Retrospective Analysis of Training Intensity Distribution Based on Race Pace Versus Physiological Benchmarks in Highly Trained Sprint Kayakers

Background Research results on the training intensity distribution (TID) in endurance athletes are equivocal. This non-uniformity appears to be partially founded in the different quantification methods that are implemented. So far, TID research has solely focused on sports involving the lower-body muscles as prime movers (e.g. running). Sprint kayaking imposes high demands on the upper-body endurance capacity of the athlete. As there are structural and physiological differences between upper- and lower-body musculature, TID in kayaking should be different to lower-body dominant sports. Therefore, we aimed to compare the training intensity distribution during an 8-wk macrocycle in a group of highly trained sprint kayakers employing three different methods of training intensity quantification. Methods Heart rate (HR) and velocity during on-water training of nine highly trained German sprint kayakers were recorded during the final 8 weeks of a competition period leading to the national championships. The fractional analysis of TID was based on three zones (Z) derived from either HR (TIDBla-HR) or velocity (TIDBla-V) based on blood lactate (Bla) concentrations (Z1 ≤ 2.5 mmol L−1 Bla, Z2 = 2.5–4.0 mmol L−1 Bla, Z3 ≥ 4.0 mmol L−1 Bla) of an incremental test or the 1000-m race pace (TIDRace): Z1 ≤ 85% of race pace, Z2 = 86–95% and Z3 ≥ 95%. Results TIDBla-V (Z1: 68%, Z2: 14%, Z3: 18%) differed from TIDBla-HR (Z1: 91%, Z2: 6%, Z3: 3%) in each zone (all p < 0.01). TIDRace (Z1: 73%, Z2: 20%, Z3: 7%) differed to Z3 in TIDBla-V (p < 0.01) and all three TIDBla-HR zones (all p < 0.01). Individual analysis revealed ranges of Z1, Z2, Z3 fractions for TIDBla-HR of 85–98%, 2–11% and 0.1–6%. For TIDBla-V, the individual ranges were 41–82% (Z1), 6–30% (Z2) and 8–30% (Z3) and for TIDRace 64–81% (Z1), 14–29% (Z2) and 4–10% (Z3). Conclusion The results show that the method of training intensity quantification substantially affects the fraction of TID in well-trained sprint kayakers. TIDRace determination shows low interindividual variation compared to the physiologically based TIDBla-HR and TIDBla-V. Depending on the aim of the analysis TIDRace, TIDBla-HR and TIDBla-V have advantages as well as drawbacks and may be implemented in conjunction to maximize adaptation.

Influence of coracoglenoid space on scapular neck fracture stability: biomechanical study

Background The anatomical variation of the coracoglenoid space has the potential to influence the stability of scapular neck fractures. This paper aimed to investigate the mechanical mechanism underlying the influence of different coracoglenoid space types on scapular neck fractures by morphometric analysis and biomechanical experiments. Methods The morphology of 68 dried scapulae (left: 36; right: 32) was studied. Two variables, the length of the coracoglenoid distance (CGD) and the coracoglenoid notch (CGN), were measured. The distribution of CGN/CGD × 100% was used to identify the morphology of the coracoglenoid space. Each specimen was tested for failure under static axial compression loading. The average failure load, stiffness, and energy were calculated. Results Two coracoglenoid space types were identified. The incidence of Type I (‘‘hook’’ shape) was 53%, and that of Type II (‘‘square bracket’’ shape) was 47%. The CGD and CGN were significantly higher for type I than type II (13.81 ± 0.74 mm vs. 11.50 ± 1.03 mm, P < 0.05; 4.74 ± 0.45 mm vs. 2.61 ± 0.45 mm, P < 0.05). The average maximum failure load of the two types was 1270.82 ± 318.85 N and 1529.18 ± 467.29 N, respectively (P = 0.011). The stiffness and energy were significantly higher for type II than type I (896.75 ± 281.14 N/mm vs. 692.91 ± 217.95 N/mm, P = 0.001; 2100.38 ± 649.54 N × mm vs. 1712.71 ± 626.02 N × mm, P = 0.015). Conclusions There was great interindividual variation in the anatomical morphology of the coracoglenoid space. Type I (hook-like) spaces bore lower forces, were less stiff, and bore less energy, which may constitute an anatomical predisposition to scapular neck fractures.

