An Investigation into the Use of a Movement Assessment Protocol for Under-14 Rugby League Players in a Talent Development Environment

This study investigated the use of a movement assessment protocol for under-14 rugby league players by evaluating the relationships between chronological age, maturation, and anthropometry, and fitness and qualitative movement assessments (QMA) of 84 rugby league players within a talent development environment. A one-way ANOVA showed Quartile 1 players were more mature, taller (173.0±7.4 vs 165.0±8.0 cm) and heavier (72.5 vs 58.7 kg) than Quartile 4 players, with no difference evident for fitness or QMA measures. Earlier maturing players had significantly greater upper body power (5.39±0.46 vs 4.42±0.68 m), 20m speed (3.48±0.14 vs 3.65±0.19s) and power pass QMA (13.88±2.18 vs 12.00±1.98) than later maturing players. Body mass was positively related to power pass fitness (r=0.50) and QMA (r=0.22) scores, with negative relationships found for vertical jump performance (r=-0.24), sprint QMA (r=-.29) and turn off either foot QMA (r=-0.26). There is a need to educate coaches about the use of both fitness testing and qualitative movement assessments to identify talented U14 rugby league players, which potentially reduces relative age and maturational biases

Development of Pore Pressure and Shear Strain in Clean Hostun Sands Under Multi-directional Loading Paths

A series of undrained multi-directional direct simple shear tests with circular paths were conducted to investigate the excess pore pressure generation and shear strain development in clean Hostun sands under multi-directional loading condition. The results of an example test are shown. The excess pore pressure accumulation and shear strain development under multi-directional loading condition exhibits evidently different characteristics compared with that under uni-directional loading condition. Excess pore pressure accumulates generally with the circular stress path but can have increase and decrease within a single cycle as well

A prognostic survival model for women diagnosed with invasive breast cancer in Queensland, Australia.

PURPOSE: Prognostic models can help inform patients on the future course of their cancer and assist the decision making of clinicians and patients in respect to management and treatment of the cancer. In contrast to previous studies considering survival following treatment, this study aimed to develop a prognostic model to quantify breast cancer-specific survival at the time of diagnosis. METHODS: A large (n = 3323), population-based prospective cohort of women were diagnosed with invasive breast cancer in Queensland, Australia between 2010 and 2013, and followed up to December 2018. Data were collected through a validated semi-structured telephone interview and a self-administered questionnaire, along with data linkage to the Queensland Cancer Register and additional extraction from medical records. Flexible parametric survival models, with multiple imputation to deal with missing data, were used. RESULTS: Key factors identified as being predictive of poorer survival included more advanced stage at diagnosis, higher tumour grade, "triple negative" breast cancers, and being symptom-detected rather than screen detected. The Harrell's C-statistic for the final predictive model was 0.84 (95% CI 0.82, 0.87), while the area under the ROC curve for 5-year mortality was 0.87. The final model explained about 36% of the variation in survival, with stage at diagnosis alone explaining 26% of the variation. CONCLUSIONS: In addition to confirming the prognostic importance of stage, grade and clinical subtype, these results highlighted the independent survival benefit of breast cancers diagnosed through screening, although lead and length time bias should be considered. Understanding what additional factors contribute to the substantial unexplained variation in survival outcomes remains an important objective

