Inferring Tie Strength from Online Directed Behavior

Some social connections are stronger than others. People have not only friends, but also best friends. Social scientists have long recognized this characteristic of social connections and researchers frequently use the term tie strength to refer to this concept. We used online interaction data (specifically, Facebook interactions) to successfully identify real-world strong ties. Ground truth was established by asking users themselves to name their closest friends in real life. We found the frequency of online interaction was diagnostic of strong ties, and interaction frequency was much more useful diagnostically than were attributes of the user or the user’s friends. More private communications (messages) were not necessarily more informative than public communications (comments, wall posts, and other interactions).     

Inferring Predator Behavior from Attack Rates on Prey-Replicas That Differ in Conspicuousness

Behavioral ecologists and evolutionary biologists have long studied how predators respond to prey items novel in color and pattern. Because a predatory response is influenced by both the predator’s ability to detect the prey and a post-detection behavioral response, variation among prey types in conspicuousness may confound inference about post-prey-detection predator behavior. That is, a relatively high attack rate on a given prey type may result primarily from enhanced conspicuousness and not predators’ direct preference for that prey. Few studies, however, account for such variation in conspicuousness. In a field experiment, we measured predation rates on clay replicas of two aposematic forms of the poison dart frog Dendrobates pumilio, one novel and one familiar, and two cryptic controls. To ask whether predators prefer or avoid a novel aposematic prey form independently of conspicuousness differences among replicas, we first modeled the visual system of a typical avian predator. Then, we used this model to estimate replica contrast against a leaf litter background to test whether variation in contrast alone could explain variation in predator attack rate. We found that absolute predation rates did not differ among color forms. Predation rates relative to conspicuousness did, however, deviate significantly from expectation, suggesting that predators do make post-detection decisions to avoid or attack a given prey type. The direction of this deviation from expectation, though, depended on assumptions we made about how avian predators discriminate objects from the visual background. Our results show that it is important to account for prey conspicuousness when investigating predator behavior and also that existing models of predator visual systems need to be refined.     

Taxi Cab Syndrome: A Review of the Extensive Genitourinary Pathology Experienced by Taxi Cab Drivers and What We Can Do to Help

This review consolidates knowledge regarding the extensive genitourinary pathology experienced by taxi cab drivers. Taxi cab, livery, truck, and other drivers all objectively and subjectively may have more voiding dysfunction, infertility, urolithiasis, bladder cancer, and urinary infections as compared with nonprofessional drivers; this is called taxi cab syndrome. Together with governmental and medical assistance, simple interventions—such as education, the addition of taxi relief stations, and possibly the use of sanitary urinary collection devices—to curb the progression of genitourinary disease in taxi drivers should be prospectively studied. It is postulated that many of these interventions may also benefit other groups of occupationally related infrequent voiders.Key words: Taxi cab syndrome, Infrequent voiders syndrome, Occupational hazard, Voiding dysfunction, Prostodynia, Infertility, UrolithiasisIn New York City, where taxi cabs flow like erythrocytes in a vast net of arteries, the drivers, New York’s backbone, often do not have sufficient flow themselves. This article demonstrates how the lack of adequate and accessible bathroom facilities in New York likely accounts for most of the genitourinary pathology that taxi drivers have. In fact, drivers represent only one of many occupations that contribute to voiding dysfunction as a result of inadequate bathroom access or other factors that lead to the inability to void regularly throughout the workday. These drivers represent the ultimate case study on how, using simple interventions, those who move us through New York City at an often bewildering speed may be helped.In the aptly worded article by Gany and colleagues,¹ “Every disease…man can get can start in this cab,” the cardiovascular risk factors of New York City taxi cabs are described in great detail. Gany and colleagues followed a cohort of South Asian immigrant taxi drivers, holding focus groups and administering surveys about the drivers’ perceptions of their own cardiovascular health. Musculoskeletal pain, diabetes, hypertension, vision problems, stress, obesity, and constipation were pervasive throughout the group. Additionally, urinary tract issues such as kidney problems, bladder dysfunction, and prostatism were noted. One of the participants attributed his onset of kidney problems to intentional infrequent urination, and said this was mostly “because you don’t have facilities at most places where you can stand and urinate.” Two other drivers with diabetes-induced polyuria also attributed their severe problem with this issue.¹     

Identifying Extrinsic versus Intrinsic Drivers of Variation in Cell Behavior in Human iPSC Lines from Healthy Donors

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Large-Scale Analysis of Auditory Segregation Behavior Crowdsourced via a Smartphone App

