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Competing Interests: Competing interests: None declared.

Objective: Ensuring an efficient response to COVID-19 requires a degree of inter-system coordination and capacity management coupled with an accurate assessment of hospital utilization including length of stay (LOS). We aimed to establish optimal practices in inter-system data sharing and LOS modeling to support patient care and regional hospital operations., Materials and Methods: We completed a retrospective observational study of patients admitted with COVID-19 followed by 12-week prospective validation, involving 36 hospitals covering the upper Midwest. We developed a method for sharing de-identified patient data across systems for analysis. From this, we compared 3 approaches, generalized linear model (GLM) and random forest (RF), and aggregated system level averages to identify features associated with LOS. We compared model performance by area under the ROC curve (AUROC)., Results: A total of 2068 patients were included and used for model derivation and 597 patients for validation. LOS overall had a median of 5.0 days and mean of 8.2 days. Consistent predictors of LOS included age, critical illness, oxygen requirement, weight loss, and nursing home admission. In the validation cohort, the RF model (AUROC 0.890) and GLM model (AUROC 0.864) achieved good to excellent prediction of LOS, but only marginally better than system averages in practice., Conclusion: Regional sharing of patient data allowed for effective prediction of LOS across systems; however, this only provided marginal improvement over hospital averages at the aggregate level. A federated approach of sharing aggregated system capacity and average LOS will likely allow for effective capacity management at the regional level., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Despite decades of improvement in the quality and outcomes of cardiovascular care, significant gaps remain. Existing quality improvement strategies are often limited in scope to specific clinical conditions and episodic care. Health services and outcomes research is essential to inform gaps in care but rarely results in the development and implementation of care delivery solutions. Although individual health systems are engaged in projects to improve the quality of care delivery, these efforts often lack a robust study design or implementation evaluation that can inform generalizability and further dissemination. Aligning the work of health care systems and health services and outcomes researchers could serve as a strategy to overcome persisting gaps in cardiovascular quality and outcomes. We describe the inception of the Cardiovascular Quality Improvement and Care Innovation Consortium that seeks to rapidly improve cardiovascular care by (1) developing, implementing, and evaluating multicenter quality improvement projects using innovative care designs; (2) serving as a resource for quality improvement and care innovation partners; and (3) establishing a presence within existing quality improvement and care innovation structures. Success of the collaborative will be defined by projects that result in changes to care delivery with demonstrable impacts on the quality and outcomes of care across multiple health systems. Furthermore, insights gained from implementation of these projects across sites in Cardiovascular Quality Improvement and Care Innovation Consortium will inform and promote broad dissemination for greater impact.

Patients with refractory angina who are suboptimal candidates for further revascularization have improved exercise time, decreased angina frequency, and reduced major adverse cardiac events with intramyocardial delivery of CD34 + cells. However, the effect of CD34 + cell therapy on health care expenditures before and after treatment is unknown. We determined the effect of CD34 + cell therapy on cardiac-related hospital visits and costs during the 12 months following stem cell injection compared with the 12 months prior to injection. Cardiac-related hospital admissions and procedures were retrospectively tabulated for patients enrolled at one site in one of three double-blinded, placebo-controlled CD34 + trials in the 12 months before and after intramyocardial injections of CD34 + cells vs placebo. Fifty-six patients were randomized to CD34 + cell therapy (n = 37) vs placebo (n = 19). Patients randomized to cell therapy experienced 1.57 ± 1.39 cardiac-related hospital visits 12 months before injection, compared with 0.78 ± 1.90 hospital visits 12 months after injection, which was associated with a 62% cost reduction translating to an average savings of $5500 per cell therapy patient. Patients in the placebo group also demonstrated a reduction in cardiac-related hospital events and costs, although to a lesser degree than the CD34 + group. Through 1 January 2019, 24% of CD34 + subjects died at an average of 6.5 ± 2.4 years after enrollment, whereas 47% of placebo patients died at an average of 3.7 ± 1.9 years after enrollment. In conclusion, CD34 + cell therapy for subjects with refractory angina is associated with improved mortality and a reduction in hospital visits and expenditures for cardiac procedures in the year following treatment., (© 2020 The Authors. STEM CELLS TRANSLATIONAL MEDICINE published by Wiley Periodicals, Inc. on behalf of AlphaMed Press.)

