Loss and gain of bone in spondyloarthritis: what drives these opposing clinical features?

The breadth of bone lesion types seen in spondyloarthritis is unprecedented in medicine and includes increased bone turnover, bone loss and fragility, osteitis, osteolysis and erosion, osteosclerosis, osteoproliferation of soft tissues adjacent to bone and spinal skeletal structure weakness. Remarkably, these effects can be present simultaneously in the same patient. The search for a potential unifying cause of effects on the skeleton necessarily focuses on inflammation arising from the dysregulation of immune response to microorganisms, particularly dysregulation of TH17 lymphocytes, and the dysbiosis of established gut and other microbiota. The compelling notion that a common antecedent pathological mechanism affects existing bone and tissues with bone-forming potential (entheses), simultaneously with variable effect in the former but bone-forming in the latter, drives basic research forward and focuses our awareness on the effects on these bone mechanisms of the increasing portfolio of targeted immunotherapies used in the clinic

A rapid and scalable method for selecting recombinant mouse monoclonal antibodies

<p>Abstract</p> <p>Background</p> <p>Monoclonal antibodies with high affinity and selectivity that work on wholemount fixed tissues are valuable reagents to the cell and developmental biologist, and yet isolating them remains a long and unpredictable process. Here we report a rapid and scalable method to select and express recombinant mouse monoclonal antibodies that are essentially equivalent to those secreted by parental IgG-isotype hybridomas.</p> <p>Results</p> <p>Increased throughput was achieved by immunizing mice with pools of antigens and cloning - from small numbers of hybridoma cells - the functionally rearranged light and heavy chains into a single expression plasmid. By immunizing with the ectodomains of zebrafish cell surface receptor proteins expressed in mammalian cells and screening for formalin-resistant epitopes, we selected antibodies that gave expected staining patterns on wholemount fixed zebrafish embryos.</p> <p>Conclusions</p> <p>This method can be used to quickly select several high quality monoclonal antibodies from a single immunized mouse and facilitates their distribution using plasmids.</p

A Brief Wellbeing Training Session Delivered by a Humanoid Social Robot: A Pilot Randomized Controlled Trial

Mental health and psychological distress are rising in adults, showing the importance of wellbeing promotion, support, and technique practice that is effective and accessible. Interactive social robots have been tested to deliver health programs but have not been explored to deliver wellbeing technique training in detail. A pilot randomised controlled trial was conducted to explore the feasibility of an autonomous humanoid social robot to deliver a brief mindful breathing technique to promote information around wellbeing. It contained two conditions: brief technique training (Technique) and control designed to represent a simple wait-list activity to represent a relationship-building discussion (Simple Rapport). This trial also explored willingness to discuss health-related topics with a robot. Recruitment uptake rate through convenience sampling was high (53%). A total of 230 participants took part (mean age = 29 years) with 71% being higher education students. There were moderate ratings of technique enjoyment, perceived usefulness, and likelihood to repeat the technique again. Interaction effects were found across measures with scores varying across gender and distress levels. Males with high distress and females with low distress who received the simple rapport activity reported greater comfort to discuss non-health topics than males with low distress and females with high distress. This trial marks a notable step towards the design and deployment of an autonomous wellbeing intervention to investigate the impact of a brief robot-delivered mindfulness training program for a sub-clinical population

Generalized Additive Models for Gigadata:Modeling the U.K. Black Smoke Network Daily Data

<p>We develop scalable methods for fitting penalized regression spline based generalized additive models with of the order of 10⁴ coefficients to up to 10⁸ data. Computational feasibility rests on: (i) a new iteration scheme for estimation of model coefficients and smoothing parameters, avoiding poorly scaling matrix operations; (ii) parallelization of the iteration’s pivoted block Cholesky and basic matrix operations; (iii) the marginal discretization of model covariates to reduce memory footprint, with efficient scalable methods for computing required crossproducts directly from the discrete representation. Marginal discretization enables much finer discretization than joint discretization would permit. We were motivated by the need to model four decades worth of daily particulate data from the U.K. Black Smoke and Sulphur Dioxide Monitoring Network. Although reduced in size recently, over 2000 stations have at some time been part of the network, resulting in some 10 million measurements. Modeling at a daily scale is desirable for accurate trend estimation and mapping, and to provide daily exposure estimates for epidemiological cohort studies. Because of the dataset size, previous work has focused on modeling time or space averaged pollution levels, but this is unsatisfactory from a health perspective, since it is often acute exposure locally and on the time scale of days that is of most importance in driving adverse health outcomes. If computed by conventional means our black smoke model would require a half terabyte of storage just for the model matrix, whereas we are able to compute with it on a desktop workstation. The best previously available reduced memory footprint method would have required three orders of magnitude more computing time than our new method. Supplementary materials for this article are available online.</p

