Krzysztof Kusy

Background/Objectives : Submaximal exercise tests may be preferred over maximal tests for many reasons related to health or performance. It is unknown if a submaximal perceptually regulated exercise test is a valid assessment of maximal oxygen uptake ( ) in master athletes. We assessed the validity of a submaximal perceptually regulated exercise test in predicting in masters track-and-field athletes. Methods : Fifty-five athletes ( n = 21 females, age = 63 ± 11 years; ) competing at the World Masters Athletics Championships completed both a graded exercise test to volitional exhaustion to directly measure and a submaximal perceptually regulated exercise test, wherein the athletes self-regulated exercise intensity based on perceived exertion with collected at four stages, ranging from very light to hard/heavy, and extrapolated to ratings of perceived exertion (RPE) 18, 19, and 20, and to age-predicted maximal heart rate (HR _max ). Results : Extrapolation to RPE 20 significantly overpredicted (+3.7 ml·kg ⁻¹ ·min ⁻¹ ; p = .02), while values attained from extrapolations to RPE 18, RPE 19, and age-predicted HR _max were not significantly different from values achieved during the graded exercise test ( p > .05). Correlations for predicting ranged from .68 to .71. Standard errors of the estimate for predicting ranged from 8.6 to 11.3 ml·kg ⁻¹ ·min ⁻¹ . Conclusions : Although predicted from a perceptually regulated exercise test is moderately correlated with actual , the standard errors of the estimate is too large to accurately track short-term changes in with aging or training. Significance/Implications : A perceptually regulated exercise test for estimating in masters athletes may not provide the necessary level of accuracy for tracking short-term changes in .

Aims: The aim of the study was to investigate the effect of systematic lumbar traction, applied in 20 sessions over four weeks, on the size of vertebrae, bone mineral density (BMD), and bone turnover markers in women with chronic low back pain (LBP).Methods: A total of 30 women with low back pain underwent 20 sessions of lumbar traction with a load of 25% to 30% of their body weight. Total body and lumbar spine BMD was measured using dual-energy X-ray absorptiometry, and bone turnover markers were determined using enzyme-linked immunosorbent assay (ELISA) with serum samples collected before the first traction session and 72 hours after the last traction session.Results: After traction, decreased BMD and T-scores, a decreased mean vertebra width, and an increased mean height of L1–L4 segments were observed. The concentration of cross-linked C-telopeptide of type I collagen (CTXI) increased, while the concentration of receptor activator for nuclear factor κ B ligand (RANKL) decreased significantly after four weeks of traction. Sclerostin and procollagen 1 N-terminal propeptide (P1NP) concentrations remained unchanged.Conclusion: Our study is the first to show the influence of traction forces on BMD and markers of bone metabolism. Future research with a longer follow-up period after traction is needed to better explore the direction of change.Cite this article: Bone Joint Res 2025;14(8):674–684.

This study aimed to determine whether obesity influences the effects of traction therapy on pain, disability, lumbar mobility, and the biomechanical and viscoelastic properties (BVPs) of tissues in the lumbar region in women with low back pain (LBP). Women aged 34 to 50 years with chronic LBP and obesity (n = 26) or normal body weight (bw; n = 17) underwent 20 traction therapy sessions. LBP (on a visual analog scale), Oswestry Disability Index, BVPs, lumbar spine mobility, and trunk tissue fat were assessed before and then 3 days and 3 months after therapy. Two-way repeated measures ANOVAs were used. Pain and disability were significantly decreased (P < .01) and anterior lumbar flexion was increased (P < .05) after treatment and maintained at this level for 3 months in both women with obesity and normal body mass index (BMI). However, while stiffness was only reduced in women with normal BMI after treatment (P < .05), this effect was not maintained at follow-up. The mobility in posterior and lateral flexions and rotations did not change. All BVPs correlated with trunk tissue fat content (P < .01). The outcomes of traction therapy with continuous mode at a force of 25% to 30% of the patient's bw were not different for women with BMI ≥ 30 and 2. Only the effect on muscle stiffness seems to be more beneficial for women without obesity. However, myotonometric results are strongly related to trunk fat content, subject to a potential measurement error in women with obesity.

