Putting Participants at the Centre of HIV Cure Research

Curing HIV infection moved from the aspirational to the theoretically plausible with the apparent elimination of latent HIV from Timothy Ray Brown, also known as the Berlin Patient, after receipt of a stem cell transplant from a donor homozygous for the CCR5-Δ32 gene deletion. As HIV cure-related research has expanded, much of the science has centred on biomedical outcomes, and less on the people for whom a cure is being sought. Specifically, there has been limited inquiry directed towards understanding the motivations, perceptions, desires, needs, and experiences of people living with HIV who are asked to participate in cure-related research. This relative lack of attention is troubling when considering trade-offs, risks, demands, and burdens accompanying many of these investigations, such as intensively monitored antiretroviral pauses in effective HIV therapy, large volume blood draws and leucaphereses, and dosing with experimental immunotherapies

DO LATITUDE, ELEVATION, TEMPERATURE, AND PRECIPITATION INFLUENCE BODY AND CLUTCH SIZES OF FEMALE COMMON FIVE-LINED SKINKS, PLESTIODON FASCIATUS (LINNAEUS, 1758)?

Common Five-lined Skinks (Plestiodon fasciatus) have an extensive distribution that includes much of eastern North America. We examined 490 female specimens (274 with putative clutch sizes) from throughout the range to see if latitude, elevation, mean annual temperature, and/or mean annual precipitation affected body or clutch sizes. We predicted that larger females would produce larger clutches, latitude and elevation would negatively affect both body and clutch sizes, and that temperature and precipitation would exert a positive effect. Our results did not consistently support those predictions. Body size was positively associated with latitude, negatively associated with temperature, and not associated with elevation or precipitation. Clutch size was not related to female body size, but in most instances was positively associated with temperature and precipitation but negatively associated with elevation and latitude. Effectively K-selected in the North and r-selected in the South, body and clutch sizes in this species appear to be responding to different select

Shoulder kinematics during cyclic overhead work are affected by a passive arm support exoskeleton

Purpose: We investigated the influence of passive arm-support exoskeleton (ASE) with different levels of torque (50, 75, and 100%) on upper arm osteokinematics. Methods: Twenty participants completed a cyclic overhead drilling task with and without ASE. Task duration, joint angles, and angular acceleration peaks were analyzed during ascent and descent phases of the dominant upper arm. Results: Maximum ASE torque was associated with decreased peak acceleration during ascent (32.2%; SD 17.8; p < 0.001) and descent phases (38.8%; SD 17.8; p < 0.001). Task duration remained consistent. Increased torque led to a more flexed (7.2°; SD 5.5; p > 0.001) and internally rotated arm posture (17.6°; SD 12.1; p < 0.001), with minimal changes in arm abduction. Conclusion: The small arm accelerations and changes in osteokinematics we observed, support the use of this ASE, even while performing overhead cyclic tasks with the highest level of support

Revisiting the ‘Sterilising Cure’ Terminology: A Call for More Patient-Centered Perspectives on HIV Cure-Related Research

The literature on HIV therapeutics research is rife with terminology associating ‘sterilisation’ with HIV cure. We find connotations of the word ‘sterilising’ problematic for the HIV cure research field. In this viewpoint, we review associations of sterilising with concepts of disinfection or cleansing, as well as coerced sterilisation. We discuss emerging findings from socio-behavioural research that show aversion from people living with HIV towards the ‘sterilising cure’ nomenclature. We call for more collaborations with people with HIV as partners to help define what would be a more acceptable terminology for describing an HIV cure

Fine tuned personalized machine learning models to detect insomnia risk based on data from a smart bed platform

IntroductionInsomnia causes serious adverse health effects and is estimated to affect 10–30% of the worldwide population. This study leverages personalized fine-tuned machine learning algorithms to detect insomnia risk based on questionnaire and longitudinal objective sleep data collected by a smart bed platform.MethodsUsers of the Sleep Number smart bed were invited to participate in an IRB approved study which required them to respond to four questionnaires (which included the Insomnia Severity Index; ISI) administered 6 weeks apart from each other in the period from November 2021 to March 2022. For 1,489 participants who completed at least 3 questionnaires, objective data (which includes sleep/wake and cardio-respiratory metrics) collected by the platform were queried for analysis. An incremental, passive-aggressive machine learning model was used to detect insomnia risk which was defined by the ISI exceeding a given threshold. Three ISI thresholds (8, 10, and 15) were considered. The incremental model is advantageous because it allows personalized fine-tuning by adding individual training data to a generic model.ResultsThe generic model, without personalizing, resulted in an area under the receiving-operating curve (AUC) of about 0.5 for each ISI threshold. The personalized fine-tuning with the data of just five sleep sessions from the individual for whom the model is being personalized resulted in AUCs exceeding 0.8 for all ISI thresholds. Interestingly, no further AUC enhancements resulted by adding personalized data exceeding ten sessions.DiscussionThese are encouraging results motivating further investigation into the application of personalized fine tuning machine learning to detect insomnia risk based on longitudinal sleep data and the extension of this paradigm to sleep medicine

The ChatGPT Artificial Intelligence Chatbot: How Well Does It Answer Accounting Assessment Questions?

ChatGPT, a language-learning model chatbot, has garnered considerable attention for its ability to respond to users’ questions. Using data from 14 countries and 186 institutions, we compare ChatGPT and student performance for 28,085 questions from accounting assessments and textbook test banks. As of January 2023, ChatGPT provides correct answers for 56.5 percent of questions and partially correct answers for an additional 9.4 percent of questions. When considering point values for questions, students significantly outperform ChatGPT with a 76.7 percent average on assessments compared to 47.5 percent for ChatGPT if no partial credit is awarded and 56.5 percent if partial credit is awarded. Still, ChatGPT performs better than the student average for 15.8 percent of assessments when we include partial credit. We provide evidence of how ChatGPT performs on different question types, accounting topics, class levels, open/closed assessments, and test bank questions. We also discuss implications for accounting education and research

Changing behaviour: Increasing the effectiveness of workplace interventions in creating pro-environmental behaviour change

There is a great deal of research outlining interventions to increase pro-environmental behaviour, many of which are aimed at employees. However, to date the results for these have not lived up to their initial promise. Instead of offering another intervention, we propose a model which identifies psychological conditions under which these interventions are most likely to succeed. Through the integration of previously separate literatures from experimental social psychology, organisational psychology, organisational behaviour and environmental psychology, we suggest that the degree to which the intervention-related goal is efficacious and attractive, self-concordant, in conflict with other goals, and perceived to be completed will affect the level and type of behaviour change. Our model aims to provide actionable knowledge that extends our understanding of the effectiveness of workplace interventions designed to increase green organisational behaviour

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe