Disorders of Potassium.

Abnormalities in serum potassium are commonly encountered in patients presenting to the emergency department. A variety of acute and chronic causes can lead to life-threatening illness in both hyperkalemia and hypokalemia. Here we summarize the relevant causes, risks, and treatment options for these frequently encountered disorders.

Whole-cell modeling of E. coli colonies enables quantification of single-cell heterogeneity in antibiotic responses.

Antibiotic resistance poses mounting risks to human health, as current antibiotics are losing efficacy against increasingly resistant pathogenic bacteria. Of particular concern is the emergence of multidrug-resistant strains, which has been rapid among Gram-negative bacteria such as Escherichia coli. A large body of work has established that antibiotic resistance mechanisms depend on phenotypic heterogeneity, which may be mediated by stochastic expression of antibiotic resistance genes. The link between such molecular-level expression and the population levels that result is complex and multi-scale. Therefore, to better understand antibiotic resistance, what is needed are new mechanistic models that reflect single-cell phenotypic dynamics together with population-level heterogeneity, as an integrated whole. In this work, we sought to bridge single-cell and population-scale modeling by building upon our previous experience in "whole-cell" modeling, an approach which integrates mathematical and mechanistic descriptions of biological processes to recapitulate the experimentally observed behaviors of entire cells. To extend whole-cell modeling to the "whole-colony" scale, we embedded multiple instances of a whole-cell E. coli model within a model of a dynamic spatial environment, allowing us to run large, parallelized simulations on the cloud that contained all the molecular detail of the previous whole-cell model and many interactive effects of a colony growing in a shared environment. The resulting simulations were used to explore the response of E. coli to two antibiotics with different mechanisms of action, tetracycline and ampicillin, enabling us to identify sub-generationally-expressed genes, such as the beta-lactamase ampC, which contributed greatly to dramatic cellular differences in steady-state periplasmic ampicillin and was a significant factor in determining cell survival.

Copper induces cell death by targeting lipoylated TCA cycle proteins.

Copper is an essential cofactor for all organisms, and yet it becomes toxic if concentrations exceed a threshold maintained by evolutionarily conserved homeostatic mechanisms. How excess copper induces cell death, however, is unknown. Here, we show in human cells that copper-dependent, regulated cell death is distinct from known death mechanisms and is dependent on mitochondrial respiration. We show that copper-dependent death occurs by means of direct binding of copper to lipoylated components of the tricarboxylic acid (TCA) cycle. This results in lipoylated protein aggregation and subsequent iron-sulfur cluster protein loss, which leads to proteotoxic stress and ultimately cell death. These findings may explain the need for ancient copper homeostatic mechanisms.

Vivarium: an interface and engine for integrative multiscale modeling in computational biology.

MOTIVATION: This article introduces Vivarium-software born of the idea that it should be as easy as possible for computational biologists to define any imaginable mechanistic model, combine it with existing models and execute them together as an integrated multiscale model. Integrative multiscale modeling confronts the complexity of biology by combining heterogeneous datasets and diverse modeling strategies into unified representations. These integrated models are then run to simulate how the hypothesized mechanisms operate as a whole. But building such models has been a labor-intensive process that requires many contributors, and they are still primarily developed on a case-by-case basis with each project starting anew. New software tools that streamline the integrative modeling effort and facilitate collaboration are therefore essential for future computational biologists. RESULTS: Vivarium is a software tool for building integrative multiscale models. It provides an interface that makes individual models into modules that can be wired together in large composite models, parallelized across multiple CPUs and run with Vivarium's discrete-event simulation engine. Vivarium's utility is demonstrated by building composite models that combine several modeling frameworks: agent-based models, ordinary differential equations, stochastic reaction systems, constraint-based models, solid-body physics and spatial diffusion. This demonstrates just the beginning of what is possible-Vivarium will be able to support future efforts that integrate many more types of models and at many more biological scales. AVAILABILITY AND IMPLEMENTATION: The specific models, simulation pipelines and notebooks developed for this article are all available at the vivarium-notebooks repository: https://github.com/vivarium-collective/vivarium-notebooks. Vivarium-core is available at https://github.com/vivarium-collective/vivarium-core, and has been released on Python Package Index. The Vivarium Collective (https://vivarium-collective.github.io) is a repository of freely available Vivarium processes and composites, including the processes used in Section 3. Supplementary Materials provide with an extensive methodology section, with several code listings that demonstrate the basic interfaces. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A community challenge to evaluate RNA-seq, fusion detection, and isoform quantification methods for cancer discovery.

