RsmG forms stable complexes with premature small subunit rRNA during bacterial ribosome biogenesis.

The ribosome is the ribonucleoprotein machine that carries out protein biosynthesis in all forms of life. Perfect synchronization between ribosomal RNA (rRNA) transcription, folding, post-transcriptional modification, maturation, and assembly of r-proteins is essential for the rapid formation of structurally and functionally accurate ribosomes. Many RNA nucleotide modification enzymes may function as assembly factors that oversee the accuracy of ribosome assembly. The protein RsmG is a methyltransferase enzyme that is responsible for N7 methylation in G527 of 16S rRNA. Here we illustrate the ability of RsmG to bind various premature small subunit ribosomal RNAs with contrasting affinities. Protein RsmG binds with approximately 15-times higher affinity to premature 16S rRNA with the full leader sequence compared to that of mature 16S rRNA. Various r-proteins which bind to the 5'-domain influence RsmG binding. The observed binding cooperativity between RsmG and r-proteins is sensitive to the maturation status of premature small subunit rRNA. However, neither the maturation of 16S rRNA nor the presence of various r-proteins significantly influence the methylation activity of RsmG. The capability of RsmG to bind to premature small subunit rRNA and alter its binding preference to various RNA-protein complexes based on the maturation of rRNA indicates its ability to influence ribosome assembly.

Comparative Effectiveness of a Technology-Facilitated Depression Care Management Model in Safety-Net Primary Care Patients With Type 2 Diabetes: 6-Month Outcomes of a Large Clinical Trial.

BACKGROUND: Comorbid depression is a significant challenge for safety-net primary care systems. Team-based collaborative depression care is effective, but complex system factors in safety-net organizations impede adoption and result in persistent disparities in outcomes. Diabetes-Depression Care-management Adoption Trial (DCAT) evaluated whether depression care could be significantly improved by harnessing information and communication technologies to automate routine screening and monitoring of patient symptoms and treatment adherence and allow timely communication with providers. OBJECTIVE: The aim of this study was to compare 6-month outcomes of a technology-facilitated care model with a usual care model and a supported care model that involved team-based collaborative depression care for safety-net primary care adult patients with type 2 diabetes. METHODS: DCAT is a translational study in collaboration with Los Angeles County Department of Health Services, the second largest safety-net care system in the United States. A comparative effectiveness study with quasi-experimental design was conducted in three groups of adult patients with type 2 diabetes to compare three delivery models: usual care, supported care, and technology-facilitated care. Six-month outcomes included depression and diabetes care measures and patient-reported outcomes. Comparative treatment effects were estimated by linear or logistic regression models that used generalized propensity scores to adjust for sampling bias inherent in the nonrandomized design. RESULTS: DCAT enrolled 1406 patients (484 in usual care, 480 in supported care, and 442 in technology-facilitated care), most of whom were Hispanic or Latino and female. Compared with usual care, both the supported care and technology-facilitated care groups were associated with significant reduction in depressive symptoms measured by scores on the 9-item Patient Health Questionnaire (least squares estimate, LSE: usual care=6.35, supported care=5.05, technology-facilitated care=5.16; P value: supported care vs usual care=.02, technology-facilitated care vs usual care=.02); decreased prevalence of major depression (odds ratio, OR: supported care vs usual care=0.45, technology-facilitated care vs usual care=0.33; P value: supported care vs usual care=.02, technology-facilitated care vs usual care=.007); and reduced functional disability as measured by Sheehan Disability Scale scores (LSE: usual care=3.21, supported care=2.61, technology-facilitated care=2.59; P value: supported care vs usual care=.04, technology-facilitated care vs usual care=.03). Technology-facilitated care was significantly associated with depression remission (technology-facilitated care vs usual care: OR=2.98, P=.04); increased satisfaction with care for emotional problems among depressed patients (LSE: usual care=3.20, technology-facilitated care=3.70; P=.05); reduced total cholesterol level (LSE: usual care=176.40, technology-facilitated care=160.46; P=.01); improved satisfaction with diabetes care (LSE: usual care=4.01, technology-facilitated care=4.20; P=.05); and increased odds of taking an glycated hemoglobin test (technology-facilitated care vs usual care: OR=3.40, P<.001). CONCLUSIONS: Both the technology-facilitated care and supported care delivery models showed potential to improve 6-month depression and functional disability outcomes. The technology-facilitated care model has a greater likelihood to improve depression remission, patient satisfaction, and diabetes care quality.

