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Recent advances in Markov chain Monte Carlo (MCMC) extend the scope of Bayesian inference to models for which the likelihood function is intractable. Although these developments allow us to estimate model parameters, other basic problems such as estimating the marginal likelihood, a fundamental tool in Bayesian model selection, remain challenging. This is an important scientific limitation because testing psychological hypotheses with hierarchical models has proven difficult with current model selection methods. We propose an efficient method for estimating the marginal likelihood for models where the likelihood is intractable, but can be estimated unbiasedly. It is based on first running a sampling method such as MCMC to obtain samples for the model parameters, and then using these samples to construct the proposal density in an importance sampling (IS) framework with an unbiased estimate of the likelihood. Our method has several attractive properties: it generates an unbiased estimate of the marginal likelihood, it is robust to the quality and target of the sampling method used to form the IS proposals, and it is computationally cheap to estimate the variance of the marginal likelihood estimator. We also obtain the convergence properties of the method and provide guidelines on maximizing computational efficiency. The method is illustrated in two challenging cases involving hierarchical models: identifying the form of individual differences in an applied choice scenario, and evaluating the best parameterization of a cognitive model in a speeded decision making context. Freely available code to implement the methods is provided. Extensions to posterior moment estimation and parallelization are also discussed., 38 pages, 4 tables, 5 appendices

Objective The present research applied a well-established measure of cognitive workload in driving literature to an in-lab paradigm. We then extended this by comparing the in-lab version of the task to an online version. Background The accurate and objective measurement of cognitive workload is important in many aspects of psychological research. The detection response task (DRT) is a well-validated method for measuring cognitive workload that has been used extensively in applied tasks, for example, to investigate the effects of phone usage or passenger conversation on driving, but has been used sparingly outside of this field. Method The study investigated whether the DRT could be used to measure cognitive workload in tasks more commonly used in experimental cognitive psychology and whether this application could be extended to online environments. We had participants perform a multiple object tracking (MOT) task while simultaneously performing a DRT. We manipulated the cognitive load of the MOT task by changing the number of dots to be tracked. Results Measurements from the DRT were sensitive to changes in the cognitive load, establishing the efficacy of the DRT for experimental cognitive tasks in lab-based situations. This sensitivity continued when applied to an online environment (our code for the online DRT implementation is freely available at https://osf.io/dc39s/ ), though to a reduced extent compared to the in-lab situation. Conclusion The MOT task provides an effective manipulation of cognitive workload. The DRT is sensitive to changes in workload across a range of settings and is suitable to use outside of driving scenarios, as well as via online delivery. Application Methodology shows how the DRT could be used to measure sources of cognitive workload in a range of human factors contexts.

With the advancement of technologies like in-car navigation and smartphones, concerns around how cognitive functioning is influenced by "workload" are increasingly prevalent. Research shows that spreading effort across multiple tasks can impair cognitive abilities through an overuse of resources, and that similar overload effects arise in difficult single-task paradigms. We developed a novel lab-based extension of the Detection Response Task, which measures workload, and paired it with a Multiple Object Tracking Task to manipulate cognitive load. Load was manipulated either by changing within-task difficulty or by the addition of an extra task. Using quantitative cognitive modelling we showed that these manipulations cause similar cognitive impairments through diminished processing rates, but that the introduction of a second task tends to invoke more cautious response strategies that do not occur when only difficulty changes. We conclude that more prudence should be exercised when directly comparing multi-tasking and difficulty-based workload impairments, particularly when relying on measures of central tendency.

Few fathers enrol in web-based preventive parenting programs for adolescent mental health, despite the evidence of the benefits associated with their participation. To inform the development of father-inclusive programs, this study used a discrete choice experiment (DCE) design to determine (a) the relative influence of number of sessions, program benefits, program participants, and user control over program content on fathers’ preferences for web-based preventive parenting programs; and (b) whether selected father characteristics were associated with their preferences. One hundred and seventy-one fathers completed the DCE survey, which comprised 25 choices between hypothetical programs. Programs that included the participant’s adolescent child (z = 10.06, p < 0.0001), or parenting partner (z = 7.30, p < 0.001) were preferred over those designed for fathers only. Participants also preferred program content that was recommended for them by experts (z = −4.31, p < 0.0001) and programs with fewer sessions (z = −2.94, p < 0.01). Program benefits did not predict fathers’ choice of program. Prior use of a parenting program, level of education, perceived role of parenting for adolescent mental health, and being part of a dual-working family were associated with preferences. Application of these findings may improve paternal enrolment in web-based preventive parenting programs.

Significance In modern life, we engage with many sources of information concurrently. To do this, we must continuously switch between different tasks, but this comes at a cost to performance, especially in older adults. Using a large dataset from an online cognitive-training platform, we develop a computational model of task switching that defines distinct latent measures of activating the relevant task, deactivating the irrelevant task, and making a decision. This model shows that, although task practice can improve task-switching performance, persistent costs remain even after extensive practice, and more so in older adults. We show that, with extensive task practice, older people can become functionally similar to less-practiced younger people., An important feature of human cognition is the ability to flexibly and efficiently adapt behavior in response to continuously changing contextual demands. We leverage a large-scale dataset from Lumosity, an online cognitive-training platform, to investigate how cognitive processes involved in cued switching between tasks are affected by level of task practice across the adult lifespan. We develop a computational account of task switching that specifies the temporal dynamics of activating task-relevant representations and inhibiting task-irrelevant representations and how they vary with extended task practice across a number of age groups. Practice modulates the level of activation of the task-relevant representation and improves the rate at which this information becomes available, but has little effect on the task-irrelevant representation. While long-term practice improves performance across all age groups, it has a greater effect on older adults. Indeed, extensive task practice can make older individuals functionally similar to less-practiced younger individuals, especially for cognitive measures that focus on the rate at which task-relevant information becomes available.