An overview of decentralized autonomous organizations on the blockchain

Blockchain technology has emerged as a new paradigm to build decentralized systems which do not require a central authority. It is most popular for enabling Bitcoin and other crypto-currencies. However, blockchain applications span beyond Finance, and recently it has been applied to decentralized governance. Blockchainenabled "Decentralized Autonomous Organizations" (DAOs) have emerged as a new form of collective governance, in which communities may organize themselves relying on decentralized infrastructure. In this article, we introduce the concept of DAO and review the main software platforms that offer DAO creation as a service, which simplifies the use of DAOs to non-blockchain experts; namely: Aragon, DAOstack, DAOhaus and Colony. These platforms will be compared by showing their key features. Finally, we will review the available visualisation tools for DAOs, and we will introduce our open-source tool to plot DAOs activity, DAOAnalyzer. We will illustrate its potential with the case of the DAO Genesis Alpha, which is the main DAO of the DAOstack project

Clinical research nursing pathways: The development and evaluation of a nursing research internship program using the RE-AIM framework.

In 2018 a Nursing Research Internship program was started within a major referral and tertiary teaching centre in Australia. We aimed to evaluate the first 12 months of the program using an implementation science framework. This was a qualitative study. Following ethical approval n = 20 semi-structured interviews were recorded and transcribed verbatim. Participants included nurses with clinical, research and management roles who had engaged in or supported a Nursing Research Internship program. The Framework Method was conducted to analyse the findings. Key themes identified included 'What is the impact of a Nursing Research Internship program?'; 'Why do a Nursing Research Internship program?'; 'How do we do a Nursing Research Internship program?'; 'How do we sustain a Nursing Research Internship program?'. Positive impacts were identified for clinical nurses and their teams, for the hospital and health service, and for patients and families. Identified key components included protected research time, specialist support (including library, statistics, health economist, implementation scientist), regulatory support (ethics and governance procedures) and access to a computer and IT resources. The Nursing Research Internship program required support from nurse clinicians, nurse managers and nurse academics. A structured Nursing Research Internship program supports clinical nurses to answer research questions identified directly from clinical practice

Modeling Insights into Deuterium Excess as an Indicator of Water Vapor Source Conditions

Deuterium excess (d) is interpreted in conventional paleoclimate reconstructions as a tracer of oceanic source region conditions, such as temperature, where precipitation originates. Previous studies have adopted co-isotopic approaches to estimate past changes in both site and oceanic source temperatures for ice core sites using empirical relationships derived from conceptual distillation models, particularly Mixed Cloud Isotopic Models (MCIMs). However, the relationship between d and oceanic surface conditions remains unclear in past contexts. We investigate this climate-isotope relationship for sites in Greenland and Antarctica using multiple simulations of the water isotope-enabled Goddard Institute for Space Studies (GISS) ModelE-R general circulation model and apply a novel suite of model vapor source distribution (VSD) tracers to assess d as a proxy for source temperature variability under a range of climatic conditions. Simulated average source temperatures determined by the VSDs are compared to synthetic source temperature estimates calculated using MCIM equations linking d to source region conditions. We show that although deuterium excess is generally a faithful tracer of source temperatures as estimated by the MCIM approach, large discrepancies in the isotope-climate relationship occur around Greenland during the Last Glacial Maximum simulation, when precipitation seasonality and moisture source regions were notably different from present. This identified sensitivity in d as a source temperature proxy suggests that quantitative climate reconstructions from deuterium excess should be treated with caution for some sites when boundary conditions are significantly different from the present day. Also, the exclusion of the influence of humidity and other evaporative source changes in MCIM regressions may be a limitation of quantifying source temperature fluctuations from deuterium excess in some instances

