Christopher T. Franck

Accurate human microsatellite genotypes from high-throughput resequencing data using informed error profiles

Repetitive sequences are biologically and clinically important because they can influence traits and disease, but repeats are challenging to analyse using short-read sequencing technology. We present a tool for genotyping microsatellite repeats called RepeatSeq, which uses Bayesian model selection guided by an empirically derived error model that incorporates sequence and read properties. Next, we apply RepeatSeq to high-coverage genomes from the 1000 Genomes Project to evaluate performance and accuracy. The software uses common formats, such as VCF, for compatibility with existing genome analysis pipelines. Source code and binaries are available at http://github.com/adaptivegenome/repeatseq.

Using crowdsourcing to compare temporal, social temporal, and probability discounting among obese and non-obese individuals

Previous research comparing obese and non-obese samples on the delayed discounting procedure has produced mixed results. The aim of the current study was to clarify these discrepant findings by comparing a variety of temporal discounting measures in a large sample of internet users (n=1163) obtained from a crowdsourcing service, Amazon Mechanical Turk (AMT). Measures of temporal, social-temporal (a combination of standard and social temporal), and probability discounting were obtained. Significant differences were obtained on all discounting measures except probability discounting, but the obtained effect sizes were small. These data suggest that larger-N studies will be more likely to detect differences between obese and non-obese samples, and may afford the opportunity, in future studies, to decompose a large obese sample into different subgroups to examine the effect of other relevant measures, such as the reinforcing value of food, on discounting.

A modified exponential behavioral economic demand model to better describe consumption data.

Behavioral economic demand analyses that quantify the relationship between the consumption of a commodity and its price have proven useful in studying the reinforcing efficacy of many commodities, including drugs of abuse. An exponential equation proposed by Hursh and Silberberg (2008) has proven useful in quantifying the dissociable components of demand intensity and demand elasticity, but is limited as an analysis technique by the inability to correctly analyze consumption values of zero. We examined an exponentiated version of this equation that retains all the beneficial features of the original Hursh and Silberberg equation, but can accommodate consumption values of zero and improves its fit to the data. In Experiment 1, we compared the modified equation with the unmodified equation under different treatments of zero values in cigarette consumption data collected online from 272 participants. We found that the unmodified equation produces different results depending on how zeros are treated, while the exponentiated version incorporates zeros into the analysis, accounts for more variance, and is better able to estimate actual unconstrained consumption as reported by participants. In Experiment 2, we simulated 1,000 datasets with demand parameters known a priori and compared the equation fits. Results indicated that the exponentiated equation was better able to replicate the true values from which the test data were simulated. We conclude that an exponentiated version of the Hursh and Silberberg equation provides better fits to the data, is able to fit all consumption values including zero, and more accurately produces true parameter values.

Using crowdsourcing to examine relations between delay and probability discounting

Although the extensive lines of research on delay and/or probability discounting have greatly expanded our understanding of human decision-making processes, the relation between these two phenomena remains unclear. For example, some studies have reported robust associations between delay and probability discounting, whereas others have failed to demonstrate a consistent relation between the two. The current study sought to clarify this relation by examining the relation between delay and probability discounting in a large sample of internet users (n=904) using the Amazon Mechanical Turk (AMT) crowdsourcing service. Because AMT is a novel data collection platform, the findings were validated through the replication of a number of previously established relations (e.g., relations between delay discounting and cigarette smoking status). A small but highly significant positive correlation between delay and probability discounting rates was obtained, and principal component analysis suggested that two (rather than one) components were preferable to account for the variance in both delay and probability discounting. Taken together, these findings suggest that delay and probability discounting may be related, but are not manifestations of a single construct (e.g., impulsivity).

Altruism in time: social temporal discounting differentiates smokers from problem drinkers

RationaleRecent studies on reinforcer valuation in social situations have informed research on mental illness. Social temporal discounting may be a way to examine effects of social context on the devaluation of delayed reinforcers. In prior research with non-drug-using groups, we demonstrated that individuals discount delayed rewards less rapidly (i.e., value the future more) for a group of which they are a member than they do for themselves alone.ObjectivesThe current study examined how cigarette smoking and level of alcohol use relate to rates of delay and social temporal discounting.MethodsIn this study, we used crowd-sourcing technology to contact a large number of individuals (N = 796). Some of these individuals were hazardous-to-harmful drinkers (n = 269), whereas others were non-problem drinkers (n = 523); some were smokers (n = 182), whereas others were nonsmokers (n = 614). Delay discounting questionnaires for individual rewards (me now, me later) and for group rewards (we now, we later; me now, we later) were used to measure individuals’ discounting rates across various social contexts.ResultsOur analyses found that smokers discounted delayed rewards more rapidly than controls under all conditions. However, hazardous-to-harmful drinkers discounted delayed rewards significantly more rapidly than the non-problem drinkers under the individual condition, but not under the social conditions.ConclusionsThis finding suggests that the use of different abused drugs may be associated with excessive discounting in the individual condition and has selective effects when discounting for a group in the social conditions.

Occupant kinematics in low-speed frontal sled tests: Human volunteers, Hybrid III ATD, and PMHS.

A total of 34 dynamic matched frontal sled tests were performed, 17 low (2.5g, Δv=4.8kph) and 17 medium (5.0g, Δv=9.7kph), with five male human volunteers of approximately 50th percentile height and weight, a Hybrid III 50th percentile male ATD, and three male PMHS. Each volunteer was exposed to two impulses at each severity, one relaxed and one braced prior to the impulse. A total of four tests were performed at each severity with the ATD and one trial was performed at each severity with each PMHS. A Vicon motion analysis system, 12 MX-T20 2 megapixel cameras, was used to quantify subject 3D kinematics (±1mm) (1kHz). Excursions of select anatomical regions were normalized to their respective initial positions and compared by test condition and between subject types. The forward excursions of the select anatomical regions generally increased with increasing severity. The forward excursions of relaxed human volunteers were significantly larger than those of the ATD for nearly every region at both severities. The forward excursions of the upper body regions of the braced volunteers were generally significantly smaller than those of the ATD at both severities. Forward excursions of the relaxed human volunteers and PMHSs were fairly similar except the head CG response at both severities and the right knee and C7 at the medium severity. The forward excursions of the upper body of the PMHS were generally significantly larger than those of the braced volunteers at both severities. Forward excursions of the PMHSs exceeded those of the ATD for all regions at both severities with significant differences within the upper body regions. Overall human volunteers, ATD, and PMHSs do not have identical biomechanical responses in low-speed frontal sled tests but all contribute valuable data that can be used to refine and validate computational models and ATDs used to assess injury risk in automotive collisions.

Accurate characterization of delay discounting: a multiple model approach using approximate Bayesian model selection and a unified discounting measure.

The study of delay discounting, or valuation of future rewards as a function of delay, has contributed to understanding the behavioral economics of addiction. Accurate characterization of discounting can be furthered by statistical model selection given that many functions have been proposed to measure future valuation of rewards. The present study provides a convenient Bayesian model selection algorithm that selects the most probable discounting model among a set of candidate models chosen by the researcher. The approach assigns the most probable model for each individual subject. Importantly, effective delay 50 (ED50) functions as a suitable unifying measure that is computable for and comparable between a number of popular functions, including both one- and two-parameter models. The combined model selection/ED50 approach is illustrated using empirical discounting data collected from a sample of 111 undergraduate students with models proposed by Laibson (1997); Mazur (1987); Myerson & Green (1995); Rachlin (2006); and Samuelson (1937). Computer simulation suggests that the proposed Bayesian model selection approach outperforms the single model approach when data truly arise from multiple models. When a single model underlies all participant data, the simulation suggests that the proposed approach fares no worse than the single model approach.

