Phylogeny of Lundia (Bignoniaceae) based on ndhF and PepC sequences

The circumscription of genera belonging to tribe Bignonieae (Bignoniaceae) has traditionally been complex, with only a few genera having stable circumscriptions in the various classification systems proposed for the tribe. The genus Lundia, for instance, is well characterized by a series of morphological synapomorphies and its circumscription has remained quite stable throughout its history. Despite the stable circumscription of Lundia, the circumscription of species within the genus has remained problematic. This study aims to reconstruct the phylogeny of Lundia in order to refine species circumscriptions, gain a better understanding of relationships between taxa, and identify potential morphological synapomorphies for species and major clades. We sampled 26 accessions representing 13 species of Lundia, and 5 outgroups, and reconstructed the phylogeny of the genus using a chloroplast (ndhF) and a nuclear marker (PepC). Data derived from sequences of the individual loci were analyzed using parsimony and Bayesian inference, and the combined molecular dataset was analyzed with Bayesian methods. The monophyly of Lundia nitidula, a species with a particularly complex circumscription, was tested using Shimodaira-Hasegawa (SH) test and the approximately unbiased test for phylogenetic tree selection (AU test). In addition, 40 morphological characters were mapped onto the tree that resulted from the analysis of the combined molecular dataset in order to identify morphological synapomorphies of individual species and major clades. Lundia and most species currently recognized within the genus were strongly supported as monophyletic in all analyses. One species, Lundia nitidula, was not resolved as monophyletic, but the monophyly of this species was not rejected by the AU and SH tests. Lundia sect. Eriolundia is resolved as paraphyletic in all analyses, while Lundia sect. Eulundia is monophyletic and supported by the same morphological characters traditionally used to circumscribe this section. The phylogeny of Lundia contributed important information for a better circumscription of species and served as basis the taxonomic revision of the genus.

The Seville Expert Workshop for Progress in Posttransplant Lymphoproliferative Disorders

Posttransplant lymphoproliferative disorders (PTLDs) are associated with significant morbidity and mortality among solid-organ transplant patients, but approaches to diagnosis and management vary considerably. An international multidisciplinary panel evaluated current understanding of risk factors and classification systems and developed recommendations to aid in PTLD prevention. We considered evidence on PTLD risk factors including Epstein- Barr virus serostatus and immunosuppression and identified knowledge gaps for future research. Recommendations address prophylactic and preemptive strategies to minimize PTLD development, including modulation of immunosuppression and antiviral drug regimens. Finally, new classification criteria were outlined that may help facilitate standardized reporting and improve our understanding of PTLD.

Elaboração de diagnósticos e intervenções à luz de diferentes sistemas de classificações de enfermagem

Este estudo faz uma análise sobre o uso de diferentes sistemas de classificação e o atendimento aos padrões estabelecidos pela ISO 18.104:2003 a partir de uma situação clínica fictícia. Foram elaborados diagnósticos e intervenções de enfermagem utilizando a NANDA-I, NIC e CIPE®, e analisou-se a correspondência terminológica destes sistemas de classificação ao modelo proposto pela norma ISO 18.104:2003. Para a construção de diagnósticos de enfermagem, a NANDA-I e a CIPE® adequando-se à norma ISO 18.104:2003. Para a construção das intervenções de enfermagem, a CIPE® atende ao modelo de referência terminológica proposto pela ISO 18104:2003. Por sua vez, a NIC não propõe um modelo de referência terminológica combinatória. A unificação das terminologias de enfermagem depende da revisão, padronização e teste dessas classificações para o estabelecimento de uma linguagem comum e sólida da profissão.

Analytic perturbation theory for bound states in the transfer matrix spectrum of weakly correlated lattice ferromagnetic spin systems

We consider general d-dimensional lattice ferromagnetic spin systems with nearest neighbor interactions in the high temperature region ('beta' << 1). Each model is characterized by a single site apriori spin distribution taken to be even. We also take the parameter 'alfa' = ('S POT.4') - 3 '(S POT.2') POT.2' > 0, i.e. in the region which we call Gaussian subjugation, where ('S POT.K') denotes the kth moment of the apriori distribution. Associated with the model is a lattice quantum field theory known to contain a particle of asymptotic mass -ln 'beta' and a bound state below the two-particle threshold. We develop a 'beta' analytic perturbation theory for the binding energy of this bound state. As a key ingredient in obtaining our result we show that the Fourier transform of the two-point function is a meromorphic function, with a simple pole, in a suitable complex spectral parameter and the coefficients of its Laurent expansion are analytic in 'beta'.

