ResearchPad - statistical-data https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[The two types of society: Computationally revealing recurrent social formations and their evolutionary trajectories]]> https://www.researchpad.co/article/elastic_article_13873 Comparative social science has a long history of attempts to classify societies and cultures in terms of shared characteristics. However, only recently has it become feasible to conduct quantitative analysis of large historical datasets to mathematically approach the study of social complexity and classify shared societal characteristics. Such methods have the potential to identify recurrent social formations in human societies and contribute to social evolutionary theory. However, in order to achieve this potential, repeated studies are needed to assess the robustness of results to changing methods and data sets. Using an improved derivative of the Seshat: Global History Databank, we perform a clustering analysis of 271 past societies from sampling points across the globe to study plausible categorizations inherent in the data. Analysis indicates that the best fit to Seshat data is five subclusters existing as part of two clearly delineated superclusters (that is, two broad “types” of society in terms of social-ecological configuration). Our results add weight to the idea that human societies form recurrent social formations by replicating previous studies with different methods and data. Our results also contribute nuance to previously established measures of social complexity, illustrate diverse trajectories of change, and shed further light on the finite bounds of human social diversity.

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<![CDATA[Scedar: A scalable Python package for single-cell RNA-seq exploratory data analysis]]> https://www.researchpad.co/article/elastic_article_13837 In single-cell RNA-seq (scRNA-seq) experiments, the number of individual cells has increased exponentially, and the sequencing depth of each cell has decreased significantly. As a result, analyzing scRNA-seq data requires extensive considerations of program efficiency and method selection. In order to reduce the complexity of scRNA-seq data analysis, we present scedar, a scalable Python package for scRNA-seq exploratory data analysis. The package provides a convenient and reliable interface for performing visualization, imputation of gene dropouts, detection of rare transcriptomic profiles, and clustering on large-scale scRNA-seq datasets. The analytical methods are efficient, and they also do not assume that the data follow certain statistical distributions. The package is extensible and modular, which would facilitate the further development of functionalities for future requirements with the open-source development community. The scedar package is distributed under the terms of the MIT license at https://pypi.org/project/scedar.

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<![CDATA[Life expectancy and survival analysis of patients with diabetes compared to the non diabetic population in Bulgaria]]> https://www.researchpad.co/article/elastic_article_7723 To evaluate the expected life expectancy in patients with diabetes in Bulgaria and to compare it to the expected life expectancy of the non-diabetic population in the country.MethodsIt is a retrospective observational population study on individuals diagnosed with diabetes, compared to the non-diabetic population in Bulgaria for the period 2012–2015. Data from the national diabetes register and national statistical institute were used to construct life-tables with probability of survival with t-test and Chi Square test. Confounder analysis was done by age, sex, and type of diabetes. All-cause mortality and deaths in diabetic patients were analyzed. Kaplan-Meier survival curves were constructed for each age group and a log-rank analysis was conducted.ResultsAverage life expectancy in the non-diabetic population, patients with Type 1 DM and with Type 2 DM is 74.8; 70.96 and 75.19 years, respectively. For 2012–2015 the mortality in the non-diabetic population remained constant and lower (average—1.48%) compared to type-1 DM (5.25%) and Type-2 (4.27%). Relative risk of death in diabetics was higher overall (12%), after the age of 70 before which the relative risk was higher for the non-diabetic population. This was observed as a trend in all analyzed years.ConclusionPatients with type 2 DM have a longer life-expectancy than patients with type-1 DM and overall Diabetics life expectancy equals that of the non-diabetic population, which could suggest improved disease control and its associated complications in Bulgaria. Male diabetics show slightly longer life expectancy than their counterparts in the non-diabetic population, by a marginal gain of 0.6 years for the entire observed period. Life expectancy in diabetic women increased by 1.3 years, which was not observed in the non-diabetic population. Prevalence of diabetes was higher for women. Improved diabetes control may explain this gain in life; however other studies are needed to confirm this. ]]> <![CDATA[Is it time to stop sweeping data cleaning under the carpet? A novel algorithm for outlier management in growth data]]> https://www.researchpad.co/article/N6ac4201b-e1d9-4dac-b706-1c6b88e127a6