Background/Objectives: Free amino acids substantially contribute to energy metabolism. Also, their profile may identify (over)training status and effectiveness. The long-term effects of speed-power training on plasma free amino acid (PFAA) profiles are not known. We aimed to observe variations in PFAA levels in high-performance sprinters in a six-month training cycle. Methods: Ten male athletes (24.6 ± 3.3 years) were examined during four training phases: transition (1 month), general preparation (2 months), specific preparation (1 month), and pre-competition/competition (2 months). Venous blood was collected at rest, after exhaustive exercise, and recovery. Forty-two PFAAs were analyzed by the LC-ESI-MS/MS method. Results: Significant decreases in resting concentrations were observed between the transition and competition phases for glutamine (762 ± 117 vs. 623 ± 53 μmol∙L⁻¹; p < 0.001, η² = 0.47) and histidine (89 ± 15 vs. 75 ± 10 μmol∙L⁻¹; p = 0.010, η² = 0.27), whereas β-alanine (30 ± 7 vs. 41 ± 9 μmol∙L⁻¹; p = 0.024, η² = 016) and sarcosine (3.6 ± 0.4 vs. 4.8 ± 0.6 μmol∙L⁻¹; p = 0.006, η² = 0.188) levels increased. Between the specific and competition phases, significant decreases in the resting levels of 1-methylhistidine (22.1 ± 19.4 vs. 9.6 ± 8.8 μmol∙L⁻¹; p = 0.14, η² = 0.19), 3-methylhistidine (7.1 ± 1.5 vs. 6.5 ± 1.6 μmol∙L⁻¹; p = 0.009, η² = 0.18), citrulline (40 ± 10 vs. 29 ± 4 μmol∙L⁻¹; p = 0.05, η² = 0.29), and ornithine (74 ± 15 vs. 56 ± 10 μmol∙L⁻¹; p = 0.015, η² = 185) were noticed. Also, for β-alanine and sarcosine, the pattern of response to exercise strongly changed between the training phases. Blood ammonia levels at exhaustion decreased between the transition and competition phases (32 ± 4 vs. 23 ± 5 μmol∙L⁻¹; p < 0.001, η² = 0.67), while lactate, the phenylalanine–tyrosine ratio, the glutamine–glutamate ratio, hematological parameters, and cardiorespiratory indices remained at similar levels. Conclusions: Speed-power training seems to affect PFAAs involved in skeletal muscle metabolic pathways responsible for neutralizing toxic ammonia (glutamine, arginine, citrulline, ornithine), attenuating the deleterious effects of H⁺ ions (histidine, β-alanine), and reducing exercise-induced protein breakdown (1- and 3-methylhistidine). Our findings suggest that sprint-oriented training supports metabolic pathways that are responsible for the removal of harmful metabolites produced during exercise.

Circulating blood is an important plasma free amino acids (PFAAs) reservoir and a pivotal link between metabolic pathways. No comparisons are available between athletes with opposite training adaptations that include a broader spectrum of both proteinogenic and non-proteinogenic amino acids, and that take into account skeletal muscle mass. We hypothesized that the levels of the exercise-induced PFAAs concentration are related to the type of training-related metabolic adaptation. We compared highly trained endurance athletes (n = 11) and sprinters (n = 10) aged 20‒35 years who performed incremental exercise until exhaustion. Venous blood was collected before and during the test and 30-min recovery (12 samples). Forty-two PFAAs were assayed using LC-ESI-MS/MS technique. Skeletal muscle mass was estimated using dual X-ray absorptiometry method. Glutamine and alanine were dominant PFAAs throughout the whole exercise and recovery period (~350‒650 μmol∙L^-1). Total, combined proteinogenic, non-essential, and non-proteinogenic PFAAs levels were significantly higher in endurance athletes than sprinters (ANOVA group effects: p = 0.007, η² = 0.321; p = 0.011, η² = 0.294; p = 0.003, η² = 0.376; p = 0.001, η² = 0.471, respectively). The exercise response was more pronounced in endurance athletes, especially for non-proteinogenic PFAAs (ANOVA interaction effect: p = 0.038, η² = 0.123). Significant between-group differences were observed for 19 of 33 PFAAs detected, including 4 essential, 7 non-essential, and 8 non-proteinogenic ones. We demonstrated that the PFAAs response to incremental aerobic exercise is associated with the type of training-related metabolic adaptation. A greater turnover and availability of circulating PFAAs for skeletal muscles and other body tissues is observed in endurance- than in sprint-trained individuals. Non-proteinogenic PFAAs, despite low concentrations, also respond to exercise loads, indicating their important, though less understood role in exercise metabolism. Our study provides additional insight into the exercise-induced physiological response of PFAAs, and may also provide a rationale in discussions regarding dietary amino acid requirements in high-performance athletes with respect to sports specialization.

