During tournaments, team sport athletes are exposed to high physical loads due to a large number of games played within a few days. To perform well and prevent injuries, recovery in between these games is crucial. To monitor the recovery kinetics the Total Quality of Recovery (TQR) is suggested as a practical and useful tool (Kentta et al, 1998). The purpose of this study was to explore the feasibility and sensitivity of the TQR as a recovery monitoring tool during a 3-day floorball tournament. Methods Eleven elite Dutch female floorball athletes (age:24.3±4.8, length:171.5±9.1, weight:67.6±8.1) participated in a 3-day tournament. Their recovery was monitored with the TQR scale (6-20) (Kentta et al, 1998). All athletes were asked to rate their recovery each morning and every two hours including;1 hour prior to the game (pre-game), immediately after the game (post-game) and 2 hours post-game. Comparisons were made for the TQR at the beginning and end of the tournament as well as pre- vs. post-game.
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Introduction: Strenuous physical stress induces a range of physiological responses, the extent depending, among others, on the nature and severity of the exercise, a person’s training level and overall physical resilience. This principle can also be used in an experimental set-up by measuring time-dependent changes in biomarkers for physiological processes. In a previous report, we described the effects of workload delivered on a bicycle ergometer on intestinal functionality. As a follow-up, we here describe an analysis of the kinetics of various other biomarkers. Aim: To analyse the time-dependent changes of 34 markers for different metabolic and immunological processes, comparing four different exercise protocols and a rest protocol. Methods: After determining individual maximum workloads, 15 healthy male participants (20–35 years) started with a rest protocol and subsequently performed (in a cross-over design with 1-week wash-out) four exercise protocols of 1-h duration at different intensities: 70% Wmax in a hydrated and a mildly dehydrated state, 50% Wmax and intermittent 85/55% Wmax in blocks of 2 min. Perceived exertion was monitored using the Borg’ Rating of Perceived Exertion scale. Blood samples were collected both before and during exercise, and at various timepoints up to 24 h afterward. Data was analyzed using a multilevel mixed linear model with multiple test correction. Results: Kinetic changes of various biomarkers were exercise-intensity-dependent. Biomarkers included parameters indicative of metabolic activity (e.g., creatinine, bicarbonate), immunological and hematological functionality (e.g., leukocytes, hemoglobin) and intestinal physiology (citrulline, intestinal fatty acid-binding protein, and zonulin). In general, responses to high intensity exercise of 70% Wmax and intermittent exercise i.e., 55/85% Wmax were more pronounced compared to exercise at 50% Wmax. Conclusion: High (70 and 55/85% Wmax) and moderate (50% Wmax) intensity exercise in a bicycle ergometer test produce different time-dependent changes in a broad range of parameters indicative of metabolic activity, immunological and hematological functionality and intestinal physiology. These parameters may be considered biomarkers of homeostatic resilience. Mild dehydration intensifies these time-related changes. Moderate intensity exercise of 50% Wmax shows sufficient physiological and immunological responses and can be employed to test the health condition of less fit individuals.
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The data of this study indicate that the acetate recovery factor, used in stable isotope research, needs to be deteremined in every subject, under similar conditions as used for the tracer-derived determination of substrate oxidation.
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The increasing interest in Aronia melanocarpa berries for their antioxidant properties sets the necessity to define sustainable strategies to valorize the by-products. This study investigates the use of supercritical carbon dioxide (scCO2) extraction, with and without ethanol as a co-solvent, for recovering lipophilic and phenolic compounds from aronia pomace. Extractions were performed at 20, 30, and 40 MPa and temperatures of 50, 70, and 90 °C. A yield of about 2.7 g per 100 g of dried pomace was obtained at 40 MPa and 90 °C. However, the highest total phenolic content of about 165 mg of gallic acid equivalent per 100 g of dried pomace was achieved with 5 % ethanol co-solvent at 50 °C and 30 MPa. The lipid extracts were rich in linoleic acid and the wax portion increased under low-density scCO2 conditions. A feedforward neural network was developed to model extraction kinetics and predict yield as a function of temperature, pressure, and time, demonstrating high predictive accuracy. These findings highlight scCO2 extraction as a viable route for the efficient and selective recovery of valuable bioactives from aronia pomace, contributing to a circular bioeconomy.