The human auditory system is adept at detecting sound sources of interest from a complex mixture of several other simultaneous sounds. The ability to selectively attend to the speech of one speaker whilst ignoring other speakers and background noise is of vital biological significance—the capacity to make sense of complex ‘auditory scenes’ is significantly impaired in aging populations as well as those with hearing loss. We investigated this problem by designing a synthetic signal, termed the ‘stochastic figure-ground’ stimulus that captures essential aspects of complex sounds in the natural environment. Previously, we showed that under controlled laboratory conditions, young listeners sampled from the university subject pool (n = 10) performed very well in detecting targets embedded in the stochastic figure-ground signal. Here, we presented a modified version of this cocktail party paradigm as a ‘game’ featured in a smartphone app (The Great Brain Experiment) and obtained data from a large population with diverse demographical patterns (n = 5148). Despite differences in paradigms and experimental settings, the observed target-detection performance by users of the app was robust and consistent with our previous results from the psychophysical study. Our results highlight the potential use of smartphone apps in capturing robust large-scale auditory behavioral data from normal healthy volunteers, which can also be extended to study auditory deficits in clinical populations with hearing impairments and central auditory disorders.     

Denial of Risk Behavior Does Not Exclude Asymptomatic Anorectal Sexually Transmitted Infection in HIV-Infected Men

Background

The Centers for Disease Control recommend screening for asymptomatic sexually transmitted infection (STI) among HIV-infected men when there is self-report of unprotected anal-receptive exposure. The study goals were: (1) to estimate the validity and usefulness for screening policies of self-reported unprotected anal-receptive exposure as a risk indicator for asymptomatic anorectal infection with Neisseria gonorrhoeae (GC) and/or Chlamydia trachomatis (CT). (2) to estimate the number of infections that would be missed if anal diagnostic assays were not performed among patients who denied unprotected anorectal exposure in the preceding month.

Methods and Findings

Retrospective analysis in HIV primary care and high resolution anoscopy (HRA) clinics. HIV-infected adult men were screened for self-reported exposure during the previous month at all primary care and HRA appointments. Four sub-cohorts were defined based on microbiology methodology (GC culture and CT direct fluorescent antibody vs. GC/CT nucleic acid amplification test) and clinical setting (primary care vs. HRA). Screening question operating characteristics were estimated using contingency table methods and then pooled across subcohorts. Among 803 patients, the prevalence of anorectal GC/CT varied from 3.5–20.1% in the 4 sub-cohorts. The sensitivity of the screening question for self-reported exposure to predict anorectal STI was higher in the primary care than in the HRA clinic, 86–100% vs. 12–35%, respectively. The negative predictive value of the screening question to predict asymptomatic anorectal STI was ≥90% in all sub-cohorts. In sensitivity analyses, the probability of being an unidentified case among those denying exposure increased from 0.4–8.1% in the primary care setting, and from 0.9–18.8% in the HRA setting as the prevalence varied from 1–20%.

Conclusion

As STI prevalence increases, denial of unprotected anal-receptive exposure leads to an increasingly unacceptable proportion of unidentified asymptomatic anorectal STI if used as a criterion not to obtain microbiologic assays.     

Inferring the Nature of Allometry from Geometric Data

The form of an organism is the combination of its size and its shape. For a sample of forms, biologists wish to characterize both mean form and the variation in form. For geometric data, where form is characterized as the spatial locations of homologous points, the first step in analysis superimposes the forms, which requires an assumption about what measure of size is appropriate. Geometric morphometrics adopts centroid size as the natural measure of size, and assumes that variation around the mean form is isometric with size. These assumptions limit the interpretation of the resulting estimates of mean and variance in form. We illustrate these problems using allometric variation in shape. We show that superimposition based on subsets of relatively isometric points can yield superior inferences about the overall pattern of variation. We propose and demonstrate two superimposition techniques based on this idea. In subset superimposition, landmarks are progressively discarded from the data used for superimposition if they result in significant decreases in the variation among the remaining landmarks. In outline superimposition, regularly distributed pseudolandmarks on the continuous outline of a form are used as the basis for superimposition of the landmarks contained within it. Simulations show that these techniques can result in dramatic improvements in the accuracy of estimated variance-covariance matrices among landmarks when our assumptions are roughly satisfied. The pattern of variation inferred by means of our superimposition techniques can be quite different from that recovered from full generalized Procrustes superimposition. The pattern of shape variation in the wings of drosophilid flies appears to meet these assumptions. Adoption of superimposition procedures that incorporate biological assumptions about the nature of size and of the variation in shape can dramatically improve the ability to infer the pattern of variation in geometric morphometric data.     

