mean of 2940± 3.97 for Rankin score of 6 (P < .001). CONCLUSION: This study shows that a Spanish-language version of the NIHSS developed with internationally recommended methods is reliable and valid when applied in a Spanish-speaking setting. [ABSTRACT FROM AUTHOR]

Abstract: Background: Increased concentration of plasmatic homocysteine (tHcy) and decreased vitamin B 12 (B12) and folate (FOL) are associated with Alzheimer''s (AD) and vascular (VaD) dementias, with type II diabetes mellitus (DM), and reported as risk factors of these diseases. Methods: The sample (n =122; males=60; mean age=73±7 years) comprised AD and VaD patients without DM, with a concomitant DM (AD+DM, VaD+DM), DM alone and controls (CTR), resulting in 6 groups. tHcy, B12 and FOL were determined in duplicate. Results: The one-way ANOVA yielded significant differences between groups for all variables: tHcy p &#60;10− 12; B12 p &#60;10− 3; FOL p &#60;10− 4. Significance for comparisons between groups was set at α =0.05, using the Bonferroni''s statistic. The comparisons: DM vs. CTR, AD+DM vs. AD, VaD+DM vs. VaD, and DM demented vs. DM non-demented resulted significant for all variables, except for B12 in 2 comparisons. Conclusions: In demented and control subjects, tHcy and FOL exhibit extreme differences, not so marked between DM and controls. Demented patients with concomitant diabetes are closer to controls than their non-diabetic counterparts. Diabetes affects tHcy and FOL values, which are changed with opposite sign to non-demented. These results suggests a paradoxical phenomenon when diabetes is superimposed to dementias. [Copyright &y& Elsevier]

The integration of gamification in mHealth interventions presents a novel approach to enhance user engagement and health outcomes. This study aims to evaluate whether comparison-oriented gamification can effectively improve various aspects of health and well-being, including physical activity, sedentary behavior, sleep, and overall quality of life among young adults. Potential 107 young adults (from 19 to 28 years old) participated in an 8-week trial. Participants were assigned to either a gamified mHealth intervention (LevantApp) with daily leaderboards and progress bars (n = 53, 26 % dropped-out), or a control condition without gamification (n = 52, 29 % dropped-out). Physical activity (number of steps, moderate and moderate-to-vigorous physical activity -MVPA-) and sleep quantity were measured objectively via accelerometry and subjectively using the International Physical Activity Questionnaire(IPAQ), Pittsburgh Sleep Quality Index(PSQI), Sedentary Behavior Questionnaire(SBQ), and Short Form Health Survey(SF-36). This mHealth intervention with social comparison-oriented gamification significantly improved moderate physical activity to a greater extent than the control group. Additionally, the intervention group showed improvements in the number of steps, moderate physical activity, sedentary time, emotional wellbeing, and social functioning. However, no significant group by time interaction was observed. No significant differences were observed in sleep quality or quantity. s: The LevantApp gamified mHealth intervention was effective in improving moderate physical activity, physical functioning, and role-emotional in young adults. No significant effects were found on step counts, MVPA or sleep, suggesting that while gamification can enhance specific aspects of physical activity and quality of life, its impact may vary across different outcomes. • An mHealth trial using comparison-oriented gamification increased physical activity. • Activity trackers along with gamification improved quality of life in young adults. • Healthy lifestyle interventions may use these insights for effective coaching systems. [ABSTRACT FROM AUTHOR]

Systemic lupus erythematosus (SLE) is a heterogeneous disease with unpredictable patterns of activity. Patients with similar activity levels may have different prognosis and molecular abnormalities. In this study, we aimed to measure the main differences in drug-induced gene expression signatures across SLE patients and to evaluate the potential for clinical data to build a machine learning classifier able to predict the SLE subset for individual patients. SLE transcriptomic data from two cohorts were compared with drug-induced gene signatures from the CLUE database to compute a connectivity score that reflects the capability of a drug to revert the patient signatures. Patient stratification based on drug connectivity scores revealed robust clusters of SLE patients identical to the clusters previously obtained through longitudinal gene expression data, implying that differential treatment depends on the cluster to which patients belongs. The best drug candidates found, mTOR inhibitors or those reducing oxidative stress, showed stronger cluster specificity. We report that drug patterns for reverting disease gene expression follow the cell-specificity of the disease clusters. We used 2 cohorts to train and test a logistic regression model that we employed to classify patients from 3 independent cohorts into the SLE subsets and provide a clinically useful model to predict subset assignment and drug efficacy. [ABSTRACT FROM AUTHOR]

