Lymphatic dysfunction in critical illness.

PURPOSE OF REVIEW: The essential role of the lymphatic system in fluid homeostasis, nutrient transport, and immune trafficking is well recognized; however, there is limited understanding of the mechanisms that regulate lymphatic function, particularly in the setting of critical illness. The lymphatics likely affect disease severity and progression in every condition, from severe systemic inflammatory states to respiratory failure. Here, we review structural and functional disorders of the lymphatic system, both congenital and acquired, as they relate to care of the pediatric patient in the intensive care setting, including novel areas of research into medical and procedural therapeutic interventions. RECENT FINDINGS: The mainstay of current therapies for congenital and acquired lymphatic abnormalities has involved nonspecific medical management or surgical procedures to obstruct or divert lymphatic flow. With the development of dynamic contrast-enhanced magnetic resonance lymphangiography, image-directed percutaneous intervention may largely replace surgery. Because of new insights into the mechanisms that regulate lymphatic biology, pharmacologic inhibitors of mTOR and leukotriene B4 signaling are each in Phase II clinical trials to treat abnormal lymphatic structure and function, respectively. SUMMARY: As our understanding of normal lymphatic biology continues to advance, we will be able to develop novel strategies to support and augment lymphatic function during critical illness and through convalescence.

A Comparison of Anterograde Versus Retrograde Approaches for Neonatal Balloon Aortic Valvuloplasty.

In neonates requiring balloon aortic valvuloplasty, both anterograde and retrograde approaches are feasible. A recent comparison of these two approaches is lacking. A retrospective cohort study of neonates at a single center undergoing BAV from 9/00 to 7/14 was performed. Records were reviewed including pre- and post-intervention echocardiograms and catheterization data. Comparisons of acute efficacy and procedural safety were made based on type of approach utilized. Forty-two neonates underwent BAV. Eleven cases utilized exclusively an anterograde approach, while 31 included a retrograde approach (including 4 with both approaches used). There were no significant differences between groups in baseline demographic and clinical characteristics. Additionally, by both pre-intervention echocardiogram and catheterization, there were no differences based on approach in aortic valve gradient, degree of aortic insufficiency (AI), or degree of mitral regurgitation (MR). Both approaches were equally efficacious in gradient reduction (45 ± 17 vs. 44 ± 21 mmHg, p = 0.97), and there was no difference in post-intervention AI as assessed by both catheterization and echocardiogram (52% vs. 64% none or trivial, p = 0.74). Additionally, there was no difference in the proportion of patients with an increased severity of MR after BAV (15% vs. 22%, p = 0.52). The retrograde approach required a larger arterial catheter and was associated with a higher rate of arterial thrombosis (61% vs. 18%, p = 0.014). Both anterograde and retrograde approaches to neonatal BAV appear to be equally efficacious in the short term. The anterograde approach avoids the need for a larger arterial catheter and may reduce the risk of arterial thrombosis.

A Case Study of Controlling Crossover in a Selection Hyper-heuristic Framework Using the Multidimensional Knapsack Problem.

Hyper-heuristics are high-level methodologies for solving complex problems that operate on a search space of heuristics. In a selection hyper-heuristic framework, a heuristic is chosen from an existing set of low-level heuristics and applied to the current solution to produce a new solution at each point in the search. The use of crossover low-level heuristics is possible in an increasing number of general-purpose hyper-heuristic tools such as HyFlex and Hyperion. However, little work has been undertaken to assess how best to utilise it. Since a single-point search hyper-heuristic operates on a single candidate solution, and two candidate solutions are required for crossover, a mechanism is required to control the choice of the other solution. The frameworks we propose maintain a list of potential solutions for use in crossover. We investigate the use of such lists at two conceptual levels. First, crossover is controlled at the hyper-heuristic level where no problem-specific information is required. Second, it is controlled at the problem domain level where problem-specific information is used to produce good-quality solutions to use in crossover. A number of selection hyper-heuristics are compared using these frameworks over three benchmark libraries with varying properties for an NP-hard optimisation problem: the multidimensional 0-1 knapsack problem. It is shown that allowing crossover to be managed at the domain level outperforms managing crossover at the hyper-heuristic level in this problem domain.