On the generalized canonical equations of Hamilton for a time-dependent mass particle

Fundamental principles of mechanics were primarily conceived for constant mass systems. Since the pioneering works of Meshcherskii (see historical review in Mikhailov (Mech. Solids 10(5):32-40, 1975), efforts have been made in order to elaborate an adequate mathematical formalism for variable mass systems. This is a current research field in theoretical mechanics. In this paper, attention is focused on the derivation of the so-called 'generalized canonical equations of Hamilton' for a variable mass particle. The applied technique consists in the consideration of the mass variation process as a dissipative phenomenon. Kozlov's (Stek. Inst. Math 223:178-184, 1998) method, originally devoted to the derivation of the generalized canonical equations of Hamilton for dissipative systems, is accordingly extended to the scenario of variable mass systems. This is done by conveniently writing the flux of kinetic energy from or into the variable mass particle as a 'Rayleigh-like dissipation function'. Cayley (Proc. R Soc. Lond. 8:506-511, 1857) was the first scholar to propose such an analogy. A deeper discussion on this particular subject will be left for a future paper.

Hypotheses, rationale, design, and methods for prognostic evaluation of cardiac biomarker elevation after percutaneous and surgical revascularization in the absence of manifest myocardial infarction. A comparative analysis of biomarkers and cardiac magnetic resonance. The MASS-V Trial

Background: Although the release of cardiac biomarkers after percutaneous (PCI) or surgical revascularization (CABG) is common, its prognostic significance is not known. Questions remain about the mechanisms and degree of correlation between the release, the volume of myocardial tissue loss, and the long-term significance. Delayed-enhancement of cardiac magnetic resonance (CMR) consistently quantifies areas of irreversible myocardial injury. To investigate the quantitative relationship between irreversible injury and cardiac biomarkers, we will evaluate the extent of irreversible injury in patients undergoing PCI and CABG and relate it to postprocedural modifications in cardiac biomarkers and long-term prognosis. Methods/Design: The study will include 150 patients with multivessel coronary artery disease (CAD) with left ventricle ejection fraction (LVEF) and a formal indication for CABG; 50 patients will undergo CABG with cardiopulmonary bypass (CPB); 50 patients with the same arterial and ventricular condition indicated for myocardial revascularization will undergo CABG without CPB; and another 50 patients with CAD and preserved ventricular function will undergo PCI using stents. All patients will undergo CMR before and after surgery or PCI. We will also evaluate the release of cardiac markers of necrosis immediately before and after each procedure. Primary outcome considered is overall death in a 5-year follow-up. Secondary outcomes are levels of CK-MB isoenzyme and I-Troponin in association with presence of myocardial fibrosis and systolic left ventricle dysfunction assessed by CMR. Discussion: The MASS-V Trial aims to establish reliable values for parameters of enzyme markers of myocardial necrosis in the absence of manifest myocardial infarction after mechanical interventions. The establishments of these indices have diagnostic value and clinical prognosis and therefore require relevant and different therapeutic measures. In daily practice, the inappropriate use of these necrosis markers has led to misdiagnosis and therefore wrong treatment. The appearance of a more sensitive tool such as CMR provides an unprecedented diagnostic accuracy of myocardial damage when correlated with necrosis enzyme markers. We aim to correlate laboratory data with imaging, thereby establishing more refined data on the presence or absence of irreversible myocardial injury after the procedure, either percutaneous or surgical, and this, with or without the use of cardiopulmonary bypass.

Determination of trace elements in bovine semen samples by inductively coupled plasma mass spectrometry and data mining techniques for identification of bovine class

The reproductive performance of cattle may be influenced by several factors, but mineral imbalances are crucial in terms of direct effects on reproduction. Several studies have shown that elements such as calcium, copper, iron, magnesium, selenium, and zinc are essential for reproduction and can prevent oxidative stress. However, toxic elements such as lead, nickel, and arsenic can have adverse effects on reproduction. In this paper, we applied a simple and fast method of multi-element analysis to bovine semen samples from Zebu and European classes used in reproduction programs and artificial insemination. Samples were analyzed by inductively coupled plasma spectrometry (ICP-MS) using aqueous medium calibration and the samples were diluted in a proportion of 1:50 in a solution containing 0.01% (vol/vol) Triton X-100 and 0.5% (vol/vol) nitric acid. Rhodium, iridium, and yttrium were used as the internal standards for ICP-MS analysis. To develop a reliable method of tracing the class of bovine semen, we used data mining techniques that make it possible to classify unknown samples after checking the differentiation of known-class samples. Based on the determination of 15 elements in 41 samples of bovine semen, 3 machine-learning tools for classification were applied to determine cattle class. Our results demonstrate the potential of support vector machine (SVM), multilayer perceptron (MLP), and random forest (RF) chemometric tools to identify cattle class. Moreover, the selection tools made it possible to reduce the number of chemical elements needed from 15 to just 8.