All data are prone to error and require data cleaning prior to analysis. An important example is longitudinal growth data, for which there are no universally agreed standard methods for identifying and removing implausible values and many existing methods have limitations that restrict their usage across different domains. A decision-making algorithm that modified or deleted growth measurements based on a combination of pre-defined cut-offs and logic rules was designed. Five data cleaning methods for growth were tested with and without the addition of the algorithm and applied to five different longitudinal growth datasets: four uncleaned canine weight or height datasets and one pre-cleaned human weight dataset with randomly simulated errors. Prior to the addition of the algorithm, data cleaning based on non-linear mixed effects models was the most effective in all datasets and had on average a minimum of 26.00% higher sensitivity and 0.12% higher specificity than other methods. Data cleaning methods using the algorithm had improved data preservation and were capable of correcting simulated errors according to the gold standard; returning a value to its original state prior to error simulation. The algorithm improved the performance of all data cleaning methods and increased the average sensitivity and specificity of the non-linear mixed effects model method by 7.68% and 0.42% respectively. Using non-linear mixed effects models combined with the algorithm to clean data allows individual growth trajectories to vary from the population by using repeated longitudinal measurements, identifies consecutive errors or those within the first data entry, avoids the requirement for a minimum number of data entries, preserves data where possible by correcting errors rather than deleting them and removes duplications intelligently. This algorithm is broadly applicable to data cleaning anthropometric data in different mammalian species and could be adapted for use in a range of other domains.

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<![CDATA[Prediction model for dengue fever based on interactive effects between multiple meteorological factors in Guangdong, China (2008–2016)]]> https://www.researchpad.co/article/Nfe4e2064-ca0a-4d6d-a8b7-4f75eb296e9a

Introduction

In order to improve the prediction accuracy of dengue fever incidence, we constructed a prediction model with interactive effects between meteorological factors, based on weekly dengue fever cases in Guangdong, China from 2008 to 2016.

Methods

Dengue fever data were derived from statistical data from the China National Notifiable Infectious Disease Reporting Information System. Daily meteorological data were obtained from the China Integrated Meteorological Information Sharing System. The minimum temperature for transmission was identified using data fitting and the Ross-Macdonald model. Correlations and interactive effects were examined using Spearman’s rank correlation and multivariate analysis of variance. A probit regression model to describe the incidence of dengue fever from 2008 to 2016 and forecast the 2017 incidence was constructed, based on key meteorological factors, interactive effects, mosquito-vector factors, and other important factors.

Results

We found the minimum temperature suitable for dengue transmission was ≥18°C, and as 97.91% of cases occurred when the minimum temperature was above 18 °C, the data were used for model training and construction. Epidemics of dengue are related to mean temperature, maximum/minimum and mean atmospheric pressure, and mean relative humidity. Moreover, interactions occur between mean temperature, minimum atmospheric pressure, and mean relative humidity. Our weekly probit regression prediction model is 0.72. Prediction of dengue cases for the first 41 weeks of 2017 exhibited goodness of fit of 0.60.

Conclusion

Our model was accurate and timely, with consideration of interactive effects between meteorological factors.

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<![CDATA[Student engagement, assessed using heart rate, shows no reset following active learning sessions in lectures]]> https://www.researchpad.co/article/Nf5514316-08af-4907-81a8-d6c8d0a0ef3a

Heart rate can be used as a measure of cognitive engagement. We measured average student heart rates during medical school lecture classes using wristwatch-style monitors. Analysis of 42 classes showed a steady decline in heart rate from the beginning to end of a lecture class. Active learning sessions (peer-discussion based problem solving) resulted in a significant uptick in heart rate, but this returned to the average level immediately following the active learning period. This is the first statistically robust assessment of changes in heart rate during the course of college lecture classes and indicates that personal heart rate monitors may be useful tools for assessment of different teaching modalities. The key findings suggest that the value of active learning within the classroom resides in the activity itself and not in an increase in engagement or reset in attention during the didactic period following an active learning session.

