9 male professional boxers (age: 26 ± 4 years, height: 175 ± 5 cm, weight: 70 ± 5 kg body fat: 11 ± 3%, rectus femoris fat thickness: 4.6 ± 2.0 mm) were recruited for this study. Body composition remained unchanged throughout the study (p > 0.05). Each athlete held a current professional licence with the British Boxing Board of Control (bouts: 15 ± 5). Participants were excluded if there was a loss of training days over the last 3 months due to musculoskeletal injury or sanction from British Boxing Board of Control preventing the athlete from taking part in training or sparring. Participants were informed verbally and in writing on the risks and benefits of the study prior to signing informed consent form and was approved by Abertay University Research Ethics Committee (EMS5604). The study was carried out in line with the Declaration of Helsinki, except for the registration in a database.

Participants were instructed to adhere to their regular training routines and dietary habits throughout the study duration. They were also advised to avoid intense physical activities and alcohol consumption for 24 h prior to each laboratory visit. Additionally, participants were required to be in a fasted state, having abstained from food or drink intake for at least 4 h prior to their arrival at the Human Performance Laboratory.

The research protocol comprised three distinct laboratory visits: an initial familiarisation session, a control period assessment, and a final evaluation post a 3 week sprint training intervention (Fig. 1). During each visit, participants had near infrared spectroscopy (NIRS; Moxy Monitor, Fortiori Design LLC, USA) taped to the rectus femoris muscle of the left and right leg. The Moxy is a lightweight (48 g) and small (62 × 52 × 15 mm) device that uses continuous four wavelengths (680 nm, 720 nm, 760 nm, and 800 nm) reporting values of SmO2 in the form of a 0–100 percentage scale (Feldmann et al. 2019).

Occlusion protocol (right rectus femoris muscle), bike sprints (boxing gym, lode bike)

The moxy monitor was set to high speed, 0.5 s update with no smoothing. The Moxy monitor has been shown to be valid and reliable during exercise with a greater dynamic scale than the Portamon monitor (McManus et al. 2018; Feldmann et al. 2019); and has been used to explore muscle oxygenation during a wide range of sporting environment and training domains (Paquette et al. 2018; Perrey and Ferrari 2018). Participants then attached a heart rate monitor (Polar H10, Polar Electro, UK). All data was then collected via Bluetooth transmission to the VO2 master app (VO2 Master Health Sensors Inc, Canada).

All participants had height determined by stadiometer (Seca 264, Seca, UK) and body composition was determined by bioimpedance (Tanita MC-780, Tanita, Japan). The fat thickness on the rectus femoris muscle was determined by ultrasound (EagleView, Wellue, Diamond Bar, CA, USA) as a fat thickness of greater than 14 mm will impede NIRS signal (Feldmann et al. 2019).

The occlusion protocol involved the application of a blood pressure cuff to the upper thigh, connected to a rapid inflation system, and the leg and was rapidly inflated to > 300 mmHg. The protocol (Fig. 1) included three rapid occlusions at rest in the supine position, each lasting 15 s with 30 s between each occlusion (see S1 for SmO2 during occlusion). Cuff inflation reaching 300 mmHg in under 2 s. The time from cuff inflation to decline in rectus femoris muscle oxygenation was 0.319 ± 0.114 s. Participants then completed an incremental treadmill test to volitional exhaustion, starting at a speed of 10 km.h−1 with a 0% incline, increasing by 1 km.h−1 every minute until reaching 18 km.h−1, after which incline increased by 1% every minute. Two minutes post-treadmill run, participants underwent a series of 10 rapid occlusions (15 s each with 30 s between each occlusion) followed by a single 5 min occlusion whilst in a supine position.

Participants were then instructed to continue with their own training for the next 3 weeks after the first testing session before returning to the lab at the same time of day and repeating the testing procedure.

Following the second visit to the lab participants were given a familiarisation of 30 s effort against 7.5% body mass on the ergometer (LODE). Briefly, participants were instructed to bring the speed up to 85 rpm and then given a 3, 2, 1 countdown and instructed to cycle as fast as possible when hearing 1. Heart rate was recorded throughout, and athletes instructed that this is where the heart rate needs to be during the first sprint in subsequent training sessions. The intervention entailed participants performing 3 × 30 s maximal efforts with 60 s recovery on 3 days of the week for 3 weeks. Participants were instructed that ideally there should be 48 h between sprint sessions. Effort levels during these remote bike sprints were monitored using the Polar H10 heart rate data to ensure consistent exertion, with a self-reported adherence of 100% (Fig. 1).

Heart rate and SmO2 were exported from VO2 master as a 1 s average and processed in Python Jupyter Lab (version 3.3.2). A median average 5 s filter was applied to the data to smooth any movement artefacts (Buchheit and Laursen, 2011). SmO2 was used for analysis as it gives a better indication of skeletal muscle oxygenation when blood flow is not steady (Buchheit and Ufland 2011). Correcting for blood volume changes during occlusions to accurately assess changes due to oxygen consumption is required as blood volume changes can obscure the true NIRS signals reflecting muscular oxygen dynamics (Ryan et al. 2012). To effectively correct these signals, the blood volume change must be proportioned between oxygenated and deoxygenated blood components. This differentiation is important because it allows for a more precise interpretation of the NIRS data, isolating the oxygen consumption component from the confounding effects of blood volume fluctuations (Ryan et al. 2012).

$$\beta \left( t \right) = \frac Hb(t)} \right|}} Hb(t)} \right| + \left| \right|} \right)}}$$

Post-exercise occlusion a linear regression model was used for partial curve fitting to calculate the rate of muscle oxygen consumption (mVO2) during arterial occlusion. Curve fitting was expressed via a monoexponential curve fit to determine mitochondrial rate function (Ryan et al 2012). SmO2 during the treadmill test was analysed using linear curve fitting from the start of the final desaturation period to plateau before exhaustion (Fig. 1) with the slope representing rate of fast desaturation and rate of fast resaturation taken as the slope from the linear part of post-exercise recovery (Fig. 1). Area under the SmO2 post-treadmill recovery curve was calculated using the trapezoidal method and reflects oxygen availability during the recovery phase.

All data is presented as means ± standard deviation. Main and interaction effects are detailed, with post hoc pairwise analyses available in subsequent tables. Statistical analyses were conducted using Jamovi software (version 2.3.13). Normality checks were performed using the Shapiro–Wilks test, and all data were found to be normally distributed. Grubbs test for outliers was applied to the time to exhaustion and mitochondrial rate datasets, with an alpha value of 0.05. The G statistic for time to exhaustion was 1.959 and the critical value was 2.215, the G statistic for mitochondrial rate was 1.639 and the critical value was 2.651. Since the G statistic is lower than the critical value for both time to exhaustion and mitochondrial rate then there were no outliers within the dataset. All data was analysed using a repeated measures ANOVA for occlusions. Where there was a significant main effect then a least squares difference post hoc test was applied to determine where differences occurred. Significance was accepted at p < 0.05.