High Quality Topic Extraction from Business News Explains Abnormal Financial Market Volatility

Understanding the mutual relationships between information flows and social activity in society today is one of the cornerstones of the social sciences. In financial economics, the key issue in this regard is understanding and quantifying how news of all possible types (geopolitical, environmental, social, financial, economic, etc.) affects trading and the pricing of firms in organized stock markets. In this article, we seek to address this issue by performing an analysis of more than 24 million news records provided by Thompson Reuters and of their relationship with trading activity for 206 major stocks in the S&P US stock index. We show that the whole landscape of news that affects stock price movements can be automatically summarized via simple regularized regressions between trading activity and news information pieces decomposed, with the help of simple topic modeling techniques, into their “thematic” features. Using these methods, we are able to estimate and quantify the impacts of news on trading. We introduce network-based visualization techniques to represent the whole landscape of news information associated with a basket of stocks. The examination of the words that are representative of the topic distributions confirms that our method is able to extract the significant pieces of information influencing the stock market. Our results show that one of the most puzzling stylized facts in financial economies, namely that at certain times trading volumes appear to be “abnormally large,” can be partially explained by the flow of news. In this sense, our results prove that there is no “excess trading,” when restricting to times when news is genuinely novel and provides relevant financial information.     

A Highlights from MBoC Selection: Kinetochore–microtubule attachment throughout mitosis potentiated by the elongated stalk of the kinetochore kinesin CENP-E

Centromere protein E (CENP-E) is a highly elongated kinesin that transports pole-proximal chromosomes during congression in prometaphase. During metaphase, it facilitates kinetochore–microtubule end-on attachment required to achieve and maintain chromosome alignment. In vitro CENP-E can walk processively along microtubule tracks and follow both growing and shrinking microtubule plus ends. Neither the CENP-E–dependent transport along microtubules nor its tip-tracking activity requires the unusually long coiled-coil stalk of CENP-E. The biological role for the CENP-E stalk has now been identified through creation of “Bonsai” CENP-E with significantly shortened stalk but wild-type motor and tail domains. We demonstrate that Bonsai CENP-E fails to bind microtubules in vitro unless a cargo is contemporaneously bound via its C-terminal tail. In contrast, both full-length and truncated CENP-E that has no stalk and tail exhibit robust motility with and without cargo binding, highlighting the importance of CENP-E stalk for its activity. Correspondingly, kinetochore attachment to microtubule ends is shown to be disrupted in cells whose CENP-E has a shortened stalk, thereby producing chromosome misalignment in metaphase and lagging chromosomes during anaphase. Together these findings establish an unexpected role of CENP-E elongated stalk in ensuring stability of kinetochore–microtubule attachments during chromosome congression and segregation.     

The Structure and Evolution of Buyer-Supplier Networks

In this paper, we investigate the structure and evolution of customer-supplier networks in Japan using a unique dataset that contains information on customer and supplier linkages for more than 500,000 incorporated non-financial firms for the five years from 2008 to 2012. We find, first, that the number of customer links is unequal across firms; the customer link distribution has a power-law tail with an exponent of unity (i.e., it follows Zipf''s law). We interpret this as implying that competition among firms to acquire new customers yields winners with a large number of customers, as well as losers with fewer customers. We also show that the shortest path length for any pair of firms is, on average, 4.3 links. Second, we find that link switching is relatively rare. Our estimates indicate that the survival rate per year for customer links is 92 percent and for supplier links 93 percent. Third and finally, we find that firm growth rates tend to be more highly correlated the closer two firms are to each other in a customer-supplier network (i.e., the smaller is the shortest path length for the two firms). This suggests that a non-negligible portion of fluctuations in firm growth stems from the propagation of microeconomic shocks – shocks affecting only a particular firm – through customer-supplier chains.     

