Estimating the effect of moving meat-free products to the meat aisle on sales of meat and meat-free products: A non-randomised controlled intervention study in a large UK supermarket chain

BackgroundReducing meat consumption could bring health and environmental benefits, but there is little research to date on effective interventions to achieve this. A non-randomised controlled intervention study was used to evaluate whether prominent positioning of meat-free products in the meat aisle was associated with a change in weekly mean sales of meat and meat-free products.Methods and findingsWeekly sales data were obtained from 108 stores: 20 intervention stores that moved a selection of 26 meat-free products into a newly created meat-free bay within the meat aisle and 88 matched control stores. The primary outcome analysis used a hierarchical negative binomial model to compare changes in weekly sales (units) of meat products sold in intervention versus control stores during the main intervention period (Phase I: February 2019 to April 2019). Interrupted time series analysis was also used to evaluate the effects of the Phase I intervention. Moreover, 8 of the 20 stores enhanced the intervention from August 2019 onwards (Phase II intervention) by adding a second bay of meat-free products into the meat aisle, which was evaluated following the same analytical methods.During the Phase I intervention, sales of meat products (units/store/week) decreased in intervention (approximately −6%) and control stores (−5%) without significant differences (incidence rate ratio [IRR] 1.01 [95% CI 0.95–1.07]. Sales of meat-free products increased significantly more in the intervention (+31%) compared to the control stores (+6%; IRR 1.43 [95% CI 1.30–1.57]), mostly due to increased sales of meat-free burgers, mince, and sausages. Consistent results were observed in interrupted time series analyses where the effect of the Phase II intervention was significant in intervention versus control stores.ConclusionsProminent positioning of meat-free products into the meat aisle in a supermarket was not effective in reducing sales of meat products, but successfully increased sales of meat-free alternatives in the longer term.A preregistered protocol (https://osf.io/qmz3a/) was completed and fully available before data analysis.

Carmen Piernas and co-workers study positioning and marketing of meat-free products in supermarkets.     

DGEclust: differential expression analysis of clustered count data

We present a statistical methodology, DGEclust, for differential expression analysis of digital expression data. Our method treats differential expression as a form of clustering, thus unifying these two concepts. Furthermore, it simultaneously addresses the problem of how many clusters are supported by the data and uncertainty in parameter estimation. DGEclust successfully identifies differentially expressed genes under a number of different scenarios, maintaining a low error rate and an excellent control of its false discovery rate with reasonable computational requirements. It is formulated to perform particularly well on low-replicated data and be applicable to multi-group data. DGEclust is available at http://dvav.github.io/dgeclust/.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-015-0604-6) contains supplementary material, which is available to authorized users.     

Irrational decision-making in an amoeboid organism: transitivity and context-dependent preferences

Most models of animal foraging and consumer choice assume that individuals make choices based on the absolute value of items and are therefore ‘economically rational’. However, frequent violations of rationality by animals, including humans, suggest that animals use comparative valuation rules. Are comparative valuation strategies a consequence of the way brains process information, or are they an intrinsic feature of biological decision-making? Here, we examine the principles of rationality in an organism with radically different information-processing mechanisms: the brainless, unicellular, slime mould Physarum polycephalum. We offered P. polycephalum amoebas a choice between food options that varied in food quality and light exposure (P. polycephalum is photophobic). The use of an absolute valuation rule will lead to two properties: transitivity and independence of irrelevant alternatives (IIA). Transitivity is satisfied if preferences have a consistent, linear ordering, while IIA states that a decision maker''s preference for an item should not change if the choice set is expanded. A violation of either of these principles suggests the use of comparative rather than absolute valuation rules. Physarum polycephalum satisfied transitivity by having linear preference rankings. However, P. polycephalum''s preference for a focal alternative increased when a third, inferior quality option was added to the choice set, thus violating IIA and suggesting the use of a comparative valuation process. The discovery of comparative valuation rules in a unicellular organism suggests that comparative valuation rules are ubiquitous, if not universal, among biological decision makers.     

