Quantifying Collective Attention from Tweet Stream

Online social media are increasingly facilitating our social interactions, thereby making available a massive “digital fossil” of human behavior. Discovering and quantifying distinct patterns using these data is important for studying social behavior, although the rapid time-variant nature and large volumes of these data make this task difficult and challenging. In this study, we focused on the emergence of “collective attention” on Twitter, a popular social networking service. We propose a simple method for detecting and measuring the collective attention evoked by various types of events. This method exploits the fact that tweeting activity exhibits a burst-like increase and an irregular oscillation when a particular real-world event occurs; otherwise, it follows regular circadian rhythms. The difference between regular and irregular states in the tweet stream was measured using the Jensen-Shannon divergence, which corresponds to the intensity of collective attention. We then associated irregular incidents with their corresponding events that attracted the attention and elicited responses from large numbers of people, based on the popularity and the enhancement of key terms in posted messages or “tweets.” Next, we demonstrate the effectiveness of this method using a large dataset that contained approximately 490 million Japanese tweets by over 400,000 users, in which we identified 60 cases of collective attentions, including one related to the Tohoku-oki earthquake. “Retweet” networks were also investigated to understand collective attention in terms of social interactions. This simple method provides a retrospective summary of collective attention, thereby contributing to the fundamental understanding of social behavior in the digital era.     

Reading the Mind in the Eyes or Reading between the Lines? Theory of Mind Predicts Collective Intelligence Equally Well Online and Face-To-Face

Recent research with face-to-face groups found that a measure of general group effectiveness (called “collective intelligence”) predicted a group’s performance on a wide range of different tasks. The same research also found that collective intelligence was correlated with the individual group members’ ability to reason about the mental states of others (an ability called “Theory of Mind” or “ToM”). Since ToM was measured in this work by a test that requires participants to “read” the mental states of others from looking at their eyes (the “Reading the Mind in the Eyes” test), it is uncertain whether the same results would emerge in online groups where these visual cues are not available. Here we find that: (1) a collective intelligence factor characterizes group performance approximately as well for online groups as for face-to-face groups; and (2) surprisingly, the ToM measure is equally predictive of collective intelligence in both face-to-face and online groups, even though the online groups communicate only via text and never see each other at all. This provides strong evidence that ToM abilities are just as important to group performance in online environments with limited nonverbal cues as they are face-to-face. It also suggests that the Reading the Mind in the Eyes test measures a deeper, domain-independent aspect of social reasoning, not merely the ability to recognize facial expressions of mental states.     

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.     

Collective Intelligence Meets Medical Decision-Making: The Collective Outperforms the Best Radiologist

While collective intelligence (CI) is a powerful approach to increase decision accuracy, few attempts have been made to unlock its potential in medical decision-making. Here we investigated the performance of three well-known collective intelligence rules (“majority”, “quorum”, and “weighted quorum”) when applied to mammography screening. For any particular mammogram, these rules aggregate the independent assessments of multiple radiologists into a single decision (recall the patient for additional workup or not). We found that, compared to single radiologists, any of these CI-rules both increases true positives (i.e., recalls of patients with cancer) and decreases false positives (i.e., recalls of patients without cancer), thereby overcoming one of the fundamental limitations to decision accuracy that individual radiologists face. Importantly, we find that all CI-rules systematically outperform even the best-performing individual radiologist in the respective group. Our findings demonstrate that CI can be employed to improve mammography screening; similarly, CI may have the potential to improve medical decision-making in a much wider range of contexts, including many areas of diagnostic imaging and, more generally, diagnostic decisions that are based on the subjective interpretation of evidence.     

