Automated analysis of immunosequencing datasets reveals novel immunoglobulin D genes across diverse species.

Immunoglobulin genes are formed through V(D)J recombination, which joins the variable (V), diversity (D), and joining (J) germline genes. Since variations in germline genes have been linked to various diseases, personalized immunogenomics focuses on finding alleles of germline genes across various patients. Although reconstruction of V and J genes is a well-studied problem, the more challenging task of reconstructing D genes remained open until the IgScout algorithm was developed in 2019. In this work, we address limitations of IgScout by developing a probabilistic MINING-D algorithm for D gene reconstruction, apply it to hundreds of immunosequencing datasets from multiple species, and validate the newly inferred D genes by analyzing diverse whole genome sequencing datasets and haplotyping heterozygous V genes.

Direct and indirect relationships among posttraumatic stress disorder, depression, hostility, anger, and verbal and physical aggression in returning veterans.

Hostility, anger, and aggression are conceptually related but unique constructs found to occur more often among veterans with posttraumatic stress disorder (PTSD) than among civilians or veterans without PTSD. However, the pathways between PTSD, depression, hostility, anger, and aggression have not been comprehensively characterized. Therefore, drawing on a sample of returning Operation Enduring Freedom/Operation Iraqi Freedom combat veterans ( N = 175; 95% male; mean age 30 years), this study sought to examine the direct and indirect relationships among PTSD, depression, hostility, anger, and four types of aggression: verbal, and physical toward self, others, and objects. Functional modeling of direct effects was done using multiple least-squares regression and bootstrapped mediation analyses were carried out to test indirect effects. Results indicate that PTSD is not the overall direct contributor to different forms of aggression, supporting the mediating role of depression and trait anger. Depression symptoms explain part of the relationships between PTSD and verbal aggression, physical aggression toward objects, and physical aggression toward self and trait anger explains part of the relationships between PTSD and verbal aggression, physical aggression toward objects, and physical aggression toward others. Our findings support the importance of assessing for anger, depression, and different types of aggression among veterans presenting for PTSD treatment to develop individualized treatment plans that may benefit from early incorporation of interventions.

Predicting and containing epidemic risk using on-line friendship networks.

To what extent can online social networks predict who is at risk of an infection? Many infections are transmitted through physical encounter between humans, but collecting detailed information about it can be expensive, might invade privacy, or might not even be possible. In this paper, we ask whether online social networks help predict and contain epidemic risk. Using a dataset from a popular online review service which includes over 100 thousand users and spans 4 years of activity, we build a time-varying network that is a proxy of physical encounter between its users (the encounter network) and a static network based on their reported online friendship (the friendship With computer simulations, we compare stochastic infection processes on the two networks, considering infections on the encounter network as the benchmark. First, we show that the friendship network is useful to identify the individuals at risk of infection, despite providing lower accuracy than the ideal case in which the encounters are known. This limited prediction accuracy is not only due to the static nature of the friendship network because a static version of the encounter network provides more accurate prediction of risk than the friendship network. Then, we show that periodical monitoring of the infection spreading on the encounter network allows to correct the infection predicted by a process spreading on the friendly staff ndship network, and achieves high prediction accuracy. Finally, we show that the friendship network contains valuable information to effectively contain epidemic outbreaks even when a limited budget is available for immunization. In particular, a strategy that immunizes random friends of random individuals achieves the same performance as knowing individuals' encounters at a small additional cost, even if the infection spreads on the encounter network.

Detecting emotional contagion in massive social networks.

Happiness and other emotions spread between people in direct contact, but it is unclear whether massive online social networks also contribute to this spread. Here, we elaborate a novel method for measuring the contagion of emotional expression. With data from millions of Facebook users, we show that rainfall directly influences the emotional content of their status messages, and it also affects the status messages of friends in other cities who are not experiencing rainfall. For every one person affected directly, rainfall alters the emotional expression of about one to two other people, suggesting that online social networks may magnify the intensity of global emotional synchrony.

Human matching behavior in social networks: an algorithmic perspective.

We argue that algorithmic modeling is a powerful approach to understanding the collective dynamics of human behavior. We consider the task of pairing up individuals connected over a network, according to the following model: each individual is able to propose to match with and accept a proposal from a neighbor in the network; if a matched individual proposes to another neighbor or accepts another proposal, the current match will be broken; individuals can only observe whether their neighbors are currently matched but have no knowledge of the network topology or the status of other individuals; and all individuals have the common goal of maximizing the total number of matches. By examining the experimental data, we identify a behavioral principle called prudence, develop an algorithmic model, analyze its properties mathematically and by simulations, and validate the model with human subject experiments for various network sizes and topologies. Our results include i) a 1/2-approximate maximum matching is obtained in logarithmic time in the network size for bounded degree networks; ii) for any constant ε > 0, a (1 - ε)-approximate maximum matching is obtained in polynomial time, while obtaining a maximum matching can require an exponential time; and iii) convergence to a maximum matching is slower on preferential attachment networks than on small-world networks. These results allow us to predict that while humans can find a "good quality" matching quickly, they may be unable to find a maximum matching in feasible time. We show that the human subjects largely abide by prudence, and their collective behavior is closely tracked by the above predictions.

Ray propagation in nonuniform random lattices. Part II.

In this paper and its companion [J. Opt. Soc. Am. A.23, 2251 (2006)], the problem of ray propagation in nonuniform random half-plane lattices is considered. Cells can be independently occupied according to a density profile that depends on the lattice depth. An electromagnetic source external to the lattice radiates a monochromatic plane wave that undergoes specular reflections on the occupied sites. The probability of penetrating up to level k inside the lattice is analytically evaluated using two different approaches, the former applying the theory of Markov chains (Markov approach) and the latter using the theory of Martingale random processes (Martingale approach). The full theory concerned with the Martingale approach is presented here, along with an innovative modification that leads to some improved results. Numerical validation shows that it outperforms the Markov approach when dealing with ray propagation in dense lattices described by a slowly varying density profile.

Ray propagation in nonuniform random lattices.

The problem of optical ray propagation in a nonuniform random half-plane lattice is considered. An external source radiates a planar monochromatic wave impinging at an angle theta on a half-plane random grid where each cell can be independently occupied with probability q(j)=1-p(j),j being the row index. The wave undergoes specular reflections on the occupied cells, and the probability of penetrating up to level k inside the lattice is analytically estimated. Numerical experiments validate the proposed approach and show improvement upon previous results that appeared in the literature. Applications are in the field of remote sensing and communications, where estimation of the penetration of electromagnetic waves in disordered media is of interest.