Computational purification of individual tumor gene expression profiles leads to significant improvements in prognostic prediction.

Tumor heterogeneity is a limiting factor in cancer treatment and in the discovery of biomarkers to personalize it. We describe a computational purification tool, ISOpure, to directly address the effects of variable normal tissue contamination in clinical tumor specimens. ISOpure uses a set of tumor expression profiles and a panel of healthy tissue expression profiles to generate a purified cancer profile for each tumor sample and an estimate of the proportion of RNA originating from cancerous cells. Applying ISOpure before identifying gene signatures leads to significant improvements in the prediction of prognosis and other clinical variables in lung and prostate cancer

Large-scale mass distribution in the Illustris simulation

Observations at low redshifts thus far fail to account for all of the baryons expected in the Universe according to cosmological constraints. A large fraction of the baryons presumably resides in a thin and warm-hot medium between the galaxies, where they are difficult to observe due to their low densities and high temperatures. Cosmological simulations of structure formation can be used to verify this picture and provide quantitative predictions for the distribution of mass in different large-scale structure components. Here we study the distribution of baryons and dark matter at different epochs using data from the Illustris simulation. We identify regions of different dark matter density with the primary constituents of large-scale structure, allowing us to measure mass and volume of haloes, filaments and voids. At redshift zero, we find that 49 % of the dark matter and 23 % of the baryons are within haloes more massive than the resolution limit of $2\times 10^8$ M$_\odot$. The filaments of the cosmic web host a further 45 % of the dark matter and 46 % of the baryons. The remaining 31 % of the baryons reside in voids. The majority of these baryons have been transported there through active galactic nuclei feedback. We note that the feedback model of Illustris is too strong for heavy haloes, therefore it is likely that we are overestimating this amount. Categorizing the baryons according to their density and temperature, we find that 17.8 % of them are in a condensed state, 21.6 % are present as cold, diffuse gas, and 53.9 % are found in the state of a warm-hot intergalactic medium.Comment: 12 pages, 15 figure

Machine Learning models for detection and assessment of progression in Alzheimer's disease based on blood and cerebrospinal fluid biomarkers

Machine-learning techniques were applied to human blood plasma and cerebrospinal fluid (CSF) biomarker data related to cognitive decline in Alzheimer’s Disease (AD) patients available via Alzheimer Disease Neuroimaging Initiative (ADNI) study. We observed the accuracy of AD diagnosis is greatest when protein biomarkers from cerebrospinal fluid are combined with plasma proteins using Support Vector Machines (SVM); this is not improved by adding age and sex. The area under the receiver operator characteristic (ROC) curve for our model of AD diagnosis based on a full (unbiased) set of plasma proteins was 0.94 in cross-validation and 0.82 on an external validation (test) set. Taking plasma in combination with CSF, the model reaches 0.98 area under the ROC curve on the test set. Accuracy of prediction of risk of mild cognitive impairment progressing to AD is the same for blood plasma biomarkers as for CSF and is not improved by combining them or adding age and sex as covariates.Clinical relevance— The identification of accurate and cost-effective biomarkers to screen for risk of developing AD and monitoring its progression is crucial for improved understanding of its causes and stratification of patients for treatments under development. This paper demonstrates the feasibility of AD detection and prognosis based on blood plasma biomarkers.<br/

Design fiction:does the search for plausibility lead to deception?

Since its inception the term ‘design fiction’ has generated considerable interest as a future-focused method of research through design whose aim is to suspend disbelief about change by depicting prototypes inside diegeses, or ‘story worlds’. Plausibility is one of the key qualities often associated with suspension of disbelief, a quality encoded within the artefacts created as design fictions. In this paper we consider whether by crafting this plausibility, works of design fiction are inherently, or can become, deceptive. The notion of deception is potentially problematic for academic researchers who are bound by the research code of ethics at their particular institution and thus it is important to understand how plausibility and deception interact so as to understand any problems associated with using design fiction as a research method. We consider the plausibility of design fictions, looking at examples that are (1) obviously design fiction, (2) identified as design fiction, and (3) whose status is either ambiguous or concealed. We then explore the challenges involved in crafting plausibility by describing our experience of world- building for a design fiction that explores the notion of empathic communications in a digital world. Our conclusions indicate that the form a design fiction takes, and pre- existing familiarity with that form, is a key determinant for whether an audience mistake it for reality and are deceived. Furthermore we suggest that designers may become minded to deliberately employ deceitful strategies in order help their design fiction reach a larger audience