Fusobacterium nucleatum (Fn) is a ubiquitous opportunistic pathogen with an emerging role as an oncomicrobe in colorectal and other cancer types. Fn can adhere to and invade host cells in a manner that varies across Fn strains and host cell phenotypes. Here we performed pairwise co-cultures between three Fn strains and two immortalized primary host cell types (colonic epithelial cells and vascular endothelial cells) followed by RNA-seq and ChIP-seq to investigate transcriptional and epigenetic host cell responses. We observed that Fn-induced host cell transcriptional modulation involves strong upregulation of genes related to immune migration and inflammatory processes, such as TNF, CXCL8, CXCL1, and CCL20. Further, we identified genes strongly upregulated specifically in conditions of host cell invasion, including overexpression of both EFNA1 and LIF, two genes commonly upregulated in colorectal cancer and associated with poor patient outcomes, and PTGS2 (COX2), a gene associated with the protective effect of aspirin in the colorectal cancer setting. Interestingly, we also observed downregulation of numerous histone modification genes upon Fn exposure. To further explore this relationship, we used the ChIP-seq data to annotate chromatin states genome-wide. We found significant chromatin remodeling following Fn exposure in conditions of host cell invasion, with substantial increases in the frequency of states corresponding to active enhancers as well as low signal or quiescent states. Thus, our results highlight increased inflammation and chemokine gene expression as conserved host cell responses to Fn exposure, and extensive host cell epigenomic changes associated with Fn host cell invasion. These results extend our understanding of Fn as an emerging pathogen and highlight the importance of considering strain heterogeneity and host cell phenotypic variation when exploring pathogenic mechanisms of Fn.

BackTrack is a multi-component, community-based intervention designed to build capacity amongst 14–17-year-old high risk young people. The aim of the current study seeks to explore community value and preferences for reducing youth crime and improving community safety using BackTrack in a rural setting in Armidale, New South Wales, Australia. The study design used discrete choice experiments (DCEs), designed in accordance with the 10-item checklist outlined by the International Society for Pharmacoeconomics and Outcomes Research. The DCE was pilot tested on 43 participants to test feasibility and comprehension. A revised version of the survey was subsequently completed by 282 people over a 12-day period between 30 May 2016 and 10 June 2016, representing a survey response rate of 35%. Ninety per cent of respondents were residents of Armidale, the local rural town where BackTrack was implemented. The DCE generated results that consistently demonstrated a preference for social programs to address youth crime and community safety in the Armidale area. Respondents chose BackTrack over Greater Police Presence 75% of the time with an annual benefit of Australian dollars (AUD) 150 per household, equivalent to a community benefit of AUD 2.04 million. This study estimates a strong community preference for BackTrack relative to more policing (a community willing to pay equivalent to AUD 2.04 million) highlighting the clear value of including community preferences when evaluating community-based programs for high-risk young people.

ObjectiveWe have designed tracking and collision prediction tasks to elucidate the differences in the physiological response to the workload variations in basic ATC tasks to untangle the impact of workload variations experienced by operators working in a complex ATC environment.BackgroundEven though several factors influence the complexity of ATC tasks, keeping track of the aircraft and preventing collision are the most crucial.MethodsPhysiological measures, such as electroencephalogram (EEG), eye activity, and heart rate variability (HRV) data, were recorded from 24 participants performing tracking and collision prediction tasks with three levels of difficulty.ResultsThe neurometrics of workload variations in the tracking and collision prediction tasks were markedly distinct, indicating that neurometrics can provide insights on the type of mental workload. The pupil size, number of blinks and HRV metric, root mean square of successive difference (RMSSD), varied significantly with the mental workload in both these tasks in a similar manner.ConclusionOur findings indicate that variations in task load are sensitively reflected in physiological signals, such as EEG, eye activity and HRV, in these basic ATC-related tasks.ApplicationThese findings have applicability to the design of future mental workload adaptive systems that integrate neurometrics in deciding not just ‘when’ but also ‘what’ to adapt. Our study provides compelling evidence in the viability of developing intelligent closed-loop mental workload adaptive systems that ensure efficiency and safety in ATC and beyond.PrécisThis article identifies the physiological correlates of mental workload variation in basic ATC tasks. The findings assert that neurometrics can provide more information on the task that contributes to the workload, which can aid in the design of intelligent mental workload adaptive system.

In a Dutch auction, an item is offered for sale at a set maximum price. The price is then gradually lowered over a fixed interval of time until a bid is made, securing the item for the bidder at the current price. Bidders must trade-off between certainty and price: bid early to secure the item and you pay a premium; bid later at a lower price but risk losing to another bidder. These properties of Dutch auctions provide new opportunities to study competitive decision-making in a group setting. We developed a novel computerised Dutch auction platform and conducted a set of experiments manipulating volatility (fixed vs varied number of items for sale) and price reduction interval rate (step-rate). Triplets of participants ($$N=66$$ N = 66 ) competed with hypothetical funds against each other. We report null effects of step-rate and volatility on bidding behaviour. We developed a novel adaptation of prospect theory to account for group bidding behaviour by balancing certainty and subjective expected utility. We show the model is sensitive to variation in auction starting price and can predict the associated changes in group bid prices that were observed in our data.

