Optimal flexibility for conformational transitions in macromolecules

Conformational transitions in macromolecular complexes often involve the reorientation of lever-like structures. Using a simple theoretical model, we show that the rate of such transitions is drastically enhanced if the lever is bendable, e.g. at a localized "hinge''. Surprisingly, the transition is fastest with an intermediate flexibility of the hinge. In this intermediate regime, the transition rate is also least sensitive to the amount of "cargo'' attached to the lever arm, which could be exploited by molecular motors. To explain this effect, we generalize the Kramers-Langer theory for multi-dimensional barrier crossing to configuration dependent mobility matrices.Comment: 4 pages, 4 figure

True Lumen Stabilization to Overcome Malperfusion in Acute Type I Aortic Dissection.

Acute type I aortic dissection (AD) complicated by true lumen (TL) collapse and malperfusion downstream is associated with devastating prognosis. The study reports an institutional mid-term experience with TL stabilization by uncovered stents to restore perfusion as a supplement to proximal thoracic aortic surgery. Between January 2007 and May 2017, 181 out of 270 acute type A AD patients were operated on type I AD. Eighteen uncovered stents (10%) were used to expand the aortic TL in presence of visceral and/or peripheral malperfusion. The procedures took place in a hybrid operating room and were combined with proximal aortic surgery. During follow-up (mean ± standard deviation 3.44 ± 2.1 years), the fate of AD was evaluated by computed tomography. Indication for TL stenting included visceral (44%) or peripheral malperfusion (11%) or both (45%). Stenting of aortic branches followed in 33%. All patients underwent proximal repair and were combined with frozen elephant trunk (67%) or retrograde descending aorta stent grafting (11%). Thirty-day mortality was 16.7%. Two-year survival was 71.8%. The false lumen around the uncovered stents remained patent in 89% and the aortic diameter increased 0.1 cm/y. No intimal rupture or occlusion of arteries occurred. In 1 patient, the stented aortic lumen was visualized after 6.3 years and neointima ingrowth covering the nitinol frame was found. In acute type I AD, combined endovascular-surgical procedures in a hybrid operation room setting can be used safely to resolve distal malperfusion. Encapsulation of uncovered stents within the intimal wall provides a stable fundament for endovascular techniques to close entry tears and false lumen

Hypotension Prediction Index Software to Prevent Intraoperative Hypotension during Major Non-Cardiac Surgery: Protocol for a European Multicenter Prospective Observational Registry (EU-HYPROTECT)

Intraoperative hypotension is common in patients having non-cardiac surgery and associated with postoperative acute myocardial injury, acute kidney injury, and mortality. Avoiding intraoperative hypotension is a complex task for anesthesiologists. Using artificial intelligence to predict hypotension from clinical and hemodynamic data is an innovative and intriguing approach. The AcumenTM Hypotension Prediction Index (HPI) software (Edwards Lifesciences; Irvine, CA, USA) was developed using artificial intelligence-specifically machine learning-and predicts hypotension from blood pressure waveform features. We aimed to describe the incidence, duration, severity, and causes of intraoperative hypotension when using HPI monitoring in patients having elective major non-cardiac surgery

Hypotension prediction index software to prevent intraoperative hypotension during major non-cardiac surgery: protocol for a european multicenter prospective observational registry (EU-HYPROTECT)

Background: Intraoperative hypotension is common in patients having non-cardiac surgery and associated with postoperative acute myocardial injury, acute kidney injury, and mortality. Avoiding intraoperative hypotension is a complex task for anesthesiologists. Using artificial intelligence to predict hypotension from clinical and hemodynamic data is an innovative and intriguing approach. The AcumenTM Hypotension Prediction Index (HPI) software (Edwards Lifesciences; Irvine, CA, USA) was developed using artificial intelligence-specifically machine learning-and predicts hypotension from blood pressure waveform features. We aimed to describe the incidence, duration, severity, and causes of intraoperative hypotension when using HPI monitoring in patients having elective major non-cardiac surgery. Methods: We built up a European, multicenter, prospective, observational registry including at least 700 evaluable patients from five European countries. The registry includes consenting adults (?18 years) who were scheduled for elective major non-cardiac surgery under general anesthesia that was expected to last at least 120 min and in whom arterial catheter placement and HPI monitoring was planned. The major objectives are to quantify and characterize intraoperative hypotension (defined as a mean arterial pressure [MAP] < 65 mmHg) when using HPI monitoring. This includes the time-weighted average (TWA) MAP < 65 mmHg, area under a MAP of 65 mmHg, the number of episodes of a MAP < 65 mmHg, the proportion of patients with at least one episode (1 min or more) of a MAP < 65 mmHg, and the absolute maximum decrease below a MAP of 65 mmHg. In addition, we will assess causes of intraoperative hypotension and investigate associations between intraoperative hypotension and postoperative outcomes. Discussion: There are only sparse data on the effect of using HPI monitoring on intraoperative hypotension in patients having elective major non-cardiac surgery. Therefore, we built up a European, multicenter, prospective, observational registry to describe the incidence, duration, severity, and causes of intraoperative hypotension when using HPI monitoring in patients having elective major non-cardiac surgery.Funding: Edwards Lifesciences SA, Department of Critical Care, Route de l’Etraz 70, 1260 Nyon, Switzerland funded the study and acts as the legal sponsor. The sponsor/funder had an active role in the design of the study. The collection, analysis, and interpretation of the data will be a collaborative effort of all investigators, who will also write the manuscript. Acknowledgments: We acknowledge the support of all participating patients and their physicians. We also acknowledge the tremendous contribution of the staff at Edwards Lifesciences, especially Edward Hembrow, Tim van den Boom, Anne Halfmann, Pierre Sibileau, Barbara Plasschaert, Volker Haag, Giulia Torricella and Alessia Longo. We further appreciate the excellent project management secured by Daniel Greinert, Marie Zielinksi and Claudia Lüske at the Institute for Pharmacology and Preventive Medicine (Cloppenburg, Germany). Data are captured using the s4trials software provided by Software for Trials Europe GmbH (Berlin, Germany)