An 8-month-old boy presented to hospital with a fever, irritability and 'back arching'. On examination, he demonstrated profound opisthotonic posturing and had tonsillitis. He had a full septic screen and was treated with broad spectrum antibiotics. Blood tests showed a transaminitis, raised alpha fetoprotein and deranged clotting. The clotting abnormalities and raised alpha fetoprotein persisted post discharge and an abdominal ultrasound showed steatosis, splenomegaly and bilateral increased renal cortical reflectivity. A full metabolic screen revealed type 1 tyrosinaemia. The opisthotonic posturing, a major part of this child's presentation, has not been reported as a presenting feature of tyrosinaemia. It was part of a 'neurological crisis' caused by tyrosinaemia and exacerbated by the intercurrent infection. These are known to occur in tyrosinaemia but not commonly as the first presentation. This represents an unusual presentation of a metabolic condition which, without intervention, can lead to severe hepatic, renal and neurodevelopmental complications., Competing Interests: Competing interests: None declared., (© BMJ Publishing Group Limited 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: To determine the implications of applying guideline-recommended definitions of aortic stenosis to echocardiographic data captured in routine clinical care., Methods: Retrospective observational study of 213 174 patients who underwent transthoracic echocardiographic imaging within Allina Health between January 2013 and October 2017. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of echocardiographic measures for severe aortic stenosis were determined relative to the documented interpretation of severe aortic stenosis., Results: Among 77 067 patients with complete assessment of the aortic valve, 1219 (1.6%) patients were categorised as having severe aortic stenosis by the echocardiographic reader. Relative to the documented interpretation, aortic valve area (AVA) as a measure of severe aortic stenosis had the high sensitivity (94.1%) but a low positive predictive value (37.5%). Aortic valve peak velocity and mean gradient were specific (>99%), but less sensitive (<70%). A measure incorporating peak velocity, mean gradient and dimensionless index (either by velocity time integral or peak velocity ratio) achieved a balance of sensitivity (92%) and specificity (99%) with little detriment in accuracy relative to peak velocity and mean gradient alone (98.9% vs 99.3%). Using all available data, the proportion of patients whose echocardiogram could be assessed for aortic stenosis was 79.8% as compared with 52.7% by documented interpretation alone., Conclusion: A measure that used dimensionless index in place of AVA addressed discrepancies between quantitative echocardiographic data and the documented interpretation of severe aortic stenosis. These findings highlight the importance of understanding the limitations of clinical data as it relates to quality improvement efforts and pragmatic research design., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2019. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Competing Interests: Competing interests: None declared.

Objective: In patients with suspected acute coronary syndrome (ACS), troponin testing is effective for diagnosis and prognosis. Troponin testing has now expanded to include patients without suspected ACS. This nonselective troponin testing has unknown consequences for resource utilization and outcome. Therefore, we examined selective versus nonselective troponin testing with respect to patient characteristics, resource utilization, and outcome., Methods: This retrospective 1-year study included all patients with troponin testing at a U.S. emergency department. Testing was classified as selective (ACS) or nonselective (non-ACS) based on admission ICD-9 codes. Troponin upper reference limit (URL) was ≥99th percentile., Results: Among 47,053 patients, troponin was measured in 9109 (19%) of whom 5764 were hospitalized. Admission diagnosis was non-ACS in 4427 (77%) and ACS in 1337 (23%). Non-ACS patients were older, 71±17 versus 65±16 years, with longer hospital stay, 77 versus 32 h, and greater 1-year mortality 22% versus 6.7%; P<.001. In patients with troponin ≥URL, revascularization was performed in 64 (4.7%) of non-ACS versus 213 (48%) of ACS; P<.001. In patients with troponin 80% of the non-ACS population CONCLUSIONS: Contemporary troponin testing is frequently nonselective. The non-ACS and ACS populations differ significantly regarding clinical characteristics, revascularization rates, and outcomes. Troponin elevation is a powerful predictor of 1-year mortality in non-ACS, this association reveals an opportunity for risk stratification and targeted therapy., Key Questions: In patients with suspected acute coronary syndrome (ACS), troponin testing is effective for diagnosis and prognosis. However, troponin testing has now expanded to include patients without suspected ACS. This nonselective troponin testing has unknown consequences for hospital resource utilization and patient outcome. Our findings demonstrate contemporary troponin testing is largely nonselective (77% of testing was performed in patients without acute coronary syndrome). In comparison to patients with acute coronary syndrome, those with non-acute coronary syndrome are older, with longer hospital stay, lower revascularization rates, and greater 1-year mortality. Troponin elevation identifies a high-risk population in both acute coronary syndrome and non-acute coronary syndrome populations, yet effective treatment for the latter is lacking., (Copyright © 2018. Published by Elsevier Inc.)

Background: Prior studies suggest that low-risk ST-segment-elevation myocardial infarction (STEMI) patients undergoing primary percutaneous coronary intervention can be considered for early discharge. We describe the implementation of an STEMI risk score to decrease cost while maintaining optimal patient outcomes., Methods and Results: We determined the impact of risk-guided STEMI care on healthcare value through the retrospective application of the Zwolle Risk Score to 967 patients receiving primary percutaneous coronary intervention between 2009 and 2011. Of these patients, 540 (56%) were categorized as low risk, indicating they may be safely triaged directly to a telemetry unit rather than the intensive care unit and targeted for early discharge. We subsequently developed and implemented a modified Zwolle Risk Calculator into the electronic medical record to support application of the fast-track protocol for low-risk STEMI patients. Among 549 prospective patients with STEMI, 62% were low risk, and the fast-track protocol was followed in 75% of cases. Prospective results confirmed lower rates of complications (low risk 8.3% versus high risk 38.7%; P <0.001) and in-hospital mortality (low risk 0.4% versus High risk 12.5%; P <0.001) in the low-risk cohort. Low-risk patients had a shorter median length of stay (median and [25th, 75th percentiles]: low risk 2 [2, 3] versus high risk: 3 [2, 6]; P <0.001) and lower overall costs (low risk $6720 [$5280-$9030] versus high risk $11 783 [$7953-$25 359]; P <0.001). Low-risk patients treated on-protocol had shorter median length of stay (on-protocol 2 [1, 2] versus off-protocol 2 [2, 3]; P <0.001) and hospital costs (on-protocol $6090 [$4730, $7356] versus off-protocol $11 783 [$7953, $25 359]; P <0.001) than those treated off-protocol. On-protocol low-risk patients in the prospective cohort also had lower costs and shorter length of stay than low-risk patients in the retrospective cohort ( P <0.001 for both)., Conclusions: In our study, risk-guided triage and discharge after primary percutaneous coronary intervention for STEMI improved healthcare value by reducing costs of care without compromising quality of care or patient outcomes., (© 2018 American Heart Association, Inc.)

