Administrative applications

Nurse managers play a critical role in ensuring an appropriate number and mix of staff are available to ensure safe patient care is provided. When leadership decisions are effective, we see improved patient care outcomes, better staff performance, increased job satisfaction and staff retention. However, when decision making is less effective both patients and staff can be negatively impacted. The impact is particularly noticeable for patients who may experience increased adverse events, including greater risk of dying. Making evidence-based staffing decisions can be challenging for nurse managers given the complexity of today’s workplace and importantly, a lack of access to real-time data. Many factors impact on their decisions including nursing shortages; challenges to skills mix (human capital such as experience and qualifications); staff stress, burnout and fatigue; changes to the complexity of patient care needs; an aging workforce and communication inefficiencies. There are many workload measurement tools used internationally, but most are not based on real-time data showing patient acuity, bed occupancy rates and the quality and availability of staffing resources, all factors which are necessary to make cost-effective staffing decisions. Instead, nurse managers are left with many static and disparate reporting systems that do not meet managerial requirements for decision-making. This can result in increased workloads and stress for nurse managers, which also ultimately impact clinical staff. Hospitals need to develop and use software systems which will harness existing data, allowing nurse managers to extract, analyze and interpret data in a timely manner to support appropriate and safe nurse staffing decisions

Retrotransposons Are the Major Contributors to the Expansion of the Drosophila ananassae Muller F Element

The discordance between genome size and the complexity of eukaryotes can partly be attributed to differences in repeat density. The Muller F element (∼5.2 Mb) is the smallest chromosome in Drosophila melanogaster, but it is substantially larger (>18.7 Mb) in D. ananassae. To identify the major contributors to the expansion of the F element and to assess their impact, we improved the genome sequence and annotated the genes in a 1.4-Mb region of the D. ananassae F element, and a 1.7-Mb region from the D element for comparison. We find that transposons (particularly LTR and LINE retrotransposons) are major contributors to this expansion (78.6%), while Wolbachia sequences integrated into the D. ananassae genome are minor contributors (0.02%). Both D. melanogaster and D. ananassae F-element genes exhibit distinct characteristics compared to D-element genes (e.g., larger coding spans, larger introns, more coding exons, and lower codon bias), but these differences are exaggerated in D. ananassae. Compared to D. melanogaster, the codon bias observed in D. ananassae F-element genes can primarily be attributed to mutational biases instead of selection. The 5′ ends of F-element genes in both species are enriched in dimethylation of lysine 4 on histone 3 (H3K4me2), while the coding spans are enriched in H3K9me2. Despite differences in repeat density and gene characteristics, D. ananassae F-element genes show a similar range of expression levels compared to genes in euchromatic domains. This study improves our understanding of how transposons can affect genome size and how genes can function within highly repetitive domains