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      Relationship Between Morning Heart Rate Variability and Creatine Kinase Response During Intensified Training in Recreational Endurance Athletes

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          Abstract

          Specific physiological responses and their relationship were analyzed in 12 recreational endurance athletes (43.8 ± 7.9 years) during a period of intensified cycling training. Heart rate (HR), HR variability (HRV), serum creatine kinase (S-CK) and haematocrit (Hct) were measured in the mornings before (PRE) and following three consecutive days of intensified training (POST 1–3). Morning HR increased during this period (PRE: 52.2 ± 6.7 bpm, POST 1: 58.8 ± 7.0 bpm, POST 2: 58.5 ± 8.1 bpm, POST 3: 57.9 ± 7.2 bpm; F(3,33) = 11.182, p < 0.001, η p 2 = 0.554). Parasympathetic HRV indices decreased from PRE to POST ( F(3,33) ≥ 11.588, p < 0.001, η p 2 ≥ 0.563), no effect was found for sympathetically modulated HRV ( F(3,33) = 2.287, p = 0.101, η p 2 = 0.203). Hct decreased (PRE: 49.9 ± 4.0%, POST 1: 46.5 ± 5.1%, POST 2: 45.5 ± 3.8%, POST 3: 43.2 ± 3.4%; F(3,33) = 11.909, p < 0.001, η p 2 = 0.520) and S-CK increased during the training period (PRE: 90.0 ± 32.1 U/L, POST 1: 334.7 ± 487.6 U/L, POST 2: 260.1 ± 303.4 U/L, POST 3: 225.1 ± 258.8 U/L; F(3,33) = 3.996, p = 0.017, η p 2 = 0.285). S-CK release was associated with HR ( r = 0.453, p = 0.002, n = 44), RMSSD ( r = −0.494, p = 0.001, n = 44) and HF-Power ( r = −0.490, p = 0.001, n = 44). A period of intensified training was associated with haemodilution, parasympathetic withdrawal and S-CK-increase. Cardiac autonomic control at morning rest correlated with the S-CK-release; and thus, may serve as a practical mean to complementary monitor and prescribe training load in this population.

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          Translating Fatigue to Human Performance.

          Despite flourishing interest in the topic of fatigue-as indicated by the many presentations on fatigue at the 2015 annual meeting of the American College of Sports Medicine-surprisingly little is known about its impact on human performance. There are two main reasons for this dilemma: (1) the inability of current terminology to accommodate the scope of the conditions ascribed to fatigue, and (2) a paucity of validated experimental models. In contrast to current practice, a case is made for a unified definition of fatigue to facilitate its management in health and disease. Based on the classic two-domain concept of Mosso, fatigue is defined as a disabling symptom in which physical and cognitive function is limited by interactions between performance fatigability and perceived fatigability. As a symptom, fatigue can only be measured by self-report, quantified as either a trait characteristic or a state variable. One consequence of such a definition is that the word fatigue should not be preceded by an adjective (e.g., central, mental, muscle, peripheral, and supraspinal) to suggest the locus of the changes responsible for an observed level of fatigue. Rather, mechanistic studies should be performed with validated experimental models to identify the changes responsible for the reported fatigue. As indicated by three examples (walking endurance in old adults, time trials by endurance athletes, and fatigue in persons with multiple sclerosis) discussed in the review, however, it has proven challenging to develop valid experimental models of fatigue. The proposed framework provides a foundation to address the many gaps in knowledge of how laboratory measures of fatigue and fatigability impact real-world performance.
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            Cell-cell and intracellular lactate shuttles.