Monitoring temporal change in riparian vegetation of Great Basin National Park

Disturbance in riparian areas of semiarid ecosystems involves complex interactions of pulsed hydrologic flows, herbivory, fire, climatic effects, and anthropogenic influences. We resampled riparian vegetation within ten 10-m × 100-m plots that were initially sampled in 1992 in 4 watersheds of the Snake Range, east central Nevada. Our finding of significantly lower coverage of grasses, forbs, and shrubs within plots in 2001 compared with 1992 was not consistent with the management decision to remove livestock grazing from the watersheds in 1999. Change over time in cover of life-forms or bare ground was not predicted by scat counts within plots in 2001. Cover results were also not well explained by variability between the 2 sampling periods in either density of native herbivores or annual precipitation. In contrast, Engelmann spruce (Picea engelmannii) exhibited reduced abundance at all but the highest-elevation plot in which it occurred in 1992, and the magnitude of change in abundance was strongly predicted by plot elevation. Abundance of white fir (Abies concolor) individuals increased while aspen (Populus tremuloides) individuals decreased at 4 of 5 sites where they were sympatric, and changes in abundance in the 2 species were negatively correlated across those sites. Utility of monitoring data to detect change over time and contribute to adaptive management will vary with sample size, observer bias, use of repeatable or published methods, and precision of measurements, among other factors

Transcriptional regulation of the urokinase receptor (u-PAR) - A central molecule of invasion and metastasis

The phenomenon of tumor-associated proteolysis has been acknowledged as a decisive step in the progression of cancer. This short review focuses on the urokinase receptor (u-PAR), a central molecule involved in tumor-associated invasion and metastasis, and summarizes the transcriptional regulation of u-PAR. The urokinase receptor (u-PAR) is a heavily glycosylated cell surface protein and binds the serine protease urokinase specifically and with high affinity. It consists of three similar cysteine-rich repeats and is anchored to the cell membrane via a GPI-anchor. The u-PAR gene comprises 7 exons and is located on chromosome 19q13. Transcriptional activation of the u-PAR promoter region can be induced by binding of transcription factors (Sp1, AP-1, AP-2, NF-kappaB). One current study gives an example for transcriptional downregulation of u-PAR through a PEA3/ets transcriptional silencing element. Knowledge of the molecular regulation of this molecule in tumor cells could be very important for diagnosis and therapy in the near future

Linear Estimation of Location and Scale Parameters Using Partial Maxima

Consider an i.i.d. sample X^*_1,X^*_2,...,X^*_n from a location-scale family, and assume that the only available observations consist of the partial maxima (or minima)sequence, X^*_{1:1},X^*_{2:2},...,X^*_{n:n}, where X^*_{j:j}=max{X^*_1,...,X^*_j}. This kind of truncation appears in several circumstances, including best performances in athletics events. In the case of partial maxima, the form of the BLUEs (best linear unbiased estimators) is quite similar to the form of the well-known Lloyd's (1952, Least-squares estimation of location and scale parameters using order statistics, Biometrika, vol. 39, pp. 88-95) BLUEs, based on (the sufficient sample of) order statistics, but, in contrast to the classical case, their consistency is no longer obvious. The present paper is mainly concerned with the scale parameter, showing that the variance of the partial maxima BLUE is at most of order O(1/log n), for a wide class of distributions.Comment: This article is devoted to the memory of my six-years-old, little daughter, Dionyssia, who leaved us on August 25, 2010, at Cephalonia isl. (26 pages, to appear in Metrika

The impact of rurality and disadvantage on the diagnostic interval for breast cancer in a large population-based study of 3202 women in Queensland, Australia

Delays in diagnosing breast cancer (BC) can lead to poorer outcomes. We investigated factors related to the diagnostic interval in a population-based cohort of 3202 women diagnosed with BC in Queensland,Australia. Interviews ascertained method of detection and dates of medical/procedural appointments,and clinical information was obtained from medical records. Time intervals were calculated from self-recognition of symptoms (symptom-detected) or mammogram (screen-detected) to diagnosis (diagnostic interval (DI)). The cohort included 1560 women with symptom-detected and 1642 with screen-detected BC. Symptom-detected women had higher odds of DI of >60 days if they were Indigenous (OR = 3.12,95% CI = 1.40,6.98); lived in outer regional (OR = 1.50,95% CI = 1.09,2.06) or remote locations (OR = 2.46,95% CI = 1.39,4.38); or presented with a “non-lump” symptom (OR = 1.84,95% CI = 1.43,2.36). For screen-detected BC,women who were Indigenous (OR = 2.36,95% CI = 1.03,5.80); lived in remote locations (OR = 2.35,95% CI = 1.24,4.44); or disadvantaged areas (OR = 1.69,95% CI = 1.17,2.43) and attended a public screening facility (OR = 2.10,95% CI = 1.40,3.17) had higher odds of DI > 30 days. Our study indicates a disadvantage in terms of DI for rural,disadvantaged and Indigenous women. Difficulties in accessing primary care and diagnostic services are evident. There is a need to identify and implement an efficient and effective model of care to minimize avoidable longer diagnostic intervals

