Using publicly available, interactive epidemiological dashboards: an innovative approach to sharing data from the Rakai Community Cohort Study.

Objectives: Public sharing of de-identified biomedical data promotes collaboration between researchers and accelerates the development of disease prevention and treatment strategies. However, open-access data sharing presents challenges to researchers who need to protect the privacy of study participants, ensure that data are used appropriately, and acknowledge the inputs of all involved researchers. This article presents an approach to data sharing which addresses the above challenges by using a publicly available dashboard with de-identified, aggregated participant data from a large HIV surveillance cohort. Materials and Methods: Data in this study originated from the Rakai Community Cohort Study (RCCS), which was integrated into a centralized data mart as part of a larger data management strategy for the Rakai Health Sciences Program in Uganda. These data were used to build a publicly available, protected health information (PHI)-secured visualization dashboard for general research use. Results: Using two unique case studies, we demonstrate the capability of the dashboard to generate the following hypotheses: firstly, that HIV prevention strategies ART and circumcision have differing levels of impact depending on the marital status of investigated communities; secondly, that ART is very successful in comparison to circumcision as an interventional strategy in certain communities. Discussion: The democratization of large-scale anonymized epidemiological data using public-facing dashboards has multiple benefits, including facilitated exploration of research data and increased reproducibility of research findings. Conclusion: By allowing the public to explore data in depth and form new hypotheses, public-facing dashboard platforms have significant potential to generate new relationships and collaborations and further scientific discovery and reproducibility.

Natural products dereplication by diffusion ordered NMR spectroscopy (DOSY).

Diffusion-ordered NMR spectroscopy (DOSY) can be used to analyze mixtures of compounds since resonances deriving from different compounds are distinguished by their diffusion coefficients (D). Previously, DOSY has mostly been used for organometallic and polymer analysis, we have now applied DOSY to investigate diffusion coefficients of structurally diverse organic compounds such as natural products (NP). The experimental Ds derived from 55 diverse NPs has allowed us to establish a power law relationship between D and molecular weight (MW) and therefore predict MW from experimental D. We have shown that D is also affected by factors such as hydrogen bonding, molar density and molecular shape of the compound and we have generated new models that incorporate experimentally derived variables for these factors so that more accurate predictions of MW can be calculated from experimental D. The recognition that multiple physicochemical properties affect D has allowed us to generate a polynomial equation based on multiple linear regression analysis of eight calculated physicochemical properties from 63 compounds to accurately correlate predicted D with experimental D for any known organic compound. This equation has been used to calculate predicted D for 217 043 compounds present in a publicly available natural product database (DEREP-NP) and to dereplicate known NPs in a mixture based on matching of experimental D and structural features derived from NMR analysis with predicted D and calculated structural features in the database. These models have been validated by the dereplication of a mixture of two known sesquiterpenes obtained from Tasmannia xerophila and the identification of new alkaloids from the bryozoan Amathia lamourouxi. These new methodologies allow the MW of compounds in mixtures to be predicted without the need for MS analysis, the dereplication of known compounds and identification of new compounds based solely on parameters derived by DOSY NMR.

Longitudinal assessment of utilities in patients with migraine: an analysis of erenumab randomized controlled trials.

