Since the initial publication of A Compendium of Strategies to Prevent Healthcare-Associated Infections in Acute Care Hospitals in 2008, the prevention of healthcare-associated infections (HAIs) has continued to be a national priority. Progress in healthcare epidemiology, infection prevention, antimicrobial stewardship, and implementation science research has led to improvements in our understanding of effective strategies for HAI prevention. Despite these advances, HAIs continue to affect ∼1 of every 31 hospitalized patients,1 leading to substantial morbidity, mortality, and excess healthcare expenditures,1 and persistent gaps remain between what is recommended and what is practiced.

The widespread impact of the coronavirus disease 2019 (COVID-19) pandemic on HAI outcomes2 in acute-care hospitals has further highlighted the essential role of infection prevention programs and the critical importance of prioritizing efforts that can be sustained even in the face of resource requirements from COVID-19 and future infectious diseases crises.3

The Compendium: 2022 Updates document provides acute-care hospitals with up-to-date, practical expert guidance to assist in prioritizing and implementing HAI prevention efforts. It is the product of a highly collaborative effort led by the Society for Healthcare Epidemiology of America (SHEA), the Infectious Disease Society of America (IDSA), the Association for Professionals in Infection Control and Epidemiology (APIC), the American Hospital Association (AHA), and The Joint Commission, with major contributions from representatives of organizations and societies with content expertise, including the Centers for Disease Control and Prevention (CDC), the Pediatric Infectious Disease Society (PIDS), the Society for Critical Care Medicine (SCCM), the Society for Hospital Medicine (SHM), the Surgical Infection Society (SIS), and others.

The U.S. Department of Agriculture–Agricultural Research Service (USDA-ARS) has been a leader in weed science research covering topics ranging from the development and use of integrated weed management (IWM) tactics to basic mechanistic studies, including biotic resistance of desirable plant communities and herbicide resistance. ARS weed scientists have worked in agricultural and natural ecosystems, including agronomic and horticultural crops, pastures, forests, wild lands, aquatic habitats, wetlands, and riparian areas. Through strong partnerships with academia, state agencies, private industry, and numerous federal programs, ARS weed scientists have made contributions to discoveries in the newest fields of robotics and genetics, as well as the traditional and fundamental subjects of weed–crop competition and physiology and integration of weed control tactics and practices. Weed science at ARS is often overshadowed by other research topics; thus, few are aware of the long history of ARS weed science and its important contributions. This review is the result of a symposium held at the Weed Science Society of America’s 62nd Annual Meeting in 2022 that included 10 separate presentations in a virtual Weed Science Webinar Series. The overarching themes of management tactics (IWM, biological control, and automation), basic mechanisms (competition, invasive plant genetics, and herbicide resistance), and ecosystem impacts (invasive plant spread, climate change, conservation, and restoration) represent core ARS weed science research that is dynamic and efficacious and has been a significant component of the agency’s national and international efforts. This review highlights current studies and future directions that exemplify the science and collaborative relationships both within and outside ARS. Given the constraints of weeds and invasive plants on all aspects of food, feed, and fiber systems, there is an acknowledged need to face new challenges, including agriculture and natural resources sustainability, economic resilience and reliability, and societal health and well-being.

Profitability, yield, and fertilizer use are compared across three different potassium (K) fertilizer rate recommendation ideologies. Existing agronomic, “build and maintain” rate recommendations (KE) are compared to profit-maximizing rates with and without taking long-run soil-test K (STK) implications into account. Regardless of starting STK, K use equilibrated over the course of 3 years irrespective of ideology. Since taking long-run STK into account did not alter ending STK and only led to a miniscule yield effect, we encourage producers to use annual profit-maximizing K rates that were 3–11% lower than KE rates and generated more profit with minimal yield loss.

