Training to failure vs not-to-failure with progressive volume reduction: neuromuscular and metabolic responses in untrained individuals

Training to failure vs not-to-failure with progressive volume reduction: neuromuscular and metabolic responses in untrained individuals | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Training to failure vs not-to-failure with progressive volume reduction: neuromuscular and metabolic responses in untrained individuals Hiago L. R. Souza, João M. G. Flora, Giovanna Pernetti, Igor J. S. Rodrigues, and 16 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8387060/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Resistance training to failure (RT F ) acutely increases neuromuscular and metabolic demands but also induces fatigue that may compromise subsequent training stimuli. Small reductions in volume at the same intensity, while avoiding failure, may attenuate fatigue while preserving training stimuli. Therefore, this study compared the acute effects of RT F and non-failure resistance training (RT NF ) during knee extension exercise. Eleven untrained men completed five RT NF conditions, each involving an individualized reduction ranging from 10–50% relative to number of repetitions performed during RT F . Outcomes included maximum voluntary isometric contraction (MVIC), electromyography (EMG), muscle swelling of the rectus femoris (RF) and vastus lateralis (VL), blood lactate concentration, and perceived exertion (RPE). RT F elicited greater increases in muscle cross-sectional area of both RF and VL (p < 0.01) compared with all RT NF conditions. EMG amplitude was higher in RT F than in the 30–50% reduction conditions (p = 0.01 for VL and RF), while MVIC (p = 0.02) and EMG frequency differed across protocols (p = 0.02 for RF; p = 0.03 for VL). Additionally, lactate and RPE (p < 0.01) responses were highest following RT F . In summary, RT F maximizes muscle swelling and metabolic stress, whereas performing repetitions up to 20% short of failure provides a comparable neuromuscular stimulus, while minimizing metabolic stress. Health sciences/Health care Biological sciences/Neuroscience Biological sciences/Physiology Electromyography Muscle Fatigue Muscle Strength Ultrasonography Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION Resistance training (RT) is an effective strategy for promoting muscle hypertrophy and strength gains, with mechanical tension and metabolic stress serving as the main mediating factors for these adaptations 1 . RT performed to muscle failure (RT F ) has been proposed to maximize these adaptations, potentially due to greater motor unit recruitment and metabolite accumulation compared to RT not performed to failure (RT NF ) 2 , 3 . Once RT F allows a higher number of repetitions to be completed, it is likely that this strategy induces greater acute muscle swelling (commonly referred to as the “muscle pump”) compared to RT NF . This interpretation aligns with previous finding 4 , which reinforce the idea that, at a given intensity, performing more repetitions in RT F leads to elevation of metabolic stress, evidenced by biological markers such as ammonia, creatine kinase (CK), and elevated blood lactate concentrations 2 , 5 . Hirono, et al. 6 reported that greater acute muscle swelling was associated with greater chronic muscle hypertrophy, suggesting that acute investigations can provide valuable insights into short-term physiological responses that may contribute to long-term adaptations. Moreover, muscle swelling and hypertrophy are not uniform along the muscle length 7 , which could result from mechanical stress that varies across the range of motion 8 . Recent research has shown that hypertrophy gains tend to be similar between RT F and RT NF when RT volume is equalized or when only small reductions in volume are implemented using repetition in reserve strategy 9 , 10 . However, the similarity in this response may indicate that there is a threshold of metabolic stress and neuromuscular demand beyond which additional stimuli does not lead to significant improvements and may instead increase muscle damage and prolong recovery time. Supporting this hypothesis, a meta-analysis conducted by Vieira, et al. 5 reported greater cellular damage and higher CK levels 48 hours after RT F , indicating the need for longer recovery periods between RT F sessions. Thus, determining the appropriate training stimulus becomes essential to maximize neuromuscular adaptation while minimizing unnecessary muscle damage. Overall improvements in physical function after RT intervention have been associated with increases in neuromuscular activation (i.e., motor unit recruitment) and/or muscle strength. RT F has traditionally been associated with greater motor unit recruitment 2 , 11 , this assumption shall be questioned. Muscle motor units vary substantially in fiber size, location, and firing rate, and these properties influence the electromyographic (EMG) signal without necessarily reflecting proportional motor unit recruitment 12 , 13 . Furthermore, similar EMG responses have been observed between RT F and RT NF when volume was equalized, in both trained 14 and untrained individuals 9 , indicating that there may be no need to train to failure in order to achieve maximal neuromuscular activation. Furthermore, several studies have reported similar adaptations in maximal dynamic strength (1RM) and maximal voluntary isometric contraction (MVIC) between RT F and RT NF conditions 9 , 14 . In contrast, the fatigue induced by RT F may acutely compromise maximal strength performance (Pareja-Blanco et al., 2016; Grgic et al., 2022), which is not always desirable. Beyond maximal strength performance after RT, a complementary approach is to examining exercise-induced fatigue by analyzing EMG frequency 15 . Previous studies indicate that the closer an individual is to failure, the greater the reduction in EMG frequency 16 . This suggests that approaching failure imposes progressively greater neural challenges. Despite the known physiological responses to training to failure, it remains unclear what is the minimal reduction in repetitions, relative to failure, that still elicits meaningful neuromuscular and metabolic responses While RT F can enhance metabolic and neuromuscular stimuli, RT NF can produce comparable outcomes when variables such as volume and intensity are equivalent. This is important, given that training status can modulate physiological responses to both RT F and RT NF 17 . Therefore, a need exists in examining the magnitude of responses elicited by these training protocols in untraining populations. The choice of untrained populations is crucial because their responses provide a clearer, 'noise-free' signal of the fundamental physiological effect of the training protocol itself, free from the confounding adaptations of prior training. Therefore, the aim of this study is to examine the acute responses of muscle swelling, EMG in both the frequency and time domains, blood lactate concentrations, MVIC and rate of perceived exertion (RPE) to varying reductions in repetitions (10% to 50%) relative to maximal repetition to failure. We hypothesize that the percentage reduction in training volume relative to failure is associated with a commensurate reduction in neuromuscular and metabolic responses. METHODS Participants A priori sample estimation (G*Power 3.1.9.2, Heinrich-Heine Universität Düsseldorf, Düsseldorf, Germany). This analysis assumed a repeated-measures, within-subjects design with six experimental conditions, effect size (η² = 0.81), α = 0.05, power (1 − β) = 0.8 and a correlation of 0.5. The results indicated a sample size of 12 participants. The effect size was based on a pilot study analyzing muscle swelling of vastus lateralis at 50% of femur. All participants had abstained from RT for at least six months prior to the study. The eligibility criteria included being male, a non-smoker, free from cardiovascular or metabolic disease, with no history of performance-enhancing drug use (e.g., androgenic anabolic steroids), no history of muscle-tendon injury, and no engagement in other forms of RT during the study period. Male participants were exclusively recruited to avoid performance variations associated with different phases of the menstrual cycle or oral contraceptive use 18 . Participants were instructed to maintain their regular dietary habits throughout the study and to refrain from using any ergogenic aids. To minimize the influence of circadian rhythm, all testing sessions were conducted at the same time of day (± 2h). Additionally, participants were required to abstain from high-intensity exercise for at least 48 hours prior to testing or training sessions, and from any physical activity immediately beforehand. The study was approved by the institutional ethics committee of the corresponding author (CAAE: 76251723.7.0000.5115, approval date: 12/18/2023) and conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent prior to participation. Experimental design A single-blind, within-subject experimental design was employed, in which the researchers’ analyzing data were blinded to the intervention allocation. Each participant completed five experimental conditions, corresponding to individualized reductions of 10%, 20%, 30%, 40%, and 50% in training volume, presented in a randomized order across experimental sessions (Fig. 1 ). The volume reductions were calculated based on the total number of repetitions performed by each participant at 50% of 1RM, ensuring that each reduction represented a specific proportion of the participant’s own prior performance. MVIC, EMG, muscle swelling through ultrasonography, and blood lactate concentration were assessed. Training protocols Prior to the experimental conditions, participants completed a familiarization session to become accustomed to the exercise protocol and equipment. Before experimental protocols, participants completed a specific warm-up of one set of 10 leg extension repetitions without external load, performed with a muscle action duration of 3s:3s, three seconds for both the concentric and eccentric phases, respectively, using a metronome. For RT F , participants performed three sets of knee extension exercise at 50% of 1RM. Muscle action duration of 3s:3s was controlled throughout the full range of motion (ROM), resulting in a total of six seconds per repetition. The evaluator provided continuous feedback to participants regarding the movement rhythm. A three-minute rest interval was provided between sets, and data on repetition duration and ROM were collected and recorded. Concentric phase was defined as angular displacement from 113° to 20° and the eccentric phase from 20° to 113° (0°=knee fully extended). The RT NF protocols followed the same procedures; however, the number of repetitions was reduced by a predetermined percentage (10, 20, 30, 40, or 50%) of the total achieved in the RT F condition. Each experimental session was separated by a one-week interval to minimize residual fatigue and carryover effects. One repetition maximum test (1RM) The 1RM test was conducted using a knee extension exercise (K&E Fitness, Divinópolis, MG, Brazil). This was preceded by a specific warm-up of one set of 10 leg extension repetitions without weight, performed with a cadence of 3:3. Rest intervals of five minutes were provided between each attempt to determine the 1RM, with no more than five attempts required. The 1RM was defined as the maximum load at which the participant could complete a single repetition. The 1RM testing procedure followed the recommendations of the National Strength and Conditioning Association 19 . A 1RM retest was conducted at least 48 hours after the initial trial. The intraclass correlation coefficient for the 1RM test–retest reliability was high (ICC: 0.923; 95% CI = 0.709–0.979; p < 0.001). Maximum voluntary isometric contraction test MVIC was recorded by a type S load cell (AEPH do Brasil, São Paulo, Brazil). Participants were secured in the knee extension exercise