A Pre-mRNA–Associating Factor Links Endogenous siRNAs to Chromatin Regulation

In plants and fungi, small RNAs silence gene expression in the nucleus by establishing repressive chromatin states. The role of endogenous small RNAs in metazoan nuclei is largely unknown. Here we show that endogenous small interfering RNAs (endo-siRNAs) direct Histone H3 Lysine 9 methylation (H3K9me) in Caenorhabditis elegans. In addition, we report the identification and characterization of nuclear RNAi defective (nrde)-1 and nrde-4. Endo-siRNA–driven H3K9me requires the nuclear RNAi pathway including the Argonaute (Ago) NRDE-3, the conserved nuclear RNAi factor NRDE-2, as well as NRDE-1 and NRDE-4. Small RNAs direct NRDE-1 to associate with the pre-mRNA and chromatin of genes, which have been targeted by RNAi. NRDE-3 and NRDE-2 are required for the association of NRDE-1 with pre-mRNA and chromatin. NRDE-4 is required for NRDE-1/chromatin association, but not NRDE-1/pre-mRNA association. These data establish that NRDE-1 is a novel pre-mRNA and chromatin-associating factor that links small RNAs to H3K9 methylation. In addition, these results demonstrate that endo-siRNAs direct chromatin modifications via the Nrde pathway in C. elegans

Clinical Sequencing Exploratory Research Consortium: Accelerating Evidence-Based Practice of Genomic Medicine

Despite rapid technical progress and demonstrable effectiveness for some types of diagnosis and therapy, much remains to be learned about clinical genome and exome sequencing (CGES) and its role within the practice of medicine. The Clinical Sequencing Exploratory Research (CSER) consortium includes 18 extramural research projects, one National Human Genome Research Institute (NHGRI) intramural project, and a coordinating center funded by the NHGRI and National Cancer Institute. The consortium is exploring analytic and clinical validity and utility, as well as the ethical, legal, and social implications of sequencing via multidisciplinary approaches; it has thus far recruited 5,577 participants across a spectrum of symptomatic and healthy children and adults by utilizing both germline and cancer sequencing. The CSER consortium is analyzing data and creating publically available procedures and tools related to participant preferences and consent, variant classification, disclosure and management of primary and secondary findings, health outcomes, and integration with electronic health records. Future research directions will refine measures of clinical utility of CGES in both germline and somatic testing, evaluate the use of CGES for screening in healthy individuals, explore the penetrance of pathogenic variants through extensive phenotyping, reduce discordances in public databases of genes and variants, examine social and ethnic disparities in the provision of genomics services, explore regulatory issues, and estimate the value and downstream costs of sequencing. The CSER consortium has established a shared community of research sites by using diverse approaches to pursue the evidence-based development of best practices in genomic medicine

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

The factors influencing the effective early career and rapid transition to a nursing specialty in differing contexts of practice: a modified Delphi consensus study

Harvey, CL ORCiD: 0000-0001-9016-8840; Hegney, DG ORCiD: 0000-0003-1267-1760; Tsai, LP ORCiD: 0000-0003-2368-4145OBJECTIVES: This study aimed to test and further develop the 'Early Career and Rapid Transition to a Nursing Specialty' (TRANSPEC) model to a nursing specialty developed from a systematic review. Semi-structured interviews of specialist clinically based nurses and a consensus Delphi study with an expert panel were used to expand and achieve consensus, agreement, reliability and stability of the model. DESIGN: A modified Delphi, two rounds (64 and 52 Likert items) of reiterative online questionnaires and one round as a nominal group technique, was informed by qualitative thematic analysis of semi-structured interviews. SETTING AND PARTICIPANTS: Interviews with 14 specialists clinical practicing registered nurses and a panel of 25 national experts participated in the Delphi study. RESULTS: The interview participants experienced 14 rapid transitions and three were early career transition. The overarching themes from the preliminary model were confirmed and further expanded. These were the self (personal and professional); the transition processes (final and informal); a sense of belonging; and the overarching context of practice over a time continuum. In the Delphi, the highest rating item was 'Specialty work colleagues respect, include, support, and accept specialist nurse on completion of transition processes'. Pre-entry was highlighted as an important time point prior to transition. All items reaching consensus were included in the final model. Cronbach α increased from 0.725 to 0.875 for the final model. CONCLUSIONS: The TRANSPEC model is a valid and reliable evidence-based tool for use in the career pathway and development of nursing specialists. Using the Benner model 'Novice to Expert' after the novice incomer phase is achieved, further lifelong learning development will transform the novice specialist over time continuum.Associated Grant Code:RSH/466

Facilitating an early career transition pathway to community nursing: A Delphi policy study

Harvey, CL ORCiD: 0000-0001-9016-8840; Hegney, DG ORCiD: 0000-0003-1267-1760; Tsai, LP ORCiD: 0000-0003-2368-4145Nursing Open published by John Wiley & Sons Ltd. Aim: To further develop and validate a new model of the early career transition pathway in the speciality of community nursing. Design: Delphi policy approach, guided by a previous systematic review and semi-structured interviews. Methods: Four rounds of an expert panel (N = 19). Rounds one, two and four were questionnaires consisting of a combination of closed (Likert response) and open-ended questions. Round three comprised of a focus group conducted using virtual meeting technology. Results: The final model demonstrated reliable and valid measures. There were deficiencies in “pre-entry”—where the marketing of community nursing was negligible and the support around orientation informal and minimal, mainly due to tight budgetary concerns. Community practice holds a whole new dimension for nurses transitioning from acute care as the concept of “knowing your community” took time and support—time to be accepted reciprocally and develop a sense of belonging to the community. © 2019 The Authors

Nurses’ experiences of transition to community-based practice

Harvey, CL ORCiD: 0000-0001-9016-8840; Hegney, DG ORCiD: 0000-0003-1267-1760; Tsai, LP ORCiD: 0000-0003-2368-4145Objectives: This paper describes the findings from interviews, presented as the second stage of a study aimed at developing a career pathway for community nursing and midwifery for one Australian state, with a particular focus on early transition to community-based practice.Background: With the increasing incidence of chronic conditions, health services are focused on primary and community care as the central point of care provision, and with it, the realisation that nurses have a central role to play in care delivery. Yet, community nursing is a poorly defined area of practice, and it is often seen as an unattractive career option.Methods: Semi-structured interviews were conducted with seven experienced registered nurses currently employed and working in the community. Data analysis was undertaken using a pragmatic approach that allowed for the examination of themes emerging from the participant narratives. One member of the research team conducted interviews, with cross-checking of transcripts undertaken by other members of the team. Narrative was drawn from the transcripts and aligned to themes emerging from a draft pathway informed by a systematic review. COREQ checklist was adhered.Results: Participants identified elements essential to a good transition that included responsive orientation, innovative leadership and the development of community-based networks related to social, legal, financial and practical elements of care. Experiential knowledge and a sense of belonging within the community were two important factors considered essential to successful transition.Conclusion: Community nursing is a specialised practice which requires a revision of expectations, preparation for practice and acknowledgement of its value, before nurses can become responsive to the changing community emphasis on health service delivery.Potential implications: For a career pathway to accommodate early transition into community practice, key issues need to be addressed in relation to educational preparation, support for practice, and acceptance