Monoclonal antibody therapeutics to treat coronavirus disease (COVID-19) have been authorized by the US Food and Drug Administration under Emergency Use Authorization (EUA). Many barriers exist when deploying a novel therapeutic during an ongoing pandemic, and it is critical to assess the needs of incorporating monoclonal antibody infusions into pandemic response activities. We examined the monoclonal antibody infusion site process during the COVID-19 pandemic and conducted a descriptive analysis using data from 3 sites at medical centers in the United States supported by the National Disaster Medical System. Monoclonal antibody implementation success factors included engagement with local medical providers, therapy batch preparation, placing the infusion center in proximity to emergency services, and creating procedures resilient to EUA changes. Infusion process challenges included confirming patient severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positivity, strained staff, scheduling, and pharmacy coordination. Infusion sites are effective when integrated into pre-existing pandemic response ecosystems and can be implemented with limited staff and physical resources.

The Variables and Slow Transients Survey (VAST) on the Australian Square Kilometre Array Pathfinder (ASKAP) is designed to detect highly variable and transient radio sources on timescales from 5 s to $\sim\!5$ yr. In this paper, we present the survey description, observation strategy and initial results from the VAST Phase I Pilot Survey. This pilot survey consists of $\sim\!162$ h of observations conducted at a central frequency of 888 MHz between 2019 August and 2020 August, with a typical rms sensitivity of $0.24\ \mathrm{mJy\ beam}^{-1}$ and angular resolution of $12-20$ arcseconds. There are 113 fields, each of which was observed for 12 min integration time, with between 5 and 13 repeats, with cadences between 1 day and 8 months. The total area of the pilot survey footprint is 5 131 square degrees, covering six distinct regions of the sky. An initial search of two of these regions, totalling 1 646 square degrees, revealed 28 highly variable and/or transient sources. Seven of these are known pulsars, including the millisecond pulsar J2039–5617. Another seven are stars, four of which have no previously reported radio detection (SCR J0533–4257, LEHPM 2-783, UCAC3 89–412162 and 2MASS J22414436–6119311). Of the remaining 14 sources, two are active galactic nuclei, six are associated with galaxies and the other six have no multi-wavelength counterparts and are yet to be identified.

We present the data and initial results from the first pilot survey of the Evolutionary Map of the Universe (EMU), observed at 944 MHz with the Australian Square Kilometre Array Pathfinder (ASKAP) telescope. The survey covers $270 \,\mathrm{deg}^2$ of an area covered by the Dark Energy Survey, reaching a depth of 25–30 $\mu\mathrm{Jy\ beam}^{-1}$ rms at a spatial resolution of $\sim$ 11–18 arcsec, resulting in a catalogue of $\sim$ 220 000 sources, of which $\sim$ 180 000 are single-component sources. Here we present the catalogue of single-component sources, together with (where available) optical and infrared cross-identifications, classifications, and redshifts. This survey explores a new region of parameter space compared to previous surveys. Specifically, the EMU Pilot Survey has a high density of sources, and also a high sensitivity to low surface brightness emission. These properties result in the detection of types of sources that were rarely seen in or absent from previous surveys. We present some of these new results here.

The learning hospital is distinguished by ceaseless evolution of erudition, enhancement, and implementation of clinical best practices. We describe a model for the learning hospital within the framework of a hospital infection prevention program and argue that a critical assessment of safety practices is possible without significant grant funding. We reviewed 121 peer-reviewed manuscripts published by the VCU Hospital Infection Prevention Program over 16 years. Publications included quasi-experimental studies, observational studies, surveys, interrupted time series analyses, and editorials. We summarized the articles based on their infection prevention focus, and we provide a brief summary of the findings. We also summarized the involvement of nonfaculty learners in these manuscripts as well as the contributions of grant funding. Despite the absence of significant grant funding, infection prevention programs can critically assess safety strategies under the learning hospital framework by leveraging a diverse collaboration of motivated nonfaculty learners. This model is a valuable adjunct to traditional grant-funded efforts in infection prevention science and is part of a successful horizontal infection control program.

Optimising short- and long-term outcomes for children and patients with CHD depends on continued scientific discovery and translation to clinical improvements in a coordinated effort by multiple stakeholders. Several challenges remain for clinicians, researchers, administrators, patients, and families seeking continuous scientific and clinical advancements in the field. We describe a new integrated research and improvement network – Cardiac Networks United – that seeks to build upon the experience and success achieved to-date to create a new infrastructure for research and quality improvement that will serve the needs of the paediatric and congenital heart community in the future. Existing gaps in data integration and barriers to improvement are described, along with the mission and vision, organisational structure, and early objectives of Cardiac Networks United. Finally, representatives of key stakeholder groups – heart centre executives, research leaders, learning health system experts, and parent advocates – offer their perspectives on the need for this new collaborative effort.

