2,145 research outputs found
Metastable Markov chains: from the convergence of the trace to the convergence of the finite-dimensional distributions
We consider continuous-time Markov chains which display a family of wells at
the same depth. We provide sufficient conditions which entail the convergence
of the finite-dimensional distributions of the order parameter to the ones of a
finite state Markov chain. We also show that the state of the process can be
represented as a time-dependent convex combination of metastable states, each
of which is supported on one well
Noncommutative Thermofield Dynamics
The real-time operator formalism for thermal quantum field theories,
thermofield dynamics, is formulated in terms of a path-integral approach in
non-commutative spaces. As an application, the two-point function for a thermal
non-commutative theory is derived at the one-loop level. The
effect of temperature and the non-commutative parameter, competing with one
another, is analyzed.Comment: 13 pages; to be published in IJMP-A
Entamoeba histolytica and E. dispar trophozoites in the liver of hamsters: in vivo binding of antibodies and complement
Impact of glycemic control on the incidence of acute kidney injury in critically ill patients: a comparison of two strategies using the RIFLE criteria
OBJECTIVE: To compare the renal outcome in patients submitted to two different regimens of glycemic control, using the RIFLE criteria to define acute kidney injury. INTRODUCTION: The impact of intensive insulin therapy on renal function outcome is controversial. The lack of a criterion for AKI definition may play a role on that. METHODS: Included as the subjects were 228 randomly selected, critically ill patients engaged in intensive insulin therapyor in a carbohydrate-restrictive strategy. Renal outcome was evaluated through the comparison of the last RIFLE score obtained during the ICU stay and the RIFLE score at admission; the outcome was classified as favorable, stable or unfavorable. RESULTS: The two groups were comparable regarding demographic data. AKI developed in 52% of the patients and was associated with a higher mortality (39.4%) compared with those who did not have AKI (8.2%) (p<0.001). Renal function outcome was comparable between the two groups (p=0.37). We observed a significant correlation between blood glucose levels and the incidence of acute kidney injury (p=0.007). In the multivariate logistic regression analysis, only APACHE III scores higher than 60 were identified as an independent risk factor for unfavorable renal outcome. APACHE III scores>60, acute kidney injury and hypoglycemia were risk factors for mortality. CONCLUSION: Intensive insulin therapy and a carbohydrate-restrictive strategy were comparable regarding the incidence of acute kidney injury evaluated using RIFLE criteria
Giant Amazonian fish pirarucu (Arapaima gigas): Its viscera as a source of thermostable trypsin
A trypsin was purified from pyloric caeca of pirarucu (Arapaima gigas). the effect of metal ions and protease inhibitors on its activity and its physicochemical and kinetic properties, as well its N-terminal sequence, were determined. A single band (28.0 kDa) was observed by SDS-PAGE. Optimum pH and temperature were 9.0 and 65 degrees C, respectively. the enzyme was stable after incubation for 30 min in a wide pH range (6.0-11.5) and at 55 degrees C. the kinetic parameters K-m, k(cat) and k(cat)/K-m were 0.47 +/- 0.042 mM, 1.33 s(-1) and 2.82 s(-1) mM(-1), respectively, using BApNA as substrate. This activity was shown to be very sensitive to some metal ions, such as Fe2+, Hg2+, Zn2+, Al3+, Pb2+, and was highly inhibited by trypsin inhibitors. the trypsin N-terminal sequence IVGGYECPRNSVPYQ was found. the features of this alkaline peptidase suggest that it may have potential for industrial applications (e.g. food and detergent industries). (C) 2012 Elsevier B.V. All rights reserved.Financiadora de Estudos e Projetos (FINEP/RECAR-CINE)Ministerio da Aquicultura e Pesca (MAP)Empresa brasileira de pesquisa agropecuaria (Embrapa)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundacao de Apoio a Ciencia e Tecnologia do Estado de Pernambuco (FACEPE)Petroleo do Brasil S/A (PETROBRAS)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Univ Fed Pernambuco, Lab Enzimol LABENZ, Dept Bioquim, BR-50670420 Recife, PE, BrazilUniv Fed Pernambuco, LIKA, BR-50670420 Recife, PE, BrazilUniversidade Federal de São Paulo, Escola Paulista Med, Dept Biofis, BR-04044020 São Paulo, BrazilUniversidade Federal de São Paulo, Escola Paulista Med, Dept Biofis, BR-04044020 São Paulo, BrazilWeb of Scienc
Photodynamic Therapy as an adjunct in the Treatment of Medication-Related Osteonecrosis of the Jaw: A Case Report
Introduction: Medication-related osteonecrosis of the jaws (MRONJ) corresponds to an adverse effect of the use of drugs such as Bisphosphonates and Denusomab. The management of MRONJ tends to be conservative, through the guidance of oral hygiene, antibiotic therapy and mouthwashes. However, the use of antimicrobial photodynamic therapy (aPDT) has shown promise in the treatment of these injuries. The purpose of this article is to report a case of MRONJ treatment associated with aPDT.