Development of Nanoinjector Devices for Electrospray Ionization - Tandem Mass Spectrometry (ESI-MSn)

In mass spectrometric (MS) systems with electrospray ionization (ESI), the sample can be analyzed coupled to separation systems (such as liquid chromatography or capillary electrophoresis) or simply by direct infusion. The greatest benefit of the type of injection is the possibility of continuous use of small amounts of samples over a long period of time. This extended analysis time allows a complete study of fragmentation by mass spectrometry, which is critical for structure elucidation of new compounds, or when using an ion trap mass analyzer. The injector filled with the sample is placed at the ESI source inlet creating an electric field suitable for the continuous formation of a spray (solvent and sample) and consequently, the gradual and even release of the sample. For the formation of the spray, is necessary that the injector end is metalized. The formation of a bilayer of titanium and gold provided an excellent attachment of the film, resulting in a nanoinjector for ionization/spray formation in the system for MS. The nanoinjectors showed high repeatability and stability over 100 min by continuous sampling with 10 mu L of sample.

Multi-element determination in Brazilian honey samples by inductively coupled plasma mass spectrometry and estimation of geographic origin with data mining techniques

Multi-element analysis of honey samples was carried out with the aim of developing a reliable method of tracing the origin of honey. Forty-two chemical elements were determined (Al, Cu, Pb, Zn, Mn, Cd, Tl, Co, Ni, Rb, Ba, Be, Bi, U, V, Fe, Pt, Pd, Te, Hf, Mo, Sn, Sb, P, La, Mg, I, Sm, Tb, Dy, Sd, Th, Pr, Nd, Tm, Yb, Lu, Gd, Ho, Er, Ce, Cr) by inductively coupled plasma mass spectrometry (ICP-MS). Then, three machine learning tools for classification and two for attribute selection were applied in order to prove that it is possible to use data mining tools to find the region where honey originated. Our results clearly demonstrate the potential of Support Vector Machine (SVM), Multilayer Perceptron (MLP) and Random Forest (RF) chemometric tools for honey origin identification. Moreover, the selection tools allowed a reduction from 42 trace element concentrations to only 5. (C) 2012 Elsevier Ltd. All rights reserved.

Using Machine Learning Classifiers to Assist Healthcare-Related Decisions: Classification of Electronic Patient Records

Surveillance Levels (SLs) are categories for medical patients (used in Brazil) that represent different types of medical recommendations. SLs are defined according to risk factors and the medical and developmental history of patients. Each SL is associated with specific educational and clinical measures. The objective of the present paper was to verify computer-aided, automatic assignment of SLs. The present paper proposes a computer-aided approach for automatic recommendation of SLs. The approach is based on the classification of information from patient electronic records. For this purpose, a software architecture composed of three layers was developed. The architecture is formed by a classification layer that includes a linguistic module and machine learning classification modules. The classification layer allows for the use of different classification methods, including the use of preprocessed, normalized language data drawn from the linguistic module. We report the verification and validation of the software architecture in a Brazilian pediatric healthcare institution. The results indicate that selection of attributes can have a great effect on the performance of the system. Nonetheless, our automatic recommendation of surveillance level can still benefit from improvements in processing procedures when the linguistic module is applied prior to classification. Results from our efforts can be applied to different types of medical systems. The results of systems supported by the framework presented in this paper may be used by healthcare and governmental institutions to improve healthcare services in terms of establishing preventive measures and alerting authorities about the possibility of an epidemic.

Structural, Spectroscopic (NMR, IR, and Raman), and DFT Investigation of the Self-Assembled Nanostructure of Pravastatin-LDH (Layered Double Hydroxides) Systems