Fusobacterium nucleatum is an emerging microbe of importance in the pathogenesis of colorectal cancer. Strains of this enigmatic bacterial species vary in their capacity to invade human epithelial cells, a virulence determinant which has important implications in disease. Here, we infected human colorectal epithelial (Caco-2) cells in vitro with a known, highly invasive strain of F. nucleatum isolated from a Crohn’s Disease patient, as well as a further invasive isolate of F. nucleatum derived from a colorectal cancer tumour. We used transcriptional profiling to determine the human genes upregulated during the invasion process compared to exposure to a non-invasive E.coli control strain. Infection with F. nucleatum strains resulted in the upregulation of several host genes, including two associated with tumorigenesis: dll4 and klf4.

It is commonly assumed that a specific testing occasion (task, design, procedure, etc.) provides insights that generalise beyond that occasion. This assumption is infrequently carefully tested in data. We develop a statistically principled method to directly estimate the correlation between latent components of cognitive processing across tasks, contexts, and time. This method simultaneously estimates individual-participant parameters of a cognitive model at each testing occasion, group-level parameters representing across-participant parameter averages and variances, and across-task correlations. The approach provides a natural way to "borrow" strength across testing occasions, which can increase the precision of parameter estimates across all testing occasions. Two example applications demonstrate that the method is practical in standard designs. The examples, and a simulation study, also provide evidence about the reliability and validity of parameter estimates from the linear ballistic accumulator model. We conclude by highlighting the potential of the parameter-correlation method to provide an "assumption-light" tool for estimating the relatedness of cognitive processes across tasks, contexts, and time., Comment: 30 pages, 10 figures, 5 tables

KRAS codon 12 mutations are among the most common hotspot mutations in human cancer. Using a functional screening platform we set out to identify αβ T-cell receptors (TCRs) as potential targeting reagents for KRASG12D and/or KRASG12V neoepitopes presented by the prevalent HLA-A*02:01 allele. Here we describe isolation and characterization of three distinct CD8+ T cell clones from a pre-treated 76 year old patient with pancreatic ductal adenocarcinoma (PDAC). One clone was KRASG12V reactive and two clones were KRASG12D reactive. Tetramer staining showed high specificity of each T cell clone for its cognate HLA-A*02:01 restricted KRASG12V or KRASG12D neoepitope (>98% tetramer positive) without appreciable cross-reactivity to wild-type KRAS (+ T cells by lentiviral transduction, substituting the human αβ TCR constant gene segments with murine αβ TCR constant gene segments to prevent mispairing with endogenous TCR subunits. Tetramer analysis and IFN-γ ELISpot analysis confirmed the specificity of each reconstituted TCR for its cognate HLA-A*02:01 restricted KRAS neoepitope. To test cytolytic activity TCR-transduced healthy donor CD8+ T cells were co-cultured with KRASG12V, KRASG12D or KRASwt peptide-pulsed K562-HLA-A*02:01 antigen presenting cells at an effector to target cell ratio of 4:1. Under these conditions we observed neoepitope-specific killing of 16.5% to 19.0% of target cell populations. To assess in vivo activity we developed a KRASG12V/A*02:01 patient-derived xenograft (PDX) mouse model. Over a 56-day period, PDX bearing mice infused with human TCR-transduced T cells had significantly reduced tumor growth and longer survival compared to mice infused with non-transduced control T cells. In conjunction with other therapeutic approaches, immune effector cell therapies expressing these TCRs may improve outcomes for HLA-A*02:01 patients with KRASG12V and/or KRASG12D positive tumors.

Anti-CD19 CAR-T therapy for B cell malignancies has shown clinical success, but a major limitation is the logistical complexity and high cost of manufacturing autologous cell products. If engineered for improved safety, direct infusion of viral gene transfer vectors to initiate in vivo CAR-T transduction, expansion and anti-tumor activity could provide an alternative, universal approach. To explore this approach we administered approximately 20 million replication-incompetent VSV-G lentiviral particles carrying an anti-CD19CAR-2A-GFP transgene comprising either an FMC63 (human) or 1D3 (murine) anti-CD19 binding domain, or a GFP-only control transgene, to wild-type C57BL/6 mice by tail vein infusion. The dynamics of immune cell subsets isolated from peripheral blood were monitored at weekly intervals. We saw emergence of a persistent CAR-transduced CD3+ T cell population beginning week 3-4 that reached a maximum of 13.5 +/-0.58% (mean +/-SD) and 7.8 +/-0.76% of the peripheral blood CD3+ T cell population in mice infused with ID3-CAR or FMC63-CAR lentivector, respectively, followed by a rapid decline in each case of the B cell content of peripheral blood. Complete B cell aplasia was apparent by week 5 and was sustained until the end of the protocol (week 8). No significant CAR positive populations were observed within other immune cell subsets or other tissues. These results indicate that direct IV infusion of conventional VSV-G pseudotyped lentiviral particles carrying a CD19 CAR transgene can transduce T cells that then fully ablate endogenous B cells in wild type mice.

