Ethnic Differences in Germline Genetic Testing For Breast Cancer

Introduction: Ethnic variations in uptake of genetic testing and differences in findings of germline mutations within ethnic groups, are not well understood. The goal of this research is to assess for any such differences or similarities within a genetic counseling and testing program at an urban Cancer Center. Methods: This is a non-comparative, descriptive epidemiology study assessing individuals with a diagnosis of breast cancer undergoing genetic counseling at the TJUH Sidney Kimmel Cancer Center in Philadelphia between 2014 and 2019. Data were compiled onto Research Electronic Data Capture (REDCAP) and analyzed statistically. Results: Patients with Breast Cancer (n=1075) were included in the analysis, 807 of whom had genetic testing conducted. In total, 81 Caucasians had pathogenic/likely pathogenic mutations (13%) and 16% had VUS. African Americans had the highest prevalence of VUS (32%) and 16 pathogenic/likely pathogenic mutations (13%). Asians (n=44) had no pathogenic but 2 likely pathogenic mutations (6%), and 3 VUS (9%). Comparatively, no statistically significant differences were observed. Asians presented for genetic counseling younger (mean age 49) than African Americans (mean age 54) and Caucasians (mean age 58) (p\u3c0.001). Caucasians were more likely to undergo genetic testing (89%) than African Americans (78%) and Asians (79%) (p\u3c0.002). Discussion: These results point toward ethnic differences in utilization and followthrough with genetic testing, as well as variations in genetic mutations. The high prevalence of VUS mutations in African Americans and few mutations in Asians suggests that the mutational spectrum in these populations is not well understood and warrants further study

Distinct ECM mechanosensing pathways regulate microtubule dynamics to control endothelial cell branching morphogenesis

The compliance and dimensionality of the ECM regulate distinct changes in microtubule growth speed and growth persistence

"I just keep thinking that I don't want to rely on people." a qualitative study of how people living with dementia achieve and maintain independence at home: stakeholder perspectives

YesBACKGROUND: Most people living with dementia want to remain in their own homes, supported by family and paid carers. Care at home often breaks down, necessitating transition to a care home and existing interventions are limited. To inform the development of psychosocial interventions to enable people with dementia to live well for longer at home, we qualitatively explored the views of people living with dementia, family carers and health and social care professionals, on how to achieve and maintain independence at home and what impedes this. METHODS: We conducted an inductive thematic analysis of qualitative interviews with 11 people living with dementia, 19 professionals and 22 family carers in England. RESULTS: We identified four overarching themes: being in a safe and familiar environment, enabling not disabling care, maintaining relationships and community connectedness, and getting the right support. For people living with dementia, the realities of staying active were complex: there was a tension between accepting support that enabled independence and a feeling that in doing so they were accepting dependency. Their and professionals' accounts prioritised autonomy and 'living well with dementia', while family carers prioritised avoiding harm. Professionals promoted positive risk-taking and facilitating independence, whereas family carers often felt they were left holding this risk. DISCUSSION: Psychosocial interventions must accommodate tensions between positive risk-taking and avoiding harm, facilitating autonomy and providing support. They should be adaptive and collaborative, combining self-management with flexible support. Compassionate implementation of rights-based dementia care must consider the emotional burden for family carers of supporting someone to live positively with risk.This work was supported by the Alzheimer’s Society (UK) and was carried out within the UCL Alzheimer’s Society Centre of Excellence for Independence at home, NIDUS (New Interventions in Dementia Study) programme (Alzheimer’s Society Centre of Excellence grant 330). This project is also part-funded funded by The National Institute for Health Research Applied Research Collaboration North West Coast (ARC NWC)

Developing the New Interventions for independence in Dementia Study (NIDUS) theoretical model for supporting people to live well with dementia at home for longer: a systematic review of theoretical models and Randomised Controlled Trial evidence

YesPurpose: To build an evidence-informed theoretical model describing how to support people with dementia to live well or for longer at home. Methods: We searched electronic databases to August 2018 for papers meeting predetermined inclusion criteria in two reviews that informed our model. We scoped literature for theoretical models of how to enable people with dementia to live at home independently, with good life quality or for longer. We systematically reviewed Randomised Controlled Trials (RCTs) reporting psychosocial intervention effects on time lived with dementia at home. Two researchers independently rated risk of bias. We developed our theoretical model through discussions with experts by personal, clinical and academic experiences, informed by this evidence base. Results: Our scoping review included 52 studies. We divided models identified into: values and approaches (relational and recovery models; optimising environment and activities; family carer skills and support); care strategies (family carer-focused; needs and goal-based; self-management); and service models (case management; integrated; consumer-directed). The 11 RCTs included in our systematic review, all judged at low risk of bias, described only two interventions that increased time people with dementia lived in their own homes. These collectively encompassed all these components except for consumer-directed and integrated care. We developed and revised our model, using review evidence and expert consultation to define the final model. Conclusions: Our theoretical model describes values, care strategies and service models that can be used in the design of interventions to enable people with dementia to live well and for longer at home.This work forms the first phase of the NIDUS (New Interventions in Dementia Study), which is hosted within the Alzheimer’s Society Centre of Excellence for Independence at home (Centre of Excellence grant 330)

A direct role for SNX9 in the biogenesis of filopodia.