OBJECTIVES/SPECIFIC AIMS: The purpose of the present secondary data analysis was to examine the effect of moderate-severe disturbed sleep before the start of radiation therapy (RT) on subsequent RT-induced pain. METHODS/STUDY POPULATION: Analyses were performed on 676 RT-naïve breast cancer patients (mean age 58, 100% female) scheduled to receive RT from a previously completed nationwide, multicenter, phase II randomized controlled trial examining the efficacy of oral curcumin on radiation dermatitis severity. The trial was conducted at 21 community oncology practices throughout the US affiliated with the University of Rochester Cancer Center NCI’s Community Oncology Research Program (URCC NCORP) Research Base. Sleep disturbance was assessed using a single item question from the modified MD Anderson Symptom Inventory (SI) on a 0–10 scale, with higher scores indicating greater sleep disturbance. Total subjective pain as well as the subdomains of pain (sensory, affective, and perceived) were assessed by the short-form McGill Pain Questionnaire. Pain at treatment site (pain-Tx) was also assessed using a single item question from the SI. These assessments were included for pre-RT (baseline) and post-RT. For the present analyses, patients were dichotomized into 2 groups: those who had moderate-severe disturbed sleep at baseline (score≥4 on the SI; n=101) Versus those who had mild or no disturbed sleep (control group; score=0–3 on the SI; n=575). RESULTS/ANTICIPATED RESULTS: Prior to the start of RT, breast cancer patients with moderate-severe disturbed sleep at baseline were younger, less likely to have had lumpectomy or partial mastectomy while more likely to have had total mastectomy and chemotherapy, more likely to be on sleep, anti-anxiety/depression, and prescription pain medications, and more likely to suffer from depression or anxiety disorder than the control group (all p’s≤0.02). Spearman rank correlations showed that changes in sleep disturbance from baseline to post-RT were significantly correlated with concurrent changes in total pain (r=0.38; p<0.001), sensory pain (r=0.35; p<0.001), affective pain (r=0.21; p<0.001), perceived pain intensity (r=0.37; p<0.001), and pain-Tx (r=0.35; p<0.001). In total, 92% of patients with moderate-severe disturbed sleep at baseline reported post-RT total pain compared with 79% of patients in the control group (p=0.006). Generalized linear estimating equations, after controlling for baseline pain and other covariates (baseline fatigue and distress, age, sleep medications, anti-anxiety/depression medications, prescription pain medications, and depression or anxiety disorder), showed that patients with moderate-severe disturbed sleep at baseline had significantly higher mean values of post-RT total pain (by 39%; p=0.033), post-RT sensory pain (by 41%; p=0.046), and post-RT affective pain (by 55%; p=0.035) than the control group. Perceived pain intensity (p=0.066) and pain-Tx (p=0.086) at post-RT were not significantly different between the 2 groups. DISCUSSION/SIGNIFICANCE OF IMPACT: These findings suggest that moderate-severe disturbed sleep prior to RT is an important predictor for worsening of pain at post-RT in breast cancer patients. There could be several plausible reasons for this. Sleep disturbance, such as sleep loss and sleep continuity disturbance, could result in impaired sleep related recovery and repair of tissue damage associated with cancer and its treatment; thus, resulting in the amplification of pain. Sleep disturbance may also reduce pain tolerance threshold through increased sensitization of the central nervous system. In addition, pain and sleep disturbance may share common neuroimmunological pathways. Sleep disturbance may modulate inflammation, which in turn may contribute to increased pain. Further research is needed to confirm these findings and whether interventions targeting sleep disturbance in early phase could be potential alternate approaches to reduce pain after RT.