Purpose: Immune checkpoint inhibitors (ICI) have revolutionized the treatment of solid tumors with dramatic and durable responses seen across multiple tumor types. However, identifying patients who will respond to these drugs remains challenging, particularly in the context of advanced and previously treated cancers. Experimental Design: We characterized fresh tumor biopsies from a heterogeneous pan-cancer cohort of 98 patients with metastatic predominantly pretreated disease through the Personalized OncoGenomics program at BC Cancer (Vancouver, Canada) using whole genome and transcriptome analysis (WGTA). Baseline characteristics and follow-up data were collected retrospectively. Results: We found that tumor mutation burden, independent of mismatch repair status, was the most predictive marker of time to progression (P = 0.007), but immune-related CD8+ T-cell and M1-M2 macrophage ratio scores were more predictive for overall survival (OS; P = 0.0014 and 0.0012, respectively). While CD274 [programmed death-ligand 1 (PD-L1)] gene expression is comparable with protein levels detected by IHC, we did not observe a clinical benefit for patients with this marker. We demonstrate that a combination of markers based on WGTA provides the best stratification of patients (P = 0.00071, OS), and also present a case study of possible acquired resistance to pembrolizumab in a patient with non–small cell lung cancer. Conclusions: Interpreting the tumor-immune interface to predict ICI efficacy remains challenging. WGTA allows for identification of multiple biomarkers simultaneously that in combination may help to identify responders, particularly in the context of a heterogeneous population of advanced and previously treated cancers, thus precluding tumor type–specific testing.

Objective: Parenthood is central to the personal and social identity of many people. For individuals with psychotic disorders, parenthood is often associated with formidable challenges. We aimed to identify predictors of adequate parenting among parents with psychotic disorders. Methods: Data pertaining to 234 parents with psychotic disorders living with dependent children were extracted from a population-based prevalence study, the 2010 second Australian national survey of psychosis, and analysed using confirmatory factor analysis. Parenting outcome was defined as quality of care of children, based on participant report and interviewer enquiry/exploration, and included level of participation, interest and competence in childcare during the last 12 months. Results: Five hypothesis-driven latent variables were constructed and labelled psychosocial support, illness severity, substance abuse/dependence, adaptive functioning and parenting role. Importantly, 75% of participants were not identified to have any dysfunction in the quality of care provided to their child(ren). Severity of illness and adaptive functioning were reliably associated with quality of childcare. Psychosocial support, substance abuse/dependence and parenting role had an indirect relationship to the outcome variable via their association with either severity of illness and/or adaptive functioning. Conclusion: The majority of parents in the current sample provided adequate parenting. However, greater symptom severity and poorer adaptive functioning ultimately leave parents with significant difficulties and in need of assistance to manage their parenting obligations. As symptoms and functioning can change episodically for people with psychotic illness, provision of targeted and flexible support that can deliver temporary assistance during times of need is necessary. This would maximise the quality of care provided to vulnerable children, with potential long-term benefits.

The digital imaging and remote sensing image generation model is a physics-based image and data simulation model that is primarily used to generate synthetic imagery across the visible to thermal infrared regions using engineering-driven descriptions of remote sensing systems. The model recently went through a major redesign and reimplementation effort to address changes in user requirements and numerical computation trends that have emerged in the 15 years since the last major development effort. The new model architecture adopts some of the latest light transport algorithms matured by the computer graphics community and features a framework that is easily parallelized at the microscale (multithreading) and macroscale (cluster-based computing). A detailed description of the framework is provided, including a novel method for efficiently storing, evaluating, integrating, and sampling spherical and hemispherical datasets appropriate for the representation of modeled or measured bidirectional scattering, reflectance, and transmission distribution functions. The capabilities of the model are then briefly demonstrated and cross-verified with scenarios of interest to the remote sensing community.

Listeners rely on multiple acoustic cues to recognize any phoneme. The relative contribution of these cues to listeners' perception is typically inferred from listeners' categorization of sounds in a two-alternative forced-choice task. Here we advocate the use of an evidence accumulation model to analyze categorization as well as response time data from such cue weighting paradigms in terms of the processes that underlie the listeners' categorization. We tested 30 Dutch listeners on their categorization of speech sounds that varied between typical /a/ and /a/ in vowel quality (F1 and F2) and duration. Using the linear ballistic accumulator model, we found that the changes in spectral quality and duration lead to changes in the speed of information processing, and the effects were larger for spectral quality. In addition, for stimuli with atypical spectral information, listeners accumulate evidence faster for /a/ compared to /ad. Finally, longer durations of sounds did not produce longer estimates of perceptual encoding time. Our results demonstrate the utility of evidence accumulation models for learning about the latent processes that underlie phoneme categorization. The implications for current theory in speech perception as well as future directions for evidence accumulation models are discussed. (C) 2016 Elsevier Ltd. All rights reserved.

Recent decades have witnessed amazing advances in both mathematical models of cognition and in the field of cognitive neuroscience. These developments were initially independent of one another, but recently the fields have started to become interested in joining forces. The resulting joint modeling of behavioral and neural data can be difficult, but has proved fruitful. We briefly review different approaches used in decision-making research for linking behavioral and neural data, and also provide an example. Our example provides a tight link between behavioral data and evoked scalp potentials measured during mental rotation. The example model illustrates a powerful hypothesis-driven way of linking such data sets. We demonstrate the use of such a model, provide a model comparison against interesting alternatives, and discuss the conclusions that follow from applying such a joint model.

