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Key Points Protein–protein interactions (PPIs) are increasingly being targeted by drug discovery groups, and there exists great scope for therapeutic modulation of this target class in disease. The array of structurally interacting elements through which proteins interact with one another is wide and resists clear-cut classification. However, broad divisions can be made by grouping interactions based upon the globular or peptidic nature of the proteins. Some strategies for developing inhibitors against a given PPI may have more traction against certain classes of PPIs than others; for example, fragment-based drug discovery has shown particular promise in targeting bromodomains, as have peptide mimetics in mimicking β-strands. We examine case studies representative of the various structural types of PPI and discuss the lessons learnt from each. A summary of current status of inhibitors in clinical trials against different targets is presented. The biological rationale for targeting protein–protein interactions as a therapeutic strategy is strong, but identifying viable small-molecule drugs to achieve this has proved highly challenging. This article uses examples of successful discovery efforts to illustrate the research strategies that have proved most useful for different classes of protein–protein interactions. Protein–protein interactions (PPIs) are of pivotal importance in the regulation of biological systems and are consequently implicated in the development of disease states. Recent work has begun to show that, with the right tools, certain classes of PPI can yield to the efforts of medicinal chemists to develop inhibitors, and the first PPI inhibitors have reached clinical development. In this Review, we describe the research leading to these breakthroughs and highlight the existence of groups of structurally related PPIs within the PPI target class. For each of these groups, we use examples of successful discovery efforts to illustrate the research strategies that have proved most useful.

Face coverings are a key component of preventive health measure strategies to mitigate the spread of respiratory illnesses. In this study five groups of masks were investigated that are of particular relevance to the SARS-CoV-2 pandemic: re-usable, fabric two-layer and multi-layer masks, disposable procedure/surgical masks, KN95 and N95 filtering facepiece respirators. Experimental work focussed on the particle penetration through mask materials as a function of particle diameter, and the total inward leakage protection performance of the mask system. Geometric mean fabric protection factors varied from 1.78 to 144.5 for the fabric two-layer and KN95 materials, corresponding to overall filtration efficiencies of 43.8% and 99.3% using a flow rate of 17 L/min, equivalent to a breathing expiration rate for a person in a sedentary or standing position conversing with another individual. Geometric mean total inward leakage protection factors for the 2-layer, multi-layer and procedure masks were <2.3, while 6.2 was achieved for the KN95 masks. The highest values were measured for the N95 group at 165.7. Mask performance is dominated by face seal leakage. Despite the additional filtering layers added to cloth masks, and the higher filtration efficiency of the materials used in disposable procedure and KN95 masks, the total inward leakage protection factor was only marginally improved. N95 FFRs were the only mask group investigated that provided not only high filtration efficiency but high total inward leakage protection, and remain the best option to protect individuals from exposure to aerosol in high risk settings. The Mask Quality Factor and total inward leakage performance are very useful to determine the best options for masking. However, it is highly recommended that testing is undertaken on prospective products, or guidance is sought from impartial authorities, to confirm they meet any implied standards.

Background Exploring the relationship between physical activity, cognition and academic performance in children is an important but developing academic field. One of the key tasks for researchers is explaining how the three factors interact. The aim of this study was to develop and test a conceptual model that explains the associations among physical activity, cognition, academic performance, and potential mediating factors in children. Methods Data were sourced from 601 New Zealand children aged 6-11 years. Weekday home, weekday school, and weekend physical activity was measured by multiple pedometer step readings, cognition by four measures from the CNS Vital Signs assessment, and academic performance from the New Zealand Ministry of Education electronic Assessment Tools for Teaching and Learning (e-asTTle) reading and maths scores. A Structured Equation Modelling approach was used to test two models of variable relationships. The first model analysed the physical activity-academic performance relationship, and the second model added cognition to determine the mediating effect of cognition on the physical activity-academic performance association. Multigroup analysis was used to consider confounding effects of gender, ethnicity and school socioeconomic decile status. Results The initial model identified a significant association between physical activity and academic performance (r = 0.225). This direct association weakened (r = 0.121) when cognition was included in the model, demonstrating a partial mediating effect of cognition. While cognition was strongly associated with academic performance (r = 0.750), physical activity was also associated with cognition (r = 0.138). Subgroups showed similar patterns to the full sample, but the smaller group sizes limited the strength of the conclusions. Conclusions This cross-sectional study demonstrates a direct association between physical activity and academic performance. Furthermore, and importantly, this study shows the relationship between physical activity and academic performance is supported by an independent relationship between physical activity and cognition. Larger sample sizes are needed to investigate confounding factors of gender, age, socioeconomic status, and ethnicity. Future longitudinal analyses could investigate whether increases in physical activity can improve both cognition and academic performance. (Autor).

The growing acknowledgment of population wellbeing as a key indicator of societal prosperity has propelled governments worldwide to devise policies aimed at improving their citizens’ overall wellbeing. In New Zealand, the General Social Survey provides wellbeing metrics for a representative subset of the population (~ 10,000 individuals). However, this sample size only provides a surface-level understanding of the country’s wellbeing landscape, limiting our ability to comprehensively assess the impacts of governmental policies, particularly on smaller subgroups who may be of high policy interest. To overcome this challenge, comprehensive population-level wellbeing data is imperative. Leveraging New Zealand’s Integrated Data Infrastructure, this study developed and validated the efficacy of three predictive models—Stepwise Linear Regression, Elastic Net Regression, and Random Forest—for predicting subjective wellbeing outcomes (life satisfaction, life worthwhileness, family wellbeing, and mental wellbeing) using census-level administrative variables as predictors. Our results demonstrated the Random Forest model’s effectiveness in predicting subjective wellbeing, reflected in low RMSE values (~ 1.5). Nonetheless, the models exhibited low R 2 values, suggesting limited explanatory capacity for the nuanced variability in outcome variables. While achieving reasonable predictive accuracy, our findings underscore the necessity for further model refinements to enhance the prediction of subjective wellbeing outcomes.

