Tailored-Made Polydopamine Nanoparticles to Induce Ferroptosis in Breast Cancer Cells in Combination with Chemotherapy

Ferroptosis is gaining followers as mechanism of selective killing cancer cells in a non-apoptotic manner, and novel nanosystems capable of inducing this iron-dependent death are being increasingly developed. Among them, polydopamine nanoparticles (PDA NPs) are arousing interest, since they have great capability of chelating iron. In this work, PDA NPs were loaded with Fe³⁺ at different pH values to assess the importance that the pH may have in determining their therapeutic activity and selectivity. In addition, doxorubicin was also loaded to the nanoparticles to achieve a synergist effect. The in vitro assays that were performed with the BT474 and HS5 cell lines showed that, when Fe³⁺ was adsorbed in PDA NPs at pH values close to which Fe(OH)₃ begins to be formed, these nanoparticles had greater antitumor activity and selectivity despite having chelated a smaller amount of Fe³⁺. Otherwise, it was demonstrated that Fe³⁺ could be released in the late endo/lysosomes thanks to their acidic pH and their Ca²⁺ content, and that when Fe³⁺ was co-transported with doxorubicin, the therapeutic activity of PDA NPs was enhanced. Thus, reported PDA NPs loaded with both Fe³⁺ and doxorubicin may constitute a good approach to target breast tumors.     

Preparation, Characterisation and Catalytic Behaviour of a New TeVMoO Crystalline Phase

TeM_xMo_1.7O mixed oxides (M = V and/or Nb; x = 0-1.7) have been prepared by calcination of the corresponding salts at 600 °C in an atmosphere of N₂. A new crystalline phase, with a Te/V/Mo atomic ratio of 1/0.2-1.5/1.7, has been isolated and characterised by XRD and IR spectroscopy. This phase is observed in the TeVMo or TeVNbMo mixed oxide but not in the TeNbMo mixed oxide. The new crystalline phase shows an XRD pattern similar to Sb₄Mo₁₀O₃₁ and probably corresponds to the M1 phase recently proposed by Aouine et al. (Chem. Commun. 1180, 2001) to be present in the active and selective MoVTeNbO catalysts. Although these catalysts present a very low activity in the propane oxidation, they are active and selective in the oxidation of propene to acrolein and/or acrylic acid. However, the product distribution depends on the catalyst composition. Acrolein or acrylic acid can be selectively obtained from propene on Nb-free or Nb-containing TeVMo catalysts, respectively. The presence of both V and Nb, in addition to Mo and Te, appears to be important in the formation of acrylic acid from propene.     

Disorder Phenomena in Quantum Solids with Vacancies

Journal of Low Temperature Physics - We have investigated disorder phenomena in solid 4He near megting in presence of vacancies by means of Quantum Monte Carlo (MC) simulations using the Shadow...     

Cardiac beta-adrenoceptors, G-proteins and adenylate cyclase regulation during myocardial hypertrophy

Reactivity to Alcohol and Neutral Cues was compared in male, inpatient problem drinkers (N = 30). Subjects reported an overall desire not to drink alcohol which decreased in the presence of the Alcohol Cue. There were no cue-specific changes in heart rate, blood pressure and arousal level and a non-significant trend for increased stress in the Alcohol Cue condition. Subgroups of subjects reporting positive and negative desire for alcohol were identified. Subjects who reported negative desire for alcohol in the Alcohol Cue condition also reported greater self-efficacy to resist drinking in the future. These findings have implications for understanding the nature of self-reported desire for alcohol and its potential role in the treatment of alcohol dependence.     

Agronomical and bromatological studies in jicama (Polymnia sonchifolia Poep et Endl.)]

An analysis of tuber roots yield and nutritional characteristics for 10 lines of jícama (Polymnia sonchifolia Poepp et Endl.) was carried out under the environmental conditions of Santa Catalina Experimental Station (12 degrees C of temperature and 3,100 m above sea level). The following average mean values were obtained: A fresh tuber root's yield from 29,755 to 73,558 kg/ha with 41,547 kg/ha of average, while the yield of the useful part (roots without skin) was from 24,309 to 60,097 kg/ha with 33,944 kg/ha of average. On the other hand, average mean values of 3.7% of protein, 3.5% ashes, 1.5% fat, 3.4% fiber, 2.2% potassium, 0.12% phosphorus, 96 micrograms/100 g iron, and 390 micrograms/100 g zinc, were obtained from the edible root samples. Besides, we obtained average values of 2.47, 2.12, 1.63 and 2.51 g/100 g of fructose, alfa glucose, beta glucose and saccharose, respectively, on edible root samples with skin, for the 10 lines studied. All these analyses were reported on a dry basis.     

Toward automatic phenotyping of developing embryos from videos.

We describe a trainable system for analyzing videos of developing C. elegans embryos. The system automatically detects, segments, and locates cells and nuclei in microscopic images. The system was designed as the central component of a fully automated phenotyping system. The system contains three modules 1) a convolutional network trained to classify each pixel into five categories: cell wall, cytoplasm, nucleus membrane, nucleus, outside medium; 2) an energy-based model, which cleans up the output of the convolutional network by learning local consistency constraints that must be satisfied by label images; 3) a set of elastic models of the embryo at various stages of development that are matched to the label images.     

Development of calibration models for quality control in the production of ethylene/propylene copolymers by FTIR spectroscopy,multivariate statistical tools,and artificial neural networks

Principal component regression (PCR), partial least squares (PLS), StepWise ordinary least squares regression (OLS), and back‐propagation artificial neural network (BP‐ANN) are applied here for the determination of the propylene concentration of a set of 83 production samples of ethylene–propylene copolymers from their infrared spectra. The set of available samples was split into (a) a training set, for models calculation; (b) a test set, for selecting the correct number of latent variables in PCR and PLS and the end point of the training phase of BP‐ANN; (c) a production set, for evaluating the predictive ability of the models. The predictive ability of the models is thus evaluated by genuine predictions. The model obtained by StepWise OLS turned out to be the best one, both in fitting and prediction. The study of the breakdown number of samples to be included in the training set showed that at least 52 experiments are necessary to build a reliable and predictive calibration model. It can be concluded that FTIR spectroscopy and OLS can be properly employed for monitoring the synthesis or the final product of ethylene–propylene copolymers, by predicting the concentration of propylene directly along the process line. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Linear mixture model applied to Amazonian vegetation classification

Many research projects require accurate delineation of different secondary succession (SS) stages over large regions/subregions of the Amazon basin. However, the complexity of vegetation stand structure, abundant vegetation species, and the smooth transition between different SS stages make vegetation classification difficult when using traditional approaches such as the maximum likelihood classifier (MLC). Most of the time, classification distinguishes only between forest/non-forest. It has been difficult to accurately distinguish stages of SS. In this paper, a linear mixture model (LMM) approach is applied to classify successional and mature forests using Thematic Mapper (TM) imagery in the Rondônia region of the Brazilian Amazon. Three endmembers (i.e., shade, soil, and green vegetation or GV) were identified based on the image itself and a constrained least-squares solution was used to unmix the image. This study indicates that the LMM approach is a promising method for distinguishing successional and mature forests in the Amazon basin using TM data. It improved vegetation classification accuracy over that of the MLC. Initial, intermediate, and advanced successional and mature forests were classified with overall accuracy of 78.2% using a threshold method on the ratio of shade to GV fractions, a 7.4% increase over the MLC. The GV and shade fractions are sensitive to the change of vegetation stand structures and better capture biophysical structure information.