BACKGROUND: Cost-effectiveness analyses in patients with migraine require estimates of patients' utility values and how these relate to monthly migraine days (MMDs). This analysis examined four different modelling approaches to assess utility values as a function of MMDs. METHODS: Disease-specific patient-reported outcomes from three erenumab clinical studies (two in episodic migraine [NCT02456740 and NCT02483585] and one in chronic migraine [NCT02066415]) were mapped to the 5-dimension EuroQol questionnaire (EQ-5D) as a function of the Migraine-Specific Quality of Life Questionnaire (MSQ) and the Headache Impact Test (HIT-6™) using published algorithms. The mapped utility values were used to estimate generic, preference-based utility values suitable for use in economic models. Four models were assessed to explain utility values as a function of MMDs: a linear mixed effects model with restricted maximum likelihood (REML), a fractional response model with logit link, a fractional response model with probit link and a beta regression model. RESULTS: All models tested showed very similar fittings. Root mean squared errors were similar in the four models assessed (0.115, 0.114, 0.114 and 0.114, for the linear mixed effect model with REML, fractional response model with logit link, fractional response model with probit link and beta regression model respectively), when mapped from MSQ. Mean absolute errors for the four models tested were also similar when mapped from MSQ (0.085, 0.086, 0.085 and 0.085) and HIT-6 and (0.087, 0.088, 0.088 and 0.089) for the linear mixed effect model with REML, fractional response model with logit link, fractional response model with probit link and beta regression model, respectively. CONCLUSIONS: This analysis describes the assessment of longitudinal approaches in modelling utility values and the four models proposed fitted the observed data well. Mapped utility values for patients treated with erenumab were generally higher than those for individuals treated with placebo with equivalent number of MMDs. Linking patient utility values to MMDs allows utility estimates for different levels of MMD to be predicted, for use in economic evaluations of preventive therapies. TRIAL REGISTRATION: ClinicalTrials.gov numbers of the trials used in this study: STRIVE, NCT02456740 (registered May 14, 2015), ARISE, NCT02483585 (registered June 12, 2015) and NCT02066415 (registered Feb 17, 2014).

Tuning of mRNA stability through altering 3'-UTR sequences generates distinct output expression in a synthetic circuit driven by p53 oscillations.

Synthetic biological circuits that can generate outputs with distinct expression dynamics are useful for a variety of biomedical and industrial applications. We present a method to control output dynamics by altering output mRNA decay rates. Using oscillatory expression of the transcription factor p53 as the circuit regulator, we use two approaches for controlling target gene transcript degradation rates based on the output gene's 3'-untranslated region (3'-UTR): introduction of copies of destabilizing AU-rich elements into the 3'-UTR or swapping in naturally occurring 3'-UTRs conferring different transcript stabilities. As a proof of principle, we apply both methods to control the expression dynamics of a fluorescent protein and visualize the circuit output dynamics in single living cells. We then use the naturally occurring 3'-UTR approach to restore apoptosis in a tunable manner in a cancer cell line deficient for caspase-3 expression. Our method can be readily adapted to regulate multiple outputs each with different expression dynamics under the control of a single naturally occurring or synthetically constructed biological oscillator.

Protein stability of p53 targets determines their temporal expression dynamics in response to p53 pulsing.

In response to DNA damage, the transcription factor p53 accumulates in a series of pulses. While p53 dynamics play a critical role in regulating stress responses, how p53 pulsing affects target protein expression is not well understood. Recently, we showed that p53 pulses generate diversity in target mRNA expression dynamics; however, given that mRNA and protein expression are not necessarily well correlated, it remains to be determined how p53 pulses impact target protein expression. Using computational and experimental approaches, we show that target protein decay rates filter p53 pulses: Distinct target protein expression dynamics are generated depending on the relationship between p53 pulse frequency and target mRNA and protein stability. Furthermore, by mutating the targets MDM2 and PUMA to alter their stabilities, we show that downstream pathways are sensitive to target protein decay rates. This study delineates the mechanisms by which p53 dynamics play a crucial role in orchestrating the timing of events in the DNA damage response network.

Migraine day frequency in migraine prevention: longitudinal modelling approaches.

BACKGROUND: Health economic models are critical tools to inform reimbursement agencies on health care interventions. Many clinical trials report outcomes using the frequency of an event over a set period of time, for example, the primary efficacy outcome in most clinical trials of migraine prevention is mean change in the frequency of migraine days (MDs) per 28 days (monthly MDs [MMD]) relative to baseline for active treatment versus placebo. Using these cohort-level endpoints in economic models, accounting for variation among patients is challenging. In this analysis, parametric models of change in MMD for migraine preventives were assessed using data from erenumab clinical studies. METHODS: MMD observations from the double-blind phases of two studies of erenumab were used: one in episodic migraine (EM) (NCT02456740) and one in chronic migraine (CM) (NCT02066415). For each trial, two longitudinal regression models were fitted: negative binomial and beta binomial. For a thorough comparison we also present the fitting from the standard multilevel Poisson and the zero inflated negative binomial. RESULTS: Using the erenumab study data, both the negative binomial and beta-binomial models provided unbiased estimates relative to observed trial data with well-fitting distribution at various time points. CONCLUSIONS: This proposed methodology, which has not been previously applied in migraine, has shown that these models may be suitable for estimating MMD frequency. Modelling MMD using negative binomial and beta-binomial distributions can be advantageous because these models can capture intra- and inter-patient variability so that trial observations can be modelled parametrically for the purposes of economic evaluation of migraine prevention. Such models have implications for use in a wide range of disease areas when assessing repeated measured utility values.