The accurate identification and quantitation of RNA isoforms present in the cancer transcriptome is key for analyses ranging from the inference of the impacts of somatic variants to pathway analysis to biomarker development and subtype discovery. The ICGC-TCGA DREAM Somatic Mutation Calling in RNA (SMC-RNA) challenge was a crowd-sourced effort to benchmark methods for RNA isoform quantification and fusion detection from bulk cancer RNA sequencing (RNA-seq) data. It concluded in 2018 with a comparison of 77 fusion detection entries and 65 isoform quantification entries on 51 synthetic tumors and 32 cell lines with spiked-in fusion constructs. We report the entries used to build this benchmark, the leaderboard results, and the experimental features associated with the accurate prediction of RNA species. This challenge required submissions to be in the form of containerized workflows, meaning each of the entries described is easily reusable through CWL and Docker containers at https://github.com/SMC-RNA-challenge. A record of this paper's transparent peer review process is included in the supplemental information.

Disaster Diagnoses in Geriatric Patients with Abdominal Pain.

Care of geriatric patients with abdominal pain can pose significant diagnostic and therapeutic challenges to emergency physicians. Older adults rarely present with classic signs, symptoms, and laboratory abnormalities. The incidence of life-threatening emergencies, including abdominal aortic aneurysm, mesenteric ischemia, perforated viscus, and other surgical emergencies, is high. This article explores the evaluation and management of several important causes of abdominal pain in geriatric patients with an emphasis on high-risk presentations.

A Multi-Scale Approach to Modeling E. coli Chemotaxis.

The degree to which we can understand the multi-scale organization of cellular life is tied to how well our models can represent this organization and the processes that drive its evolution. This paper uses Vivarium-an engine for composing heterogeneous computational biology models into integrated, multi-scale simulations. Vivarium's approach is demonstrated by combining several sub-models of biophysical processes into a model of chemotactic E. coli that exchange molecules with their environment, express the genes required for chemotaxis, swim, grow, and divide. This model is developed incrementally, highlighting cross-compartment mechanisms that link E. coli to its environment, with models for: (1) metabolism and transport, with transport moving nutrients across the membrane boundary and metabolism converting them to useful metabolites, (2) transcription, translation, complexation, and degradation, with stochastic mechanisms that read real gene sequence data and consume base pairs and ATP to make proteins and complexes, and (3) the activity of flagella and chemoreceptors, which together support navigation in the environment.

36-year-old Male with Syncope.

CASE PRESENTATION: A 36-year-old incarcerated male presented to the emergency department (ED) after an episode concerning for syncope. The patient had nystagmus and ataxia on initial examination. DISCUSSION: There is a broad differential diagnosis for syncope, and for patients presenting to the ED we tend to focus on cardiogenic and neurologic causes. This case takes the reader through the differential diagnosis and systemic work-up of a patient presenting to the ED with syncope.

Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation.

The extensive heterogeneity of biological data poses challenges to analysis and interpretation. Construction of a large-scale mechanistic model of Escherichia coli enabled us to integrate and cross-evaluate a massive, heterogeneous dataset based on measurements reported by various groups over decades. We identified inconsistencies with functional consequences across the data, including that the total output of the ribosomes and RNA polymerases described by data are not sufficient for a cell to reproduce measured doubling times, that measured metabolic parameters are neither fully compatible with each other nor with overall growth, and that essential proteins are absent during the cell cycle-and the cell is robust to this absence. Finally, considering these data as a whole leads to successful predictions of new experimental outcomes, in this case protein half-lives.

Discovering the anti-cancer potential of non-oncology drugs by systematic viability profiling.

