Habitual carbohydrate ingestion reduces the efficacy of oral carbohydrate rinsing during repetitions to failure

Carbohydrate mouth rinsing has been reported to enhance exercise performance although individual variation exists. The present study aimed to investigate the effect of habitual dietary carbohydrate intake on the efficacy of rinsing a 6% carbohydrate solution on the number of bench press repetitions to failure at 60% of 1‐RM. Twenty‐one recreationally active male participants (Mean ± SD) (age: 24 ± 4 years, height: 177.8 ± 7.8 cm, body mass: 78.6 ± 8.1 kg; bench press 1‐RM: 73.3 ± 20.5 kg) performed bench press repetitions to failure at 60% 1‐RM following rinsing with 25 mL of a 6% carbohydrate (CHO), an artificially sweetened solution (PLA) and a non‐rising control condition (CON) in a randomised cross‐over design. A 7‐day dietary record was completed prior to the first session and subsequently analysed for daily carbohydrate consumption. The number of repetitions performed during CHO (24 ± 4) was higher than CON [21 ± 4; p < 0.001; 95% CI: 1, 4; d = 0.64], as was PLA [23 ± 4; p = 0.002; 95% CI: 1, 3; d = 0.48]. However, there was a large, negative relationship [r = −0.68 (95% CI: −0.86, −0.36), p < 0.001] between daily relative carbohydrate intake (g kg−1) and the difference in the number of repetitions between CHO and PLA. The present study suggests the existence of an inverse relationship between daily carbohydrate ingestion and the efficacy of carbohydrate mouth rinsing; participants who consumed the most daily carbohydrate were generally less likely to see an increase in performance with carbohydrate rinsing

Explicit equilibrium modeling of transcription-factor binding and gene regulation

We have developed a computational model that predicts the probability of transcription factor binding to any site in the genome. GOMER (generalizable occupancy model of expression regulation) calculates binding probabilities on the basis of position weight matrices, and incorporates the effects of cooperativity and competition by explicit calculation of coupled binding equilibria. GOMER can be used to test hypotheses regarding gene regulation that build upon this physically principled prediction of protein-DNA binding

Inferring direct regulatory targets from expression and genome location analyses: a comparison of transcription factor deletion and overexpression

BACKGROUND: Effects on gene expression due to environmental or genetic changes can be easily measured using microarrays. However, indirect effects on expression can be substantial. The indirect effects of a perturbation need to be distinguished from the direct effects if we are to understand the structure and behavior of regulatory networks. RESULTS: The most direct way to perturb a transcriptional network is to alter transcription factor activity. Here, for the first time, we compare expression changes and genomic binding in a simple regulon under conditions of both low and high transcription factor activity. Specifically, we assessed the effects on expression and binding due to deletion of the yeast LEU3 transcription factor gene and effects due to elevation of Leu3 activity. Leu3 activity was elevated through overexpression and the introduction of a mutation that renders the protein constitutively active. Genes that are bound and/or regulated by Leu3 under one or both conditions were characterized in terms of their functional annotations and their predicted potential to be bound by Leu3. We also assessed the evolutionary conservation of the predicted binding potential using a novel alignment-independent method. Both perturbations yield genes that are likely to be direct targets of Leu3, including most of the classically defined targets. Additional direct targets are identified by each of the methods. However, experimental and computational criteria suggest that most genes whose expression is affected by the Leu3 genotype are unlikely to be regulated by binding of the protein. CONCLUSION: Most genes that are differentially expressed by Leu3 are not direct targets despite the exceptional simplicity of the regulon, and the unusually direct nature of the perturbations investigated. These conclusions are reached through computational analyses that support and extend chromatin immunoprecipitation data on the identities of direct targets. These results have implications for the interpretation of expression experiments, especially in cases for which chromatin immunoprecipitation data are unavailable, incomplete, or ambiguous

Success in the DREAM3 Signaling Response Challenge Using Simple Weighted-Average Imputation: Lessons for Community-Wide Experiments in Systems Biology

Our group produced the best predictions overall in the DREAM3 signaling response challenge, being tops by a substantial margin in the cytokine sub-challenge and nearly tied for best in the phosphoprotein sub-challenge. We achieved this success using a simple interpolation strategy. For each combination of a stimulus and inhibitor for which predictions were required, we had noted there were six other datasets using the same stimulus (but different inhibitor treatments) and six other datasets using the same inhibitor (but different stimuli). Therefore, for each treatment combination for which values were to be predicted, we calculated rank correlations for the data that were in common between the treatment combination and each of the 12 related combinations. The data from the 12 related combinations were then used to calculate missing values, weighting the contributions from each experiment based on the rank correlation coefficients. The success of this simple method suggests that the missing data were largely over-determined by similarities in the treatments. We offer some thoughts on the current state and future development of DREAM that are based on our success in this challenge, our success in the earlier DREAM2 transcription factor target challenge, and our experience as the data provider for the gene expression challenge in DREAM3

Not Another Caffeine Effect on Sports Performance Study—Nothing New or More to Do?

The performance-enhancing potential of acute caffeine consumption is firmly established with benefits for many aspects of physical performance and cognitive function summarised in a number of meta-analyses. Despite this, there remains near exponential growth in research articles examining the ergogenic effects of caffeine. Many such studies are confirmatory of well-established ideas, and with a wealth of convincing evidence available, the value of further investigation may be questioned. However, several important knowledge gaps remain. As such, the purpose of this review is to summarise key knowledge gaps regarding the current understanding of the performance-enhancing effect of caffeine and justify their value for future investigation. The review will provide a particular focus on ten research priorities that will aid in the translation of caffeine’s ergogenic potential to real-world sporting scenarios. The discussion presented here is therefore essential in guiding the design of future work that will aid in progressing the current understanding of the effects of caffeine as a performance enhancer

Whole body precooling attenuates the extracellular HSP72, IL-6 and IL-10 responses after an acute bout of running in the heat

The impact of whole-body precooling on the extracellular heat shock protein 72 (eHSP72) and cytokine responses to running in the heat is undefined. The aim of this study was to determine whether precooling would attenuate post-exercise eHSP72 and cytokine responses.Eight male recreational runnerscompleted two90-minuteboutsofrunningat65% _VO2maxin32±0.9°Cand47±6%relativehumidity(RH)preceded by either 60-minutes of precooling in 20.3 ± 0.3°C water (COOL) or 60 min rest in an air-conditioned laboratory (20.2 ± 1.7°C, 60 ± 3% RH; CON). eHSP72, TNF-α, IL-6, IL-10 IL-1ra were determined before and immediately after exercise. The elevation in post-exercise eHSP72 was attenuated after COOL (+0.04 ± 0.10 ng.mL−1) compared to CON (+ 0.29 ± 0.26 ng.mL−1;P < 0.001). No changes in TNF-α were observed at any stage. COOL reduced the absolute post-exercise change in IL-6 (P = 0.011) and IL-10 (P = 0.03) compared to CON. IL-1ra followed this trend (P = 0.063). A precooling-induced attenuation of eHSP72 and proinflammatory cytokines may aid recovery during multi-day sporting events, but could be counterproductive if a training response or adaptation to environmental stress is a desired outcome