The expansion of GPCR transactivation-dependent signalling to include serine/threonine kinase receptors represents a new cell signalling frontier

G protein-coupled receptor (GPCR) signalling is mediated through transactivation-independent signalling pathways or the transactivation of protein tyrosine kinase receptors and the recently reported activation of the serine/threonine kinase receptors, most notably the transforming growth factor-β receptor family. Since the original observation of GPCR transactivation of protein tyrosine kinase receptors, there has been considerable work on the mechanism of transactivation and several pathways are prominent. These pathways include the “triple membrane bypass” pathway and the generation of reactive oxygen species. The recent recognition of GPCR transactivation of serine/threonine kinase receptors enormously broadens the GPCR signalling paradigm. It may be predicted that the transactivation of serine/threonine kinase receptors would have mechanistic similarities with transactivation of tyrosine kinase pathways; however, initial studies suggest that these two transactivation pathways are mechanistically distinct. Important questions are the relative importance of tyrosine and serine/threonine transactivation pathways, the contribution of transactivation to overall GPCR signalling, mechanisms of transactivation and the range of cell types in which this phenomenon occurs. The ultimate significance of transactivation-dependent signalling remains to be defined but it appears to be prominent and if so will represent a new cell signalling frontier.     

Aristotle Said “Happiness is a State of Activity” — Predicting Mood Through Body Sensing with Smartwatches

We measure and predict states of Activation and Happiness using a body sensing application connected to smartwatches. Through the sensors of commercially available smartwatches we collect individual mood states and correlate them with body sensing data such as acceleration, heart rate, light level data, and location, through the GPS sensor built into the smartphone connected to the smartwatch. We polled users on the smartwatch for seven weeks four times per day asking for their mood state. We found that both Happiness and Activation are negatively correlated with heart beats and with the levels of light. People tend to be happier when they are moving more intensely and are feeling less activated during weekends. We also found that people with a lower Conscientiousness and Neuroticism and higher Agreeableness tend to be happy more frequently. In addition, more Activation can be predicted by lower Openness to experience and higher Agreeableness and Conscientiousness. Lastly, we find that tracking people’s geographical coordinates might play an important role in predicting Happiness and Activation. The methodology we propose is a first step towards building an automated mood tracking system, to be used for better teamwork and in combination with social network analysis studies.     

Digging with ‘hands’: observations of food capture in the flying gurnard Dactylopterus volitans (Linnaeus, 1758)

ABSTRACT

Videofilms of a foraging flying gurnard (Dactylopterus volitans) were collected at Itaipu, Niterói, RJ, Brazil. Analysis revealed details of the use of anterior parts of the pectoral fins which act as digging ‘hands’ to access infaunal prey items that are subsequently captured by oral suction feeding. Each pectoral fin has two distinct sections articulated separately on the pectoral girdle. The digging ‘anterior pectoral fin’ mainly consists of segmented and flexible fin rays but has an anterior robust unsegmented ray that provides an edge to the ‘hand’, allowing penetration of the substratum. The huge ‘posterior pectoral fins’ are supported by unsegmented rays. Most digging episodes involved one ‘hand’ and consisted of 1–7 cycles of movement with frequencies 1.15–3.74 cycles s^?1. During a cycle, the ‘hand’ is moved forwards and medially above the substratum, then is twisted medially and simultaneously depressed so that the anterior unsegmented ray impacts and enters the substratum. The hand is then drawn backwards and laterally to disturb the substratum. To prevent upward pitching of the head during digging, the ‘posterior pectoral fins’ are both moved anteriorly and laterally to shift the centre of gravity forwards while the caudal and ?second dorsal fins continue to provide propulsive force.     

Lattice Solid/Boltzmann Microscopic Model to Simulate Solid/Fluid Systems-A Tool to Study Creation of Fluid Flow Networks for Viable Deep Geothermal Energy

SUMMARY:Realizing the potential of geothermal energy as a cheap, green, sustainable resource to provide for the planet’s future energy demands that a key geophysical problem be solved first:how to deve...     