Anti-cancer uses of non-oncology drugs have occasionally been found, but such discoveries have been serendipitous. We sought to create a public resource containing the growth inhibitory activity of 4,518 drugs tested across 578 human cancer cell lines. We used PRISM, a molecular barcoding method, to screen drugs against cell lines in pools. An unexpectedly large number of non-oncology drugs selectively inhibited subsets of cancer cell lines in a manner predictable from the cell lines' molecular features. Our findings include compounds that killed by inducing PDE3A-SLFN12 complex formation; vanadium-containing compounds whose killing depended on the sulfate transporter SLC26A2; the alcohol dependence drug disulfiram, which killed cells with low expression of metallothioneins; and the anti-inflammatory drug tepoxalin, which killed via the multi-drug resistance protein ABCB1. The PRISM drug repurposing resource (https://depmap.org/repurposing) is a starting point to develop new oncology therapeutics, and more rarely, for potential direct clinical translation.

Exploring Integrative Analysis Using the BioMedical Evidence Graph.

PURPOSE: The analysis of cancer biology data involves extremely heterogeneous data sets, including information from RNA sequencing, genome-wide copy number, DNA methylation data reporting on epigenetic regulation, somatic mutations from whole-exome or whole-genome analyses, pathology estimates from imaging sections or subtyping, drug response or other treatment outcomes, and various other clinical and phenotypic measurements. Bringing these different resources into a common framework, with a data model that allows for complex relationships as well as dense vectors of features, will unlock integrated data set analysis. METHODS: We introduce the BioMedical Evidence Graph (BMEG), a graph database and query engine for discovery and analysis of cancer biology. The BMEG is unique from other biologic data graphs in that sample-level molecular and clinical information is connected to reference knowledge bases. It combines gene expression and mutation data with drug-response experiments, pathway information databases, and literature-derived associations. RESULTS: The construction of the BMEG has resulted in a graph containing > 41 million vertices and 57 million edges. The BMEG system provides a graph query-based application programming interface to enable analysis, with client code available for Python, Javascript, and R, and a server online at bmeg.io. Using this system, we have demonstrated several forms of cross-data set analysis to show the utility of the system. CONCLUSION: The BMEG is an evolving resource dedicated to enabling integrative analysis. We have demonstrated queries on the system that illustrate mutation significance analysis, drug-response machine learning, patient-level knowledge-base queries, and pathway level analysis. We have compared the resulting graph to other available integrated graph systems and demonstrated the former is unique in the scale of the graph and the type of data it makes available.

Evaluation of the Renal Transplant Recipient in the Emergency Department.

Renal transplants are becoming more and more frequent in the United States and worldwide. Studies demonstrate that these patients inevitably end up visiting an emergency department. In addition to typical medical and surgical problems encountered in the general population, this group of patients has unique problems arising from their immunocompromised state and also due to side effects of the medications required. This article discusses these risks and management decisions that the emergency department physician should be aware of in order to prevent adverse outcomes for the patient and transplanted kidney.

Association of Extracellular Vesicle Biomarkers With Alzheimer Disease in the Baltimore Longitudinal Study of Aging.

