Pseudomonas aeruginosa is a major life-threatening opportunistic pathogen that commonly infects immunocompromised patients. This bacterium owes its success as a pathogen largely to its metabolic versatility and flexibility. A thorough understanding of P. aeruginosa's metabolism is thus pivotal for the design of effective intervention strategies. Here we aim to provide, through systems analysis, a basis for the characterization of the genome-scale properties of this pathogen's versatile metabolic network. To this end, we reconstructed a genome-scale metabolic network of Pseudomonas aeruginosa PAO1. This reconstruction accounts for 1,056 genes (19% of the genome), 1,030 proteins, and 883 reactions. Flux balance analysis was used to identify key features of P. aeruginosa metabolism, such as growth yield, under defined conditions and with defined knowledge gaps within the network. BIOLOG substrate oxidation data were used in model expansion, and a genome-scale transposon knockout set was compared against in silico knockout predictions to validate the model. Ultimately, this genome-scale model provides a basic modeling framework with which to explore the metabolism of P. aeruginosa in the context of its environmental and genetic constraints, thereby contributing to a more thorough understanding of the genotype-phenotype relationships in this resourceful and dangerous pathogen.With sequenced genomes now routinely being made available to the public, detailed annotations and various publicly available genomic resources have enabled the formation of genome-scale models of metabolism for a wide variety of organisms (12,21,26,42,63,65). A wealth of data from wellcontrolled experiments, coupled with advancements in methods for computational network analysis, have allowed these models to aid interrogation of metabolic behavior. In addition, an iterative process to model development-cycles of in silico model predictions, experimental (i.e., wet lab) validation, and subsequent model refinement-has enabled the development of methods that have contributed to biological discovery, such as in determination of likely drug targets in Mycobacterium tuberculosis (3,26), metabolic engineering of cells for production of valuable compounds (5, 32, 34), and development of novel frameworks for contextualizing high-throughput "-omics" data sets (15,24,64).Pseudomonas aeruginosa is a ubiquitous gram-negative bacterium that is capable of surviving in a broad range of natural

Purpose The purpose of this article is to illustrate and discuss the impact the 2019 novel Coronavirus (COVID-19) pandemic on the delivery of obstetric care, including a discussion on the preexisting barriers, prenatal framework and need for transition to telehealth. Description The COVID-19 was first detected in China in December of 2019 and by March 2020 spread to the United States. As this virus has been associated with severe illness, it poses a threat to vulnerable populations-including pregnant women. The obstetric population already faces multiple barriers to receiving quality healthcare due to personal, environmental and economic barriers, now challenged with the additional risks of COVID-19 exposure and limited care in times much defined by social distancing. Assessment The current prenatal care framework requires patients to attend multiple in-office prenatal visits that can exponentially multiply depending on maternal and fetal comorbidities. To decrease the rate of transmission of the COVID-19 and limit exposure to patients, providers in Hillsborough County, Florida (and nationwide) are rapidly transitioning to telehealth. The use of a virtual care model allows providers to reduce in-person visits and incorporate virtual visits into the schedule of prenatal care. Conclusion Due to the COVID-19 pandemic, implementation of telehealth and telehealth have become crucial to ensure the safe and effective delivery of obstetric care. This implementation is one that will continue to require attention to planning, procedures and processes, and thoughtful evaluation to ensure the sustainability of telehealth and telehealth post COVID-19 pandemic.

Prenatal care is one of the most widely used preventive care services in the United States, yet prenatal care delivery recommendations have remained largely unchanged since just before World War II. The current prenatal care model can be improved to better serve modern patients and the health care providers who care for them in three key ways: 1) focusing more on promotion of health and wellness as opposed to primarily focusing on medical complications, 2) flexibly incorporating patient preferences, and 3) individualizing care. As key policymakers and stakeholders grapple with higher maternity care costs and poorer outcomes, including lagging access, equity, and maternal and infant morbidity and mortality in the United States compared with other high-income countries, the opportunity to improve prenatal care has been given insufficient attention. In this manuscript, we present a new conceptual model for prenatal care that incorporates both patients' medical and social needs into four phenotypes, and use human-centered design methods to describe how better matching patient needs with prenatal services can increase the use of high-value services and decrease the use of low-value services. Finally, we address some of the key challenges to implementing right-sized prenatal care, including capturing outcomes through research and payment.