with straps positioned across the hip to minimize extraneous body movement. Subsequently, participants were instructed to complete two MVIC of approximately 5 seconds each, with a two-minute rest interval between trials, at a knee joint angle of 60° 9 . They were instructed to avoid any countermovement prior to initiating the extension and to perform the movement as “hard” as possible 20 during each contraction. Each trial commenced following an auditory cue, and force output was recorded using the load cell. Verbal encouragement was provided throughout each contraction. If peak torque values differed by more than 5% between trials, an additional attempt was performed. The peak value of each trial was subsequently converted offline into Newtons. MVIC tests were performed before experimental intervention and at 30 s and 15 min post-intervention. The intraclass correlation coefficient for the MVIC inter experimental condition was high (ICC: 0.984; 95% CI = 0.961–0.995; p < 0.001). Muscle swelling assessment through ultrasonography For muscle swelling, cross-sectional area (CSA) of the rectus femoris (RF) and vastus lateralis (VL) muscles was assessed using an ultrasound system (VINNO®, V5, Suzhou, China) equipped with a 5 cm linear transducer in “extended-field-of-view” mode. The acquisition procedures were similar to those previously described 21 . Briefly, participants were positioned supine, and measurement sites were marked at 30%, 50%, and 70% of the femur length, measured between the greater trochanter and the lateral epicondyle, and aligned perpendicular to the line connecting the lateral epicondyle and the adductor tubercle. The ultrasound system was configured with a 10 MHz frequency; image acquisition rate of 21 Hz, gain ranging from 25Db to 71Db and depth of image capturing ranging from 2,3 cm to 8 cm. Settings were individually adjusted and maintained throughout the study to ensure optimal image quality of the target muscles. An experienced examiner (L.T.L.) acquired two images at each femur percentage site (30%, 50%, and 70%) before and one after the experimental intervention, resulting in a total of nine images per muscle. During acquisition, the probe was positioned transversely, parallel to the intercondylar line, using a coupled guide on the participant’s thigh. The images were analyzed using RadiAnt software (Medixant®, Poznan, Poland). CSA was analyzed based on the absolute changes between pre- and post-measurements. The intraclass correlation coefficient (ICC) were calculated by comparing CSA measurements from images acquired inter experimental sessions for both muscles were high (ICC VL : 0.997; 95% CI = 0.994–0.999, P < 0.001; ICC RF : 0.997; 95% CI = 0.992–0.999, p < 0.001). Lactate Lactate concentrations were determined from capillary whole-blood samples obtained from the hyperemic earlobe using sterile disposable lancets (YSI 2500, YSI Incorporated, Yellow Springs, Ohio, USA). The earlobe was first cleaned with neutral soap and water, followed by sterilization with 70% alcohol prior to puncture. A 30 µL blood sample was collected into heparinized capillary tubes, which were then transferred into tubes containing 60 µL of 1% sodium fluoride and stored in a refrigerator at − 20 ºC. Blood samples were collected immediately before, and at 1, 5, 10, and 15 minutes after the experimental intervention. Samples were subsequently thawed and analyzed in duplicate. The ICC for the lactate inter experimental condition was high (ICC: 0.919; 95% CI = 0.806–0.977, p < 0.001). Electromyography activity EMG activity was obtained using an 8-channel system (SAS1000V8-WF, EMG System do Brasil®, São José dos Campos, Brazil) connected to a A/D Converter (NI USB-6009, National Instruments, Austin, TX, USA) at a sampling rate of 4 kHz. Signals were recorded and processed using specialized software (DasyLab 11.0; Measurement Computing Corporation, Norton, MA, USA) using a bipolar montage (gain: 2000×; CMRR: ≥100 dB; impedance: 10 9 Ohms; signal-to-noise ratio: ≤3 µV RMS; range: ±5000 µV). Following skin preparation (trichotomy and cleaning with 70% alcohol) in accordance with SENIAM recommendations (Hermens et al., 2000), disposable Ag/AgCl surface electrodes (Qingdao Bright Medical Manufacturing Co. Ltd., Qingdao, China) were placed over the RF and VL with a 2 cm interelectrode distance. A reference electrode was positioned over the patella of the respective limb. For the time domain, the EMG data was filtered (4th-order Butterworth band-pass filter of 20–500 Hz) before calculating the EMG amplitude as the root mean square (EMG RMS ). Before commencing each training session, participants were asked to perform an MVIC test for 5 seconds on the knee extension machine exercise at 60° knee flexion (controlled by the potentiometer). The EMG RMS value found during the MVIC test was then used as a reference for the normalization of the subsequent protocol measurements (normalization test). The mean EMG of concentric muscle actions for each protocol was then calculated. These values were divided by the respective reference values previously described, generating the normalized EMG RMS per protocol. The mean for each of the 6 protocols of EMG RMS was used in the statistical analysis as the mean neuromuscular activation for each training session. The ICC for the EMG RMS(VL) and EMG RMS(RF) inter experimental condition were high (ICC VL : 0.980; 95% CI = 0.995–0.994; p < 0.001; ICC RF : 0.968; 95% CI = 0.927–0.990; p < 0.001). For the frequency domain (FREQ), median frequency values obtained during the MVIC were derived from the power spectral density estimated using Welch’s method, a procedure that averages partially overlapping windowed segments to provide a smoother and more reliable spectral estimate. The segment length was limited to a maximum of 2048 samples (corresponding to 512 ms at a 4000-Hz sampling rate). The mean frequency was defined as the frequency that divides the spectral power into two equal halves. FREQ measurements were performed before experimental intervention and at 30 s and 15 min post-intervention. The ICC for the FREQ VL and FREQ RF inter experimental condition were high (ICC VL : 0.935; 95% CI = 0.852–0.980; p < 0.001; ICC RF : 0.934; 95% CI = 0.848–0.979; p < 0.001). Rate of perceived exertion To assess participant’s RPE, we used the Omnibus-Resistance 22 . After each set during protocols, participants were asked to indicate how hard the exercise felt on an 11-point Likert-type scale, anchored from 0 (extremely easy) to 10 (extremely hard). The median of all three sets was calculated for analysis. The procedure for the establishment of the low (“1” score) and high (“10” score) anchors for each individual’s perceived exertion was read to volunteers during performing one repetition in knee extension exercise without adding weight to the equipment and in 1RM test, respectively. Statistical Analysis Data was entered into SPSS (Statistics for Windows, version 22) and screened for missing values and outliers. The ICC was calculated to assess the reliability of 1RM, MVIC, ultrasonography, lactate and EMG measurements. The Shapiro–Wilk test was performed to evaluate the normality of the data. If no deviations from normality were observed, two-way analysis of variance (ANOVA) was conducted to examine the effects of training protocol and time on MVIC, EMG frequency, and lactate. MVIC and EMG frequency were analyzed as the changes of pre-experimental interventions. When a significant main effect was detected, post hoc pairwise comparisons were performed using the least significant difference (LSD) test. The assumption of sphericity was evaluated using Mauchly’s test prior to conducting repeated-measures analyses and Huynh-Feldt correction was considered when necessary. Additionally, a one-way ANOVA was conducted to assess differences in muscle swelling (CSA), EMG time domain, and FREQ. For RPE, a non-parametric Friedman test was performed. Partial eta square effect size (partial η 2 ) was calculated and interpreted as small ( 0.14) 23 . In addition, statistical power (1 − β) was calculated for all analyses. A threshold of 0.80 was considered acceptable. Data are presented as mean and standard deviation (SD) unless stated otherwise, and statistical significance was set at p < 0.05. RESULTS A total of 12 participants were randomized and began the study. One participant did not complete all tests due to illness unrelated to the study and was excluded. This resulted in a final sample of 11 participants (age: 23.27 ± 4.92 years; height: 180.00 ± 7.00 cm; body mass: 74.19 ± 15.91 kg; body fat: 18.3 ± 8.32%; fat-free mass: 59.85 ± 10.53 kg). Considering this missing data, post hoc power analysis was calculated for each outcome. Additionally, Table 1 presents parameters controlled to ensure standardized training-load prescription. ***Please insert Table 1 here*** Table 1 Parameters controlled to ensure standardized training-load prescription. Experimental condition Variable RT F 10% 20% 30% 40% 50% Rep. Duration 6.08 ± 0.3 5.97 ± 0.42 5.99 ± 0.35 6.05 ± 0.31 6.00 ± 0.31 5.95 ± 0.33 Number of Reps. 21.55 ± 5.41 19.45 ± 5.05 17.18 ± 3.95 15.27 ± 3.82 13.00 ± 3.19 11.00 ± 2.90 Range of Motion 81.44 ± 1.09 81.32 ± 1.03 81.90 ± 0.88 81.76 ± 1.04 81.39 ± 0.85 81.38 ± 0.66 RT F : resistance training to failure; 10 to 50% denotes individualized reductions of 10%, 20%, 30%, 40%, or 50% in training volume. Data are present as mean and SD. Rep. Duration: Repetition duration; Number of Reps.: number of repetitions. Muscle swelling (changes in CSA) For CSA VL , a significant effect was found for protocol (F 2.53,22.85 = 23.67, p < 0.01, partial η 2 = 0.72; power = 0.99). For CSA RF , a significant effect was found for protocol (F 5,45 = 15.43, p < 0.01, partial η 2 = 0.63; power = 0.99). Detailed information for least significance difference post hoc comparisons for both muscles is presented in Fig. 2 A–B. ***Please insert Fig. 2 here*** Amplitude EMG (RMS) For the time domain, EMG VL , a significant effect was found for protocol (F 2.75,27.49 = 4.88, p = 0.01, partial η 2 = 0.32; power = 0.84). Least significance difference post hoc comparisons indicated that RT F were different from reductions of 30%, 40% and 50% (Fig. 3 A). No other differences were found among protocols. For EMG RF , a significant effect was found for protocol (F 2.40,24.08 = 5.16, p = 0.01, partial η 2 = 0.34; power = 0.82) (Fig. 3 B). ***Please insert Fig. 3 here*** Frequency EMG (median data) Related to FREQ VL , no significant effect was found for protocol (F 5,45 = 8.44, p = 0.65, partial η 2 = 0.06; power = 0.21) and time (F 1,9 = 1.77, p = 0.21, partial η 2 = 0.16; power = 0.22). However, a significant effect was found for interaction (F 4.62,41.61 = 2.72, p = 0.035, partial η 2 = 0.23; power = 0.74). Related to FREQ RF , a significant effect was found for time (F 1,10 = 14.82, p = 0.01, partial η 2 = 0.59; power = 0.93) and interaction (F 5,50 = 2.94, p = 0.02, partial η 2 = 0.22; power = 0.81). However, no significant effect was found for protocol (F 5,50 = 2.10, p = 0.08, partial η 2 = 0.17; power = 0.64). Results of each analysis and least significance difference post hoc comparisons are reported in Fig. 4 . ***Please insert Fig. 4 here*** Maximal strength performance (change in MVIC) For MVIC, a significant effect was found for protocol (F 4.56,45.65 = 3.04, p = 0.02, partial η 2 = 0.23; power = 0.79) and interaction (F 5,50 = 2.77, p = 0.02, partial η 2 = 0.21; power = 0.78). However, no significant effect was found for time (F 1,10 = 0.13, p = 0.72, partial η 2 = 0.01; power = 0.06) (Fig. 5 ). ***Please insert Fig. 5 here*** Blood lactate concentration For lactate, a significant effect were found for protocol (F 3.58,35.82 = 37.57, p < 0.01, partial η 2 = 0.79; power = 0.99), time (F 1.33,13.32 = 70.49, p < 0.01, partial η 2 = 0.87; power = 0.99) and interactions (F 8.70,87.04 = 19.31, p < 0.01, partial η 2 = 0.65; power = 0.99). Detailed information for least significance difference post hoc comparisons is presented in