Roles of leader and follower cells in collective cell migration

Collective cell migration is a widely observed phenomenon during animal development, tissue repair, and cancer metastasis. Considering its broad involvement in biological processes, it is essential to understand the basics behind the collective movement. Based on the topology of migrating populations, tissue-scale kinetics, called the “leader–follower” model, has been proposed for persistent directional collective movement. Extensive in vivo and in vitro studies reveal the characteristics of leader cells, as well as the special mechanisms leader cells employ for maintaining their positions in collective migration. However, follower cells have attracted increasing attention recently due to their important contributions to collective movement. In this Perspective, the current understanding of the molecular mechanisms behind the “leader–follower” model is reviewed with a special focus on the force transmission and diverse roles of leaders and followers during collective cell movement.     

Task-Level Strategies for Human Sagittal-Plane Running Maneuvers Are Consistent with Robotic Control Policies

The strategies that humans use to control unsteady locomotion are not well understood. A “spring-mass” template comprised of a point mass bouncing on a sprung leg can approximate both center of mass movements and ground reaction forces during running in humans and other animals. Legged robots that operate as bouncing, “spring-mass” systems can maintain stable motion using relatively simple, distributed feedback rules. We tested whether the changes to sagittal-plane movements during five running tasks involving active changes to running height, speed, and orientation were consistent with the rules used by bouncing robots to maintain stability. Changes to running height were associated with changes to leg force but not stance duration. To change speed, humans primarily used a “pogo stick” strategy, where speed changes were associated with adjustments to fore-aft foot placement, and not a “unicycle” strategy involving systematic changes to stance leg hip moment. However, hip moments were related to changes to body orientation and angular speed. Hip moments could be described with first order proportional-derivative relationship to trunk pitch. Overall, the task-level strategies used for body control in humans were consistent with the strategies employed by bouncing robots. Identification of these behavioral strategies could lead to a better understanding of the sensorimotor mechanisms that allow for effective unsteady locomotion.     

Collective predator evasion: Putting the criticality hypothesis to the test

According to the criticality hypothesis, collective biological systems should operate in a special parameter region, close to so-called critical points, where the collective behavior undergoes a qualitative change between different dynamical regimes. Critical systems exhibit unique properties, which may benefit collective information processing such as maximal responsiveness to external stimuli. Besides neuronal and gene-regulatory networks, recent empirical data suggests that also animal collectives may be examples of self-organized critical systems. However, open questions about self-organization mechanisms in animal groups remain: Evolutionary adaptation towards a group-level optimum (group-level selection), implicitly assumed in the “criticality hypothesis”, appears in general not reasonable for fission-fusion groups composed of non-related individuals. Furthermore, previous theoretical work relies on non-spatial models, which ignore potentially important self-organization and spatial sorting effects. Using a generic, spatially-explicit model of schooling prey being attacked by a predator, we show first that schools operating at criticality perform best. However, this is not due to optimal response of the prey to the predator, as suggested by the “criticality hypothesis”, but rather due to the spatial structure of the prey school at criticality. Secondly, by investigating individual-level evolution, we show that strong spatial self-sorting effects at the critical point lead to strong selection gradients, and make it an evolutionary unstable state. Our results demonstrate the decisive role of spatio-temporal phenomena in collective behavior, and that individual-level selection is in general not a viable mechanism for self-tuning of unrelated animal groups towards criticality.     

Detection of Functional Modes in Protein Dynamics

Proteins frequently accomplish their biological function by collective atomic motions. Yet the identification of collective motions related to a specific protein function from, e.g., a molecular dynamics trajectory is often non-trivial. Here, we propose a novel technique termed “functional mode analysis” that aims to detect the collective motion that is directly related to a particular protein function. Based on an ensemble of structures, together with an arbitrary “functional quantity” that quantifies the functional state of the protein, the technique detects the collective motion that is maximally correlated to the functional quantity. The functional quantity could, e.g., correspond to a geometric, electrostatic, or chemical observable, or any other variable that is relevant to the function of the protein. In addition, the motion that displays the largest likelihood to induce a substantial change in the functional quantity is estimated from the given protein ensemble. Two different correlation measures are applied: first, the Pearson correlation coefficient that measures linear correlation only; and second, the mutual information that can assess any kind of interdependence. Detecting the maximally correlated motion allows one to derive a model for the functional state in terms of a single collective coordinate. The new approach is illustrated using a number of biomolecules, including a polyalanine-helix, T4 lysozyme, Trp-cage, and leucine-binding protein.     