The Association between Child Maltreatment and Adult Poverty – A Systematic Review of Longitudinal Research

Child maltreatment is a global problem affecting millions of children and is associated with an array of cumulative negative outcomes later in life, including unemployment and financial difficulties. Although establishing child maltreatment as a causal mechanism for adult economic outcomes is fraught with difficulty, understanding the relationship between the two is essential to reducing such inequality. This paper presents findings from a systematic review of longitudinal research examining experiences of child maltreatment and economic outcomes in adulthood. A systematic search of seven databases found twelve eligible retrospective and prospective cohort studies. From the available evidence, there was a relatively clear relationship between ‘child maltreatment’ and poorer economic outcomes such as reduced income, unemployment, lower level of job skill and fewer assets, over and above the influence of family of origin socio-economic status. Despite an extremely limited evidence base, neglect had a consistent relationship with a number of long-term economic outcomes, while physical abuse has a more consistent relationship with income and employment. Studies examining sexual abuse found less of an association with income and employment, although they did find a relationship to other outcomes such as sickness absence, assets, welfare receipt and financial insecurity. Nonetheless, all twelve studies showed some association between at least one maltreatment type and at least one economic measure. The task for future research is to clarify the relationship between specific maltreatment types and specific economic outcomes, taking account of how this may be influenced by gender and life course stag

Clinicians' Understanding of Preferences and Values of People with Hematological Malignancies at the End of Life: Concurrent Surveys

Background: People with hematological malignancies can deteriorate rapidly to a terminal event and have variable levels of engagement when transitioning to palliative and end-of-life care. Objectives: To describe end-of-life care values and preferences of people with hematological malignancies and explore whether these align with hematology clinicians' perceptions. Design: Two matched anonymous quantitative cross-sectional surveys explored: (1) patients' values and preferences around manner and timing of discussions regarding life expectancy and prognosis, involvement in decision making, and concurrent integration of palliative care with active treatment; and (2) clinicians' perceptions of their patients' values and preferences in relation to prognostic information. Settings/Participants: Concurrent online national surveys of people with hematological malignancies known to the Leukemia Foundation of Australia, and clinicians in Australia with membership to the Hematology Society of Australia and New Zealand. Results: Five hundred nine (38% response rate) patients (median age 64 [min 20, max 89, interquartile range 56-70]) and 272 clinicians (21% response rate) responded to the survey. If their health was deteriorating, most patients wanted honest prognostic and life expectancy information (87%); welcomed involvement in decision making (94%); felt they would be comfortable talking to the treating team about the possibility of death (86%); and would be comfortable seeing someone from a specialist palliative care team (74%). Clinicians generally underestimated most of these responses. Conclusion: Although our findings indicate that most people believe they would be comfortable discussing prognosis, life expectancy, and wishes at the end of life, clinicians were largely unaware of their preferences. This highlights the need to embed values clarification in routine care for each patient and family.</p

Statistical Workflow for Feature Selection in Human Metabolomics Data.

High-throughput metabolomics investigations, when conducted in large human cohorts, represent a potentially powerful tool for elucidating the biochemical diversity underlying human health and disease. Large-scale metabolomics data sources, generated using either targeted or nontargeted platforms, are becoming more common. Appropriate statistical analysis of these complex high-dimensional data will be critical for extracting meaningful results from such large-scale human metabolomics studies. Therefore, we consider the statistical analytical approaches that have been employed in prior human metabolomics studies. Based on the lessons learned and collective experience to date in the field, we offer a step-by-step framework for pursuing statistical analyses of cohort-based human metabolomics data, with a focus on feature selection. We discuss the range of options and approaches that may be employed at each stage of data management, analysis, and interpretation and offer guidance on the analytical decisions that need to be considered over the course of implementing a data analysis workflow. Certain pervasive analytical challenges facing the field warrant ongoing focused research. Addressing these challenges, particularly those related to analyzing human metabolomics data, will allow for more standardization of as well as advances in how research in the field is practiced. In turn, such major analytical advances will lead to substantial improvements in the overall contributions of human metabolomics investigations