Subjective optimality in finite sequential decision-making

Many decisions in life are sequential and constrained by a time window. Although mathematically derived optimal solutions exist, it has been reported that humans often deviate from making optimal choices. Here, we used a secretary problem, a classic example of finite sequential decision-making, and investigated the mechanisms underlying individuals’ suboptimal choices. Across three independent experiments, we found that a dynamic programming model comprising subjective value function explains individuals’ deviations from optimality and predicts the choice behaviors under fewer and more opportunities. We further identified that pupil dilation reflected the levels of decision difficulty and subsequent choices to accept or reject the stimulus at each opportunity. The value sensitivity, a model-based estimate that characterizes each individual’s subjective valuation, correlated with the extent to which individuals’ physiological responses tracked stimuli information. Our results provide model-based and physiological evidence for subjective valuation in finite sequential decision-making, rediscovering human suboptimality in subjectively optimal decision-making processes.     

BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling

Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx.     

A Randomised Controlled Trial of Neuronavigated Repetitive Transcranial Magnetic Stimulation (rTMS) in Anorexia Nervosa

Background

Anorexia nervosa (AN) is associated with morbid fear of fatness, extreme food restriction and altered self-regulation. Neuroimaging data implicate fronto-striatal circuitry, including the dorsolateral prefrontal cortex (DLPFC).

Methods

In this double-blind parallel group study, we investigated the effects of one session of sham-controlled high-frequency repetitive transcranial magnetic stimulation (rTMS) to the left DLPFC (l-DLPFC) in 60 individuals with AN. A food exposure task was administered before and after the procedure to elicit AN-related symptoms.

Outcomes

The primary outcome measure was ‘core AN symptoms’, a variable which combined several subjective AN-related experiences. The effects of rTMS on other measures of psychopathology (e.g. mood), temporal discounting (TD; intertemporal choice behaviour) and on salivary cortisol concentrations were also investigated. Safety, tolerability and acceptability were assessed.

Results

Fourty-nine participants completed the study. Whilst there were no interaction effects of rTMS on core AN symptoms, there was a trend for group differences (p = 0.056): after controlling for pre-rTMS scores, individuals who received real rTMS had reduced symptoms post-rTMS and at 24-hour follow-up, relative to those who received sham stimulation. Other psychopathology was not altered differentially following real/sham rTMS. In relation to TD, there was an interaction trend (p = 0.060): real versus sham rTMS resulted in reduced rates of TD (more reflective choice behaviour). Salivary cortisol concentrations were unchanged by stimulation. rTMS was safe, well–tolerated and was considered an acceptable intervention.

Conclusions

This study provides modest evidence that rTMS to the l-DLPFC transiently reduces core symptoms of AN and encourages prudent decision making. Importantly, individuals with AN considered rTMS to be a viable treatment option. These findings require replication in multiple-session studies to evaluate therapeutic efficacy.

Trial Registration

www.Controlled-Trials.com ISRCTN22851337     

Invertebrate drift,discharge, and sediment relations in a southern Appalachian headwater stream

Drifting invertebrates and suspended sediments were collected at monthly intervals from June 1977 to May 1978. The numbers and biomass of drifting organisms reflected the seasonal cycles of aquatic insects. Some aquatic organisms showed behavioral drift either during a sample day or during some portion of their life cycle. Parapsyche cardis Ross and Diplectrona modesta Banks (Trichoptera: Hydropsychidae) dispersed as first instar larvae; few later instars of these two net-spinning caddisflies drifted. The drift of nymphal Peltoperla maria Needham et Smith (Plecoptera: Peltoperlidae) was apparently related more to detritus transport than to benthic densities or discharge alone. Power law relations between the magnitude of daily invertebrate drift and discharge or sediment variables are demonstrated for some taxa in Hugh White Creek. The general level of stream invertebrate drift appears to be related to detritus transport, and drift during storms is also related to detritus transport. During storms, terrestrial invertebrate drift was related to rainfall intensity, canopy washing, and channel expansion. Drift density of aquatic invertebrates in Hugh White Creek was within the range of previously reported values for other streams, but the estimate of yearly export (aquatic invertebrates = 134 g · y^?1; terrestrial invertebrates = 23 g · y^?1) is lower reflecting the smaller size of Hugh White Creek in comparison with those other streams.     

Comparative Genome-Scale Reconstruction of Gapless Metabolic Networks for Present and Ancestral Species

We introduce a novel computational approach, CoReCo, for comparative metabolic reconstruction and provide genome-scale metabolic network models for 49 important fungal species. Leveraging on the exponential growth in sequenced genome availability, our method reconstructs genome-scale gapless metabolic networks simultaneously for a large number of species by integrating sequence data in a probabilistic framework. High reconstruction accuracy is demonstrated by comparisons to the well-curated Saccharomyces cerevisiae consensus model and large-scale knock-out experiments. Our comparative approach is particularly useful in scenarios where the quality of available sequence data is lacking, and when reconstructing evolutionary distant species. Moreover, the reconstructed networks are fully carbon mapped, allowing their use in 13C flux analysis. We demonstrate the functionality and usability of the reconstructed fungal models with computational steady-state biomass production experiment, as these fungi include some of the most important production organisms in industrial biotechnology. In contrast to many existing reconstruction techniques, only minimal manual effort is required before the reconstructed models are usable in flux balance experiments. CoReCo is available at http://esaskar.github.io/CoReCo/.     

