ORN: Inferring patient-specific dysregulation status of pathway modules in cancer with OR-gate Network

Pathway level understanding of cancer plays a key role in precision oncology. However, the current amount of high-throughput data cannot support the elucidation of full pathway topology. In this study, instead of directly learning the pathway network, we adapted the probabilistic OR gate to model the modular structure of pathways and regulon. The resulting model, OR-gate Network (ORN), can simultaneously infer pathway modules of somatic alterations, patient-specific pathway dysregulation status, and downstream regulon. In a trained ORN, the differentially expressed genes (DEGs) in each tumour can be explained by somatic mutations perturbing a pathway module. Furthermore, the ORN handles one of the most important properties of pathway perturbation in tumours, the mutual exclusivity. We have applied the ORN to lower-grade glioma (LGG) samples and liver hepatocellular carcinoma (LIHC) samples in TCGA and breast cancer samples from METABRIC. Both datasets have shown abnormal pathway activities related to immune response and cell cycles. In LGG samples, ORN identified pathway modules closely related to glioma development and revealed two pathways closely related to patient survival. We had similar results with LIHC samples. Additional results from the METABRIC datasets showed that ORN could characterize critical mechanisms of cancer and connect them to less studied somatic mutations (e.g., BAP1, MIR604, MICAL3, and telomere activities), which may generate novel hypothesis for targeted therapy.     

Daily Rhythms in Mobile Telephone Communication

Circadian rhythms are known to be important drivers of human activity and the recent availability of electronic records of human behaviour has provided fine-grained data of temporal patterns of activity on a large scale. Further, questionnaire studies have identified important individual differences in circadian rhythms, with people broadly categorised into morning-like or evening-like individuals. However, little is known about the social aspects of these circadian rhythms, or how they vary across individuals. In this study we use a unique 18-month dataset that combines mobile phone calls and questionnaire data to examine individual differences in the daily rhythms of mobile phone activity. We demonstrate clear individual differences in daily patterns of phone calls, and show that these individual differences are persistent despite a high degree of turnover in the individuals’ social networks. Further, women’s calls were longer than men’s calls, especially during the evening and at night, and these calls were typically focused on a small number of emotionally intense relationships. These results demonstrate that individual differences in circadian rhythms are not just related to broad patterns of morningness and eveningness, but have a strong social component, in directing phone calls to specific individuals at specific times of day.     

A neural network model of basal ganglia’s decision-making circuitry

The basal ganglia have been increasingly recognized as an important structure involved in decision making. Neurons in the basal ganglia were found to reflect the evidence accumulation process during decision making. However, it is not well understood how the direct and indirect pathways of the basal ganglia work together for decision making. Here, we create a recurrent neural network model that is composed of the direct and indirect pathways and test it with the classic random dot motion discrimination task. The direct pathway drives the outputs, which are modulated through a gating mechanism controlled by the indirect pathway. We train the network to learn the task and find that the network reproduces the accuracy and reaction time patterns of previous animal studies. Units in the model exhibit ramping activities that reflect evidence accumulation. Finally, we simulate manipulations of the direct and indirect pathways and find that the manipulations of the direct pathway mainly affect the choice while the manipulations of the indirect pathway affect the model’s reaction time. These results suggest a potential circuitry mechanism of the basal ganglia’s role in decision making with predictions that can be tested experimentally in the future.     

Evolutionary origins of metabolic compartmentalization in eukaryotes

Many genes in eukaryotes are acquisitions from the free-living antecedents of chloroplasts and mitochondria. But there is no evolutionary ‘homing device’ that automatically directs the protein product of a transferred gene back to the organelle of its provenance. Instead, the products of genes acquired from endosymbionts can explore all targeting possibilities within the cell. They often replace pre-existing host genes, or even whole pathways. But the transfer of an enzymatic pathway from one compartment to another poses severe problems: over evolutionary time, the enzymes of the pathway acquire their targeting signals for the new compartment individually, not in unison. Until the whole pathway is established in the new compartment, newly routed individual enzymes are useless, and their genes will be lost through mutation. Here it is suggested that pathways attain novel compartmentation variants via a ‘minor mistargeting’ mechanism. If protein targeting in eukaryotic cells possesses enough imperfection such that small amounts of entire pathways continuously enter novel compartments, selectable units of biochemical function would exist in new compartments, and the genes could become selected. Dual-targeting of proteins is indeed very common within eukaryotic cells, suggesting that targeting variation required for this minor mistargeting mechanism to operate exists in nature.     

