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

Distribution and Acute Stressor-Induced Activation of Corticotrophin-Releasing Hormone Neurones in the Central Nervous System of Xenopus laevis

In mammals, corticotrophin-releasing hormone (CRH) and related peptides are known to play essential roles in the regulation of neuroendocrine, autonomic and behavioural responses to physical and emotional stress. In nonmammalian species, CRH-like peptides are hypothesized to play similar neuroendocrine and neurocrine roles. However, there is relatively little detailed information on the distribution of CRH neurones in the central nervous system (CNS) of nonmammalian vertebrates, and there are currently no comparative data on stress-induced changes in CRH neuronal physiology. We used a specific, affinity-purified antibody raised against synthetic Xenopus laevis CRH to map the distribution of CRH in the CNS of juvenile South African clawed frogs . We then analysed stress-induced changes in CRH immunoreactivity (CRH-ir) throughout the CNS. We found that CRH-positive cell bodies and fibres are widely distributed throughout the brain and rostral spinal cord of juvenile X. laevis . Strong CRH-immunoreactovity (ir) was found in cell bodies and fibres in the anterior preoptic area (POA, an area homologous to the mammalian paraventricular nucleus) and the external zone of the median eminence. Specific CRH-ir cell bodies and fibres were also identified in the septum, pallium and striatum in the telencephalon; the amygdala, bed nucleus of the stria terminalis and various hypothalamic and thalamic nuclei in the diencephalon; the tectum, torus semicircularis and tegmental nuclei of the mesencephalon; the cerebellum and locus coeruleus in the rhombencephalon; and the ventral horn of the rostral spinal cord. To determine if exposure to an acute physical stressor alters CRH neuronal physiology, we exposed juvenile frogs to shaking/handling and conducted morphometric analysis. Plasma corticosterone was significantly elevated by 30 min after exposure to the stressor and continued to increase up to 6 h. Morphometric analysis of CRH-ir after 4 h of stress showed a significant increase in CRH-ir in parvocellular neurones of the anterior preoptic area, the medial amygdala and the bed nucleus of the stria terminalis, but not in other brain regions. The stress-induced increase in CRH-ir in the POA was associated with increased Fos-like immunoreactivity (Fos-LI), and confocal microscopy showed that CRH-ir colocalized with Fos-LI in a subset of Fos-LI-positive neurones. Our results support the view that the basic pattern of CNS CRH expression arose early in vertebrate evolution and lend further support to earlier studies suggesting that amphibians may be a transitional species for descending CRH-ergic pathways. Furthermore, CRH neurones in the frog brain exhibit changes in response to a physical stressor that parallel those seen in mammals, and thus are likely to play an active role in mediating neuroendocrine, behavioural and autonomic stress responses.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73585/1/j.1365-2826.2004.01246.x.pd

Phenotypic Switching of Nonpeptidergic Cutaneous Sensory Neurons following Peripheral Nerve Injury

In adult mammals, the phenotype of half of all pain-sensing (nociceptive) sensory neurons is tonically modulated by growth factors in the glial cell line-derived neurotrophic factor (GDNF) family that includes GDNF, artemin (ARTN) and neurturin (NRTN). Each family member binds a distinct GFRα family co-receptor, such that GDNF, NRTN and ARTN bind GFRα1, -α2, and -α3, respectively. Previous studies revealed transcriptional regulation of all three receptors in following axotomy, possibly in response to changes in growth factor availability. Here, we examined changes in the expression of GFRα1-3 in response to injury in vivo and in vitro. We found that after dissociation of adult sensory ganglia, up to 27% of neurons die within 4 days (d) in culture and this can be prevented by nerve growth factor (NGF), GDNF and ARTN, but not NRTN. Moreover, up-regulation of ATF3 (a marker of neuronal injury) in vitro could be prevented by NGF and ARTN, but not by GDNF or NRTN. The lack of NRTN efficacy was correlated with rapid and near-complete loss of GFRα2 immunoreactivity. By retrogradely-labeling cutaneous afferents in vivo prior to nerve cut, we demonstrated that GFRα2-positive neurons switch phenotype following injury and begin to express GFRα3 as well as the capsaicin receptor, transient receptor potential vanilloid 1(TRPV1), an important transducer of noxious stimuli. This switch was correlated with down-regulation of Runt-related transcription factor 1 (Runx1), a transcription factor that controls expression of GFRα2 and TRPV1 during development. These studies show that NRTN-responsive neurons are unique with respect to their plasticity and response to injury, and suggest that Runx1 plays an ongoing modulatory role in the adult