Sex-related changes in physical performance, wellbeing and neuromuscular function of elite Touch players during a four-day international tournament.

Accepted author manuscript version reprinted, by permission, from International Journal of Sports Physiology and Performance, 2020, 15(8): 1138–1146, https://doi.org/10.1123/ijspp.2019-0594. © Human Kinetics, Inc.Purpose: To examine the within- and between-sex physical performance, wellbeing and neuromuscular function responses across a four-day international touch rugby (Touch) tournament. Methods: Twenty females and twenty-one males completed measures of wellbeing (fatigue, soreness, sleep, mood, stress) and neuromuscular function (countermovement jump (CMJ) height, peak power output (PPO) and peak force (PF)) during a 4-day tournament with internal, external and perceptual loads recorded for all matches. Results: Relative and absolute total, low- (females) and high-intensity distance was lower on day 3 (males and females) (ES = -0.37 to -0.71) compared to day 1. Mean heart rate was possibly to most likely reduced during the tournament (except day 2 males) (ES = -0.36 to -0.74), whilst RPE-TL was consistently higher in females (ES = 0.02 to 0.83). The change in mean fatigue, soreness and overall wellbeing were unclear to most likely lower (ES = -0.33 to -1.90) across the tournament for both sexes, with greater perceived fatigue and soreness in females on days 3-4 (ES = 0.39 to 0.78). Jump height and PPO were possibly to most likely lower across days 2-4 (ES = -0.30 to -0.84), with greater reductions in females (ES = 0.21 to 0.66). Wellbeing, CMJ height, and PF were associated with changes in external, internal and perceptual measures of load across the tournament (2 = -0.37 to 0.39). Conclusions: Elite Touch players experience reductions in wellbeing, neuromuscular function and running performance across a 4-day tournament, with notable differences in fatigue and running between males and females, suggesting sex-specific monitoring and intervention strategies are necessary

Toxicity of cancer therapy: what the cardiologist needs to know about angiogenesis inhibitors

Clinical outcomes for patients with a wide range of malignancies have improved substantially over the last two decades. Tyrosine kinase inhibitors (TKIs) are potent signalling cascade inhibitors and have been responsible for significant advances in cancer therapy. By inhibiting vascular endothelial growth factor receptor (VEGFR)-mediated tumour blood vessel growth, VEGFR-TKIs have become a mainstay of treatment for a number of solid malignancies. However, the incidence of VEGFR-TKI-associated cardiovascular toxicity is substantial and previously under-recognised. Almost all patients have an acute rise in blood pressure, and the majority develop hypertension. They are associated with the development of left ventricular systolic dysfunction (LVSD), heart failure and myocardial ischaemia and can have effects on myocardial repolarisation. Attention should be given to rigorous baseline assessment of patients prior to commencing VEGFR-TKIs, with careful consideration of baseline cardiovascular risk factors. Baseline blood pressure measurement, ECG and cardiac imaging should be performed routinely. Hypertension management currently follows national guidelines, but there may be a future role forendothelin-1 antagonism in the prevention or treatment of VEGFR-TKI-associated hypertension. VEGFR-TKI-associated LVSD appears to be independent of dose and is reversible. Patients who develop LVSD and heart failure should be managed with conventional heart failure therapies, but the role of prophylactic therapy is yet to be defined. Serial monitoring of left ventricular function and QT interval require better standardisation and coordinated care. Management of these complex patients requires collaborative, cardio-oncology care to allow the true therapeutic potential from cancer treatment while minimising competing cardiovascular effects

Effect of venting range hood flow rate on size-resolved ultrafine particle concentrations from gas stove cooking

Cooking is the main source of ultrafine particles (UFP) in homes. This study investigated the effect of venting range hood flow rate on size-resolved UFP concentrations from gas stove cooking. The same cooking protocol was conducted 60 times using three venting range hoods operated at six flow rates in twin research houses. Size-resolved particle (10–420 nm) concentrations were monitored using a NanoScan scanning mobility particle sizer (SMPS) from 15 min before cooking to 3 h after the cooking had stopped. Cooking increased the background total UFP number concentrations to 1.3 × 103 particles/cm3 on average, with a mean exposure-relevant source strength of 1.8 × 1012 particles/min. Total particle peak reductions ranged from 25% at the lowest fan flow rate of 36 L/s to 98% at the highest rate of 146 L/s. During the operation of a venting range hood, particle removal by deposition was less significant compared to the increasing air exchange rate driven by exhaust ventilation. Exposure to total particles due to cooking varied from 0.9 to 5.8 × 104 particles/cm3·h, 3 h after cooking ended. Compared to the 36 L/s range hood, higher flow rates of 120 and 146 L/s reduced the first-hour post-cooking exposure by 76% and 85%, respectively. © 2018 Crown Copyright. Published with license by Taylor & Francis Group, LLC

Differential Hox expression in murine embryonic stem cell models of normal and malignant hematopoiesis