Intrinsic and realized generation intervals in infectious-disease transmission

The generation interval is the interval between the time when an individual is infected by an infector and the time when this infector was infected. Its distribution underpins estimates of the reproductive number and hence informs public health strategies. Empirical generation-interval distributions are often derived from contact-tracing data. But linking observed generation intervals to the underlying generation interval required for modelling purposes is surprisingly not straightforward, and misspecifications can lead to incorrect estimates of the reproductive number, with the potential to misguide interventions to stop or slow an epidemic. Here, we clarify the theoretical framework for three conceptually different generation-interval distributions: the ‘intrinsic’ one typically used in mathematical models and the ‘forward’ and ‘backward’ ones typically observed from contact-tracing data, looking, respectively, forward or backward in time. We explain how the relationship between these distributions changes as an epidemic progresses and discuss how empirical generation-interval data can be used to correctly inform mathematical models.     

An Evaluation of the Implementation of Maternal Obesity Pathways of Care: A Mixed Methods Study with Data Integration

ObjectivesMaternal obesity has multiple associated risks and requires substantial intervention. This research evaluated the implementation of maternal obesity care pathways from multiple stakeholder perspectives.ResultsStudy 1: Four themes were identified: women’s overall (positive and negative) views of the pathways; knowledge and understanding of the pathways; views on clinical and weight management advice and support; and views on the information leaflet. Key results included positive views of receiving additional clinical care, negative experiences of risk communication, and weight management support was considered a priority. Study 2: Healthcare professionals felt the pathways were worthwhile, facilitated good practice, and increased confidence. Training was consistently identified as being required. Healthcare professionals predominantly focussed on women’s response to sensitive obesity communication. Study 3: There was good compliance with antenatal clinical interventions. However, there was poor compliance with public health and postnatal interventions. There were some strong areas of agreement between component studies which can inform future development of the pathways. However, disagreement between studies included a lack of shared priorities between healthcare professionals and women, different perspectives on communication issues, and different perspectives on women’s prioritisation of weight management.ConclusionThe differences between healthcare professionals’ and women’s priorities and perspectives are important factors to consider when developing care pathways. Shared perspectives could help facilitate more effective implementation of the pathway interventions that have poor compliance.     

Individual boldness is linked to protective shell shape in aquatic snails

The existence of consistent individual differences in behaviour (‘animal personality’) has been well documented in recent years. However, how such individual variation in behaviour is maintained over evolutionary time is an ongoing conundrum. A well-studied axis of animal personality is individual variation along a bold–shy continuum, where individuals differ consistently in their propensity to take risks. A predation-risk cost to boldness is often assumed, but also that the reproductive benefits associated with boldness lead to equivalent fitness outcomes between bold and shy individuals over a lifetime. However, an alternative or complementary explanation may be that bold individuals phenotypically compensate for their risky lifestyle to reduce predation costs, for instance by investing in more pronounced morphological defences. Here, we investigate the ‘phenotypic compensation’ hypothesis, i.e. that bold individuals exhibit more pronounced anti-predator defences than shy individuals, by relating shell shape in the aquatic snail Radix balthica to an index of individual boldness. Our analyses find a strong relationship between risk-taking propensity and shell shape in this species, with bolder individuals exhibiting a more defended shell shape than shy individuals. We suggest that this supports the ‘phenotypic compensation’ hypothesis and sheds light on a previously poorly studied mechanism to promote the maintenance of personality variation among animals.     