Comorbid depression, antisocial personality, and substance dependence: Relationship with delay discounting

BACKGROUND Within the field of addiction, as many as four-fifths of individuals in treatment for substance use disorder have co-existing lifetime psychopathology and as high as two-thirds have current psychopathology. Among substance-dependent individuals, excessive delay discounting is pervasive. Despite evidence of excessive discounting across substance use disorders, few studies have investigated the impact of co-occurring psychopathologies and SUD on delay discounting. METHODS We compared delay discounting in currently abstaining substance users with (a) SUD (n=166), (b) SUD and managed major depressive disorder (MDD; n=44), (c) SUD and antisocial personality disorder (APD; n=35), (d) SUD and managed MDD and APD (n=22) and (e) no SUD or co-occurring psychopathology (n=60). RESULTS All groups with SUD discounted future delayed rewards significantly more than healthy controls (p<0.001 in each case, d=0.686, 0.835, 1.098 and 1.650, respective to groups a-d above). Individuals with both APD and SUD and individuals with MDD, APD, and SUD discounted future rewards significantly more than substance users without comorbid psychopathology (p=0.029, d=0.412 and p<0.001, d=0.964, respectively). CONCLUSIONS Overall, individuals with multiple psychopathologies in addition to substance use have exacerbated deficits in discounting of the future, above and beyond that observed in substance use alone. Increased discounting in combined substance and psychopathology profiles suggest a greater chance of treatment failure and therefore may necessitate individualized treatment using adjunctive interventions to achieve better treatment outcomes.

Impulsivity and polysubstance use: A systematic comparison of delay discounting in mono-, dual-, and trisubstance use.

Understanding the association between polysubstance use and impulsivity is pertinent to treatment planning and efficacy. Delay discounting, a measure of impulsivity, supplies the rate at which a reinforcer loses value as the temporal delay to its receipt increases. Excessive delay discounting has been widely observed among drug-using individuals, though the impact of using more than 1 substance has been only minimally studied. Here, after controlling for demographic variables, we systematically compared delay discounting in community controls, heavy smokers, and alcohol- and cocaine-dependent individuals to assess the impact of non-, mono-, dual-, and trisubstance use. All substance-using groups discounted significantly more than did community controls (p < .05). Additionally, groups that smoked cigarettes in addition to another substance dependency discounted significantly more than did the group that smoked cigarettes only (p < .05). Last, trisubstance users who were alcohol-dependent, cocaine-dependent, and heavy cigarette smokers discounted significantly more than did heavy smokers (p < .01). However, trisubstance users did not discount significantly more than did any dual-substance group. Trisubstance use was associated with greater impulsivity than was monosubstance smoking but exhibited no greater impulsivity than did dual-substance use, suggesting a ceiling effect on discounting when more than 2 substances are in use. The present study suggests that smokers who engage in additional substance use may experience worse treatment outcomes, given that excessive discounting is predictive of poor therapeutic outcomes in several studies.

Understanding environmentally significant behavior among whitewater rafting and trekking guides in the Garhwal Himalaya, India

Garhwal, Uttarakhand, India, is planning for large-scale sustainable mountain tourism. However, current tourism practices have resulted in waste accumulation and vegetation loss. This paper explores the possibility of increasing the role of whitewater rafting and adventure tour guides to reduce tourists’ environmental impacts. Earlier studies on guides acquiescent with this role have found it to be effective in altering client behavior and minimizing environmentally destructive behavior. However, only limited research focuses on guides from developing countries outside an ecotourism context. This exploratory research in Garhwal, India, helps explain adventure guide intentions to perform pro-environmental behavior. The theory of planned behavior was applied to identify factors leading to a sample of 68 whitewater and trekking guides to perform three environmentally significant behaviors – packing out rubbish, burying their human waste and cutting living trees for firewood. Results suggest that the theoretical antecedents of the theory of planned behavior can predict intentions to perform pro-environmental behavior among non-western guides. Possible impediments to consistent performance of pro-environmental behavior among guides were noted, including lack of social pressure to change, abhorrence of contact with excreta, caste issues, effort expended to dig burial holes, etc. Managerial possibilities to encourage change are discussed.