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<![CDATA[Microglia exit the CNS in spinal root avulsion]]> https://www.researchpad.co/article/5c79a3e5d5eed0c4841d1bf2

Microglia are central nervous system (CNS)-resident cells. Their ability to migrate outside of the CNS, however, is not understood. Using time-lapse imaging in an obstetrical brachial plexus injury (OBPI) model, we show that microglia squeeze through the spinal boundary and emigrate to peripheral spinal roots. Although both macrophages and microglia respond, microglia are the debris-clearing cell. Once outside the CNS, microglia re-enter the spinal cord in an altered state. These peripheral nervous system (PNS)-experienced microglia can travel to distal CNS areas from the injury site, including the brain, with debris. This emigration is balanced by two mechanisms—induced emigration via N-methyl-D-aspartate receptor (NMDA) dependence and restriction via contact-dependent cellular repulsion with macrophages. These discoveries open the possibility that microglia can migrate outside of their textbook-defined regions in disease states.

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<![CDATA[Expected total thyroxine (TT4) concentrations and outlier values in 531,765 cats in the United States (2014–2015)]]> https://www.researchpad.co/article/5c89778cd5eed0c4847d2f8c

Background

Levels exceeding the standard reference interval (RI) for total thyroxine (TT4) concentrations are diagnostic for hyperthyroidism, however some hyperthyroid cats have TT4 values within the RI. Determining outlier TT4 concentrations should aid practitioners in identification of hyperthyroidism. The objective of this study was to determine the expected distribution of TT4 concentration using a large population of cats (531,765) of unknown health status to identify unexpected TT4 concentrations (outlier), and determine whether this concentration changes with age.

Methodology/Principle findings

This study is a population-based, retrospective study evaluating an electronic database of laboratory results to identify unique TT4 measurement between January 2014 and July 2015. An expected distribution of TT4 concentrations was determined using a large population of cats (531,765) of unknown health status, and this in turn was used to identify unexpected TT4 concentrations (outlier) and determine whether this concentration changes with age. All cats between the age of 1 and 9 years (n = 141,294) had the same expected distribution of TT4 concentration (0.5–3.5ug/dL), and cats with a TT4 value >3.5ug/dL were determined to be unexpected outliers. There was a steep and progressive rise in both the total number and percentage of statistical outliers in the feline population as a function of age. The greatest acceleration in the percentage of outliers occurred between the age of 7 and 14 years, which was up to 4.6 times the rate seen between the age of 3 and 7 years.

Conclusions

TT4 concentrations >3.5ug/dL represent outliers from the expected distribution of TT4 concentration. Furthermore, age has a strong influence on the proportion of cats. These findings suggest that patients with TT4 concentrations >3.5ug/dL should be more closely evaluated for hyperthyroidism, particularly between the ages of 7 and 14 years. This finding may aid clinicians in earlier identification of hyperthyroidism in at-risk patients.

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<![CDATA[Normalization of large-scale behavioural data collected from zebrafish]]> https://www.researchpad.co/article/5c706738d5eed0c4847c6c63