Filopodia are finger-like actin-rich protrusions that extend from the cell surface and are important for cell-cell communication and pathogen internalization. The small size and transient nature of filopodia combined with shared usage of actin regulators within cells confounds attempts to identify filopodial proteins. Here, we used phage display phenotypic screening to isolate antibodies that alter the actin morphology of filopodia-like structures (FLS) in vitro. We found that all of the antibodies that cause shorter FLS interact with SNX9, an actin regulator that binds phosphoinositides during endocytosis and at invadopodia. In cells, we discover SNX9 at specialized filopodia in Xenopus development and that SNX9 is an endogenous component of filopodia that are hijacked by Chlamydia entry. We show the use of antibody technology to identify proteins used in filopodia-like structures, and a role for SNX9 in filopodia

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Exponential growth, high prevalence of SARS-CoV-2, and vaccine effectiveness associated with the Delta variant

SARS-CoV-2 infections were rising during early summer 2021 in many countries associated with the Delta variant. We assessed RT-PCR swab-positivity in the REal-time Assessment of Community Transmission-1 (REACT-1) study in England. We observed sustained exponential growth with average doubling time (June-July 2021) of 25 days driven by complete replacement of Alpha variant by Delta, and by high prevalence at younger less-vaccinated ages. Unvaccinated people were three times more likely than double-vaccinated people to test positive. However, after adjusting for age and other variables, vaccine effectiveness for double-vaccinated people was estimated at between ~50% and ~60% during this period in England. Increased social mixing in the presence of Delta had the potential to generate sustained growth in infections, even at high levels of vaccination

Hospital admission and emergency care attendance risk for SARS-CoV-2 delta (B.1.617.2) compared with alpha (B.1.1.7) variants of concern: a cohort study

Background: The SARS-CoV-2 delta (B.1.617.2) variant was first detected in England in March, 2021. It has since rapidly become the predominant lineage, owing to high transmissibility. It is suspected that the delta variant is associated with more severe disease than the previously dominant alpha (B.1.1.7) variant. We aimed to characterise the severity of the delta variant compared with the alpha variant by determining the relative risk of hospital attendance outcomes. Methods: This cohort study was done among all patients with COVID-19 in England between March 29 and May 23, 2021, who were identified as being infected with either the alpha or delta SARS-CoV-2 variant through whole-genome sequencing. Individual-level data on these patients were linked to routine health-care datasets on vaccination, emergency care attendance, hospital admission, and mortality (data from Public Health England's Second Generation Surveillance System and COVID-19-associated deaths dataset; the National Immunisation Management System; and NHS Digital Secondary Uses Services and Emergency Care Data Set). The risk for hospital admission and emergency care attendance were compared between patients with sequencing-confirmed delta and alpha variants for the whole cohort and by vaccination status subgroups. Stratified Cox regression was used to adjust for age, sex, ethnicity, deprivation, recent international travel, area of residence, calendar week, and vaccination status. Findings: Individual-level data on 43 338 COVID-19-positive patients (8682 with the delta variant, 34 656 with the alpha variant; median age 31 years [IQR 17–43]) were included in our analysis. 196 (2·3%) patients with the delta variant versus 764 (2·2%) patients with the alpha variant were admitted to hospital within 14 days after the specimen was taken (adjusted hazard ratio [HR] 2·26 [95% CI 1·32–3·89]). 498 (5·7%) patients with the delta variant versus 1448 (4·2%) patients with the alpha variant were admitted to hospital or attended emergency care within 14 days (adjusted HR 1·45 [1·08–1·95]). Most patients were unvaccinated (32 078 [74·0%] across both groups). The HRs for vaccinated patients with the delta variant versus the alpha variant (adjusted HR for hospital admission 1·94 [95% CI 0·47–8·05] and for hospital admission or emergency care attendance 1·58 [0·69–3·61]) were similar to the HRs for unvaccinated patients (2·32 [1·29–4·16] and 1·43 [1·04–1·97]; p=0·82 for both) but the precision for the vaccinated subgroup was low. Interpretation: This large national study found a higher hospital admission or emergency care attendance risk for patients with COVID-19 infected with the delta variant compared with the alpha variant. Results suggest that outbreaks of the delta variant in unvaccinated populations might lead to a greater burden on health-care services than the alpha variant. Funding: Medical Research Council; UK Research and Innovation; Department of Health and Social Care; and National Institute for Health Research

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

AbstractUnderstanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.</jats:p