The Geometry of Locomotive Behavioral States in C. elegans

We develop a new hidden Markov model-based method to analyze C elegans locomotive behavior and use this method to quantitatively characterize behavioral states. In agreement with previous work, we find states corresponding to roaming, dwelling, and quiescence. However, we also find evidence for a continuum of intermediate states. We suggest that roaming, dwelling, and quiescence may best be thought of as extremes which, mixed in any proportion, define the locomotive repertoire of C elegans foraging and feeding behavior.     

Forest Age and Plant Species Composition Determine the Soil Fungal Community Composition in a Chinese Subtropical Forest

Fungal diversity and community composition are mainly related to soil and vegetation factors. However, the relative contribution of the different drivers remains largely unexplored, especially in subtropical forest ecosystems. We studied the fungal diversity and community composition of soils sampled from 12 comparative study plots representing three forest age classes (Young: 10–40 yrs; Medium: 40–80 yrs; Old: ≥80 yrs) in Gutianshan National Nature Reserve in South-eastern China. Soil fungal communities were assessed employing ITS rDNA pyrotag sequencing. Members of Basidiomycota and Ascomycota dominated the fungal community, with 22 putative ectomycorrhizal fungal families, where Russulaceae and Thelephoraceae were the most abundant taxa. Analysis of similarity showed that the fungal community composition significantly differed among the three forest age classes. Forest age class, elevation of the study plots, and soil organic carbon (SOC) were the most important factors shaping the fungal community composition. We found a significant correlation between plant and fungal communities at different taxonomic and functional group levels, including a strong relationship between ectomycorrhizal fungal and non-ectomycorrhizal plant communities. Our results suggest that in subtropical forests, plant species community composition is the main driver of the soil fungal diversity and community composition.     

Towards Estimation of HIV-1 Date of Infection: A Time-Continuous IgG-Model Shows That Seroconversion Does Not Occur at the Midpoint between Negative and Positive Tests

Estimating date of infection for HIV-1-infected patients is vital for disease tracking and informed public health decisions, but is difficult to obtain because most patients have an established infection of unknown duration at diagnosis. Previous studies have used HIV-1-specific immunoglobulin G (IgG) levels as measured by the IgG capture BED enzyme immunoassay (BED assay) to indicate if a patient was infected recently, but a time-continuous model has not been available. Therefore, we developed a logistic model of IgG production over time. We used previously published metadata from 792 patients for whom the HIV-1-specific IgG levels had been longitudinally measured using the BED assay. To account for patient variability, we used mixed effects modeling to estimate general population parameters. The typical patient IgG production rate was estimated at r = 6.72[approximate 95% CI 6.17,7.33]×10⁻³ OD-n units day⁻¹, and the carrying capacity at K = 1.84[1.75,1.95] OD-n units, predicting how recently patients seroconverted in the interval ^∧ t = (31,711) days. Final model selection and validation was performed on new BED data from a population of 819 Swedish HIV-1 patients diagnosed in 2002–2010. On an appropriate subset of 350 patients, the best model parameterization had an accuracy of 94% finding a realistic seroconversion date. We found that seroconversion on average is at the midpoint between last negative and first positive HIV-1 test for patients diagnosed in prospective/cohort studies such as those included in the training dataset. In contrast, seroconversion is strongly skewed towards the first positive sample for patients identified by regular public health diagnostic testing as illustrated in the validation dataset. Our model opens the door to more accurate estimates of date of infection for HIV-1 patients, which may facilitate a better understanding of HIV-1 epidemiology on a population level and individualized prevention, such as guidance during contact tracing.     

How the Polls Can Be Both Spot On and Dead Wrong: Using Choice Blindness to Shift Political Attitudes and Voter Intentions

Political candidates often believe they must focus their campaign efforts on a small number of swing voters open for ideological change. Based on the wisdom of opinion polls, this might seem like a good idea. But do most voters really hold their political attitudes so firmly that they are unreceptive to persuasion? We tested this premise during the most recent general election in Sweden, in which a left- and a right-wing coalition were locked in a close race. We asked our participants to state their voter intention, and presented them with a political survey of wedge issues between the two coalitions. Using a sleight-of-hand we then altered their replies to place them in the opposite political camp, and invited them to reason about their attitudes on the manipulated issues. Finally, we summarized their survey score, and asked for their voter intention again. The results showed that no more than 22% of the manipulated replies were detected, and that a full 92% of the participants accepted and endorsed our altered political survey score. Furthermore, the final voter intention question indicated that as many as 48% (±9.2%) were willing to consider a left-right coalition shift. This can be contrasted with the established polls tracking the Swedish election, which registered maximally 10% voters open for a swing. Our results indicate that political attitudes and partisan divisions can be far more flexible than what is assumed by the polls, and that people can reason about the factual issues of the campaign with considerable openness to change.     

