Andersen JL, Klitgaard H, Saltin B (1994) Myosin heavy chain isoforms in single fibres from m. vastus lateralis of sprinters: influence of training. Acta Physiol Scand 151(2):135–142. https://doi.org/10.1111/j.1748-1716.1994.tb09730.x

Article  CAS  PubMed  Google Scholar 

Baker JS, McCormick MC, Robergs RA (2010) Interaction among skeletal muscle metabolic energy systems during intense exercise. J Nutr Metab 2010:905612. https://doi.org/10.1155/2010/905612

Article  CAS  PubMed  PubMed Central  Google Scholar 

Beneke R, Hütler M, Jung M, Leithäuser RM (2005) Modeling the blood lactate kinetics at maximal short-term exercise conditions in children, adolescents, and adults. J Appl Physiol 99(2):499–504. https://doi.org/10.1152/japplphysiol.00062.2005

Article  CAS  PubMed  Google Scholar 

Beneke R, Jumah MD, Leithäuser RM (2007) Modelling the lactate response to short-term all out exercise. Dyn Med 6:10. https://doi.org/10.1186/1476-5918-6-10

Article  CAS  PubMed  PubMed Central  Google Scholar 

Bottinelli R, Canepari M, Pellegrino MA, Reggiani C (1996) Force-velocity properties of human skeletal muscle fibres: myosin heavy chain isoform and temperature dependence. J Physiol 495(2):573–586. https://doi.org/10.1113/jphysiol.1996.sp021617

Article  CAS  PubMed  PubMed Central  Google Scholar 

Bundle MW, Weyand PG (2012) Sprint exercise performance: does metabolic power matter? Exerc Sport Sci Rev 40(3):174–182. https://doi.org/10.1097/JES.0b013e318258e1c1

Article  PubMed  Google Scholar 

Burke ER, Fleck S, Dickson T (1981) Post-competition blood lactate concentrations in competitive track cyclists. Br J Sports Med 15(4):242–245. https://doi.org/10.1136/bjsm.15.4.242

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chung Y, Sharman R, Carlsen R, Unger SW, Larson D, Jue T (1998) Metabolic fluctuation during a muscle contraction cycle. Am J Physiol 274(3):C846–C852. https://doi.org/10.1152/ajpcell.1998.274.3.C846

Article  CAS  PubMed  Google Scholar 

Cohen, J (1988) Statistical power analysis for the behavioral sciences (2 edn). Erlbaum. http://www.loc.gov/catdir/enhancements/fy0731/88012110-d.html

Crowther GJ, Carey MF, Kemper WF, Conley KE (2002) Control of glycolysis in contracting skeletal muscle. I. Turning it on. Am J Physiol Endocrinol Metab 282(1):E67-73. https://doi.org/10.1152/ajpendo.2002.282.1.E67

Article  CAS  PubMed  Google Scholar 

di Prampero PE (1981) Energetics of muscular exercise. Rev Physiol Biochem Pharmacol 89:143–222. https://doi.org/10.1007/BFb0035266

Article  PubMed  Google Scholar 

Duffield R, Dawson B, Goodman C (2004) Energy system contribution to 100-m and 200-m track running events. J Sci Med Sport 7(3):302–313. https://doi.org/10.1016/s1440-2440(04)80025-2

Article  CAS  PubMed  Google Scholar 

Duffield R, Dawson B, Goodman C (2005) Energy system contribution to 400-metre and 800-metre track running. J Sports Sci 23(3):299–307. https://doi.org/10.1080/02640410410001730043

Article  PubMed  Google Scholar 

Dunst AK, Grüneberger R (2021) A novel approach of modelling and predicting track cycling sprint performance. Appl Sci 11(24):12098. https://doi.org/10.3390/app112412098

Article  CAS  Google Scholar 

Dunst AK, Grüneberger R, Holmberg H-C (2021) Modeling optimal cadence as a function of time during maximal sprint exercises can improve performance by elite track cyclists. Appl Sci 11(24):12105. https://doi.org/10.3390/app112412105

Article  CAS  Google Scholar 

Dunst AK, Hesse C, Feldmann A, Holmberg HC (2023a) A novel approach to determining the alactic time span in connection with assessment of the maximal rate of lactate accumulation in elite track cyclists. Int J Sports Physiol Perform 18(2):157–163. https://doi.org/10.1123/ijspp.2021-0464