Healthcare value, defined as health outcomes achieved relative to the costs of care, has been proposed as a unifying approach to measure improvements in the quality and affordability of healthcare. Although value is of increasing interest to payers, many providers remain unfamiliar with how value differs from other approaches to the comparison of cost and outcomes (ie, cost-effectiveness analysis). While cost-effectiveness studies can be used by policy makers and payers to inform decisions about coverage and reimbursement for new therapies, the assessment of healthcare can guide improvements in the delivery of healthcare to achieve better outcomes at lower cost. Comparison on value allows for the identification of healthcare delivery organisations or care delivery settings where patient outcomes have been optimised at a lower cost. Gaps remain in the measurement of healthcare value, particularly as it relates to patient-reported health status (symptoms, functional status and health-related quality of life). The use of technology platforms that capture health status measures with minimal disruption to clinical workflow (ie, web portals, automated telephonic systems and tablets to facilitate capture outside of in-person clinical interaction) is facilitating use of health status measures to improve clinical care and optimise patient outcomes. Furthermore, the use of a value framework has catalysed quality improvement efforts and research to seek better patient outcomes at lower cost., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Thermostabilization of an enzyme with complete retention of catalytic efficiency was demonstrated on recombinant 3-dehydroshikimate dehydratase (DHSase or wtAsbF) from Bacillus thuringiensis serovar konkukian 97-27 (hereafter, B. thuringiensis 97-27). The wtAsbF is relatively unstable at 37 °C, in vitro (t 1/2 37 = 15 min), in the absence of divalent metal. We adopted a structure-based design to identify stabilizing mutations and created a combinatorial library based upon predicted mutations at specific locations on the enzyme surface. A diversified asbF library (∼2000 variants) was expressed in E. coli harboring a green fluorescent protein (GFP) reporter system linked to the product of wtAsbF activity (3,4-dihydroxybenzoate, DHB). Mutations detrimental to DHSase function were rapidly eliminated using a high throughput fluorescence activated cell sorting (FACS) approach. After a single sorting round and heat screen at 50 °C, a triple AsbF mutant (Mut1), T61N, H135Y, and H257P, was isolated and characterized. The half-life of Mut1 at 37 °C was >10-fold higher than the wtAsbF (t 1/2 37 = 169 min). Further, the second-order rate constants for both wtAsbF and Mut1 were approximately equal (9.9 × 10 5 M -1 s -1 , 7.8 × 10 5 M -1 s -1 , respectively), thus demonstrating protein thermostability did not come at the expense of enzyme thermophilicity. In addition, in vivo overexpression of Mut1 in E. coli resulted in a ∼60-fold increase in functional enzyme when compared to the wild-type enzyme under the identical expression conditions. Finally, overexpression of the thermostable AsbF resulted in an approximate 80-120% increase in DHB accumulation in the media relative to the wild-type enzyme.

A whole-cell biosensor utilizing a transcription factor (TF) is an effective tool for sensitive and selective detection of specialty chemicals or anthropogenic molecules, but requires access to an expanded repertoire of TFs. Using homology modeling and ligand docking for binding pocket identification, assisted by conservative mutations in the pocket, we engineered a novel specificity in an Acinetobacter TF, PobR, to 'sense' a chemical p-nitrophenol (pNP) and measured the response via a fluorescent protein reporter expressed from a PobR promoter. Out of 10(7) variants of PobR, four were active when dosed with pNP, with two mutants showing a specificity switch from the native effector 4-hydroxybenzoate (4HB). One of the mutants, pNPmut1 was then used to create a smart microbial cell responding to pNP production from hydrolysis of an insecticide, paraoxon, in a coupled assay involving phosphotriesterase (PTE) enzyme expressed from a separate promoter. We show the fluorescence of the cells correlated with the catalytic efficiency of the PTE variant expressed in each cell. High selectivity between similar molecules (4HB versus pNP), high sensitivity for pNP detection (∼2 μM) and agreement of apo- and holo-structures of PobR scaffold with predetermined computational models are other significant results presented in this work., (Published by Oxford University Press on behalf of Nucleic Acids Research 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

Postoperative atrial fibrillation (POAF) is a frequent complication of cardiac surgery, which results in increased morbidity, mortality, length of stay, and hospital costs. We developed and followed a process map to implement a protocol to decrease POAF: (1) identify stakeholders and form a working committee, (2) formal literature and guideline review, (3) retrospective analysis of current institutional data, (4) data modeling to determine expected effects of change, (4) protocol development and implementation into the electronic medical record, and (5) ongoing review of data and protocol adjustment. Retrospective analysis demonstrated that POAF occurred in 29.8% of all cardiovascular surgery cases. Median length of stay was 2 days longer (P<0.001), and median total variable costs $2495 higher (P<0.001) in POAF patients. Modeling predicted that up to 60 cases of POAF and >$200 000 annually could be saved. A clinically based electronic medical record tool was implemented into the electronic medical record to aid preoperative clinic providers in identifying patients eligible for prophylactic amiodarone. Initial results during the 9-month period after implementation demonstrated a reduction in POAF in patients using the protocol, compared with those who qualified but did not receive amiodarone and those not evaluated (11.1% versus 38.7% and 38.8%; P=0.022); however, only 17.3% of patients used the protocol. A standardized methodological approach to quality improvement and electronic medical record integration has potential to significantly decrease the incidence of POAF, length of stay, and total variable cost in patients undergoing elective coronary artery bypass graft and valve surgeries. This framework for quality improvement interventions may be adapted to similar clinical problems beyond POAF., (© 2016 American Heart Association, Inc.)