PathAct: a novel method for pathway analysis using gene expression profiles

We developed PathAct, a novel method for pathway analysis to investigate the biological and clinical implications of the gene expression profiles. The advantage of PathAct in comparison with the conventional pathway analysis methods is that it can estimate pathway activity levels for individual patient quantitatively in the form of a pathway-by-sample matrix. This matrix can be used for further analysis such as hierarchical clustering and other analysis methods. To evaluate the feasibility of PathAct, comparison with frequently used gene-enrichment analysis methods was conducted using two public microarray datasets. The dataset #1 was that of breast cancer patients, and we investigated pathways associated with triple-negative breast cancer by PathAct, compared with those obtained by gene set enrichment analysis (GSEA). The dataset #2 was another breast cancer dataset with disease-free survival (DFS) of each patient. Contribution by each pathway to prognosis was investigated by our method as well as the Database for Annotation, Visualization and Integrated Discovery (DAVID) analysis. In the dataset #1, four out of the six pathways that satisfied p < 0.05 and FDR < 0.30 by GSEA were also included in those obtained by the PathAct method. For the dataset #2, two pathways (“Cell Cycle” and “DNA replication”) out of four pathways by PathAct were commonly identified by DAVID analysis. Thus, we confirmed a good degree of agreement among PathAct and conventional methods. Moreover, several applications of further statistical analyses such as hierarchical cluster analysis by pathway activity, correlation analysis and survival analysis between pathways were conducted.     

Cultural Differences in Donation Decision-Making

Decisions to help those in need are essential for human development and survival. Previous studies have demonstrated the “identified effect”, in which one identifiable individual typically invokes stronger feelings of compassion and receives greater aid than statistical victim. However, this preference might be influenced by cultural differences. In the current study, Chinese respondents’ ratings of distress and sympathy and their willingness to contribute are greater for a group of sick children than an individual. In the U.S., greater willingness to help and sympathy are elicited by an identified victim in comparison with an unidentified one. The different results may demonstrate the importance of cultural differences when trying to understand people’s prosocial behavior.     

Carotid Artery Infusions for Pharmacokinetic and Pharmacodynamic Analysis of Taxanes in Mice

When proposing the use of a drug, drug combination, or drug delivery into a novel system, one must assess the pharmacokinetics of the drug in the study model. As the use of mouse models are often a vital step in preclinical drug discovery and drug development^1-8, it is necessary to design a system to introduce drugs into mice in a uniform, reproducible manner. Ideally, the system should permit the collection of blood samples at regular intervals over a set time course. The ability to measure drug concentrations by mass-spectrometry, has allowed investigators to follow the changes in plasma drug levels over time in individual mice^{1, 9, 10}. In this study, paclitaxel was introduced into transgenic mice as a continuous arterial infusion over three hours, while blood samples were simultaneously taken by retro-orbital bleeds at set time points. Carotid artery infusions are a potential alternative to jugular vein infusions, when factors such as mammary tumors or other obstructions make jugular infusions impractical. Using this technique, paclitaxel concentrations in plasma and tissue achieved similar levels as compared to jugular infusion. In this tutorial, we will demonstrate how to successfully catheterize the carotid artery by preparing an optimized catheter for the individual mouse model, then show how to insert and secure the catheter into the mouse carotid artery, thread the end of the catheter out through the back of the mouse’s neck, and hook the mouse to a pump to deliver a controlled rate of drug influx. Multiple low volume retro-orbital bleeds allow for analysis of plasma drug concentrations over time.     

Giemsa-Stained Wet Mount Based Method for Reticulocyte Quantification: A Viable Alternative in Resource Limited or Malaria Endemic Settings

The quantity of circulating reticulocytes is an important indicator of erythropoietic activity in response to a wide range of haematological pathologies. While most modern laboratories use flow cytometry to quantify reticulocytes, most field laboratories still rely on ‘subvital’ staining. The specialist ‘subvital’ stains, New Methylene Blue (NMB) and Brilliant Crésyl Blue are often difficult to procure, toxic, and show inconsistencies between batches. Here we demonstrate the utility of Giemsa''s stain (commonly used microbiology and parasitology) in a ‘subvital’ manner to provide an accurate method to visualize and count reticulocytes in blood samples from normal and malaria-infected individuals.     