Table 2 . ***Please insert Table 1 here*** Table 2 Lactate response at different time points across the experimental conditions. Experimental condition Variable RT F 10% 20% 30% 40% 50% Lac PRE (mmol/L) 1.26 ± 0.37 1.28 ± 0.37 1.22 ± 0.54 1.27 ± 0.42 1.24 ± 0.48 1.35 ± 0.51 Lac 1MIN (mmol/L) 4.63 ± 0.87 * 4.29 ± 0.78 * 3.42 ± 1.32 ab* 2.84 ± 0.72 ab* 2.52 ± 0.96 abc* 2.36 ± 0.75 abcd* Lac 5MIN (mmol/L) 5.07 ± 1.24 *$ 3.66 ± 0.83 a*$ 3.04 ± 1.19 ab* 2.53 ± 0.88 ab*$ 1.94 ± 0.59 abcd*$ 1.89 ± 0.70 abcd*$ Lac 10MIN (mmol/L) 4.24 ± 1.22 *# 2.95 ± 0.84 a*$# 2.47 ± 1.20 a*$# 1.95 ± 0.63 ab*$# 1.53 ± 0.50 abcd$# 1.36 ± 0.66 abcd$# Lac 15MIN (mmol/L) 3.43 ± 1.23 *$#& 2.18 ± 0.58 a*$#& 1.80 ± 0.92 a*$#& 1.38 ± 0.41 ab$#& 1.10 ± 0.28 abcd$#& 1.19 ± 0.43 abc$# Lac PRE : blood lactate concentration at baseline; Lac 1MIN : blood lactate concentration at 1 min post training protocol; Lac 5MIN : blood lactate concentration at 5 min post training protocol; Lac 10MIN : blood lactate concentration at 10 min post training protocol; Lac 15MIN : blood lactate concentration at 15 min post training protocol; RT F : resistance training to failure; 10 to 50% denotes individualized reductions of 10%, 20%, 30%, 40%, or 50% in training volume. a denotes differences from RT F . b denotes differences from 10%. c denotes difference from 20%. d denotes differences from 30%. * denotes difference from Lac Pre ; $ denotes difference from Lac 1MIN ; # denotes difference from Lac 5MIN ; & denotes difference from Lac 10MIN . Data are presented as mean and SD. Perceptual exertion For RPE median scores, a significant effect for protocol was found (X 2 (5) = 44.47; p < 0.01; Kendall’s W effect size = 0.81) (Fig. 6 ). ***Please insert Fig. 6 here*** DISCUSSION We examined the acute effects of varying reductions in repetitions (10% to 50%) relative to RT F performed at 50% of 1RM on neuromuscular, metabolic and perceptual parameters of untrained men. Specifically, we analyzed muscle swelling, EMG (amplitude and frequency), MVIC, blood lactate concentrations, and RPE. Overall, the findings support the hypothesis that greater reductions in training volume are associated with proportionally lower neuromuscular and metabolic responses. Our primary findings showed that RT F elicited greater muscle swelling, neuromuscular, metabolic and perceptual demands compared to all other protocols in untrained individuals. As exercise approaches muscle failure, metabolic stress increases, leading to an elevated level of osmotic metabolites such as inorganic phosphate and free creatine 24 , 25 . These metabolites enhance intracellular osmotic pressure, promoting fluid influx into the muscle fiber and contributing to transient muscle swelling 26 . Previous evidence has also shown a linear relationship between the number of repetitions performed and muscle swelling assessed through the transverse relaxation time (T 2 ) measured via MRI, a technique that indirectly captures shifts in intracellular and interstitial fluid and changes in osmotic balance 27 . Ultimately, muscle swelling reflects increased intracellular hydration, which has been theorized to activate anabolic signaling pathways and potentially contribute to hypertrophic adaptations 25 , 26 . This mechanism may help explain our findings, as we observed more pronounced muscle swelling in the RT F condition, with proportional reductions as repetitions decreased across the other protocols (10–50%). Although we did not directly analyze hypertrophy, our results may align with previous evidence demonstrating associations between acute muscle swelling and chronic hypertrophy after six weeks of RT 6 . Conversely, it is noteworthy that RT F can also induce substantial more physiological stresses 28 and muscle damage 29 , which can require a prolonged recovery period between training sessions, consequently affecting intensity and volume of subsequent sessions 28 . With respect to EMG activity, RT F elicited higher EMG amplitude compared with the 30–50% reduction conditions. Several variables influence neuromuscular activation, including volume, intensity, and time under tension 30 , 31 . With respect to volume, previous evidence has shown that RT F induces greater EMG amplitude compared with RT NF 32 , 33 . These findings may be partially explained by the premise that additional motor units must be recruited to maintain force output as fatigue develops 34 . When RT F protocols are performed with light loads (50% 1RM), this effect appear to be even more pronounced 35 . Conversely, when total volume is equalized within a session, similar EMG amplitude has been reported for both RT F and RT NF protocol, contradicting this initial assumption 9 . In this context, our results showed that reductions of up to 20% in the RT NF produced EMG activity comparable to RT F , suggesting that the neuromuscular system was stimulated in a similar manner. This is consistent with findings in untrained women showing that full motor-unit recruitment occurs within 3–5 repetitions of failure, indicating that RT F is not required 32 . Together, these results suggest a volume threshold beyond which additional repetitions offer no further neuromuscular benefit. Although EMG amplitude does not fully capture motor-unit recruitment 13 , factors such as firing frequency and motor-unit synchronization also contribute. Notably, studies using EMG decomposition report recruitment of higher-threshold motor units when the vastus lateralis is fatigued 11 . Considering muscle strength, RT F caused a significant reduction in MVIC values immediately after session cessation compared to all other protocols. The reduction in MVIC may be partially explained by metabolite accumulation activating group III and IV afferents, which exert an inhibitory effect on the central nervous system 36 , 37 . This afferent feedback decreases spinal excitability and, combined with the fatigue-induced reduction in muscle fiber conduction velocity 38 , results in a lower neural drive to the muscle 39 . Consequently, motoneuron firing rates decline, reducing the muscle’s capacity to generate maximal force. Additionally, in agreement with the MVIC response, FREQ VL and FREQ RF followed a similar pattern. EMG frequency-domain measures have frequently been proposed as indicators of muscle fatigue 40 , 41 . This may reflect physiological processes occurring within the muscle, such as metabolic stress, ionic disturbances, or reduced membrane excitability 2 , 38 , 42 . Furthermore, the observed reduction in the EMG frequency domain after RT F is consistent with previous findings from fatiguing protocols 15 , 40 , 41 . This response may be related to slow action potential propagation 41 , induced by greater metabolic stress 2 , which directly affects conductivity velocity. It has also been proposed that shifts in the EMG power spectrum toward lower frequencies, partly driven by decreases in intramuscular pH, contribute to reductions frequency-domain variables during protocols performed to failure 42 . The inverse relationship between blood lactate concentrations and training volume observed in the present study suggests that progressive reductions in volume imposed lower metabolic stress, potentially resulting in faster recovery across the post-exercise time points, as values returned toward baseline more rapidly. This finding aligns with the premise that lactate is a byproduct of the glycolytic system whose concentration is modulated according to training load arrangement (i.e., volume, intensity, time under tension) and acts as a potential signaling molecule capable of modulating beneficial adaptations in several tissues 43 , 44 . Nevertheless, performing RT F is thought to impose greater demands on energy systems and elicit higher anabolic signaling than RT NF 25 , 45 , 46 , thereby inducing higher metabolic stress and delaying recovery. In contrast, similar hypertrophic responses between RT F and RT NF protocols early reported 9 reinforce the reasoning that there is a threshold for metabolic stress beyond which no further beneficial effects are realized 47 . Our result appears to support this notion, suggesting that a 10–20% reduction in volume may induce considerable metabolic demand without exceeding this threshold, which could still support hypertrophy adaptations. This reasoning warrants further investigations into chronic responses provided by RT F and RT NF at varying proximities to failure. Lastly, the maximal RPE scores observed after RT F align with the notion that greater perceptual effort is required to maintain performance as fatigue accumulates 48 . Higher RPE values during RT F compared with RT NF have also been reported previously 5 . Additionally, correlations between exercise tolerance and mental fatigue have been described 49 . Ultimately, the greater accumulation of metabolic by-products, such as lactate, observed in the presented study corroborates supports earlier associations between metabolic stress and increased RPE. This study presents several limitations. First, the relatively small sample size may have reduced the statistical power to detect subtle differences across conditions. Indeed, observed power values were high (≥ 0.93) across most outcome measures. Second, the randomization across five experimental conditions, while using one condition as a reference to determine volume reductions, may have introduced bias, as individual fatigue responses and volume-response relationships are not necessarily linear, even when counterbalanced. However, the experimental sessions were interspersed by one week, and the counterbalancing strategy likely minimized systematic order effects. Finally, the findings are limited to untrained young adults and may not generalize to other populations or to different exercise modalities. Nevertheless, this sample allows for a clearer observation of the acute physiological responses without the confounding influence of chronic adaptations. Lastly, there are strengths to be highlighted. For instance, the experimental protocols conducted in untrained individuals using an objective reduction in training volume referenced to RT F , along with the inclusion of both neuromuscular and metabolic assessments, address an important gap in literature. Furthermore, from a practical standpoint, these findings provide trainees and practitioners with evidence that choosing between RT F and RT NF imposes distinct demands that should be considered when prescribing RT. CONCLUSION In summary, choosing between RT F or varying proximities to failure in untrained individuals should be guided by the specific adaptations one aims to elicit. RT F appears to be preferable when the goal is to induce greater muscle swelling. However, when the priority is elevating the neuromuscular demand, reducing repetitions by up to 20% can provide a comparable stimulus, as demonstrated by the similar EMG amplitude observed. Therefore, performing a protocol in closer proximity to, but not reaching, failure may offer an alternative for achieving similar neuromuscular activation while minimizing metabolic stress. Declarations COMPETING INTERESTS The authors declare no competing interests. FUNDING This study was partially supported by the State Funding Agency of Minas Gerais, Brazil (FAPEMIG), processes APQ-00617-22, APQ-03875-23, APQ-03316-23. L.T.L is also supported by FAPEMIG (process BIP-00113-24). We also would like to thank Pró-Reitoria de Pesquisa da Universidade do Estado de Minas Gerais (UEMG). Author Contribution L.T.L. conceived and designed the study. J.M.G.F., G.P., I.J.S.R, I.H.A.L, L.C.S. and A.S.V. collected the data. K.C.P., A.V.L.L.C., Y.L.M.V and C.F.C.M.B collected and analyzed blood lactate concentrations. D.A.B., M.J.O.A. and L.R.D. performed formal analyses. H.L.R.S. and J.M.G.F drafted the manuscript. G.F.P., C.M.T.C., H.C.M.C., R.C.R.D and M.B.L. reviewed the manuscript and contributed technically to the quality of the manuscript. L.T.L. and H.L.R.S interpreted and validated the data. L.T.L., L.R.D. and C.F.C.M.B. obtained funding support. L.T.L., L.R.D. and C.F.C.M.B provided supervision and administrative support. All authors reviewed and approved the final manuscript text. 