Weakley, J, Chalkley, D, Johnston, R, García-Ramos, A, Townshend, A, Dorrell, H, Pearson, M, Morrison, M, and Cole, M. Criterion validity, and interunit and between-day reliability of the FLEX for measuring barbell velocity during commonly used resistance training exercises. J Strength Cond Res 34(6): 1519–1524, 2020—The aim of this study was to assess the criterion validity, interunit reliability (accounting for technological and biological variance), and between-day reliability of a novel optic laser device (FLEX) for quantifying mean concentric velocity. To assess the validity against a three-dimensional motion capture system and interunit reliability with both technological and biological variation, 18 men and women completed repetitions at 20, 40, 60, 80, 90, and 100% of one repetition maximum in the free-weight barbell back squat and bench press. To assess interunit (technological only) reliability, a purpose-built, calibrated rig completed a set protocol with 2 devices. To assess between-day reliability of the technology, the same protocol was repeated 21 days later. Standardized bias, typical error of the estimate (TEE; %), and Pearson's correlation coefficient (r) were used to assess validity, whereas typical error and coefficient of variation (CV%) were calculated for reliability. Overall, TEE (±90 CL) between the FLEX and criterion measure was 0.03 (±0.004) and 0.04 (±0.005) m·s⁻¹ in the back squat and bench press, respectively. For measures of reliability, overall interunit technological variance (CV% [± 90% confidence interval]) was 3.96% (3.83–4.12) but increased to 9.82% (9.31–10.41) and 9.83% (9.17–10.61) in the back squat and bench press, respectively, when biological variance was introduced. Finally, the overall between-day reliability was 3.77% (3.63–3.91). These findings demonstrate that the FLEX provides valid and reliable mean concentric velocity outputs across a range of velocities. Thus, practitioners can confidently implement this device for the monitoring and prescription of resistance training loads.

Purpose : To determine whether menstrual-cycle symptoms are associated with sleep in elite female athletes. Methods : Sleep was assessed for a minimum of 25 nights (range = 25–31) using activity monitoring and sleep diaries. Menstrual-cycle symptoms were collected over the same duration in 12 elite female professional soccer players. Generalized estimating equations were used to examine the relationship between the day of the menstrual cycle (from day 1) and total menstrual-cycle symptoms on sleep characteristics. Results : There was a significant relationship between sleep duration and the day of the menstrual cycle ( P = .042) and total symptoms reported that day ( P < .001), with sleep duration increasing by 21 minutes for every symptom reported. There was a negative day × symptom interaction on sleep duration ( P = .004), indicating that with increased symptoms, the day of the menstrual cycle had a smaller relationship with sleep duration. Sleep efficiency ( P = .950), wake after sleep onset ( P = .217), and subjective sleep quality ( P = .080) were not related to the day of the menstrual cycle. The total symptoms reported had no relationship with sleep efficiency ( P = .220), subjective sleep quality ( P = .502), or sleep latency ( P = .740) but did significantly relate to wake after sleep onset ( P < .001), with a significant day × symptom interaction ( P < .001). Conclusions : Sleep duration increased from day 1 of the menstrual cycle and was associated with the number of menstrual-cycle symptoms reported. All other sleep metrics remained unchanged; however, total symptoms reported were related to wake after sleep onset. Monitoring and managing menstrual-cycle symptoms should be encouraged due to a potential relationship with sleep characteristics.

Exercise velocity and relative velocity loss thresholds (VLTs) are commonly used in velocity-based resistance training. This study aims to quantify the between-day reliability of 10%, 20%, and 30% VLTs on kinetic and kinematic outputs, changes in external load, and repetition characteristics in well-trained athletes. Using a repeated, counter-balanced crossover design, twelve semi-professional athletes completed five sets of the back squat with an external load corresponding to a mean concentric velocity of ~0.70 m·s⁻¹ and a VLT applied. The testing sessions were repeated after four weeks of unstructured training to assess the long-term reliability of each VLT. A coefficient of variation (CV) 10% (CV: 11.14–14.92%). Alternatively, the repetitions completed within each set showed large variation (CV: 18.92–67.49%). These findings demonstrate that by utilizing VLTs, kinetic and kinematic outputs can be prescribed and replicated across training mesocycles. Thus, for practitioners wishing to reliably control the kinetic and kinematic stimulus that is being applied to their athletes, it is advised that a velocity-based approach is used.

