Wim Derave’s research while affiliated with Ghent University and other places

Purpose : Identifying the determinants of performance is fundamental to talent identification and individualizing training prescription. Consequently, the aim of this study was to determine whether estimated muscle typology is associated with the key mechanical characteristics of track sprint cycling. Methods : Sixteen world-class and elite track cyclists (n = 7 female) completed a laboratory session wherein torque–cadence and power–cadence profiles were constructed to determine maximal power output (P max ), optimal cadence ( F opt ), and maximal cadence ( F max ), and fatigue rate per pedal stroke was determined during a 15-second maximal sprint at F opt . Muscle typology was estimated by measuring carnosine content via proton magnetic resonance spectroscopy in the gastrocnemius and soleus. Results : Using partial correlation analysis to account for sex, greater muscle carnosine content (ie, greater estimated proportion of type II fibers) was associated with a greater P max ( r = .68, P = .007), F max ( r = .77, P = .0014), F opt ( r = .61, P = .0196), and absolute fatigue rate (W·stroke ⁻¹ ; r = −.55, P = .0418) but not relative fatigue rate (%peak power·stroke ⁻¹ ; r = −.33, P = .246). Conclusions : The findings from this study substantiate the mechanical differences in muscle-fiber types derived from single muscle-fiber studies and highlight the importance of estimated muscle typology for sprint cycling performance.

Running economy is an important determinant of endurance running performance, yet insights into characteristics contributing to its inter‐individual variability remain limited. Although slow‐twitch muscle fibers are more energy‐efficient than fast‐twitch fibers during the (near‐)isometric contractions common during submaximal running, current literature lacks a consensus on whether a relationship between muscle fiber–type distribution and running economy exists. This study aims to resolve the ongoing debate by addressing potential confounding factors often overlooked in prior research, such as the effect of different running speeds, the homogeneity of investigated groups, and the potential impact of the adopted running gait. We selected two groups with predetermined distinct muscle fiber–type distribution in their triceps surae muscle by measurement of carnosine via ¹H‐MRS, one predominantly slow (ST; n = 11; carnosine z‐score = −1.31) and the other predominantly fast (FT; n = 10; z‐score = 0.83). Across a range of running speeds (2–4 m/s), we measured running economy (W/kg) through indirect calorimetry, along with running kinematics, kinetics and muscle activity of the lower limb. The ST‐group exhibited, on average, 7.8% better running economy than the FT‐group (p = 0.01) and this difference was consistent across speeds. Both groups demonstrated almost identical kinematics, kinetics, and muscle activity patterns across submaximal running speeds. Overall, our findings indicate that distinct muscle fiber–type distribution explains some of the observed variability in running economy, for which a predominance of energy‐efficient slow‐twitch fibers appear beneficial. In contrast, muscle fiber–type distribution does not affect running gait substantially.

Human skeletal muscle fiber type composition varies greatly along the muscle, so one biopsy may not accurately represent the whole muscle. Recommendations on the number of biopsies and fiber counts using immunohistochemistry and whether these findings can be extrapolated to other muscles are lacking. We assessed fiber type composition in the vastus lateralis and gastrocnemius medialis muscles of 40 individuals. Per muscle, we took four biopsy samples from one incision, collecting two samples each from a proximally and distally directed needle. Based on another dataset involving 10 vastus lateralis biopsies per participant (N=7), we calculated 95% limits of agreement for subsets of biopsies and fiber counts compared to the 10-biopsy average. Average absolute differences in type I fiber proportions between proximal and distal, and between within-needle samples were 6.9 and 4.5 percentage points in the vastus lateralis, and 5.5 and 4.4 percentage points in the gastrocnemius medialis, respectively. The 95% limits of agreement narrowed to ±10 percentage points when 200 fibers from at least three biopsies were analyzed, with minimal improvements with greater fiber counts. Type I fiber proportions in the vastus lateralis and gastrocnemius medialis showed a moderate positive association (r²=0.22; p=0.006; at least 200 fibers in each of three to four samples per muscle). In conclusion, three biopsies with a minimum of 200 counted fibers are required to estimate vastus lateralis fiber type composition within ±10 percentage points. Even when using these standards, researchers should be cautious when extrapolating muscle fiber type proportions from one muscle to another.

The heterogeneous fiber type composition of skeletal muscle makes it challenging to decipher the molecular signaling events driving the health- and performance benefits of exercise. We developed an optimized workflow for transcriptional profiling of individual human muscle fibers before, immediately after, and after three hours of recovery from high-intensity interval cycling exercise. From a transcriptional point-of-view, we observe that there is no dichotomy in fiber activation, that could refer to a fiber being recruited or non-recruited. Rather, the activation pattern displays a continuum with a more uniform response within fast versus slow fibers during the recovery from exercise. The transcriptome-wide response immediately after exercise is characterized by some distinct signatures for slow versus fast fibers, although the most exercise-responsive genes are common between the two fiber types. The temporal transcriptional waves further converge the gene signatures of both fiber types towards a more similar profile during the recovery from exercise. Furthermore, a large heterogeneity among all resting and exercised fibers was observed, with the principal drivers being independent of a slow/fast typology. This profound heterogeneity extends to distinct exercise responses of fibers beyond a classification based on myosin heavy chains. Collectively, our single-fiber methodological approach points to a substantial between-fiber diversity in muscle fiber responses to high-intensity interval exercise.