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07:48:57","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":74691,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8387060/v1/e5119c3c61287ae2feb6fe68.png"},{"id":100363065,"identity":"f8e38efb-4333-4fda-82fd-a7c41828c5ac","added_by":"auto","created_at":"2026-01-16 07:48:43","extension":"png","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":102228,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8387060/v1/df246ef8b05bc94cbf4a98c2.png"},{"id":100363128,"identity":"674947da-27b5-414b-b759-4030893044a4","added_by":"auto","created_at":"2026-01-16 07:48:57","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":46843,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8387060/v1/d7122de0091e38f30e0b9cb8.png"},{"id":100363050,"identity":"c53eaf8c-a2c5-46ef-a972-ff2d1ca3d445","added_by":"auto","created_at":"2026-01-16 07:48:41","extension":"png","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":47656,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8387060/v1/70bf80a7320a815ab12eecd4.png"},{"id":100028521,"identity":"dd4f469c-9690-4a94-bb84-0df07ea6669f","added_by":"auto","created_at":"2026-01-12 09:05:55","extension":"xml","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":146662,"visible":true,"origin":"","legend":"","description":"","filename":"1bcd072550ba496b9c75377d49870c841structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8387060/v1/17185aaae09cd24d5e742990.xml"},{"id":100028524,"identity":"286c461d-8706-4947-ac4b-ff0d62db14dd","added_by":"auto","created_at":"2026-01-12 09:05:55","extension":"html","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":161535,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8387060/v1/f506be4dcb3d73d55324cd1d.html"},{"id":100028501,"identity":"3512d87d-102b-4801-8765-569c64fd2483","added_by":"auto","created_at":"2026-01-12 09:05:54","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":332551,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental design of the study. RT\u003csub\u003eF\u003c/sub\u003e: resistance training to failure; RT\u003csub\u003eNF\u003c/sub\u003e: resistance training not to failure; MVIC: maximal voluntary isometric contraction test; 1RM: One maximal repetition test; PAR-Q: physical activity readiness questionnaire; RPE: Rating of Perceived Exertion Scale; US: ultrasonography; EMG: electromyography activity; 10 to 50% denotes individualized reductions of 10%, 20%, 30%, 40%, or 50% in training volume related to the total number of repetitions performed by each participant at 50% of 1RM performed in experimental conditions of the study.\u003c/p\u003e","description":"","filename":"image1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8387060/v1/6c01966b2e6612735203ab3f.jpeg"},{"id":100363365,"identity":"211dee3e-2863-4c96-b9b9-9f93b55cd6cc","added_by":"auto","created_at":"2026-01-16 07:49:32","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":93887,"visible":true,"origin":"","legend":"\u003cp\u003eMuscle swelling across experimental conditions. A) Changes in vastus lateralis; B) Changes in rectus femoris muscles; RT\u003csub\u003eF\u003c/sub\u003e: resistance training to failure; 10 to 50% denotes individualized reductions of 10%, 20%, 30%, 40%, or 50% in training volume. CSA\u003csub\u003eVL\u003c/sub\u003e: cross sectional area of vastus lateralis; CSA\u003csub\u003eRF\u003c/sub\u003e: cross sectional area of rectus femoralis. \u003csup\u003ea\u003c/sup\u003edenotes differences from RT\u003csub\u003eF\u003c/sub\u003e. \u003csup\u003eb\u003c/sup\u003edenotes differences from 10%. \u003csup\u003ec\u003c/sup\u003edenotes difference from 20%. \u003csup\u003ed\u003c/sup\u003edenotes differences from 30%. Data are presented as mean and SD.\u003c/p\u003e","description":"","filename":"image2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8387060/v1/a4d6e79b6a02896a5a66ebd0.jpeg"},{"id":100363295,"identity":"65022570-b837-4eea-8db5-e45059df0009","added_by":"auto","created_at":"2026-01-16 07:49:22","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":116948,"visible":true,"origin":"","legend":"\u003cp\u003eNeuromuscular activity across experimental conditions. A) Normalized EMG\u003csub\u003eRMS\u003c/sub\u003e of the vastus lateralis; B) Normalized EMG\u003csub\u003eRMS\u003c/sub\u003e of the rectus femoris. 10 to 50% denotes individualized reductions of 10%, 20%, 30%, 40%, or 50% in training volume. EMG\u003csub\u003eRMS(VL)\u003c/sub\u003e: electromyography root mean square of vastus lateralis; EMG\u003csub\u003eRMS(RF)\u003c/sub\u003e: electromyography root mean square of rectus femoralis. \u003csup\u003ea\u003c/sup\u003edenotes differences from RT\u003csub\u003eF\u003c/sub\u003e. \u003csup\u003eb\u003c/sup\u003edenotes differences from 10%. \u003csup\u003ec\u003c/sup\u003edenotes difference from 20%. \u003csup\u003ed\u003c/sup\u003edenotes differences from 30%. Data are presented as mean and SD.\u003c/p\u003e","description":"","filename":"image3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8387060/v1/bf674b437c1db51e196deea1.jpeg"},{"id":100028503,"identity":"13531bbd-72e6-4e64-bf83-493ccf0dea5d","added_by":"auto","created_at":"2026-01-12 09:05:54","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":155103,"visible":true,"origin":"","legend":"\u003cp\u003eNeuromuscular fatigue parameters across experimental conditions. A) Changes in frequency domain EMG activity for vastus lateralis muscle at 30 s after experimental conditions; B) Changes in frequency domain EMG activity for vastus lateralis muscle at 15 min after experimental conditions. C) Changes in frequency domain EMG activity for rectus femoris muscle at 30 s after experimental conditions; D) Changes in frequency domain EMG activity for rectus femoris muscle at 15 min after experimental conditions. RT\u003csub\u003eF\u003c/sub\u003e: resistance training to failure; 10 to 50% denotes individualized reductions of 10%, 20%, 30%, 40%, or 50% in training volume. \u003csup\u003ea\u003c/sup\u003edenotes differences from RT\u003csub\u003eF\u003c/sub\u003e. Data are presented as mean and SD.\u003c/p\u003e","description":"","filename":"image4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8387060/v1/5bf99dfa763bd8ed7869d208.jpeg"},{"id":100362843,"identity":"2a6618c3-e636-4ba0-8695-7b656e174a05","added_by":"auto","created_at":"2026-01-16 07:48:09","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":71809,"visible":true,"origin":"","legend":"\u003cp\u003eStrength performance across experimental conditions. A) Changes in maximal voluntary isometric contraction (MVIC) at 30s after experimental conditions; B) Changes in maximal voluntary isometric contraction (MVIC) at 15 min after experimental conditions; RT\u003csub\u003eF\u003c/sub\u003e: resistance training to failure; 10 to 50% denotes individualized reductions of 10%, 20%, 30%, 40%, or 50% in training volume. \u003csup\u003ea\u003c/sup\u003edenotes differences from RT\u003csub\u003eF\u003c/sub\u003e. Data are presented as mean and SD.\u003c/p\u003e","description":"","filename":"image5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8387060/v1/4a6f74287d3fa92209c3f060.jpeg"},{"id":100028504,"identity":"ff3ea1a1-e908-44bb-aeb5-0eafd41b7237","added_by":"auto","created_at":"2026-01-12 09:05:54","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":83805,"visible":true,"origin":"","legend":"\u003cp\u003ePerceived effort across experimental conditions. RT\u003csub\u003eF\u003c/sub\u003e: resistance training to failure; 10 to 50% denotes individualized reductions of 10%, 20%, 30%, 40%, or 50% in training volume. \u003csup\u003ea\u003c/sup\u003edenotes differences from RT\u003csub\u003eF\u003c/sub\u003e. \u003csup\u003eb\u003c/sup\u003edenotes differences from 10%. \u003csup\u003ec\u003c/sup\u003edenotes difference from 20%. Data are presented as median and interquartile range.\u003c/p\u003e","description":"","filename":"image6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8387060/v1/08d8521208d981b59dbb4e96.jpeg"},{"id":104867651,"identity":"8daa96db-303e-481e-acd8-c14d158dd5cc","added_by":"auto","created_at":"2026-03-18 07:13:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1885070,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8387060/v1/18056656-714e-46e9-9cb6-ca54e01969ef.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Training to failure vs not-to-failure with progressive volume reduction: neuromuscular and metabolic responses in untrained individuals","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eResistance training (RT) is an effective strategy for promoting muscle hypertrophy and strength gains, with mechanical tension and metabolic stress serving as the main mediating factors for these adaptations \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. RT performed to muscle failure (RT\u003csub\u003eF\u003c/sub\u003e) has been proposed to maximize these adaptations, potentially due to greater motor unit recruitment and metabolite accumulation compared to RT not performed to failure (RT\u003csub\u003eNF\u003c/sub\u003e) \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOnce RT\u003csub\u003eF\u003c/sub\u003e allows a higher number of repetitions to be completed, it is likely that this strategy induces greater acute muscle swelling (commonly referred to as the \u0026ldquo;muscle pump\u0026rdquo;) compared to RT\u003csub\u003eNF\u003c/sub\u003e. This interpretation aligns with previous finding \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, which reinforce the idea that, at a given intensity, performing more repetitions in RT\u003csub\u003eF\u003c/sub\u003e leads to elevation of metabolic stress, evidenced by biological markers such as ammonia, creatine kinase (CK), and elevated blood lactate concentrations \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Hirono, et al. \u003csup\u003e6\u003c/sup\u003e reported that greater acute muscle swelling was associated with greater chronic muscle hypertrophy, suggesting that acute investigations can provide valuable insights into short-term physiological responses that may contribute to long-term adaptations. Moreover, muscle swelling and hypertrophy are not uniform along the muscle length \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, which could result from mechanical stress that varies across the range of motion \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRecent research has shown that hypertrophy gains tend to be similar between RT\u003csub\u003eF\u003c/sub\u003e and RT\u003csub\u003eNF\u003c/sub\u003e when RT volume is equalized or when only small reductions in volume are implemented using repetition in reserve strategy \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. However, the similarity in this response may indicate that there is a threshold of metabolic stress and neuromuscular demand beyond which additional stimuli does not lead to significant improvements and may instead increase muscle damage and prolong recovery time. Supporting this hypothesis, a meta-analysis conducted by Vieira, et al. \u003csup\u003e5\u003c/sup\u003e reported greater cellular damage and higher CK levels 48 hours after RT\u003csub\u003eF\u003c/sub\u003e, indicating the need for longer recovery periods between RT\u003csub\u003eF\u003c/sub\u003e sessions. Thus, determining the appropriate training stimulus becomes essential to maximize neuromuscular adaptation while minimizing unnecessary muscle damage.