Preparation and characterization of proton‐exchange hybrid membranes

Two types of composite were prepared, based on a thermoplastic polymer, polyvinylidene fluoride (PVDF), and an elastomer, ethylene‐propylene‐diene terpolymer (EPDM), respectively. We obtained both series by addition of an inorganic proton‐conducting antimonic acid derivative (HSb) and polystyrene crosslinked with a small percentage of divinylbenzene (PS‐co‐DVB). From these composites, membranes were obtained and subjected to a heterogeneous‐phase sulfonation reaction with chlorosulfonic acid. All experimental materials were characterized from a morphological and electrical point of view, by means of techniques such as differential scanning calorimetry (DSC), dynamic mechanical analysis (DMA), non‐isothermal crystallization and complex impedance analysis. Copyright © 2005 Society of Chemical Industry     

Fullerene Reactivity in an Oxygen Plasma

Fullerene reactivity in an oxygen plasma was measured and compared with those determined under the same conditions for a comprehensive set of 50 carbon materials. The possible reasons for the high plasma reactivity of the fullerene sample in an oxygen plasma are discussed.     

The effect of structural features on mechanical properties of loose optical fiber poly(butylene terephthalate) tubes

Results of a study on the modifying mechanical properties of loose optical‐fiber poly(butylene terephthalate) (PBT) tubes, produced during the standard industrial extrusion process, show that heat treatment make the structure of their material to change. The study comprised measurements of mechanical strengths properties of the tubes (tensile strength, compression strength, kinking) and determination of tube material structure [by differential thermal analysis (DTA), wide angle X‐ray scattering analysis (WAXD), and scanning electron microscopy (SEM)]. Results of the study allowed observation that the annealing at 70°C for 34 h of the tubes caused the crystalline α phase to increase in the tube material from ～28.5% to ～31.5% and the structure of the existing crystallites to become more perfect. This made the values of certain mechanical properties of the tubes to increase even by as much as 30%. The tubes following such thermal treatment could be used in cables exposed to heavy‐duty operation in arduous environments, where a larger margin from the standpoint of mechanical properties is required. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 2130–2134, 2002     

Current basis for the ultrastructural clinical diagnosis of tumors: A review

The ultrastructural diagnosis of tumors requires a careful analysis that should be done in an orderly fashion. It requires precise planning from the time of specimen collection to the selection of the area to be examined. Pictures must be taken systematically and every micrograph should allow to answer whether the number of cells photographed is adequate; whether mitoses are present, what is the pattern of the tumor; what is the appearance of the cell membrane; whether the cells are joined by junctional complexes; whether free surfaces possess microvilli or cilia; what organelles are present and how they are distributed; whether there are secretory granules, melanosomes, or other cytoplasmic elements. Nuclear and nucleolar size and shape have to be taken into consideration. The composition of the interstitial extracellular matrix is important in certain types of tumors. Although these questions are not the only ones to be addressed, their use in a logical fashion is helpful when it concerns the ultrastructural diagnosis.     

Precision Oncology via NMR-Based Metabolomics: A Review on Breast Cancer

Precision oncology is an emerging approach in cancer care. It aims at selecting the optimal therapy for the right patient by considering each patient’s unique disease and individual health status. In the last years, it has become evident that breast cancer is an extremely heterogeneous disease, and therefore, patients need to be appropriately stratified to maximize survival and quality of life. Gene-expression tools have already positively assisted clinical decision making by estimating the risk of recurrence and the potential benefit from adjuvant chemotherapy. However, these approaches need refinement to further reduce the proportion of patients potentially exposed to unnecessary chemotherapy. Nuclear magnetic resonance (NMR) metabolomics has demonstrated to be an optimal approach for cancer research and has provided significant results in BC, in particular for prognostic and stratification purposes. In this review, we give an update on the status of NMR-based metabolomic studies for the biochemical characterization and stratification of breast cancer patients using different biospecimens (breast tissue, blood serum/plasma, and urine).     