Article  PubMed  Google Scholar 

Dunst AK, Manunzio C, Feldmann A, Hesse C (2023b) Applications of near-infrared spectroscopy in “anaerobic” diagnostics - SmO2 kinetics reflect PCr dephosphorylation and correlate with maximal lactate accumulation and maximal pedalling rate. Biol Sport 40(4):1019–1031. https://doi.org/10.5114/biolsport.2023.122481

Article  PubMed  PubMed Central  Google Scholar 

Dunst AK, Hesse C, Ueberschär O (2024) Understanding optimal cadence dynamics: a systematic analysis of the power-velocity relationship in track cyclists with increasing exercise intensity. Front Physiol 15:1343601. https://doi.org/10.3389/fphys.2024.1343601

Article  PubMed  PubMed Central  Google Scholar 

Esbjörnsson-Liljedahl M, Sundberg CJ, Norman B, Jansson E (1999) Metabolic response in type I and type II muscle fibers during a 30-s cycle sprint in men and women. J Appl Physiol 87(4):1326–1332. https://doi.org/10.1152/jappl.1999.87.4.1326

Article  PubMed  Google Scholar 

Essén-Gustavsson B, Henriksson J (1984) Enzyme levels in pools of microdissected human muscle fibres of identified type. Adaptive response to exercise. Acta Physiol Scand 120(4):505–515. https://doi.org/10.1111/j.1748-1716.1984.tb07414.xvxvc

Article  PubMed  Google Scholar 

Fujitsuka N, Yamamoto T, Ohkuwa T, Saito M, Miyamura M (1982) Peak blood lactate after short periods of maximal treadmill running. Eur J Appl Physiol 48(3):289–296. https://doi.org/10.1007/BF00430218

Article  CAS  Google Scholar 

Gastin PB (2001) Energy system interaction and relative contribution during maximal exercise. Sports Med 31(10):725–741. https://doi.org/10.2165/00007256-200131100-00003

Article  CAS  PubMed  Google Scholar 

Gupta S, Stanula A, Goswami A (2021) Peak blood lactate concentration and its arrival time following different track running events in under-20 male track athletes. Int J Sports Physiol Perform 16(11):1625–1633. https://doi.org/10.1123/ijspp.2020-0685

Article  PubMed  Google Scholar 

Gupta S, Stanula A, Goswami A, Adhikari A, Singh A, Ostrowski A (2022) Relationship between cycling speed and blood lactate level at various intervals following 1-km time trial cycling. J Kinesiol Exerc Sci 32(97):29–36. https://doi.org/10.5604/01.3001.0015.8589

Article  Google Scholar 

Haase R, Dunst AK, Nitzsche N (2024) The influence of pedaling frequency on blood lactate accumulation in cycling sprints. Int J Sports Med 45(8):608–615. https://doi.org/10.1055/a-2255-5254

Article  CAS  PubMed  Google Scholar 

Hansen EA, Andersen JL, Nielsen JS, Sjøgaard G (2002) Muscle fibre type, efficiency, and mechanical optima affect freely chosen pedal rate during cycling. Acta Physiol Scand 176(3):185–194. https://doi.org/10.1046/j.1365-201X.2002.01032.x

Article  CAS  PubMed  Google Scholar 

Hauser T, Adam J, Schulz H (2014) Comparison of calculated and experimental power in maximal lactate-steady state during cycling. Theor Biol Med Model 11:25. https://doi.org/10.1186/1742-4682-11-25

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hautier CA, Wouassi D, Arsac LM, Bitanga E, Thiriet P, Lacour JR (1994) Relationships between postcompetition blood lactate concentration and average running velocity over 100-m and 200-m races. Eur J Appl Physiol 68(6):508–513. https://doi.org/10.1007/BF00599521

Article  CAS  Google Scholar 

Hautier CA, Linossier MT, Belli A, Lacour JR, Arsac LM (1996) Optimal velocity for maximal power production in non-isokinetic cycling is related to muscle fibre type composition. Eur J Appl Physiol 74(1–2):114–118. https://doi.org/10.1007/BF00376503

Article  CAS  Google Scholar 

Heck H, Schulz H, Bartmus U (2003) Diagnostics of anaerobic power and capacity. Eur J Sport Sci 3(3):1–23. https://doi.org/10.1080/17461390300073302

Article  Google Scholar