A Mathematical Theory for Studying and Controlling the Disinformation System Dynamics

This study explores the connection between disinformation, defined as deliberate spread of false information, and rate-induced tipping (R-tipping), a phenomenon where systems undergo sudden changes due to rapid shifts in ex-ternal forces. While traditionally, tipping points were associated with exceeding critical thresholds, R-tipping highlights the influence of the rate of change, even without crossing specific levels. The study argues that disinformation campaigns, often organized and fast-paced, can trigger R-tipping events in public opinion and societal behavior. This can happen even if the disinformation itself doesn't reach a critical mass, making it challenging to predict and control. Here, by Transforming a population dynamics model into a network model, Investigating the interplay between the source of disinformation, the exposed population, and the medium of transmission under the influence of external sources, the study aims to provide valuable insights for predicting and controlling the spread of disinformation. This mathematical approach holds promise for developing effective countermeasures against this increasingly prevalent threat to public discourse and decision-making.Comment: 8 Pages, 6 Figures, Accepted Paper, Proceedings of the ICMAAM-2023, Part of the Book Series: Springer Proceedings in Mathemat-ics & Statistic

Research Through Board Game Design

This research presents the design of a board game that explores issues related to privacy, ethics, trust, risk, acceptability, and security within the Internet of Things (IoT). In particular, it aims to assist players in developing mental models of the increasing hybrid digital/physical spaces they inhabit in which notions of public and private are increasingly blurred. The game is based on an Heterotopical Model for Inter-Spatial Interaction, inspired by Michel Foucault’s essay “Of Other Spaces”, which can act as a lens for designing IoT products and services. In the game players: explore the spatial division between physical and virtual; and are rather exposed to its procedural rhetoric which highlights how notions of public and private are in constant flux and must be constantly renegotiated as they add or make connections with any new IoT devices they encounter. As the meaning of any game only emerges through play, it was developed through iterative play-testing in which player experience was evaluated against the intended rhetoric. This led to a number of fundamental re-designs and proved useful for evaluating the model itself. This discussion highlights that while game design research somewhat sits apart from more general design research it aligns closely with research through design

Using Heterotopias to Characterise Interactions in Physical/Digital Spaces

This paper addresses the complexity of designing interactions in hybrid digital/physical spaces, in which notions of public and private are becoming increasingly blurred, by using a philosophical lens to characterise such spaces. In particular it references the ideas presented by Michel Foucault in his essay “Of Other Spaces”. It proposes the presence of a spatial division within physical and virtual, in terms of private and public, and juxtaposes them through a Heterotopical Model for Inter-Spatial Interaction through which designers can examine the coexistence of physical and digital interactions. The purpose of modelling this juxtaposition is to help designers understand the nature of connections that happen between physical and digital objects in these spaces and consider how meaningful interactions can respond to this complexity

Crohn’s Disease and Treatment in a Predominantly African American General GI Clinic

Given the high percentage of African Americans (AA) in our GI clinics and the paucity of AA focused studies on Crohn’s Disease (CD), we assessed racial disparity of the disease and its treatment in our predominately AA patient population. Patient records were examined to determine the accuracy of the CD diagnosis and to obtain relevant information for characterizing patients’ characteristics and treatments. In addition to race, patients were also categorized by GI visits to distinguish between patients under long term care (three or more visits) and those being seen to establish care (one or two visits). The 146 CD patients were 55% male, 71% AA, and the average age at diagnosis was 28 years. Patients with 3 or more visits were not significantly different with respect to therapy as compared to patients with only 1 or 2 visits to GI. AA patients with multiple visits had higher C-Reactive Protein (CRP) early in their disease as compared to non-AA patients (40.7 ng/ml vs 18.8 ng/ml). Although Non-AA patients were more likely to be on combination therapy, the difference was not statistically significant (single therapy (AA 61% vs non-AA 56%); combination therapy (AA 29% vs non-AA 37%)). When improvement of CRP was used as the objective criteria of therapeutic efficacy of the current therapy, both AA and Non-AA patients improved in individual CRP, but only the AA improvement was statistically significant