The objective of this study is to evaluate biomarkers for neurodegenerative disorders in adult SMA patients and their potential for monitoring the response to nusinersen. Biomarkers for neurodegenerative disorders were assessed in plasma and CSF samples obtained from a total of 30 healthy older adult controls and 31 patients with adult SMA type 2 and 3. The samples were collected before and during nusinersen treatment at various time points, approximately at 2, 6, 10, and 22 months. Using ELISA technology, the levels of total tau, pNF-H, NF-L, sAPPβ, Aβ40, Aβ42, and YKL-40 were evaluated in CSF samples. Additionally, plasma samples were used to measure NF-L and total tau levels using SIMOA technology. SMA patients showed improvements in clinical outcomes after nusinersen treatment, which were statistically significant only in walkers, in RULM (p = 0.04) and HFMSE (p = 0.05) at 24 months. A reduction in sAPPβ levels was found after nusinersen treatment, but these levels did not correlate with clinical outcomes. Other neurodegeneration biomarkers (NF-L, pNF-H, total tau, YKL-40, Aβ40, and Aβ42) were not found consistently changed with nusinersen treatment. The slow progression rate and mild treatment response of adult SMA types 2 and 3 may not lead to detectable changes in common markers of axonal degradation, inflammation, or neurodegeneration, since it does not involve large pools of damaged neurons as observed in pediatric forms. However, changes in biomarkers associated with the APP processing pathway might be linked to treatment administration. Further studies are warranted to better understand these findings. [ABSTRACT FROM AUTHOR]

The article is a response to a letter discussing the effectiveness of a web application called MyPROSLE in classifying patients with lupus nephritis. The authors clarify that MyPROSLE is meant to provide additional information for clinical decisions, not replace standard diagnostic procedures. They address concerns raised in the letter and provide detailed explanations and analysis of MyPROSLE's performance. The authors also discuss the impact of incorporating healthy samples in the analysis and highlight the need for considering multiple performance metrics. They emphasize that MyPROSLE should only be used for research purposes and provide data availability and funding information. [Extracted from the article]

Background: Several studies investigated the effects of caffeine supplementation on movement velocity in resistance exercise. However, these studies presented inconsistent findings. Objective: This paper aimed to: (a) review the studies that explored the effects of caffeine supplementation on movement velocity in resistance exercise; and (b) pool their results using a meta-analysis. Methods: A search for studies was performed through seven databases. Random-effects meta-analyses of standardized mean differences (SMD) were performed to analyze the data. Sub-group meta-analyses explored the effects of caffeine on different velocity variables (i.e., mean and peak velocity), different loads (i.e., low, moderate, and high loads), and upper- and lower-body exercises. Results: Twelve studies met the inclusion criteria. In the main meta-analysis, in which we pooled all available studies, the SMD favored the caffeine condition (SMD = 0.62; 95% confidence interval [CI]: 0.39–0.84; p < 0.001). Sub-group analyses indicated that caffeine significantly enhances mean (SMD = 0.80; 95% CI: 0.48–1.12; p < 0.001) and peak velocity (SMD = 0.41; 95% CI: 0.08–0.75; p = 0.014), movement velocity with low loads (SMD = 0.78; 95% CI: 0.41–1.14; p < 0.001), moderate loads (SMD = 0.58; 95% CI: 0.25–0.91; p = 0.001), and high loads (SMD = 0.70; 95% CI: 0.33–1.07; p < 0.001), as well as in lower-body (SMD = 0.82; 95% CI: 0.42–1.23; p < 0.001) and upper-body exercises (SMD = 0.59; 95% CI: 0.37–0.82; p < 0.001). Conclusion: Acute caffeine supplementation is highly ergogenic for movement velocity in resistance exercise. Sub-group analyses indicated that caffeine ingestion is ergogenic: (a) for both mean and peak velocity; (b) for movement velocity when exercising with low, moderate and high loads, and (c) for movement velocity in both lower- and upper-body exercises. Previous meta-analyses that explored the effects of caffeine on various aspects of resistance exercise performance (i.e., muscular strength and endurance) reported trivial to moderate ergogenic effects (effect size range: 0.16–0.38). In the present meta-analysis, the pooled effect size ranged from 0.41 to 0.82. From a resistance exercise performance standpoint, this suggests that caffeine has the most pronounced performance-enhancing effects on movement velocity. [ABSTRACT FROM AUTHOR]

