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New dietary-based concepts are needed for treatment and effective prevention of overweight and obesity. The primary objective was to investigate if reduction in appetite is associated with improved weight loss maintenance. This cohort study was nested within the European Commission project Satiety Innovation (SATIN). Participants achieving ≥8% weight loss during an initial 8-week low-energy formula diet were included in a 12-week randomised double-blind parallel weight loss maintenance intervention. The intervention included food products designed to reduce appetite or matching controls along with instructions to follow national dietary guidelines. Appetite was assessed by ad libitum energy intake and self-reported appetite evaluations using visual analogue scales during standardised appetite probe days. These were evaluated at the first day of the maintenance period compared with baseline (acute effects after a single exposure of intervention products) and post-maintenance compared with baseline (sustained effects after repeated exposures of intervention products) regardless of randomisation. A total of 181 participants (forty-seven men and 134 women) completed the study. Sustained reduction in 24-h energy intake was associated with improved weight loss maintenance (R 0·37; P = 0·001), whereas the association was not found acutely (P = 0·91). Suppression in self-reported appetite was associated with improved weight loss maintenance both acutely (R −0·32; P = 0·033) and sustained (R −0·33; P = 0·042). Reduction in appetite seems to be associated with improved body weight management, making appetite-reducing food products an interesting strategy for dietary-based concepts.
Background: Intracranial mycotic aneurysms are rare forms of vascular abnormalities. They are typically fragile and have high tendency to bleed. Even when they are successfully secured upon intervention, the medical management can be challenging in presence of other non-ruptured aneurysms and concomitant cerebral vasospasm. Methods: A 31 year old female was admitted with right sided large intracerebral hemorrhage due to ruptured mycotic MCA aneurysm. She was also known with severe tricuspid regurgitation from drug abuse. Others aneurysms were also located intracranially and extracranially, including subclavian and renal arteries. Results: The MCA aneurysm was successfully clipped during decompressive craniectomy. The non-ruptured left ACA aneurysm was occluded through endovascular intervention. Due to cardiac condition and presence of other non-secured extarcranial aneurysms, we followed the MNI protocol for treating cerebral vasospsam by milrinone infusion. The treatment was successful for over three weeks until another micro-aneurysm had ruptured which had lead to severe and rapid clinical deterioration, that had lead eventually to death. Conclusions: Intracranial mycotic aneurysms remain challenging. Patients should be selected for surgical clipping versus endovascular intervention based on clinical state and radiological features. We suggest using milrinone over induced hypertension therapy for post-intervention cerebral vasospasm in order to lower the risk for rupturing non-secured aneurysms.
By applying a display ecology to the Deeper, Wider, Faster proactive, simultaneous telescope observing campaign, we have shown a dramatic reduction in the time taken to inspect DECam CCD images for potential transient candidates and to produce time-critical triggers to standby telescopes. We also show how facilitating rapid corroboration of potential candidates and the exclusion of non-candidates improves the accuracy of detection; and establish that a practical and enjoyable workspace can improve the experience of an otherwise taxing task for astronomers. We provide a critical road test of two advanced displays in a research context—a rare opportunity to demonstrate how they can be used rather than simply discuss how they might be used to accelerate discovery.
This work experimentally examines the detachment of liquid droplets from both oleophilic and oleophobic fibres, using an atomic force microscope. The droplet detachment force was found to increase with increasing fibre diameter and forces were higher for philic fibres than phobic fibres. We also considered the detachment of droplets situated on the intersection of two fibres and arrays of fibres (such as found in fibrous mats or filters) and found that the required detachment forces were higher than for similarly sized droplets on a single fibre, though not as high as expected based on theory. A model was developed to predict the detachment force, from single fibres, which agreed well with experimental results. It was found that the entire dataset (single and multiple fibres) could be best described by power law relationships.