Purpose : To gather information on practices and perceptions of high-performance experts regarding their athletes’ muscle fiber-type composition (MFTC) and its estimation. Methods : A questionnaire on the noninvasive versus invasive estimation of MFTC was completed by 446 experts including coaches and sport-science/sports-medicine staff. Moreover, the perceived importance of MFTC for training and performance optimization was assessed. Differences between sport types (individual and team sports) were analyzed using chi-square tests. Results : Forty percent of the experts implemented MFTC assessment in pursuit of performance optimization, while 50% did not know their athletes’ MFTC but expressed a desire to implement it if they would be able to assess MFTC. Ten percent did not perceive value in MFTC assessment. Only 18% of experts believed that their athletes would undergo a muscle biopsy, leading to the adoption of alternative noninvasive techniques. Experts primarily relied on their experience to estimate MFTC (65%), with experts working in individual sports using their experience more frequently than those working in team sports (68% vs 51%; P = .009). Jump tests emerged as the second-most commonly employed method for estimating MFTC (56%). When only considering experts who are currently using MFTC, 87% use MFTC to individualize training volume and 84% to individualize training intensity. Conclusions : Experts value MFTC assessment primarily to individualize training but mainly rely on noninvasive methods to estimate MFTC. Some of these methods lack scientific validity, suggesting a continuing need for education and further research in this area.

Purpose Apnea duration is dependent on three factors: oxygen storage, oxygen consumption, hypoxia and hypercapnia tolerance. While current literature focuses on maximal apneas to improve apnea duration, apnea trained individuals use timed-repeated submaximal apneas, called “O2 and CO2 tables”. These tables claim to accommodate the body to cope with hypoxia and hypercapnia, respectively. The aim of this study was twofold. First, to investigate the determinants of maximal apnea duration in apnea novices. Second, to compare physiologic responses to maximal apneas, O2 and CO2 tables. Methods After medical screening, lung function test and hemoglobin mass measurement, twenty-eight apnea novices performed three apnea protocols in random order: maximal apneas, O2 table and CO2 table. During apnea, peripheral oxygen saturation (SpO2), heart rate (HR), muscle (mTOI) and cerebral (cTOI) tissue oxygenation index were measured continuously. End-tidal carbon dioxide (EtCO2) was measured before and after apneas. Results Larger lung volumes, higher resting cTOI and lower resting EtCO2 levels correlated with longer apnea durations. Maximal apneas induced greater decreases in SpO2 (− 16%) and cTOI (− 13%) than O2 (− 8%; − 8%) and CO2 tables (− 6%; − 6%), whereas changes in EtCO2, HR and mTOI did not differ between protocols. Conclusion These results suggest that, in apnea novices, O2 and CO2 tables did not induce a more profound hypoxia and hypercapnia, but a similar reduction in oxygen consumption than maximal apneas. Therefore, apnea novices should mainly focus on maximal apneas to improve hypoxia and hypercapnia tolerance. The use of specific lung training protocols can help to increase oxygen storage capacity.

Background Chronic obstructive pulmonary disease (COPD) is a disease characterized by skeletal muscle dysfunction. A spatial relationship exists between satellite cells and muscle fiber capillaries, which has been suggested to be of major importance for satellite cell function. In the present study we compared the spatial relationship between satellite cells and capillaries in patients with COPD and age-matched healthy older adults. Methods Muscle biopsies were obtained from the vastus lateralis of n=18 patients with COPD (8f/10 m, 66±5 y, mild to severe airflow obstruction) and n=18 age-, gender- and BMI-matched healthy control adults (8f/10 m, 68±5 y). Immunohistochemistry was used to assess type I/II muscle fiber size, distribution, myonuclear content, satellite cell number, and fiber capillarization. In addition, type I/II muscle fiber satellite cell distance to its nearest capillary was assessed. Results The percentage of type II muscle fibers was significantly greater in patients with COPD (62±10%) compared with control (50±12%, p<0.05). Muscle fiber capillarization was significantly lower in patients with COPD compared with controls (p<0.05). Whereas satellite cell content was not different between groups, type I and type II satellite cell distance to its nearest capillary was significantly greater in patients with COPD (type I: 21.3±4.8 and type II: 26.7±9.3 µm) compared with controls (type I: 16.1±3.5 and type II: 22.7±5.8 µm; p<0.05). Conclusion Satellite cells are located at a greater distance from their nearest capillary in patients with COPD compared with age-matched controls. This increased distance could play a role in impaired satellite cell function in patients with COPD.

Multiple intramuscular variables have been proposed to explain the high variability in resistance training induced muscle hypertrophy across humans. This study investigated if muscular androgen receptor (AR), estrogen receptor α (ERα) and β (ERβ) content and fiber capillarization are associated with fiber and whole‐muscle hypertrophy after chronic resistance training. Male (n = 11) and female (n = 10) resistance training novices (22.1 ± 2.2 years) trained their knee extensors 3×/week for 10 weeks. Vastus lateralis biopsies were taken at baseline and post the training period to determine changes in fiber type specific cross‐sectional area (CSA) and fiber capillarization by immunohistochemistry and, intramuscular AR, ERα and ERβ content by Western blotting. Vastus lateralis volume was quantified by MRI‐based 3D segmentation. Vastus lateralis muscle volume significantly increased over the training period (+7.22%; range: −1.82 to +18.8%, p < 0.0001) but no changes occurred in all fiber (+1.64%; range: −21 to +34%, p = 0.869), type I fiber (+1.33%; range: −24 to +41%, p = 0.952) and type II fiber CSA (+2.19%; range: −23 to +29%, p = 0.838). However, wide inter‐individual ranges were found. Resistance training increased the protein expression of ERα but not ERβ and AR, and the increase in ERα content was positively related to changes in fiber CSA. Only for the type II fibers, the baseline capillary‐to‐fiber‐perimeter index was positively related to type II fiber hypertrophy but not to whole muscle responsiveness. In conclusion, an upregulation of ERα content and an adequate initial fiber capillarization may be contributing factors implicated in muscle fiber hypertrophy responsiveness after chronic resistance training.