Background/Objectives: A high level of specific metabolic capacity is essential for maximal sprinting in both male and female athletes. Various factors dictate sex differences in maximal power production and energy utilization. This study aims to compare the contribution of energy systems between male and female athletes with similar sport-specific physiological adaptations during a 15-s sprint exercise. Methods: The endurance group consisted of 17 males (23 ± 7 y) and 17 females (20 ± 2 y). The speed-power group included 14 males (21.1 ± 2.6 y) and 14 females (20 ± 3 y). The contribution of phosphagen, glycolytic, and aerobic systems was determined using the three-component PCr-LA-O₂ method. Results: Significant differences were observed in the energy expenditure for all systems and total energy expenditure between males and females in both groups (p = 0.001–0.013). The energy expenditure in kJ for individual systems (phosphagen–glycolytic–aerobic) was 35:25:7 vs. 20:16:5 in endurance males vs. female athletes, respectively. In the speed-power group, male athletes expended 33:37:6 kJ and female athletes expended 21:25:4 kJ, respectively. The percentage proportions did not differ between males and females in any system. The contribution of the phosphagen–glycolytic–aerobic systems was 52:37:11 vs. 48:39:13 in endurance male and female athletes, respectively. For speed-power males vs. female athletes, the proportions were 42:50:8 vs. 41:50:9, respectively. Conclusions: Despite the differences in body composition, mechanical output, and absolute energy expenditure, the energy system contribution appears to have a similar metabolic effect between male and female athletes engaged in sprint exercises with similar sport-related adaptations. The magnitude and profile of sex differences are related to sports discipline.

Emerging research links the endocannabinoid system to gut microbiota, influencing nociception, mood, and immunity, yet the molecular interactions remain unclear. This study focused on the effects of probiotics on ECS markers—cannabinoid receptor type 2 (CB2) and fatty acid amide hydrolase (FAAH)—in dancers, a group selected due to their high exposure to physical and psychological stress. In a double-blind, placebo-controlled trial (ClinicalTrials.gov NCT05567653), 15 dancers were assigned to receive either a 12-week regimen of Lactobacillus helveticus Rosell-52 and Bifidobacterium longum Rosell-17 or a placebo (PLA: n = 10, PRO: n = 5). There were no significant changes in CB2 (probiotic: 0.55 to 0.29 ng/mL; placebo: 0.86 to 0.72 ng/mL) or FAAH levels (probiotic: 5.93 to 6.02 ng/mL; placebo: 6.46 to 6.94 ng/mL; p > 0.05). A trend toward improved sleep quality was observed in the probiotic group, while the placebo group showed a decline (PRO: from 1.4 to 1.0; PLA: from 0.8 to 1.2; p = 0.07841). No other differences were noted in assessed outcomes (pain and fatigue). Probiotic supplementation showed no significant impact on CB2 or FAAH levels, pain, or fatigue but suggested potential benefits for sleep quality, suggesting an area for further research.

The study aimed to evaluate the lower limb skin temperature (Tsk) and blood concentrations of lactate (LA) and ammonia (NH₃) during exercise and recovery. Eleven elite sprint athletes (25 ± 3.4 yrs) and 11 elite endurance athletes (24.45 ± 5.4 yrs) performed an incremental running test until exhaustion. Body composition was estimated using the DXA method. Thermograms of the anterior and posterior surfaces of the lower limbs were recorded at rest, before each test stage (every 3 min, starting from 10 km h⁻¹ and increasing by 2 km h⁻¹), and in the 5th, 10th, 15th, 20th, and 30th minute of recovery. Endurance athletes had a higher maximum oxygen uptake than sprint athletes (5.0 ± 0.7 vs 4.3 ± 0.4 l·kg⁻¹, p = 0.018), lower percentage of lean content (79 ± 2 vs 83 ± 2%, p < 0.001), and a higher percentage of fat content in the lower limbs (17 ± 2 vs 12 ± 2%, p < 0.001). In both groups, a significant decrease in Tsk was observed compared to resting value (endurance athletes—31.5 ± 0.6 °C; sprint athletes—32.3 ± 0.6 °C), during exercise (p < 0.001) and rewarming during recovery (p < 0.001). However, endurance athletes had a lower Tsk than sprint athletes at the exhaustion point (30.0 ± 1.1 vs 31.6 ± 0.8 °C, p < 0.05) and the pattern of change in Tsk differed between groups (p < 0.001). Tsk in the endurance athletes group decreased throughout the exercise protocol and returned more rapidly to initial values during recovery, while Tsk in the sprint group stabilised between moderate intensity and exhaustion, recovering more slowly after exercise. Both LA (endurance athletes—max 10.2 ± 1.5; sprint athletes—max 10.1 ± 1.4 mmol⋅L⁻¹, p < 0.001) and NH₃ (endurance athletes—max 75.6 ± 11.5; sprint athletes—max 76.7 ± 9.0 mmol⋅L⁻¹, p < 0.001) increased during exercise and decreased during recovery (p < 0.001). During exercise, lower levels and slower increases in LA were observed during exercise in the endurance athletes’ group (p < 0.05). A negative correlation was revealed between Tsk and fat percentage (r = −0.43 to −0.71, p < 0.05). Tsk was positively correlated with LA during recovery (r = 0.43 to 0.48, p < 0.05), and negatively during recovery (r = −0.45 to −0.54, p < 0.05). Differences between groups in maximum aerobic capacity, the pattern of change in Tsk, and the correlation between Tsk and LA suggest that individuals who decrease less Tsk during exercise and higher Tsk during recovery are those with better aerobic capacity. In addition, athletes with less body fat dissipate heat from their tissues more efficiently.