Probit-based models relating a proportional response variable to a temporal explanatory variable, assuming that the times to response are normally distributed within the population, have been used in seed biology for describing the rate of loss of viability during seed ageing and the progress of germination over time in response to environmental signals (e.g. water, temperature). These models may be expressed as generalized linear models (GLMs) with a probit (cumulative normal distribution) link function, and, using GLM fitting procedures in current statistical software, parameters of these models are efficiently estimated while taking into account the binomial error distribution of the dependent variable. The fitted parameters can then be used to calculate the ‘traditional’ model parameters, such as the hydro- or hydrothermal time constant, the mean or median response of the seeds (e.g. mean time to death, median base water potential), and the standard deviation of the normal distribution of that response. Furthermore, through consideration of the deviance and residuals, performing model evaluation and modification can lead to improved understanding of the underlying physiological/ecological processes. However, fitting a binomial GLM is not appropriate for the cumulative count data often collected from germination studies, as successive observations are not independent, and time-to-event/survival analysis should be considered instead. This review discusses well-known probit-based models, providing advice on how to collect appropriate data and fit the models to those data, and gives an overview of alternative analysis approaches to improve understanding of the underlying mechanisms of seed dormancy and germination behaviour.
Depression is a common and important cause of morbidity and mortality worldwide. It is commonly treated with antidepressants and/or psychological therapy, but some people prefer alternative approaches such as exercise. There are a number of theoretical reasons why exercise may improve depression. This is an update of a review first published in 2009.
Our aim in this book is to explain and illustrate the fundamental statistical concepts required for designing efficient experiments to answer real questions. This book has evolved from a previous book written by the first author. That book was based on 25 years of experience of designing experiments for research scientists and of teaching the concepts of statistical design both to statisticians and to experimenters. The present book is based on approximately a combined 100 years of experience of designing experiments for research scientists, and of teaching the concepts of statistical design both to statisticians and to experimenters.
The development of statistical philosophy about the design of experiments has always been dominated by mathematical theory. In contrast the influence of the availability of vastly improved computing facilities on teaching, textbooks and, most crucially, practical experimentation has been relatively small. The existence of statistical programs capable of analysing the results from any designed experiment does not imply any changes in the main statistical concepts of design. However, developments from these concepts have often been restricted by the earlier need to develop mathematical theory for design in such a way that the results from the designs could be analysed without recourse to computers. The fundamental concepts continually require reexamination and reinterpretation outside the limits implied by classical mathematical theory so that the full range of design possibilities may be considered. The result of the revolution in computing facilities is that the design of experiments should become a much wider and more exciting subject. We hope that this book will display that breadth and excitement.
(a) In an animal feeding experiment, six dietary treatments are to be compared. The diets are all possible combinations of three different levels of molasses at two energy levels. Twenty-four sheep are available and each sheep can be fed a different diet in each of two time periods. It is expected that there will be large differences in nutritional performances between sheep and some systematic differences between the results for the first and second periods. The structure of the experimental units therefore has two blocking classifications, giving a 24 × 2 row-and-column structure. The treatments have a 3 × 2 structure and main effect comparisons, particularly between the three levels of molasses, are the principal area of interest.
(b) An industrial experiment is to be planned to investigate the effects of varying seven factors in a chemical process. Eight treatment combinations can be tested using the same batch of basic material. Eight different batches of material will be available, and it is expected that theremay be substantial differences in output for sample units from the different batches. If it is decided to use two levels of each factor how shall the 64 treatment combinations to be included in the experiment be chosen, and how shall they be allocated to the eight blocks, or batches?
(c) An experiment on absorption of sugar by rabbits is to be designed to compare eight experimental treatments.
(a) An experiment to examine the pattern of variation over time of a particular chemical constituent of blood involved sampling the blood of nine chickens on 25 weekly occasions. The principal interest is in the variation of the chemical over the 25 times, the nine chickens being included to provide replication. The chemical analysis is complex and long and a set of at most ten blood samples can be analysed concurrently. It is known that there may be substantial differences in the results of the chemical analysis between different sets of samples. How should the 225 samples (25 times for nine chickens) be allocated to sets of ten (or fewer) so that comparisons between the 25 times are made as precise as possible?
(b) In an experiment to compare diets for cows the experimenter has five diet treatments that he wishes to compare. The diets have to be fed to fistulated (surgically prepared) cows so that the performance of the cows can be monitored throughout the application of each diet. Nine such cows are available for sufficient time that four periods of observation can be used for each cow, providing a set of 9 × 4 = 36 observations. Concerned that there will be differences between cows, so that cows have to be treated as a blocking structure, the experimenter had already decided before consulting a statistician that he could only test four of the diet treatments, each cow receiving each diet once.