The food industry demands novel green solvents for the extraction of bioactive compounds, particularly from residues of the agrifood industry. Herein, an ultrasound-assisted method has been developed for the environmentally friendly extraction of phenolic compounds from blueberry leaves using natural deep eutectic solvents (NADES). After the screening of multiple NADES, the best extraction efficiencies in terms of total phenol content and antioxidant activity were provided by NADES composed of lactate, sodium acetate, and water (3:1:2), and of choline chloride and oxalic acid (1:1). Using a Box–Behnken experimental design, the optimal extraction conditions were achieved by sonicating for 45 min at 65 °C and using solvent:sample ratios of 15 and 75 (v/w) for the NADES based on lactic acid and choline, respectively. Compared with conventional organic solvents, the use of these NADES composed of lactic acid and choline provided superior performance for the recovery of phenolic compounds (1.6-fold and 2.2-fold greater efficacy, respectively) and antioxidant compounds (1.6-fold and 2.8-fold greater efficacy, respectively). The chromatographic characterization of the extracts obtained under these optimized conditions evidenced that the lactic-based NADES enabled the extraction of a wide range of hydroxycinnamic acids and flavonol derivatives, whereas the choline-based NADES was selective towards the extraction of anthocyanins. These results indicate that the proposed method could represent an excellent green alternative for the recovery of phenolic compounds from plant materials and agrifood wastes, with improved extraction efficacy and/or selectivity compared to that provided by traditional organic solvents. [Display omitted] • Novel method for the extraction of polyphenols from blueberry leaves using NADES. • Lactic-based NADES extracts hydroxycinnamic acids and flavonols. • Choline-based NADES is selective for the extraction of anthocyanins. [ABSTRACT FROM AUTHOR]

The purpose of this study is to analyze the relationship between self-esteem and the dimensions that define physical self-concept, and the perception of health in older people, in relation to the level of physical activity practice they perform. To do this, 130 participants between 63 and 75 years old (M = 67.3 and DT = 3.14), were classified into two groups, physically active and physically inactive, depending on the level of physical activity they perform; Rosenberg's Self-Esteem Scale, Fox and Corbin's Physical Self-Perception Profile, and SF-36 Health Survey from Ware and Sherbourne were all applied to them. The results show the positive relationship established between being a physically active person and the best levels in self-esteem, physical condition and perceived competence. In addition, it is determined that the physical and emotional role played by people in daily routines, are respectively related to perceived competence and physical appearance. [ABSTRACT FROM AUTHOR]

Shoulder pain has been associated with glenohumeral internal rotation deficit (GIRD) and a reduction in external rotation (ER) strength; however, in tennis players, there is scarce evidence regarding the impact of a single match on shoulder range of motion (ROM), strength and serve speed. The aim of this study was to determine the acute effect of a single tennis match on shoulder rotation ROM, isometric strength and serve speed. Twenty-six professional tennis players participated in the study (20.4±4.4 years; 10.5±3.2 years tennis expertise; 20.5±5.4 h/week training). Passive shoulder external (ER-ROM) and internal rotation ROM (IR-ROM), ER and IR isometric strength were measured before and after a single tennis match (80.3±21.3 min) in both shoulder´s. Moreover, the total arc of motion (TAM) and ER/IR strength ratio were calculated. Video analysis was used to assess the number of serves and groundstrokes, while a radar gun was utilized to measure maximal ball speed. In the dominant shoulder, compared to pre-match levels, IR-ROM was significantly reduced (-1.3%; p = 0.042), while ER-ROM (5.3%; p = 0.037) and TAM (3.1%; p = 0.050) were significantly increased. In the non-dominant shoulder, ER-ROM (3.7%; p = 0.006) was increased. Furthermore, in the dominant shoulder, the isometric ER strength was significantly reduced after the match (-4.8%; p = 0.012), whereas serve speed was not significantly reduced after match (-1.16%; p = 0.197). A single tennis match leads to significant reductions in shoulder ROM (e.g., IR of the dominant shoulder) and isometric strength (e.g., ER of the dominant shoulder). This study reveals the importance of recovery strategies prescription aiming at minimize post-match alteration in the shoulders. [ABSTRACT FROM AUTHOR]

