Low resolution structural characterization of the Hsp70-interacting protein - Hip - from Leishmania braziliensis emphasizes its high asymmetry

The Hsp70 is an essential molecular chaperone in protein metabolism since it acts as a pivot with other molecular chaperone families. Several co-chaperones act as regulators of the Hsp70 action cycle, as for instance Hip (Hsp70-interacting protein). Hip is a tetratricopeptide repeat protein (TPR) that interacts with the ATPase domain in the Hsp70-ADP state, stabilizing it and preventing substrate dissociation. Molecular chaperones from protozoans, which can cause some neglected diseases, are poorly studied in terms of structure and function. Here, we investigated the structural features of Hip from the protozoa Leishmania braziliensis (LbHip), one of the causative agents of the leishmaniasis disease. LbHip was heterologously expressed and purified in the folded state, as attested by circular dichroism and intrinsic fluorescence emission techniques. LbHip forms an elongated dimer, as observed by analytical gel filtration chromatography, analytical ultracentrifugation and small angle X-ray scattering (SAXS). With the SAXS data a low resolution model was reconstructed, which shed light on the structure of this protein, emphasizing its elongated shape and suggesting its domain organization. We also investigated the chemical-induced unfolding behavior of LbHip and two transitions were observed. The first transition was related to the unfolding of the TPR domain of each protomer and the second transition of the dimer dissociation. Altogether. LbHip presents a similar structure to mammalian Hip, despite their low level of conservation, suggesting that this class of eukaryotic protein may use a similar mechanism of action. (C) 2012 Elsevier Inc. All rights reserved.

Network-based high level data classification

Traditional supervised data classification considers only physical features (e. g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.

Low levels of adherence with proton pump inhibitor therapy contribute to therapeutic failure in gastroesophageal reflux disease

To assess adherence to proton pump inhibitor (PPI) treatment and associated variables in patients with gastroesophageal reflux disease (GERD). Cross-sectional and prospective comprising 240 consecutive adult patients, diagnosed with GERD for whom continuous use of standard or double dose of omeprazole had been prescribed. Patients were ranked as ne-GERD (162: 67.5%) or e-GERD classified according to the Los Angeles classification as A (48:20.0%), B (21:8.6%), C (1:0.5%), D (1:0.5%), and Barrett's esophagus (7:2.9%). The Morisky questionnaire was applied to assess adherence to therapy and a GERD questionnaire to assess symptoms and their impact. Adherence was correlated with demographics, cotherapies, comorbidities, treatment duration, symptoms scores, endoscopic findings, and patient awareness of their disease. 126 patients (52.5%) exhibited high level of adherence and 114 (47.5%) low level. Youngers (P= 0.002) or married (O.R. 2.41, P= 0.03 vs. widowers) patients had lower levels of adherence; symptomatic patients exhibited lower adherence (P= 0.02). All other variables studied had no influence on adherence. Patients with GERD attending a tertiary referral hospital in Sao Paulo exhibited a high rate of low adherence to the prescribed PPI therapy that may play a role in the therapy failure. Age <60 years, marital status and being symptomatic were risk factors for low adherence.

PyGirl Generating Whole-System VMs from high-level models using PyPy

Virtual machines emulating hardware devices are generally implemented in low-level languages and using a low-level style for performance reasons. This trend results in largely difficult to understand, difficult to extend and unmaintainable systems. As new general techniques for virtual machines arise, it gets harder to incorporate or test these techniques because of early design and optimization decisions. In this paper we show how such decisions can be postponed to later phases by separating virtual machine implementation issues from the high-level machine-specific model. We construct compact models of whole-system VMs in a high-level language, which exclude all low-level implementation details. We use the pluggable translation toolchain PyPy to translate those models to executables. During the translation process, the toolchain reintroduces the VM implementation and optimization details for specific target platforms. As a case study we implement an executable model of a hardware gaming device. We show that our approach to VM building increases understandability, maintainability and extendability while preserving performance.

