Smart Metering Early Learning Project: Synthesis Report

Smart electricity and gas meters with the offer of an in-home display are due to be rolled out to all households in Great Britain by the end of 2020. DECC commissioned this synthesis research as part of its work to support a successful smart metering implementation programme (the Programme), to offer an initial analysis of progress to date and to learn how householders can best be engaged in order to benefit from the roll-out, in particular by saving energy. This report summarises and analyses evidence from a range of sources, including three new DECC research projects into how GB householders engage with smart metering, GB and international evidence on smart metering and energy feedback, and evidence from public health behaviour change programmes

Ages on weathered Plio-Pleistocene tephra sequences, western North Island, New Zealand

Using the zircon fission-track method, we have obtained five ages on members of two strongly-weathered silicic, Pliocene-Pleistocene tephra sequences, the Kauroa and Hamilton Ash formations, in western North Island, New Zealand. These are the first numerical ages to be obtained directly on these deposits. Of the Kauroa Ash sequence, member K1 (basal unit) was dated at 2.24 ± 0.29 Ma, confirming a previous age of c. 2.25 Ma obtained (via tephrochronology)from K/Ar ages on associated basalt lava. Members K2 and K3 gave indistinguishable ages between 1.68 ± 0.12 and 1.43 ± 0.17 Ma. Member K12, a correlative of Oparau Tephra and probably also Ongatiti Ignimbrite, was dated at 1.28 ± 0.11 Ma, consistent with an age of 1.23 ± 0.02 Ma obtained by various methods on Ongatiti Ignimbrite. Palaeomagnetic measurements indicated that members K13 to K15 (top unit, Waiterimu Ash) are aged between c. 1.2 Ma and 0.78 Ma. Possible sources of the Kauroa Ash Formation include younger volcanic centres in the southern Coromandel Volcanic Zone or older volcanic centres in the Taupo Volcanic Zone, or both. Of the Hamilton Ash sequence, the basal member Ohinewai Ash (HI) was dated at 0.38 ± 0.04 Ma. This age matches those obtained by various methods on Rangitawa Tephra of 0.34-0.35 Ma, supporting correlation with this Whakamaru-caldera derived deposit. The origin of the other Hamilton Ash beds is unknown but various younger volcanic centres in the Taupo Volcanic Zone are possible sources. The topmost member, Tikotiko Ash (H6-H7), is estimated to be aged between c. 0.18 and 0.08 Ma. Various silicic pyroclastic deposits documented in North Island and in marine cores may be co-eval with members of the Kauroa Ash and Hamilton Ash sequences on the basis of their age

Scorpion toxin peptide action at the ion channel subunit level

This review categorizes functionally validated actions of defined scorpion toxin (SCTX) neuropeptides across ion channel subclasses, highlighting key trends in this rapidly evolving field. Scorpion envenomation is a common event in many tropical and subtropical countries, with neuropharmacological actions, particularly autonomic nervous system modulation, causing significant mortality. The primary active agents within scorpion venoms are a diverse group of small neuropeptides that elicit specific potent actions across a wide range of ion channel classes. The identification and functional characterisation of these SCTX peptides has tremendous potential for development of novel pharmaceuticals that advance knowledge of ion channels and establish lead compounds for treatment of excitable tissue disorders. This review delineates the unique specificities of 320 individual SCTX peptides that collectively act on 41 ion channel subclasses. Thus the SCTX research field has significant translational implications for pathophysiology spanning neurotransmission, neurohumoral signalling, sensori-motor systems and excitation-contraction coupling

Changes in predator exposure, but not diet induce phenotypic plasticity in scorpion venom

Animals embedded between trophic levels must simultaneously balance pressures to deter predators and acquire resources. Venomous animals may use venom toxins to mediate both pressures, and thus changes in this balance may alter the composition of venoms. Basic theory suggests that greater exposure to a predator should induce a larger proportion of defensive venom components relative to offensive venom components, while increases in arms races with prey will elicit the reverse. Alternatively, reducing the need for venom expenditure for food acquisition, for example due to an increase in scavenging, may reduce the production of offensive venom components. Here, we investigated changes in scorpion venom composition using a mesocosm experiment where we manipulated scorpions’ exposure to a surrogate vertebrate predator and live and dead prey. After six weeks, scorpions exposed to surrogate predators exhibited significantly different venom chemistry compared to naïve scorpions. This change included a relative increase in some compounds toxic to vertebrate cells, and a relative decrease in some compounds effective against their invertebrate prey. Our findings provide, to our knowledge, the first evidence for adaptive plasticity in venom composition. These changes in venom composition may increase the stability of food webs involving venomous animals