Human Collective Intelligence under Dual Exploration-Exploitation Dilemmas

The exploration-exploitation dilemma is a recurrent adaptive problem for humans as well as non-human animals. Given a fixed time/energy budget, every individual faces a fundamental trade-off between exploring for better resources and exploiting known resources to optimize overall performance under uncertainty. Colonies of eusocial insects are known to solve this dilemma successfully via evolved coordination mechanisms that function at the collective level. For humans and other non-eusocial species, however, this dilemma operates within individuals as well as between individuals, because group members may be motivated to take excessive advantage of others'' exploratory findings through social learning. Thus, even though social learning can reduce collective exploration costs, the emergence of disproportionate “information scroungers” may severely undermine its potential benefits. We investigated experimentally whether social learning opportunities might improve the performance of human participants working on a “multi-armed bandit” problem in groups, where they could learn about each other''s past choice behaviors. Results showed that, even though information scroungers emerged frequently in groups, social learning opportunities reduced total group exploration time while increasing harvesting from better options, and consequentially improved collective performance. Surprisingly, enriching social information by allowing participants to observe others'' evaluations of chosen options (e.g., Amazon''s 5-star rating system) in addition to choice-frequency information had a detrimental impact on performance compared to the simpler situation with only the choice-frequency information. These results indicate that humans groups can handle the fundamental “dual exploration-exploitation dilemmas” successfully, and that social learning about simple choice-frequencies can help produce collective intelligence.     

Certifying achievement in the control of Chagas disease native vectors: what is a viable scenario?

As an evaluation scheme, we propose certifying for “control”, as alternative to “interruption”, of Chagas disease transmission by native vectors, to project a more achievable and measurable goal and sharing good practices through an “open online platform” rather than “formal certification” to make the key knowledge more accumulable and accessible.     

Pathological States and Criminal Responsibility

The doctor is embarrassed in court when asked to testify to the effects of illness on a defendant''s capability “of appreciating the nature and quality of an act or omission or of knowing that an act or omission is wrong”. The source of his difficulty is traced to the legal concepts of “guilt”, “crime” and “punishment” which imply a legal view of man at variance with our modern biological view. To abolish this discrepancy we need not accept a medical model for criminal law where “crime” is analogous to “disease”, and “punishment” to “treatment”. A pragmatic approach to the handling of the criminal could exclude the notions of “guilt” and “punishment” and yet fulfil the rational goals of protecting society from the criminal and of compensating his victims.     

“Liking” as an early and editable draft of long-run affective value

Psychological and neural distinctions between the technical concepts of “liking” and “wanting” pose important problems for motivated choice for goods. Why could we “want” something that we do not “like,” or “like” something but be unwilling to exert effort to acquire it? Here, we suggest a framework for answering these questions through the medium of reinforcement learning. We consider “liking” to provide immediate, but preliminary and ultimately cancellable, information about the true, long-run worth of a good. Such initial estimates, viewed through the lens of what is known as potential-based shaping, help solve the temporally complex learning problems faced by animals.

What is the distinction between ’liking’ and ’wanting’? Why could we ’want’ something that we do not ’like,’ or ’like’ something but be unwilling to exert effort to acquire it? This Essay argues that the primary hedonic phenomenon called ’liking’ might solve the temporal credit assignment problem for learning that arises when true reinforcement values are available slowly or late.     

