Interaction of miltefosine with intercellular membranes of stratum corneum and biomimetic lipid vesicles

Miltefosine (MT) is an alkylphospholipid approved for breast cancer metastasis and visceral leishmaniasis treatments, although the respective action mechanisms at the molecular level remain poorly understood. In this work, the interaction of miltefosine with the lipid component of stratum corneum (SC), the uppermost skin layer, was studied by electron paramagnetic resonance (EPR) spectroscopy of several fatty acid spin-labels. In addition, the effect of miltefosine on (i) spherical lipid vesicles of 1,2-dipalmitoyl-sn-glycero-3-phosphatidylcholine (DPPC) and (ii) lipids extracted from SC was also investigated, by EPR and time-resolved polarized fluorescence methods. In SC of neonatal Wistar rats, 4% (w/w) miltefosine give rise to a large increase of the fluidity of the intercellular membranes, in the temperature range from 6 to about 50 degrees C. This effect becomes negligible at temperatures higher that ca. 60 degrees C. In large unilamelar vesicles of DPPC no significant changes could be observed with a miltefosine concentration 25% molar, in close analogy with the behavior of biomimetic vesicles prepared with bovine brain ceramide, behenic acid and cholesterol. In these last samples, a 25 mol% molar concentration of miltefosine produced only a modest decrease in the bilayer fluidity. Although miltefosine is not a feasible skin permeation enhancer due to its toxicity, the information provided in this work could be of utility in the development of a MT topical treatment of cutaneous leishmaniasis. Published by Elsevier B.V.

Uma análise dos principais elementos influenciadores da tomada de decisão de compra de produtos de marca própria de supermercados

A adoção de marcas próprias no mix de produtos de supermercados é uma ação estratégica que alguns varejistas estão utilizando para melhorar sua competitividade no setor. No Brasil, a participação de mercado das marcas próprias ainda é pouco representativa, o que reflete a atitude dos consumidores diante desses produtos. A proposta deste trabalho foi avaliar os fatores que influenciam no comportamento do consumidor em relação aos produtos de marcas próprias de supermercados. Foi desenvolvida uma pesquisa de campo de caráter exploratório com abordagem quantitativa, por meio de questionário auto-administrado, o que possibilitou a coleta de opiniões de uma amostra de 983 clientes de supermercados. Os resultados obtidos demonstram que os respondentes não possuem uma imagem positiva dos produtos de marcas próprias, devido: à grande variação na qualidade dos produtos dentro das categorias e entre as categorias ofertadas, ao risco percebido, à ausência de comunicação efetiva sobre os produtos e à imagem de inferioridade transmitida pelos atributos das marcas próprias como embalagem, forma de exposição e política de preços. Dos fatores obtidos, pode-se concluir que a imagem da loja, a comunicação e preço, a qualidade e preço destacaram-se como os mais importantes para os respondentes e que exerceram maior influência em seu comportamento.

Plasma kinetics of an LDL-like nanoemulsion and lipid transfer to HDL in subjects with glucose intolerance

OBJECTIVE: Glucose intolerance is frequently associated with an altered plasma lipid profile and increased cardiovascular disease risk. Nonetheless, lipid metabolism is scarcely studied in normolipidemic glucose-intolerant patients. The aim of this study was to investigate whether important lipid metabolic parameters, such as the kinetics of LDL free and esterified cholesterol and the transfer of lipids to HDL, are altered in glucose-intolerant patients with normal plasma lipids. METHODS: Fourteen glucose-intolerant patients and 15 control patients were studied; none of the patients had cardiovascular disease manifestations, and they were paired for age, sex, race and co-morbidities. A nanoemulsion resembling a LDL lipid composition (LDE) labeled with 14C-cholesteryl ester and ³H-free cholesterol was intravenously injected, and blood samples were collected over a 24-h period to determine the fractional clearance rate of the labels by compartmental analysis. The transfer of free and esterified cholesterol, triglycerides and phospholipids from the LDE to HDL was measured by the incubation of the LDE with plasma and radioactivity counting of the supernatant after chemical precipitation of non-HDL fractions. RESULTS: The levels of LDL, non-HDL and HDL cholesterol, triglycerides, apo A1 and apo B were equal in both groups. The 14C-esterified cholesterol fractional clearance rate was not different between glucose-intolerant and control patients, but the ³H-free-cholesterol fractional clearance rate was greater in glucose-intolerant patients than in control patients. The lipid transfer to HDL was equal in both groups. CONCLUSION: In these glucose-intolerant patients with normal plasma lipids, a faster removal of LDE free cholesterol was the only lipid metabolic alteration detected in our study. This finding suggests that the dissociation of free cholesterol from lipoprotein particles occurs in normolipidemic glucose intolerance and may participate in atherogenic signaling.

A semi-supervised classification technique based on interacting forces

Semi-supervised learning is a classification paradigm in which just a few labeled instances are available for the training process. To overcome this small amount of initial label information, the information provided by the unlabeled instances is also considered. In this paper, we propose a nature-inspired semi-supervised learning technique based on attraction forces. Instances are represented as points in a k-dimensional space, and the movement of data points is modeled as a dynamical system. As the system runs, data items with the same label cooperate with each other, and data items with different labels compete among them to attract unlabeled points by applying a specific force function. In this way, all unlabeled data items can be classified when the system reaches its stable state. Stability analysis for the proposed dynamical system is performed and some heuristics are proposed for parameter setting. Simulation results show that the proposed technique achieves good classification results on artificial data sets and is comparable to well-known semi-supervised techniques using benchmark data sets.

QuMinS: fast and scalable querying, mining and summarizing multi-modal databases

Given a large image set, in which very few images have labels, how to guess labels for the remaining majority? How to spot images that need brand new labels different from the predefined ones? How to summarize these data to route the user’s attention to what really matters? Here we answer all these questions. Specifically, we propose QuMinS, a fast, scalable solution to two problems: (i) Low-labor labeling (LLL) – given an image set, very few images have labels, find the most appropriate labels for the rest; and (ii) Mining and attention routing – in the same setting, find clusters, the top-'N IND.O' outlier images, and the 'N IND.R' images that best represent the data. Experiments on satellite images spanning up to 2.25 GB show that, contrasting to the state-of-the-art labeling techniques, QuMinS scales linearly on the data size, being up to 40 times faster than top competitors (GCap), still achieving better or equal accuracy, it spots images that potentially require unpredicted labels, and it works even with tiny initial label sets, i.e., nearly five examples. We also report a case study of our method’s practical usage to show that QuMinS is a viable tool for automatic coffee crop detection from remote sensing images.