Although growing evidence points to a pivotal role of perturbed metal homeostasis in childhood obesity, sexual dimorphisms in this association have rarely been investigated. In this study, we applied multi‐elemental analysis to plasma and erythrocyte samples from an observational cohort comprising children with obesity, with and without insulin resistance, and healthy control children. Furthermore, a wide number of variables related to carbohydrate and lipid metabolism, inflammation, and sex hormones were also determined. Children with obesity, regardless of sex and insulin resistance status, showed increased plasma copper‐to‐zinc ratios. More interestingly, obesity‐related erythroid alterations were found to be sex‐dependent, with increased contents of iron, zinc, and copper being exclusively detected among female subjects. Our findings suggest that a sexually dimorphic hormonal dysregulation in response to a pathological cascade involving inflammatory processes and hyperinsulinemia could be the main trigger of this female‐specific intracellular sequestration of trace elements. Therefore, the present study highlights the relevance of genotypic sex as a susceptibility factor influencing the pathogenic events behind childhood obesity, thereby opening the door to develop sex‐personalized approaches in the context of precision medicine. [ABSTRACT FROM AUTHOR]

Although puberty is known to influence obesity progression, the molecular mechanisms underlying the role of sexual maturation in obesity‐related complications remains largely unexplored. Here, we delve into the impact of puberty on the most relevant pathogenic hallmarks of obesity, namely oxidative stress and inflammation, and their association with trace element blood status. To this end, we studied a well‐characterized observational cohort comprising prepubertal (N = 46) and pubertal (N = 48) children with obesity. From all participants, plasma and erythrocyte samples were collected and subjected to metallomics analysis and determination of classical biomarkers of oxidative stress and inflammation. Besides the expected raise of sexual hormones, pubertal children displayed better inflammatory and oxidative control, as reflected by lower levels of C‐reactive protein and oxidative damage markers, as well as improved antioxidant defense. This was in turn accompanied by a healthier multielemental profile, with increased levels of essential elements involved in the antioxidant system and metabolic control (metalloproteins containing zinc, molybdenum, selenium, and manganese) and decreased content of potentially deleterious species (total copper, labile free iron). Therefore, our findings suggest that children with obesity have an exacerbated inflammatory and oxidative damage at early ages, which could be ameliorated during pubertal development by the action of trace element‐mediated buffering mechanisms. [ABSTRACT FROM AUTHOR]

Purpose: Beetroot juice is a dietary supplement that contains high levels of inorganic nitrate (NO3-) and that its intake has proven effective at increasing blood nitric oxide (NO) concentrations improving endurance performance. However, the effect of this supplement in team sport performance, especially in female athletes, has been barely studied. This study aimed to compare the acute effects of beetroot juice supplementation on neuromuscular performance and match-play demands in elite female field hockey players. Methods: Eleven elite female hockey players (22.8 ± 5.1 years) belonging to a bronze team medal in Eurohockey Club Champions Cup participated in this study. Participants were randomly divided into two groups undergoing a test battery with beetroot juice (70 mL, 6.4 mmol NO3−) or placebo (70 mL, 0.04 mmol NO3−) in two different days with one week between protocols. The neuromuscular test battery consisted of a countermovement jump, isometric handgrip strength (i.e., dominant hand), 20 m-sprint and repeated sprint ability test (RSA). Afterward, a simulated hockey match play (2 × 12.5 min) was performed and recorded by Global Positioning System (GPS). Results: No statistically significant improvements were observed in any physical parameters analysed comparing beetroot juice compared to placebo ingestion, countermovement jump (p = 0.776, ES = 0.16), isometric handgrip strength (p = 0.829; ES = – 0.08), 20 m sprint test (p = 0.227; ES = – 0.23), mean repeated sprint ability (p = 0.955, ES = 0.03) and in any physical match demands measured by GPS (p = 0.243–1.000; ES = 0.02–0.47). Conclusion: Acute beetroot juice supplementation did not produce any statistically significant improvement in neuromuscular performance or match-play demands in elite female field hockey players. Trial registration: The study was registered in ClinicalTrials.gov with the following ID: NCT05209139. The study was retrospectively registered by 26 January 2022. [ABSTRACT FROM AUTHOR]