\u003c/p\u003e \u003cp\u003eOverall improvements in physical function after RT intervention have been associated with increases in neuromuscular activation (i.e., motor unit recruitment) and/or muscle strength. RT\u003csub\u003eF\u003c/sub\u003e has traditionally been associated with greater motor unit recruitment \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, this assumption shall be questioned. Muscle motor units vary substantially in fiber size, location, and firing rate, and these properties influence the electromyographic (EMG) signal without necessarily reflecting proportional motor unit recruitment \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Furthermore, similar EMG responses have been observed between RT\u003csub\u003eF\u003c/sub\u003e and RT\u003csub\u003eNF\u003c/sub\u003e when volume was equalized, in both trained \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e and untrained individuals \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, indicating that there may be no need to train to failure in order to achieve maximal neuromuscular activation. Furthermore, several studies have reported similar adaptations in maximal dynamic strength (1RM) and maximal voluntary isometric contraction (MVIC) between RT\u003csub\u003eF\u003c/sub\u003e and RT\u003csub\u003eNF\u003c/sub\u003e conditions \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. In contrast, the fatigue induced by RT\u003csub\u003eF\u003c/sub\u003e may acutely compromise maximal strength performance (Pareja-Blanco et al., 2016; Grgic et al., 2022), which is not always desirable. Beyond maximal strength performance after RT, a complementary approach is to examining exercise-induced fatigue by analyzing EMG frequency \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Previous studies indicate that the closer an individual is to failure, the greater the reduction in EMG frequency \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. This suggests that approaching failure imposes progressively greater neural challenges. Despite the known physiological responses to training to failure, it remains unclear what is the minimal reduction in repetitions, relative to failure, that still elicits meaningful neuromuscular and metabolic responses\u003c/p\u003e \u003cp\u003eWhile RT\u003csub\u003eF\u003c/sub\u003e can enhance metabolic and neuromuscular stimuli, RT\u003csub\u003eNF\u003c/sub\u003e can produce comparable outcomes when variables such as volume and intensity are equivalent. This is important, given that training status can modulate physiological responses to both RT\u003csub\u003eF\u003c/sub\u003e and RT\u003csub\u003eNF\u003c/sub\u003e \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Therefore, a need exists in examining the magnitude of responses elicited by these training protocols in untraining populations. The choice of untrained populations is crucial because their responses provide a clearer, 'noise-free' signal of the fundamental physiological effect of the training protocol itself, free from the confounding adaptations of prior training.\u003c/p\u003e \u003cp\u003eTherefore, the aim of this study is to examine the acute responses of muscle swelling, EMG in both the frequency and time domains, blood lactate concentrations, MVIC and rate of perceived exertion (RPE) to varying reductions in repetitions (10% to 50%) relative to maximal repetition to failure. We hypothesize that the percentage reduction in training volume relative to failure is associated with a commensurate reduction in neuromuscular and metabolic responses.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eA priori sample estimation (G*Power 3.1.9.2, Heinrich-Heine Universit\u0026auml;t D\u0026uuml;sseldorf, D\u0026uuml;sseldorf, Germany). This analysis assumed a repeated-measures, within-subjects design with six experimental conditions, effect size (η\u0026sup2; = 0.81), α\u0026thinsp;=\u0026thinsp;0.05, power (1\u0026thinsp;\u0026minus;\u0026thinsp;β)\u0026thinsp;=\u0026thinsp;0.8 and a correlation of 0.5. The results indicated a sample size of 12 participants. The effect size was based on a pilot study analyzing muscle swelling of vastus lateralis at 50% of femur. All participants had abstained from RT for at least six months prior to the study. The eligibility criteria included being male, a non-smoker, free from cardiovascular or metabolic disease, with no history of performance-enhancing drug use (e.g., androgenic anabolic steroids), no history of muscle-tendon injury, and no engagement in other forms of RT during the study period. Male participants were exclusively recruited to avoid performance variations associated with different phases of the menstrual cycle or oral contraceptive use \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eParticipants were instructed to maintain their regular dietary habits throughout the study and to refrain from using any ergogenic aids. To minimize the influence of circadian rhythm, all testing sessions were conducted at the same time of day (\u0026plusmn;\u0026thinsp;2h). Additionally, participants were required to abstain from high-intensity exercise for at least 48 hours prior to testing or training sessions, and from any physical activity immediately beforehand. The study was approved by the institutional ethics committee of the corresponding author (CAAE: 76251723.7.0000.5115, approval date: 12/18/2023) and conducted in accordance with the Declaration of Helsinki. All participants provided written informed consent prior to participation.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExperimental design\u003c/h3\u003e\n\u003cp\u003eA single-blind, within-subject experimental design was employed, in which the researchers\u0026rsquo; analyzing data were blinded to the intervention allocation. Each participant completed five experimental conditions, corresponding to individualized reductions of 10%, 20%, 30%, 40%, and 50% in training volume, presented in a randomized order across experimental sessions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The volume reductions were calculated based on the total number of repetitions performed by each participant at 50% of 1RM, ensuring that each reduction represented a specific proportion of the participant\u0026rsquo;s own prior performance. MVIC, EMG, muscle swelling through ultrasonography, and blood lactate concentration were assessed.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eTraining protocols\u003c/h3\u003e\n\u003cp\u003ePrior to the experimental conditions, participants completed a familiarization session to become accustomed to the exercise protocol and equipment. Before experimental protocols, participants completed a specific warm-up of one set of 10 leg extension repetitions without external load, performed with a muscle action duration of 3s:3s, three seconds for both the concentric and eccentric phases, respectively, using a metronome. For RT\u003csub\u003eF\u003c/sub\u003e, participants performed three sets of knee extension exercise at 50% of 1RM. Muscle action duration of 3s:3s was controlled throughout the full range of motion (ROM), resulting in a total of six seconds per repetition. The evaluator provided continuous feedback to participants regarding the movement rhythm. A three-minute rest interval was provided between sets, and data on repetition duration and ROM were collected and recorded. Concentric phase was defined as angular displacement from 113\u0026deg; to 20\u0026deg; and the eccentric phase from 20\u0026deg; to 113\u0026deg; (0\u0026deg;=knee fully extended). The RT\u003csub\u003eNF\u003c/sub\u003e protocols followed the same procedures; however, the number of repetitions was reduced by a predetermined percentage (10, 20, 30, 40, or 50%) of the total achieved in the RT\u003csub\u003eF\u003c/sub\u003e condition. Each experimental session was separated by a one-week interval to minimize residual fatigue and carryover effects.\u003c/p\u003e\n\u003ch3\u003eOne repetition maximum test (1RM)\u003c/h3\u003e\n\u003cp\u003eThe 1RM test was conducted using a knee extension exercise (K\u0026amp;E Fitness, Divin\u0026oacute;polis, MG, Brazil). This was preceded by a specific warm-up of one set of 10 leg extension repetitions without weight, performed with a cadence of 3:3. Rest intervals of five minutes were provided between each attempt to determine the 1RM, with no more than five attempts required. The 1RM was defined as the maximum load at which the participant could complete a single repetition. The 1RM testing procedure followed the recommendations of the National Strength and Conditioning Association \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. A 1RM retest was conducted at least 48 hours after the initial trial. The intraclass correlation coefficient for the 1RM test\u0026ndash;retest reliability was high (ICC: 0.923; 95% CI\u0026thinsp;=\u0026thinsp;0.709\u0026ndash;0.979; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003ch3\u003eMaximum voluntary isometric contraction test\u003c/h3\u003e\n\u003cp\u003eMVIC was recorded by a type S load cell (AEPH do Brasil, S\u0026atilde;o Paulo, Brazil). Participants were secured in the knee extension exercise with straps positioned across the hip to minimize extraneous body movement. Subsequently, participants were instructed to complete two MVIC of approximately 5 seconds each, with a two-minute rest interval between trials, at a knee joint angle of 60\u0026deg; \u003csup\u003e9\u003c/sup\u003e. They were instructed to avoid any countermovement prior to initiating the extension and to perform the movement as \u0026ldquo;hard\u0026rdquo; as possible \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e during each contraction. Each trial commenced following an auditory cue, and force output was recorded using the load cell. Verbal encouragement was provided throughout each contraction. If peak torque values differed by more than 5% between trials, an additional attempt was performed. The peak value of each trial was subsequently converted offline into Newtons. MVIC tests were performed before experimental intervention and at 30 s and 15 min post-intervention. The intraclass correlation coefficient for the MVIC inter experimental condition was high (ICC: 0.984; 95% CI\u0026thinsp;=\u0026thinsp;0.961\u0026ndash;0.995; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMuscle swelling assessment through ultrasonography\u003c/h2\u003e \u003cp\u003eFor muscle swelling, cross-sectional area (CSA) of the rectus femoris (RF) and vastus lateralis (VL) muscles was assessed using an ultrasound system (VINNO\u0026reg;, V5, Suzhou, China) equipped with a 5 cm linear transducer in \u0026ldquo;extended-field-of-view\u0026rdquo; mode. The acquisition procedures were similar to those previously described \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Briefly, participants were positioned supine, and measurement sites were marked at 30%, 50%, and 70% of the femur length, measured between the greater trochanter and the lateral epicondyle, and aligned perpendicular to the line connecting the lateral epicondyle and the adductor tubercle.