IMPORTANCE: Blood biomarkers able to diagnose Alzheimer disease (AD) at the preclinical stage would enable trial enrollment when the disease is potentially reversible. Plasma neuronal-enriched extracellular vesicles (nEVs) of patients with AD were reported to exhibit elevated levels of phosphorylated (p) tau, Aß42, and phosphorylated insulin receptor substrate 1 (IRS-1). OBJECTIVE: To validate nEV biomarkers as AD predictors. DESIGN, SETTING, PARTICIPANTS: This case-control study included longitudinal plasma samples from cognitively normal participants in the Baltimore Longitudinal Study of Aging (BLSA) cohort who developed AD up to January 2015 and age- and sex-matched controls who remained cognitively normal over a similar length of follow-up. Repeated samples were blindly analyzed over 1 year from participants with clinical AD and controls from the Johns Hopkins Alzheimer Disease Research Center (JHADRC). Data were collected from September 2016 to January 2018. Analyses were conducted in March 2019. MAIN OUTCOMES AND MEASURES: Neuronal-enriched extracellular vesicles were immunoprecipitated; tau, Aß42, and IRS-1 biomarkers were quantified by immunoassays; and nEV concentration and diameter were determined by nanoparticle tracking analysis. Levels and longitudinal trajectories of nEV biomarkers between participants with future AD and control participants were compared. RESULTS: Overall, 887 longitudinal plasma samples from 128 BLSA participants who eventually developed AD and 222 age and sex-matched controls who remained cognitively normal were analyzed. Participants were followed up (from earliest sample to AD symptom onset) for a mean (SD) of 3.5 (2.31) years (range, 0-9.73 years). Overall, 161 participants were included in the training set, and 80 were in the test set. Participants in the BLSA cohort with future AD (mean [SD] age, 79.09 [7.02] years; 68 women [53.13%]) had longitudinally higher p-tau181, p-tau231, pSer312-IRS-1, pY-IRS-1, and nEV diameter than controls (mean [SD] age, 76.2 [7.36] years; 110 women [50.45%]) but had similar Aß42, total tau, TSG101, and nEV concentration. In the training BLSA set, a model combining preclinical longitudinal data achieved 89.6% area under curve (AUC), 81.8% sensitivity, and 85.8% specificity for predicting AD. The model was validated in the test BLSA set (80% AUC, 55.6% sensitivity, 88.7% specificity). Preclinical levels of nEV biomarkers were associated with cognitive performance. In addition, 128 repeated samples over 1 year from 64 JHADRC participants with clinical AD and controls were analyzed. In the JHADRC cohort (35 participants with AD: mean [SD] age, 74.03 [8.73] years; 18 women [51.43%] and 29 controls: mean [SD] age, 72.14 [7.86] years; 23 women [79.31%]), nEV biomarkers achieved discrimination with 98.9% AUC, 100% sensitivity, and 94.7% specificity in the training set and 76.7% AUC, 91.7% sensitivity, and 60% specificity in the test set. CONCLUSIONS AND RELEVANCE: We validated nEV biomarker candidates and further demonstrated that their preclinical longitudinal trajectories can predict AD diagnosis. These findings motivate further development of nEV biomarkers toward a clinical blood test for AD.

Mice lacking the transcriptional regulator Bhlhe40 have enhanced neuronal excitability and impaired synaptic plasticity in the hippocampus.

Bhlhe40 is a transcription factor that is highly expressed in the hippocampus; however, its role in neuronal function is not well understood. Here, we used Bhlhe40 null mice on a congenic C57Bl6/J background (Bhlhe40 KO) to investigate the impact of Bhlhe40 on neuronal excitability and synaptic plasticity in the hippocampus. Bhlhe40 KO CA1 neurons had increased miniature excitatory post-synaptic current amplitude and decreased inhibitory post-synaptic current amplitude, indicating CA1 neuronal hyperexcitability. Increased CA1 neuronal excitability was not associated with increased seizure severity as Bhlhe40 KO relative to +/+ (WT) control mice injected with the convulsant kainic acid. However, significant reductions in long term potentiation and long term depression at CA1 synapses were observed in Bhlhe40 KO mice, indicating impaired hippocampal synaptic plasticity. Behavioral testing for spatial learning and memory on the Morris Water Maze (MWM) revealed that while Bhlhe40 KO mice performed similarly to WT controls initially, when the hidden platform was moved to the opposite quadrant Bhlhe40 KO mice showed impairments in relearning, consistent with decreased hippocampal synaptic plasticity. To investigate possible mechanisms for increased neuronal excitability and decreased synaptic plasticity, a whole genome mRNA expression profile of Bhlhe40 KO hippocampus was performed followed by a chromatin immunoprecipitation sequencing (ChIP-Seq) screen of the validated candidate genes for Bhlhe40 protein-DNA interactions consistent with transcriptional regulation. Of the validated genes identified from mRNA expression analysis, insulin degrading enzyme (Ide) had the most significantly altered expression in hippocampus and was significantly downregulated on the RNA and protein levels; although Bhlhe40 did not occupy the Ide gene by ChIP-Seq. Together, these findings support a role for Bhlhe40 in regulating neuronal excitability and synaptic plasticity in the hippocampus and that indirect regulation of Ide transcription may be involved in these phenotypes.