Objective To test the effects of enhanced display information (“symbology”) on cognitive workload in a simulated helicopter environment, using the detection response task (DRT). Background Workload in highly demanding environments can be influenced by the amount of information given to the operator and consequently it is important to limit potential overload. Methods Participants (highly trained military pilots) completed simulated helicopter flights, which varied in visual conditions and the amount of information given. During these flights, participants also completed a DRT as a measure of cognitive workload. Results With more visual information available, pilots’ landing accuracy was improved across environmental conditions. The DRT is sensitive to changes in cognitive workload, with workload differences shown between environmental conditions. Increasing symbology appeared to have a minor effect on workload, with an interaction effect of symbology and environmental condition showing that symbology appeared to moderate workload. Conclusion The DRT is a useful workload measure in simulated helicopter settings. The level of symbology-moderated pilot workload. The increased level of symbology appeared to assist pilots’ flight behavior and landing ability. Results indicate that increased symbology has benefits in more difficult scenarios. Applications The DRT is an easily implemented and effective measure of cognitive workload in a variety of settings. In the current experiment, the DRT captures the increased workload induced by varying the environmental conditions, and provides evidence for the use of increased symbology to assist pilots.

Independent racing evidence-accumulator models have proven fruitful in advancing understanding of rapid decisions, mainly in the case of binary choice, where they can be relatively easily estimated and are known to account for a range of benchmark phenomena. Typically, such models assume a one-to-one mapping between accumulators and responses. We explore an alternative independent-race framework where more than one accumulator can be associated with each response, and where a response is triggered when a sufficient number of accumulators associated with that response reach their thresholds. Each accumulator is primarily driven by the difference in evidence supporting one versus another response (i.e., that response's "advantage"), with secondary inputs corresponding to the total evidence for both responses and a constant term. We use Brown and Heathcote's (2008) linear ballistic accumulator (LBA) to instantiate the framework in a mathematically tractable measurement model (i.e., a model whose parameters can be successfully recovered from data). We show this "advantage LBA" model provides a detailed quantitative account of a variety of benchmark binary and multiple choice phenomena that traditional independent accumulator models struggle with; in binary choice the effects of additive versus multiplicative changes to input values, and in multiple choice the effects of manipulations of the strength of lure (i.e., nontarget) stimuli and Hick's law. We conclude that the advantage LBA provides a tractable new avenue for understanding the dynamics of decisions among multiple choices. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

With the advancement of technologies like in-car navigation and smartphones, concerns around how cognitive functioning is influenced by ``workload'' are increasingly prevalent. Research shows that spreading effort across multiple tasks can impair cognitive abilities through an overuse of resources, and that similar overload effects arise in difficult single-task paradigms. We developed a novel lab-based extension of the Detection Response Task, which measures workload, and paired it with a Multiple Object Tracking Task to manipulate cognitive load. Load was manipulated either by changing within-task difficulty or by the addition of an extra task. Using quantitative cognitive modelling we showed that these manipulations cause similar cognitive impairments through diminished processing rates, but that the introduction of a second task tends to invoke more cautious response strategies that do not occur when only difficulty changes. We conclude that more prudence should be exercised when directly comparing multitasking and difficulty-based workload impairments, particularly when relying on measures of central tendency.

Neoantigens present unique and specific targets for personalized cancer immunotherapy strategies. Given the low mutational burden yet immunotherapy responsiveness of malignant mesothelioma (MM) when compared to other carcinogen-induced malignancies, identifying candidate neoantigens and T cells that recognize them has been a challenge. We used pleural effusions to gain access to MM tumor cells as well as immune cells in order to characterize the tumor-immune interface in MM. We characterized the landscape of potential neoantigens from SNVs identified in 27 MM patients and performed whole transcriptome sequencing of cell populations from 18 patient-matched pleural effusions. IFNγ ELISpot was performed to detect a CD8+ T cell responses to predicted neoantigens in one patient. We detected a median of 68 (range 7–258) predicted neoantigens across the samples. Wild-type non-binding to mutant binding predicted neoantigens increased risk of death in a model adjusting for age, sex, smoking status, histology and treatment (HR: 33.22, CI: 2.55–433.02, p = .007). Gene expression analysis indicated a dynamic immune environment within the pleural effusions. TCR clonotypes increased with predicted neoantigen burden. A strong activated CD8+ T-cell response was identified for a predicted neoantigen produced by a spontaneous mutation in the ROBO3 gene. Despite the challenges associated with the identification of bonafide neoantigens, there is growing evidence that these molecular changes can provide an actionable target for personalized therapeutics in difficult to treat cancers. Our findings support the existence of candidate neoantigens in MM despite the low mutation burden of the tumor, and may present improved treatment opportunities for patients.

Mechanistic studies in human cancer have relied heavily on cell lines and mouse models, but are limited by in vitro adaptation and species context issues, respectively. More recent efforts have utilized patient-derived xenografts; however, these are hampered by variable genetic background, inability to study early events, and practical issues with availability/reproducibility. We report here an efficient, reproducible model of T-cell leukemia in which lentiviral transduction of normal human cord blood yields aggressive leukemia that appears indistinguishable from natural disease. We utilize this synthetic model to uncover a role for oncogene-induced HOXB activation which is operative in leukemia cells-of-origin and persists in established tumors where it defines a novel subset of patients distinct from other known genetic subtypes and with poor clinical outcome. We show further that anterior HOXB genes are specifically activated in human T-ALL by an epigenetic mechanism and confer growth advantage in both pre-leukemia cells and established clones., Studies with patient derived xenografts are hampered by factors such as genetic variability and sample availability. Here, the authors generate a leukemia mouse model by lentiviral transduction of normal human cord blood and show an oncogenic role of HOXB genes.