Structure-based rational mutagenesis for engineering protein functionality has been limited by the scarcity and difficulty of obtaining crystal structures of desired proteins. On the other hand, when high-throughput selection is possible, directed evolution-based approaches for gaining protein functionalities have been random and fortuitous with limited rationalization. We combine comparative modeling of dimer structures, ab initio loop reconstruction, and ligand docking to select positions for mutagenesis to create a library focused on the ligand-contacting residues. The rationally reduced library requirement enabled conservative control of the substitutions by oligonucleotide synthesis and bounding its size within practical transformation efficiencies (∼ 10(7) variants). This rational approach was successfully applied on an inducer-binding domain of an Acinetobacter transcription factor (TF), pobR, which shows high specificity for natural effector molecule, 4-hydroxy benzoate (4HB), but no native response to 3,4-dihydroxy benzoate (34DHB). Selection for mutants with high transcriptional induction by 34DHB was carried out at the single-cell level under flow cytometry (via green fluorescent protein expression under the control of pobR promoter). Critically, this selection protocol allows both selection for induction and rejection of constitutively active mutants. In addition to gain-of-function for 34DHB induction, the selected mutants also showed enhanced sensitivity and response for 4HB (native inducer) while no sensitivity was observed for a non-targeted but chemically similar molecule, 2-hydroxy benzoate (2HB). This is unique application of the Rosetta modeling protocols for library design to engineer a TF. Our approach extends applicability of the Rosetta redesign protocol into regimes without a priori precision structural information., (© 2015 Wiley Periodicals, Inc.)

Abstract Objective. To examine injuries produced by chest compressions in out-of-hospital cardiac arrest (OHCA) patients who survive to hospital admission. Methods. A retrospective cohort study was conducted among 235 consecutive patients who were hospitalized after nontraumatic OHCA in Minnesota between January 2009 and May 2012 (117 survived to discharge; 118 died during hospitalization). Cases were eligible if the patient had received prehospital compressions from an emergency medical services (EMS) provider. One EMS provider in the area was using a mechanical compression device (LUCAS TM ) as standard equipment, so the association between injury and use of mechanical compression was also examined. Prehospital care information was abstracted from EMS run sheets, and hospital records were reviewed for injuries documented during the post-arrest hospitalization that likely resulted from compressions. Results. Injuries were identified in 31 patients (13%), the most common being rib fracture (9%) and intrathoracic hemorrhage (3%). Among those who survived to discharge, the mean length of stay was not statistically significantly different between those with injuries (13.5 days) and those without (10.8 days; p = 0.23). Crude injury prevalence was higher in those who died prior to discharge, had received compressions for >10 minutes (versus ≤10 minutes) and underwent computer tomography (CT) imaging, but did not differ by bystander compressions or use of mechanical compression. After multivariable adjustment, only compression time > 10 min and CT imaging during hospitalization were positively associated with detected injury (OR = 7.86 [95% CI = 1.7-35.9] and 6.30 [95% CI = 2.6-15.5], respectively). Conclusion. In patients who survived OHCA to admission, longer duration of compressions and use of CT during the post-arrest course were associated positively with documented compression injury. Compression-induced injuries detected via routine post-arrest care are likely to be largely insignificant in terms of length of recovery.

We created a single cell sorting system to screen for enzyme activity in Escherichia coli producing 3,4 dihydroxy benzoate (34DHB). To do so, we engineered a transcription factor regulon controlling the expression of green fluorescent protein (GFP) for induction by 34DHB. An autoregulated transcription factor, pcaU, was borrowed from Acinetobacter sp ADP1 to E. coli and its promoter region adapted for activity in E. Coli. The engineered pcaU regulon was inducible at >5 μM exogenous 34DHB, making it a sensitive biosensor for this industrially significant nylon precursor. Addition of a second plasmid provided IPTG inducible expression of dehydroshikimate dehydratase enzyme (AsbF), which converts endogenous dehydroshikimate to 34DHB. This system produced GFP fluorescence in an IPTG dose-dependent manner, and was easily detected in single cell on flow cytometer despite a moderate catalytic efficiency of AsbF. Using fluorescence-activated cell sorting (FACS), individual cells carrying the active AsbF could be isolated even when diluted into a decoy population of cells carrying a mutant (inactivated) AsbF variant at one part in a million. The same biosensor was also effective for further optimization of itself. FACS on E. coli carrying randomized loci in the promoter showed several variants with enhanced response to 34DHB., (Published by Oxford University Press on behalf of Nucleic Acids Research 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

Protein G is an IgG binding protein that has been widely exploited for biotechnological purposes. Rosetta protein modeling identified a set of favorable polar mutations in Protein G, at its binding interface with the Fc domain of Immunoglobulin G, that were predicted to increase the stability and tighten the binding relative to native Protein G, with only a minor perturbation of the binding mode seen in the crystal structure. This triple mutant was synthesized and evaluated experimentally. Relative to the native protein G, the mutant showed a 3.5-fold enhancement in display level on the surface of yeast and a 5-fold tighter molar affinity for rabbit and human IgG. We attribute the improved affinity to a network of hydrogen bonds exploiting specific polar groups on human and rabbit Fc. The relative specificity increased as well since there was little affinity enhancement for goat and mouse Fc, while the affinity for rat Fc was poorer by half. This designed Protein G will be useful in biotechnological applications as a recombinant protein, where its improved affinity, display and specificity will increase antibody capture sensitivity and capacity. Furthermore, the display of this protein on the surface of yeast introduces the concept of the use of yeast as an affinity matrix.

