Case Report: Load, Intensity, and Performance Characteristics in Multiple Grand Tours

Introduction The aim of this study was to present the load, intensity, and performance characteristics of a general classification (GC) contender during multiple grand tours (GTs). This study also investigated which factors influence climbing performance. Methods Power output (PO) data were collected from a GC contender from the Vuelta a España 2015, the Giro d'Italia 2017, the Giro d'Italia 2018, and the Tour de France 2018. Load (e.g., Training Stress Score and kJ spent) and intensity in five PO zones were quantified. One-way ANOVA was used to identify differences between the GTs. Furthermore, performance during the four GTs was quantified based on maximal mean PO (W·kg-1) over different durations and by the relative PO (W·kg-1) on the key mountains in the GTs. Stepwise multiple regression analysis was used to identify which factors influence relative PO on the key mountains. Results No significant differences were found between load and intensity characteristics between the four GTs, with the exception that during the Giro d'Italia 2018, a significantly lower absolute time was spent in PO zone 5 (P = 0.005) compared with the other three GTs. The average relative PO on the key mountains (n = 33) was 5.9 ± 0.6 W·kg-1 and was negatively influenced by the duration of the climb and the total elevation gain before the key mountain, whereas the gradient of the mountain had a positive effect on relative PO. Conclusions The physiological load imposed on a GC contender did not differ between multiple GTs. Climbing performance was influenced by short-term fatigue induced by previous altitude meters in the stage and the duration and gradient of the mountain

Towards Machine Learning on data from Professional Cyclists

Professional sports are developing towards increasingly scientific training methods with increasing amounts of data being collected from laboratory tests, training sessions and competitions. In cycling, it is standard to equip bicycles with small computers recording data from sensors such as power-meters, in addition to heart-rate, speed, altitude etc. Recently, machine learning techniques have provided huge success in a wide variety of areas where large amounts of data (big data) is available. In this paper, we perform a pilot experiment on machine learning to model physical response in elite cyclists. As a first experiment, we show that it is possible to train a LSTM machine learning algorithm to predict the heart-rate response of a cyclist during a training session. This work is a promising first step towards developing more elaborate models based on big data and machine learning to capture performance aspects of athletes.Comment: Accepted for the 12th World Congress on Performance Analysis of Sports, Opatija, Croatia, 201

In Vitro Enhancement of Respiratory Syncytial Virus Infection by Maternal Antibodies Does Not Explain Disease Severity in Infants.

Respiratory syncytial virus (RSV) is the leading cause of severe respiratory illness in infants. At this young age, infants typically depend on maternally transferred antibodies (matAbs) and their innate immune system for protection against infections. RSV-specific matAbs are thought to protect from severe illness, yet severe RSV disease occurs mainly below 6 months of age, when neutralizing matAb levels are present. To investigate this discrepancy, we asked if disease severity is related to antibody properties other than neutralization. Some antibody effector functions are mediated via their Fc binding region. However, it has been shown that this binding may lead to antibody-dependent enhancement (ADE) of infection or reduction of neutralization, both possibly leading to more disease. In this study, we first showed that high levels of ADE of RSV infection occur in monocytic THP-1 cells in the presence of RSV antibodies and that neutralization by these antibodies was reduced in Vero cells when they were transduced with Fc gamma receptors. We then demonstrated that antibodies from cotton rats with formalin-inactivated (FI)-RSV-induced pulmonary pathology were capable of causing ADE. Human matAbs also caused ADE and were less neutralizing in vitro in cells that carry Fc receptors. However, these effects were unrelated to disease severity because they were seen both in uninfected controls and in infants hospitalized with different levels of RSV disease severity. We conclude that ADE and reduction of neutralization are unlikely to be involved in RSV disease in infants with neutralizing matAbs.IMPORTANCE It is unclear why severity of RSV disease peaks at the age when infants have neutralizing levels of maternal antibodies. Additionally, the exact reason for FI-RSV-induced enhanced disease, as seen in the 1960s vaccine trials, is still unclear. We hypothesized that antibodies present under either of these conditions could contribute to disease severity. Antibodies can have effects that may lead to more disease instead of protection. We investigated two of those effects: antibody-dependent enhancement of infection (ADE) and neutralization reduction. We show that ADE occurs in vitro with antibodies from FI-RSV-immunized RSV-infected cotton rats. Moreover, passively acquired maternal antibodies from infants had the capacity to induce ADE and reduction of neutralization. However, no clear association with disease severity was seen, ruling out that these properties explain disease in the presence of maternal antibodies. Our data contribute to a better understanding of the impact of antibodies on RSV disease in infants

