Purpose: To investigate changes in self-reported physical fitness, performance, and side effects across the menstrual cycle (MC) phases among competitive endurance athletes and to describe their knowledge and communication with coaches about the MC. Methods: The responses of 140 participants (older than 18 y) competing in biathlon or cross-country skiing at the (inter)national level were analyzed. Data were collected via an online questionnaire addressing participants’ competitive level, training volume, MC history, physical fitness, and performance during the MC, MC-related side effects, and knowledge and communication with coaches about the MC and its effects on training and performance. Results: About 50% and 71% of participants reported improved and reduced fitness, respectively, during specific MC phases, while 42% and 49% reported improved and reduced performance, respectively. Most athletes reported their worst fitness (47%) and performance (30%) and the highest number of side effects during bleeding (P < .01; compared with all other phases). The phase following bleeding was considered the best phase for perceived fitness (24%, P < .01) and performance (18%, P < .01). Only 8% of participants reported having sufficient knowledge about the MC in relation to training, and 27% of participants communicated about it with their coach. Conclusions: A high proportion of athletes perceived distinct changes in fitness, performance, and side effects across the MC phases, with their worst perceived fitness and performance during the bleeding phase. Because most athletes indicate a lack of knowledge about the MC’s effect on training and performance and few communicate with coaches on the topic, the authors recommend that more time be devoted to educating athletes and coaches.

The maximal accumulated oxygen deficit (MAOD) method has been extensively, but unfortunately not very methodically, used; the procedure used to determine the MAOD varies considerably. Therefore, this review evaluates the effect of different numbers and durations of submaximal exercise bouts on the linear power output (PO)-oxygen uptake ((.)VO2) relationship and thus the MAOD. Changing the number and duration of the submaximal exercise bouts substantially influences the calculated MAOD when relatively long submaximal exercise bouts are used and no fixed value of the y-intercept is forced into the linear regression line. This is most likely due to non-linearity of the PO-(.)VO2 relationship for exercise intensities above the lactate threshold (LT). Non-linearity of the PO-(.)VO2 relationship is probably caused by the development of a slow component in (.)VO2 during submaximal exercise at intensities above the LT. Thus, it is important to standardize the number, duration and intensity of submaximal exercise bouts necessary to establish the PO-(.)VO2 relationship. Beyond changing the number and duration of the submaximal exercise bouts, the effect of different supramaximal exercise bouts on the calculated MAOD has been investigated. While it has become clear that different exercise protocols result in relatively similar values of the MAOD, a closer look at individual data suggests that it may be important to choose an exercise protocol that is representative of the athlete's event. The validity of the MAOD method was studied by different authors comparing the MAOD with metabolic measurements of anaerobic adenosine triphosphate (ATP) production. The main limitation with the metabolic measurements of anaerobic ATP production from muscle biopsy data is that the active muscle mass is unknown, which makes it hard to accurately study the validity of the MAOD method. From the studies that evaluated the reliability of the MAOD method it is clear that the MAOD method may not be a reliable measure of anaerobic capacity. From these findings it can be concluded that the MAOD method may have limitations as a valid and reliable measure of anaerobic capacity and needs to be further improved. We suggest the use of 10 x 4 minute submaximal exercise bouts and a fixed value of the y-intercept for the construction of the linear PO-(.)VO2 relationship, after which the MAOD can be determined during a supramaximal exercise protocol specific for the athlete's event. This method will lead to a more robust PO-(.)VO2 relationship and will therefore result in more valid and reliable results.

Optimizing physical performance is a major goal in current physiology. However, basic understanding of combining high sprint and endurance performance is currently lacking. This study identifies critical determinants of combined sprint and endurance performance using multiple regression analyses of physiologic determinants at different biologic levels. Cyclists, including 6 international sprint, 8 team pursuit, and 14 road cyclists, completed a Wingate test and 15-km time trial to obtain sprint and endurance performance results, respectively. Performance was normalized to lean body mass 2/3 to eliminate the influence of body size. Performance determinants were obtained from whole-body oxygen consumption, blood sampling, knee-extensor maximal force, muscle oxygenation, wholemuscle morphology, and muscle fiber histochemistry of musculus vastus lateralis. Normalized sprint performance was explained by percentage of fast-type fibers and muscle volume (R 2 = 0.65; P < 0.001) and normalized endurance performance by performance oxygen consumption (Vȯ 2 ), mean corpuscular hemoglobin concentration, and muscle oxygenation (R 2 = 0.92; P < 0.001). Combined sprint and endurance performance was explained by gross efficiency, performance Vȯ 2 , and likely by muscle volume and fascicle length (P = 0.056; P = 0.059). High performance Vȯ 2 related to a high oxidative capacity, high capillarization 3 myoglobin, and small physiologic cross-sectional area (R 2 = 0.67; P < 0.001). Results suggest that fascicle length and capillarization are important targets for training to optimize sprint and endurance performance simultaneously.-Van der Zwaard, S., van der Laarse, W. J., Weide, G., Bloemers, F. W., Hofmijster, M. J., Levels, K., Noordhof, D. A., de Koning, J. J., de Ruiter, C. J., Jaspers, R. T. Critical determinants of combined sprint and endurance performance: an integrative analysis from muscle fiber to the human body. FASEB J. 32, 2110FASEB J. 32, -2123FASEB J. 32, (2018 Many sports require a combination of sprint and endurance performance. During the past decades, physiologic determinants of physical performance have been the subject of intensive investigation (e.g., in cycling, 1-11). Studies focused on determinants of either sprint (e.g., 8-18) or endurance performance (e.g., 1-7, 19-23), even though physical performance is rarely a dichotomous function of only sprint or only endurance. Generally, a limited number of whole-body determinants of sprint or endurance performance have been studied, although there are many physical performance determinants at different levels (i.e., molecular, cellular, whole-muscle, organ, and whole ABBREVIATIONS: 3D, 3-dimensional; CAF, capillaries around the fiber; CD, capillary density; C/F, capillary-to-fiber ratio; FCSA, fiber cross-sectional area; fVȯ 2max , fiber maximal oxygen consumption; [Hb], hemoglobin concentration; Hct, hematocrit; [HHbMb], deoxygenated hemoglobin and myoglobin concentration; iSDH activity, spatially integrated SDH activity, SDH activity 3 FCSA; KE, k...