Effect of different acids with Δ9,12-dienoic structures on Δ9 desaturation activity in rat liver microsomes

The effect of oral administration, for 24 or 48 hr, of different octadeca fatty acids containing a 9,12-dienoic structure on the fatty acid composition and Δ9 desaturation activity of liver microsomes of rat fed a fat-free diet was studied. The ethyl esters of linoelaidic and γ-linolenic acids, the methyl ester of linoleic acid and free columbinic acid were administered to rats maintained on a fat-free diet. The supplementation of the fat-free diet with linoelaidate produced no relevant changes in the fatty acid composition pattern of liver microsomes and did not modify the percentage of conversion of palmitic to palmitoleic acid. The addition of linoleate or γ-linolenate to the fat-free diet returned liver microsome Δ9 desaturation activity toward the control and partially restored the liver microsome fatty acid spectrum found in the fat-free diet. Columbinic acid (5-trans-9-cis,12-cis-18∶3), which cannot be transformed into arachidonic acid, also decreased the Δ9 desaturation activity enhanced by the fat-free diet and evoked changes in the microsomal fatty acid composition similar to those produced by the ω6 fatty acids. These results suggest that the modulation of Δ9 desaturase activity evoked by dietary administration of unsaturated acids of ω6 series would depend on thecis double bond configuration of these acids.     

The biological leaching of an auriferous pyrite ore

The oxidation of an auriferous pyrite ore sample was evaluated in biological leaching experiments for subsequent gold recovery via cyanidation. In batch cultures, organisms derived from the mine site oxidized pyrite and ferrous iron at pH values as low as pH 0.6. The recovery of gold was variable in shake flask experiments. In stirred tank bioreactor leaching, gold recovery was proportional to the extent of iron dissolution by bioleaching. The leaching of arsenic from the sample was also directly proportional to iron dissolution.     

Standard goal programming with fuzzy hierarchies: a sequential approach

This paper proposes a pragmatic model for multi-objective decision-making processes involving clusters of objectives which have a decisional meaning for the decision maker (DM). We provide the DMs with a comfortable tool that allows them to express their preferences both by comparing criteria of the same cluster and via the comparison between the different clusters. In standard goal programming the importance of the goals is modeled by the introduction of preferential weights or/and the incorporation of pre-emptive priorities. However, in many cases the DM is not able to establish a precise preference structure. Even in the case of precise weights the solution does not match necessarily the relative weights or, in the case of precise pre-emptive priority, the result could be very restrictive. In order to overcome these drawbacks, in this paper the normalized unwanted deviations are interpreted in terms of achievement degrees of the goals and fuzzy relations are used to model the relative importance of the goals. Thus, we show how several methodologies from the fuzzy goal programming literature can be tailored for solving standard GP problems. We apply this new modeling to problems where there is a “natural” clustering between goals of the same class. We address this situation by solving two phases; in the first one each class is handled separately taking into account the hierarchy of their goals and, in the second phase, we integrate the results of the first phase and the imprecise hierarchy of the different classes. We formulate a new goal programming model called as sequential goal programming with fuzzy hierarchy model. Because many real situations involve decision making in this environment, our proposal can be a useful tool of broad application. A numerical example illustrates the methodology.     

Cell-protection mechanism through autophagy in HGFs/<Emphasis Type="Italic">S. mitis</Emphasis> co-culture treated with Chitlac-nAg

Silver-based products have been proven to be effective in retarding and preventing bacterial growth since ancient times. In the field of restorative dentistry, the use of silver ions/nanoparticles has been explored to counteract bacterial infections, as silver can destroy bacterial cell walls by reacting with membrane proteins. However, it is also cytotoxic towards eukaryotic cells, which are capable of internalizing nanoparticles. In this work, we investigated the biological effects of Chitlac-nAg, a colloidal system based on a modified chitosan (Chitlac), administered for 24–48?h to a co-culture of primary human gingival fibroblasts and Streptococcus mitis in the presence of saliva, developed to mimic the microenvironment of the oral cavity. We sought to determine its efficiency to combat oral hygiene-related diseases without affecting eukaryotic cells. Cytotoxicity, reactive oxygen species production, apoptosis induction, nanoparticles uptake, and lysosome and autophagosome metabolism were evaluated. In vitro results show that Chitlac-nAg does not exert cytotoxic effects on human gingival fibroblasts, which seem to survive through a homoeostasis mechanism involving autophagy. That suggests that the novel biomaterial Chitlac-nAg could be a promising tool in the field of dentistry.     

Multiple instance learning for classifying students in learning management systems

In this paper, a new approach based on multiple instance learning is proposed to predict student’s performance and to improve the obtained results using a classical single instance learning. Multiple instance learning provides a more suitable and optimized representation that is adapted to available information of each student and course eliminating the missing values that make difficult to find efficient solutions when traditional supervised learning is used. To check the efficiency of the new proposed representation, the most popular techniques of traditional supervised learning based on single instances are compared to those based on multiple instance learning. Computational experiments show that when the problem is regarded as a multiple instance one, performance is significantly better and the weaknesses of single-instance representation are overcome.