Comparison of rating of perceived exertion scales during incremental and interval exercise

The Rating of Perceived Exertion (RPE) is an important measure of exercise intensity, which is useful both as a primary and adjunctive method of exercise prescription. However, there are multiple variants of the Borg RPE scale, primarily the Borg 6-20 RPE scale (BORG-RPE) and the Borg Category-Ratio-10 scale (BORG-CR10). There are inadequate data available to address the comparability and interchangeability of these two widely used scales. Well-trained non-athletes performed two increment cycle tests, with each scale used in a random sequence. Subjects also performed interval sessions at three intensities (50, 75 and 85% of peak power output) with each scale used in a random sequence. There were very large correlations during the incremental exercise between the conventional physiological measures (% heart rate reserve – r=0.89 & r=.87); and %VO2reserve (r=.88 & r=.90) and RPE measured by either the BORG-RPE or the BORGCR10, respectively. This pattern was also evident during the interval exercise (% heart rate reserve (r=.85 & r=.84; and blood lactate concentration – r=.74 & r=.78) and RPE measured by either the BORG-RPE or the BORG-CR10, respectively. The relationship between RPE measured by the BORG-RPE and the BORGCR10 was large and best described by a non-linear relationship for both the incremental (R2=89) and the interval (R2=.89) exercise. The incremental and interval curves were virtually overlapping. We concluded that the two most popular versions of the RPE scale, BORG-RPE and BORG-CR10, were both highly related to the conventional physiological measures and very strongly related to each other, with an easily described conversion

Demands of professional cycling races:Influence of race category and result

This study analyses the influence of race category and result on the demands of professional cycling races. In total, 2920 race files were collected from 20 male professional cyclists, within a variety of race categories: Single-day (1.WT) and multi-day (2.WT) World Tour races, single-day (1.HC) and multi-day (2.HC) Hors Catégorie races and single-day (1.1) and multi-day (2.1) category 1 races. Additionally, the five cycling “monuments” were analysed separately. Maximal mean power outputs (MMP) were measured across a broad range of durations. Volume and load were large to very largely (d = 1.30–4.80) higher in monuments compared to other single-day race categories. Trivial to small differences were observed for most intensity measures between different single-day race categories, with only RPE and sRPE·km−1 being moderately (d = 0.70–1.50) higher in the monuments. Distance and duration were small to moderately (d = 0.20–0.80) higher in 2.WT races compared to 2.HC and 2.1 multi-day race categories with only small differences in terms of load and intensity. Generally, higher ranked races (i.e. Monuments, 2.WT and GT) tend to present with lower shorter-duration MMPs (e.g. 5–120 sec) compared to races of “lower rank” (with less differences and/or mixed results being present over longer durations), potentially caused by a “blunting” effect of the higher race duration and load of higher ranked races on short duration MMPs. MMP were small to largely higher over shorter durations (<5 min) for a top-10 result compared to no top-10, within the same category

Training characteristics of male and female professional road cyclists:A 4-year retrospective analysis