            Once thought to be the consequence of oxygen lack in contracting skeletal muscle, the glycolytic product lactate is formed and utilized continuously in diverse cells under fully aerobic conditions. 'Cell-cell' and 'intracellular lactate shuttle' concepts describe the roles of lactate in delivery of oxidative and gluconeogenic substrates as well as in cell signalling. Examples of the cell-cell shuttles include lactate exchanges between between white-glycolytic and red-oxidative fibres within a working muscle bed, and between working skeletal muscle and heart, brain, liver and kidneys. Examples of intracellular lactate shuttles include lactate uptake by mitochondria and pyruvate for lactate exchange in peroxisomes. Lactate for pyruvate exchanges affect cell redox state, and by itself lactate is a ROS generator. In vivo, lactate is a preferred substrate and high blood lactate levels down-regulate the use of glucose and free fatty acids (FFA). As well, lactate binding may affect metabolic regulation, for instance binding to G-protein receptors in adipocytes inhibiting lipolysis, and thus decreasing plasma FFA availability. In vitro lactate accumulation upregulates expression of MCT1 and genes coding for other components of the mitochondrial reticulum in skeletal muscle. The mitochondrial reticulum in muscle and mitochondrial networks in other aerobic tissues function to establish concentration and proton gradients necessary for cells with high mitochondrial densities to oxidize lactate. The presence of lactate shuttles gives rise to the realization that glycolytic and oxidative pathways should be viewed as linked, as opposed to alternative, processes, because lactate, the product of one pathway, is the substrate for the other.
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              Monitoring training status with HR measures: do all roads lead to Rome?

              Measures of resting, exercise, and recovery heart rate are receiving increasing interest for monitoring fatigue, fitness and endurance performance responses, which has direct implications for adjusting training load (1) daily during specific training blocks and (2) throughout the competitive season. However, these measures are still not widely implemented to monitor athletes' responses to training load, probably because of apparent contradictory findings in the literature. In this review I contend that most of the contradictory findings are related to methodological inconsistencies and/or misinterpretation of the data rather than to limitations of heart rate measures to accurately inform on training status. I also provide evidence that measures derived from 5-min (almost daily) recordings of resting (indices capturing beat-to-beat changes in heart rate, reflecting cardiac parasympathetic activity) and submaximal exercise (30- to 60-s average) heart rate are likely the most useful monitoring tools. For appropriate interpretation at the individual level, changes in a given measure should be interpreted by taking into account the error of measurement and the smallest important change of the measure, as well as the training context (training phase, load, and intensity distribution). The decision to use a given measure should be based upon the level of information that is required by the athlete, the marker's sensitivity to changes in training status and the practical constrains required for the measurements. However, measures of heart rate cannot inform on all aspects of wellness, fatigue, and performance, so their use in combination with daily training logs, psychometric questionnaires and non-invasive, cost-effective performance tests such as a countermovement jump may offer a complete solution to monitor training status in athletes participating in aerobic-oriented sports.
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                Author and article information

                Contributors
                Journal
                Front Physiol
                Front Physiol
                Front. Physiol.
                Frontiers in Physiology
                Frontiers Media S.A.
                1664-042X
                13 September 2018
                2018
                : 9
                : 1267
                Affiliations
                [1] 1Institute of Sport Science, University of Rostock , Rostock, Germany
                [2] 2ISBA University of Cooperative Education , Schwerin, Germany
                Author notes

                Edited by: Martin Burtscher, Universität Innsbruck, Austria

                Reviewed by: Jesús Álvarez-Herms, Ministerio de Educación Cultura y Deporte, Spain; Beat Knechtle, University Hospital Zurich, Switzerland

                *Correspondence: Matthias Weippert, matthias.weippert@ 123456uni-rostock.de

                This article was submitted to Exercise Physiology, a section of the journal Frontiers in Physiology

                Article
                10.3389/fphys.2018.01267
                6161148
                980e1937-14d7-4c57-88f1-91626962f514
                Copyright © 2018 Weippert, Behrens, Mau-Moeller, Bruhn and Behrens.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 28 May 2018
                : 21 August 2018
                Page count
                Figures: 3, Tables: 1, Equations: 0, References: 54, Pages: 7, Words: 0
                Categories
                Physiology
                Original Research

                Anatomy & Physiology
                training load,cycling,muscle damage,aerobic exercise,rmssd,hf-power,haemodilution,haematocrit

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