Understanding how binding of a transcription factor to an operator is influenced by the operator sequence is an ongoing quest. It facilitates discovery of alternative binding sites as well as tuning of transcriptional regulation. We investigated the behavior of the Escherichia coli Lac repressor (LacI) protein with a large set of lac O(1) operator variants. The 114 variants examined contained a mean of 2.9 (range 0-4) mutations at positions -4, -2, +2 and +4 in the minimally required 17 bp operator. The relative affinity of LacI for the operators was examined by quantifying expression of a GFP reporter gene and Rosetta structural modeling. The combinations of mutations in the operator sequence created a wide range of regulatory behaviors. We observed variations in the GFP fluorescent signal among the operator variants of more than an order of magnitude under both uninduced and induced conditions. We found that a single nucleotide change may result in changes of up to six- and 12-fold in uninduced and induced GFP signals, respectively. Among the four positions mutated, we found that nucleotide G at position -4 is strongly correlated with strong repression. By Rosetta modeling, we found a significant correlation between the calculated binding energy and the experimentally observed transcriptional repression strength for many operators. However, exceptions were also observed, underscoring the necessity for further improvement in biophysical models of protein-DNA interactions., (© 2012 The Authors Journal compilation © 2012 FEBS.)

Background and Aim of the Study: Chronic mitral regurgitation (MR) causes volume overload on the left ventricle and, if uncorrected, will over time lead to left ventricular remodeling and heart failure. The benefits of angiotensin-converting enzyme (ACE) inhibitors or angiotensin II receptor blockers (ARBs) in primary MR are not well defined., Methods: MEDLINE was searched for studies in which the effects of ACE inhibitors and ARBs on chronic MR had been examined. The inclusion criteria required the patient population to have chronic MR, a normal left ventricular ejection fraction, and to report a quantitative measure of the change in MR severity. Studies in which patients had secondary MR were excluded., Results: Nineteen studies met the inclusion criteria (13 daily therapy, five single-dose, and one combined study). The pooled mean decrease in regurgitant fraction (RF) was 7.7% [95% CI 4.9, 10.6] and 9.3% [95% CI 3.4, 15.2] for studies in patients with daily therapy and single-dose therapy, respectively. Among studies which reported changes in regurgitant volume (RV), the pooled mean decrease was 7.9 ml [95% CI 1.4, 14.5]. For patients with mitral valve prolapse (MVP), the pooled mean reduction in RF was 8.1% [95% CI 4.3, 11.9] and in rheumatic disease it was 3.4% [95% CI 13.2 - 7.0]. Across the seven studies of daily therapy which reported a change in left ventricular end-diastolic volume index (LVEDVI), the mean decrease was 11.5 ml/m2 [95% CI 2.4, 20.6]., Conclusion: ACE inhibitors and ARBs each reduced the RF, RV, and left ventricular size by a modest degree in chronic primary MR.

The p21-activated kinase (PAK) family plays a versatile role in cell signaling by forming a hub of interactions. PAKs bind the GTPases like RAC and CDC42. Their proline-rich motifs bind SH3 adaptor proteins such as PIX and NCK. PAKs display nuclear localization signal sites and a potential Integrin binding site. No fully complete structure of the PAKs has been published; partial 3D structures of the PAK family kinases include portions of the auto-inhibited PAK1, GTPase bound to small peptides from PAKs, and the kinase domains from PAK1 and PAK4-6 (with small ligands in a few cases). This review focuses on exploring the intermolecular interaction regions in these 3D structures and we offer insights on the missing regions in crystal structure of the auto-inhibited PAK1. Understanding and modulation of PAK intermolecular interactions can pave the way for PAK blockers and biosensors.

The Rosetta de novo structure prediction and loop modeling protocols begin with coarse grained Monte Carlo searches in which the moves are based on short fragments extracted from a database of known structures. Here we describe a new object oriented program for picking fragments that greatly extends the functionality of the previous program (nnmake) and opens the door for new approaches to structure modeling. We provide a detailed description of the code design and architecture, highlighting its modularity, and new features such as extensibility, total control over the fragment picking workflow and scoring system customization. We demonstrate that the program provides at least as good building blocks for ab-initio structure prediction as the previous program, and provide examples of the wide range of applications that are now accessible.

Naturally occurring homooligomeric protein complexes exhibit striking internal symmetry. The evolutionary origins of this symmetry have been the subject of considerable speculation; proposals for the advantages associated with symmetry include greater folding efficiency, reduced aggregation, amenability to allosteric regulation, and greater adaptability. An alternative possibility stems from the idea that to contribute to fitness, and hence be subject to evolutionary optimization, a complex must be significantly populated, which implies that the interaction energy between monomers in the ancestors of modern-day complexes must have been sufficient to at least partially overcome the entropic cost of association. Here, we investigate the effects of this bias toward very-low-energy complexes on the distribution of symmetry in primordial homooligomers modeled as randomly interacting pairs of monomers. We demonstrate quantitatively that a bias toward very-low-energy complexes can result in the emergence of symmetry from random ensembles in which the overall frequency of symmetric complexes is vanishingly small. This result is corroborated by using explicit protein-protein docking calculations to generate ensembles of randomly docked complexes: the fraction of these that are symmetric increases from 0.02% in the overall population to >50% in very low energy subpopulations.