Strain differences in delay discounting using inbred rats

A heightened aversion to delayed rewards is associated with substance abuse and numerous other neuropsychiatric disorders. Many of these disorders are heritable, raising the possibility that delay aversion may also have a significant genetic or heritable component. To examine this possibility, we compared delay discounting in six inbred strains of rats (Brown Norway, Copenhagen, Lewis, Fischer, Noble and Wistar Furth) using the adjusting amount procedure, which provides a measure of the subjective value of delayed rewards. The subjective value of rewards decreased as the delay to receipt increased for all strains. However, a main effect of strain and a strain × delay interaction indicated that some strains were more sensitive to the imposition of delays than others. Fitting a hyperbolic discount equation showed significant strain differences in sensitivity to delay ( k ). These data indicate that there are significant strain differences in delay discounting. All strains strongly preferred the 10% sucrose solution (the reinforcer in the delay discounting task) over water and the amount of sucrose consumed was correlated with sensitivity to delay. Locomotor activity was not correlated with delay discounting behavior. Additional research will be required to disentangle genetic influences from maternal effects and to determine how these factors influence the underlying association between heightened delay discounting and neuropsychiatric disorders.     

Genome sequence of the acid-tolerant Burkholderia sp. strain WSM2232 from Karijini National Park,Australia

Burkholderia sp. strain WSM2232 is an aerobic, motile, Gram-negative, non-spore-forming acid-tolerant rod that was trapped in 2001 from acidic soil collected from Karijini National Park (Australia) using Gastrolobium capitatum as a host. WSM2232 was effective in nitrogen fixation with G. capitatum but subsequently lost symbiotic competence during long-term storage. Here we describe the features of Burkholderia sp. strain WSM2232, together with genome sequence information and its annotation. The 7,208,311 bp standard-draft genome is arranged into 72 scaffolds of 72 contigs containing 6,322 protein-coding genes and 61 RNA-only encoding genes. The loss of symbiotic capability can now be attributed to the loss of nodulation and nitrogen fixation genes from the genome. This rhizobial genome is one of 100 sequenced as part of the DOE Joint Genome Institute 2010 Genomic Encyclopedia for Bacteria and Archaea-Root Nodule Bacteria (GEBA-RNB) project.     

Estimating the subjective value of future rewards: comparison of adjusting-amount and adjusting-delay procedures

The present study examined whether equivalent discounting of delayed rewards is observed with different experimental procedures. If the underlying decision-making process is the same, then similar patterns of results should be observed regardless of procedure, and similar estimates of the subjective value of future rewards (i.e., indifference points) should be obtained. Two experiments compared discounting on three types of procedure: adjusting-delay (AD), adjusting-immediate-amount (AIA), and adjusting-delayed-amount (ADA). For the two procedures for which discounting functions can be established (i.e., AD and AIA), a hyperboloid provided good fits to the data at both the group and individual levels, and individuals' discounting on one procedure tended to be correlated with their discounting on the other. Notably, the AIA procedure produced the more consistent estimates of the degree of discounting, and in particular, discounting on the AIA procedure was unaffected by the order in which choices were presented. Regardless of which of the three procedures was used, however, similar patterns of results were obtained: Participants systematically discounted the value of delayed rewards, and robust magnitude effects were observed. Although each procedure may have its own advantages and disadvantages, use of all three types of procedure in the present study provided converging evidence for common decision-making processes underlying the discounting of delayed rewards.     

Wham: Identifying Structural Variants of Biological Consequence

Existing methods for identifying structural variants (SVs) from short read datasets are inaccurate. This complicates disease-gene identification and efforts to understand the consequences of genetic variation. In response, we have created Wham (Whole-genome Alignment Metrics) to provide a single, integrated framework for both structural variant calling and association testing, thereby bypassing many of the difficulties that currently frustrate attempts to employ SVs in association testing. Here we describe Wham, benchmark it against three other widely used SV identification tools–Lumpy, Delly and SoftSearch–and demonstrate Wham’s ability to identify and associate SVs with phenotypes using data from humans, domestic pigeons, and vaccinia virus. Wham and all associated software are covered under the MIT License and can be freely downloaded from github (https://github.com/zeeev/wham), with documentation on a wiki (http://zeeev.github.io/wham/). For community support please post questions to https://www.biostars.org/.