General rules for environmental management to prioritise social ecological systems research based on a value of information approach

This is the final version. Available on open access from Wiley via the DOI in this record1. Globally, billions of dollars are invested each year to help understand the dynamics of social ecological systems (SES) in bettering both social and environmental outcomes. However, there is no scientific consensus on which aspect of an SES is most important and urgent to understand; particularly given the realities of limited time and money. 2. Here we use a simulation‐based “value of information” approach to examine where research will deliver the most important information for environmental management in four SESs representing a range of real‐life environmental issues. 3. We find that neither social nor ecological information is consistently the most important: instead, researchers should focus on understanding the primary effects of their management actions. 4. Thus, when managers are undertaking social actions the highest research priority should be understanding the dynamics of social groups. Alternatively, when manipulating ecological systems it will be most important to quantify ecological population dynamics. 5. Synthesis and applications. Our results provide a standard assessment to determine the uncertain social ecological systems (SES) component with the highest expected impact for management outcomes. First, managers should determine the structure of their SES by identifying social and ecological nodes. Second, managers should identify the qualitative nature of the network, by determining which nodes are linked, but not the strength of those interactions. Finally, managers should identify the actions available to them to intervene in the SES. From these steps, managers will be able to identify the SES components that are closest to the management action(s), and it is these nodes and interactions that should receivepriority research attention to achieve effective environmental decision making.Centre of Excellence for Environmental Decisions, Australian Research Counc

Mass screening of rice mutant populations at low CO2 for identification of lowered photorespiration and respiration rates

Introduction: Identifying rice (Oryza sativa) germplasm with improved efficiency of primary metabolism is of utmost importance in order to increase yields. One such approach can be attained through screening genetically diverse populations under altered environmental conditions. Growth or treatment under low carbon dioxide (CO2) concentrations can be used as a means of revealing altered leaf photorespiration, respiration and other metabolic variants. Methods: We developed a pipeline for very high throughput treatment of gamma- and ethyl methanesulfonate- (EMS) induced mutant populations of IR64 rice seedlings at very low CO2 for 7 days. 1050 seedlings per batch at 5th leaf stage were exposed to 60 ppm CO2 for the first day and 30 ppm for the remaining three days. Following this, putative candidates were identified by measuring chlorophyll depletion using SPAD. Screening results showed a distinct difference between the mutants and the WTs. Results and discussion: The mean chlorophyll loss in WTs ranged from 65% to 11% respectively, whereas in the mutant lines chlorophyll loss ranged from 0 to 100%, suggesting considerable phenotypic variation. Rice mutants with a reduced chlorophyll reduction (<10%) were identified as ‘Chlorophyll retention mutants’ (CRMs) under low CO2 stress. In total, 1909 mutant lines (14,000 seedlings) were screened for chlorophyll content under 30 ppm CO2, with 26 lines selected for detailed screening. These 26 putative candidates were self-seeded to produce an M5 generation, used to determine the genetic control of the altered response to low CO2. Gas exchange of light and CO2 response revealed that there were significant variations among photosynthetic properties in two selected rice mutants. The CO2 compensation points in the absence of photorespiration and leaf respiration rates were lower than the WTs and anatomical analyses showed that CRM 29 had improved mesophyll cell area. We propose that this approach is useful for generating new material for breeding rice with improved primary metabolism