Chordomas are neoplasms derived from notochord cells that typically form in the spine or skull base, and affect both adults and children. Poorly differentiated chordomas, associated with particularly poor outcomes, occur predominantly in children and are characterized by expression of the transcription factor brachyury and loss of INI1/SMARCB1. The use of immune checkpoint inhibitors in pediatric cancer is of growing interest, with reported anti-tumour activity in pediatric Hodgkin lymphoma and gliomas with mismatch repair deficiency. However, responses to immune checkpoint inhibitors are infrequent and unpredictable in pediatric solid tumours, and the molecular markers that can distinguish the seemingly indiscriminate response remain to be defined. Understanding which pediatric patient populations may benefit from immune checkpoint inhibitor therapies is essential. Here we describe the molecular profiles of two pediatric poorly differentiated chordomas using whole-genome, transcriptome and whole-genome bisulfite sequencing as part of the Personalized Oncogenomics program at BC Cancer (NCT02155621) that studies the impact of embedding comprehensive genomic profiling into the clinical care of advanced cancer patients. Genomic profiling and multiplex IHC revealed a high level of CD8+ T cells in both chordoma samples, despite low mutation burden. DNA methylation-based clustering revealed similarities with SMARCB1-deficient rhabdoid tumour subtypes that are have been characterized by increased levels of immune cell infiltration. A dominant tumour-associated T cell receptor clone was identified in one patient sample, which was demonstrated to have affinity for reconstituted brachyury-MHC complexes, indicating a potential anti-tumour immune response directed against brachyury-derived antigens. As these collective observations pointed to a potential benefit of immune targeted therapy, the patient was treated with nivolumab and subsequently achieved a partial radiographic response by RANO criteria. These observations provide support for the benefit of immune checkpoint inhibitors in poorly differentiated chordomas with high levels of infiltrating CD8+ T cells. Citation Format: Laura Williamson, Craig Rive, Daniela Di Francesco, Emma Titmuss, Elizabeth Chun, Scott Brown, Katy Milne, Erin Pleasance, Anna F. Lee, Stephen Yip, David Dix, Daniel Renouf, Robert Holt, Brad H. Nelson, Martin Hirst, Steven Jones, Shahrad Rassekh, Rebecca Deyell, Janessa Laskin, Macro A. Marra. Response to nivolumab in a pediatric chordoma with overexpression of brachyury [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 630.

Dramatic and durable responses to immune checkpoint inhibitors (ICIs) have been observed across multiple tumor types, but identifying the patients most likely to respond to these drugs remains challenging, particularly in the context of metastatic and pre-treated disease. Recent clinically approved biomarkers for patient selection are tumor agnostic, but currently all approved markers are evaluated independently. Through the Personalized Onco Genomics (POG) program at BC Cancer, we aimed to study the impact of evaluating multiple biomarkers in a tumor agnostic cohort. We performed whole genome and transcriptome analysis (WGTA) on fresh tumor biopsies from a heterogeneous pan-cancer cohort of 82 patients with advanced metastatic disease subsequently treated with ICIs. Established biomarkers, including tumor mutation burden (TMB) and CD8+ T cell scores, were able to distinguish responders in our advanced and pre-treated cohort. Additionally, we discovered that combining multiple biomarkers provided the best stratification of patients, suggesting a multifaceted approach, such as WGTA, may be suitable for more accurate identification of patients that may benefit from ICIs. As such, we have initiated a Phase II clinical trial, CAPTIV-8 (NCT04273061), which is distinctive in its use of WGTA to evaluate multiple markers including TMB, CD8+ T cell scores, an M1-M2 macrophage score and viral integration to select patients most likely to respond to atezolizumab. Clinical and genomic data prospectively collected from two hundred patients will be evaluated to test the efficacy of combining these biomarkers and identify additional biomarkers of response which can be used to guide treatment with ICIs. Citation Format: Emma Titmuss, Alexandra Pender, Erin Pleasance, Scott Brown, Cameron J. Grisdale, James Topham, Yaoqing Shen, Melika Bonakdar, Gregory A. Taylor, Laura Williamson, Karen Mungall, Eric Chuah, Andrew J. Mungall, Richard A. Moore, Jean-Michel Lavoie, Stephen Yip, Howard Lim, Daniel J. Renouf, Sophie Sun, Steven J. Jones, Robert Holt, Marco A. Marra, Janessa Laskin. CAPTIV-8: A prospective trial of atezolizumab using a multivariate model incorporating whole genome and transcriptome analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1647.

Motivation In T-cell lymphoma, malignant T cells arising from a founding clone share an identical T cell receptor (TCR) and can be identified by the over-representation of this TCR relative to TCRs from the patient’s repertoire of normal T cells. Here, we demonstrate that TCR information extracted from RNA-seq data can provide a higher resolution view of peripheral T cell lymphomas (PTCLs) than that provided by conventional methods. Results For 60 subjects with PTCL, flow cytometry/FACS was used to identify and sort aberrant T cell populations from diagnostic lymph node cell suspensions. For samples that did not appear to contain aberrant T cell populations, T helper (TH), T follicular helper (TFH) and cytotoxic T lymphocyte (CTL) subsets were sorted. RNA-seq was performed on sorted T cell populations, and TCR alpha and beta chain sequences were extracted and quantified directly from the RNA-seq data. 96% of the immunophenotypically aberrant samples had a dominant T cell clone readily identifiable by RNA-seq. Of the samples where no aberrant population was found by flow cytometry, 80% had a dominant clone by RNA-seq. This demonstrates the increased sensitivity and diagnostic ability of RNA-seq over flow cytometry and shows that the presence of a normal immunophenotype does not exclude clonality. Availability and Implementation R scripts used in the processing of the data are available online at https://www.github.com/scottdbrown/RNAseq-TcellClonality Supplementary information Supplementary data are available at Bioinformatics online.

