The purpose of this study was to analyse the validity and reliability of a novel iPhone app (named: PowerLift) for the measurement of mean velocity on the bench-press exercise. Additionally, the accuracy of the estimation of the 1-Repetition maximum (1RM) using the load–velocity relationship was tested. To do this, 10 powerlifters (Mean (SD): age = 26.5 ± 6.5 years; bench press 1RM · kg⁻¹ = 1.34 ± 0.25) completed an incremental test on the bench-press exercise with 5 different loads (75–100% 1RM), while the mean velocity of the barbell was registered using a linear transducer (LT) and Powerlift. Results showed a very high correlation between the LT and the app (r = 0.94, SEE = 0.028 m · s⁻¹) for the measurement of mean velocity. Bland–Altman plots (R² = 0.011) and intraclass correlation coefficient (ICC = 0.965) revealed a very high agreement between both devices. A systematic bias by which the app registered slightly higher values than the LT (P < 0.05; mean difference (SD) between instruments = 0.008 ± 0.03 m · s⁻¹). Finally, actual and estimated 1RM using the app were highly correlated (r = 0.98, mean difference (SD) = 5.5 ± 9.6 kg, P < 0.05). The app was found to be highly valid and reliable in comparison with a LT. These findings could have valuable practical applications for strength and conditioning coaches who wish to measure barbell velocity in the bench-press exercise.

The purpose of this study was to analyze the validity, reliability and accuracy of new wearable and smartphone-based technology for the measurement of barbell velocity in resistance training exercises. To do this, 10 highly trained powerlifters (age = 26.1 3.9yrs.) performed 11 repetitions with loads ranging 50-100% of the 1-Repetition maximum in the bench-press, full-squat and hip-thrust exercises while barbell velocity was simultaneously measured using a linear transducer (LT), two Beast wearable devices (one placed on the subjects’ wrist –BW–, and the other one directly attached to the barbell –BB–) and the iOS PowerLift app. Results showed a very high correlation between the LT and BW (r = 0.94-0.98, SEE = 0.04-0.07 m/s), BB (r = 0.97-0.98, SEE = 0.04-0.05 m/s) and the PowerLift app (r = 0.97-0.98, SEE = 0.03-0.05 m/s) for the measurement of barbell velocity in the three exercises. Paired samples T-test revealed systematic biases between the LT and BW, BB and the app in the hip-thrust, between the LT and BW in the full-squat and between the LT and BB in the bench-press exercise (p < 0.001). Moreover, the analysis of the linear regression on the Bland-Altman plots showed that the differences between the LT and BW (R2 = 0.004-0.03), BB (R2 = 0.007-0.01) and the app (R2 = 0.001-0.03) were stable across the whole range of velocities analyzed. Finally, the reliability of the BW (ICC = 0.910-0.988; Cronbach’s α = 0.952-0.975), BB (ICC = 0.922-0.990; Cronbach’s α = 0.958-0.981) and the app (ICC = 0.928-0.989; Cronbach’s α = 0.961-0.981) for the measurement of the two repetitions performed with each load were almost the same than that observed with the LT (ICC = 0.937-0.990; Cronbach’s α = 0.961-0.981). Both the Beast wearable device and the PowerLift app were highly valid, reliable and accurate for the measurement of barbell velocity in the bench-press, full-squat and hip-thrust exercises. These results could have potential practical applications for strength & conditioning coaches who wish to measure barbell velocity during resistance training.

Purpose: To analyze the load-, force-, and power-velocity relationships and determine the load that optimizes power output on the pull-up exercise. Methods: Eighty-two resistance-trained men (age 26.8 ± 5.0 y; pull-up 1-repetition maximum [1-RM; normalized per kg of body mass] 1.5 ± 0.34) performed 2 repetitions with 4 incremental loads (range 70–100%1-RM) in the pull-up exercise while mean propulsive velocity (MPV), force (MPF), and power (MPP) were measured using a linear transducer. Relationships between variables were studied using first- and second-order least-squares regression, and subjects were divided into 3 groups depending on their 1-RM for comparison purposes. Results: Almost perfect individual load-velocity (R² = .975 ± 0.02), force-velocity (R² = .954 ± 0.04), and power-velocity (R² = .966 ± 0.04) relationships, which allowed to determine the velocity at each %1-RM, as well as the maximal theoretical force (F0), velocity (V0), and power (Pmax) for each subject were observed. Statistically significant differences between groups were observed for F0 (P < .01) but not for MPV at each %1-RM, V0, and Pmax (P > .05). In addition, high correlations between F0 and 1-RM (r = .811) and V0 and Pmax (r = .865) were observed. Finally, the authors observed that the load that maximized MPP was 71.0% ± 6.6%1-RM. Conclusions: The very high load-velocity, force-velocity, and power-velocity relationships enables estimation of 1-RM by measuring movement velocity, as well as determination of maximal force, velocity, and power capabilities. This information could be of great interest to strength and conditioning coaches who wish to monitor pull-up performance.