Carprofen inhibits the release of matrix metalloproteinases 1, 3, and 13 in the secretome of an explant model of articular cartilage stimulated with interleukin 1β

Introduction: Arthritic diseases are characterized by the degradation of collagenous and noncollagenous extracellular matrix (ECM) components in articular cartilage. The increased expression and activity of matrix metalloproteinases (MMPs) is partly responsible for cartilage degradation. This study used proteomics to identify inflammatory proteins and catabolic enzymes released in a serum-free explant model of articular cartilage stimulated with the pro-inflammatory cytokine interleukin 1β (IL-1β). Western blotting was used to quantify the release of selected proteins in the presence or absence of the cyclooxygenase-2 specific nonsteroidal pro-inflammatory drug carprofen. Methods: Cartilage explant cultures were established by using metacarpophalangeal joints from horses euthanized for purposes other than research. Samples were treated as follows: no treatment (control), IL-1β (10 ng/ml), carprofen (100 μg/ml), and carprofen (100 μg/ml) + IL-1β (10 ng/ml). Explants were incubated (37°C, 5% CO2) over twelve day time courses. High-throughput nano liquid chromatography/mass spectrometry/mass spectrometry uncovered candidate proteins for quantitative western blot analysis. Proteoglycan loss was assessed by using the dimethylmethylene blue (DMMB) assay, which measures the release of sulfated glycosaminoglycans (GAGs). Results: Mass spectrometry identified MMP-1, -3, -13, and the ECM constituents thrombospondin-1 (TSP-1) and fibronectin-1 (FN1). IL-1β stimulation increased the release of all three MMPs. IL-1β also stimulated the fragmentation of FN1 and increased chondrocyte cell death (as assessed by β-actin release). Addition of carprofen significantly decreased MMP release and the appearance of a 60 kDa fragment of FN1 without causing any detectable cytotoxicity to chondrocytes. DMMB assays suggested that carprofen initially inhibited IL-1β-induced GAG release, but this effect was transient. Overall, during the two time courses, GAG release was 58.67% ± 10.91% (SD) for IL-1β versus 52.91% ± 9.35% (SD) with carprofen + IL-1β. Conclusions: Carprofen exhibits beneficial anti-inflammatory and anti-catabolic effects in vitro without causing any detectable cytotoxicity. Combining proteomics with this explant model provides a sensitive screening system for anti-inflammatory compounds

The effect of hearing loss on the Intelligibility of Synthetic Speech

Many factors affect the intelligibility of synthetic\ud speech. One aspect that has been severely neglected\ud in past work is hearing loss. In this study, we investigate\ud whether pure-tone audiometry thresholds\ud across a wide range of frequencies (0.25–20kHz)\ud are correlated with participants’ performance on a\ud simple task that involves accurately recalling and\ud processing reminders. Participants’ scores correlate\ud not only with thresholds in the frequency ranges\ud commonly associated with speech, but also with extended\ud high-frequency thresholds

Application of machine learning to proteomics data: classification and biomarker identification in postgenomics biology

Mass spectrometry is an analytical technique for the characterization of biological samples and is increasingly used in omics studies because of its targeted, nontargeted, and high throughput abilities. However, due to the large datasets generated, it requires informatics approaches such as machine learning techniques to analyze and interpret relevant data. Machine learning can be applied to MS-derived proteomics data in two ways. First, directly to mass spectral peaks and second, to proteins identified by sequence database searching, although relative protein quantification is required for the latter. Machine learning has been applied to mass spectrometry data from different biological disciplines, particularly for various cancers. The aims of such investigations have been to identify biomarkers and to aid in diagnosis, prognosis, and treatment of specific diseases. This review describes how machine learning has been applied to proteomics tandem mass spectrometry data. This includes how it can be used to identify proteins suitable for use as biomarkers of disease and for classification of samples into disease or treatment groups, which may be applicable for diagnostics. It also includes the challenges faced by such investigations, such as prediction of proteins present, protein quantification, planning for the use of machine learning, and small sample sizes