Modern high-throughput molecular and analytical tools offer exciting opportunities to gain a mechanistic understanding of unique traits of weeds. During the past decade, tremendous progress has been made within the weed science discipline using genomic techniques to gain deeper insights into weedy traits such as invasiveness, hybridization, and herbicide resistance. Though the adoption of newer “omics” techniques such as proteomics, metabolomics, and physionomics has been slow, applications of these omics platforms to study plants, especially agriculturally important crops and weeds, have been increasing over the years. In weed science, these platforms are now used more frequently to understand mechanisms of herbicide resistance, weed resistance evolution, and crop–weed interactions. Use of these techniques could help weed scientists to further reduce the knowledge gaps in understanding weedy traits. Although these techniques can provide robust insights about the molecular functioning of plants, employing a single omics platform can rarely elucidate the gene-level regulation and the associated real-time expression of weedy traits due to the complex and overlapping nature of biological interactions. Therefore, it is desirable to integrate the different omics technologies to give a better understanding of molecular functioning of biological systems. This multidimensional integrated approach can therefore offer new avenues for better understanding of questions of interest to weed scientists. This review offers a retrospective and prospective examination of omics platforms employed to investigate weed physiology and novel approaches and new technologies that can provide holistic and knowledge-based weed management strategies for future.

Leafy spurge (Euphorbia esula L.) is an invasive perennial weed infesting range and recreational lands of North America. Previous research and omics projects with E. esula have helped develop it as a model for studying many aspects of perennial plant development and response to abiotic stress. However, the lack of an assembled genome for E. esula has limited the power of previous transcriptomics studies to identify functional promoter elements and transcription factor binding sites. An assembled genome for E. esula would enhance our understanding of signaling processes controlling plant development and responses to environmental stress and provide a better understanding of genetic factors impacting weediness traits, evolution, and herbicide resistance. A comprehensive transcriptome database would also assist in analyzing future RNA-seq studies and is needed to annotate and assess genomic sequence assemblies. Here, we assembled and annotated 56,234 unigenes from an assembly of 589,235 RNA-seq-derived contigs and a previously published Sanger-sequenced expressed sequence tag collection. The resulting data indicate that we now have sequence for >90% of the expressed E. esula protein-coding genes. We also assembled the gene space of E. esula by using a limited coverage (18X) genomic sequence database. In this study, the programs Velvet and Trinity produced the best gene-space assemblies based on representation of expressed and conserved eukaryotic genes. The results indicate that E. esula contains as much as 23% repetitive sequences, of which 11% are unique. Our sequence data were also sufficient for assembling a full chloroplast and partial mitochondrial genome. Further, marker analysis identified more than 150,000 high-quality variants in our E. esula L-RNA–scaffolded, whole-genome, Trinity-assembled genome. Based on these results, E. esula appears to have limited heterozygosity. This study provides a blueprint for low-cost genomic assemblies in weed species and new resources for identifying conserved and novel promoter regions among coordinately expressed genes of E. esula.

Objectives: The aim of this study was to examine the evidence payers cited in their coverage policies for multi-gene panels and sequencing tests (panels), and to compare these findings with the evidence payers cited in their coverage policies for other types of medical interventions.

Methods: We used the University of California at San Francisco TRANSPERS Payer Coverage Registry to identify coverage policies for panels issued by five of the largest US private payers. We reviewed each policy and categorized the evidence cited within as: clinical studies, systematic reviews, technology assessments, cost-effectiveness analyses (CEAs), budget impact studies, and clinical guidelines. We compared the evidence cited in these coverage policies for panels with the evidence cited in policies for other intervention types (pharmaceuticals, medical devices, diagnostic tests and imaging, and surgical interventions) as reported in a previous study.

Results: Fifty-five coverage policies for panels were included. On average, payers cited clinical guidelines in 84 percent of their coverage policies (range, 73–100 percent), clinical studies in 69 percent (50–87 percent), technology assessments 47 percent (33–86 percent), systematic reviews or meta-analyses 31 percent (7–71 percent), and CEAs 5 percent (0–7 percent). No payers cited budget impact studies in their policies. Payers less often cited clinical studies, systematic reviews, technology assessments, and CEAs in their coverage policies for panels than in their policies for other intervention types. Payers cited clinical guidelines in a comparable proportion of policies for panels and other technology types.

Conclusions: Payers in our sample less often cited clinical studies and other evidence types in their coverage policies for panels than they did in their coverage policies for other types of medical interventions.