Reducing Drug Wastage in Pharmaceuticals Dosed by Weight or Body Surface Areas by Optimising Vial Sizes.

BACKGROUND: When pharmaceuticals are administered based on patient characteristics (for example weight or body surface area), an amount of product will be unused and must be disposed of. This wastage represents inefficiency and can distort decision making. METHODS: We present a method for the analysis of optimum fill volumes of pharmaceuticals to minimise wastage across a patient population, using publicly available data. Wastage for patients at each 'step' e.g. by kg of bodyweight is calculated, the frequency of each of these steps in the structure of the population is then estimated using the method of moments, with wastage then estimated for each 'step' multiplied by its prevalence. Illustrative examples of pembrolizumab and cabazitaxel show how wastage could be reduced using UK population data, whilst simultaneously reducing administrative burden. RESULTS: Changing the available vial sizes for pembrolizumab (available as 50 mg/100 mg vials) to 70 mg/100 mg, wastage could be cut from 13.3% to 8.7%. For cabazitaxel (only 60 mg vials available), increasing the fill to 70 mg could reduce wastage from 19.4% to 18.8%, or alternatively, adding a 12.5 mg vial reduce this to 6.5%. A secondary finding is that wastage is higher when the larger vial size is perfectly divisible by the smaller vial size. CONCLUSIONS: Reductions in wastage have the potential to reduce the cost of manufacturing medicines, which is not necessarily low for novel products. These cost reductions could lead to increased profit (at the same prices), constant profit with a better return rate (at lower prices), or a combination of the two. Most importantly, they would improve the efficiency of the health-care sector, increasing funding available to treat patients.

Costs of Acute Headache Medication Use and Productivity Losses Among Patients with Migraine: Insights from Three Randomized Controlled Trials.

BACKGROUND: Migraine is associated with a substantial physical and emotional burden for patients. There is also a large economic burden associated with migraine, in terms of lost productivity and healthcare resource use. By reducing the number of monthly migraine days (MMD) experienced by patients, effective preventive treatments can reduce acute medication use and costs of lost productivity. METHODS: Patient level data from three erenumab clinical trials (NCT02456740, NCT02483585 and NCT02066415) were combined and migraine day frequencies were examined. The number of days per month on which patients used acute medication was estimated as a function of MMD. Productivity losses were estimated based on patient responses to the Migraine Disability Assessment questionnaire. Zero-inflated Poisson regression models were used to predict acute medication use and productivity losses per MMD. RESULTS: The results demonstrated that as MMD increased, use of acute medication also increased. Similarly, as MMD increased, loss of productivity (due to absenteeism and presenteeism) also increased. The relationship of MMD to both acute headache medication use and lost productivity was non-linear, with marginal outcomes increasing with frequency. CONCLUSIONS: As MMD increased, acute medication use and productivity loss also increased, but the relationship was non-linear. Therefore, it is important that the distribution of MMD patients is accounted for when estimating the outcomes of migraine patients. By reducing the MMD experienced by patients, effective preventive agents may reduce the requirement for acute medication and also reduce productivity loss, which may translate into potential economic savings.

Estimating the clinical effectiveness and value-based price range of erenumab for the prevention of migraine in patients with prior treatment failures: a US societal perspective.

