Utility of the JAX Clinical Knowledgebase in capture and assessment of complex genomic cancer data.

Cancer genomic data is continually growing in complexity, necessitating improved methods for data capture and analysis. Tumors often contain multiple therapeutically relevant alterations, and co-occurring alterations may have a different influence on therapeutic response compared to if those alterations were present alone. One clinically important example of this is the existence of a resistance conferring alteration in combination with a therapeutic sensitizing mutation. The JAX Clinical Knowledgebase (JAX-CKB) (https://ckb.jax.org/) has incorporated the concept of the complex molecular profile, which enables association of therapeutic efficacy data with multiple genomic alterations simultaneously. This provides a mechanism for rapid and accurate assessment of complex cancer-related data, potentially aiding in streamlined clinical decision making. Using the JAX-CKB, we demonstrate the utility of associating data with complex profiles comprising ALK fusions with another variant, which have differing impacts on sensitivity to various ALK inhibitors depending on context

Coordination Implications of Software Coupling in Open Source Projects

The effect of software coupling on the quality of software has been studied quite widely since the seminal paper on software modularity by Parnas [1]. However, the effect of the increase in software coupling on the coordination of the developers has not been researched as much. In commercial software development environments there normally are coordination mechanisms in place to manage the coordination requirements due to software dependencies. But, in the case of Open Source software such coordination mechanisms are harder to implement, as the developers tend to rely solely on electronic means of communication. Hence, an understanding of the changing coordination requirements is essential to the management of an Open Source project. In this paper we study the effect of changes in software coupling on the coordination requirements in a case study of a popular Open Source project called JBoss

Sequential design of computer experiments for the estimation of a probability of failure

This paper deals with the problem of estimating the volume of the excursion set of a function $f:\mathbb{R}^d \to \mathbb{R}$ above a given threshold, under a probability measure on $\mathbb{R}^d$ that is assumed to be known. In the industrial world, this corresponds to the problem of estimating a probability of failure of a system. When only an expensive-to-simulate model of the system is available, the budget for simulations is usually severely limited and therefore classical Monte Carlo methods ought to be avoided. One of the main contributions of this article is to derive SUR (stepwise uncertainty reduction) strategies from a Bayesian-theoretic formulation of the problem of estimating a probability of failure. These sequential strategies use a Gaussian process model of $f$ and aim at performing evaluations of $f$ as efficiently as possible to infer the value of the probability of failure. We compare these strategies to other strategies also based on a Gaussian process model for estimating a probability of failure.Comment: This is an author-generated postprint version. The published version is available at http://www.springerlink.co

Robots that can adapt like animals

As robots leave the controlled environments of factories to autonomously function in more complex, natural environments, they will have to respond to the inevitable fact that they will become damaged. However, while animals can quickly adapt to a wide variety of injuries, current robots cannot "think outside the box" to find a compensatory behavior when damaged: they are limited to their pre-specified self-sensing abilities, can diagnose only anticipated failure modes, and require a pre-programmed contingency plan for every type of potential damage, an impracticality for complex robots. Here we introduce an intelligent trial and error algorithm that allows robots to adapt to damage in less than two minutes, without requiring self-diagnosis or pre-specified contingency plans. Before deployment, a robot exploits a novel algorithm to create a detailed map of the space of high-performing behaviors: This map represents the robot's intuitions about what behaviors it can perform and their value. If the robot is damaged, it uses these intuitions to guide a trial-and-error learning algorithm that conducts intelligent experiments to rapidly discover a compensatory behavior that works in spite of the damage. Experiments reveal successful adaptations for a legged robot injured in five different ways, including damaged, broken, and missing legs, and for a robotic arm with joints broken in 14 different ways. This new technique will enable more robust, effective, autonomous robots, and suggests principles that animals may use to adapt to injury

Cisplatin-resistant triple-negative breast cancer subtypes: multiple mechanisms of resistance.