Background This study explores opinions and experiences of people with Parkinson’s disease (PwP) in Sweden of using self-tracking. Parkinson’s disease (PD) is a neurodegenerative condition entailing varied and changing symptoms and side effects that can be a challenge to manage optimally. Patients’ self-tracking has demonstrated potential in other diseases, but we know little about PD self-tracking. The aim of this study was therefore to explore the opinions and experiences of PwP in Sweden of using self-tracking for PD. Method A mixed methods approach was used, combining qualitative data from seven interviews with quantitative data from a survey to formulate a model for self-tracking in PD. In total 280 PwP responded to the survey, 64% ( n  = 180) of which had experience from self-tracking. Result We propose a model for self-tracking in PD which share distinctive characteristics with the Plan-Do-Study-Act (PDSA) cycle for healthcare improvement. PwP think that tracking takes a lot of work and the right individual balance between burdens and benefits needs to be found. Some strategies have here been identified; to focus on positive aspects rather than negative, to find better solutions for their selfcare, and to increase the benefits through improved tools and increased use of self-tracking results in the dialogue with healthcare. Conclusion The main identified benefits are that self-tracking gives PwP a deeper understanding of their own specific manifestations of PD and contributes to a more effective decision making regarding their own selfcare. The process of self-tracking also enables PwP to be more active in communicating with healthcare. Tracking takes a lot of work and there is a need to find the right balance between burdens and benefits.

Value in healthcare can be defined as providing the optimal outcome per health dollar spent. Improving the value of healthcare for patients and healthcare organizations requires an understanding and evaluation of the costs and benefits. Investing in quality improvement (QI) work can bring about financial results for healthcare organizations over time, have beneficial organizational effects, and improve outcomes for patients. This article continues a series of QI educational papers in the Journal of Perinatology, and reviews financial and economic measures used to create the business case for QI. Ultimately, the business case for QI is better defined as a business strategy for success.

Drug discovery institutes comprised of experienced drug discovery scientists collaborating with fundamental biomedical researchers provide solutions to many of the challenges in translating biomedical research.Drug discovery institutes comprised of experienced drug discovery scientists collaborating with fundamental biomedical researchers provide solutions to many of the challenges in translating biomedical research.

IntroductionIn countries with access to the electronic health record (EHR), both patients and healthcare professionals have reported finding errors in the EHR, so-called EHRrors. These can range from simple typos to more serious cases of missing or incorrect health information. Despite their potential detrimental effect, the evidence on EHRrors has not been systematically analysed. It is unknown how common EHRrors are or how they impact patients and healthcare professionals.Methods and analysisA mixed systematic review will be carried out to address the research gap. We will search PubMed, Web of Science and CINAHL for studies published since 2000, which report original research data on patient-identified and healthcare professional-identified EHRrors. We will analyse (1) the prevalence of EHRrors, (2) the types of EHRrors and (3) their impact on care. Quantitative and qualitative findings will be synthesised following the Joanna Briggs Institute Framework for Mixed Systematic Reviews. Identified studies will be critically appraised for meta-biases and risk of bias in individual studies. The confidence in the emerging evidence will be further assessed through the Grading of Recommendations Assessment, Development and Evaluation approach. Findings will be contextualised and interpreted involving an international team of patient representatives and practising healthcare professionals.Ethics and disseminationThe study will not involve collection or analysis of individual patient data; thus, ethical approval is not required. Results will be published in a peer-reviewed publication and further disseminated through scientific events and educational materials.PROSPERO registration numberCRD42024622849.

Worldwide, public health physical activity guidelines include special emphasis on populations of children (typically 6-11 years) and adolescents (typically 12-19 years). Existing guidelines are commonly expressed in terms of frequency, time, and intensity of behaviour. However, the simple step output from both accelerometers and pedometers is gaining increased credibility in research and practice as a reasonable approximation of daily ambulatory physical activity volume. Therefore, the purpose of this article is to review existing child and adolescent objectively monitored step-defined physical activity literature to provide researchers, practitioners, and lay people who use accelerometers and pedometers with evidence-based translations of these public health guidelines in terms of steps/day. In terms of normative data (i.e., expected values), the updated international literature indicates that we can expect 1) among children, boys to average 12,000 to 16,000 steps/day and girls to average 10,000 to 13,000 steps/day; and, 2) adolescents to steadily decrease steps/day until approximately 8,000-9,000 steps/day are observed in 18-year olds. Controlled studies of cadence show that continuous MVPA walking produces 3,300-3,500 steps in 30 minutes or 6,600-7,000 steps in 60 minutes in 10-15 year olds. Limited evidence suggests that a total daily physical activity volume of 10,000-14,000 steps/day is associated with 60-100 minutes of MVPA in preschool children (approximately 4-6 years of age). Across studies, 60 minutes of MVPA in primary/elementary school children appears to be achieved, on average, within a total volume of 13,000 to 15,000 steps/day in boys and 11,000 to 12,000 steps/day in girls. For adolescents (both boys and girls), 10,000 to 11,700 may be associated with 60 minutes of MVPA. Translations of time- and intensity-based guidelines may be higher than existing normative data (e.g., in adolescents) and therefore will be more difficult to achieve (but not impossible nor contraindicated). Recommendations are preliminary and further research is needed to confirm and extend values for measured cadences, associated speeds, and MET values in young people; continue to accumulate normative data (expected values) for both steps/day and MVPA across ages and populations; and, conduct longitudinal and intervention studies in children and adolescents required to inform the shape of step-defined physical activity dose-response curves associated with various health parameters.