Bayesian optimization for materials design

We introduce Bayesian optimization, a technique developed for optimizing time-consuming engineering simulations and for fitting machine learning models on large datasets. Bayesian optimization guides the choice of experiments during materials design and discovery to find good material designs in as few experiments as possible. We focus on the case when materials designs are parameterized by a low-dimensional vector. Bayesian optimization is built on a statistical technique called Gaussian process regression, which allows predicting the performance of a new design based on previously tested designs. After providing a detailed introduction to Gaussian process regression, we introduce two Bayesian optimization methods: expected improvement, for design problems with noise-free evaluations; and the knowledge-gradient method, which generalizes expected improvement and may be used in design problems with noisy evaluations. Both methods are derived using a value-of-information analysis, and enjoy one-step Bayes-optimality

The Search for Invariance: Repeated Positive Testing Serves the Goals of Causal Learning

Positive testing is characteristic of exploratory behavior, yet it seems to be at odds with the aim of information seeking. After all, repeated demonstrations of one’s current hypothesis often produce the same evidence and fail to distinguish it from potential alternatives. Research on the development of scientific reasoning and adult rule learning have both documented and attempted to explain this behavior. The current chapter reviews this prior work and introduces a novel theoretical account—the Search for Invariance (SI) hypothesis—which suggests that producing multiple positive examples serves the goals of causal learning. This hypothesis draws on the interventionist framework of causal reasoning, which suggests that causal learners are concerned with the invariance of candidate hypotheses. In a probabilistic and interdependent causal world, our primary goal is to determine whether, and in what contexts, our causal hypotheses provide accurate foundations for inference and intervention—not to disconfirm their alternatives. By recognizing the central role of invariance in causal learning, the phenomenon of positive testing may be reinterpreted as a rational information-seeking strategy

Statistical Inference of Selection and Divergence from a Time-Dependent Poisson Random Field Model

We apply a recently developed time-dependent Poisson random field model to aligned DNA sequences from two related biological species to estimate selection coefficients and divergence time. We use Markov chain Monte Carlo methods to estimate species divergence time and selection coefficients for each locus. The model assumes that the selective effects of non-synonymous mutations are normally distributed across genetic loci but constant within loci, and synonymous mutations are selectively neutral. In contrast with previous models, we do not assume that the individual species are at population equilibrium after divergence. Using a data set of 91 genes in two Drosophila species, D. melanogaster and D. simulans, we estimate the species divergence time (or 1.68 million years, assuming the haploid effective population size years) and a mean selection coefficient per generation . Although the average selection coefficient is positive, the magnitude of the selection is quite small. Results from numerical simulations are also presented as an accuracy check for the time-dependent model

Molecular evolution of the membrane associated progesterone receptor in the Brachionus plicatilis (Rotifera, Monogononta) species complex

Author Posting. © Springer, 2010. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Hydrobiologia 662 (2011): 99-106, doi:10.1007/s10750-010-0484-4.Many studies have investigated physiological roles of the membrane associated progesterone receptor (MAPR), but little is known of its evolution. Marked variations in response to exogenous progesterone have been reported for four brachionid rotifer species, suggesting differences in progesterone signaling and reception. Here we report sequence variation for the MAPR gene in the Brachionus plicatilis species complex. Phylogenetic analysis of this receptor is compared with relatedness based on cytochrome c oxidase subunit 1 sequences. Nonsynonymous to synonymous site substitution rate ratios, amino acid divergence, and variations in predicted phosphorylation sites are examined to assess evolution of the MAPR among brachionid clades.National Science Foundation grant BE/GenEn MCB-0412674E to TWS and DMW, and an NSF IGERT fellowship to HAS under DGE 0114400, supported this work

The role of the fat mass and obesity associated gene (FTO) in breast cancer risk

<p>Abstract</p> <p>Background</p> <p>Obesity has been shown to increase breast cancer risk. <it>FTO </it>is a novel gene which has been identified through genome wide association studies (GWAS) to be related to obesity. Our objective was to evaluate tissue expression of FTO in breast and the role of FTO SNPs in predicting breast cancer risk.</p> <p>Methods</p> <p>We performed a case-control study of 354 breast cancer cases and 364 controls. This study was conducted at Northwestern University. We examined the role of single nucleotide polymorphisms (SNPs) of intron 1 of <it>FTO </it>in breast cancer risk. We genotyped cases and controls for four SNPs: rs7206790, rs8047395, rs9939609 and rs1477196. We also evaluated tissue expression of FTO in normal and malignant breast tissue.</p> <p>Results</p> <p>We found that all SNPs were significantly associated with breast cancer risk with rs1477196 showing the strongest association. We showed that FTO is expressed both in normal and malignant breast tissue. We found that <it>FTO </it>genotypes provided powerful classifiers to predict breast cancer risk and a model with epistatic interactions further improved the prediction accuracy with a receiver operating characteristic (ROC) curves of 0.68.</p> <p>Conclusion</p> <p>In conclusion we have shown a significant expression of FTO in malignant and normal breast tissue and that <it>FTO </it>SNPs in intron 1 are significantly associated with breast cancer risk. Furthermore, these <it>FTO </it>SNPs are powerful classifiers in predicting breast cancer risk.</p

A Novel Microwave Sensor to Detect Specific Biomarkers in Human Cerebrospinal Fluid and Their Relationship to Cellular Ischemia During Thoracoabdominal Aortic Aneurysm Repair

Thoraco-abdominal aneurysms (TAAA) represents a particularly lethal vascular disease that without surgical repair carries a dismal prognosis. However, there is an inherent risk from surgical repair of spinal cord ischaemia that can result in paraplegia. One method of reducing this risk is cerebrospinal fluid (CSF) drainage. We believe that the CSF contains clinically significant biomarkers that can indicate impending spinal cord ischaemia. This work therefore presents a novel measurement method for proteins, namely albumin, as a precursor to further work in this area. The work uses an interdigitated electrode (IDE) sensor and shows that it is capable of detecting various concentrations of albumin (from 0 to 100 g/L) with a high degree of repeatability at 200 MHz (R2 = 0.991) and 4 GHz (R2 = 0.975)

The weight of representing the body: addressing the potentially indefinite number of body representations in healthy individuals

There is little consensus about the characteristics and number of body representations in the brain. In the present paper, we examine the main problems that are encountered when trying to dissociate multiple body representations in healthy individuals with the use of bodily illusions. Traditionally, task-dependent bodily illusion effects have been taken as evidence for dissociable underlying body representations. Although this reasoning holds well when the dissociation is made between different types of tasks that are closely linked to different body representations, it becomes problematic when found within the same response task (i.e., within the same type of representation). Hence, this experimental approach to investigating body representations runs the risk of identifying as many different body representations as there are significantly different experimental outputs. Here, we discuss and illustrate a different approach to this pluralism by shifting the focus towards investigating task-dependency of illusion outputs in combination with the type of multisensory input. Finally, we present two examples of behavioural bodily illusion experiments and apply Bayesian model selection to illustrate how this different approach of dissociating and classifying multiple body representations can be applied

Investigating organizational quality improvement systems, patient empowerment, organizational culture, professional involvement and the quality of care in European hospitals: the 'Deepening our Understanding of Quality Improvement in Europe (DUQuE)' project

BACKGROUND: Hospitals in European countries apply a wide range of quality improvement strategies. Knowledge of the effectiveness of these strategies, implemented as part of an overall hospital quality improvement system, is limited. METHODS/DESIGN: We propose to study the relationships among organisational quality improvement systems, patient empowerment, organisational culture, professionals' involvement with the quality of hospital care, including clinical effectiveness, patient safety and patient involvement. We will employ a cross-sectional, multi-level study design in which patient-level measurements are nested in hospital departments, which are in turn nested in hospitals in different EU countries. Mixed methods will be used for data collection, measurement and analysis. Hospital/care pathway level constructs that will be assessed include external pressure, hospital governance, quality improvement system, patient empowerment in quality improvement, organisational culture and professional involvement. These constructs will be assessed using questionnaires. Patient-level constructs include clinical effectiveness, patient safety and patient involvement, and will be assessed using audit of patient records, routine data and patient surveys. For the assessment of hospital and pathway level constructs we will collect data from randomly selected hospitals in eight countries. For a sample of hospitals in each country we will carry out additional data collection at patient-level related to four conditions (stroke, acute myocardial infarction, hip fracture and delivery). In addition, structural components of quality improvement systems will be assessed using visits by experienced external assessors. Data analysis will include descriptive statistics and graphical representations and methods for data reduction, classification techniques and psychometric analysis, before moving to bi-variate and multivariate analysis. The latter will be conducted at hospital and multilevel. In addition, we will apply sophisticated methodological elements such as the use of causal diagrams, outcome modelling, double robust estimation and detailed sensitivity analysis or multiple bias analyses to assess the impact of the various sources of bias. DISCUSSION: Products of the project will include a catalogue of instruments and tools that can be used to build departmental or hospital quality and safety programme and an appraisal scheme to assess the maturity of the quality improvement system for use by hospitals and by purchasers to contract hospitals

Disruption of Neuronal Autophagy by Infected Microglia Results in Neurodegeneration

There is compelling evidence to support the idea that autophagy has a protective function in neurons and its disruption results in neurodegenerative disorders. Neuronal damage is well-documented in the brains of HIV-infected individuals, and evidence of inflammation, oxidative stress, damage to synaptic and dendritic structures, and neuronal loss are present in the brains of those with HIV-associated dementia. We investigated the role of autophagy in microglia-induced neurotoxicity in primary rodent neurons, primate and human models. We demonstrate here that products of simian immunodeficiency virus (SIV)-infected microglia inhibit neuronal autophagy, resulting in decreased neuronal survival. Quantitative analysis of autophagy vacuole numbers in rat primary neurons revealed a striking loss from the processes. Assessment of multiple biochemical markers of autophagic activity confirmed the inhibition of autophagy in neurons. Importantly, autophagy could be induced in neurons through rapamycin treatment, and such treatment conferred significant protection to neurons. Two major mediators of HIV-induced neurotoxicity, tumor necrosis factor-α and glutamate, had similar effects on reducing autophagy in neurons. The mRNA level of p62 was increased in the brain in SIV encephalitis and as well as in brains from individuals with HIV dementia, and abnormal neuronal p62 dot structures immunoreactivity was present and had a similar pattern with abnormal ubiquitinylated proteins. Taken together, these results identify that induction of deficits in autophagy is a significant mechanism for neurodegenerative processes that arise from glial, as opposed to neuronal, sources, and that the maintenance of autophagy may have a pivotal role in neuroprotection in the setting of HIV infection