PyGirl: Generating Whole-System VMs from High-Level Prototypes Using PyPy

Virtual machines (VMs) emulating hardware devices are generally implemented in low-level languages for performance reasons. This results in unmaintainable systems that are difficult to understand. In this paper we report on our experience using the PyPy toolchain to improve the portability and reduce the complexity of whole-system VM implementations. As a case study we implement a VM prototype for a Nintendo Game Boy, called PyGirl, in which the high-level model is separated from low-level VM implementation issues. We shed light on the process of refactoring from a low-level VM implementation in Java to a high-level model in RPython. We show that our whole-system VM written with PyPy is significantly less complex than standard implementations, without substantial loss in performance.

Analysis of ⁸⁵Kr: a comparison at the 10-14 level using micro-liter samples

The isotopic abundance of 85Kr in the atmosphere, currently at the level of 10−11, has increased by orders of magnitude since the dawn of nuclear age. With a half-life of 10.76 years, 85Kr is of great interest as tracers for environmental samples such as air, groundwater and ice. Atom Trap Trace Analysis (ATTA) is an emerging method for the analysis of rare krypton isotopes at isotopic abundance levels as low as 10−14 using krypton gas samples of a few micro-liters. Both the reliability and reproducibility of the method are examined in the present study by an inter-comparison among different instruments. The 85Kr/Kr ratios of 12 samples, in the range of 10−13 to 10−10, are measured independently in three laboratories: a low-level counting laboratory in Bern, Switzerland, and two ATTA laboratories, one in Hefei, China, and another in Argonne, USA. The results are in agreement at the precision level of 5%.

Towards high-level execution primitives for and-parallelism: preliminary results

Most implementations of parallel logic programming rely on complex low-level machinery which is arguably difflcult to implement and modify. We explore an alternative approach aimed at taming that complexity by raising core parts of the implementation to the source language level for the particular case of and-parallelism. Therefore, we handle a signiflcant portion of the parallel implementation mechanism at the Prolog level with the help of a comparatively small number of concurrency-related primitives which take care of lower-level tasks such as locking, thread management, stack set management, etc. The approach does not eliminate altogether modiflcations to the abstract machine, but it does greatly simplify them and it also facilitates experimenting with different alternatives. We show how this approach allows implementing both restricted and unrestricted (i.e., non fork-join) parallelism. Preliminary experiments show that the amount of performance sacriflced is reasonable, although granularity control is required in some cases. Also, we observe that the availability of unrestricted parallelism contributes to better observed speedups.

The assessment of the level of knowledge about dietary fibre among the portuguese population

The aim of this work was to assess the degree of knowledge about dietary fibre (DF), as influenced by factors such as age, gender, level of education and living environment. For this, a descriptive cross- sectional study was undertaken by means of a questionnaire and the total number of respondents was 382. The results revealed that the participants had a not satisfying global level of knowledge (3.59 ± 0.64, on a scale from 1 to 5). The overall knowledge was found lower for young adults aged 19 to 30 years, when compared to adults aged over 31 and up to 65 years, being this difference statistically significant (p=0.030). However, no statistical significant differences were found between genders, levels of education or living environments. The low level of knowledge demonstrated by the enquired alerts for the need to plan some additional actions to further inform the Portuguese population about dietary fibre.

Why is Coccidoxenoides perminutus, a mealybug parasitoid, ineffective as a biocontrol agent - Inaccurate measures of parasitism or low adult survival?