BACKGROUND: Frequent migraine with four or more headache days per month is a common, disabling neurovascular disease. From a US societal perspective, this analysis models the clinical efficacy and estimates the value-based price (VBP) for erenumab, a fully human monoclonal antibody that inhibits the calcitonin gene-related peptide receptor. METHODS: A Markov health state transition model was developed to estimate the incremental costs, quality-adjusted life-years (QALYs), and value-based price range for erenumab in migraine prevention. The model comprises "on preventive treatment", "off preventive treatment", and "death" health states across a 10-year time horizon. The evaluation compared erenumab to no preventive treatment in episodic and chronic migraine patients that have failed at least one preventive therapy. Therapeutic benefits are based on estimated changes in monthly migraine days (MMD) from erenumab pivotal clinical trials and a network meta-analysis of migraine studies. Utilities were estimated using previously published mapping algorithms. A VBP analysis was performed to identify maximum erenumab annual prices at willingness-to-pay (WTP) thresholds of $100,000-$200,000 per QALY. Estimates of VBP under different scenarios such as choice of different comparators, assumptions around inclusion of placebo effect, and exclusion of work productivity losses were also generated. RESULTS: Erenumab resulted in incremental QALYs of 0.185 vs supportive care (SC) and estimated cost offsets due to reduced MMD of $8,482 over 10 years, with an average duration of treatment of 2.01 years. The estimated VBP at WTP thresholds of $100,000-$200,000 for erenumab compared to SC ranged from $14,238-$23,998. VBP estimates including the placebo effect and excluding work productivity ranged from $7,445-$13,809; increasing to $12,151-$18,589 with onabotulinumtoxinA as a comparator in chronic migraine. CONCLUSION: Erenumab is predicted to reduce migraine-related direct and indirect costs, and increase QALYs compared to SC.

Global Inhibition with Specific Activation: How p53 and MYC Redistribute the Transcriptome in the DNA Double-Strand Break Response.

In response to stresses, cells often halt normal cellular processes, yet stress-specific pathways must bypass such inhibition to generate effective responses. We investigated how cells redistribute global transcriptional activity in response to DNA damage. We show that an oscillatory increase of p53 levels in response to double-strand breaks drives a counter-oscillatory decrease of MYC levels. Using RNA sequencing (RNA-seq) of newly synthesized transcripts, we found that p53-mediated reduction of MYC suppressed general transcription, with the most highly expressed transcripts reduced to a greater extent. In contrast, upregulation of p53 targets was relatively unaffected by MYC suppression. Reducing MYC during the DNA damage response was important for cell-fate regulation, as counteracting MYC repression reduced cell-cycle arrest and elevated apoptosis. Our study shows that global inhibition with specific activation of transcriptional pathways is important for the proper response to DNA damage; this mechanism may be a general principle used in many stress responses.

Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards.

Gene expression measurements from bulk populations of cells can obscure the considerable transcriptomic variation of individual cells within those populations. Single-cell gene expression measurements can help assess the role of noise in gene expression, identify correlations in the expression of pairs of genes, and reveal subpopulations of cells that respond differently to a stimulus. Here, we describe a procedure to measure the expression of up to 96 genes in single mammalian cells isolated from a population growing in tissue culture. Cells are sorted into lysis buffer by fluorescence-activated cell sorting (FACS), and the mRNA species of interest are reverse-transcribed and amplified. Gene expression is then measured using a microfluidic real-time PCR machine, which performs up to 96 qPCR assays on up to 96 samples at a time. We also describe the generation and use of PCR amplicon standards to enable the estimation of the absolute number of each transcript. Compared with other methods of measuring gene expression in single cells, this approach allows for the quantification of more distinct transcripts than RNA FISH at a lower cost than RNA-Seq.

The Cost of Costing Treatments Incorrectly: Errors in the Application of Drug Prices in Economic Evaluation Due to Failing to Account for the Distribution of Patient Weight.

BACKGROUND: The cost of pharmaceuticals dosed by weight or body surface area (BSA) can be estimated in several ways for economic evaluations. A review of 20 recent National Institute for Health and Care Excellence appraisals showed that 17 of them took the mean weight or BSA of patients, 2 costed the individual patient data from trials, and 2 fitted a distribution to patient-level data. OBJECTIVES: To investigate the estimated drug costs using different methodologies to account for patient characteristics for pharmaceuticals with a weight- or BSA-based posology. The secondary objective was to explore the suitability of general population data as a proxy for patient-level data. METHODS: Patient-level data were pooled from three clinical trials and used to calculate a hypothetical cost per administration of eight licensed pharmaceuticals, applying the three methods used in recent National Institute for Health and Care Excellence appraisals. The same analysis was performed using data from the Health Survey for England (in place of patient-level data) to investigate the validity of using general population data as a substitute for patient-level data. RESULTS: Compared with using patient-level data from clinical trials, the mean patient characteristics (weight or BSA) led to an underestimation of drug cost by 6.1% (range +1.5% to -25.5%). Fitting a distribution to patient-level data led to a mean difference of +0.04%. All estimates were consistent using general population data. CONCLUSIONS: Estimation of drug costs in health economic evaluation should account for the distribution in weight or BSA to produce accurate results. When patient data are not available, general population data may be used as an alternative.

