A linked data approach to publishing complex scientific workflows

Past data management practices in many fields of natural science, including climate research, have focused primarily on the final research output - the research publication - with less attention paid to the chain of intermediate data results and their associated metadata, including provenance. Data were often regarded merely as an adjunct to the publication, rather than a scientific resource in their own right. In this paper, we attempt to address the issues of capturing and publishing detailed workflows associated with the climate/research datasets held by the Climatic Research Unit (CRU) at the University of East Anglia. To this end, we present a customisable approach to exposing climate research workflows for the effective re-use of the associated data, through the adoption of linked-data principles, existing widely adopted citation techniques (Digital Object Identifier) and data exchange mechanisms (Open Archives Initiative Object Reuse and Exchange)

The M Dwarf Problem in the Galaxy

We present evidence that there is an M dwarf problem similar to the previously identified G dwarf and K dwarf problems: the number of low-metallicity M dwarfs is not sufficient to match simple closed-box models of local Galactic chemical evolution. We estimated the metallicity of 4141 M dwarf stars with spectra from the Sloan Digital Sky Survey (SDSS) using a molecular band strength versus metallicity calibration developed using high resolution spectra of nearby M dwarfs. Using a sample of M dwarfs with measured magnitudes, parallaxes, and metallicities, we derived a relation that describes the absolute magnitude variation as a function of metallicity. When we examined the metallicity distribution of SDSS stars, after correcting for the different volumes sampled by the magnitude-limited survey, we found that there is an M dwarf problem, with the number of M dwarfs at [Fe/H] ~ -0.5 less than 1% the number at [Fe/H] = 0, where a simple model of Galactic chemical evolution predicts a more gradual drop in star numbers with decreasing metallicity.Comment: To be published in Monthly Notices of the RAS by the Royal Astronomical Society and Blackwell Publishing. 7 pages, 3 figure

Detection of cold pain, cold allodynia and cold hyperalgesia in freely behaving rats

BACKGROUND: Pain is elicited by cold, and a major feature of many neuropathic pain states is that normally innocuous cool stimuli begin to produce pain (cold allodynia). To expand our understanding of cold induced pain states we have studied cold pain behaviors over a range of temperatures in several animal models of chronic pain. RESULTS: We demonstrate that a Peltier-cooled cold plate with ± 1°C sensitivity enables quantitative measurement of a detection withdrawal response to cold stimuli in unrestrained rats. In naïve rats the threshold for eliciting cold pain behavior is 5°C. The withdrawal threshold for cold allodynia is 15°C in both the spared nerve injury and spinal nerve ligation models of neuropathic pain. Cold hyperalgesia is present in the spared nerve injury model animals, manifesting as a reduced latency of withdrawal response threshold at temperatures that elicit cold pain in naïve rats. We also show that following the peripheral inflammation produced by intraplantar injection of complete Freund's adjuvant, a hypersensitivity to cold occurs. CONCLUSION: The peltier-cooled provides an effective means of assaying cold sensitivity in unrestrained rats. Behavioral testing of cold allodynia, hyperalgesia and pain will greatly facilitate the study of the neurobiological mechanisms involved in cold/cool sensations and enable measurement of the efficacy of pharmacological treatments to reduce these symptoms

Using mechanistic Bayesian networks to identify downstream targets of the Sonic Hedgehog pathway

Background: The topology of a biological pathway provides clues as to how a pathway operates, but rationally using this topology information with observed gene expression data remains a challenge. Results: We introduce a new general-purpose analytic method called Mechanistic Bayesian Networks (MBNs) that allows for the integration of gene expression data and known constraints within a signal or regulatory pathway to predict new downstream pathway targets. The MBN framework is implemented in an open-source Bayesian network learning package, the Python Environment for Bayesian Learning (PEBL). We demonstrate how MBNs can be used by modeling the early steps of the sonic hedgehog pathway using gene expression data from different developmental stages and genetic backgrounds in mouse. Using the MBN approach we are able to automatically identify many of the known downstream targets of the hedgehog pathway such as Gas1 and Gli1, along with a short list of likely targets such as Mig12. Conclusions: The MBN approach shown here can easily be extended to other pathways and data types to yield a more mechanistic framework for learning genetic regulatory models.Molecular and Cellular BiologyStem Cell and Regenerative Biolog