Coccidoxenoides perminutus achieves only low levels of parasitism of its host Planococcus citri in southeast Queensland citrus. Two possible causes were investigated. Adult survival under natural conditions was assessed to determine whether providing adult food sources could enhance survival. Behavioural changes of hosts, induced by C perminutus parasitism, was also investigated to establish if parasitised P. citri move from their feeding site to seek protected shelters some distance away and are thus not accounted for in field assessments of parasitism rates. Unparasitised mealybugs placed in the field for two periods were retrieved before the effects of parasitism were manifested and parasitism rates were still low (0.3% at 5 days and 1.2% at 10 days). Levels of locomotion of P. citri exposed to C perminutus were compared with those of unexposed ones. Parasitised mealybugs, regardless of instar, undergo behavioural changes. In comparison to unparasitised controls, the mealybugs become highly active 7-14 days after exposure to wasps. All parasitised mealybugs undergo physical changes, their body becomes cylindrical, their legs go so rigid that the mealybugs become immobile, and this signifies the typical mummy appearance. All mealybugs that became mummies eventually fell from the host lemon fruit because of impaired locomotion and were caught on sticky traps that had been placed beneath the lemons. Consequently, their final site of mummification was not established. C perminutus adults provided with nectar or honey survived longer (about 5 days) in the field than those without food (about a day). Nectar from two plant species, Alpinia zerumbet and Datura candida, proved to be good sources of food for the adult wasps, and were comparable in quality to honey. The low level of parasitism achieved by C perminutus in southeast Queensland citrus thus appears to be a consequence of the short adult life and the negative effects of a harsh environment. Provision of a suitable food source (e.g., nectar) may well enhance levels of parasitism in the field. (c) 2005 Elsevier Inc. All rights reserved.

A DHA14 drug efflux gene from Xanthomonas albilineans confers high-level albicidin antibiotic resistance in Escherichia coli

Aims: Identification of a gene for self-protection from the antibiotic-producing plant pathogen Xanthomonas albilineans, and functional testing by heterologous expression. Methods and Results: Albicidin antibiotics and phytotoxins are potent inhibitors of prokaryote DNA replication. A resistance gene (albF) isolated by shotgun cloning from the X. albilineans albicidin-biosynthesis region encodes a protein with typical features of DHA14 drug efflux pumps. Low-level expression of albF in Escherichia coli increased the MIC of albicidin 3000-fold, without affecting tsx-mediated albicidin uptake into the periplasm or resistance to other tested antibiotics. Bioinformatic analysis indicates more similarity to proteins involved in self-protection in polyketide-antibiotic-producing actinomycetes than to multi-drug resistance pumps in other Gram-negative bacteria. A complex promoter region may co-regulate albF with genes for hydrolases likely to be involved in albicidin activation or self-protection. Conclusions: AlbF is the first apparent single-component antibiotic-specific efflux pump from a Gram-negative antibiotic producer. It shows extraordinary efficiency as measured by resistance level conferred upon heterologous expression. Significance and Impact of the Study: Development of the clinical potential of albicidins as potent bactericidial antibiotics against diverse bacteria has been limited because of low yields in culture. Expression of albF with recently described albicidin-biosynthesis genes may enable large-scale production. Because albicidins are X. albilineans pathogenicity factors, interference with AlbF function is also an opportunity for control of the associated plant disease.

Low back pain patients demonstrate increased hip extensor muscle activity during standardized submaximal rotation efforts

Study Design. A comparative study of trunk and hip extensor muscle recruitment patterns in 2 subject groups. Objective. To examine for changes in recruitment of the hip and back extensor muscles during low level isometric trunk rotation efforts in chronic low back pain (CLBP) subjects by comparison with matched asymptomatic control subjects. Summary of Background Data. Anatomic and biomechanical models have provided evidence that muscles attaching to the thoracolumbar fascia (TLF) are important for providing stabilization to the lumbopelvic region during trunk rotation. This has guided rehabilitation programs. The muscles that link diagonally to the posterior layer of the TLF have not previously been examined individually and compared during low-level trunk rotation efforts in CLBP patients and matched controls. Methods. Thirty CLBP patients and 30 matched controls were assessed using surface electromyography (EMG) as they performed low-level isometric rotation efforts while standing upright. Muscles studied included latissimus dorsi, erector spinae, upper and lower gluteus maximus, and biceps femoris. Subjects performed the rotation exertion with various levels of external trunk support, related to different functional tasks. Results. EMG results demonstrated that subjects with CLBP had significantly higher levels of recruitment for the lower and upper gluteus maximus (P < 0.05), hamstrings (P < 0.05), and erector spinae muscles (P < 0.05) during rotation to the left compared with the control subjects. Conclusion. This study provided evidence of increased muscle recruitment in CLBP patients when performing a standardized trunk rotation task. These results may have implications for the design of therapeutic exercise programs for CLBP patients.