Case report: A 75-year-old patient, with a history of breast cancer and use of intravenous Zoledronic Acid, presented with bilateral MRONJ lesions in tuberosity on the right and left sides. Treatment was conservatively instituted with the use of aPDT as an adjuvant. After 12 aPDT sessions, complete regression of the lesion was observed. However, after two weeks, the presence of a new lesion was noted, this time in the anterior region of the maxilla. The same protocol previously established was followed and after two aPDT sessions, the patient returned with complete lesion regression.
Conclusion: The use of aPDT may represent an important adjuvant within a set of clinical protocols in the treatment of MRONJ.
DOI:10.34172/jlms.2021.1
Biosynthesis of silver nanoparticles mediated by entomopathogenic fungi: antimicrobial resistance, nanopesticides, and toxicity
Silver nanoparticles are widely used in the biomedical and agri-food fields due to their versatility. The use of biological methods for the synthesis of silver nanoparticles has increased considerably due to their feasibility and high biocompatibility. In general, microorganisms have been widely explored for the production of silver nanoparticles for several applications. The objective of this work was to evaluate the use of entomopathogenic fungi for the biological synthesis of silver nanoparticles, in comparison to the use of other filamentous fungi, and the possibility of using these nanoparticles as antimicrobial agents and for the control of insect pests. In addition, the in vitro methods commonly used to assess the toxicity of these materials are discussed. Several species of filamentous fungi are known to have the ability to form silver nanoparticles, but few studies have been conducted on the potential of entomopathogenic fungi to produce these materials. The investigation of the toxicity of silver nanoparticles is usually carried out in vitro through cytotoxicity/genotoxicity analyses, using well-established methodologies, such as MTT and comet assays, respectively. The use of silver nanoparticles obtained through entomopathogenic fungi against insects is mainly focused on mosquitoes that transmit diseases to humans, with satisfactory results regarding mortality estimates. Entomopathogenic fungi can be employed in the synthesis of silver nanoparticles for potential use in insect control, but there is a need to expand studies on toxicity so to enable their use also in insect control in agriculture.The work was funded by the Coordination for the Improvement of Higher Education Personnel (Capes); Sergipe Agricultural Development Company (Emdagro), the Industrial Biotechnology Program, University Tiradentes, Sergipe Technological Park (SergipeTec), and the Banco do Nordeste.info:eu-repo/semantics/publishedVersio
Visceral leishmaniasis in the State of Maranhão, Brazil: evolution of an epidemic
The authors provide a brief report on the historical evolution of visceral leishmaniasis in the State of Maranhão, Brazil, evaluating possible factors for growth of the disease in the State and control measures by the Brazilian Ministry of Health to integrate health services finto the maintenance of control programs.Os autores fazem um breve relato da evolução histórica da leishmaniose visceral no Estado do Maranhão, Brasil, avaliando as possíveis causas da expansão da referida doença no Estado, assim como as medidas de controle adotadas pelo Ministério da Saúde objetivando a diminuição da incidência da mesma.Universidade Federal do Maranhão Faculdade de Medicina Departamento de PatologiaEscola Paulista de MedicinaUNIFESP, EPMSciEL
Deep-pretrained-FWI: combining supervised learning with physics-informed neural network
An accurate velocity model is essential to make a good seismic image.
Conventional methods to perform Velocity Model Building (VMB) tasks rely on
inverse methods, which, despite being widely used, are ill-posed problems that
require intense and specialized human supervision. Convolutional Neural
Networks (CNN) have been extensively investigated as an alternative to solve
the VMB task. Two main approaches were investigated in the literature:
supervised training and Physics-Informed Neural Networks (PINN). Supervised
training presents some generalization issues since structures, and velocity
ranges must be similar in training and test set. Some works integrated
Full-waveform Inversion (FWI) with CNN, defining the problem of VMB in the PINN
framework. In this case, the CNN stabilizes the inversion, acting like a
regularizer and avoiding local minima-related problems and, in some cases,
sparing an initial velocity model. Our approach combines supervised and
physics-informed neural networks by using transfer learning to start the
inversion. The pre-trained CNN is obtained using a supervised approach based on
training with a reduced and simple data set to capture the main velocity trend
at the initial FWI iterations. We show that transfer learning reduces the
uncertainties of the process, accelerates model convergence, and improves the
final scores of the iterative process.Comment: Paper present at machine Learning and the Physical Sciences workshop,
NeurIPS 202
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