Allosteric Communication Occurs via Networks of Tertiary and Quaternary Motions in Proteins

Allosteric proteins bind an effector molecule at one site resulting in a functional change at a second site. We hypothesize that allosteric communication in proteins relies upon networks of quaternary (collective, rigid-body) and tertiary (residue–residue contact) motions. We argue that cyclic topology of these networks is necessary for allosteric communication. An automated algorithm identifies rigid bodies from the displacement between the inactive and the active structures and constructs “quaternary networks” from these rigid bodies and the substrate and effector ligands. We then integrate quaternary networks with a coarse-grained representation of contact rearrangements to form “global communication networks” (GCNs). The GCN reveals allosteric communication among all substrate and effector sites in 15 of 18 multidomain and multimeric proteins, while tertiary and quaternary networks exhibit such communication in only 4 and 3 of these proteins, respectively. Furthermore, in 7 of the 15 proteins connected by the GCN, 50% or more of the substrate-effector paths via the GCN are “interdependent” paths that do not exist via either the tertiary or the quaternary network. Substrate-effector “pathways” typically are not linear but rather consist of polycyclic networks of rigid bodies and clusters of rearranging residue contacts. These results argue for broad applicability of allosteric communication based on structural changes and demonstrate the utility of the GCN. Global communication networks may inform a variety of experiments on allosteric proteins as well as the design of allostery into non-allosteric proteins.     

Categorizing Ideas about Trees: A Tree of Trees

The aim of this study is to explore whether matrices and MP trees used to produce systematic categories of organisms could be useful to produce categories of ideas in history of science. We study the history of the use of trees in systematics to represent the diversity of life from 1766 to 1991. We apply to those ideas a method inspired from coding homologous parts of organisms. We discretize conceptual parts of ideas, writings and drawings about trees contained in 41 main writings; we detect shared parts among authors and code them into a 91-characters matrix and use a tree representation to show who shares what with whom. In other words, we propose a hierarchical representation of the shared ideas about trees among authors: this produces a “tree of trees.” Then, we categorize schools of tree-representations. Classical schools like “cladists” and “pheneticists” are recovered but others are not: “gradists” are separated into two blocks, one of them being called here “grade theoreticians.” We propose new interesting categories like the “buffonian school,” the “metaphoricians,” and those using “strictly genealogical classifications.” We consider that networks are not useful to represent shared ideas at the present step of the study. A cladogram is made for showing who is sharing what with whom, but also heterobathmy and homoplasy of characters. The present cladogram is not modelling processes of transmission of ideas about trees, and here it is mostly used to test for proximity of ideas of the same age and for categorization.     

Re-Examination of Globally Flat Space-Time

In the following, we offer a novel approach to modeling the observed effects currently attributed to the theoretical concepts of “dark energy,” “dark matter,” and “dark flow.” Instead of assuming the existence of these theoretical concepts, we take an alternative route and choose to redefine what we consider to be inertial motion as well as what constitutes an inertial frame of reference in flat space-time. We adopt none of the features of our current cosmological models except for the requirement that special and general relativity be local approximations within our revised definition of inertial systems. Implicit in our ideas is the assumption that at “large enough” scales one can treat objects within these inertial systems as point-particles having an insignificant effect on the curvature of space-time. We then proceed under the assumption that time and space are fundamentally intertwined such that time- and spatial-translational invariance are not inherent symmetries of flat space-time (i.e., observable clock rates depend upon both relative velocity and spatial position within these inertial systems) and take the geodesics of this theory in the radial Rindler chart as the proper characterization of inertial motion. With this commitment, we are able to model solely with inertial motion the observed effects expected to be the result of “dark energy,” “dark matter,” and “dark flow.” In addition, we examine the potential observable implications of our theory in a gravitational system located within a confined region of an inertial reference frame, subsequently interpreting the Pioneer anomaly as support for our redefinition of inertial motion. As well, we extend our analysis into quantum mechanics by quantizing for a real scalar field and find a possible explanation for the asymmetry between matter and antimatter within the framework of these redefined inertial systems.     