p53 Pulses Diversify Target Gene Expression Dynamics in an mRNA Half-Life-Dependent Manner and Delineate Co-regulated Target Gene Subnetworks.

The transcription factor p53 responds to DNA double-strand breaks by increasing in concentration in a series of pulses of fixed amplitude, duration, and period. How p53 pulses influence the dynamics of p53 target gene expression is not understood. Here, we show that, in bulk cell populations, patterns of p53 target gene expression cluster into groups with stereotyped temporal behaviors, including pulsing and rising dynamics. These behaviors correlate statistically with the mRNA decay rates of target genes: short mRNA half-lives produce pulses of gene expression. This relationship can be recapitulated by mathematical models of p53-dependent gene expression in single cells and cell populations. Single-cell transcriptional profiling demonstrates that expression of a subset of p53 target genes is coordinated across time within single cells; p53 pulsing attenuates this coordination. These results help delineate how p53 orchestrates the complex DNA damage response and give insight into the function of pulsatile signaling pathways.

Using computational modeling and experimental synthetic perturbations to probe biological circuits.

This chapter describes approaches for using computational modeling of synthetic biology perturbations to analyze endogenous biological circuits, with a particular focus on signaling and metabolic pathways. We describe a bottom-up approach in which ordinary differential equations are constructed to model the core interactions of a pathway of interest. We then discuss methods for modeling synthetic perturbations that can be used to investigate properties of the natural circuit. Keeping in mind the importance of the interplay between modeling and experimentation, we next describe experimental methods for constructing synthetic perturbations to test the computational predictions. Finally, we present a case study of the p53 tumor-suppressor pathway, illustrating the process of modeling the core network, designing informative synthetic perturbations in silico, and testing the predictions in vivo.

A comparison of the cost-effectiveness of treatment of prolonged acute convulsive epileptic seizures in children across Europe.

In the majority of children and adolescents with epilepsy, optimal drug therapy adequately controls their condition. However, among the remaining patients who are still uncontrolled despite mono-, bi- or tri-therapy with chronic anti-epileptic treatment, a rescue medication is required. In Western Europe, the licensed medications available for first-line treatment of prolonged acute convulsive seizures (PACS) vary widely, and so comparators for clinical and economic evaluation are not consistent. No European guidelines currently exist for the treatment of PACS in children and adolescents and limited evidence is available for the effectiveness of treatments in the community setting. The authors present cost-effectiveness data for BUCCOLAM® (midazolam oromucosal solution) for the treatment of PACS in children and adolescents in the context of the treatment pathway in seven European countries in patients from 6 months to 18 years. For each country, the health economic model consisted of a decision tree, with decision nodes informed by clinical data and expert opinion obtained via a Delphi methodology. The events modelled are those associated with a patient experiencing a seizure in the community setting. The model assessed the likelihood of medication being administered successfully and of seizure cessation. The associated resource use was also modelled, and ambulance call-outs and hospitalisations were considered. The patient's quality of life was estimated by clinicians, who completed a five-level EuroQol five dimensions questionnaire from the perspective of a child or adolescent suffering a seizure. Despite differences in current therapy, treatment patterns and healthcare costs in all countries assessed, BUCCOLAM was shown to be cost saving and offered increased health-related benefits for patients in the treatment of PACS compared with the current local standard of care.

A cost-utility analysis of degarelix in the treatment of advanced hormone-dependent prostate cancer in the United Kingdom.