In Vitro and In Vivo Detection of Mitophagy in Human Cells, C. Elegans, and Mice.

Mitochondria are the powerhouses of cells and produce cellular energy in the form of ATP. Mitochondrial dysfunction contributes to biological aging and a wide variety of disorders including metabolic diseases, premature aging syndromes, and neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD). Maintenance of mitochondrial health depends on mitochondrial biogenesis and the efficient clearance of dysfunctional mitochondria through mitophagy. Experimental methods to accurately detect autophagy/mitophagy, especially in animal models, have been challenging to develop. Recent progress towards the understanding of the molecular mechanisms of mitophagy has enabled the development of novel mitophagy detection techniques. Here, we introduce several versatile techniques to monitor mitophagy in human cells, Caenorhabditis elegans (e.g., Rosella and DCT-1/ LGG-1 strains), and mice (mt-Keima). A combination of these mitophagy detection techniques, including cross-species evaluation, will improve the accuracy of mitophagy measurements and lead to a better understanding of the role of mitophagy in health and disease.

In a randomized trial in prostate cancer patients, dietary protein restriction modifies markers of leptin and insulin signaling in plasma extracellular vesicles.

Obesity, metabolic syndrome, and hyperleptinemia are associated with aging and age-associated diseases including prostate cancer. One experimental approach to inhibit tumor growth is to reduce dietary protein intake and hence levels of circulating amino acids. Dietary protein restriction (PR) increases insulin sensitivity and suppresses prostate cancer cell tumor growth in animal models, providing a rationale for clinical trials. We sought to demonstrate that biomarkers derived from plasma extracellular vesicles (EVs) reflect systemic leptin and insulin signaling and respond to dietary interventions. We studied plasma samples from men with prostate cancer awaiting prostatectomy who participated in a randomized trial of one month of PR or control diet. We found increased levels of leptin receptor in the PR group in total plasma EVs and in a subpopulation of plasma EVs expressing the neuronal marker L1CAM. Protein restriction also shifted the phosphorylation status of the insulin receptor signal transducer protein IRS1 in L1CAM+ EVs in a manner suggestive of improved insulin sensitivity. Dietary PR modifies indicators of leptin and insulin signaling in circulating EVs. These findings are consistent with improved insulin and leptin sensitivity in response to PR and open a new window for following physiologic responses to dietary interventions in humans.

Management of Crashing Patients with Pulmonary Hypertension.

Critically ill patients with pulmonary hypertension (PH) often seem well, but they can decompensate dramatically in a short time. PH has several causes, classes, and complications; but the natural progression eventually leads to right ventricular failure, which can be extraordinarily difficult to manage. The purpose of this review is to discuss the causes, signs, and symptoms of PH as well as its management strategies and emergent complications. Treatment options are often limited, so it is imperative that the emergency department physician can recognize and manage these patients in a timely fashion.

Hypothyroidism: causes, killers, and life-saving treatments.

Hypothyroidism is a very common, yet often overlooked disease. It can have a myriad of signs and symptoms, and is often nonspecific. Identification requires analysis of thyroid hormones circulating in the bloodstream, and treatment is simply replacement with exogenous hormone, usually levothyroxine (Synthroid). The deadly manifestation of hypothyroidism is myxedema coma. Similarly nonspecific and underrecognized, treatment with exogenous hormone is necessary to decrease the high mortality rate.

Abdominal emergencies in the geriatric patient.

Abdominal pain is one of the most frequent reasons that elderly people visit the emergency department (ED). In this article, we review the deadliest causes of abdominal pain in this population, including mesenteric ischemia, abdominal aortic aneurysm, and appendicitis and potentially lethal non-abdominal causes. We also highlight the pitfalls in diagnosing, or rather misdiagnosing, these clinical entities.