The Donor-Dependent and Colon-Region-Dependent Metabolism of (+)-Catechin by Colonic Microbiota in the Simulator of the Human Intestinal Microbial Ecosystem

The intestinal absorption of dietary catechins is quite low, resulting in most of them being metabolized by gut microbiota in the colon. It has been hypothesized that microbiota-derived metabolites may be partly responsible for the association between catechin consumption and beneficial cardiometabolic effects. Given the profound differences in gut microbiota composition and microbial load between individuals and across different colon regions, this study examined how microbial (+)-catechin metabolite profiles differ between colon regions and individuals. Batch exploration of the interindividual variability in (+)-catechin microbial metabolism resulted in a stratification based on metabolic efficiency: from the 12 tested donor microbiota, we identified a fast- and a slow-converting microbiota that was subsequently inoculated to SHIME, a dynamic model of the human gut. Monitoring of microbial (+)-catechin metabolites from proximal and distal colon compartments with UHPLC-MS and UPLC-IMS-Q-TOF-MS revealed profound donor-dependent and colon-region-dependent metabolite profiles with 5-(3′,4′-dihydroxyphenyl)-γ-valerolactone being the largest contributor to differences between the fast- and slow-converting microbiota and the distal colon being a more important region for (+)-catechin metabolism than the proximal colon. Our findings may contribute to further understanding the role of the gut microbiota as a determinant of interindividual variation in pharmacokinetics upon (+)-catechin ingestion.

Slow-Fast Cognitive Phenotypes and Their Significance for Social Behavior: What Can We Learn From Honeybees?

Cognitive variation is proposed to be the fundamental underlying factor that drives behavioral variation, yet it is still to be fully integrated with the observed variation at other phenotypic levels that has recently been unified under the common pace-of-life framework. This cognitive and the resulting behavioral diversity is especially significant in the context of a social group, the performance of which is a collective outcome of this diversity. In this review, we argue about the utility of classifying cognitive traits along a slow-fast continuum in the larger context of the pace-of-life framework. Using Tinbergen’s explanatory framework for different levels of analyses and drawing from the large body of knowledge about honeybee behavior, we discuss the observed interindividual variation in cognitive traits and slow-fast cognitive phenotypes from an adaptive, evolutionary, mechanistic and developmental perspective. We discuss the challenges in this endeavor and suggest possible next steps in terms of methodological, statistical and theoretical approaches to move the field forward for an integrative understanding of how slow-fast cognitive differences, by influencing collective behavior, impact social evolution.

Shedding Light on the Circadian Clock of the Threespine Stickleback

The circadian clock is an internal timekeeping system shared by most organisms, and knowledge about its functional importance and evolution in natural environments is still needed. Here, we investigated the circadian clock of wild-caught threespine sticklebacks (Gasterosteus aculeatus) at the behavioural and molecular levels. While their behaviour, ecology, and evolution are well studied, information on their circadian rhythms are scarce. We quantified the daily locomotor activity rhythm under a light-dark cycle (LD) and under constant darkness (DD). Under LD, all fish exhibited significant daily rhythmicity, while under DD, only 18% of individuals remained rhythmic. This interindividual variation suggests that the circadian clock controls activity only in certain individuals. Moreover, under LD, some fish were almost exclusively nocturnal, while others were active around the clock. Furthermore, the most nocturnal fish were also the least active. These results suggest that light masks activity (i.e. suppresses activity without entraining the internal clock) more strongly in some individuals than others. Finally, we quantified the expression of five clock genes in the brain of sticklebacks under DD using qPCR. We did not detect circadian rhythmicity, which could either indicate that the clock molecular oscillator is highly light-dependent, or that there was an oscillation but that we were unable to detect it. Overall, our study suggests that a strong circadian control on behavioural rhythms may not necessarily be advantageous in a natural population of sticklebacks and that the daily phase of activity varies greatly between individuals because of a differential masking effect of light.