Cathepsin D interacts with adenosine A2A receptors in mouse macrophages to modulate cell surface localization and inflammatory signaling

Adenosine A_2A receptor (A_2AR)–dependent signaling in macrophages plays a key role in the regulation of inflammation. However, the processes regulating A_2AR targeting to the cell surface and degradation in macrophages are incompletely understood. For example, the C-terminal domain of the A_2AR and proteins interacting with it are known to regulate receptor recycling, although it is unclear what role potential A_2AR-interacting partners have in macrophages. Here, we aimed to identify A_2AR-interacting partners in macrophages that may effect receptor trafficking and activity. To this end, we performed a yeast two-hybrid screen using the C-terminal tail of A_2AR as the “bait” and a macrophage expression library as the “prey.” We found that the lysosomal protease cathepsin D (CtsD) was a robust hit. The A_2AR–CtsD interaction was validated in vitro and in cellular models, including RAW 264.7 and mouse peritoneal macrophage (IPMΦ) cells. We also demonstrated that the A_2AR is a substrate of CtsD and that the blockade of CtsD activity increases the density and cell surface targeting of A_2AR in macrophages. Conversely, we demonstrate that A_2AR activation prompts the maturation and enzymatic activity of CtsD in macrophages. In summary, we conclude that CtsD is a novel A_2AR-interacting partner and thus describe molecular and functional interplay that may be crucial for adenosine-mediated macrophage regulation in inflammatory processes.     

How Much Is the Whole Really More than the Sum of Its Parts? 1 ? 1?=?2.5: Superlinear Productivity in Collective Group Actions

In a variety of open source software projects, we document a superlinear growth of production intensity () as a function of the number of active developers , with a median value of the exponent , with large dispersions of from slightly less than up to . For a typical project in this class, doubling of the group size multiplies typically the output by a factor , explaining the title. This superlinear law is found to hold for group sizes ranging from 5 to a few hundred developers. We propose two classes of mechanisms, interaction-based and large deviation, along with a cascade model of productive activity, which unifies them. In this common framework, superlinear productivity requires that the involved social groups function at or close to criticality, or in a “superradiance” mode, in the sense of the appearance of a cooperative process and order involving a collective mode of developers defined by the build up of correlation between the contributions of developers. In addition, we report the first empirical test of the renormalization of the exponent of the distribution of the sizes of first generation events into the renormalized exponent of the distribution of clusters resulting from the cascade of triggering over all generation in a critical branching process in the non-meanfield regime. Finally, we document a size effect in the strength and variability of the superlinear effect, with smaller groups exhibiting widely distributed superlinear exponents, some of them characterizing highly productive teams. In contrast, large groups tend to have a smaller superlinearity and less variability.     

Neurodegeneration and Unfolded-Protein Response in Mice Expressing a Membrane-Tethered Flexible Tail of PrP

The cellular prion protein (PrP^C) consists of a flexible N-terminal tail (FT, aa 23–128) hinged to a membrane-anchored globular domain (GD, aa 129–231). Ligation of the GD with antibodies induces rapid neurodegeneration, which is prevented by deletion or functional inactivation of the FT. Therefore, the FT is an allosteric effector of neurotoxicity. To explore its mechanism of action, we generated transgenic mice expressing the FT fused to a GPI anchor, but lacking the GD (PrP_Δ141–225, or “FTgpi”). Here we report that FTgpi mice develop a progressive, inexorably lethal neurodegeneration morphologically and biochemically similar to that triggered by anti-GD antibodies. FTgpi was mostly retained in the endoplasmic reticulum, where it triggered a conspicuous unfolded protein response specifically activating the PERK pathway leading to phosphorylation of eIF2α and upregulation of CHOP ultimately leading to neurodegeration similar to what was observed in prion infection.     

A first-principles model of early evolution: emergence of gene families, species, and preferred protein folds

In this work we develop a microscopic physical model of early evolution where phenotype—organism life expectancy—is directly related to genotype—the stability of its proteins in their native conformations—which can be determined exactly in the model. Simulating the model on a computer, we consistently observe the “Big Bang” scenario whereby exponential population growth ensues as soon as favorable sequence–structure combinations (precursors of stable proteins) are discovered. Upon that, random diversity of the structural space abruptly collapses into a small set of preferred proteins. We observe that protein folds remain stable and abundant in the population at timescales much greater than mutation or organism lifetime, and the distribution of the lifetimes of dominant folds in a population approximately follows a power law. The separation of evolutionary timescales between discovery of new folds and generation of new sequences gives rise to emergence of protein families and superfamilies whose sizes are power-law distributed, closely matching the same distributions for real proteins. On the population level we observe emergence of species—subpopulations that carry similar genomes. Further, we present a simple theory that relates stability of evolving proteins to the sizes of emerging genomes. Together, these results provide a microscopic first-principles picture of how first-gene families developed in the course of early evolution.     