Beyond arbitrium: identification of a second communication system in Bacillus phage phi3T that may regulate host defense mechanisms

The evolutionary stability of temperate bacteriophages at low abundance of susceptible bacterial hosts lies in the trade-off between the maximization of phage replication, performed by the host-destructive lytic cycle, and the protection of the phage-host collective, enacted by lysogeny. Upon Bacillus infection, Bacillus phages phi3T rely on the “arbitrium” quorum sensing (QS) system to communicate on their population density in order to orchestrate the lysis-to-lysogeny transition. At high phage densities, where there may be limited host cells to infect, lysogeny is induced to preserve chances of phage survival. Here, we report the presence of an additional, host-derived QS system in the phi3T genome, making it the first known virus with two communication systems. Specifically, this additional system, coined “Rapφ-Phrφ”, is predicted to downregulate host defense mechanisms during the viral infection, but only upon stress or high abundance of Bacillus cells and at low density of population of the phi3T phages. Post-lysogenization, Rapφ-Phrφ is also predicted to provide the lysogenized bacteria with an immediate fitness advantage: delaying the costly production of public goods while nonetheless benefiting from the public goods produced by other non-lysogenized Bacillus bacteria. The discovered “Rapφ-Phrφ” QS system hence provides novel mechanistic insights into how phage communication systems could contribute to the phage-host evolutionary stability.Subject terms: Bacteriophages, Viral genetics     

Metformin and Resveratrol Inhibited High Glucose-Induced Metabolic Memory of Endothelial Senescence through SIRT1/p300/p53/p21 Pathway

Endothelial senescence plays crucial roles in diabetic vascular complication. Recent evidence indicated that transient hyperglycaemia could potentiate persistent diabetic vascular complications, a phenomenon known as “metabolic memory.” Although SIRT1 has been demonstrated to mediate high glucose-induced endothelial senescence, whether and how “metabolic memory” would affect endothelial senescence through SIRT1 signaling remains largely unknown. In this study, we investigated the involvement of SIRT1 axis as well as the protective effects of resveratrol (RSV) and metformin (MET), two potent SIRT1 activators, during the occurrence of “metabolic memory” of cellular senescence (senescent “memory”). Human umbilical vascular endothelial cells (HUVECs) were cultured in either normal glucose (NG)/high glucose (HG) media for 6 days, or 3 days of HG followed by 3 days of NG (HN), with or without RSV or MET treatment. It was shown that HN incubation triggered persistent downregulation of deacetylase SIRT1 and upregulation of acetyltransferase p300, leading to sustained hyperacetylation (at K382) and activation of p53, and subsequent p53/p21-mediated senescent “memory.” In contrast, senescent “memory” was abrogated by overexpression of SIRT1 or knockdown of p300. Interestingly, we found that SIRT1 and p300 could regulate each other in response to HN stimulation, suggesting that a delicate balance between acetyltransferases and deacetylases may be particularly important for sustained acetylation and activation of non-histone proteins (such as p53), and eventually the occurrence of “metabolic memory.” Furthermore, we found that RSV or MET treatment prevented senescent “memory” by modulating SIRT1/p300/p53/p21 pathway. Notably, early and continuous treatment of MET, but not RSV, was particularly important for preventing senescent “memory.” In conclusion, short-term high glucose stimulation could induce sustained endothelial senescence via SIRT1/p300/p53/p21 pathway. RVS or MET treatment could enhance SIRT1-mediated signaling and thus protect against senescent “memory” independent of their glucose lowering mechanisms. Therefore, they may serve as promising therapeutic drugs against the development of “metabolic memory.”     