Many contemporary neuroscience experiments utilize high-throughput approaches to simultaneously collect behavioural data from many animals. The resulting data are often complex in structure and are subjected to systematic biases, which require new approaches for analysis and normalization. This study addressed the normalization need by establishing an approach based on linear-regression modeling. The model was established using a dataset of visual motor response (VMR) obtained from several strains of wild-type (WT) zebrafish collected at multiple stages of development. The VMR is a locomotor response triggered by drastic light change, and is commonly measured repeatedly from multiple larvae arrayed in 96-well plates. This assay is subjected to several systematic variations. For example, the light emitted by the machine varies slightly from well to well. In addition to the light-intensity variation, biological replication also created batch-batch variation. These systematic variations may result in differences in the VMR and must be normalized. Our normalization approach explicitly modeled the effect of these systematic variations on VMR. It also normalized the activity profiles of different conditions to a common baseline. Our approach is versatile, as it can incorporate different normalization needs as separate factors. The versatility was demonstrated by an integrated normalization of three factors: light-intensity variation, batch-batch variation and baseline. After normalization, new biological insights were revealed from the data. For example, we found larvae of TL strain at 6 days post-fertilization (dpf) responded to light onset much stronger than the 9-dpf larvae, whereas previous analysis without normalization shows that their responses were relatively comparable. By removing systematic variations, our model-based normalization can facilitate downstream statistical comparisons and aid detecting true biological differences in high-throughput studies of neurobehaviour.

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<![CDATA[Analysis of development and evolution rules of civil aviation in China based on life cycle theory]]> https://www.researchpad.co/article/5c76fe58d5eed0c484e5b913

The development of CAAC began in the early days of 1949. From a comparatively less popular means of transport to the world's second largest by volume, this means of transport has undergone major and minor changes in the last 70 years. It is not known whether there are significant laws in the process of development. For this reason, we analyze the statistical indicators of the development of civil aviation transport and select representative indicators, namely, the total turnover of transport, the number of routes, the number of aircraft, the number of transport aircraft, and the number of domestic city connections. At the same time, the life cycle theory is introduced, and the typical growth curve model is used to fit the data. It is found that the evolution life cycle of civil aviation in China can be divided into three stages: the first life cycle stage from 1950 to 1981, the second from 1982 to 2003, and the third from 2004 to 2017. Each life cycle follows the growth characteristics of occurrence, growth and maturity, and each life cycle has a time range of approximately 30 years. At present, China's civil aviation industry is in the period of rapid growth in the third life cycle. This industry is expected to reach maturity in approximately 2026 and then to begin to grow slowly. Relevant departments can adopt corresponding development strategies to guide the smooth development of civil aviation in accordance with the growth law of the development and evolution life cycle of civil aviation in China.

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<![CDATA[Evidence that nonsignificant results are sometimes preferred: Reverse P-hacking or selective reporting?]]> https://www.researchpad.co/article/5c57e687d5eed0c484ef35c2

There is increased concern about poor scientific practices arising from an excessive focus on P-values. Two particularly worrisome practices are selective reporting of significant results and ‘P-hacking’. The latter is the manipulation of data collection, usage, or analyses to obtain statistically significant outcomes. Here, we introduce the novel, to our knowledge, concepts of selective reporting of nonsignificant results and ‘reverse P-hacking’ whereby researchers ensure that tests produce a nonsignificant result. We test whether these practices occur in experiments in which researchers randomly assign subjects to treatment and control groups to minimise differences in confounding variables that might affect the focal outcome. By chance alone, 5% of tests for a group difference in confounding variables should yield a significant result (P < 0.05). If researchers less often report significant findings and/or reverse P-hack to avoid significant outcomes that undermine the ethos that experimental and control groups only differ with respect to actively manipulated variables, we expect significant results from tests for group differences to be under-represented in the literature. We surveyed the behavioural ecology literature and found significantly more nonsignificant P-values reported for tests of group differences in potentially confounding variables than the expected 95% (P = 0.005; N = 250 studies). This novel, to our knowledge, publication bias could result from selective reporting of nonsignificant results and/or from reverse P-hacking. We encourage others to test for a bias toward publishing nonsignificant results in the equivalent context in their own research discipline.