Proteome Folding Kinetics Is Limited by Protein Halflife

How heterogeneous are proteome folding timescales and what physical principles, if any, dictate its limits? We answer this by predicting copy number weighted folding speed distribution – using the native topology – for E.coli and Yeast proteome. E.coli and Yeast proteomes yield very similar distributions with average folding times of 100 milliseconds and 170 milliseconds, respectively. The topology-based folding time distribution is well described by a diffusion-drift mutation model on a flat-fitness landscape in free energy barrier between two boundaries: i) the lowest barrier height determined by the upper limit of folding speed and ii) the highest barrier height governed by the lower speed limit of folding. While the fastest time scale of the distribution is near the experimentally measured speed limit of 1 microsecond (typical of barrier-less folders), we find the slowest folding time to be around seconds (8 seconds for Yeast distribution), approximately an order of magnitude less than the fastest halflife (approximately 2 minutes) in the Yeast proteome. This separation of timescale implies even the fastest degrading protein will have moderately high (96%) probability of folding before degradation. The overall agreement with the flat-fitness landscape model further hints that proteome folding times did not undergo additional major selection pressures – to make proteins fold faster – other than the primary requirement to “sufficiently beat the clock” against its lifetime. Direct comparison between the predicted folding time and experimentally measured halflife further shows 99% of the proteome have a folding time less than their corresponding lifetime. These two findings together suggest that proteome folding kinetics may be bounded by protein halflife.     

Short-Term Regulation of Nitrogenase Activity by NH4+ in Rhodobacter capsulatus: Multiple In Vivo Nitrogenase Responses to NH4+ Addition

The photosynthetic bacterium Rhodobacter capsulatus has been shown to carry out nitrogenase “switch-off,” a rapid, reversible inhibition of in vivo activity. Here, we demonstrate that highly nitrogen-limited cultures of both the wild-type strain and a draT draG mutant are capable of nitrogenase switch-off while moderately nitrogen-limited cultures show instead a “magnitude” response, with a decrease in in vivo nitrogenase activity that is proportional to the amount of added NH₄⁺.     

Driver Gaze Behavior Is Different in Normal Curve Driving and when Looking at the Tangent Point

Several steering models in the visual science literature attempt to capture the visual strategies in curve driving. Some of them are based on steering points on the future path (FP), others on tangent points (TP). It is, however, challenging to differentiate between the models’ predictions in real–world contexts. Analysis of optokinetic nystagmus (OKN) parameters is one useful measure, as the different strategies predict measurably different OKN patterns. Here, we directly test this prediction by asking drivers to either a) “drive as they normally would” or b) to “look at the TP”. The design of the experiment is similar to a previous study by Kandil et al., but uses more sophisticated methods of eye–movement analysis. We find that the eye-movement patterns in the “normal” condition are indeed markedly different from the “tp” condition, and consistent with drivers looking at waypoints on the future path. This is the case for both overall fixation distribution, as well as the more informative fixation–by–fixation analysis of OKN. We find that the horizontal gaze speed during OKN corresponds well to the quantitative prediction of the future path models. The results also definitively rule out the alternative explanation that the OKN is produced by an involuntary reflex even while the driver is “trying” to look at the TP. The results are discussed in terms of the sequential organization of curve driving.     

Sources of Variability in Metabolite Measurements from Urinary Samples

Background

The application of metabolomics in epidemiological studies would potentially allow researchers to identify biomarkers associated with exposures and diseases. However, within-individual variability of metabolite levels caused by temporal variation of metabolites, together with technical variability introduced by laboratory procedures, may reduce the study power to detect such associations. We assessed the sources of variability of metabolites from urine samples and the implications for designing epidemiologic studies.

Methods

We measured 539 metabolites in urine samples from the Navy Colon Adenoma Study using liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectroscopy (GC-MS). The study collected 2–3 samples per person from 17 male subjects (age 38–70) over 2–10 days. We estimated between-individual, within-individual, and technical variability and calculated expected study power with a specific focus on large case-control and nested case-control studies.