A co-ordinated business object approach for supporting tactical level management decisions

The proliferation of data throughout the strategic, tactical and operational areas within many organisations, has provided a need for the decision maker to be presented with structured information that is appropriate for achieving allocated tasks. However, despite this abundance of data, managers at all levels in the organisation commonly encounter a condition of ‘information overload’, that results in a paucity of the correct information. Specifically, this thesis will focus upon the tactical domain within the organisation and the information needs of management who reside at this level. In doing so, it will argue that the link between decision making at the tactical level in the organisation, and low-level transaction processing data, should be through a common object model that used a framework based upon knowledge leveraged from co-ordination theory. In order to achieve this, the Co-ordinated Business Object Model (CBOM) was created. Detailing a two-tier framework, the first tier models data based upon four interactive object models, namely, processes, activities, resources and actors. The second tier analyses the data captured by the four object models, and returns information that can be used to support tactical decision making. In addition, the Co-ordinated Business Object Support System (CBOSS), is a prototype tool that has been developed in order to both support the CBOM implementation, and to also demonstrate the functionality of the CBOM as a modelling approach for supporting tactical management decision making. Containing a graphical user interface, the system’s functionality allows the user to create and explore alternative implementations of an identified tactical level process. In order to validate the CBOM, three verification tests have been completed. The results provide evidence that the CBOM framework helps bridge the gap between low level transaction data, and the information that is used to support tactical level decision making.

High Level Color Similarity Retrieval

In this paper a new method for image retrieval using high level color semantic features is proposed. It is based on extraction of low level color characteristics and their conversion into high level semantic features using Johannes Itten theory of color, Dempster-Shafer theory of evidence and fuzzy production rules.

Formal modeling and analysis techniques for high level Petri nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. ^ There are two issues in using HLPNs—modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. ^ For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. ^ For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. ^ The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.^

Formal Modeling and Analysis Techniques for High Level Petri Nets

Petri Nets are a formal, graphical and executable modeling technique for the specification and analysis of concurrent and distributed systems and have been widely applied in computer science and many other engineering disciplines. Low level Petri nets are simple and useful for modeling control flows but not powerful enough to define data and system functionality. High level Petri nets (HLPNs) have been developed to support data and functionality definitions, such as using complex structured data as tokens and algebraic expressions as transition formulas. Compared to low level Petri nets, HLPNs result in compact system models that are easier to be understood. Therefore, HLPNs are more useful in modeling complex systems. There are two issues in using HLPNs - modeling and analysis. Modeling concerns the abstracting and representing the systems under consideration using HLPNs, and analysis deals with effective ways study the behaviors and properties of the resulting HLPN models. In this dissertation, several modeling and analysis techniques for HLPNs are studied, which are integrated into a framework that is supported by a tool. For modeling, this framework integrates two formal languages: a type of HLPNs called Predicate Transition Net (PrT Net) is used to model a system's behavior and a first-order linear time temporal logic (FOLTL) to specify the system's properties. The main contribution of this dissertation with regard to modeling is to develop a software tool to support the formal modeling capabilities in this framework. For analysis, this framework combines three complementary techniques, simulation, explicit state model checking and bounded model checking (BMC). Simulation is a straightforward and speedy method, but only covers some execution paths in a HLPN model. Explicit state model checking covers all the execution paths but suffers from the state explosion problem. BMC is a tradeoff as it provides a certain level of coverage while more efficient than explicit state model checking. The main contribution of this dissertation with regard to analysis is adapting BMC to analyze HLPN models and integrating the three complementary analysis techniques in a software tool to support the formal analysis capabilities in this framework. The SAMTools developed for this framework in this dissertation integrates three tools: PIPE+ for HLPNs behavioral modeling and simulation, SAMAT for hierarchical structural modeling and property specification, and PIPE+Verifier for behavioral verification.