Item does not contain fulltext Functional neuroimaging data indicate the dorsal striatum is engaged when people are required to vary the cautiousness of their decisions, by emphasizing the speed or accuracy of responding in laboratory-based decision tasks. However, the functional contribution of the striatum to decision making is unknown. In the current study we tested patients with focal ischemic lesions of the dorsal striatum and matched non-lesion control participants on a speed-accuracy tradeoff (SAT) task. Analysis using a computational model of response selection in a competitive and time-pressured context indicated that the decisions of patients with striatal lesions were less cautious than those of matched controls. This deficit was most prominent when the accuracy of decisions was emphasized. The results are consistent with the hypothesis that the striatum plays an important role in strategically setting response caution, an essential function for flexible behavior.

Organisms making repeated simple decisions are faced with a tradeoff between urgent and cautious strategies. While animals can adopt a statistically optimal policy for this tradeoff, findings about human decision-makers have been mixed. Some studies have shown that people can optimize this "speed-accuracy tradeoff", while others have identified a systematic bias towards excessive caution. These issues have driven theoretical development and spurred debate about the nature of human decision-making. We investigated a potential resolution to the debate, based on two factors that routinely differ between human and animal studies of decision-making: the effects of practice, and of longer-term feedback. Our study replicated the finding that most people, by default, are overly cautious. When given both practice and detailed feedback, people moved rapidly towards the optimal policy, with many participants reaching optimality with less than 1 h of practice. Our findings have theoretical implications for cognitive and neural models of simple decision-making, as well as methodological implications.

Strength imbalances between the hamstrings and quadriceps are an essential predictor for hamstring strain in soccer. The study aimed to investigate and compare the muscle strength imbalances of professional soccer players of different performance levels. One hundred and fifty nine senior male professional soccer players from first (n = 75) and second league (n = 84) Portuguese clubs participated in this study. Muscle strength was evaluated with a REV9000 isokinetic dynamometer. Maximal peak torque data were used to calculate quadriceps and hamstrings strength during concentric and eccentric actions, bilateral asymmetry, conventional strength ratios and dynamic control ratios. Second league athletes produced slightly lower conventional strength ratios in the right and left legs (ES = 0.22, p = 0.17 and ES = 0.36, p = 0.023, respectively) compared to the first league athletes. No significant differences were found in dynamic control ratios or in bilateral asymmetry among first and second league athletes. These findings do not show a clear link between the competitive level and injury risk in soccer players. However, some of the differences found, particularly in conventional strength ratios, highlight the importance of performing off-season and pre-season strength assessments to prescribe and adjust individual strength training programs among professional soccer players.

Theory development in both psychology and neuroscience can benefit by consideration of both behavioral and neural data sets. However, the development of appropriate methods for linking these data sets is a difficult statistical and conceptual problem. Over the past decades, different linking approaches have been employed in the study of perceptual decision-making, beginning with rudimentary linking of the data sets at a qualitative, structural level, culminating in sophisticated statistical approaches with quantitative links. We outline a new approach, in which a single model is developed that jointly addresses neural and behavioral data. This approach allows for specification and testing of quantitative links between neural and behavioral aspects of the model. Estimating the model in a Bayesian framework allows both data sets to equally inform the estimation of all model parameters. The use of a hierarchical model architecture allows for a model, which accounts for and measures the variability between neurons. We demonstrate the approach by re-analysis of a classic data set containing behavioral recordings of decision-making with accompanying single-cell neural recordings. The joint model is able to capture most aspects of both data sets, and also supports the analysis of interesting questions about prediction, including predicting the times at which responses are made, and the corresponding neural firing rates.

Markov Chain Monte–Carlo (MCMC) is an increasingly popular method for obtaining information about distributions, especially for estimating posterior distributions in Bayesian inference. This article provides a very basic introduction to MCMC sampling. It describes what MCMC is, and what it can be used for, with simple illustrative examples. Highlighted are some of the benefits and limitations of MCMC sampling, as well as different approaches to circumventing the limitations most likely to trouble cognitive scientists.

The Linear Ballistic Accumulator (Brown & Heathcote, 2008) model is used as a measurement tool to answer questions about applied psychology. The analyses based on this model depend upon the model selected and its estimated parameters. Modern approaches use hierarchical Bayesian models and Markov chain Monte-Carlo (MCMC) methods to estimate the posterior distribution of the parameters. Although there are several approaches available for model selection, they are all based on the posterior samples produced via MCMC, which means that the model selection inference inherits the properties of the MCMC sampler. To improve on current approaches to LBA inference we propose two methods that are based on recent advances in particle MCMC methodology; they are qualitatively different from existing approaches as well as from each other. The first approach is particle Metropolis-within-Gibbs; the second approach is density tempered sequential Monte Carlo. Both new approaches provide very efficient sampling and can be applied to estimate the marginal likelihood, which provides Bayes factors for model selection. The first approach is usually faster. The second approach provides a direct estimate of the marginal likelihood, uses the first approach in its Markov move step and is very efficient to parallelize on high performance computers. The new methods are illustrated by applying them to simulated and real data, and through pseudo code. The code implementing the methods is freely available., 35 pages, 6 figures, 7 tables