Inferring patterns of aggression from red howler monkey injuries

Venezuelan red howler monkeys in a semideciduous habitat typically survive injuries and disabilities. Intraspecific physical aggression was the most frequently observed and inferred cause of injury. Thirty-eight percent of 119 howlers of all ages examined during capture had scars or other evidence of “damage.” Overall, the sexes did not differ significantly in total number of injuries or number of individuals classified as “damaged.” The incidence of injury was not independent of age-sex class. The subadult male class had the highest percentage of “damaged” individuals. However, when total injuries per age class were examined for each sex separately, only females showed a pattern that was significantly different than expected based on age (i.e., exposure to injury factors). Subadult females experienced more injuries than expected, whereas adult females had fewer injuries. Troop status (resident troop, natal troop, or extratroop) was not significantly related to the number of injuries in adult and subadult males. Thin finding was not surprising, because adult and subadult males of all status classes are involved in aggression related to breeding competition. Extratroop females had more injuries than expected, and natal females had the fewest injuries. The higher incidence of injuries on subadult females and extratroop females is consistent with aggression-mediated emigration of some females and observed resistance to female immigration by resident females. Overall, 74% of injuries were located on anterior-ventral portions of the body, consistent with the face-to-face fighting observed in howlers. Sociobiological costs of aggression in red howlers are difficult to assess because many howlers, despite frequent and severe injury, subsequently survive and reproduce. We recommend caution in inferring mortality from injuries, especially when social mobility and emigration out of the study area are common.     

Inferring relationships between pairs of individuals from locus heterozygosities

Background  

The traditional exact method for inferring relationships between individuals from genetic data is not easily applicable in all situations that may be encountered in several fields of applied genetics. This study describes an approach that gives affordable results and is easily applicable; it is based on the probabilities that two individuals share 0, 1 or both alleles at a locus identical by state.     

Inferring protein domain interactions from databases of interacting proteins

We describe domain pair exclusion analysis (DPEA), a method for inferring domain interactions from databases of interacting proteins. DPEA features a log odds score, E_ij, reflecting confidence that domains i and j interact. We analyzed 177,233 potential domain interactions underlying 26,032 protein interactions. In total, 3,005 high-confidence domain interactions were inferred, and were evaluated using known domain interactions in the Protein Data Bank. DPEA may prove useful in guiding experiment-based discovery of previously unrecognized domain interactions.     

Inferring spatial variations of microstructural properties from macroscopic mechanical response

Disease alters tissue microstructure, which in turn affects the macroscopic mechanical properties of tissue. In elasticity imaging, the macroscopic response is measured and is used to infer the spatial distribution of the elastic constitutive parameters. When an empirical constitutive model is used, these parameters cannot be linked to the microstructure. However, when the constitutive model is derived from a microstructural representation of the material, it allows for the possibility of inferring the local averages of the spatial distribution of the microstructural parameters. This idea forms the basis of this study. In particular, we first derive a constitutive model by homogenizing the mechanical response of a network of elastic, tortuous fibers. Thereafter, we use this model in an inverse problem to determine the spatial distribution of the microstructural parameters. We solve the inverse problem as a constrained minimization problem and develop efficient methods for solving it. We apply these methods to displacement fields obtained by deforming gelatin–agar co-gels and determine the spatial distribution of agar concentration and fiber tortuosity, thereby demonstrating that it is possible to image local averages of microstructural parameters from macroscopic measurements of deformation.     

Drivers of megaherbivore demographic fluctuations: inference from elephants

Environmentally induced variation in survival and fecundity generates demographic fluctuations that affect population growth rate. However, a general pattern of the comparative influence of variation in fecundity and juvenile survival on elephant population dynamics has not been investigated at a broad scale. We evaluated the relative importance of conception, gestation, first year survival and subsequent survivorship for controlling demographic variation by exploring the relationship between past environmental conditions determined by integrated normalized difference vegetation index (INDVI) and the shape of age distributions at 17 sites across Africa. We showed that, generally, INDVI during gestation best explained anomalies in age structure. However, in areas with low mean annual rainfall, INDVI during the first year of life was critical. The results challenge Eberhardt's paradigm for population analysis that suggests that populations respond to limited resource availability through a sequential decrease in juvenile survival, reproductive rate and adult survival. Contrastingly, elephants appear to respond first through a reduction in reproductive rate. We conclude that this discrepancy is likely due to the evolutionary significance of extremely large body size – an adaptation that increases survival rate but decreases reproductive potential. Other megaherbivores may respond similarly to resource limitation due to similarities in population dynamics. Knowing how vital rates vary with changing environmental conditions will permit better forecasts of the trajectories of megaherbivore populations.     

Inferring the dynamics of a spatial epidemic from time-series data

Spatial interactions are key determinants in the dynamics of many epidemiological and ecological systems; therefore it is important to use spatio-temporal models to estimate essential parameters. However, spatially-explicit data sets are rarely available; moreover, fitting spatially-explicit models to such data can be technically demanding and computationally intensive. Thus non-spatial models are often used to estimate parameters from temporal data. We introduce a method for fitting models to temporal data in order to estimate parameters which characterise spatial epidemics. The method uses semi-spatial models and pair approximation to take explicit account of spatial clustering of disease without requiring spatial data. The approach is demonstrated for data from experiments with plant populations invaded by a common soilborne fungus, Rhizoctonia solani. Model inferences concerning the number of sources of disease and primary and secondary infections are tested against independent measures from spatio-temporal data. The applicability of the method to a wide range of host-pathogen systems is discussed.     