Cryoelectron microscopy (cryoEM) is an experimental technique to determine the three-dimensional (3D) structure of large protein complexes. Currently, this technique is able to generate protein density maps at 6-9 A resolution, at which the skeleton of the structure (which is composed of alpha-helices and beta-sheets) can be visualized. As a step towards predicting the entire backbone of the protein from the protein density map, we developed a method to predict the topology and sequence alignment for the skeleton helices. Our method combines the geometrical information of the skeleton helices with the Rosetta ab initio structure prediction method to derive a consensus topology and sequence alignment for the skeleton helices. We tested the method with 60 proteins. For 45 proteins, the majority of the skeleton helices were assigned a correct topology from one of our top ten predictions. The offsets of the alignment for most of the assigned helices were within +/-2 amino acids in the sequence. We also analyzed the use of the skeleton helices as a clustering tool for the decoy structures generated by Rosetta. Our comparison suggests that the topology clustering is a better method than a general overlap clustering method to enrich the ranking of decoys, particularly when the decoy pool is small.

Saccharomyces cerevisiae is one of the best-studied model organisms, yet the three-dimensional structure and molecular function of many yeast proteins remain unknown. Yeast proteins were parsed into 14,934 domains, and those lacking sequence similarity to proteins of known structure were folded using the Rosetta de novo structure prediction method on the World Community Grid. This structural data was integrated with process, component, and function annotations from the Saccharomyces Genome Database to assign yeast protein domains to SCOP superfamilies using a simple Bayesian approach. We have predicted the structure of 3,338 putative domains and assigned SCOP superfamily annotations to 581 of them. We have also assigned structural annotations to 7,094 predicted domains based on fold recognition and homology modeling methods. The domain predictions and structural information are available in an online database at http://rd.plos.org/10.1371&#95;journal.pbio.0050076&#95;01.

Literature mining is expected to help not only with automatically sifting through huge biomedical literature and annotation databases, but also with linking bio-chemical entities to appropriate functional hypotheses. However, there has been very limited success in testing literature mining methods due to the lack of large, objectively validated test sets or "gold standards". To improve this situation we created a large-scale test of literature mining methods and resources. We report on a specific implementation of this test: how well can the Pfam protein family classification be replicated from independently mining different literature/annotation resources? We test and compare different keyterm sets as well as different algorithms for issuing protein family predictions. We find that protein families can indeed be automatically predicted from the literature. Using words from PubMed abstracts, of 3663 proteins tested, over 75% were correctly assigned to one of 618 Pfam families. For 90% of proteins the correct Pfam family was among the top 5 ranked families. We found that protein family prediction is far superior with keywords extracted from PubMed abstracts than with GO annotations or MeSH keyterms, suggesting that the text itself (in combination with the vector space model) is superior to GO and MeSH as a literature mining resources, at least for detecting protein family membership. Finally, we show that Shannon's entropy can be exploited to improve prediction by facilitating the integration of the different literature sources tested.

Many applications require a method for translating a large list of bond angles and bond lengths to precise atomic Cartesian coordinates. This simple but computationally consuming task occurs ubiquitously in modeling proteins, DNA, and other polymers as well as in many other fields such as robotics. To find an optimal method, algorithms can be compared by a number of operations, speed, intrinsic numerical stability, and parallelization. We discuss five established methods for growing a protein backbone by serial chain extension from bond angles and bond lengths. We introduce the Natural Extension Reference Frame (NeRF) method developed for Rosetta's chain extension subroutine, as well as an improved implementation. In comparison to traditional two-step rotations, vector algebra, or Quaternion product algorithms, the NeRF algorithm is superior for this application: it requires 47% fewer floating point operations, demonstrates the best intrinsic numerical stability, and offers prospects for parallel processor acceleration. The NeRF formalism factors the mathematical operations of chain extension into two independent terms with orthogonal subsets of the dependent variables; the apparent irreducibility of these factors hint that the minimal operation set may have been identified. Benchmarks are made on Intel Pentium and Motorola PowerPC CPUs.

A major limitation of current comparative modeling methods is the accuracy with which regions that are structurally divergent from homologues of known structure can be modeled. Because structural differences between homologous proteins are responsible for variations in protein function and specificity, the ability to model these differences has important functional consequences. Although existing methods can provide reasonably accurate models of short loop regions, modeling longer structurally divergent regions is an unsolved problem. Here we describe a method based on the de novo structure prediction algorithm, Rosetta, for predicting conformations of structurally divergent regions in comparative models. Initial conformations for short segments are selected from the protein structure database, whereas longer segments are built up by using three- and nine-residue fragments drawn from the database and combined by using the Rosetta algorithm. A gap closure term in the potential in combination with modified Newton's method for gradient descent minimization is used to ensure continuity of the peptide backbone. Conformations of variable regions are refined in the context of a fixed template structure using Monte Carlo minimization together with rapid repacking of side-chains to iteratively optimize backbone torsion angles and side-chain rotamers. For short loops, mean accuracies of 0.69, 1.45, and 3.62 A are obtained for 4, 8, and 12 residue loops, respectively. In addition, the method can provide reasonable models of conformations of longer protein segments: predicted conformations of 3A root-mean-square deviation or better were obtained for 5 of 10 examples of segments ranging from 13 to 34 residues. In combination with a sequence alignment algorithm, this method generates complete, ungapped models of protein structures, including regions both similar to and divergent from a homologous structure. This combined method was used to make predictions for 28 protein domains in the Critical Assessment of Protein Structure 4 (CASP 4) and 59 domains in CASP 5, where the method ranked highly among comparative modeling and fold recognition methods. Model accuracy in these blind predictions is dominated by alignment quality, but in the context of accurate alignments, long protein segments can be accurately modeled. Notably, the method correctly predicted the local structure of a 39-residue insertion into a TIM barrel in CASP 5 target T0186., (Copyright 2004 Wiley-Liss, Inc.)