Oxidative stress in cancer associated fibroblasts drives tumor-stroma co-evolution: A new paradigm for understanding tumor metabolism,the field effect and genomic instability in cancer cells

Loss of stromal fibroblast caveolin-1 (Cav-1) is a powerful single independent predictor of poor prognosis in human breast cancer patients, and is associated with early tumor recurrence, lymph node metastasis and tamoxifen-resistance. We developed a novel co-culture system to understand the mechanism(s) by which a loss of stromal fibroblast Cav-1 induces a “lethal tumor microenvironment.” Here, we propose a new paradigm to explain the powerful prognostic value of stromal Cav-1. In this model, cancer cells induce oxidative stress in cancer-associated fibroblasts, which then acts as a “metabolic” and “mutagenic” motor to drive tumor-stroma co-evolution, DNA damage and aneuploidy in cancer cells. More specifically, we show that an acute loss of Cav-1 expression leads to mitochondrial dysfunction, oxidative stress and aerobic glycolysis in cancer associated fibroblasts. Also, we propose that defective mitochondria are removed from cancer-associated fibroblasts by autophagy/mitophagy that is induced by oxidative stress. As a consequence, cancer associated fibroblasts provide nutrients (such as lactate) to stimulate mitochondrial biogenesis and oxidative metabolism in adjacent cancer cells (the “Reverse Warburg effect”). We provide evidence that oxidative stress in cancer-associated fibroblasts is sufficient to induce genomic instability in adjacent cancer cells, via a bystander effect, potentially increasing their aggressive behavior. Finally, we directly demonstrate that nitric oxide (NO) over-production, secondary to Cav-1 loss, is the root cause for mitochondrial dysfunction in cancer associated fibroblasts. In support of this notion, treatment with anti-oxidants (such as N-acetyl-cysteine, metformin and quercetin) or NO inhibitors (L-NAME) was sufficient to reverse many of the cancer-associated fibroblast phenotypes that we describe. Thus, cancer cells use “oxidative stress” in adjacent fibroblasts (1) as an “engine” to fuel their own survival via the stromal production of nutrients and (ii) to drive their own mutagenic evolution towards a more aggressive phenotype, by promoting genomic instability. We also present evidence that the “field effect” in cancer biology could also be related to the stromal production of ROS and NO species. eNOS-expressing fibroblasts have the ability to downregulate Cav-1 and induce mitochondrial dysfunction in adjacent fibroblasts that do not express eNOS. As such, the effects of stromal oxidative stress can be laterally propagated, amplified and are effectively “contagious”—spread from cell-to-cell like a virus—creating an “oncogenic/mutagenic” field promoting widespread DNA damage.Key words: caveolin-1, cancer associated fibroblasts, oxidative stress, reactive oxygen species (ROS), mitochondrial dysfunction, autophagy, nitric oxide (NO), DNA damage, aneuploidy, genomic instability, anti-oxidant cancer therapy, the “field effect” in cancer biology     

Blood Pressure: A Consideration of Terminology

Concepts of hypertension have changed and changes in terminology to reflect this state of affairs are suggested. Statistically, the best mortality experience is associated with blood pressure commonly regarded as subnormal, and increments of blood pressure above this level are associated with progressive increases in mortality. The terms “normal”, “benign” and “essential” in relation to blood pressure should be abandoned. “Optimal”, “acceptable” and “hypertensive” ranges of blood pressure are suggested. Hypertension is regarded as a symptom of disease, rather than as a disease in itself, and “hypertension”, when used as a diagnostic label, should be qualified always by the primary disease, if known, or by the modifying phrase, “of unknown cause”, if not known.     

European population substructure: clustering of northern and southern populations

Using a genome-wide single nucleotide polymorphism (SNP) panel, we observed population structure in a diverse group of Europeans and European Americans. Under a variety of conditions and tests, there is a consistent and reproducible distinction between “northern” and “southern” European population groups: most individual participants with southern European ancestry (Italian, Spanish, Portuguese, and Greek) have >85% membership in the “southern” population; and most northern, western, eastern, and central Europeans have >90% in the “northern” population group. Ashkenazi Jewish as well as Sephardic Jewish origin also showed >85% membership in the “southern” population, consistent with a later Mediterranean origin of these ethnic groups. Based on this work, we have developed a core set of informative SNP markers that can control for this partition in European population structure in a variety of clinical and genetic studies.