We examined factors that inform iron-deficiency screening practices in female athletes, with a focus on the menstrual cycle. Twenty-four National Rugby League athletes attended a 5-week training camp (age 21.6 ± 3.4 years old, body mass: 76.3 ± 12.1 kg, height: 164.9 ± 4.6 cm). Athletes were either naturally cycling (athleteNC; n = 11) or using hormonal contraception (athleteHC; n = 13). Venous blood samples were collected during Phases 1, 2, and 4 of the menstrual cycle in athleteNC for determination of iron status. Three equally spaced, corresponding time points were sampled in athleteHC. Every 48 hr, a capillary blood sample was collected and analyzed for ferritin, hepcidin, creatine kinase, and C-reactive protein. No differences across menstrual phases or groups were evident for ferritin, hepcidin, transferrin or hemoglobin ( p > .05). Serum iron (12.9 ± 4.6 μmol/L to 16.9 ± 8.5 μmol/L; p = .045) and transferrin saturation (17.3% ± 7.8% to 22.1% ± 14.5%; p = .041) increased from Phase 1 to Phase 2 in athleteNC only, with no change seen in athleteHC. Ferritin (−16%; p < .001) and hepcidin (−23%; p < .001) declined across the training camp in all athletes. Concentrations of C-reactive protein ( p = .039) were consistently higher in athleteHC compared with athleteNC, whereas creatine kinase activity were similar between groups ( p = .140). Our findings did not identify clear menstrual cycle phase–related differences in markers of iron status or regulation, suggesting that the influence of cycle phase may be relatively small compared with other sources of variation. Practitioners should be mindful that athletes using hormonal contraceptives may report with greater C-reactive protein concentrations than naturally cycling athletes.

Nicotinamide adenine dinucleotide (+)-dependent class III histone deacetylases, widely known as sirtuins (SIRTs), have been found to play key functions in a wide range of biological processes implicated in ageing processes. The downregulation of some specific SIRTs was reported in ageing and in some neurological diseases such as Alzheimer’s disease. SIRT modulator factors, such as diet, exercise and various natural compounds, have recently emerged as a potential new avenue of therapy to modify the progression of Alzheimer’s disease and delay some ageing effects. This review synthesises recent advances in the understanding of the modulatory effects of SIRTs in the context of healthy ageing with a particular focus on cognitive function and implications for Alzheimer’s disease.

Purpose : To describe objective sleep quantity and quality and nocturnal physiological measures in elite and recreational female athletes and compare between and within groups on weekdays and weekends. Methods : Sleep was assessed over 4 to 8 nights (mean [SD]: 7 [1] nights) in 21 elite and 27 recreational athletes using partial polysomnography in their home environment. Linear mixed models compared measures between groups and day (weekends: Friday and Saturday night, weekdays: Sunday to Thursday night). Results : Sleep variables were similar between groups. Elite athletes obtained a lower minimum heart rate (estimate ± SE: −5 ± 2 beats/min, Cohen effect size: d = −0.3 ± 0.3, significance: P = .03) and blood oxygen saturation (−1.4 ± 0.7%, d = −0.3 ± 0.3, P = .045) than recreational athletes. On weekdays, elite athletes obtained a greater percentage of nonrapid eye movement stages 1 and 2 sleep (light sleep: 4 ± 1.2%, d = 0.2 ± 0.1, P = .001) and a lower percentage of rapid eye movement sleep (−2.4 ± 1.2%, d = −0.1 ± 0.1, P = .04) than on weekends. On weekdays, both elite and recreational athletes obtained earlier sleep onset time than on weekends (elite mean ± SD: 22:38 [1:03] hh:mm vs 22:52 [1:45] hh:mm, d = −0.24 ± 0.12, P ≤ .001; recreational 22:11 [0:59] hh:mm vs 22:41 [1:16] hh:mm, d = −0.19 ± 0.12, P = .002). Only recreational athletes obtained earlier sleep offset times (5:37 [1:27] hh:mm vs 6:23 [1:10] hh:mm, d = −0.19 ± 0.12, P = .002) on weekdays than on weekends. Conclusions : Sleep outcomes did not vary by athlete level, but nocturnal physiological measures did. Sleep outcomes also differed within each group between weekends and weekdays, suggesting strategies may be required to minimize sleep irregularity.