Robetta is a fully automated protein structure prediction server that uses the Rosetta fragment-insertion method. It combines template-based and de novo structure prediction methods in an attempt to produce high quality models that cover every residue of a submitted sequence. The first step in the procedure is the automatic detection of the locations of domains and selection of the appropriate modeling protocol for each domain. For domains matched to a homolog with an experimentally characterized structure by PSI-BLAST or Pcons2, Robetta uses a new alignment method, called K*Sync, to align the query sequence onto the parent structure. It then models the variable regions by allowing them to explore conformational space with fragments in fashion similar to the de novo protocol, but in the context of the template. When no structural homolog is available, domains are modeled with the Rosetta de novo protocol, which allows the full length of the domain to explore conformational space via fragment-insertion, producing a large decoy ensemble from which the final models are selected. The Robetta server produced quite reasonable predictions for targets in the recent CASP-5 and CAFASP-3 experiments, some of which were at the level of the best human predictions., (Copyright 2003 Wiley-Liss, Inc.)

We describe predictions of the structures of CASP5 targets using Rosetta. The Rosetta fragment insertion protocol was used to generate models for entire target domains without detectable sequence similarity to a protein of known structure and to build long loop insertions (and N-and C-terminal extensions) in cases where a structural template was available. Encouraging results were obtained both for the de novo predictions and for the long loop insertions; we describe here the successes as well as the failures in the context of current efforts to improve the Rosetta method. In particular, de novo predictions failed for large proteins that were incorrectly parsed into domains and for topologically complex (high contact order) proteins with swapping of segments between domains. However, for the remaining targets, at least one of the five submitted models had a long fragment with significant similarity to the native structure. A fully automated version of the CASP5 protocol produced results that were comparable to the human-assisted predictions for most of the targets, suggesting that automated genomic-scale, de novo protein structure prediction may soon be worthwhile. For the three targets where the human-assisted predictions were significantly closer to the native structure, we identify the steps that remain to be automated., (Copyright 2003 Wiley-Liss, Inc.)

Advances in structural genomics and protein structure prediction require the design of automatic, fast, objective, and well benchmarked methods capable of comparing and assessing the similarity of low-resolution three-dimensional structures, via experimental or theoretical approaches. Here, a new method for sequence-independent structural alignment is presented that allows comparison of an experimental protein structure with an arbitrary low-resolution protein tertiary model. The heuristic algorithm is given and then used to show that it can describe random structural alignments of proteins with different folds with good accuracy by an extreme value distribution. From this observation, a structural similarity score between two proteins or two different conformations of the same protein is derived from the likelihood of obtaining a given structural alignment by chance. The performance of the derived score is then compared with well established, consensus manual-based scores and data sets. We found that the new approach correlates better than other tools with the gold standard provided by a human evaluator. Timings indicate that the algorithm is fast enough for routine use with large databases of protein models. Overall, our results indicate that the new program (MAMMOTH) will be a good tool for protein structure comparisons in structural genomics applications. MAMMOTH is available from our web site at http://physbio.mssm.edu/~ortizg/.

We use the Rosetta de novo structure prediction method to produce three-dimensional structure models for all Pfam-A sequence families with average length under 150 residues and no link to any protein of known structure. To estimate the reliability of the predictions, the method was calibrated on 131 proteins of known structure. For approximately 60% of the proteins one of the top five models was correctly predicted for 50 or more residues, and for approximately 35%, the correct SCOP superfamily was identified in a structure-based search of the Protein Data Bank using one of the models. This performance is consistent with results from the fourth critical assessment of structure prediction (CASP4). Correct and incorrect predictions could be partially distinguished using a confidence function based on a combination of simulation convergence, protein length and the similarity of a given structure prediction to known protein structures. While the limited accuracy and reliability of the method precludes definitive conclusions, the Pfam models provide the only tertiary structure information available for the 12% of publicly available sequences represented by these large protein families.

