Partial oxidation of methane towards hydrogen production over a promising class of catalysts: Rh supported on Ti-modified MgO

The partial oxidation of methane over the supported Rh (0.8 wt.%) catalysts was investigated. Two kinds of supports were used, MgO and Ti-modified MgO (prepared by grafting technique). Among the Ti-modified MgO supports, two different compounds were used as source of Ti: inorganic (chloride) and organic (alkoxide). The catalytic performance of Rh-supported catalysts depends on the support and varies in the sequence: Ti-MgO/I > Ti-MgO/O > MgO. Ti-containing catalysts exhibited higher activity and selectivity compared to MgO, which is especially noticeable at low temperature. Possible explanations for the phenomena observed were proposed on the basis of characterization results.     

Incremental wrapper-based gene selection from microarray data for cancer classification

Gene expression microarray is a rapidly maturing technology that provides the opportunity to assay the expression levels of thousands or tens of thousands of genes in a single experiment. We present a new heuristic to select relevant gene subsets in order to further use them for the classification task. Our method is based on the statistical significance of adding a gene from a ranked-list to the final subset. The efficiency and effectiveness of our technique is demonstrated through extensive comparisons with other representative heuristics. Our approach shows an excellent performance, not only at identifying relevant genes, but also with respect to the computational cost.     

The minimum dosage of praziquantel in the treatment of Taenia saginata, 1986-1993

Patients who have a unicornuate uterus with a noncommunicating rudimentary horn that contains an endometrial cavity are at risk for endometriosis and obstetric complications. As in this case, resection of the rudimentary horn can be performed laparoscopically without increased risk to the patient and with some potential benefit.     

Enantiomer analysis of chiral lactones in foods by on-line coupled reversed-phase liquid chromatography-gas chromatography

A new application is proposed for the on-line coupling of reversed-phase liquid chromatography to gas chromatography (RPLC-GC) that allows the GC chirospecific analysis of gamma-lactones in fruits and commercially available fruit-containing products. The use of a programmed temperature vaporizer as an interface with the system makes the transfer of large volume fractions (i.e., 2520 microL) of aqueous eluents from LC to GC possible (speed of sample transfer, 1800 microL/min). Relative standard deviations obtained for the investigated lactones under the experimental conditions vary from 7 to 14%. The described system enlarges the LC-GC application field and overcomes the limitations reported thus far concerning the use of typical normal-phase eluents (i.e., the transfer of rather small volume fractions at low speeds of sample introduction).     

Developing an expert law tutor

This paper outlines the development considerations which led to the construction of a prototype “expert law tutor”. This is a system which models the competencies of the trained law teacher and is intended primarily for use as an interactive student‐directed multidimensional learning tool. The aim is to computerize those activities which might be encountered in a real‐life tutorial exercise—research, reasoning, problem solving and advising, testing, diagnosis and feedback. The paper takes a liberal view of what constitutes an expert system. The terminology expert system is retained but is defined broadly, perhaps contrary to convention, to encompass not only an advisory component or a diagnostic tool but other tutorial functions. To highlight this difference reference is made to an “expert law tutor”. It is the “expertise” of the human law tutor which is called upon. For this reason the system includes a hypertext library or information component and an multiple choice assessment component as well as a legal adviser. Providing “expert” tutor feedback is a key element in the dialogue between system and student. The prototype system was developed using (inter alia) a rule‐based expert system shell and an object‐oriented hypertext tool, and the paper comments on the features of these development tools.     

Evolutionary Generalized Radial Basis Function neural networks for improving prediction accuracy in gene classification using feature selection

Radial Basis Function Neural Networks (RBFNNs) have been successfully employed in several function approximation and pattern recognition problems. The use of different RBFs in RBFNN has been reported in the literature and here the study centres on the use of the Generalized Radial Basis Function Neural Networks (GRBFNNs). An interesting property of the GRBF is that it can continuously and smoothly reproduce different RBFs by changing a real parameter τ. In addition, the mixed use of different RBF shapes in only one RBFNN is allowed. Generalized Radial Basis Function (GRBF) is based on Generalized Gaussian Distribution (GGD), which adds a shape parameter, τ, to standard Gaussian Distribution. Moreover, this paper describes a hybrid approach, Hybrid Algorithm (HA), which combines evolutionary and gradient-based learning methods to estimate the architecture, weights and node topology of GRBFNN classifiers. The feasibility and benefits of the approach are demonstrated by means of six gene microarray classification problems taken from bioinformatic and biomedical domains. Three filters were applied: Fast Correlation-Based Filter (FCBF), Best Incremental Ranked Subset (BIRS), and Best Agglomerative Ranked Subset (BARS); this was done in order to identify salient expression genes from among the thousands of genes in microarray data that can directly contribute to determining the class membership of each pattern. After different gene subsets were obtained, the proposed methodology was performed using the selected gene subsets as new input variables. The results confirm that the GRBFNN classifier leads to a promising improvement in accuracy.     