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<![CDATA[The graduation shift of German universities of applied sciences]]> https://www.researchpad.co/article/5c57e6e5d5eed0c484ef41e7

In research into higher education, the evaluation of completion and dropout rates has generated a steady stream of interest for decades. While most studies only calculate quotes using student and graduate numbers for both phenomena, we propose to additionally consider the budget available to universities. We transfer the idea of the excellence shift indicator [1] from the research to the teaching area, in particular to the completion rate of educational entities. The graduation shift shows the institutions’ ability to produce graduates as measured against their basic academic teaching efficiency. It is an important advantage of the graduation shift that it avoids the well-known heterogeneity problem in efficiency measurements. Our study is based on German universities of applied science. Given their politically determined focus on education, this dataset is well-suited for introducing and evaluating the graduation shift. Using a comprehensive dataset covering the years 2008 to 2013, we show that the graduation shift produces results, which correlate closely with the results of the well-known graduation rate and standard Data Envelopment Analysis (DEA). Compared to the graduation rate, the graduation shift is preferable because it allows to take the budget of institutions into account. Compared to the DEA, the computation of the graduation shift is easy, the results are robust, and non-economists can understand them results. Thus, we recommend the graduation shift as an alternative method of efficiency measurement in the teaching area.

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<![CDATA[Analysis of real crashes against metal roadside barriers]]> https://www.researchpad.co/article/5c61e8d9d5eed0c48496f253

Objective

Metal Road Safety Barriers (MRSB) are one of the devices implemented in roadsides to mitigate the consequences of run-off crashes. In Europe, they have to meet the requirements of the European Standard EN-1317-2. This article analyzes a set of run-off crashes against MRSB, for which an in-depth investigation has been performed, comparing them with the standard tests. It has been observed that in many of these real crashes, the barriers have not worked properly in spite of having passed these standard tests. This paper demonstrates which variables may be responsible for this, with the objective of helping to improve the current test standard through the analysis of new test variables.

Methods

Multidimensional Scaling, a dimension reduction multivariate statistical technique, has been used to better understand how real crashes compare to standard tests, using several impact variables at the same time. Then, a statistical analysis has been developed to show the influence of the “Relative orientation impact angle” on the performance of the MRSB.

Results

Most of the real crashes analyzed are close to “TB11” and “TB32” standard tests. In many of these real crashes, the “Relative orientation impact angle” is very different from the “Impact angle”, and in these situations, the vehicle is not safely redirected to the road concerning the so-called “Exit-Box”.

Conclusions

MRSB are not working properly in some situations that are not far from the standard tests. To handle this, it could be interesting to include the “Relative orientation impact angle” as a control variable in new versions of the EN-1317-2 tests to guarantee the behavior of the MRSB. These results can help to adapt some test variables from the EN-1317-2 to what is happening in crashes.

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<![CDATA[Intensive longitudinal modelling predicts diurnal activity of salivary alpha-amylase]]> https://www.researchpad.co/article/5c5217f6d5eed0c484795c77

Salivary alpha-amylase (sAA) activity has been widely used in psychological and medical research as a surrogate marker of sympathetic nervous system activation, though its utility remains controversial. The aim of this work was to compare alternative intensive longitudinal models of sAA data: (a) a traditional model, where sAA is a function of hour (hr) and hr squared (sAAj,t = f(hr, hr2), and (b) an autoregressive model, where values of sAA are a function of previous values (sAAj,t = f(sAA j,t-1, sAA j,t-2, , sAA j,t-p). Nineteen normal subjects (9 males and 10 females) participated in the experiments and measurements were performed every hr between 9:00 and 21:00 hr. Thus, a total of 13 measurements were obtained per participant. The Napierian logarithm of the enzymatic activity of sAA was analysed. Data showed that a second-order autoregressive (AR(2)) model was more parsimonious and fitted better than the traditional multilevel quadratic model. Therefore, sAA follows a process whereby, to forecast its value at any given time, sAA values one and two hr prior to that time (sAA j,t = f(SAAj,t-1, SAAj,t-2) are most predictive, thus indicating that sAA has its own inertia, with a “memory” of the two previous hr. These novel findings highlight the relevance of intensive longitudinal models in physiological data analysis and have considerable implications for physiological and biobehavioural research involving sAA measurements and other stress-related biomarkers.