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Development of novel testing strategies to detect adverse human health effects is of interest to replace in vivo-based drug and chemical safety testing. The aim of the present study was to investigate whether physiologically based kinetic (PBK) modeling-facilitated conversion of in vitro toxicity data is an adequate approach to predict in vivo cardiotoxicity in humans. To enable evaluation of predictions made, methadone was selected as the model compound, being a compound for which data on both kinetics and cardiotoxicity in humans are available. A PBK model for methadone in humans was developed and evaluated against available kinetic data presenting an adequate match. Use of the developed PBK model to convert concentration–response curves for the effect of methadone on human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) in the so-called multi electrode array (MEA) assay resulted in predictions for in vivo dose–response curves for methadone-induced cardiotoxicity that matched the available in vivo data. The results also revealed differences in protein plasma binding of methadone to be a potential factor underlying variation between individuals with respect to sensitivity towards the cardiotoxic effects of methadone. The present study provides a proof-of-principle of using PBK modeling-based reverse dosimetry of in vitro data for the prediction of cardiotoxicity in humans, providing a novel testing strategy in cardiac safety studies.
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Background Running-related injuries (RRIs) can be considered the primary enemy of runners. Most literature on injury prediction and prevention overlooks the mental aspects of overtraining and under-recovery, despite their potential role in injury prediction and prevention. Consequently, knowledge on the role of mental aspects in RRIs is lacking. Objective To investigate mental aspects of overtraining and under-recovery by means of an online injury prevention programme. Methods and analysis The ‘Take a Mental Break!’ study is a randomised controlled trial with a 12 month follow-up. After completing a web-based baseline survey, half and full marathon runners were randomly assigned to the intervention group or the control group. Participants of the intervention group obtained access to an online injury prevention programme, consisting of a running-related smartphone application. This app provided the participants of the intervention group with information on how to prevent overtraining and RRIs with special attention to mental aspects. The primary outcome measure is any self-reported RRI over the past 12 months. Secondary outcome measures include vigour, fatigue, sleep and perceived running performance. Regression analysis will be conducted to investigate whether the injury prevention programme has led to a lower prevalence of RRIs, better health and improved perceived running performance. Ethics and dissemination The Medical Ethics Committee of the University Medical Center Utrecht, the Netherlands, has exempted the current study from ethical approval (reference number: NL64342.041.17). Results of the study will be communicated through scientific articles in peer-reviewed journals, scientific reports and presentations on scientific conferences.
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Objective. Clinicians may use implicit or explicit motor learning approaches to facilitatemotor learning of patients with stroke. Implicit motor learning approaches have shown promising results in healthy populations. The purpose of this study was to assess whether an implicit motor learning walking intervention is more effective compared with an explicit motor learning walking intervention delivered at home regarding walking speed in people after stroke in the chronic phase of recovery. Methods. This randomized, controlled, single-blind trial was conducted in the home environment. The 79 participants, who were in the chronic phase after stroke (age = 66.4 [SD = 11.0] years; time poststroke = 70.1 [SD = 64.3] months; walking speed = 0.7 [SD = 0.3] m/s; Berg Balance Scale score = 44.5 [SD = 9.5]), were randomly assigned to an implicit (n = 38) or explicit (n = 41) group. Analogy learning was used as the implicit motor learning walking intervention, whereas the explicit motor learning walking intervention consisted of detailed verbal instructions. Both groups received 9 training sessions (30 minutes each), for a period of 3 weeks, targeted at improving quality of walking. The primary outcome was walking speed measured by the 10-MeterWalk Test at a comfortable walking pace. Outcomes were assessed at baseline, immediately after intervention, and 1 month postintervention. Results. No statistically or clinically relevant differences between groups were obtained postintervention (between-group difference was estimated at 0.02 m/s [95% CI = −0.04 to 0.08] and at follow-up (between-group difference estimated at −0.02 m/s [95% CI = −0.09 to 0.05]). Conclusion. Implicit motor learning was not superior to explicit motor learning to improve walking speed in people after stroke in the chronic phase of recovery. Impact. To our knowledge, this is the first study to examine the effects of implicit compared with explicit motor learning on a functional task in people after stroke. Results indicate that physical therapists can use (tailored) implicit and explicit motor learning strategies to improve walking speed in people after stroke who are in the chronic phase of recovery.