Balsalobre-Fernández, C, Muñoz-López, M, Marchante, D, and García-Ramos, A. Repetitions in reserve and rate of perceived exertion increase the prediction capabilities of the load-velocity relationship. J Strength Cond Res 35(3): 724–730, 2021—This study aimed to (a) analyze the relationships between relative load (i.e., %1 repetition maximum; 1RM) and movement velocity, repetitions in reserve (RIR) and rate of perceived exertion (RPE) in competitive powerlifters and (b) examine whether a multiple linear regression model with the movement velocity, RIR, and RPE as predictor variables could improve the goodness of fit of the load-velocity relationship. Ten competitive powerlifters performed an incremental loading test (from 50 to 100% 1RM) on the full-squat, hip-thrust, and bench press exercises. Barbell velocity was measured using a linear position transducer, while RIR and RPE were registered immediately after each set. Velocity (r ²: 0.747–0.887), RIR (r ²: 0.857–0.928), and RPE (r ²: 0.908–0.933) were moderately to highly related to relative load. A higher amount of variance of the relative load was explained when the RIR and RPE were added to velocity in a multiple regression model in comparison with the load-velocity relationship (r ²: 0.924–0.947). Moreover, it was observed that, in all cases, individual load-velocity, load-RIR, and load-RPE relationships had higher r ² scores than the generalized load-velocity relationship. Incorporating the RIR and RPE as predictors of the relative load along with movement velocity into a multiple linear regression was shown to provide better estimations of the %1RM than using a linear load-velocity relationship.

Background: Skeletal muscle hypertrophy has traditionally been attributed to transient spikes in translational efficiency governed by the mTORC1 signaling cascade. However, contemporary molecular evidence reveals that sustained macroscopic growth is strongly associated with the physical expansion of the translational machinery itself. The activation of RNA Polymerase I and the subsequent synthesis of new ribosomes represent a critical biological correlate for long-term protein accretion. Objective: This comprehensive review critically examines ribosome biogenesis as the primary structural bottleneck shaping human skeletal muscle adaptation, differentiating acute signaling efficiency from chronic translational capacity. Synthesis: We dissect the molecular orchestration of nucleolar expansion and critically address the pervasive methodological pitfalls plaguing the current literature. Specifically, we highlight the moving denominator paradox, demonstrating how flawed bulk RNA normalization strategies systematically underestimate true ribosomal accretion in actively growing tissue. By synthesizing in vivo human evidence, we delineate how age, concurrent training, and training volume modulate this structural capacity. We further establish the high-responder phenotype as a function of successful nucleolar adaptation. Finally, we explore advanced molecular frontiers, including epigenetic chromatin remodeling, ribosomal heterogeneity as an emerging frontier, non-coding RNA regulation, and nuclear mechanotransduction via the YAP/TAZ axis. Conclusions: Acute anabolic signaling is merely permissive. Permanent hypertrophic adaptation fundamentally relies on overcoming the translational capacity bottleneck. Shifting the scientific and applied focus toward the architectural expansion of the nucleolus will fundamentally redefine practical hypertrophy programming and clinical interventions for sarcopenia.

Marine halophytes are gaining attention as a source of plant-derived bioactive compounds with potential applications across nutraceuticals, functional foods, and preventive nutrition. Among them, Salicornia europaea L. is a coastal succulent whose adaptation to hypersaline environments shapes a distinctive phytochemical profile of pharmacological interest. This narrative review integrates current evidence on the bioactive composition, mechanistic activities, and translational relevance of S. europaea and related Salicornia species. Their secondary metabolome includes flavonols, isorhamnetin glycosides, hydroxycinnamic acids, oleanane-type triterpene saponins, fermentable polysaccharides, carotenoids, and a mineral-rich ionic matrix. Reported activities span antioxidant, anti-inflammatory, vascular-protective, anti-adipogenic, glycaemic-modulating, antimicrobial, and microbiome-related effects, mediated through pathways involving NF-κB, PPAR-γ, endothelial nitric oxide signalling, and short-chain fatty acid production. Beyond its individual phytochemical components, the matrix as a whole may also support sodium-reduction strategies in food formulation, providing a complementary nutritional rationale for its incorporation as a functional ingredient. Despite a coherent body of mechanistic and preclinical findings, clinical evidence remains limited, particularly regarding long-term efficacy, dose standardisation, and bioavailability in humans. Future work should prioritise adequately powered intervention trials and standardised characterisation of marine halophyte bioactives to clarify their evidence-based role in functional food development and future precision nutrition applications.