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<![CDATA[Characterization of advanced glycation end products and their receptor (RAGE) in an animal model of myocardial infarction]]> https://www.researchpad.co/article/5c42438bd5eed0c4845e0546

Circulating advanced glycation end products (AGE) and their receptor, RAGE, are increased after a myocardial infarction (MI) episode and seem to be associated with worse prognosis in patients. Despite the increasing importance of these molecules in the course of cardiac diseases, they have never been characterized in an animal model of MI. Thus, the aim of this study was to characterize AGE formation and RAGE expression in plasma and cardiac tissue during cardiac remodeling after MI in rats. Adult male Wistar rats were randomized to receive sham surgery (n = 15) or MI induction (n = 14) by left anterior descending coronary artery ligation. The MI group was stratified into two subgroups based on postoperative left ventricular ejection fraction: low (MIlowEF) and intermediate (MIintermEF). Echocardiography findings and plasma levels of AGEs, protein carbonyl, and free amines were assessed at baseline and 2, 30, and 120 days postoperatively. At the end of follow-up, the heart was harvested for AGE and RAGE evaluation. No differences were observed in AGE formation in plasma, except for a decrease in absorbance in MIlowEF at the end of follow-up. A decrease in yellowish-brown AGEs in heart homogenate was found, which was confirmed by immunodetection of N-ε-carboxymethyl-lysine. No differences could be seen in plasma RAGE levels among the groups, despite an increase in MI groups over the time. However, MI animals presented an increase of 50% in heart RAGE at the end of the follow-up. Despite the inflammatory and oxidative profile of experimental MI in rats, there was no increase in plasma AGE or RAGE levels. However, AGE levels in cardiac tissue declined. Thus, we suggest that the rat MI model should be employed with caution when studying the AGE-RAGE signaling axis or anti-AGE drugs for not reflecting previous clinical findings.

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<![CDATA[Sounding the alarm: Defining thresholds to trigger a public health response to monkeypox]]> https://www.researchpad.co/article/5c25450bd5eed0c48442bd8e

Endemic to the Democratic Republic of the Congo (DRC), monkeypox is a zoonotic disease that causes smallpox-like illness in humans. Observed fluctuations in reported cases over time raises questions about when it is appropriate to mount a public health response, and what specific actions should be taken. We evaluated three different thresholds to differentiate between baseline and heightened disease incidence, and propose a novel, tiered algorithm for public health action. Monkeypox surveillance data from Tshuapa Province, 2011–2013, were used to calculate three different statistical thresholds: Cullen, c-sum, and a World Health Organization (WHO) method based on monthly incidence. When the observed cases exceeded the threshold for a given month, that month was considered to be ‘aberrant’. For each approach, the number of aberrant months detected was summed by year—each method produced vastly different results. The Cullen approach generated a number of aberrant signals over the period of consideration (9/36 months). The c-sum method was the most sensitive (30/36 months), followed by the WHO method (12/24 months). We conclude that triggering public health action based on signals detected by a single method may be inefficient and overly simplistic for monkeypox. We propose instead a response algorithm that integrates an objective threshold (WHO method) with contextual information about epidemiological and spatiotemporal links between suspected cases to determine whether a response should be operating under i) routine surveillance ii) alert status, or iii) outbreak status. This framework could be modified and adopted by national and zone level health workers in monkeypox-endemic countries. Lastly, we discuss considerations for selecting thresholds for monkeypox outbreaks across gradients of endemicity and public health resources.