\u003c/p\u003e \u003cp\u003eThe ultrasound system was configured with a 10 MHz frequency; image acquisition rate of 21 Hz, gain ranging from 25Db to 71Db and depth of image capturing ranging from 2,3 cm to 8 cm. Settings were individually adjusted and maintained throughout the study to ensure optimal image quality of the target muscles. An experienced examiner (L.T.L.) acquired two images at each femur percentage site (30%, 50%, and 70%) before and one after the experimental intervention, resulting in a total of nine images per muscle. During acquisition, the probe was positioned transversely, parallel to the intercondylar line, using a coupled guide on the participant\u0026rsquo;s thigh. The images were analyzed using RadiAnt software (Medixant\u0026reg;, Poznan, Poland). CSA was analyzed based on the absolute changes between pre- and post-measurements. The intraclass correlation coefficient (ICC) were calculated by comparing CSA measurements from images acquired inter experimental sessions for both muscles were high (ICC\u003csub\u003eVL\u003c/sub\u003e: 0.997; 95% CI\u0026thinsp;=\u0026thinsp;0.994\u0026ndash;0.999, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; ICC\u003csub\u003eRF\u003c/sub\u003e: 0.997; 95% CI\u0026thinsp;=\u0026thinsp;0.992\u0026ndash;0.999, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eLactate\u003c/h3\u003e\n\u003cp\u003eLactate concentrations were determined from capillary whole-blood samples obtained from the hyperemic earlobe using sterile disposable lancets (YSI 2500, YSI Incorporated, Yellow Springs, Ohio, USA). The earlobe was first cleaned with neutral soap and water, followed by sterilization with 70% alcohol prior to puncture. A 30 \u0026micro;L blood sample was collected into heparinized capillary tubes, which were then transferred into tubes containing 60 \u0026micro;L of 1% sodium fluoride and stored in a refrigerator at \u0026minus;\u0026thinsp;20 \u0026ordm;C. Blood samples were collected immediately before, and at 1, 5, 10, and 15 minutes after the experimental intervention. Samples were subsequently thawed and analyzed in duplicate. The ICC for the lactate inter experimental condition was high (ICC: 0.919; 95% CI\u0026thinsp;=\u0026thinsp;0.806\u0026ndash;0.977, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003ch3\u003eElectromyography activity\u003c/h3\u003e\n\u003cp\u003eEMG activity was obtained using an 8-channel system (SAS1000V8-WF, EMG System do Brasil\u0026reg;, S\u0026atilde;o Jos\u0026eacute; dos Campos, Brazil) connected to a A/D Converter (NI USB-6009, National Instruments, Austin, TX, USA) at a sampling rate of 4 kHz. Signals were recorded and processed using specialized software (DasyLab 11.0; Measurement Computing Corporation, Norton, MA, USA) using a bipolar montage (gain: 2000\u0026times;; CMRR: \u0026ge;100 dB; impedance: 10\u003csup\u003e9\u003c/sup\u003e Ohms; signal-to-noise ratio: \u0026le;3 \u0026micro;V RMS; range: \u0026plusmn;5000 \u0026micro;V). Following skin preparation (trichotomy and cleaning with 70% alcohol) in accordance with SENIAM recommendations (Hermens et al., 2000), disposable Ag/AgCl surface electrodes (Qingdao Bright Medical Manufacturing Co. Ltd., Qingdao, China) were placed over the RF and VL with a 2 cm interelectrode distance. A reference electrode was positioned over the patella of the respective limb.\u003c/p\u003e \u003cp\u003eFor the time domain, the EMG data was filtered (4th-order Butterworth band-pass filter of 20\u0026ndash;500 Hz) before calculating the EMG amplitude as the root mean square (EMG\u003csub\u003eRMS\u003c/sub\u003e). Before commencing each training session, participants were asked to perform an MVIC test for 5 seconds on the knee extension machine exercise at 60\u0026deg; knee flexion (controlled by the potentiometer). The EMG\u003csub\u003eRMS\u003c/sub\u003e value found during the MVIC test was then used as a reference for the normalization of the subsequent protocol measurements (normalization test). The mean EMG of concentric muscle actions for each protocol was then calculated. These values were divided by the respective reference values previously described, generating the normalized EMG\u003csub\u003eRMS\u003c/sub\u003e per protocol. The mean for each of the 6 protocols of EMG\u003csub\u003eRMS\u003c/sub\u003e was used in the statistical analysis as the mean neuromuscular activation for each training session. The ICC for the EMG\u003csub\u003eRMS(VL)\u003c/sub\u003e and EMG\u003csub\u003eRMS(RF)\u003c/sub\u003e inter experimental condition were high (ICC\u003csub\u003eVL\u003c/sub\u003e: 0.980; 95% CI\u0026thinsp;=\u0026thinsp;0.995\u0026ndash;0.994; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; ICC\u003csub\u003eRF\u003c/sub\u003e: 0.968; 95% CI\u0026thinsp;=\u0026thinsp;0.927\u0026ndash;0.990; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eFor the frequency domain (FREQ), median frequency values obtained during the MVIC were derived from the power spectral density estimated using Welch\u0026rsquo;s method, a procedure that averages partially overlapping windowed segments to provide a smoother and more reliable spectral estimate. The segment length was limited to a maximum of 2048 samples (corresponding to 512 ms at a 4000-Hz sampling rate). The mean frequency was defined as the frequency that divides the spectral power into two equal halves. FREQ measurements were performed before experimental intervention and at 30 s and 15 min post-intervention. The ICC for the FREQ\u003csub\u003eVL\u003c/sub\u003e and FREQ\u003csub\u003eRF\u003c/sub\u003e inter experimental condition were high (ICC\u003csub\u003eVL\u003c/sub\u003e: 0.935; 95% CI\u0026thinsp;=\u0026thinsp;0.852\u0026ndash;0.980; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; ICC\u003csub\u003eRF\u003c/sub\u003e: 0.934; 95% CI\u0026thinsp;=\u0026thinsp;0.848\u0026ndash;0.979; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRate of perceived exertion\u003c/h2\u003e \u003cp\u003eTo assess participant\u0026rsquo;s RPE, we used the Omnibus-Resistance \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. After each set during protocols, participants were asked to indicate how hard the exercise felt on an 11-point Likert-type scale, anchored from 0 (extremely easy) to 10 (extremely hard). The median of all three sets was calculated for analysis. The procedure for the establishment of the low (\u0026ldquo;1\u0026rdquo; score) and high (\u0026ldquo;10\u0026rdquo; score) anchors for each individual\u0026rsquo;s perceived exertion was read to volunteers during performing one repetition in knee extension exercise without adding weight to the equipment and in 1RM test, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData was entered into SPSS (Statistics for Windows, version 22) and screened for missing values and outliers. The ICC was calculated to assess the reliability of 1RM, MVIC, ultrasonography, lactate and EMG measurements. The Shapiro\u0026ndash;Wilk test was performed to evaluate the normality of the data. If no deviations from normality were observed, two-way analysis of variance (ANOVA) was conducted to examine the effects of training protocol and time on MVIC, EMG frequency, and lactate. MVIC and EMG frequency were analyzed as the changes of pre-experimental interventions. When a significant main effect was detected, post hoc pairwise comparisons were performed using the least significant difference (LSD) test. The assumption of sphericity was evaluated using Mauchly\u0026rsquo;s test prior to conducting repeated-measures analyses and Huynh-Feldt correction was considered when necessary. Additionally, a one-way ANOVA was conducted to assess differences in muscle swelling (CSA), EMG time domain, and FREQ. For RPE, a non-parametric Friedman test was performed. Partial eta square effect size (partial η\u003csup\u003e2\u003c/sup\u003e) was calculated and interpreted as small (\u0026lt;\u0026thinsp;0.01), medium (0.02\u0026ndash;0.13), or large (\u0026gt;\u0026thinsp;0.14) \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. In addition, statistical power (1\u0026thinsp;\u0026minus;\u0026thinsp;β) was calculated for all analyses. A threshold of 0.80 was considered acceptable. Data are presented as mean and standard deviation (SD) unless stated otherwise, and statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 12 participants were randomized and began the study. One participant did not complete all tests due to illness unrelated to the study and was excluded. This resulted in a final sample of 11 participants (age: 23.27\u0026thinsp;\u0026plusmn;\u0026thinsp;4.92 years; height: 180.00\u0026thinsp;\u0026plusmn;\u0026thinsp;7.00 cm; body mass: 74.19\u0026thinsp;\u0026plusmn;\u0026thinsp;15.91 kg; body fat: 18.3\u0026thinsp;\u0026plusmn;\u0026thinsp;8.32%; fat-free mass: 59.85\u0026thinsp;\u0026plusmn;\u0026thinsp;10.53 kg). Considering this missing data, post hoc power analysis was calculated for each outcome. Additionally, Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents parameters controlled to ensure standardized training-load prescription.\u003c/p\u003e \u003cp\u003e***Please insert Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e here***\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParameters controlled to ensure standardized training-load prescription.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eExperimental condition\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRT\u003csub\u003eF\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRep. Duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of Reps.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.55\u0026thinsp;\u0026plusmn;\u0026thinsp;5.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.45\u0026thinsp;\u0026plusmn;\u0026thinsp;5.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.18\u0026thinsp;\u0026plusmn;\u0026thinsp;3.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.27\u0026thinsp;\u0026plusmn;\u0026thinsp;3.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.00\u0026thinsp;\u0026plusmn;\u0026thinsp;3.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange of Motion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.44\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e81.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRT\u003csub\u003eF\u003c/sub\u003e: resistance training to failure; 10 to 50% denotes individualized reductions of 10%, 20%, 30%, 40%, or 50% in training volume. Data are present as mean and SD. Rep. Duration: Repetition duration; Number of Reps.: number of repetitions.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eMuscle swelling (changes in CSA)\u003c/h2\u003e \u003cp\u003eFor CSA\u003csub\u003eVL\u003c/sub\u003e, a significant effect was found for protocol (F\u003csub\u003e2.53,22.85\u003c/sub\u003e = 23.67, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.72; power\u0026thinsp;=\u0026thinsp;0.99). For CSA\u003csub\u003eRF\u003c/sub\u003e, a significant effect was found for protocol (F\u003csub\u003e5,45\u003c/sub\u003e = 15.43, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.63; power\u0026thinsp;=\u0026thinsp;0.99). Detailed information for least significance difference post hoc comparisons for both muscles is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u0026ndash;B.\u003c/p\u003e \u003cp\u003e***Please insert Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e here***\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eAmplitude EMG (RMS)\u003c/h2\u003e \u003cp\u003eFor the time domain, EMG\u003csub\u003eVL\u003c/sub\u003e, a significant effect was found for protocol (F\u003csub\u003e2.75,27.49\u003c/sub\u003e = 4.88, p\u0026thinsp;=\u0026thinsp;0.01, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.32; power\u0026thinsp;=\u0026thinsp;0.84). Least significance difference post hoc comparisons indicated that RT\u003csub\u003eF\u003c/sub\u003e were different from reductions of 30%, 40% and 50% (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). No other differences were found among protocols. For EMG\u003csub\u003eRF\u003c/sub\u003e, a significant effect was found for protocol (F\u003csub\u003e2.40,24.08\u003c/sub\u003e = 5.16, p\u0026thinsp;=\u0026thinsp;0.01, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.34; power\u0026thinsp;=\u0026thinsp;0.82) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e***Please insert Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e here***\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eFrequency EMG (median data)\u003c/h2\u003e \u003cp\u003eRelated to FREQ\u003csub\u003eVL\u003c/sub\u003e, no significant effect was found for protocol (F\u003csub\u003e5,45\u003c/sub\u003e = 8.44, p\u0026thinsp;=\u0026thinsp;0.65, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.06; power\u0026thinsp;=\u0026thinsp;0.21) and time (F\u003csub\u003e1,9\u003c/sub\u003e = 1.77, p\u0026thinsp;=\u0026thinsp;0.21, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.16; power\u0026thinsp;=\u0026thinsp;0.22). However, a significant effect was found for interaction (F\u003csub\u003e4.62,41.61\u003c/sub\u003e = 2.72, p\u0026thinsp;=\u0026thinsp;0.035, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.23; power\u0026thinsp;=\u0026thinsp;0.74). Related to FREQ\u003csub\u003eRF\u003c/sub\u003e, a significant effect was found for time (F\u003csub\u003e1,10\u003c/sub\u003e = 