Is nevirapine atropisomeric? Experimental and computational evidence for rapid conformational inversion.

The non-nucleoside reverse transcriptase inhibitor nevirapine displays in its room temperature (1)H-NMR spectrum signals characteristic of a chiral compound. Following suggestions in the recent literature that nevirapine may display atropisomerism-and therefore be a chiral compound, due to slow interconversion between two enantiomeric conformers-we report the results of an NMR and computational study which reveal that while nevirapine does indeed possess two stable enantiomeric conformations, they interconvert with a barrier of about 76 kJ mol(-1) at room temperature. Nevirapine has a half life for enantiomerisation at room temperature of the order of seconds, is not atropisomeric, and cannot exist as separable enantiomers.

Automating the packing heuristic design process with genetic programming.

The literature shows that one-, two-, and three-dimensional bin packing and knapsack packing are difficult problems in operational research. Many techniques, including exact, heuristic, and metaheuristic approaches, have been investigated to solve these problems and it is often not clear which method to use when presented with a new instance. This paper presents an approach which is motivated by the goal of building computer systems which can design heuristic methods. The overall aim is to explore the possibilities for automating the heuristic design process. We present a genetic programming system to automatically generate a good quality heuristic for each instance. It is not necessary to change the methodology depending on the problem type (one-, two-, or three-dimensional knapsack and bin packing problems), and it therefore has a level of generality unmatched by other systems in the literature. We carry out an extensive suite of experiments and compare with the best human designed heuristics in the literature. Note that our heuristic design methodology uses the same parameters for all the experiments. The contribution of this paper is to present a more general packing methodology than those currently available, and to show that, by using this methodology, it is possible for a computer system to design heuristics which are competitive with the human designed heuristics from the literature. This represents the first packing algorithm in the literature able to claim human competitive results in such a wide variety of packing domains.

Search graph structure and its implications for multi-graph constrained routing and scheduling problems.

Multi-graphs where several edges connect a pair of nodes are an important modelling approach for many real-world optimisation problems. The multi-graph structure is often based on infrastructure and available connections between nodes. In this study, we conduct case studies for a special type of constrained routing and scheduling problems. Using the airport ground movement problem as an example, we analyse how the number of parallel edges and their costs in multi-graph structure influence the quality of obtained solutions found by the routing algorithm. The results show that the number of parallel edges not only affects the computational complexity but also the number of trade-off solutions and the quality of the found solutions. An indicator is further proposed which can estimate when the multi-graph would benefit from a higher number of parallel edges. Furthermore, we show that including edges with dominated costs in the multi-graph can also improve the results in the presence of time window constraints. The findings pave the way to an informed approach to multi-graph creation for similar problems based on multi-graphs.

Effect of acute administration of an herbal preparation on blood pressure and heart rate in humans.

Confusion and controversy exist regarding the cardiovascular effects of dietary supplements containing caffeine and Citrus aurantium (bitter orange) extract. The primary protoalkaloidal ingredient in bitter orange extract is p-synephrine which has some structural similarities to ephedrine and nor-epinephrine, but exhibits markedly different pharmacokinetic and receptor binding properties. The goal of this study was to investigate the cardiovascular effects of a product containing caffeine, bitter orange extract (p-synephrine) and green tea extract in mildly overweight individuals. Fourteen female and nine male subjects (age 24.7 ±7.4 yrs, BMI: 26.6 ±3.8) volunteered in this randomized, placebo-controlled, crossover, double-blind designed study. On day one, subjects entered the laboratory following an overnight fast. Heart rate and blood pressure were recorded at 60 min. Expired air was analyzed for the next 10 min of the session. At each of three meals, subjects ingested one capsule that was either a non-caloric placebo or a dietary supplement that contained 13 mg p-synephrine and 176 mg caffeine. On the following day, the subjects returned and repeated the protocol for data collection beginning 60 min after consuming one capsule of the placebo or the dietary supplement. No effects of the dietary supplement on heart rate, systolic and diastolic blood pressure or mean arterial pressure were observed. No between or within group differences were observed when data were analyzed for gender and caffeine usage. A small but significant decrease in resting respiratory exchange ratio was observed for the low caffeine user group in response to the product containing caffeine and p-synephrine. The results of this study indicate that ingestion of a product containing bitter orange extract, caffeine and green tea extract does not lead to increased cardiovascular stress and that fat oxidation may increase in certain populations.