Are Treatments More Effective than Placebos? A Systematic Review and Meta-Analysis

BackgroundPlacebos are widely used in clinical practice in spite of ethical restrictions. Whether such use is justified depends in part on the relative benefit of placebos compared to ‘active’ treatments. A direct test for differences between placebo and ‘active’ treatment effects has not been conducted.ObjectivesWe aimed to test for differences between treatment and placebo effects within similar trial populations.ResultsIn trials with continuous outcomes (n = 115) we found no difference between treatment and placebo effects (MD = −0.29, 95% CI −0.62 to 0.05, P = 0.10). In trials with binary outcomes (n = 37) treatments were significantly more effective than placebos (RRR = 0.72, 95%CI = 0.61 to 0.86, P = 0.0003). Treatment and placebo effects were not different in 22 out of 28 predefined subgroup analyses. Of the six subgroups with differences treatments were more effective than placebos in five. However when all criteria for reducing bias were ruled out (continuous outcomes) placebos were more effective than treatments (MD = 1.59, 95% CI = 0.40 to 2.77, P = 0.009).

Conclusions and Implications

Placebos and treatments often have similar effect sizes. Placebos with comparatively powerful effects can benefit patients either alone or as part of a therapeutic regime, and trials involving such placebos must be adequately blinded.     

Animal Models In Mycology: What Have We Learned Over The Past 30 Years

Animal models have long been used to explore various pathophysiological, immunological and microbiological questions in the field of medical mycology. These models have been adapted and altered over time, yet their use has persisted. They remain valuable as research tools due to similarities to processes in human physiology and disease, and are evolving to include more fungal pathogens and infections that better mimic disease in humans. Animal availability, animal cost, housing requirements, the need for immunosuppression, the potential for tissue, fluid or blood samples, a researcher’s familiarity with the model, as well as governmental or institutional regulations, must all be considered when selecting an appropriate one to use. Although the questions of interest have changed over the past 30 years, one idea persists: animal models are valuable tools in research that span the gap between the bench and the clinic.     

MMP-9 and CXCL8/IL-8 Are Potential Therapeutic Targets in Epidermolysis Bullosa Simplex

Epidermolysis bullosa refers to a group of genodermatoses that affects the integrity of epithelial layers, phenotypically resulting in severe skin blistering. Dowling-Meara, the major subtype of epidermolysis bullosa simplex, is inherited in an autosomal dominant manner and can be caused by mutations in either the keratin-5 (K5) or the keratin-14 (K14) gene. Currently, no therapeutic approach is known, and the main objective of this study was to identify novel therapeutic targets. We used microarray analysis, semi-quantitative real-time PCR, western blot and ELISA to identify differentially regulated genes in two K14 mutant cell lines carrying the mutations K14 R125P and K14 R125H, respectively. We found kallikrein-related peptidases and matrix metalloproteinases to be upregulated. We also found elevated expression of chemokines, and we observed deregulation of the Cdc42 pathway as well as aberrant expression of cytokeratins and junction proteins. We further demonstrated, that expression of these genes is dependent on interleukin-1 β signaling. To evaluate these data in vivo we analysed the blister fluids of epidermolysis bullosa simplex patients vs. healthy controls and identified matrix metalloproteinase-9 and the chemokine CXCL8/IL-8 as potential therapeutic targets.     

Rapid Expectation Adaptation during Syntactic Comprehension

When we read or listen to language, we are faced with the challenge of inferring intended messages from noisy input. This challenge is exacerbated by considerable variability between and within speakers. Focusing on syntactic processing (parsing), we test the hypothesis that language comprehenders rapidly adapt to the syntactic statistics of novel linguistic environments (e.g., speakers or genres). Two self-paced reading experiments investigate changes in readers’ syntactic expectations based on repeated exposure to sentences with temporary syntactic ambiguities (so-called “garden path sentences”). These sentences typically lead to a clear expectation violation signature when the temporary ambiguity is resolved to an a priori less expected structure (e.g., based on the statistics of the lexical context). We find that comprehenders rapidly adapt their syntactic expectations to converge towards the local statistics of novel environments. Specifically, repeated exposure to a priori unexpected structures can reduce, and even completely undo, their processing disadvantage (Experiment 1). The opposite is also observed: a priori expected structures become less expected (even eliciting garden paths) in environments where they are hardly ever observed (Experiment 2). Our findings suggest that, when changes in syntactic statistics are to be expected (e.g., when entering a novel environment), comprehenders can rapidly adapt their expectations, thereby overcoming the processing disadvantage that mistaken expectations would otherwise cause. Our findings take a step towards unifying insights from research in expectation-based models of language processing, syntactic priming, and statistical learning.