Post-dynamic Resistance Exercise Hypotension: Exploring Individual Responses and Predictors

Background: Post-dynamic resistance exercise hypotension (PREH) has been largely demonstrated. However, little is known regarding the interindividual variation of PREH magnitude and its predictors (i.e. factors of influence).Aims: To assess the interindividual variation of PREH and its predictors related to the characteristics of the individuals and the exercise protocol.Methods: This study retrospectively analysed data from 131 subjects included in seven controlled trials about PREH (including at least one dynamic resistance exercise and one control session) conducted by two research laboratories. The interindividual variation was assessed by the standard deviation of the individual responses (SDIR), and linear regression analyses were conducted to explore the predictors.Results: PREH showed moderate interindividual variation for systolic (SBP, SDIR=4.4mmHg; 0.35 standardised units) and diastolic blood pressures (DBP, SDIR=3.6mmHg; 0.32 standardised units). For systolic PREH, multivariate regression analysis (R2=0.069) revealed higher baseline SBP (B=−0.157, p=0.008) and higher number of sets (B=−3.910, p=0.041) as significant predictors. For diastolic PREH, multivariate regression analysis (R2=0.174) revealed higher baseline DBP (B=−0.191, p=0.001) and higher exercise volume (i.e. number of exercises *sets per exercise *repetitions per sets &gt;150; B=−4.212, p=0.001) as significant predictors.Conclusion: PREH has a considerable interindividual variation. Greater PREH magnitude is observed in individuals with higher baseline blood pressure and after exercise protocols that comprehend higher number of sets and exercise volume.

Variability of human fasted venous plasma metabolomic profiles with tourniquet induced hemostasis

Venous plasma metabolomics is a potent and highly sensitive tool for identifying and measuring metabolites of interest in human health and disease. Accurate and reproducible insights from such metabolomic studies require extreme care in removing preanalytical confounders; one of these is the duration of tourniquet application when drawing the venous blood sample. Using an untargeted plasma metabolomics approach, we evaluated the effect of varying durations of tourniquet application on the variability in plasma metabolite concentrations in five healthy female subjects. Tourniquet application introduced appreciable variation in the metabolite abundances: 73% of the identified metabolites had higher temporal variation compared to interindividual variation [Intra-Class Correlation (ICC) > 0.50]. As such, we recommend tourniquet application for minimal duration and to wait for 5 min with the needle in situ after removing the tourniquet, to reduce hemostasis-induced variability and false flags in interpretation.

Patterns of psychopathology and cognition in sex chromosome aneuploidy

Background Sex chromosome aneuploidies (SCAs) are a collectively common family of genetic disorders that increase the risk for neuropsychiatric and cognitive impairment. Beyond being important medical disorders in their own right, SCAs also offer a unique naturally occurring model for studying X- and Y-chromosome influences on the human brain. However, it remains unclear if (i) different SCAs are associated with different profiles of psychopathology and (ii) the notable interindividual variation in psychopathology is related to co-occurring variation in cognitive ability. Methods We examined scores for 11 dimensions of psychopathology [Child/Adult Behavior Checklist (CBCL)] and general cognitive ability [full-scale IQ (FSIQ) from Wechsler tests] in 110 youth with varying SCAs (XXY = 41, XYY = 22, XXX = 27, XXYY = 20) and 131 typically developing controls (XX = 59, XY = 72). Results All SCAs were associated with elevated CBCL scores across several dimensions of psychopathology (two-sample t tests comparing the euploidic and aneuploidic groups [all |T| > 9, and p < 0.001]). Social and attentional functioning were particularly sensitive to the carriage of a supernumerary Y-chromosome. In particular, the XYY group evidenced significantly more social problems than both extra-X groups (Cohen’s d effect size > 0.5, Bonferroni corrected p < .05). There was marked variability in CBCL scores within each SCA group, which generally correlated negatively with IQ, but most strongly so for social and attentional difficulties (standardized β, − 0.3). These correlations showed subtle differences as a function of the SCA group and CBCL scale. Conclusions There is domain-specific variation in psychopathology across SCA groups and domain-specific correlation between psychopathology and IQ within SCAs. These findings (i) help to tailor clinical assessment of this common and impactful family of genetic disorders and (ii) suggest that dosage abnormalities of X- and Y-linked genes impart somewhat distinct profiles of neuropsychiatric risk.