Evolutionary squeaky wheel optimization: a new framework for analysis.

Squeaky wheel optimization (SWO) is a relatively new metaheuristic that has been shown to be effective for many real-world problems. At each iteration SWO does a complete construction of a solution starting from the empty assignment. Although the construction uses information from previous iterations, the complete rebuilding does mean that SWO is generally effective at diversification but can suffer from a relatively weak intensification. Evolutionary SWO (ESWO) is a recent extension to SWO that is designed to improve the intensification by keeping the good components of solutions and only using SWO to reconstruct other poorer components of the solution. In such algorithms a standard challenge is to understand how the various parameters affect the search process. In order to support the future study of such issues, we propose a formal framework for the analysis of ESWO. The framework is based on Markov chains, and the main novelty arises because ESWO moves through the space of partial assignments. This makes it significantly different from the analyses used in local search (such as simulated annealing) which only move through complete assignments. Generally, the exact details of ESWO will depend on various heuristics; so we focus our approach on a case of ESWO that we call ESWO-II and that has probabilistic as opposed to heuristic selection and construction operators. For ESWO-II, we study a simple problem instance and explicitly compute the stationary distribution probability over the states of the search space. We find interesting properties of the distribution. In particular, we find that the probabilities of states generally, but not always, increase with their fitness. This nonmonotonocity is quite different from the monotonicity expected in algorithms such as simulated annealing.

RNA FRABASE 2.0: an advanced web-accessible database with the capacity to search the three-dimensional fragments within RNA structures.

BACKGROUND: Recent discoveries concerning novel functions of RNA, such as RNA interference, have contributed towards the growing importance of the field. In this respect, a deeper knowledge of complex three-dimensional RNA structures is essential to understand their new biological functions. A number of bioinformatic tools have been proposed to explore two major structural databases (PDB, NDB) in order to analyze various aspects of RNA tertiary structures. One of these tools is RNA FRABASE 1.0, the first web-accessible database with an engine for automatic search of 3D fragments within PDB-derived RNA structures. This search is based upon the user-defined RNA secondary structure pattern. In this paper, we present and discuss RNA FRABASE 2.0. This second version of the system represents a major extension of this tool in terms of providing new data and a wide spectrum of novel functionalities. An intuitionally operated web server platform enables very fast user-tailored search of three-dimensional RNA fragments, their multi-parameter conformational analysis and visualization. DESCRIPTION: RNA FRABASE 2.0 has stored information on 1565 PDB-deposited RNA structures, including all NMR models. The RNA FRABASE 2.0 search engine algorithms operate on the database of the RNA sequences and the new library of RNA secondary structures, coded in the dot-bracket format extended to hold multi-stranded structures and to cover residues whose coordinates are missing in the PDB files. The library of RNA secondary structures (and their graphics) is made available. A high level of efficiency of the 3D search has been achieved by introducing novel tools to formulate advanced searching patterns and to screen highly populated tertiary structure elements. RNA FRABASE 2.0 also stores data and conformational parameters in order to provide "on the spot" structural filters to explore the three-dimensional RNA structures. An instant visualization of the 3D RNA structures is provided. RNA FRABASE 2.0 is freely available at http://rnafrabase.cs.put.poznan.pl. CONCLUSIONS: RNA FRABASE 2.0 provides a novel database and powerful search engine which is equipped with new data and functionalities that are unavailable elsewhere. Our intention is that this advanced version of the RNA FRABASE will be of interest to all researchers working in the RNA field.

Search strategies in structural bioinformatics.

Optimisation problems pervade structural bioinformatics. In this review, we describe recent work addressing a selection of bioinformatics challenges. We begin with a discussion of research into protein structure comparison, and highlight the utility of Kolmogorov complexity as a measure of structural similarity. We then turn to research into de novo protein structure prediction, in which structures are generated from first principles. In this endeavour, there is a compromise between the detail of the model and the extent to which the conformational space of the protein can be sampled. We discuss some developments in this area, including off-lattice structure prediction using the great deluge algorithm. One strategy to reduce the size of the search space is to restrict the protein chain to sites on a regular lattice. In this context, we highlight the use of memetic algorithms, which combine genetic algorithms with local optimisation, to the study of simple protein models on the two-dimensional square lattice and the face-centred cubic lattice.