14.82, p\u0026thinsp;=\u0026thinsp;0.01, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.59; power\u0026thinsp;=\u0026thinsp;0.93) and interaction (F\u003csub\u003e5,50\u003c/sub\u003e = 2.94, p\u0026thinsp;=\u0026thinsp;0.02, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.22; power\u0026thinsp;=\u0026thinsp;0.81). However, no significant effect was found for protocol (F\u003csub\u003e5,50\u003c/sub\u003e = 2.10, p\u0026thinsp;=\u0026thinsp;0.08, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.17; power\u0026thinsp;=\u0026thinsp;0.64). Results of each analysis and least significance difference post hoc comparisons are reported in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e***Please insert Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e here***\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eMaximal strength performance (change in MVIC)\u003c/h2\u003e \u003cp\u003eFor MVIC, a significant effect was found for protocol (F\u003csub\u003e4.56,45.65\u003c/sub\u003e = 3.04, p\u0026thinsp;=\u0026thinsp;0.02, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.23; power\u0026thinsp;=\u0026thinsp;0.79) and interaction (F\u003csub\u003e5,50\u003c/sub\u003e = 2.77, p\u0026thinsp;=\u0026thinsp;0.02, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.21; power\u0026thinsp;=\u0026thinsp;0.78). However, no significant effect was found for time (F\u003csub\u003e1,10\u003c/sub\u003e = 0.13, p\u0026thinsp;=\u0026thinsp;0.72, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.01; power\u0026thinsp;=\u0026thinsp;0.06) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e***Please insert Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e here***\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eBlood lactate concentration\u003c/h2\u003e \u003cp\u003eFor lactate, a significant effect were found for protocol (F\u003csub\u003e3.58,35.82\u003c/sub\u003e = 37.57, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.79; power\u0026thinsp;=\u0026thinsp;0.99), time (F\u003csub\u003e1.33,13.32\u003c/sub\u003e = 70.49, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.87; power\u0026thinsp;=\u0026thinsp;0.99) and interactions (F\u003csub\u003e8.70,87.04\u003c/sub\u003e = 19.31, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, partial η\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.65; power\u0026thinsp;=\u0026thinsp;0.99). Detailed information for least significance difference post hoc comparisons is presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e***Please insert Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e here***\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLactate response at different time points across the experimental conditions.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eExperimental condition\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRT\u003csub\u003eF\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e50%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLac\u003csub\u003ePRE\u003c/sub\u003e (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLac\u003csub\u003e1MIN\u003c/sub\u003e (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003csup\u003eab*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003csup\u003eab*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003csup\u003eabc*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003csup\u003eabcd*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLac\u003csub\u003e5MIN\u003c/sub\u003e (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.24\u003csup\u003e*$\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003csup\u003ea*$\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.04\u0026thinsp;\u0026plusmn;\u0026thinsp;1.19\u003csup\u003eab*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003csup\u003eab*$\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.59\u003csup\u003eabcd*$\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003csup\u003eabcd*$\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLac\u003csub\u003e10MIN\u003c/sub\u003e (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.24\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003csup\u003e*#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003csup\u003ea*$#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20\u003csup\u003ea*$#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63\u003csup\u003eab*$#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003csup\u003eabcd$#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003csup\u003eabcd$#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLac\u003csub\u003e15MIN\u003c/sub\u003e (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23\u003csup\u003e*$#\u0026amp;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003csup\u003ea*$#\u0026amp;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003csup\u003ea*$#\u0026amp;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003csup\u003eab$#\u0026amp;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003csup\u003eabcd$#\u0026amp;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003csup\u003eabc$#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eLac\u003csub\u003ePRE\u003c/sub\u003e: blood lactate concentration at baseline; Lac\u003csub\u003e1MIN\u003c/sub\u003e: blood lactate concentration at 1 min post training protocol; Lac\u003csub\u003e5MIN\u003c/sub\u003e: blood lactate concentration at 5 min post training protocol; Lac\u003csub\u003e10MIN\u003c/sub\u003e: blood lactate concentration at 10 min post training protocol; Lac\u003csub\u003e15MIN\u003c/sub\u003e: blood lactate concentration at 15 min post training protocol; RT\u003csub\u003eF\u003c/sub\u003e: resistance training to failure; 10 to 50% denotes individualized reductions of 10%, 20%, 30%, 40%, or 50% in training volume. \u003csup\u003ea\u003c/sup\u003edenotes differences from RT\u003csub\u003eF\u003c/sub\u003e. \u003csup\u003eb\u003c/sup\u003edenotes differences from 10%. \u003csup\u003ec\u003c/sup\u003edenotes difference from 20%. \u003csup\u003ed\u003c/sup\u003edenotes differences from 30%. \u003csup\u003e*\u003c/sup\u003edenotes difference from Lac\u003csub\u003ePre\u003c/sub\u003e; \u003csup\u003e$\u003c/sup\u003edenotes difference from Lac\u003csub\u003e1MIN\u003c/sub\u003e; \u003csup\u003e#\u003c/sup\u003edenotes difference from Lac\u003csub\u003e5MIN\u003c/sub\u003e; \u003csup\u003e\u0026amp;\u003c/sup\u003edenotes difference from Lac\u003csub\u003e10MIN\u003c/sub\u003e. Data are presented as mean and SD.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003ePerceptual exertion\u003c/h2\u003e \u003cp\u003eFor RPE median scores, a significant effect for protocol was found (X\u003csup\u003e2\u003c/sup\u003e (5)\u0026thinsp;=\u0026thinsp;44.47; p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Kendall\u0026rsquo;s W effect size\u0026thinsp;=\u0026thinsp;0.81) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e***Please insert Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e here***\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eWe examined the acute effects of varying reductions in repetitions (10% to 50%) relative to RT\u003csub\u003eF\u003c/sub\u003e performed at 50% of 1RM on neuromuscular, metabolic and perceptual parameters of untrained men. Specifically, we analyzed muscle swelling, EMG (amplitude and frequency), MVIC, blood lactate concentrations, and RPE. Overall, the findings support the hypothesis that greater reductions in training volume are associated with proportionally lower neuromuscular and metabolic responses.\u003c/p\u003e \u003cp\u003eOur primary findings showed that RT\u003csub\u003eF\u003c/sub\u003e elicited greater muscle swelling, neuromuscular, metabolic and perceptual demands compared to all other protocols in untrained individuals. As exercise approaches muscle failure, metabolic stress increases, leading to an elevated level of osmotic metabolites such as inorganic phosphate and free creatine \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. These metabolites enhance intracellular osmotic pressure, promoting fluid influx into the muscle fiber and contributing to transient muscle swelling \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Previous evidence has also shown a linear relationship between the number of repetitions performed and muscle swelling assessed through the transverse relaxation time (T\u003csub\u003e2\u003c/sub\u003e) measured via MRI, a technique that indirectly captures shifts in intracellular and interstitial fluid and changes in osmotic balance \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Ultimately, muscle swelling reflects increased intracellular hydration, which has been theorized to activate anabolic signaling pathways and potentially contribute to hypertrophic adaptations \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. This mechanism may help explain our findings, as we observed more pronounced muscle swelling in the RT\u003csub\u003eF\u003c/sub\u003e condition, with proportional reductions as repetitions decreased across the other protocols (10\u0026ndash;50%). Although we did not directly analyze hypertrophy, our results may align with previous evidence demonstrating associations between acute muscle swelling and chronic hypertrophy after six weeks of RT \u003csup\u003e6\u003c/sup\u003e. Conversely, it is noteworthy that RT\u003csub\u003eF\u003c/sub\u003e can also induce substantial more physiological stresses \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e and muscle damage \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, which can require a prolonged recovery period between training sessions, consequently affecting intensity and volume of subsequent sessions \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWith respect to EMG activity, RT\u003csub\u003eF\u003c/sub\u003e elicited higher EMG amplitude compared with the 30\u0026ndash;50% reduction conditions. Several variables influence neuromuscular activation, including volume, intensity, and time under tension \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. With respect to volume, previous evidence has shown that RT\u003csub\u003eF\u003c/sub\u003e induces greater EMG amplitude compared with RT\u003csub\u003eNF\u003c/sub\u003e \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. These findings may be partially explained by the premise that additional motor units must be recruited to maintain force output as fatigue develops \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. When RT\u003csub\u003eF\u003c/sub\u003e protocols are performed with light loads (50% 1RM), this effect appear to be even more pronounced \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Conversely, when total volume is equalized within a session, similar EMG amplitude has been reported for both RT\u003csub\u003eF\u003c/sub\u003e and RT\u003csub\u003eNF\u003c/sub\u003e protocol, contradicting this initial assumption \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. In this context, our results showed that reductions of up to 20% in the RT\u003csub\u003eNF\u003c/sub\u003e produced EMG activity comparable to RT\u003csub\u003eF\u003c/sub\u003e, suggesting that the neuromuscular system was stimulated in a similar manner. This is consistent with findings in untrained women showing that full motor-unit recruitment occurs within 3\u0026ndash;5 repetitions of failure, indicating that RT\u003csub\u003eF\u003c/sub\u003e is not required \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Together, these results suggest a volume threshold beyond which additional repetitions offer no further neuromuscular benefit. Although EMG amplitude does not fully capture motor-unit recruitment \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, factors such as firing frequency and motor-unit synchronization also contribute. Notably, studies using EMG decomposition report recruitment of higher-threshold motor units when the vastus lateralis is fatigued \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eConsidering muscle strength, RT\u003csub\u003eF\u003c/sub\u003e