Rowers need to combine high sprint and endurance capacities. Muscle morphology largely explains muscle power generating capacity, however, little is known on how muscle morphology relates to rowing performance measures. The aim was to determine how muscle morphology of the vastus lateralis relates to rowing ergometer performance, sprint and endurance capacity of Olympic rowers. Eighteen rowers (12♂, 6♀, who competed at 2016 Olympics) performed an incremental rowing test to obtain maximal oxygen consumption, reflecting endurance capacity. Sprint capacity was assessed by Wingate cycling peak power. M. vastus lateralis morphology (volume, physiological cross-sectional area, fascicle length and pennation angle) was derived from 3-dimensional ultrasound imaging. Thirteen rowers (7♂, 6♀) completed a 2000-m rowing ergometer time trial. Muscle volume largely explained variance in 2000-m rowing performance (R = 0.85), maximal oxygen consumption (R = 0.65), and Wingate peak power (R = 0.82). When normalized for differences in body size, maximal oxygen consumption and Wingate peak power were negatively related in males (r = -0.94). Fascicle length, not physiological cross-sectional area, attributed to normalized peak power. In conclusion, vastus lateralis volume largely explains variance in rowing ergometer performance, sprint and endurance capacity. For a high normalized sprint capacity, athletes may benefit from long fascicles rather than a large physiological cross-sectional area.

Anaerobic capacity (AnC) can be estimated by subtracting VO (2) consumed from VO (2) demand, which can be estimated from multiple submaximal exercise bouts or by gross efficiency (GE), requiring one submaximal bout. This study compares AnC using the MAOD and GE method. The precision of estimated VO (2) demand and AnC, determined by MAOD using 3 power output - VO (2) regressions, based on VO (2) from min 8-10 (10 - Y), during min 4 without (4 - Y) and with forced y-intercept (4+Y), and from GE was evaluated by the 95% confidence interval (CI). Well-trained males (n=15) performed submaximal exercise tests to establish VO (2) demand with the MAOD and GE method. To determine AnC subjects completed a constant power output trial. The 3 MAOD procedures and GE method had no significant difference for VO (2) demand and AnC. The 4+Y MAOD procedure and GE method resulted in a smaller 95% CI of VO (2) demand and AnC than the 10 - Y ( P<0.05; P<0.01) and 4 - Y ( P<0.001; P<0.01) MAOD procedures. Therefore, the 4+Y MAOD procedure and GE method are preferred for estimating AnC, but as individual differences exist, they cannot be used interchangeably.

V̇o2 max during whole body exercise is presumably constrained by oxygen delivery to mitochondria rather than by mitochondria's ability to consume oxygen. Humans and animals have been reported to exploit only 60-80% of their mitochondrial oxidative capacity at maximal oxygen uptake (V̇o2 max). However, ex vivo quantification of mitochondrial overcapacity is complicated by isolation or permeabilization procedures. An alternative method for estimating mitochondrial oxidative capacity is via enzyme histochemical quantification of succinate dehydrogenase (SDH) activity. We determined to what extent V̇o2 max attained during cycling exercise differs from mitochondrial oxidative capacity predicted from SDH activity of vastus lateralis muscle in chronic heart failure patients, healthy controls, and cyclists. V̇o2 max was assessed in 20 healthy subjects and 28 cyclists, and SDH activity was determined from biopsy cryosections of vastus lateralis using quantitative histochemistry. Similar data from our laboratory of 14 chronic heart failure patients and 6 controls were included. Mitochondrial oxidative capacity was predicted from SDH activity using estimated skeletal muscle mass and the relationship between ex vivo fiber V̇o2 max and SDH activity of isolated single muscle fibers and myocardial trabecula under hyperoxic conditions. Mitochondrial oxidative capacity predicted from SDH activity was related (r(2) = 0.89, P < 0.001) to V̇o2 max measured during cycling in subjects with V̇o2 max ranging from 9.8 to 79.0 ml·kg(-1)·min(-1) V̇o2 max measured during cycling was on average 90 ± 14% of mitochondrial oxidative capacity. We conclude that human V̇o2 max is related to mitochondrial oxidative capacity predicted from skeletal muscle SDH activity. Mitochondrial oxidative capacity is likely marginally limited by oxygen supply to mitochondria.

Anaerobic capacity/anaerobically attributable power is an important parameter for athletic performance, not only for short high-intensity activities but also for breakaway efforts and end spurts during endurance events. Unlike aerobic capacity, anaerobic capacity cannot be easily quantified. The 3 most commonly used methodologies to quantify anaerobic capacity are the maximal accumulated oxygen deficit method, the critical power concept, and the gross efficiency method. This review describes these methods, evaluates if they result in similar estimates of anaerobic capacity, and highlights how anaerobic capacity is used during sporting activities. All 3 methods have their own strengths and weaknesses and result in more or less similar estimates of anaerobic capacity but cannot be used interchangeably. The method of choice depends on the research question or practical goal.

GE decreases during time-trial exercise. Unfortunately, the cause of the decrease remains uncertain. Future modeling studies should consider using a declining instead of a constant GE. In sport situations, the declining GE has to be taken into account when selecting a pacing strategy.