The self-immunopeptidome is the repertoire of all self-peptides that can be presented by the combination of MHC variants carried by an individual, defined by their HLA genotype. Each MHC variant presents a distinct set of self-peptides, and the number of peptides in a set is variable. Subjects carrying MHC variants that present fewer self-peptides should also present fewer mutated peptides, resulting in decreased immune pressure on tumor cells. To explore this, we predicted peptide-MHC binding values using all unique 8-11mer human peptides in the human proteome and all available HLA class I allelic variants, for a total of 134 billion unique peptide--MHC binding predictions. From these predictions, we observe that most peptides are able to be presented by relatively few (< 250) MHC, while some can be presented by upwards of 1,500 different MHC. There is substantial overlap among the repertoires of peptides presented by different MHC and no relationship between the number of peptides presented and HLA population frequency. Nearly 30% of self-peptides are presentable by at least one MHC, leaving 70% of the human peptidome unsurveyed by T cells. We observed similar distributions of predicted self-immunopeptidome sizes in cancer subjects compared to controls, and within the pan-cancer population, predicted self-immunopeptidome size combined with mutational load to predict survival. Self-immunopeptidome analysis revealed evidence for tumor immunoediting and identified specific peptide positions that most influence immunogenicity. Because self-immunopeptidome size is defined by HLA genotypes and approximates neoantigen load, HLA genotyping could offer a rapid predictive biomarker for response to immunotherapy.

Neuroscientific theories of attention-deficit/hyperactivity disorder (ADHD) alternately posit that cognitive aberrations in the disorder are due to acute attentional lapses, slowed neural processing, or reduced signal-to-noise ratios. However, they make similar predictions about behavioral summary statistics (response times [RTs] and accuracy), hindering the field's ability to produce strong and specific tests of these theories. The current study uses the linear ballistic accumulator (LBA; BrownHeathcote, 2008), a mathematical model of choice RT tasks, to distinguish between competing theory predictions. Children with ADHD (n = 80) and age-matched controls (n = 32) completed a numerosity discrimination paradigm at 2 levels of difficulty, and RT data were fit to the LBA model to test theoretical predictions. Individuals with ADHD displayed slowed processing of evidence for correct responses (signal) relative to their peers but comparable processing of evidence for error responses (noise) and between-trial variability in processing (performance lapses). The findings are inconsistent with accounts that posit an increased incidence of attentional lapses in the disorder and provide partial support for those that posit slowed neural processing and lower signal-to-noise ratios. Results also highlight the utility of well-developed cognitive models for distinguishing between the predictions of etiological theories of psychopathology. (PsycINFO Database Record

How does the process of information transmission affect the cultural or linguistic products that emerge? This question is often studied experimentally and computationally via iterated learning: a procedure in which participants learn from previous participants in a chain. Iterated learning is a powerful tool because, when all participants share the same priors, the stationary distributions of the iterated learning chains reveal those priors. In many situations, however, it is unreasonable to assume that all participants share the same prior beliefs. We present four simulation studies and one experiment demonstrating that when the population of learners is heterogeneous, the behavior of an iterated learning chain can be unpredictable, and is often systematically distorted by the learners with the most extreme biases. This results in group-level outcomes that reflect neither the behavior of any individuals within the population nor the overall population average. We discuss implications for the use of iterated learning as a methodological tool as well as for the processes that might have shaped cultural and linguistic evolution in the real world.

Evidence accumulation models of decision-making have led to advances in several different areas of psychology. These models provide a way to integrate response time and accuracy data, and to describe performance in terms of latent cognitive processes. Testing important psychological hypotheses using cognitive models requires a method to make inferences about different versions of the models which assume different parameters to cause observed effects. The task of model-based inference using noisy data is difficult, and has proven especially problematic with current model selection methods based on parameter estimation. We provide a method for computing Bayes factors through Monte-Carlo integration for the linear ballistic accumulator (LBA; Brown and Heathcote, 2008), a widely used evidence accumulation model. Bayes factors are used frequently for inference with simpler statistical models, and they do not require parameter estimation. In order to overcome the computational burden of estimating Bayes factors via brute force integration, we exploit general purpose graphical processing units; we provide free code for this. This approach allows estimation of Bayes factors via Monte-Carlo integration within a practical time frame. We demonstrate the method using both simulated and real data. We investigate the stability of the Monte-Carlo approximation, and the LBA's inferential properties, in simulation studies.

We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes—wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant—characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field. Thorsson et al. present immunogenomics analyses of more than 10,000 tumors, identifying six immune subtypes that encompass multiple cancer types and are hypothesized to define immune response patterns impacting prognosis. This work provides a resource for understanding tumor-immune interactions, with implications for identifying ways to advance research on immunotherapy., 0, info:eu-repo/semantics/published

Trueblood, Brown, and Heathcote (2014) developed a new model, called the multiattribute linear ballistic accumulator (MLBA), to explain contextual preference reversals in multialternative choice. MLBA was shown to provide good accounts of human behavior through both qualitative analyses and quantitative fitting of choice data. Tsetsos, Chater, and Usher (2015) investigated the ability of MLBA to simultaneously capture 3 prominent context effects (attraction, compromise, and similarity). They concluded that MLBA must set a "fine balance" of competing forces to account for all 3 effects simultaneously and that its predictions are sensitive to the position of the stimuli in the attribute space. Through a new experiment, we show that the 3 effects are very fragile and that only a small subset of people shows all 3 simultaneously. Thus, the predictions that Tsetsos et al. generated from the MLBA model turn out to match closely real data in a new experiment. Support for these predictions provides strong evidence for the MLBA. A corollary is that a model that can "robustly" capture all 3 effects simultaneously is not necessarily a good model. Rather, a good model captures patterns found in human data, but cannot accommodate patterns that are not found.