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      Attenuated Lower Limb Stretch-Shorten-Cycle Capacity in ACL Injured vs. Non-Injured Female Alpine Ski Racers: Not Just a Matter of Between-Limb Asymmetry

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          Abstract

          A retrospective analysis of routine countermovement jump (CMJ) testing, a coupled eccentric-concentric (stretch-shorten-cycle: SSC) movement, was performed in female elite alpine skiers with anterior cruciate ligament (ACL) reconstruction (ACLR) and without ACLR. A total of 567 tests obtained from the daily training environment were analyzed in 41 elite female athletes (non-injured control: n = 30, ACLR: n = 17), including n = 6 athletes with pre-injury data, between 16 and 32 years of age from alpine ski racing ( n = 32) and skier cross ( n = 9). Bilateral CMJ testing was conducted on a dual force plate system, and the limb-specific vertical ground reaction force (Fz) was analyzed to obtain the net eccentric deceleration impulse (Ecc), lower limb stiffness (Stiff), maximal vertical jump height (JH), peak external mechanical power (PP) exerted on the body center of mass (BCM), modified-reactive-strength-index (RSImod), and the loss in BCM velocity during the final phase of the takeoff Δ(Vmax–Vtakeoff). Eccentric and concentric phase-specific between-limb asymmetry indexes (AIs) were also calculated. Additive mixed effects models (AMMs) were used to compare the age-dependent and post-injury time course change between groups. The mean values for non-injured controls >25 years of age were used as a comparative benchmark for recovery given the absence of pre-injury data. Net eccentric deceleration impulse increased and Δ(Vmax–Vtakeoff) decreased with age for the non-injured control group ( p < 0.001) while between-limb AI (mean ± SD) fell between 1 ± 5% for the concentric phase and 3 ± 7% for the eccentric deceleration phase. Between-limb asymmetry became smaller in ACLR skiers with time-from-surgery to reach non-injured control values by 2 years, but SSC function, such as JH and PP, remained depressed up to 5 years post-surgery ( p < 0.01), indicating impairments in SSC function. This highlights the importance of evaluating SSC performance capacity alongside vertical jump force-time asymmetries in female ACLR alpine skiers.

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          Generalized linear mixed models: a practical guide for ecology and evolution.

          How should ecologists and evolutionary biologists analyze nonnormal data that involve random effects? Nonnormal data such as counts or proportions often defy classical statistical procedures. Generalized linear mixed models (GLMMs) provide a more flexible approach for analyzing nonnormal data when random effects are present. The explosion of research on GLMMs in the last decade has generated considerable uncertainty for practitioners in ecology and evolution. Despite the availability of accurate techniques for estimating GLMM parameters in simple cases, complex GLMMs are challenging to fit and statistical inference such as hypothesis testing remains difficult. We review the use (and misuse) of GLMMs in ecology and evolution, discuss estimation and inference and summarize 'best-practice' data analysis procedures for scientists facing this challenge.
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            Monitoring Training Load to Understand Fatigue in Athletes

            Many athletes, coaches, and support staff are taking an increasingly scientific approach to both designing and monitoring training programs. Appropriate load monitoring can aid in determining whether an athlete is adapting to a training program and in minimizing the risk of developing non-functional overreaching, illness, and/or injury. In order to gain an understanding of the training load and its effect on the athlete, a number of potential markers are available for use. However, very few of these markers have strong scientific evidence supporting their use, and there is yet to be a single, definitive marker described in the literature. Research has investigated a number of external load quantifying and monitoring tools, such as power output measuring devices, time-motion analysis, as well as internal load unit measures, including perception of effort, heart rate, blood lactate, and training impulse. Dissociation between external and internal load units may reveal the state of fatigue of an athlete. Other monitoring tools used by high-performance programs include heart rate recovery, neuromuscular function, biochemical/hormonal/immunological assessments, questionnaires and diaries, psychomotor speed, and sleep quality and quantity. The monitoring approach taken with athletes may depend on whether the athlete is engaging in individual or team sport activity; however, the importance of individualization of load monitoring cannot be over emphasized. Detecting meaningful changes with scientific and statistical approaches can provide confidence and certainty when implementing change. Appropriate monitoring of training load can provide important information to athletes and coaches; however, monitoring systems should be intuitive, provide efficient data analysis and interpretation, and enable efficient reporting of simple, yet scientifically valid, feedback.
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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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                Author and article information

                Contributors
                Journal
                Front Sports Act Living
                Front Sports Act Living
                Front. Sports Act. Living
                Frontiers in Sports and Active Living
                Frontiers Media S.A.
                2624-9367
                31 March 2022
                2022
                : 4
                : 853701
                Affiliations
                [1] 1Canadian Sport Institute Calgary , Calgary, AB, Canada
                [2] 2Faculty of Kinesiology, The University of Calgary , Calgary, AB, Canada
                [3] 3School of Medical and Health Science, Centre for Human Performance, Edith Cowan University , Joondalup, WA, Australia
                [4] 4Department of Sports Science and Clinical Biomechanics, University of Southern Denmark , Odense, Denmark
                Author notes

                Edited by: Olivier Girard, University of Western Australia, Australia

                Reviewed by: Žiga Kozinc, University of Primorska, Slovenia; Chris J. Bishop, Middlesex University, United Kingdom; Jasper Verheul, University of Birmingham, United Kingdom

                *Correspondence: Matthew J. Jordan mjordan@ 123456ucalgary.ca

                This article was submitted to Elite Sports and Performance Enhancement, a section of the journal Frontiers in Sports and Active Living

                Article
                10.3389/fspor.2022.853701
                9008592
                35434617
                125fd94d-c26a-4670-baee-0cf7e1f6b15f
                Copyright © 2022 Jordan, Morris, Nimphius, Aagaard and Herzog.

                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
                : 12 January 2022
                : 03 February 2022
                Page count
                Figures: 6, Tables: 4, Equations: 2, References: 62, Pages: 13, Words: 9142
                Categories
                Sports and Active Living
                Original Research

                return to sport (rts),jump asymmetry,plyometric,knee injuries,athlete monitoring,countermovement jump,cmj

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