Layered double hydroxide (LDH) nanocontainers, suitable as carriers for anionic drugs, were intercalated with Pravastatin drug using magnesium-aluminum and zinc-aluminum in a M-II/Al molar ratio equal 2 and different Al3+/Pravastatin molar ratios. Postsynthesis treatments were used in order to increase the materials crystallinity. Hybrid materials were characterized by a set of physical chemical techniques: chemical elemental analysis, X-ray diffraction (XRD), mass coupled thermal analyses, vibrational infrared and Raman spectroscopies, and solid-state C-13 nuclear magnetic resonance (NMR). Results were interpreted in light of computational density functional theory (DFT) calculations performed for Sodium Pravastatin in order to assign the data obtained for the LDH intercalated materials. XRD peaks of LDH-Pravastatin material and the one-dimensional (1D) electron density map pointed out to a bilayer arrangement of Pravastatin in the interlayer region, where its associated carboxylate and vicinal hydroxyl groups are close to the positive LDH. The structural organization observed for the stacked assembly containing the unsymmetrical and bulky monoanion Pravastatin and LDH seems to be promoted by a self-assembling process, in which local interactions are maximized and chloride ion cointercalation is required. It is observed a high similarity among vibrational and C-13 NMR spectra of Na-Pravastatin and LDH-Pravastatin materials. Those features indicate that the intercalation preserves the drug structural integrity. Spectroscopic techniques corroborate the nature of the guest species and their arrangement between the inorganic layers. Changes related to carboxylate, alcohol, and olefinic moieties are observed in both vibrational Raman and C-13 NMR spectra after the drug intercalation. Thus, Pravastatin ions are forced to be arranged as head to tail through intermolecular hydrogen bonding between adjacent organic species. The thermal decomposition profile of the hybrid samples is distinct of that one observed for Na-Pravastatin salt, however, with no visible increase in the thermal behavior when the organic anion is sequestrated within LDH gap.

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.

EVOLUTIONARY TRAJECTORIES OF ULTRACOMPACT "BLACK WIDOW" PULSARS WITH VERY LOW MASS COMPANIONS

The existence of millisecond pulsars with planet-mass companions in close orbits is challenging from the stellar evolution point of view. We calculate in detail the evolution of binary systems self-consistently, including mass transfer, evaporation, and irradiation of the donor by X-ray feedback, demonstrating the existence of a new evolutionary path leading to short periods and compact donors as required by the observations of PSR J1719-1438. We also point out the alternative of an exotic nature of the companion planet-mass star.

Effect of Complete Revascularization on 10-Year Survival of Patients With Stable Multivessel Coronary Artery Disease MASS II Trial

Background-The importance of complete revascularization remains unclear and contradictory. This current investigation compares the effect of complete revascularization on 10-year survival of patients with stable multivessel coronary artery disease (CAD) who were randomly assigned to percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG). Methods and Results-This is a post hoc analysis of the Second Medicine, Angioplasty, or Surgery Study (MASS II), which is a randomized trial comparing treatments in patients with stable multivessel CAD, and preserved systolic ventricular function. We analyzed patients who underwent surgery (CABG) or stent angioplasty (PCI). The survival free of overall mortality of patients who underwent complete (CR) or incomplete revascularization (IR) was compared. Of the 408 patients randomly assigned to mechanical revascularization, 390 patients (95.6%) underwent the assigned treatment; complete revascularization was achieved in 224 patients (57.4%), 63.8% of those in the CABG group and 36.2% in the PCI group (P = 0.001). The IR group had more prior myocardial infarction than the CR group (56.2% X 39.2%, P = 0.01). During a 10-year follow-up, the survival free of cardiovascular mortality was significantly different among patients in the 2 groups (CR, 90.6% versus IR, 84.4%; P = 0.04). This was mainly driven by an increased cardiovascular specific mortality in individuals with incomplete revascularization submitted to PCI (P = 0.05). Conclusions-Our study suggests that in 10-year follow-up, CR compared with IR was associated with reduced cardiovascular mortality, especially due to a higher increase in cardiovascular-specific mortality in individuals submitted to PCI.

Modeling and simulation of severe slugging with mass transfer effects

A mathematical model and numerical simulations are presented to investigate the dynamics of gas, oil and water flow in a pipeline-riser system. The pipeline is modeled as a lumped parameter system and considers two switchable states: one in which the gas is able to penetrate into the riser and another in which there is a liquid accumulation front, preventing the gas from penetrating the riser. The riser model considers a distributed parameter system, in which movable nodes are used to evaluate local conditions along the subsystem. Mass transfer effects are modeled by using a black oil approximation. The model predicts the liquid penetration length in the pipeline and the liquid level in the riser, so it is possible to determine which type of severe slugging occurs in the system. The method of characteristics is used to simplify the differentiation of the resulting hyperbolic system of equations. The equations are discretized and integrated using an implicit method with a predictor-corrector scheme for the treatment of the nonlinearities. Simulations corresponding to severe slugging conditions are presented and compared to results obtained with OLGA computer code, showing a very good agreement. A description of the types of severe slugging for the three-phase flow of gas, oil and water in a pipeline-riser system with mass transfer effects are presented, as well as a stability map. (C) 2011 Elsevier Ltd. All rights reserved.