OBJECTIVE: To determine the cost-effectiveness of the treatment of advanced hormone-dependent prostate cancer with degarelix compared to luteinizing hormone-releasing hormone (LHRH) agonists in the UK using the latest available evidence and the model submitted to AWMSG. METHODS: A cost-effectiveness model was developed from the perspective of the UK National Health Service evaluating monthly injection of degarelix against 3-monthly leuprorelin therapy plus anti-androgen flare cover for the first-line treatment of patients with advanced (locally advanced or metastatic) hormone-dependent prostate cancer. A Markov process model was constructed using the patient population characteristics and efficacy information from the CS21 Phase III clinical trial and associated extension study (CS21A). The intention-to-treat (ITT) population and a high-risk sub-group with a PSA level >20 ng/mL were modeled. RESULTS: In the base-case analysis using the patient access scheme (PAS) price, degarelix was dominant compared to leuprorelin with cost savings of £3633 in the ITT population and £4310 in the PSA > 20 ng/mL sub-group. The chance of being cost-effective was 95% in the ITT population and 96% in the PSA > 20 ng/mL sub-group at a threshold of £20,000 per quality-adjusted life-year (QALY). In addition, degarelix remained dominant when PSA progression was assumed equal and only the benefits of preventing testosterone flare were taken into account. Treatment with degarelix also remained dominant in both populations when the list price was used. The additional investment required to treat patients with degarelix could be offset in 19 months for the ITT population and 13 months for the PSA > 20 ng/mL population. The model was most sensitive to the hazard ratio assumed for PSA progression between degarelix and leuprorelin and the quality-of-life (utility) of patients receiving palliative care. CONCLUSION: Degarelix is likely to be cost-effective compared to leuprorelin plus anti-androgen flare cover in the first-line treatment of advanced hormone-dependent prostate cancer.

Don't let go of the rope: reducing readmissions by recognizing hospitals' fiduciary duties to their discharged patients.

In the early years of the twenty-first century, it was widely speculated that massive, multi-purpose hospitals were becoming the "dinosaurs" of health care, to be largely replaced by community-based clinics providing specialty services on an outpatient basis. Hospitals, however, have roared back to life, in part by reworking their business model. There has been a wave of consolidations and acquisitions (including acquisitions of community-based clinics), with deals valued at $7.9 billion in 2011, the most in a decade, and the number of deals increasing another 18% in 2012. The costs of hospital care are enormous, with 31.5% ($851 billion) of the total health expenditures in the United States in 2011 devoted to these services. Hospitals are (1) placing growing emphasis on increasing revenue and decreasing costs; (2) engaging in pervasive marketing campaigns encouraging patients to view hospitals as an all-purpose care provider; (3) geographically targeting the expansion of their services to "capture" well-insured patients, while placing greater pressure on patients to pay for the services delivered; (4) increasing their size, wealth, and clout, with two-thirds of hospitals undertaking renovations or additional construction and smaller hospitals being squeezed out, and (5) expanding their use of hospital-employed physicians, rather than relying on community-based physicians with hospital privileges, and exercising greater control over medical staff. Hospitals have become so pivotal in the U.S. healthcare system that the Patient Protection and Affordable Care Act of 2010 (PPACA) frequently targeted them as a vehicle to enhance patient safety and control escalating health care costs. One such provision--the Hospital Readmissions Reduction Program, which goes into effect in fiscal year 2013--will reduce payments ordinarily made to hospitals if they have an "excess readmission" rate. It is estimated that adverse events following a hospital discharge impact as many as 19% of all discharged patients. When hospitals and similar health care facilities fail to adequately manage the discharge of their patients, devastating medical emergencies and sizeable healthcare costs can result. The urgency to better manage these discharges is compounded by the fact that the average length of hospital stays continues to shorten, potentially increasing the number of discharged patients who are at considerable risk of relapse. Also exacerbating the problem is a lack of clarity regarding who, if anyone, is responsible for these patients following discharge. Confusion over who bears responsibility for discharge-related preparation and community outreach, concerns about compensation, a lack of clear institutional policies, and the absence of legal mandates that patients be properly prepared for and monitored after discharge all contribute to the potential abandonment of patients at a crucial juncture. Although the PPACA establishes financial incentives for hospitals and similar facilities to combat the long-standing problem of high readmission rates, it does not provide a remedy for patients who have suffered avoidable harm after being discharged without adequate preparation or post-discharge assistance. This omission is particularly problematic as existing legal remedies, including medical malpractice suits, have provided little recourse for patients who have suffered injury that could have been prevented through the implementation of reasonable discharge-related policies. To protect the many patients who are highly vulnerable to complications following discharge and to provide them redress when needed services are not provided, hospitals' obligations to these patients should be recognized for what they are: a fiduciary duty to provide adequate discharge preparation and post-discharge services. The recognition of this duty is driven by changes in the nature of hospital care that enhance the perception that hospitals have become a "big business" that should "carry their own freight." Properly interpreted, this duty requires facilities to implement an appropriate discharge plan and provide post-discharge services for a period of time commensurate with a patient's continuing health risks. Notably, this is not the same as a generalized duty to provide all patients with continuing post-discharge treatment. It is a more limited obligation to offer necessary clarification and direction to patients upon discharge, and to institute a reasonable post-discharge monitoring program for patients with continuing health risks.