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Surgery aims to improve a patient’s medical condition. However, surgery is a major life event with the risk of negative consequences, like peri- and postoperative complications, prolonged hospitalization and delayed recovery of physical functioning. One of the major common side effects, functional decline, before (in the “waiting” period), during and after hospitalization is impressive, especially in frail people. Preoperative screening aims to identify frail, highrisk patients at an early stage, and advice these high-risk patients to start supervised preoperative home-based exercise training (prehabilitation) as soon as possible. Depending on the health status of the patient and his/her outcomes during the screening and the type of surgery, prehabilitation should focus on respiratory, cardiovascular and/or musculoskeletal parameters to prepare the patient for surgery. By improving preoperative physical fitness, a patient is able to better with stand the impact of major surgery and this will lead to a both reduced risk of negative side effects and better short term outcomes as a result. Besides prehabilitation hospital culture and infrastructure should be inherently activating so that patients stay as active as can be, socially, mentally and physically. In the first part of this chapter the concept of prehabilitation and different parameters that should be trained will be described. The second part focuses on the “Better in, Better out” (BiBo™) strategy, which aims to optimize patient’s pre-, peri- and postoperative physical fitness. Prehabilitation should comprise “shared decisions” between patient and physical therapist regarding experience and evidence based best options for rehabilitation goals, needs, and potential of the individual patient and his/her (in) formal support-system. Next, a case will describe the preoperative care pathway. This chapter will close with conclusions about how moving people before and after surgery will improve their outcomes.
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from the article: "Abstract: The oral mucosa is the first immune tissue that encounters allergens upon ingestion of food. We hypothesized that the bio-accessibility of allergens at this stage may be a key determinant for sensitization. Light roasted peanut flour was suspended at various pH in buffers mimicking saliva. Protein concentrations and allergens profiles were determined in the supernatants. Peanut protein solubility was poor in the pH range between 3 and 6, while at a low pH (1.5) and at moderately high pHs (>8), it increased. In the pH range of saliva, between 6.5 and 8.5, the allergens Ara h2 and Ara h6 were readily released, whereas Ara h1 and Ara h3 were poorly released. Increasing the pH from 6.5 to 8.5 slightly increased the release of Ara h1 and Ara h3, but the recovery remained low (approximately 20%) compared to that of Ara h2 and Ara h6 (approximately 100% and 65%, respectively). This remarkable difference in the extraction kinetics suggests that Ara h2 and Ara h6 are the first allergens an individual is exposed to upon ingestion of peanut-containing food. We conclude that the peanut allergens Ara h2 and Ara h6 are quickly bio-accessible in the mouth, potentially explaining their extraordinary allergenicity."
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Manure application can spread antimicrobial resistance (AMR) from manure to soil and surface water. This study evaluated the role of the soil texture on the dynamics of antimicrobial resistance genes (ARGs) in soils and surrounding surface waters. Six dairy farms with distinct soil textures (clay, sand, and peat) were sampled at different time points after the application of manure, and three representative ARGs sul1, erm(B), and tet(W) were quantified with qPCR. Manuring initially increased levels of erm(B) by 1.5 ± 0.5 log copies/kg of soil and tet(W) by 0.8 ± 0.4 log copies/kg across soil textures, after which levels gradually declined. In surface waters from clay environments, regardless of the ARG, the gene levels initially increased by 2.6 ± 1.6 log copies/L, after which levels gradually declined. The gene decay in soils was strongly dependent on the type of ARG (erm(B) < tet(W) < sul1; half-lives of 7, 11, and 75 days, respectively), while in water, the decay was primarily dependent on the soil texture adjacent to the sampled surface water (clay < peat < sand; half-lives of 2, 6, and 10 days, respectively). Finally, recovery of ARG levels was predicted after 29–42 days. The results thus showed that there was not a complete restoration of ARGs in soils between rounds of manure application. In conclusion, this study demonstrates that rather than showing similar dynamics of decay, factors such as the type of ARG and soil texture drive the ARG persistence in the environment.
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