Self-organizing dominance hierarchies in a wild primate population

Linear dominance hierarchies, which are common in social animals, can profoundly influence access to limited resources, reproductive opportunities and health. In spite of their importance, the mechanisms that govern the dynamics of such hierarchies remain unclear. Two hypotheses explain how linear hierarchies might emerge and change over time. The ‘prior attributes hypothesis’ posits that individual differences in fighting ability directly determine dominance ranks. By contrast, the ‘social dynamics hypothesis’ posits that dominance ranks emerge from social self-organization dynamics such as winner and loser effects. While the prior attributes hypothesis is well supported in the literature, current support for the social dynamics hypothesis is limited to experimental studies that artificially eliminate or minimize individual differences in fighting abilities. Here, we present the first evidence supporting the social dynamics hypothesis in a wild population. Specifically, we test for winner and loser effects on male hierarchy dynamics in wild baboons, using a novel statistical approach based on the Elo rating method for cardinal rank assignment, which enables the detection of winner and loser effects in uncontrolled group settings. Our results demonstrate (i) the presence of winner and loser effects, and (ii) that individual susceptibility to such effects may have a genetic basis. Taken together, our results show that both social self-organization dynamics and prior attributes can combine to influence hierarchy dynamics even when agonistic interactions are strongly influenced by differences in individual attributes. We hypothesize that, despite variation in individual attributes, winner and loser effects exist (i) because these effects could be particularly beneficial when fighting abilities in other group members change over time, and (ii) because the coevolution of prior attributes and winner and loser effects maintains a balance of both effects.     

An ontogenetic perspective on individual differences

Phenotypic differences among individuals can arise during any stage of life. Although several distinct processes underlying individual differences have been defined and studied (e.g. parental effects, senescence), we lack an explicit, unified perspective for understanding how these processes contribute separately and synergistically to observed variation in functional traits. We propose a conceptual framework based on a developmental view of life-history variation, linking each ontogenetic stage with the types of individual differences originating during that period. In our view, the salient differences among these types are encapsulated by three key criteria: timing of onset, when fitness consequences are realized, and potential for reversibility. To fill a critical gap in this framework, we formulate a new term to refer to individual differences generated during adulthood—reversible state effects. We define these as ‘reversible changes in a functional trait resulting from life-history trade-offs during adulthood that affect fitness’, highlighting how the adult phenotype can be repeatedly altered in response to environmental variation. Defining individual differences in terms of trade-offs allows explicit predictions regarding when and where fitness consequences should be expected. Moreover, viewing individual differences in a developmental context highlights how different processes can work in concert to shape phenotype and fitness, and lays a foundation for research linking individual differences to ecological and evolutionary theory.     

How social network structure affects decision-making in Drosophila melanogaster

Animals use a number of different mechanisms to acquire crucial information. During social encounters, animals can pass information from one to another but, ideally, they would only use information that benefits survival and reproduction. Therefore, individuals need to be able to determine the value of the information they receive. One cue can come from the behaviour of other individuals that are already using the information. Using a previous extended dataset, we studied how individual decision-making is influenced by the behaviour of conspecifics in Drosophila melanogaster. We analysed how uninformed flies acquire and later use information about oviposition site choice they learn from informed flies. Our results suggest that uninformed flies adjust their future choices based on how coordinated the behaviours of the informed individuals they encounter are. Following social interaction, uninformed flies tended either to collectively follow the choice of the informed flies or to avoid it. Using social network analysis, we show that this selective information use seems to be based on the level of homogeneity of the social network. In particular, we found that the variance of individual centrality parameters among informed flies was lower in the case of a ‘follow’ outcome compared with the case of an ‘avoid’ outcome.     