Optical and radio variability of the BL Lac object AO 0235+16: a possible 5-6 year periodicity

New optical and radio data on the BL Lacertae object AO 0235+16 have been collected in the last four years by a wide international collaboration, which confirm the intense activity of this source. The optical data also include the results of the Whole Earth Blazar Telescope (WEBT) first-light campaign organized in November 1997. The optical spectrum is observed to basically steepen when the source gets fainter. We have investigated the existence of typical variability time scales and of possible correlations between the optical and radio emissions by means of visual inspection, Discrete Correlation Function analysis, and Discrete Fourier Transform technique. The major radio outbursts are found to repeat quasi-regularly with a periodicity of about 5.7 years; this period is also in agreement with the occurrence of some of the major optical outbursts, but not all of them.Comment: to be published in A&

A linguistic approach to assess the dynamics of design team preference in concept selection

This paper addresses the problem of describing the decision-making process of a committee of engineers based upon their verbalized linguistic appraisals of alternatives. First, we show a way to model an individual’s evaluation of an alternative through natural language based on the Systemic-Functional Linguistics system of APPRAISAL. The linguistic model accounts for both the degree of intensity and the uncertainty of expressed evaluations. Second, this multi-dimensional linguistic model is converted into a scalar to represent the degree of intensity and a probability distribution function for the stated evaluation. Finally, we present a Markovian model to calculate the time-varying change in preferential probability, the probability that an alternative is the most preferred alternative. We further demonstrate how preferential probability toward attributes of alternatives correspond to preferential probability toward alternatives. We illustrate the method on two case studies to highlight the time-variant dynamics of preferences toward alternatives and attributes. This research contributes to process tracing in descriptive decision science to understand how engineers actually take decisions.National Science Foundation (U.S.) (Award CMMI-0900255

An integrative strategy to identify the entire protein coding potential of prokaryotic genomes by proteogenomics

Accurate annotation of all protein-coding sequences (CDSs) is an essential prerequisite to fully exploit the rapidly growing repertoire of completely sequenced prokaryotic genomes. However, large discrepancies among the number of CDSs annotated by different resources, missed functional short open reading frames (sORFs), and overprediction of spurious ORFs represent serious limitations. Our strategy toward accurate and complete genome annotation consolidates CDSs from multiple reference annotation resources, ab initio gene prediction algorithms and in silico ORFs (a modified six-frame translation considering alternative start codons) in an integrated proteogenomics database (iPtgxDB) that covers the entire protein-coding potential of a prokaryotic genome. By extending the PeptideClassifier concept of unambiguous peptides for prokaryotes, close to 95% of the identifiable peptides imply one distinct protein, largely simplifying downstream analysis. Searching a comprehensive Bartonella henselae proteomics data set against such an iPtgxDB allowed us to unambiguously identify novel ORFs uniquely predicted by each resource, including lipoproteins, differentially expressed and membrane-localized proteins, novel start sites and wrongly annotated pseudogenes. Most novelties were confirmed by targeted, parallel reaction monitoring mass spectrometry, including unique ORFs and single amino acid variations (SAAVs) identified in a re-sequenced laboratory strain that are not present in its reference genome. We demonstrate the general applicability of our strategy for genomes with varying GC content and distinct taxonomic origin. We release iPtgxDBs for B. henselae, Bradyrhizobium diazoefficiens and Escherichia coli and the software to generate both proteogenomics search databases and integrated annotation files that can be viewed in a genome browser for any prokaryote