The Hox family are master transcriptional regulators of developmental processes, including hematopoiesis. The Hox regulators, caudal homeobox factors (Cdx1-4), and Meis1, along with several individual Hox proteins, are implicated in stem cell expansion during embryonic development, with gene dosage playing a significant role in the overall function of the integrated Hox network. To investigate the role of this network in normal and aberrant, early hematopoiesis, we employed an in vitro embryonic stem cell differentiation system, which recapitulates mouse developmental hematopoiesis. Expression profiles of Hox, Pbx1, and Meis1 genes were quantified at distinct stages during the hematopoietic differentiation process and compared with the effects of expressing the leukemic oncogene Tel/PDGFR;2. During normal differentiation the Hoxa cluster, Pbx1 and Meis1 predominated, with a marked reduction in the majority of Hox genes (27/39) and Meis1 occurring during hematopoietic commitment. Only the posterior Hoxa cluster genes (a9, a10, a11, and a13) maintained or increased expression at the hematopoietic colony stage. Cdx4, Meis1, and a subset of Hox genes, including a7 and a9, were differentially expressed after short-term oncogenic (Tel/PDGFR;2) induction. Whereas Hoxa4-10, b1, b2, b4, and b9 were upregulated during oncogenic driven myelomonocytic differentiation. Heterodimers between Hoxa7/Hoxa9, Meis1, and Pbx have previously been implicated in regulating target genes involved in hematopoietic stem cell (HSC) expansion and leukemic progression. These results provide direct evidence that transcriptional flux through the Hox network occurs at very early stages during hematopoietic differentiation and validates embryonic stem cell models for gaining insights into the genetic regulation of normal and malignant hematopoiesis

Reassessing Design and Analysis of two-Colour Microarray Experiments Using Mixed Effects Models

Gene expression microarray studies have led to interesting experimental design and statistical analysis challenges. The comparison of expression profiles across populations is one of the most common objectives of microarray experiments. In this manuscript we review some issues regarding design and statistical analysis for two-colour microarray platforms using mixed linear models, with special attention directed towards the different hierarchical levels of replication and the consequent effect on the use of appropriate error terms for comparing experimental groups. We examine the traditional analysis of variance (ANOVA) models proposed for microarray data and their extensions to hierarchically replicated experiments. In addition, we discuss a mixed model methodology for power and efficiency calculations of different microarray experimental designs

A dedicated haem lyase is required for the maturation of a novel bacterial cytochrome c with unconventional covalent haem binding

In bacterial c-type cytochromes, the haem cofactor is covalently attached via two cysteine residues organized in a haem c-binding motif. Here, a novel octa-haem c protein, MccA, is described that contains only seven conventional haem c-binding motifs (CXXCH), in addition to several single cysteine residues and a conserved CH signature. Mass spectrometric analysis of purified MccA from Wolinella succinogenes suggests that two of the single cysteine residues are actually part of an unprecedented CX15CH sequence involved in haem c binding. Spectroscopic characterization of MccA identified an unusual high-potential haem c with a red-shifted absorption maximum, not unlike that of certain eukaryotic cytochromes c that exceptionally bind haem via only one thioether bridge. A haem lyase gene was found to be specifically required for the maturation of MccA in W. succinogenes. Equivalent haem lyase-encoding genes belonging to either the bacterial cytochrome c biogenesis system I or II are present in the vicinity of every known mccA gene suggesting a dedicated cytochrome c maturation pathway. The results necessitate reconsideration of computer-based prediction of putative haem c-binding motifs in bacterial proteomes

Optimally splitting cases for training and testing high dimensional classifiers

<p>Abstract</p> <p>Background</p> <p>We consider the problem of designing a study to develop a predictive classifier from high dimensional data. A common study design is to split the sample into a training set and an independent test set, where the former is used to develop the classifier and the latter to evaluate its performance. In this paper we address the question of what proportion of the samples should be devoted to the training set. How does this proportion impact the mean squared error (MSE) of the prediction accuracy estimate?</p> <p>Results</p> <p>We develop a non-parametric algorithm for determining an optimal splitting proportion that can be applied with a specific dataset and classifier algorithm. We also perform a broad simulation study for the purpose of better understanding the factors that determine the best split proportions and to evaluate commonly used splitting strategies (1/2 training or 2/3 training) under a wide variety of conditions. These methods are based on a decomposition of the MSE into three intuitive component parts.</p> <p>Conclusions</p> <p>By applying these approaches to a number of synthetic and real microarray datasets we show that for linear classifiers the optimal proportion depends on the overall number of samples available and the degree of differential expression between the classes. The optimal proportion was found to depend on the full dataset size (n) and classification accuracy - with higher accuracy and smaller <it>n </it>resulting in more assigned to the training set. The commonly used strategy of allocating 2/3rd of cases for training was close to optimal for reasonable sized datasets (<it>n </it>≥ 100) with strong signals (i.e. 85% or greater full dataset accuracy). In general, we recommend use of our nonparametric resampling approach for determing the optimal split. This approach can be applied to any dataset, using any predictor development method, to determine the best split.</p

Validity of a portable jump mat for assessing countermovement jump performance in elite rugby league players

Validity of a portable jump mat for assessing countermovement jump performance in elite rugby league player