This is PLOS Computational Biology software paper.

     

Ensuring the quality and specificity of preregistrations

Researchers face many, often seemingly arbitrary, choices in formulating hypotheses, designing protocols, collecting data, analyzing data, and reporting results. Opportunistic use of “researcher degrees of freedom” aimed at obtaining statistical significance increases the likelihood of obtaining and publishing false-positive results and overestimated effect sizes. Preregistration is a mechanism for reducing such degrees of freedom by specifying designs and analysis plans before observing the research outcomes. The effectiveness of preregistration may depend, in part, on whether the process facilitates sufficiently specific articulation of such plans. In this preregistered study, we compared 2 formats of preregistration available on the OSF: Standard Pre-Data Collection Registration and Prereg Challenge Registration (now called “OSF Preregistration,” http://osf.io/prereg/). The Prereg Challenge format was a “structured” workflow with detailed instructions and an independent review to confirm completeness; the “Standard” format was “unstructured” with minimal direct guidance to give researchers flexibility for what to prespecify. Results of comparing random samples of 53 preregistrations from each format indicate that the “structured” format restricted the opportunistic use of researcher degrees of freedom better (Cliff’s Delta = 0.49) than the “unstructured” format, but neither eliminated all researcher degrees of freedom. We also observed very low concordance among coders about the number of hypotheses (14%), indicating that they are often not clearly stated. We conclude that effective preregistration is challenging, and registration formats that provide effective guidance may improve the quality of research.

Researchers face many, often seemingly arbitrary choices in formulating hypotheses, designing protocols, collecting data, analyzing data, and reporting results. A study of two formats of preregistration available on the OSF reveals that the opportunistic use of researcher degrees of freedom aimed at obtaining statistical significance is restricted by using more extensive preregistration guidelines; however, these guidelines should be further improved.     

pyTFM: A tool for traction force and monolayer stress microscopy

Cellular force generation and force transmission are of fundamental importance for numerous biological processes and can be studied with the methods of Traction Force Microscopy (TFM) and Monolayer Stress Microscopy. Traction Force Microscopy and Monolayer Stress Microscopy solve the inverse problem of reconstructing cell-matrix tractions and inter- and intra-cellular stresses from the measured cell force-induced deformations of an adhesive substrate with known elasticity. Although several laboratories have developed software for Traction Force Microscopy and Monolayer Stress Microscopy computations, there is currently no software package available that allows non-expert users to perform a full evaluation of such experiments. Here we present pyTFM, a tool to perform Traction Force Microscopy and Monolayer Stress Microscopy on cell patches and cell layers grown in a 2-dimensional environment. pyTFM was optimized for ease-of-use; it is open-source and well documented (hosted at https://pytfm.readthedocs.io/) including usage examples and explanations of the theoretical background. pyTFM can be used as a standalone Python package or as an add-on to the image annotation tool ClickPoints. In combination with the ClickPoints environment, pyTFM allows the user to set all necessary analysis parameters, select regions of interest, examine the input data and intermediary results, and calculate a wide range of parameters describing forces, stresses, and their distribution. In this work, we also thoroughly analyze the accuracy and performance of the Traction Force Microscopy and Monolayer Stress Microscopy algorithms of pyTFM using synthetic and experimental data from epithelial cell patches.     