caused a significant reduction in MVIC values immediately after session cessation compared to all other protocols. The reduction in MVIC may be partially explained by metabolite accumulation activating group III and IV afferents, which exert an inhibitory effect on the central nervous system \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. This afferent feedback decreases spinal excitability and, combined with the fatigue-induced reduction in muscle fiber conduction velocity \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e, results in a lower neural drive to the muscle \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Consequently, motoneuron firing rates decline, reducing the muscle\u0026rsquo;s capacity to generate maximal force. Additionally, in agreement with the MVIC response, FREQ\u003csub\u003eVL\u003c/sub\u003e and FREQ\u003csub\u003eRF\u003c/sub\u003e followed a similar pattern. EMG frequency-domain measures have frequently been proposed as indicators of muscle fatigue \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. This may reflect physiological processes occurring within the muscle, such as metabolic stress, ionic disturbances, or reduced membrane excitability \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Furthermore, the observed reduction in the EMG frequency domain after RT\u003csub\u003eF\u003c/sub\u003e is consistent with previous findings from fatiguing protocols \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. This response may be related to slow action potential propagation \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, induced by greater metabolic stress \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, which directly affects conductivity velocity. It has also been proposed that shifts in the EMG power spectrum toward lower frequencies, partly driven by decreases in intramuscular pH, contribute to reductions frequency-domain variables during protocols performed to failure \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe inverse relationship between blood lactate concentrations and training volume observed in the present study suggests that progressive reductions in volume imposed lower metabolic stress, potentially resulting in faster recovery across the post-exercise time points, as values returned toward baseline more rapidly. This finding aligns with the premise that lactate is a byproduct of the glycolytic system whose concentration is modulated according to training load arrangement (i.e., volume, intensity, time under tension) and acts as a potential signaling molecule capable of modulating beneficial adaptations in several tissues \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Nevertheless, performing RT\u003csub\u003eF\u003c/sub\u003e is thought to impose greater demands on energy systems and elicit higher anabolic signaling than RT\u003csub\u003eNF\u003c/sub\u003e\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e, thereby inducing higher metabolic stress and delaying recovery. In contrast, similar hypertrophic responses between RT\u003csub\u003eF\u003c/sub\u003e and RT\u003csub\u003eNF\u003c/sub\u003e protocols early reported \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e reinforce the reasoning that there is a threshold for metabolic stress beyond which no further beneficial effects are realized \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Our result appears to support this notion, suggesting that a 10\u0026ndash;20% reduction in volume may induce considerable metabolic demand without exceeding this threshold, which could still support hypertrophy adaptations. This reasoning warrants further investigations into chronic responses provided by RT\u003csub\u003eF\u003c/sub\u003e and RT\u003csub\u003eNF\u003c/sub\u003e at varying proximities to failure.\u003c/p\u003e \u003cp\u003eLastly, the maximal RPE scores observed after RT\u003csub\u003eF\u003c/sub\u003e align with the notion that greater perceptual effort is required to maintain performance as fatigue accumulates \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Higher RPE values during RT\u003csub\u003eF\u003c/sub\u003e compared with RT\u003csub\u003eNF\u003c/sub\u003e have also been reported previously \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Additionally, correlations between exercise tolerance and mental fatigue have been described \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Ultimately, the greater accumulation of metabolic by-products, such as lactate, observed in the presented study corroborates supports earlier associations between metabolic stress and increased RPE.\u003c/p\u003e \u003cp\u003eThis study presents several limitations. First, the relatively small sample size may have reduced the statistical power to detect subtle differences across conditions. Indeed, observed power values were high (\u0026ge;\u0026thinsp;0.93) across most outcome measures. Second, the randomization across five experimental conditions, while using one condition as a reference to determine volume reductions, may have introduced bias, as individual fatigue responses and volume-response relationships are not necessarily linear, even when counterbalanced. However, the experimental sessions were interspersed by one week, and the counterbalancing strategy likely minimized systematic order effects. Finally, the findings are limited to untrained young adults and may not generalize to other populations or to different exercise modalities. Nevertheless, this sample allows for a clearer observation of the acute physiological responses without the confounding influence of chronic adaptations. Lastly, there are strengths to be highlighted. For instance, the experimental protocols conducted in untrained individuals using an objective reduction in training volume referenced to RT\u003csub\u003eF\u003c/sub\u003e, along with the inclusion of both neuromuscular and metabolic assessments, address an important gap in literature. Furthermore, from a practical standpoint, these findings provide trainees and practitioners with evidence that choosing between RT\u003csub\u003eF\u003c/sub\u003e and RT\u003csub\u003eNF\u003c/sub\u003e imposes distinct demands that should be considered when prescribing RT.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn summary, choosing between RT\u003csub\u003eF\u003c/sub\u003e or varying proximities to failure in untrained individuals should be guided by the specific adaptations one aims to elicit. RT\u003csub\u003eF\u003c/sub\u003e appears to be preferable when the goal is to induce greater muscle swelling. However, when the priority is elevating the neuromuscular demand, reducing repetitions by up to 20% can provide a comparable stimulus, as demonstrated by the similar EMG amplitude observed. Therefore, performing a protocol in closer proximity to, but not reaching, failure may offer an alternative for achieving similar neuromuscular activation while minimizing metabolic stress.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCOMPETING INTERESTS\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFUNDING\u003c/h2\u003e \u003cp\u003eThis study was partially supported by the State Funding Agency of Minas Gerais, Brazil (FAPEMIG), processes APQ-00617-22, APQ-03875-23, APQ-03316-23. L.T.L is also supported by FAPEMIG (process BIP-00113-24). We also would like to thank Pr\u0026oacute;-Reitoria de Pesquisa da Universidade do Estado de Minas Gerais (UEMG).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eL.T.L. conceived and designed the study. J.M.G.F., G.P., I.J.S.R, I.H.A.L, L.C.S. and A.S.V. collected the data. K.C.P., A.V.L.L.C., Y.L.M.V and C.F.C.M.B collected and analyzed blood lactate concentrations. D.A.B., M.J.O.A. and L.R.D. performed formal analyses. H.L.R.S. and J.M.G.F drafted the manuscript. G.F.P., C.M.T.C., H.C.M.C., R.C.R.D and M.B.L. reviewed the manuscript and contributed technically to the quality of the manuscript. L.T.L. and H.L.R.S interpreted and validated the data. L.T.L., L.R.D. and C.F.C.M.B. obtained funding support. L.T.L., L.R.D. and C.F.C.M.B provided supervision and administrative support. All authors reviewed and approved the final manuscript text.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe database that supports the conclusions of this study is available from the corresponding author Lucas Tulio de Lacerda upon request (via the Email: [email protected]), without any restrictions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eOzaki, H. et al. 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Mental fatigue impairs physical performance in humans. \u003cem\u003eJ. Appl. Physiol. (1985)\u003c/em\u003e. \u003cb\u003e106\u003c/b\u003e, 857\u0026ndash;864. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1152/japplphysiol.91324.2008\u003c/span\u003e\u003cspan address=\"10.1152/japplphysiol.91324.2008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2009).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Electromyography, Muscle Fatigue, Muscle Strength, Ultrasonography","lastPublishedDoi":"10.21203/rs.3.rs-8387060/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8387060/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eResistance training to failure (RT\u003csub\u003eF\u003c/sub\u003e) acutely increases neuromuscular and metabolic demands but also induces fatigue that may compromise subsequent training stimuli. Small reductions in volume at the same intensity, while avoiding failure, may attenuate fatigue while preserving training stimuli. Therefore, this study compared the acute effects of RT\u003csub\u003eF\u003c/sub\u003e and non-failure resistance training (RT\u003csub\u003eNF\u003c/sub\u003e) during knee extension exercise. Eleven untrained men completed five RT\u003csub\u003eNF\u003c/sub\u003e conditions, each involving an individualized reduction ranging from 10\u0026ndash;50% relative to number of repetitions performed during RT\u003csub\u003eF\u003c/sub\u003e. Outcomes included maximum voluntary isometric contraction (MVIC), electromyography (EMG), muscle swelling of the rectus femoris (RF) and vastus lateralis (VL), blood lactate concentration, and perceived exertion (RPE). RT\u003csub\u003eF\u003c/sub\u003e elicited greater increases in muscle cross-sectional area of both RF and VL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) compared with all RT\u003csub\u003eNF\u003c/sub\u003e conditions. EMG amplitude was higher in RT\u003csub\u003eF\u003c/sub\u003e than in the 30\u0026ndash;50% reduction conditions (p\u0026thinsp;=\u0026thinsp;0.01 for VL and RF), while MVIC (p\u0026thinsp;=\u0026thinsp;0.02) and EMG frequency differed across protocols (p\u0026thinsp;=\u0026thinsp;0.02 for RF; p\u0026thinsp;=\u0026thinsp;0.03 for VL). Additionally, lactate and RPE (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) responses were highest following RT\u003csub\u003eF\u003c/sub\u003e. In summary, RT\u003csub\u003eF\u003c/sub\u003e maximizes muscle swelling and metabolic stress, whereas performing repetitions up to 20% short of failure provides a comparable neuromuscular stimulus, while minimizing metabolic stress.\u003c/p\u003e","manuscriptTitle":"Training to failure vs not-to-failure with progressive volume reduction: neuromuscular and metabolic responses in untrained individuals","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-12 09:05:46","doi":"10.21203/rs.3.rs-8387060/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"010e2894-6a16-4b1d-8c14-dc7d5d263f9a","owner":[],"postedDate":"January 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":60813181,"name":"Health sciences/Health care"},{"id":60813182,"name":"Biological sciences/Neuroscience"},{"id":60813183,"name":"Biological sciences/Physiology"}],"tags":[],"updatedAt":"2026-03-18T07:12:45+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-12 09:05:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8387060","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8387060","identity":"rs-8387060","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}