Laccases of prokaryotic origin: enzymes at the interface of protein science and protein technology

The ubiquitous members of the multicopper oxidase family of enzymes oxidize a range of aromatic substrates such as polyphenols, methoxy-substituted phenols, amines and inorganic compounds, concomitantly with the reduction of molecular dioxygen to water. This family of enzymes can be broadly divided into two functional classes: metalloxidases and laccases. Several prokaryotic metalloxidases have been described in the last decade showing a robust activity towards metals, such as Cu(I), Fe(II) or Mn(II) and have been implicated in the metal metabolism of the corresponding microorganisms. Many laccases, with a superior efficiency for oxidation of organic compounds when compared with metals, have also been identified and characterized from prokaryotes, playing roles that more closely conform to those of intermediary metabolism. This review aims to present an update of current knowledge on prokaryotic multicopper oxidases, with a special emphasis on laccases, anticipating their enormous potential for industrial and environmental applications.     

Predicting Stock Return Volatility: Can We Benefit from Regression Models for Return Intervals?

We study the performance of recently developed linear regression models for interval data when it comes to forecasting the uncertainty surrounding future stock returns. These interval data models use easy‐to‐compute daily return intervals during the modeling, estimation and forecasting stage. They have to stand up to comparable point‐data models of the well‐known capital asset pricing model type—which employ single daily returns based on successive closing prices and might allow for GARCH effects—in a comprehensive out‐of‐sample forecasting competition. The latter comprises roughly 1000 daily observations on all 30 stocks that constitute the DAX, Germany's main stock index, for a period covering both the calm market phase before and the more turbulent times during the recent financial crisis. The interval data models clearly outperform simple random walk benchmarks as well as the point‐data competitors in the great majority of cases. This result does not only hold when one‐day‐ahead forecasts of the conditional variance are considered, but is even more evident when the focus is on forecasting the width or the exact location of the next day's return interval. Regression models based on interval arithmetic thus prove to be a promising alternative to established point‐data volatility forecasting tools. Copyright ©2015 John Wiley & Sons, Ltd.     

Inconsistent idealizations and inferentialism about scientific representation

Inferentialists about scientific representation hold that an apparatus's representing a target system consists in the apparatus allowing “surrogative inferences” about the target. I argue that a serious problem for inferentialism arises from the fact that many scientific theories and models contain internal inconsistencies. Inferentialism, left unamended, implies that inconsistent scientific models have unlimited representational power, since an inconsistency permits any conclusion to be inferred. I consider a number of ways that inferentialists can respond to this challenge before suggesting my own solution. I develop an analogy to exploitable glitches in a game. Even though inconsistent representational apparatuses may in some sense allow for contradictions to be generated within them, doing so violates the intended function of the apparatus's parts and hence violates representational “gameplay”.     

Long Memory of Financial Time Series and Hidden Markov Models with Time‐Varying Parameters

Hidden Markov models are often used to model daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time‐varying behavior have not been thoroughly examined. This paper presents an adaptive estimation approach that allows for the parameters of the estimated models to be time varying. It is shown that a two‐state Gaussian hidden Markov model with time‐varying parameters is able to reproduce the long memory of squared daily returns that was previously believed to be the most difficult fact to reproduce with a hidden Markov model. Capturing the time‐varying behavior of the parameters also leads to improved one‐step density forecasts. Finally, it is shown that the forecasting performance of the estimated models can be further improved using local smoothing to forecast the parameter variations. Copyright © 2016 John Wiley & Sons, Ltd.     

Dynamic Dominating Set and Turbo-Charging Greedy Heuristics

The main purpose of this paper is to exposit two very different, but very general, motivational schemes in the art of parameterization and a concrete example connecting them. We introduce a dynamic version of the DOMINATING SET problem and prove that it is fixed-parameter tractable（FPT）. The problem is motivated by settings where problem instances evolve. It also arises in the quest to improve a natural greedy heuristic for the DOMINATING SET problem.