Brain Connectivity Predicts Placebo Response across Chronic Pain Clinical Trials

Placebo response in the clinical trial setting is poorly understood and alleged to be driven by statistical confounds, and its biological underpinnings are questioned. Here we identified and validated that clinical placebo response is predictable from resting-state functional magnetic-resonance-imaging (fMRI) brain connectivity. This also led to discovering a brain region predicting active drug response and demonstrating the adverse effect of active drug interfering with placebo analgesia. Chronic knee osteoarthritis (OA) pain patients (n = 56) underwent pretreatment brain scans in two clinical trials. Study 1 (n = 17) was a 2-wk single-blinded placebo pill trial. Study 2 (n = 39) was a 3-mo double-blinded randomized trial comparing placebo pill to duloxetine. Study 3, which was conducted in additional knee OA pain patients (n = 42), was observational. fMRI-derived brain connectivity maps in study 1 were contrasted between placebo responders and nonresponders and compared to healthy controls (n = 20). Study 2 validated the primary biomarker and identified a brain region predicting drug response. In both studies, approximately half of the participants exhibited analgesia with placebo treatment. In study 1, right midfrontal gyrus connectivity best identified placebo responders. In study 2, the same measure identified placebo responders (95% correct) and predicted the magnitude of placebo’s effectiveness. By subtracting away linearly modeled placebo analgesia from duloxetine response, we uncovered in 6/19 participants a tendency of duloxetine enhancing predicted placebo response, while in another 6/19, we uncovered a tendency for duloxetine to diminish it. Moreover, the approach led to discovering that right parahippocampus gyrus connectivity predicts drug analgesia after correcting for modeled placebo-related analgesia. Our evidence is consistent with clinical placebo response having biological underpinnings and shows that the method can also reveal that active treatment in some patients diminishes modeled placebo-related analgesia.Trial Registration ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT02903238","term_id":"NCT02903238"}}NCT02903238ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT01558700","term_id":"NCT01558700"}}NCT01558700     

tcR: an R package for T cell receptor repertoire advanced data analysis

Background

The Immunoglobulins (IG) and the T cell receptors (TR) play the key role in antigen recognition during the adaptive immune response. Recent progress in next-generation sequencing technologies has provided an opportunity for the deep T cell receptor repertoire profiling. However, a specialised software is required for the rational analysis of massive data generated by next-generation sequencing.

Results

Here we introduce tcR, a new R package, representing a platform for the advanced analysis of T cell receptor repertoires, which includes diversity measures, shared T cell receptor sequences identification, gene usage statistics computation and other widely used methods. The tool has proven its utility in recent research studies.

Conclusions

tcR is an R package for the advanced analysis of T cell receptor repertoires after primary TR sequences extraction from raw sequencing reads. The stable version can be directly installed from The Comprehensive R Archive Network (http://cran.r-project.org/mirrors.html). The source code and development version are available at tcR GitHub (http://imminfo.github.io/tcr/) along with the full documentation and typical usage examples.     

Hyperbolic Discounting: Value and Time Processes of Substance Abusers and Non-Clinical Individuals in Intertemporal Choice

The single parameter hyperbolic model has been frequently used to describe value discounting as a function of time and to differentiate substance abusers and non-clinical participants with the model''s parameter k. However, k says little about the mechanisms underlying the observed differences. The present study evaluates several alternative models with the purpose of identifying whether group differences stem from differences in subjective valuation, and/or time perceptions. Using three two-parameter models, plus secondary data analyses of 14 studies with 471 indifference point curves, results demonstrated that adding a valuation, or a time perception function led to better model fits. However, the gain in fit due to the flexibility granted by a second parameter did not always lead to a better understanding of the data patterns and corresponding psychological processes. The k parameter consistently indexed group and context (magnitude) differences; it is thus a mixed measure of person and task level effects. This was similar for a parameter meant to index payoff devaluation. A time perception parameter, on the other hand, fluctuated with contexts in a non-predicted fashion and the interpretation of its values was inconsistent with prior findings that supported enlarged perceived delays for substance abusers compared to controls. Overall, the results provide mixed support for hyperbolic models of intertemporal choice in terms of the psychological meaning afforded by their parameters.     

A Novel Nondevelopmental Role of the SAX-7/L1CAM Cell Adhesion Molecule in Synaptic Regulation in Caenorhabditis elegans

The L1CAM family of cell adhesion molecules is a conserved set of single-pass transmembrane proteins that play diverse roles required for proper nervous system development and function. Mutations in L1CAMs can cause the neurological L1 syndrome and are associated with autism and neuropsychiatric disorders. L1CAM expression in the mature nervous system suggests additional functions besides the well-characterized developmental roles. In this study, we demonstrate that the gene encoding the Caenorhabditis elegans L1CAM, sax-7, genetically interacts with gtl-2, as well as with unc-13 and rab-3, genes that function in neurotransmission. These sax-7 genetic interactions result in synthetic phenotypes that are consistent with abnormal synaptic function. Using an inducible sax-7 expression system and pharmacological reagents that interfere with cholinergic transmission, we uncovered a previously uncharacterized nondevelopmental role for sax-7 that impinges on synaptic function.