The aim of this study was to assess the effects of a mixture of four dietary fibers on obese rats. Four groups of male Wistar rats were fed with either standard chow (STD) or cafeteria diet (CAF) and were orally supplemented with either fibre mixture (2 g kg-1 of body weight) (STD+F or CAF+F groups) or vehicle (STD+VH or CAF+VH groups). We studied a wide number of biometric, biochemical, transcriptomic, metagenomic and metabolomic variables and applied an integrative multivariate approach based on multiple factor analysis and Pearson's correlation analysis. A significant reduction in body weight, adiposity, HbA1c and HDL-cholesterol serum levels, and colon MPO activity was observed, whereas cecal weight and small intestine length:weight ratio were significantly increased in F-treated groups compared to control animals. CAF+F rats displayed a significant enhancement in energy expenditure, fat oxidation and fresh stool weight, and a significant reduction in adiponectin and LPS serum levels, compared to control group. Animals in STD+F group showed reduced serum LDL-cholesterol levels and a significant reduction in total cholesterol levels in the liver compared to STF+VH group. The intervention effect was reflected at the metabolomic (i.e., production of short-chain fatty acids, phenolic acids, and amino acids), metagenomic (i.e., modulation of Ruminococcus and Lactobacillus genus) and transcriptomic (i.e., expression of tight junctions and proteolysis) levels. Altogether, our integrative multi-omics approach highlights the potential of supplementation with a mixture of fibers to ameliorate the impairments triggered by obesity in terms of adiposity, metabolic profile, and intestinal health. [ABSTRACT FROM AUTHOR]

Summary The Gene Expression Omnibus (GEO) database provides an invaluable resource of publicly available gene expression data that can be integrated and analyzed to derive new hypothesis and knowledge. In this context, gene expression meta-analysis (geMAs) is increasingly used in several fields to improve study reproducibility and discovering robust biomarkers. Nevertheless, integrating data is not straightforward without bioinformatics expertise. Here, we present ImaGEO, a web tool for geMAs that implements a complete and comprehensive meta-analysis workflow starting from GEO dataset identifiers. The application integrates GEO datasets, applies different meta-analysis techniques and provides functional analysis results in an easy-to-use environment. ImaGEO is a powerful and useful resource that allows researchers to integrate and perform meta-analysis of GEO datasets to lead robust findings for biomarker discovery studies. Availability and implementation ImaGEO is accessible at http://bioinfo.genyo.es/imageo/. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Immunotherapy with immune checkpoint inhibitors (ICIs) have been reported to induce de novo or exacerbate pre-existing Myasthenia Gravis (MG). We present a single center case series of patients who developed an immune-related myasthenia gravis (irMG) related with ICIs. We performed a retrospective chart review of the electronic medical records between 1 September 2017 and 2022. We report the clinical features, presentation forms, diagnostic workflows, general management and outcomes of six patients who received ICIs for different solid organ malignancies and developed an irMG frequently overlapping with immune-related myocarditis and/or myositis. The aim of the article is to describe the clinical features, treatment and outcomes of this challenging and potentially life-threating syndrome, comparing our data with those described in the literature. Differences between irMG and classic MG are highlighted. [ABSTRACT FROM AUTHOR]