Prediction of peptide and protein propensity for amyloid formation

Understanding which peptides and proteins have the potential to undergo amyloid formation and what driving forces are responsible for amyloid-like fiber formation and stabilization remains limited. This is mainly because proteins that can undergo structural changes, which lead to amyloid formation, are quite diverse and share no obvious sequence or structural homology, despite the structural similarity found in the fibrils. To address these issues, a novel approach based on recursive feature selection and feed-forward neural networks was undertaken to identify key features highly correlated with the self-assembly problem. This approach allowed the identification of seven physicochemical and biochemical properties of the amino acids highly associated with the self-assembly of peptides and proteins into amyloid-like fibrils (normalized frequency of β-sheet, normalized frequency of β-sheet from LG, weights for β-sheet at the window position of 1, isoelectric point, atom-based hydrophobic moment, helix termination parameter at position j+1 and ΔGº values for peptides extrapolated in 0 M urea). Moreover, these features enabled the development of a new predictor (available at http://cran.r-project.org/web/packages/appnn/index.html) capable of accurately and reliably predicting the amyloidogenic propensity from the polypeptide sequence alone with a prediction accuracy of 84.9 % against an external validation dataset of sequences with experimental in vitro, evidence of amyloid formation

Characteristics and well-being of urban informal home care providers during COVID-19 pandemic: a population-based study

Objectives Globally, the COVID-19 pandemic has overwhelmed many healthcare systems, which has hampered access to routine clinical care during lockdowns. Informal home care, care provided by non-healthcare professionals, increases the community’s healthcare capacity during pandemics. There is, however, limited research about the characteristics of informal home care providers and the challenges they face during such public health emergencies.Design A random, cross-sectional, population-based, RDD, telephone survey study was conducted to examine patterns of home care, characteristics of informal home care providers and the challenges experienced by these care providers during this pandemic.Setting Data were collected from 22 March to 1 April 2020 in Hong Kong, China.Participants A population representative study sample of Chinese-speaking adults (n=765) was interviewed.Primary and secondary outcome measures The study examined the characteristics of informal home care providers and self-reported health requirements of those who needed care. The study also examined providers’ self-perceived knowledge to provide routine home care as well as COVID-19 risk reduction care. Respondents were asked of their mental health status related to COVID-19.Results Of the respondents, 25.1% of 765 provided informal home care during the studied COVID-19 pandemic period. Among the informal home care providers, 18.4% of respondents took leave from school/work during the epidemic to provide care for the sick, fragile elderly and small children. Care providers tended to be younger aged, female and housewives. Approximately half of care providers reported additional mental strain and 37.2% reported of challenges in daily living during epidemic. Although most informal home care providers felt competent to provide routine care, 49.5% felt inadequately prepared to cope with the additional health risks of COVID-19.Conclusion During public health emergencies, heavy reliance on informal home healthcare providers necessitates better understanding of their specific needs and increased government services to support informal home care

Listening to patients, for the patients: The COVAD Study-Vision, organizational structure, and challenges

Background: The pandemic presented unique challenges for individuals with autoimmune and rheumatic diseases (AIRDs) due to their underlying condition, the effects of immunosuppressive treatments, and increased vaccine hesitancy. Objectives: The COVID-19 vaccination in autoimmune diseases (COVAD) study, a series of ongoing, patient self-reported surveys were conceived with the vision of being a unique tool to gather patient perspectives on AIRDs. It involved a multinational, multicenter collaborative effort amidst a global lockdown. Methods: Leveraging social media as a research tool, COVAD collected data using validated patient-reported outcomes (PROs). The study, comprising a core team, steering committee, and global collaborators, facilitated data collection and analysis. A pilot-tested, validated survey, featuring questions regarding COVID-19 infection, vaccination and outcomes, patient demographics, and PROs was circulated to patients with AIRDs and healthy controls (HCs). Discussion: We present the challenges encountered during this international collaborative project, including coordination, data management, funding constraints, language barriers, and authorship concerns, while highlighting the measures taken to address them. Conclusion: Collaborative virtual models offer a dynamic new frontier in medical research and are vital to studying rare diseases. The COVAD study demonstrates the potential of online platforms for conducting large-scale, patient-focused research and underscores the importance of integrating patient perspective into clinical care. Care of patients is our central motivation, and it is essential to recognize their voices as equal stakeholders and valued partners in the study of the conditions that affect them