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<![CDATA[A validation of the PAWPER XL-MAC tape for total body weight estimation in preschool children from low- and middle-income countries]]> https://www.researchpad.co/article/5c3d011ad5eed0c484038543

Importance

The PAWPER tape system is one of the three most accurate paediatric weight estimation systems in the world. The latest version of the tape, which does not rely on a subjective assessment of habitus, is the PAWPER XL-MAC method which uses length and mid-arm circumference (MAC) to estimate weight. It was derived and validated in a population in the USA and has not yet been fully validated in a population from a resource-limited setting.

Objective

The objective of this study was to evaluate the performance of the PAWPER XL-MAC tape weight estimation system in a large dataset sample of children from resource-limited settings.

Methods

This was a “virtual” study in which weight estimates were generated using the PAWPER XL-MAC tape and Broselow tape 2007B and 2011A editions in a very large open access dataset. The dataset contained anthropometric information of children aged 6 to 59 months from standardised nutritional surveys in 51 low- and middle-income countries. The performance of PAWPER XL-MAC method was compared with the Broselow tape and a new length- and habitus-based tape, the Ralston method.

Main outcomes and measures

The bias of the weight estimation methods was assessed using the mean percentage error (MPE) and precision using the 95% limits of agreement (LOA) of the MPE. The overall accuracy was denoted by the percentage of weight estimates falling within 10% and 20% of actual weight (abbreviated as p10 and p20 respectively).

Results

The MPE (LOA) for the PAWPER XL-MAC tape, the Broselow 2007B and 2011A and Ralston method were 1.9 (-15.3, 19.2), 5.4 (-15.9, 26.7), 7.7 (-13.3, 30.5) and -0.7 (-20.2, 19.3) respectively. The p10 and p20 for each method were 79.3% and 96.9% for the PAWPER XL-MAC tape, 64.3% and 91.0% for the Broselow tape 2007B, 55.5% and 85.9% for the Broselow tape 2011A and 67.4 and 94.0% for the Ralston method respectively. The PAWPER XL-MAC system was statistically significantly more accurate than the Broselow tape 2011A, the Broselow tape 2007B and the Ralston method. The relative difference in accuracy (p10) was 43% (odds ratio 4.4 (4.4, 4.5), p<0.001), 23% (odds ratio 2.9 (2.8, 2.9), p<0.001) and 18% (odds ratio 1.8 (1.8, 1.8), p<0.001) compared to each method, respectively.

Conclusions and relevance

The PAWPER XL-MAC tape performed well in this study and was statistically significantly more accurate than both the Broselow tape editions and the Ralston method. This difference was substantial and clinically important. The tape did not perform as well at extremes of habitus-type, however, and might benefit from recalibration.

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<![CDATA[Cardiorespiratory fitness data from 18,189 participants who underwent treadmill cardiopulmonary exercise testing in a Brazilian population]]> https://www.researchpad.co/article/5c3fa5a8d5eed0c484ca6ff7

Purpose

Cardiorespiratory fitness is inversely associated with a high risk of cardiovascular disease, all-cause mortality, and mortality attributable to various cancers. It is often estimated indirectly using mathematical formulas for estimating oxygen uptake. Cardiopulmonary exercise testing, especially oxygen uptake, represents the “gold standard” for assessing exercise capacity. The purpose of this report was to develop reference standards for exercise capacity by establishing cardiorespiratory fitness values derived from cardiopulmonary exercise testing in a Brazilian population. We focused on oxygen uptake standards and compared the maximal oxygen uptake [mLO2·kg-1·min-1] values with those in the existing literature.

Methods

A database was constructed using reports from cardiopulmonary exercise testing performed at Fleury laboratory. The final cohort included 18,189 individuals considered to be free of structural heart disease. Percentiles of maximal oxygen uptake for men and women were determined for six age groups between 7 and 84 years. We compared the values with existing reference data from patients from Norway and the United States.