The U.S. Department of Energy recently announced the first five grants for the Genomes to Life (GTL) Program. The goal of this program is to "achieve the most far-reaching of all biological goals: a fundamental, comprehensive, and systematic understanding of life." While more information about the program can be found at the GTL website (www.doegenomestolife.org), this paper provides an overview of one of the five GTL projects funded, "Carbon Sequestration in Synechococcus Sp.: From Molecular Machines to Hierarchical Modeling." This project is a combined experimental and computational effort emphasizing developing, prototyping, and applying new computational tools and methods to elucidate the biochemical mechanisms of the carbon sequestration of Synechococcus Sp., an abundant marine cyanobacteria known to play an important role in the global carbon cycle. Understanding, predicting, and perhaps manipulating carbon fixation in the oceans has long been a major focus of biological oceanography and has more recently been of interest to a broader audience of scientists and policy makers. It is clear that the oceanic sinks and sources of CO(2) are important terms in the global environmental response to anthropogenic atmospheric inputs of CO(2) and that oceanic microorganisms play a key role in this response. However, the relationship between this global phenomenon and the biochemical mechanisms of carbon fixation in these microorganisms is poorly understood. The project includes five subprojects: an experimental investigation, three computational biology efforts, and a fifth which deals with addressing computational infrastructure challenges of relevance to this project and the Genomes to Life program as a whole. Our experimental effort is designed to provide biology and data to drive the computational efforts and includes significant investment in developing new experimental methods for uncovering protein partners, characterizing protein complexes, identifying new binding domains. We will also develop and apply new data measurement and statistical methods for analyzing microarray experiments. Our computational efforts include coupling molecular simulation methods with knowledge discovery from diverse biological data sets for high-throughput discovery and characterization of protein-protein complexes and developing a set of novel capabilities for inference of regulatory pathways in microbial genomes across multiple sources of information through the integration of computational and experimental technologies. These capabilities will be applied to Synechococcus regulatory pathways to characterize their interaction map and identify component proteins in these pathways. We will also investigate methods for combining experimental and computational results with visualization and natural language tools to accelerate discovery of regulatory pathways. Furthermore, given that the ultimate goal of this effort is to develop a systems-level of understanding of how the Synechococcus genome affects carbon fixation at the global scale, we will develop and apply a set of tools for capturing the carbon fixation behavior of complex of Synechococcus at different levels of resolution. Finally, because the explosion of data being produced by high-throughput experiments requires data analysis and models which are more computationally complex, more heterogeneous, and require coupling to ever increasing amounts of experimentally obtained data in varying formats, we have also established a companion computational infrastructure to support this effort as well as the Genomes to Life program as a whole.

This study explores the use of multiple sequence alignment (MSA) information and global measures of hydrophobic core formation for improving the Rosetta ab initio protein structure prediction method. The most effective use of the MSA information is achieved by carrying out independent folding simulations for a subset of the homologous sequences in the MSA and then identifying the free energy minima common to all folded sequences via simultaneous clustering of the independent folding runs. Global measures of hydrophobic core formation, using ellipsoidal rather than spherical representations of the hydrophobic core, are found to be useful in removing non-native conformations before cluster analysis. Through this combination of MSA information and global measures of protein core formation, we significantly increase the performance of Rosetta on a challenging test set. Proteins 2001;43:1-11., (Copyright 2001 Wiley-Liss, Inc.)

Rosetta ab initio protein structure predictions in CASP4 were considerably more consistent and more accurate than previous ab initio structure predictions. Large segments were correctly predicted (>50 residues superimposed within an RMSD of 6.5 A) for 16 of the 21 domains under 300 residues for which models were submitted. Models with the global fold largely correct were produced for several targets with new folds, and for several difficult fold recognition targets, the Rosetta models were more accurate than those produced with traditional fold recognition models. These promising results suggest that Rosetta may soon be able to contribute to the interpretation of genome sequence information., (Copyright 2002 Wiley-Liss, Inc.)

We describe a method for generating moderate to high-resolution protein structures using limited NMR data combined with the ab initio protein structure prediction method Rosetta. Peptide fragments are selected from proteins of known structure based on sequence similarity and consistency with chemical shift and NOE data. Models are built from these fragments by minimizing an energy function that favors hydrophobic burial, strand pairing, and satisfaction of NOE constraints. Models generated using this procedure with approximately 1 NOE constraint per residue are in some cases closer to the corresponding X-ray structures than the published NMR solution structures. The method requires only the sparse constraints available during initial stages of NMR structure determination, and thus holds promise for increasing the speed with which protein solution structures can be determined.

We have developed a technique for laser tuning at rates of 100 kHz or more using a pair of acousto-optic modulators. In addition to all-electronic wavelength control, the same modulators also can provide electronically variable Q-switching, cavity length and power stabilization, chirp and linewidth control, and variable output coupling, all at rates far beyond what is possible with conventional mechanically tuned components. Tuning rates of 70 kHz have been demonstrated on a radio-frequency-pumped CO2 laser, with random access to over 50 laser lines spanning a 17% range in wavelength and with wavelength discrimination better than 1 part in 1000. A compact tuner and Q-switch has been deployed in a 5-10-kHz pulsed lidar system. The modulators each operate at a fixed Bragg angle, with the acoustic frequency determining the selected wavelength. This arrangement doubles the wavelength resolution without introducing an undesirable frequency shift.

A simple technique, synthetic-array heterodyne detection, permits an ordinary single-element optical detector to behave as though it were a coherent array. A successful experimental implementation of a synthetic two-pixel array, using a CO(2) laser and a single-element HgCdTe photodiode is reported. A different heterodyne local oscillator frequency is incident upon each resolvable region of the detector surface. Thus different regions are mapped to different heterodyne beat frequencies. One can determine where the photons struck the detector surface even though a single electrical connection to the detector is used. This also prevents the destructive interference that occurs when multiple speckles are imaged (akin to spatial diversity). In coherent lidar this permits a larger field of view. An acousto-optic modulator produces the local oscillator frequencies and can achieve good spatial separation of optical frequencies of the order of a megahertz apart.

During annual training, a reserve hospital unit staffed a clinic, providing sick-call for its own members and secondary care for about 3,000 National Guard soldiers. Reservists reporting for sick call were treated predominantly for respiratory infection, while the Guard members complained most frequently of field-related injuries. Quality assurance (QA) was done by the authors to evaluate handling of sick call over the 2 weeks, and few problems emerged upon review of the clinic records. Suggestions for future years include establishing standard terminology for recording chief complaint and discharge disposition, and the use of treatment guidelines for training and QA purposes.