(a) In an experiment to investigate the effect of training on human-computer-human interactions, six subjects were randomly allocated to each of four training programmes. Subjects were then paired into 12 blocks using two replicates of an unreduced balanced incomplete block design. Each pair carried out a conversation through a computer ‘chat’ program. In addition to several response variables measured on each subject individually, each pair was given a score by an independent observer, for the success of their interaction.
We have only a single response representing each block. Can we use this information and, if so, how? If we can, do the block totals contain useful information about the effects of treatments on other responses? Does this affect how we should design the experiment? In particular, for this response, should we have used some blocks with both subjects getting the same treatment?
(b) Eight feeds are to be compared for their effects on the growth of young chickens. The experiment will be carried out using 32 cages, arranged in four brooders, with each brooder having four tiers of two cages. Should the experiment be designed to ensure that each treatment appears once in each brooder and once in each tier, or should we consider the brooder×tier combinations as blocks of size 2 and choose a good design for this setup? Can we do both simultaneously?
Identifying multiple levels in data
In Section 7.3 we considered the analysis for general block–treatment designs. However, in that analysis only the information about treatments from comparisons within blocks was considered.
This book is about the statistical principles behind the design of effective experiments and focuses on the practical needs of applied statisticians and experimenters engaged in design, implementation and analysis. Emphasising the logical principles of statistical design, rather than mathematical calculation, the authors demonstrate how all available information can be used to extract the clearest answers to many questions. The principles are illustrated with a wide range of examples drawn from real experiments in medicine, industry, agriculture and many experimental disciplines. Numerous exercises are given to help the reader practise techniques and to appreciate the difference that good design can make to an experimental research project. Based on Roger Mead's excellent Design of Experiments, this new edition is thoroughly revised and updated to include modern methods relevant to applications in industry, engineering and modern biology. It also contains seven new chapters on contemporary topics, including restricted randomisation and fractional replication.
In an experiment to compare different treatments, each treatment must be applied to several different units. This is because the responses from different units vary, even if the units are treated identically. If each treatment is only applied to a single unit, the results will be ambiguous – we will not be able to distinguish whether a difference in the responses from two units is caused by the different treatments, or is simply due to the inherent differences between the units.
The simplest experimental design to compare t treatments is that in which treatment 1 is applied to n1 units, treatment 2 to n2 units,… and treatment t to nt units. In many experiments the numbers of units per treatment, n1, n2, …, nt, will be equal, but this is not necessary, or even always desirable. Some treatments may be of greater importance than others, in which case more information will be needed about them, and this will be achieved by increasing the replication for these treatments. This design, in which the only recognisable difference between units is the treatments which are applied to those units, is called a completely randomised design.
However, the ambiguity, when each treatment is only applied to a single unit, is not always removed by applying each treatment to multiple units. One treatment might be ‘lucky’ in the selection of units to which it is to be applied, and another might be ‘unlucky’.
Thus far in this book we have considered the design of individual experiments and have been concerned to ensure that each experiment should provide answers to the questions which motivated the experiment as efficiently as possible. In general this has required that the variation in the experimental units be controlled so that the answers provided from each experiment should be as precise as possible. This will frequently require that there should be relatively little variation between the experimental units, i.e. the population from which the units are drawn will be narrowly defined.
However, if the population from which the units are taken is narrowly defined, then it follows logically that the results from the experiment would apply only to that narrowly defined population. This would usually be quite unacceptable to an experimenter who would hope to convince the wider world that the results from the experiment would apply for a much wider population. For example determining which variety of rice gives the best results in a highly controlled experiment on the paddy fields of a research institute is only going to be useful if that variety of rice is going to be the best for a large region within which the institute is located, and if farmers in that region believe in the results. Similarly if a new drug is shown to be an improvement on current practice, through a rigorously controlled clinical trial, the pharmaceutical company which has produced the drug will wish to promote the use of the drug across the whole population of the country, or even of several countries.