Results

There were significant differences in maximal oxygen uptake between sexes and across the age groups. In our cohort, the 50th percentile maximal oxygen uptake values for men and women decreased from 44.7 and 36.3 mLO2·kg-1·min-1 to 28.4 and 22.3 mLO2·kg-1·min-1 for patients aged 20–29 years to patients aged 60–69 years, respectively. For each age group, both Norwegian men and women had greater cardiorespiratory fitness than cohorts in the United States and Brazil.

Conclusion

To our knowledge, our analysis represents the largest reference data for cardiorespiratory fitness based on treadmill cardiopulmonary exercise testing. Our findings provide reference values of maximal oxygen uptake measurements from treadmill tests in Brazilian populations that are more accurate than previous standard values based on workload-derived estimations. This data may also add information to the global data used for the interpretation of cardiorespiratory fitness.

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<![CDATA[Citizen science in data and resource-limited areas: A tool to detect long-term ecosystem changes]]> https://www.researchpad.co/article/5c3fa5d0d5eed0c484ca8e59

Coral reefs are threatened by numerous global and local stressors. In the face of predicted large-scale coral degradation over the coming decades, the importance of long-term monitoring of stress-induced ecosystem changes has been widely recognised. In areas where sustained funding is unavailable, citizen science monitoring has the potential to be a powerful alternative to conventional monitoring programmes. In this study we used data collected by volunteers in Southeast Sulawesi (Indonesia), to demonstrate the potential of marine citizen science programmes to provide scientifically sound information necessary for detecting ecosystem changes in areas where no alternative data are available. Data were collected annually between 2002 and 2012 and consisted of percent benthic biotic and abiotic cover and fish counts. Analyses revealed long-term coral reef ecosystem change. We observed a continuous decline of hard coral, which in turn had a significant effect on the associated fishes, at community, family and species levels. We provide evidence of the importance of marine citizen science programmes in detecting long-term ecosystem change as an effective way of delivering conservation data to local government and national agencies. This is particularly true for areas where funding for monitoring is unavailable, resulting in an absence of ecological data. For citizen science data to contribute to ecological monitoring and local decision-making, the data collection protocols need to adhere to sound scientific standards, and protocols for data evaluation need to be available to local stakeholders. Here, we describe the monitoring design, data treatment and statistical analyses to be used as potential guidelines in future marine citizen science projects.

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<![CDATA[Conserved mRNA-granule component Scd6 targets Dhh1 to repress translation initiation and activates Dcp2-mediated mRNA decay in vivo]]> https://www.researchpad.co/article/5c141f0dd5eed0c484d296ca

Scd6 protein family members are evolutionarily conserved components of translationally silent mRNA granules. Yeast Scd6 interacts with Dcp2 and Dhh1, respectively a subunit and a regulator of the mRNA decapping enzyme, and also associates with translation initiation factor eIF4G to inhibit translation in cell extracts. However, the role of Scd6 in mRNA turnover and translational repression in vivo is unclear. We demonstrate that tethering Scd6 to a GFP reporter mRNA reduces mRNA abundance via Dcp2 and suppresses reporter mRNA translation via Dhh1. Thus, in a dcp2Δ mutant, tethered Scd6 reduces GFP protein expression with little effect on mRNA abundance, whereas tethered Scd6 has no impact on GFP protein or mRNA expression in a dcp2Δ dhh1Δ double mutant. The conserved LSm domain of Scd6 is required for translational repression and mRNA turnover by tethered Scd6. Both functions are enhanced in a ccr4Δ mutant, suggesting that the deadenylase function of Ccr4-Not complex interferes with a more efficient repression pathway enlisted by Scd6. Ribosome profiling and RNA-Seq analysis of scd6Δ and dhh1Δ mutants suggests that Scd6 cooperates with Dhh1 in translational repression and turnover of particular native mRNAs, with both processes dependent on Dcp2. Our results suggest that Scd6 can (i) recruit Dhh1 to confer translational repression and (ii) activate mRNA decapping by Dcp2 with attendant degradation of specific mRNAs in vivo, in a manner dependent on the Scd6 LSm domain and modulated by Ccr4.

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