Delay-bounded data gathering in urban vehicular sensor networks

Vehicular sensor networks are an emerging network paradigm, suitable for various applications in vehicular environment making use of vehicles’ sensors as data sources and Inter-Vehicle Communication systems for the transmissions. We present a solution, based on vehicular sensor networks, for gathering data from a certain geographic area while satisfying with a specific delay bound. The method leverages the time interval during which the query is active in order to make the gathering process efficient, properly alternating data muling and multi-hop forwarding strategies like in delay-bounded routing protocols. Simulations show that our proposed solution succeeds in performing efficient data gathering outperforming other solutions.     

Nuclear Receptor Nur77 Controls Cardiac Fibrosis through Distinct Actions on Fibroblasts and Cardiomyocytes

Fibrosis is a hallmark of adverse cardiac remodeling, which promotes heart failure, but it is also an essential repair mechanism to prevent cardiac rupture, signifying the importance of appropriate regulation of this process. In the remodeling heart, cardiac fibroblasts (CFs) differentiate into myofibroblasts (MyoFB), which are the key mediators of the fibrotic response. Additionally, cardiomyocytes are involved by providing pro-fibrotic cues. Nuclear receptor Nur77 is known to reduce cardiac hypertrophy and associated fibrosis; however, the exact function of Nur77 in the fibrotic response is yet unknown. Here, we show that Nur77-deficient mice exhibit severe myocardial wall thinning, rupture and reduced collagen fiber density after myocardial infarction and chronic isoproterenol (ISO) infusion. Upon Nur77 knockdown in cultured rat CFs, expression of MyoFB markers and extracellular matrix proteins is reduced after stimulation with ISO or transforming growth factor–β (TGF-β). Accordingly, Nur77-depleted CFs produce less collagen and exhibit diminished proliferation and wound closure capacity. Interestingly, Nur77 knockdown in neonatal rat cardiomyocytes results in increased paracrine induction of MyoFB differentiation, which was blocked by TGF-β receptor antagonism. Taken together, Nur77-mediated regulation involves CF-intrinsic promotion of CF-to-MyoFB transition and inhibition of cardiomyocyte-driven paracrine TGF-β-mediated MyoFB differentiation. As such, Nur77 provides distinct, cell-specific regulation of cardiac fibrosis.     

Transcriptomic Profiles of CD47 in Breast Tumors Predict Outcome and Are Associated with Immune Activation

Targeting the innate immune system has attracted attention with the development of anti- CD47 antibodies. Anti-CD47 antibodies block the inhibition of the phagocytic activity of macrophages caused by the up-regulation of CD47 on tumor cells. In this study, public genomic data was used to identify genes highly expressed in breast tumors with elevated CD47 expression and analyzed the association between the presence of tumor immune infiltrates and the expression of the selected genes. We found that 142 genes positively correlated with CD47, of which 83 predicted favorable and 32 detrimental relapse-free survival (RFS). From those associated with favorable RFS, we selected the genes with immunologic biological functions and defined a CD47-immune signature composed of PTPRC, HLA-E, TGFBR2, PTGER4, ETS1, and OPTN. In the basal-like and HER2+ breast cancer subtypes, the expression of the CD47-immune signature predicted favorable outcome, correlated with the presence of tumor immune infiltrates, and with gene expression signatures of T cell activation. Moreover, CD47 up-regulated genes associated with favorable survival correlated with pro-tumoral macrophages. In summary, we described a CD47-immune gene signature composed of 6 genes associated with favorable prognosis, T cell activation, and pro-tumoral macrophages in breast cancer tumors expressing high levels of CD47.     

Immune Checkpoint Inhibitors: A Promising Treatment Option for Metastatic Castration-Resistant Prostate Cancer?

Since 2010, several treatment options have been available for men with metastatic castration-resistant prostate cancer (mCRPC), including immunotherapeutic agents, although the clinical benefit of these agents remains inconclusive in unselected mCRPC patients. In recent years, however, immunotherapy has re-emerged as a promising therapeutic option to stimulate antitumor immunity, particularly with the use of immune checkpoint inhibitors (ICIs), such as PD-1/PD-L1 and CTLA-4 inhibitors. There is increasing evidence that ICIs may be especially beneficial in specific subgroups of patients with high PD-L1 tumor expression, high tumor mutational burden, or tumors with high microsatellite instability/mismatch repair deficiency. If we are to improve the efficacy of ICIs, it is crucial to have a better understanding of the mechanisms of resistance to ICIs and to identify predictive biomarkers to determine which patients are most likely to benefit. This review focuses on the current status of ICIs for the treatment of mCRPC (either as monotherapy or in combination with other drugs), mechanisms of resistance, potential predictive biomarkers, and future challenges in the management of mCRPC.