Optimizing efficiency and operations at a California safety-net endoscopy center: a modeling and simulation approach.

BACKGROUND: Improvements in endoscopy center efficiency are needed, but scant data are available. OBJECTIVE: To identify opportunities to improve patient throughput while balancing resource use and patient wait times in a safety-net endoscopy center. SETTING: Safety-net endoscopy center. PATIENTS: Outpatients undergoing endoscopy. INTERVENTION: A time and motion study was performed and a discrete event simulation model constructed to evaluate multiple scenarios aimed at improving endoscopy center efficiency. MAIN OUTCOME MEASUREMENTS: Procedure volume and patient wait time. RESULTS: Data were collected on 278 patients. Time and motion study revealed that 53.8 procedures were performed per week, with patients spending 2.3 hours at the endoscopy center. By using discrete event simulation modeling, a number of proposed changes to the endoscopy center were assessed. Decreasing scheduled endoscopy appointment times from 60 to 45 minutes led to a 26.4% increase in the number of procedures performed per week, but also increased patient wait time. Increasing the number of endoscopists by 1 each half day resulted in increased procedure volume, but there was a concomitant increase in patient wait time and nurse utilization exceeding capacity. By combining several proposed scenarios together in the simulation model, the greatest improvement in performance metrics was created by moving patient endoscopy appointments from the afternoon to the morning. In this simulation at 45- and 40-minute appointment times, procedure volume increased by 30.5% and 52.0% and patient time spent in the endoscopy center decreased by 17.4% and 13.0%, respectively. The predictions of the simulation model were found to be accurate when compared with actual changes implemented in the endoscopy center. LIMITATIONS: Findings may not be generalizable to non-safety-net endoscopy centers. CONCLUSIONS: The combination of minor, cost-effective changes such as reducing appointment times, minimizing and standardizing recovery time, and making small increases in preprocedure ancillary staff maximized endoscopy center efficiency across a number of performance metrics.

Patient-centered technological assessment and monitoring of depression for low-income patients.

Depression is a significant challenge for ambulatory care because it worsens health status and outcomes, increases health care utilizations and costs, and elevates suicide risk. An automatic telephonic assessment (ATA) system that links with tasks and alerts to providers may improve quality of depression care and increase provider productivity. We used ATA system in a trial to assess and monitor depressive symptoms of 444 safety-net primary care patients with diabetes. We assessed system properties, evaluated preliminary clinical outcomes, and estimated cost savings. The ATA system is feasible, reliable, valid, safe, and likely cost-effective for depression screening and monitoring for low-income primary care population.

Uncertainty and operational considerations in mass prophylaxis workforce planning.

BACKGROUND: The public health response to an influenza pandemic or other large-scale health emergency may include mass prophylaxis using multiple points of dispensing (PODs) to deliver countermeasures rapidly to affected populations. Computer models created to date to determine "optimal" staffing levels at PODs typically assume stable patient demand for service. The authors investigated POD function under dynamic and uncertain operational environments. METHODS: The authors constructed a Monte Carlo simulation model of mass prophylaxis (the Dynamic POD Simulator, or D-PODS) to assess the consequences of nonstationary patient arrival patterns on POD function under a variety of POD layouts and staffing plans. Compared are the performance of a standard POD layout under steady-state and variable patient arrival rates that may mimic real-life variation in patient demand. RESULTS: To achieve similar performance, PODs functioning under nonstationary patient arrival rates require higher staffing levels than would be predicted using the assumption of stationary arrival rates. Furthermore, PODs may develop severe bottlenecks unless staffing levels vary over time to meet changing patient arrival patterns. Efficient POD networks therefore require command and control systems capable of dynamically adjusting intra- and inter-POD staff levels to meet demand. In addition, under real-world operating conditions of heightened uncertainty, fewer large PODs will require a smaller total staff than many small PODs to achieve comparable performance. CONCLUSIONS: Modeling environments that capture the effects of fundamental uncertainties in public health disasters are essential for the realistic evaluation of response mechanisms and policies. D-PODS quantifies POD operational efficiency under more realistic conditions than have been modeled previously. The authors' experiments demonstrate that effective POD staffing plans must be responsive to variation and uncertainty in POD arrival patterns. These experiments highlight the need for command and control systems to be created to manage emergency response successfully.