Results

Overall technical reliability was high (median intraclass correlation = 0.92), and for 72% of the metabolites, the majority of total variance can be attributed to between-individual variability. Age, gender and body mass index explained only a small proportion of the total metabolite variability. For a relative risk (comparing upper and lower quartiles of “usual” levels) of 1.5, we estimated that a study with 500, 1,000, and 5,000 individuals could detect 1.0%, 4.5% and 75% of the metabolite associations.

Conclusions

The use of metabolomics in urine samples from epidemiological studies would require large sample sizes to detect associations with moderate effect sizes.     

Synchrony in Broadband Fluctuation and the 2008 Financial Crisis

We propose phase-like characteristics in scale-free broadband processes and consider fluctuation synchrony based on the temporal signature of significant amplitude fluctuation. Using wavelet transform, successful captures of similar fluctuation pattern between such broadband processes are demonstrated. The application to the financial data leading to the 2008 financial crisis reveals the transition towards a qualitatively different dynamical regime with many equity price in fluctuation synchrony. Further analysis suggests an underlying scale free “price fluctuation network” with large clustering coefficient.     

Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics

The new digital revolution of big data is deeply changing our capability of understanding society and forecasting the outcome of many social and economic systems. Unfortunately, information can be very heterogeneous in the importance, relevance, and surprise it conveys, affecting severely the predictive power of semantic and statistical methods. Here we show that the aggregation of web users’ behavior can be elicited to overcome this problem in a hard to predict complex system, namely the financial market. Specifically, our in-sample analysis shows that the combined use of sentiment analysis of news and browsing activity of users of Yahoo! Finance greatly helps forecasting intra-day and daily price changes of a set of 100 highly capitalized US stocks traded in the period 2012–2013. Sentiment analysis or browsing activity when taken alone have very small or no predictive power. Conversely, when considering a news signal where in a given time interval we compute the average sentiment of the clicked news, weighted by the number of clicks, we show that for nearly 50% of the companies such signal Granger-causes hourly price returns. Our result indicates a “wisdom-of-the-crowd” effect that allows to exploit users’ activity to identify and weigh properly the relevant and surprising news, enhancing considerably the forecasting power of the news sentiment.     

A Linear City Model with Asymmetric Consumer Distribution

The article analyzes a linear-city model where the consumer distribution can be asymmetric, which is important because in real markets this distribution is often asymmetric. The model yields equilibrium price differences, even though the firms’ costs are equal and their locations are symmetric (at the two endpoints of the city). The equilibrium price difference is proportional to the transportation cost parameter and does not depend on the good''s cost. The firms'' markups are also proportional to the transportation cost. The two firms’ prices will be equal in equilibrium if and only if half of the consumers are located to the left of the city’s midpoint, even if other characteristics of the consumer distribution are highly asymmetric. An extension analyzes what happens when the firms have different costs and how the two sources of asymmetry – the consumer distribution and the cost per unit – interact together. The model can be useful as a tool for further development by other researchers interested in applying this simple yet flexible framework for the analysis of various topics.     

Linkage Rules for Plant–Pollinator Networks: Trait Complementarity or Exploitation Barriers?

Recent attempts to examine the biological processes responsible for the general characteristics of mutualistic networks focus on two types of explanations: nonmatching biological attributes of species that prevent the occurrence of certain interactions (“forbidden links”), arising from trait complementarity in mutualist networks (as compared to barriers to exploitation in antagonistic ones), and random interactions among individuals that are proportional to their abundances in the observed community (“neutrality hypothesis”). We explored the consequences that simple linkage rules based on the first two hypotheses (complementarity of traits versus barriers to exploitation) had on the topology of plant–pollination networks. Independent of the linkage rules used, the inclusion of a small set of traits (two to four) sufficed to account for the complex topological patterns observed in real-world networks. Optimal performance was achieved by a “mixed model” that combined rules that link plants and pollinators whose trait ranges overlap (“complementarity models”) and rules that link pollinators to flowers whose traits are below a pollinator-specific barrier value (“barrier models”). Deterrence of floral parasites (barrier model) is therefore at least as important as increasing pollination efficiency (complementarity model) in the evolutionary shaping of plant–pollinator networks.     