Effect of a region-wide incorporation of an algorithm based on the 2012 international consensus guideline on the practice pattern for the management of pancreatic cystic neoplasms in an integrated health system.

AIM: To examine the practice pattern in Kaiser Permanente Southern California (KPSC), i.e., gastroenterology (GI)/surgery referrals and endoscopic ultrasound (EUS), for pancreatic cystic neoplasms (PCNs) after the region-wide dissemination of the PCN management algorithm. METHODS: Retrospective review was performed; patients with PCN diagnosis given between April 2012 and April 2015 (18 mo before and after the publication of the algorithm) in KPSC (integrated health system with 15 hospitals and 202 medical offices in Southern California) were identified. RESULTS: 2558 (1157 pre- and 1401 post-algorithm) received a new diagnosis of PCN in the study period. There was no difference in the mean cyst size (pre- 19.1 mm vs post- 18.5 mm, P = 0.119). A smaller percentage of PCNs resulted in EUS after the implementation of the algorithm (pre- 45.5% vs post- 34.8%, P < 0.001). A smaller proportion of patients were referred for GI (pre- 65.2% vs post- 53.3%, P < 0.001) and surgery consultations (pre- 24.8% vs post- 16%, P < 0.001) for PCN after the implementation. There was no significant change in operations for PCNs. Cost of diagnostic care was reduced after the implementation by 24%, 18%, and 36% for EUS, GI, and surgery consultations, respectively, with total cost saving of 24%. CONCLUSION: In the current healthcare climate, there is increased need to optimize resource utilization. Dissemination of an algorithm for PCN management in an integrated health system resulted in fewer EUS and GI/surgery referrals, likely by aiding the physicians ordering imaging studies in the decision making for the management of PCNs. This translated to cost saving of 24%, 18%, and 36% for EUS, GI, and surgical consultations, respectively, with total diagnostic cost saving of 24%.

Effect of Fetal Growth on 1-Year Mortality in Neonates With Critical Congenital Heart Disease.

Background Infants with critical congenital heart disease ( CCHD ) are more likely to be small for gestational age (GA). It is unclear how this affects mortality. The authors investigated the effect of birth weight Z score on 1-year mortality separately in preterm (GA <37 weeks), early-term (GA 37-38 weeks), and full-term (GA 39-42 weeks) infants with CCHD . Methods and Results Live-born infants with CCHD and GA 22 to 42 weeks born in California 2007-2012 were included in the analysis. The primary predictor was Z score for birth weight and the primary outcome was 1-year mortality. Multivariable logistic regression was used. Results are presented as adjusted odds ratios and 95% confidence intervals ( CIs ). The authors identified 6903 infants with CCHD . For preterm and full-term infants, only a Z score for birth weight <-2 was associated with increased mortality compared with the reference group ( Z score 0-0.5, adjusted odds ratio, 2.15 [95% CI , 1.1-4.21] and adjusted odds ratio, 3.93 [95% CI , 2.32-6.68], respectively). In contrast, in early-term infants, the adjusted odds ratios for Z scores <-2, -2 to -1, and -1 to -0.5 were 3.42 (95% CI , 1.93-6.04), 1.78 (95% CI , 1.12-2.83), and 2.03 (95% CI , 1.27-3.23), respectively, versus the reference group. Conclusions GA seems to modify the effect of birth weight Z score on mortality in infants with CCHD . In preterm and full-term infants, only the most severe small-for-GA infants ( Z score <-2) were at increased risk for mortality, while, in early-term infants, the risk extended to mild to moderate small-for-GA infants ( Z score <-0.5). This information helps to identify high-risk infants and is useful for surgical planning.

ProCKSI: a decision support system for Protein (structure) Comparison, Knowledge, Similarity and Information.