Predicting Risk-Taking Behavior from Prefrontal Resting-State Activity and Personality

Risk-taking is subject to considerable individual differences. In the current study, we tested whether resting-state activity in the prefrontal cortex and trait sensitivity to reward and punishment can help predict risk-taking behavior. Prefrontal activity at rest was assessed in seventy healthy volunteers using electroencephalography, and compared to their choice behavior on an economic risk-taking task. The Behavioral Inhibition System/Behavioral Activation System scale was used to measure participants’ trait sensitivity to reward and punishment. Our results confirmed both prefrontal resting-state activity and personality traits as sources of individual differences in risk-taking behavior. Right-left asymmetry in prefrontal activity and scores on the Behavioral Inhibition System scale, reflecting trait sensitivity to punishment, were correlated with the level of risk-taking on the task. We further discovered that scores on the Behavioral Inhibition System scale modulated the relationship between asymmetry in prefrontal resting-state activity and risk-taking. The results of this study demonstrate that heterogeneity in risk-taking behavior can be traced back to differences in the basic physiology of decision-makers’ brains, and suggest that baseline prefrontal activity and personality traits might interplay in guiding risk-taking behavior.     

Gene action,genetic variation,and GWAS: A user-friendly web tool

Fisher’s partitioning of genotypic values and genetic variance is highly relevant in the current era of genome-wide association studies (GWASs). However, despite being more than a century old, a number of persistent misconceptions related to nonadditive genetic effects remain. We developed a user-friendly web tool, the Falconer ShinyApp, to show how the combination of gene action and allele frequencies at causal loci translate to genetic variance and genetic variance components for a complex trait. The app can be used to demonstrate the relationship between a SNP effect size estimated from GWAS and the variation the SNP generates in the population, i.e., how locus-specific effects lead to individual differences in traits. In addition, it can also be used to demonstrate how within and between locus interactions (dominance and epistasis, respectively) usually do not lead to a large amount of nonadditive variance relative to additive variance, and therefore, that these interactions usually do not explain individual differences in a population.     

What Is the Significance of Difference in Phenotypic Variability across SNP Genotypes?

We studied the general problem of interpreting and detecting differences in phenotypic variability among the genotypes at a locus, from both a biological and a statistical point of view. The scales on which we measure interval-scale quantitative traits are man-made and have little intrinsic biological relevance. Before claiming a biological interpretation for genotype differences in variance, we should be sure that no monotonic transformation of the data can reduce or eliminate these differences. We show theoretically that for an autosomal diallelic SNP, when the three corresponding means are distinct so that the variance can be expressed as a quadratic function of the mean, there implicitly exists a transformation that will tend to equalize the three variances; we also demonstrate how to find a transformation that will do this. We investigate the validity of Bartlett’s test, Box’s modification of it, and a modified Levene’s test to test for differences in variances when normality does not hold. We find that, although they may detect differences in variability, these tests do not necessarily detect differences in variance. The same is true for permutation tests that use these three statistics.     

Investigating Neuroanatomical Features in Top Athletes at the Single Subject Level

In sport events like Olympic Games or World Championships competitive athletes keep pushing the boundaries of human performance. Compared to team sports, high achievements in many athletic disciplines depend solely on the individual’s performance. Contrasting previous research looking for expertise-related differences in brain anatomy at the group level, we aim to demonstrate changes in individual top athlete’s brain, which would be averaged out in a group analysis. We compared structural magnetic resonance images (MRI) of three professional track-and-field athletes to age-, gender- and education-matched control subjects. To determine brain features specific to these top athletes, we tested for significant deviations in structural grey matter density between each of the three top athletes and a carefully matched control sample. While total brain volumes were comparable between athletes and controls, we show regional grey matter differences in striatum and thalamus. The demonstrated brain anatomy patterns remained stable and were detected after 2 years with Olympic Games in between. We also found differences in the fusiform gyrus in two top long jumpers. We interpret our findings in reward-related areas as correlates of top athletes’ persistency to reach top-level skill performance over years.