Regulation of SREBP during hypoxia requires Ofd1-mediated control of both DNA binding and degradation.

Cells adapt to changes in ambient oxygen by changing their gene expression patterns. In fission yeast, the sterol regulatory element-binding protein Sre1 is proteolytically cleaved under low oxygen, and its N-terminal segment (Sre1N) serves as a hypoxic transcription factor. When oxygen is present, the prolyl hydroxylase Ofd1 down-regulates Sre1N activity in two ways: first, by inhibiting its binding to DNA, and second, by accelerating its degradation. Here we use a mathematical model to assess what each of these two regulatory functions contributes to the hypoxic response of the cell. By disabling individual regulatory functions in the model, which would be difficult in vivo, we found that the Ofd1 function of inhibiting Sre1N binding to DNA is essential for oxygen-dependent Sre1N regulation. The other Ofd1 function of accelerating Sre1N degradation is necessary for the yeast to quickly turn off its hypoxic response when oxygen is restored. In addition, the model predicts that increased Ofd1 production at low oxygen plays an important role in the hypoxic response, and the model indicates that the Ofd1 binding partner Nro1 tunes the response to oxygen. This model quantifies our understanding of a novel oxygen-sensing mechanism that is widely conserved.

Identifying a static nonlinear structure in a biological system using noisy, sparse data.

When part of a biological system cannot be investigated directly by experimentation, we face the problem of structure identification: how can we construct a model for an unknown part of a mostly known system using measurements gathered from its input and output? This problem is especially difficult to solve when the measurements available are noisy and sparse, i.e. widely and unevenly spaced in time, as is common when measuring biological quantities at the cellular level. Here we present a procedure to identify a static nonlinearity embedded between two dynamical systems using noisy, sparse measurements. To reduce the level of error caused by measurement noise, we introduce the concept of weighted-sum predictability. If we make the input and output subsystems weighted-sum predictable and normalize the measurements to their weighted sum, we achieve better noise reduction than through normalizing to a loading control. We then interpolate the normalized measurements to obtain continuous input and output signals, with which we solve directly for the input-output characteristics of the unknown static nonlinearity. We demonstrate the effectiveness of this structure identification procedure by applying it to identify a model for ergosterol sensing by the proteins Sre1 and Scp1 in fission yeast. Simulations with this model produced outputs consistent with experimental observations. The techniques introduced here will provide researchers with a new tool by which biological systems can be identified and characterized.

A framework for designing and analyzing binary decision-making strategies in cellular systems.

Cells make many binary (all-or-nothing) decisions based on noisy signals gathered from their environment and processed through noisy decision-making pathways. Reducing the effect of noise to improve the fidelity of decision-making comes at the expense of increased complexity, creating a tradeoff between performance and metabolic cost. We present a framework based on rate distortion theory, a branch of information theory, to quantify this tradeoff and design binary decision-making strategies that balance low cost and accuracy in optimal ways. With this framework, we show that several observed behaviors of binary decision-making systems, including random strategies, hysteresis, and irreversibility, are optimal in an information-theoretic sense for various situations. This framework can also be used to quantify the goals around which a decision-making system is optimized and to evaluate the optimality of cellular decision-making systems by a fundamental information-theoretic criterion. As proof of concept, we use the framework to quantify the goals of the externally triggered apoptosis pathway.