Morphology and adsorption properties of chemically modified MWCNT probed by nitrogen,n-propane and water vapor

The poor compatibility of carbon materials with different dispersion media can be overcome by surface functionalization. In this work, multiwall carbon nanotubes (MWCNTs) were doped by oxygen and nitrogen at low concentrations. Morphological and structural changes caused by chemical treatment were monitored using nitrogen, propane and water vapor adsorption measurements. Pore size distribution (PSD) functions derived from various models are compared. The contribution of slit-shaped pores to the total surface area available for adsorbed molecules is smaller than that of cylindrical pores. Functionalities with heteroatoms (both O and N) enhance water adsorption onto MWCNTs. However, no statistical difference is observed between the water adsorption properties of O- or N-containing MWCNTs.     

Avoiding structure degradation during activation of ordered mesoporous carbons

Hierarchical micro–mesoporous carbons with high porosity development and ordered structure were prepared. The innovative proposal consists in developing microporosity in ordered mesoporous carbon by chemical activation in template presence in order to minimize the structural damage. Thus, we have directly carried out the chemical activation of a mesoporous carbon/silica composite with KOH. The effect on mesoporous ordered structure of both KOH/carbon ratio and activation temperature has been studied. Following chemical activation the specific surface area is increased from 341 to 1757 m²/g and the micropore volume becomes almost six times larger than initial value. Although a slight widening of the mesopore distribution and an increase in the mesopore volume has been observed during activation, TEM and XRD results reveal an excellent conservation of the ordered mesoporous structure during activation even at conditions well above the limits that a CMK-3 type carbon can resist.     

ANXA1 Contained in EVs Regulates Macrophage Polarization in Tumor Microenvironment and Promotes Pancreatic Cancer Progression and Metastasis

The tumor microenvironment (TME) is a dynamic system where nontumor and cancer cells intercommunicate through soluble factors and extracellular vesicles (EVs). The TME in pancreatic cancer (PC) is critical for its aggressiveness and the annexin A1 (ANXA1) has been identified as one of the oncogenic elements. Previously, we demonstrated that the autocrine/paracrine activities of extracellular ANXA1 depend on its presence in EVs. Here, we show that the complex ANXA1/EVs modulates the macrophage polarization further contributing to cancer progression. The EVs isolated from wild type (WT) and ANXA1 knock-out MIA PaCa-2 cells have been administrated to THP-1 macrophages finding that ANXA1 is crucial for the acquisition of a protumor M2 phenotype. The M2 macrophages activate endothelial cells and fibroblasts to induce angiogenesis and matrix degradation, respectively. We have also found a significantly increased presence of M2 macrophage in mice tumor and liver metastasis sections previously obtained by orthotopic xenografts with WT cells. Taken together, our data interestingly suggest the relevance of ANXA1 as potential diagnostic/prognostic and/or therapeutic PC marker.     

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).     

Hereditary Prostate Cancer: Genes Related,Target Therapy and Prevention

Prostate cancer (PCa) is globally the second most diagnosed cancer type and the most common cause of cancer-related deaths in men. Family history of PCa, hereditary breast and ovarian cancer (HBOC) and Lynch syndromes (LS), are among the most important risk factors compared to age, race, ethnicity and environmental factors for PCa development. Hereditary prostate cancer (HPCa) has the highest heritability of any major cancer in men. The proportion of PCa attributable to hereditary factors has been estimated in the range of 5–15%. To date, the genes more consistently associated to HPCa susceptibility include mismatch repair (MMR) genes (MLH1, MSH2, MSH6, and PMS2) and homologous recombination genes (BRCA1/2, ATM, PALB2, CHEK2). Additional genes are also recommended to be integrated into specific research, including HOXB13, BRP1 and NSB1. Importantly, BRCA1/BRCA2 and ATM mutated patients potentially benefit from Poly (ADP-ribose) polymerase PARP inhibitors, through a mechanism of synthetic lethality, causing selective tumor cell cytotoxicity in cell lines. Moreover, the detection of germline alterations in MMR genes has therapeutic implications, as it may help to predict immunotherapy benefits. Here, we discuss the current knowledge of the genetic basis for inherited predisposition to PCa, the potential target therapy, and the role of active surveillance as a management strategy for patients with low-risk PCa. Finally, the current PCa guideline recommendations are reviewed.     

Applying Web usage mining for personalizing hyperlinks in Web-based adaptive educational systems

Nowadays, the application of Web mining techniques in e-learning and Web-based adaptive educational systems is increasing exponentially. In this paper, we propose an advanced architecture for a personalization system to facilitate Web mining. A specific Web mining tool is developed and a recommender engine is integrated into the AHA! system in order to help the instructor to carry out the whole Web mining process. Our objective is to be able to recommend to a student the most appropriate links/Web pages within the AHA! system to visit next. Several experiments are carried out with real data provided by Eindhoven University of Technology students in order to test both the architecture proposed and the algorithms used. Finally, we have also described the meaning of several recommendations, starting from the rules discovered by the Web mining algorithms.     

Combining propensity score matching and group-based trajectory analysis in an observational study.

In a nonrandomized or observational study, propensity scores may be used to balance observed covariates and trajectory groups may be used to control baseline or pretreatment measures of outcome. The trajectory groups also aid in characterizing classes of subjects for whom no good matches are available and to define substantively interesting groups between which treatment effects may vary. These and related methods are illustrated using data from a Montreal-based study. The effects on subsequent violence of gang joining at age 14 are studied while controlling for measured characteristics of boys prior to age 14. The boys are divided into trajectory groups based on violence from ages 11 to 13. Within trajectory group, joiners are optimally matched to a variable number of controls using propensity scores, Mahalanobis distances, and a combinatorial optimization algorithm. Use of variable ratio matching results in greater efficiency than pair matching and also greater bias reduction than matching at a fixed ratio. The possible impact of failing to adjust for an important but unmeasured covariate is examined using sensitivity analysis. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Modelling of palm oil production using fuzzy expert system

The production of crude palm oil and palm kernel is a complex problem due to the influence of processing variables and environmental factors. These processing variables influence the amount of crude palm oil and palm kernel losses during processing. Instead of mathematical model, fuzzy logic approach provides a simpler and easier mechanism to describe the relationships between the processing variables and the amount of crude palm oil and palm kernel losses. In this study, four fuzzy expert system models were developed for each palm oil processing station. An approximation of centre of gravity method for defuzzification is also proposed to enable the development of the model using Microsoft^®Excel. For comparison purpose, the models were also developed using MATLAB^®. Results obtained from the Excel model are found to be very close to the results from MATLAB.     

Study of different nanostructured carbon supports for fuel cell catalysts

Pt clusters were deposited by an impregnation process on three carbon supports: multi-wall carbon nanotubes (MWNT), single-wall carbon nanohorns (SWNH), and Vulcan XC-72 carbon black to investigate the effect of the carbon support structure on the possibility of reducing Pt loading on electrodes for direct methanol (DMFC) fuel cells without impairing performance. MWNT and SWNH were in-house synthesised by a DC and an AC arc discharge process between pure graphite electrodes, respectively. UV-vis spectrophotometry, scanning and transmission electron microscopy, X-ray diffraction, and cyclic voltammetry measurements were used to characterize the Pt particles deposited on the three carbon supports. A differential yield for Pt deposition, not strictly related to the surface area of the carbon support, was observed. SWNH showed the highest surface chemical activity toward Pt deposition. Pt deposited in different forms depending on the carbon support. Electrochemical characterizations showed that the Pt nanostructures deposited on MWNT are particularly efficient in the methanol oxidation reaction.