Development and Validation of Prediction Formula of Wingate Test Peak Power From Force–Velocity Test in Male Soccer Players

Peak power of the Wingate anaerobic test (WAnT), either in W (Ppeak) or in W.kg–1 (rPpeak), has been widely used to evaluate the performance of soccer players; however, its relationship with force–velocity (F-v) test (e.g., whether these tests can be used interchangeably) has received little scientific attention so far. The aim of this work was to develop and validate a prediction equation of Ppeak and rPpeak from F-v characteristics in male soccer players. Participants were 158 adult male soccer players (sport experience 11.4 ± 4.5 years, mean ± standard deviation, approximately five weekly training units, age 22.6 ± 3.9 years, body mass 74.8 ± 7.8 kg, and height 178.3 ± 7.8 cm) who performed both WAnT and F-v test. An experimental (EXP, n = 79) and a control group (CON, n = 79) were used for development and validation, respectively, of the prediction equation of Ppeak and rPpeak from F-v test. In EXP, Ppeak correlated very largely with body mass (r = 0.787), fat-free mass (r = 0.765), largely with maximal power of F-v test (Pmax; r = 0.639), body mass index (r = 0.603), height (r = 0.558), moderately with theoretical maximal force (F0; r = 0.481), percentage of body fat (r = 0.471), fat mass (r = 0.443, p &lt; 0.001); rPpeak correlated with rPmax (largely; r = 0.596, p &lt; 0.001), theoretical maximal velocity (v0; moderately; r = 0.341, p = 0.002), F0 (small magnitude; r = 0.280, p = 0.012), BF (r = −0.230, p = 0.042), and fat mass (r = −0.242, p = 0.032). Ppeak in EXP could be predicted using the formula “44.251 + 7.431 × body mass (kg) + 0.576 × Pmax (W) – 19.512 × F0” (R = 0.912, R2 = 0.833, standard error of estimate (SEE) = 42.616), and rPpeak from “3.148 + 0.218 × rPmax (W.kg–1) + v0 (rpm)” (R = 0.765, R2 = 0.585, SEE = 0.514). Applying these formulas in CON, no bias was observed between the actual and the predicted Ppeak (mean difference 2.5 ± 49.8 W; 95% CI, −8.7, 13.6; p = 0.661) and rPpeak (mean difference 0.05 ± 0.71 W.kg–1; 95% CI, −0.11, 0.21, p = 0.525). These findings provided indirect estimates of Ppeak of the WAnT, especially useful in periods when this test should not be applied considering the fatigue it causes; in this context, the F-v test can be considered as an alternative of exercise testing for estimating the average Ppeak of a group of soccer players rather than for predicting individual scores when the interindividual variation of performance is small.

Cytochrome P450 Enzymes and Drug Metabolism in Humans

Human cytochrome P450 (CYP) enzymes, as membrane-bound hemoproteins, play important roles in the detoxification of drugs, cellular metabolism, and homeostasis. In humans, almost 80% of oxidative metabolism and approximately 50% of the overall elimination of common clinical drugs can be attributed to one or more of the various CYPs, from the CYP families 1–3. In addition to the basic metabolic effects for elimination, CYPs are also capable of affecting drug responses by influencing drug action, safety, bioavailability, and drug resistance through metabolism, in both metabolic organs and local sites of action. Structures of CYPs have recently provided new insights into both understanding the mechanisms of drug metabolism and exploiting CYPs as drug targets. Genetic polymorphisms and epigenetic changes in CYP genes and environmental factors may be responsible for interethnic and interindividual variations in the therapeutic efficacy of drugs. In this review, we summarize and highlight the structural knowledge about CYPs and the major CYPs in drug metabolism. Additionally, genetic and epigenetic factors, as well as several intrinsic and extrinsic factors that contribute to interindividual variation in drug response are also reviewed, to reveal the multifarious and important roles of CYP-mediated metabolism and elimination in drug therapy.