BACKGROUND: Understanding mechanisms underlying specific chemotherapeutic responses in subtypes of cancer may improve identification of treatment strategies most likely to benefit particular patients. For example, triple-negative breast cancer (TNBC) patients have variable response to the chemotherapeutic agent cisplatin. Understanding the basis of treatment response in cancer subtypes will lead to more informed decisions about selection of treatment strategies. METHODS: In this study we used an integrative functional genomics approach to investigate the molecular mechanisms underlying known cisplatin-response differences among subtypes of TNBC. To identify changes in gene expression that could explain mechanisms of resistance, we examined 102 evolutionarily conserved cisplatin-associated genes, evaluating their differential expression in the cisplatin-sensitive, basal-like 1 (BL1) and basal-like 2 (BL2) subtypes, and the two cisplatin-resistant, luminal androgen receptor (LAR) and mesenchymal (M) subtypes of TNBC. RESULTS: We found 20 genes that were differentially expressed in at least one subtype. Fifteen of the 20 genes are associated with cell death and are distributed among all TNBC subtypes. The less cisplatin-responsive LAR and M TNBC subtypes show different regulation of 13 genes compared to the more sensitive BL1 and BL2 subtypes. These 13 genes identify a variety of cisplatin-resistance mechanisms including increased transport and detoxification of cisplatin, and mis-regulation of the epithelial to mesenchymal transition. CONCLUSIONS: We identified gene signatures in resistant TNBC subtypes indicative of mechanisms of cisplatin. Our results indicate that response to cisplatin in TNBC has a complex foundation based on impact of treatment on distinct cellular pathways. We find that examination of expression data in the context of heterogeneous data such as drug-gene interactions leads to a better understanding of mechanisms at work in cancer therapy response

An Empirical Study of Goto in C Code from GitHub Repositories

ABSTRACT It is nearly 50 years since Dijkstra argued that goto obscures the flow of control in program execution and urged programmers to abandon the goto statement. While past research has shown that goto is still in use, little is known about whether goto is used in the unrestricted manner that Dijkstra feared, and if it is 'harmful' enough to be a part of a post-release bug. We, therefore, conduct a two part empirical study -(1) qualitatively analyze a statistically representative sample of 384 files from a population of almost 250K C programming language files collected from over 11K GitHub repositories and find that developers use goto in C files for error handling (80.21±5%) and cleaning up resources at the end of a procedure (40.36 ± 5%); an

The Secret to Successful User Communities: An Analysis of Computer Associates’ User Groups

This paper provides the first large scale study that examines the impact of both individual- and group-specific factors on the benefits users obtain from their user communities. By empirically analysing 924 survey responses from individuals in 161 Computer Associates' user groups, this paper aims to identify the determinants of successful user communities. To measure success, the amount of time individual members save through having access to their user networks is used. As firms can significantly profit from successful user communities, this study proposes four key implications of the empirical results for the management of user communities

A Classification of Hyper-heuristic Approaches

The current state of the art in hyper-heuristic research comprises a set of approaches that share the common goal of automating the design and adaptation of heuristic methods to solve hard computational search problems. The main goal is to produce more generally applicable search methodologies. In this chapter we present and overview of previous categorisations of hyper-heuristics and provide a unified classification and definition which captures the work that is being undertaken in this field. We distinguish between two main hyper-heuristic categories: heuristic selection and heuristic generation. Some representative examples of each category are discussed in detail. Our goal is to both clarify the main features of existing techniques and to suggest new directions for hyper-heuristic research

PD-1 Dynamically Regulates Inflammation and Development of Brain-Resident Memory CD8 T Cells During Persistent Viral Encephalitis

Programmed cell death-1 (PD-1) receptor signaling dampens the functionality of T cells faced with repetitive antigenic stimulation from chronic infections or tumors. Using intracerebral (i.c.) inoculation with mouse polyomavirus (MuPyV), we have shown that CD8 T cells establish a PD-1hi, tissue-resident memory population in the brains (bTRM) of mice with a low-level persistent infection. In MuPyV encephalitis, PD-L1 was expressed on infiltrating myeloid cells, microglia and astrocytes, but not on oligodendrocytes. Engagement of PD-1 on anti-MuPyV CD8 T cells limited their effector activity. NanoString gene expression analysis showed that neuroinflammation was higher in PD-L1−/− than wild type mice at day 8 post-infection, the peak of the MuPyV-specific CD8 response. During the persistent phase of infection, however, the absence of PD-1 signaling was found to be associated with a lower inflammatory response than in wild type mice. Genetic disruption and intracerebroventricular blockade of PD-1 signaling resulted in an increase in number of MuPyV-specific CD8 bTRM and the fraction of these cells expressing CD103, the αE integrin commonly used to define tissue-resident T cells. However, PD-L1−/− mice persistently infected with MuPyV showed impaired virus control upon i.c. re-infection with MuPyV. Collectively, these data reveal a temporal duality in PD-1-mediated regulation of MuPyV-associated neuroinflammation. PD-1 signaling limited the severity of neuroinflammation during acute infection but sustained a level of inflammation during persistent infection for maintaining control of virus re-infection