Purpose: To describe the training intensity and load characteristics of professional cyclists using a 4-year retrospective analysis. Particularly, this study aimed to describe the differences in training characteristics between men and women professional cyclists. Method: For 4 consecutive years, training data were collected from 20 male and 10 female professional cyclists. From those training sessions, heart rate, rating of perceived exertion, and power output (PO) were analyzed. Training intensity distribution as time spent in different heart rate and PO zones was quantified. Training load was calculated using different metrics such as Training Stress Score, training impulse, and session rating of perceived exertion. Standardized effect size is reported as Cohen's d. Results: Small to large higher values were observed for distance, duration, kilojoules spent, and (relative) mean PO in men's training (d = 0.44-1.98). Furthermore, men spent more time in low-intensity zones (ie, zones 1 and 2) compared with women. Trivial differences in training load (ie, Training Stress Score and training impulse) were observed between men's and women's training (d = 0.07-0.12). However, load values expressed per kilometer were moderately (d = 0.67-0.76) higher in women compared with men's training. Conclusions: Substantial differences in training characteristics exist between male and female professional cyclists. Particularly, it seems that female professional cyclists compensate their lower training volume, with a higher training intensity, in comparison with male professional cyclists

Intensity and load characteristics of professional road cycling: Differences between men’s and women’s races

Purpose: To provide a retrospective analysis of a large competition database describing the intensity and load demands of professional road-cycling races, highlighting the differences between men’s and women’s races. Methods: In total, 20 male and 10 female professional cyclists participated in this study. During 4 consecutive years, heart rate, rating of perceived exertion, and power-output data were collected during both men’s (n = 3024) and women’s (n = 667) professional races. Intensity distribution in 5 heart-rate zones was quantified. Competition load was calculated using different metrics, including Training Stress Score (TSS), training impulse (TRIMP), and session rating of perceived exertion. Standardized effect size is reported as Cohen d. Results: Large to very large higher values (d = 1.36–2.86) were observed for distance, duration, total work (in kilojoules), and mean power output in men’s races. Time spent in high-intensity heart-rate zones (ie, zones 4 and 5) was largely higher in women’s races (d = 1.38–1.55) than in men’s races. Small higher loads were observed in men’s races quantified using TSS (d = 0.53) and TRIMP (d = 0.23). However, load metrics expressed per kilometer were large to very largely higher in women’s races for TSS·km –1 (d = 1.50) and TRIMP·km –1 (d = 2.31). Conclusions: Volume and absolute load are higher in men’s races, whereas intensity and time spent in high-intensity zones is higher in women’s races. Coaches and practitioners should consider these differences in demands in the preparation of professional road cyclists

The influence of exercise intensity on the association between kilojoules spent and various training loads in professional cycling

Purpose: A valid measure for training load (TL) is an important tool for cyclists, trainers, and sport scientists involved in professional cycling. The aim of this study was to explore the influence of exercise intensity on the association between kilojoules (kJ) spent and different measures of TL to arrive at valid measures of TL. Methods: Four years of field data were collected from 21 cyclists of a professional cycling team, including 11,716 training and race sessions. kJ spent was obtained from power output measurements, and others TLs were calculated based on the session rating of perceived exertion (sRPE), heart rate (Lucia training impulse [luTRIMP]), and power output (training stress score [TSS]). Exercise intensity was expressed by the intensity factor (IF). To study the effect of exercise intensity on the association between kJ spent and various other TLs (sRPE, luTRIMP, and TSS), data from low- and high-intensity sessions were subjected to regression analyses using generalized estimating equations. Results: This study shows that the IF is significantly different for training and race sessions (0.59 [0.03] vs 0.73 [0.03]). Significant regression coefficients show that kJ spent is a good predictor of sRPE, and luTRIMP, as well as TSS. However, IF does not influence the associations between kJ spent and sRPE and luTRIMP, while the association with TSS is different when sessions are done with low or high IF. Conclusion: It seems that the TSS reacts differently to exercise intensity than sRPE and luTRIMP. A possible explanation could be the quadratic relation between IF and TSS