Phenotypic plasticity in life‐history traits of Daphnia galeata in response to temperature – a comparison across clonal lineages separated in time

Climatic changes are projected to result in rapid adaptive events with considerable phenotypic shifts. In order to reconstruct the impact of increased mean water temperatures during past decades and to reveal possible thermal micro‐evolution, we applied a resurrection ecology approach using dormant eggs of the freshwater keystone species Daphnia galeata. To this end, we compared the adaptive response of D. galeata clones from Lake Constance of two different time periods, 1965–1974 (“historical”) versus 2000–2009 (“recent”), to experimentally increased temperature regimes. In order to distinguish between genetic versus environmentally induced effects, we performed a common garden experiment in a flow‐through system and measured variation in life‐history traits. Experimental thermal regimes were chosen according to natural temperature conditions during the reproductive period of D. galeata in Central European lakes, with one additional temperature regime exceeding the currently observable maximum (+2°C). Increased water temperatures were shown to significantly affect measured life‐history traits, and significant “temperature × clonal age” interactions were revealed. Compared to historical clones, recent clonal lineages exhibited a shorter time to first reproduction and a higher survival rate, which may suggest temperature‐driven micro‐evolution over time but does not allow an explicit conclusion on the adaptive nature of such responses.     

PICH and Cotargeted Plk1 Coordinately Maintain Prometaphase Chromosome Arm Architecture

To maintain genomic stability, chromosome architecture needs to be tightly regulated as chromosomes undergo condensation during prophase and separation during anaphase, but the mechanisms remain poorly understood. Here, we show that the Plk1-binding protein PICH and Plk1 kinase coordinately maintain chromosome architecture during prometaphase. PICH knockdown results in a loss of Plk1 from the chromosome arm and an increase in highly disorganized “wavy” chromosomes that exhibit an “open” or “X-shaped” configuration, consistent with a loss of chromosome arm cohesion. Such chromosome disorganization occurs with essentially no change in the localization of condensin or cohesin on chromosomes. Interestingly, the chromosome disorganization could be prevented by treatment with a topoisomerase II inhibitor ICRF-193, suggesting that the PICH–Plk1 complex normally maintains chromosome architecture in a manner that involves topoisomerase II activity. PICH knockdown does not affect initial chromosome compaction at prophase but causes anaphase DNA bridge formation and failed abscission. Our studies suggest that the PICH–Plk1 complex plays a critical role in maintaining prometaphase chromosome architecture.     

Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data

Use of socially generated “big data” to access information about collective states of the minds in human societies has become a new paradigm in the emerging field of computational social science. A natural application of this would be the prediction of the society''s reaction to a new product in the sense of popularity and adoption rate. However, bridging the gap between “real time monitoring” and “early predicting” remains a big challenge. Here we report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. We show that the popularity of a movie can be predicted much before its release by measuring and analyzing the activity level of editors and viewers of the corresponding entry to the movie in Wikipedia, the well-known online encyclopedia.     

Biomechanics of the Peacock’s Display: How Feather Structure and Resonance Influence Multimodal Signaling

Courtship displays may serve as signals of the quality of motor performance, but little is known about the underlying biomechanics that determines both their signal content and costs. Peacocks (Pavo cristatus) perform a complex, multimodal “train-rattling” display in which they court females by vibrating the iridescent feathers in their elaborate train ornament. Here we study how feather biomechanics influences the performance of this display using a combination of field recordings and laboratory experiments. Using high-speed video, we find that train-rattling peacocks stridulate their tail feathers against the train at 25.6 Hz, on average, generating a broadband, pulsating mechanical sound at that frequency. Laboratory measurements demonstrate that arrays of peacock tail and train feathers have a broad resonant peak in their vibrational spectra at the range of frequencies used for train-rattling during the display, and the motion of feathers is just as expected for feathers shaking near resonance. This indicates that peacocks are able to drive feather vibrations energetically efficiently over a relatively broad range of frequencies, enabling them to modulate the feather vibration frequency of their displays. Using our field data, we show that peacocks with longer trains use slightly higher vibration frequencies on average, even though longer train feathers are heavier and have lower resonant frequencies. Based on these results, we propose hypotheses for future studies of the function and energetics of this display that ask why its dynamic elements might attract and maintain female attention. Finally, we demonstrate how the mechanical structure of the train feathers affects the peacock’s visual display by allowing the colorful iridescent eyespots–which strongly influence female mate choice–to remain nearly stationary against a dynamic iridescent background.