BACKGROUND: We introduce the decision support system for Protein (Structure) Comparison, Knowledge, Similarity and Information (ProCKSI). ProCKSI integrates various protein similarity measures through an easy to use interface that allows the comparison of multiple proteins simultaneously. It employs the Universal Similarity Metric (USM), the Maximum Contact Map Overlap (MaxCMO) of protein structures and other external methods such as the DaliLite and the TM-align methods, the Combinatorial Extension (CE) of the optimal path, and the FAST Align and Search Tool (FAST). Additionally, ProCKSI allows the user to upload a user-defined similarity matrix supplementing the methods mentioned, and computes a similarity consensus in order to provide a rich, integrated, multicriteria view of large datasets of protein structures. RESULTS: We present ProCKSI's architecture and workflow describing its intuitive user interface, and show its potential on three distinct test-cases. In the first case, ProCKSI is used to evaluate the results of a previous CASP competition, assessing the similarity of proposed models for given targets where the structures could have a large deviation from one another. To perform this type of comparison reliably, we introduce a new consensus method. The second study deals with the verification of a classification scheme for protein kinases, originally derived by sequence comparison by Hanks and Hunter, but here we use a consensus similarity measure based on structures. In the third experiment using the Rost and Sander dataset (RS126), we investigate how a combination of different sets of similarity measures influences the quality and performance of ProCKSI's new consensus measure. ProCKSI performs well with all three datasets, showing its potential for complex, simultaneous multi-method assessment of structural similarity in large protein datasets. Furthermore, combining different similarity measures is usually more robust than relying on one single, unique measure. CONCLUSION: Based on a diverse set of similarity measures, ProCKSI computes a consensus similarity profile for the entire protein set. All results can be clustered, visualised, analysed and easily compared with each other through a simple and intuitive interface.ProCKSI is publicly available at http://www.procksi.net for academic and non-commercial use.

Simplified partial digest problem: enumerative and dynamic programming algorithms.

We study the Simplified Partial Digest Problem (SPDP), which is a mathematical model for a new simplified partial digest method of genome mapping. This method is easy for laboratory implementation and robust with respect to the experimental errors. SPDP is NP-hard in the strong sense. We present an $O(n2;n)$ time enumerative algorithm and an O(n(2q)) time dynamic programming algorithm for the error-free SPDP, where $n$ is the number of restriction sites and n is the number of distinct intersite distances. We also give examples of the problem, in which there are 2(n+2)/(3)-1 non-congruent solutions. These examples partially answer a question recently posed in the literature about the number of solutions of SPDP. We adapt our enumerative algorithm for handling SPDP with imprecise input data. Finally, we describe and discuss the results of the computer experiments with our algorithms.

Machine learning in virtual screening.

In this review, we highlight recent applications of machine learning to virtual screening, focusing on the use of supervised techniques to train statistical learning algorithms to prioritize databases of molecules as active against a particular protein target. Both ligand-based similarity searching and structure-based docking have benefited from machine learning algorithms, including naïve Bayesian classifiers, support vector machines, neural networks, and decision trees, as well as more traditional regression techniques. Effective application of these methodologies requires an appreciation of data preparation, validation, optimization, and search methodologies, and we also survey developments in these areas.

The effects of ad libitum fluid ingestion on fluid balance during alpine skiing in recreational skiers.

The aim of this study was to assess the influence of ad libitum water ingestion, using a back-mounted hydration system (BMHS), on fluid balance during alpine skiing. Fourteen skiers skied on two different days. On one day, seven skiers ingested water during skiing via the BMHS and the other seven skiers refrained from fluid ingestion during skiing until the midday break (NW trial). On the second day, the trials were reversed. Results indicated that when skiers used the BMHS they drank significantly more water than during the NW trials (2.0 +/- 0.9 vs. 0.78 +/- 0.4 litres). However, skiers drank significantly more at the midday break during the NW trials than during the BMHS trials (0.78 +/- 0.4 vs. 0.4 +/- 0.2 litres). Percent change in plasma volume was less during the BMHS trials than during the NW trials (-0.1 +/- 5.3 vs. -4.9 +/- 5.2%), urine osmolality was maintained in the BMHS trials but rose from 295 +/- 80 to 818 +/- 168 mOsm . kg(-1) at midday during the NW trials, and body mass loss was minimized during the BMHS trials compared with the NW trials (0.4 +/- 0.4 vs. 1.1 +/- 0.2 kg). Skiers reported that they felt significantly better when they ingested water during the BMHS trials. In conclusion, a back-mounted hydration system allowed the skiers to maintain hydration status.