Large-Scale isolation of acid phosphatase from human erythrocytes

A laboratory process for the isolation of type B acid phosphatase from human erythrocytes has been scaled up 80 times. The enzyme was purified 1300-fold by adsorption on calcium phosphate gel, ammonium sulfate precipitation, and gel filtration. The yield was 27%. Results for the type A enzyme are also presented.     

Inferring Patterns of Migration from Gene Frequencies under Equilibrium Conditions

A new maximum likelihood method to simultaneously estimate the parameters of any migration pattern from gene frequencies in stochastic equilibrium is developed, based on a model of multivariate genetic drift in a subdivided population. Motivated by simulations of this process in the simplified case of two subpopulations, problems related to the nuisance parameter q, the equilibrium gene frequency, are eliminated by conditioning on the observed mean gene frequency. The covariance matrix of this conditional distribution is calculated by constructing an abstract process that mimics the behavior of the original process in the subspace of interest. The approximation holds as long as there is limited differentiation between subpopulations. The bias and variance of estimates of long-range and short-range migration in a finite stepping stone model are evaluated by fitting the model to simulated data with known values of the parameters. Possible ecological extensions of the model are discussed.     

Inferring Demographic History from a Spectrum of Shared Haplotype Lengths

There has been much recent excitement about the use of genetics to elucidate ancestral history and demography. Whole genome data from humans and other species are revealing complex stories of divergence and admixture that were left undiscovered by previous smaller data sets. A central challenge is to estimate the timing of past admixture and divergence events, for example the time at which Neanderthals exchanged genetic material with humans and the time at which modern humans left Africa. Here, we present a method for using sequence data to jointly estimate the timing and magnitude of past admixture events, along with population divergence times and changes in effective population size. We infer demography from a collection of pairwise sequence alignments by summarizing their length distribution of tracts of identity by state (IBS) and maximizing an analytic composite likelihood derived from a Markovian coalescent approximation. Recent gene flow between populations leaves behind long tracts of identity by descent (IBD), and these tracts give our method power by influencing the distribution of shared IBS tracts. In simulated data, we accurately infer the timing and strength of admixture events, population size changes, and divergence times over a variety of ancient and recent time scales. Using the same technique, we analyze deeply sequenced trio parents from the 1000 Genomes project. The data show evidence of extensive gene flow between Africa and Europe after the time of divergence as well as substructure and gene flow among ancestral hominids. In particular, we infer that recent African-European gene flow and ancient ghost admixture into Europe are both necessary to explain the spectrum of IBS sharing in the trios, rejecting simpler models that contain less population structure.     

Inferring the diameter of a biopolymer from its stretching response

We investigate the stretching response of a thick polymer model by means of extensive stochastic simulations. The computational results are synthesized in an analytic expression that characterizes how the force versus elongation curve depends on the polymer structural parameters: its thickness and granularity (spacing of the monomers). The expression is used to analyze experimental data for the stretching of various different types of biopolymers: polypeptides, polysaccharides, and nucleic acids. Besides recovering elastic parameters (such as the persistence length) that are consistent with those obtained from standard entropic models, the approach allows us to extract viable estimates for the polymers diameter and granularity. This shows that the basic structural polymer features have such a profound impact on the elastic behavior that they can be recovered with the sole input of stretching measurements.     

Inferring Clonal Composition from Multiple Sections of a Breast Cancer

Cancers arise from successive rounds of mutation and selection, generating clonal populations that vary in size, mutational content and drug responsiveness. Ascertaining the clonal composition of a tumor is therefore important both for prognosis and therapy. Mutation counts and frequencies resulting from next-generation sequencing (NGS) potentially reflect a tumor''s clonal composition; however, deconvolving NGS data to infer a tumor''s clonal structure presents a major challenge. We propose a generative model for NGS data derived from multiple subsections of a single tumor, and we describe an expectation-maximization procedure for estimating the clonal genotypes and relative frequencies using this model. We demonstrate, via simulation, the validity of the approach, and then use our algorithm to assess the clonal composition of a primary breast cancer and associated metastatic lymph node. After dividing the tumor into subsections, we perform exome sequencing for each subsection to assess mutational content, followed by deep sequencing to precisely count normal and variant alleles within each subsection. By quantifying the frequencies of 17 somatic variants, we demonstrate that our algorithm predicts clonal relationships that are both phylogenetically and spatially plausible. Applying this method to larger numbers of tumors should cast light on the clonal evolution of cancers in space and time.