Delayed sympathetic dependence in the spared nerve injury (SNI) model of neuropathic pain

Background: Clinical and experimental studies of neuropathic pain support the hypothesis that a functional coupling between postganglionic sympathetic efferent and sensory afferent fibers contributes to the pain. We investigated whether neuropathic pain-related behavior in the spared nerve injury (SNI) rat model is dependent on the sympathetic nervous system. Results: Permanent chemical sympathectomy was achieved by daily injection of guanethidine (50 mg/kg s.c.) from age P8 to P21. SNI was performed at adulthood followed by 11 weeks of mechanical and thermal hypersensitivity testing. A significant but limited effect of the sympathectomy on SNI-induced pain sensitivity was observed. The effect was delayed and restricted to cold allodynia-like behavior: SNI-related cold scores were lower in the sympathectomized group compared to the control group at 8 and 11 weeks after the nerve injury but not before. Mechanical hypersensitivity tests (pinprick and von Frey hair threshold tests) showed no difference between groups during the study period. Concomitantly, pericellular tyrosine-hydroxylase immunoreactive basket structures were observed around dorsal root ganglia (DRG) neurons 8 weeks after SNI, but were absent at earlier time points after SNI and in sham operated controls. Conclusion: These results suggest that the early establishment of neuropathic pain-related behavior after distal nerve injury such as in the SNI model is mechanistically independent of the sympathetic system, whereas the system contributes to the maintenance, albeit after a delay of many weeks, of response to cold-related stimuli

Delayed sympathetic dependence in the spared nerve injury (SNI) model of neuropathic pain

BACKGROUND: Clinical and experimental studies of neuropathic pain support the hypothesis that a functional coupling between postganglionic sympathetic efferent and sensory afferent fibers contributes to the pain. We investigated whether neuropathic pain-related behavior in the spared nerve injury (SNI) rat model is dependent on the sympathetic nervous system. RESULTS: Permanent chemical sympathectomy was achieved by daily injection of guanethidine (50 mg/kg s.c.) from age P8 to P21. SNI was performed at adulthood followed by 11 weeks of mechanical and thermal hypersensitivity testing. A significant but limited effect of the sympathectomy on SNI-induced pain sensitivity was observed. The effect was delayed and restricted to cold allodynia-like behavior: SNI-related cold scores were lower in the sympathectomized group compared to the control group at 8 and 11 weeks after the nerve injury but not before. Mechanical hypersensitivity tests (pinprick and von Frey hair threshold tests) showed no difference between groups during the study period. Concomitantly, pericellular tyrosine-hydroxylase immunoreactive basket structures were observed around dorsal root ganglia (DRG) neurons 8 weeks after SNI, but were absent at earlier time points after SNI and in sham operated controls. CONCLUSION: These results suggest that the early establishment of neuropathic pain-related behavior after distal nerve injury such as in the SNI model is mechanistically independent of the sympathetic system, whereas the system contributes to the maintenance, albeit after a delay of many weeks, of response to cold-related stimuli

Constrained Adaptive Sensing

Suppose that we wish to estimate a vector x∈Cn from a small number of noisy linear measurements of the form y=Ax+z, where z represents measurement noise. When the vector x is sparse, meaning that it has only s nonzeros with s≪n, one can obtain a significantly more accurate estimate of x by adaptively selecting the rows of A based on the previous measurements provided that the signal-to-noise ratio (SNR) is sufficiently large. In this paper we consider the case where we wish to realize the potential of adaptivity but where the rows of A are subject to physical constraints. In particular, we examine the case where the rows of A are constrained to belong to a finite set of allowable measurement vectors. We demonstrate both the limitations and advantages of adaptive sensing in this constrained setting. We prove that for certain measurement ensembles, the benefits offered by adaptive designs fall far short of the improvements that are possible in the unconstrained adaptive setting. On the other hand, we also provide both theoretical and empirical evidence that in some scenarios adaptivity does still result in substantial improvements even in the constrained setting. To illustrate these potential gains, we propose practical algorithms for constrained adaptive sensing by exploiting connections to the theory of optimal experimental design and show that these algorithms exhibit promising performance in some representative applications