Osteosarcoma Pathogenesis Leads the Way to New Target Treatments

Osteosarcoma (OS) is a rare condition with very poor prognosis in a metastatic setting. Basic research has enabled a better understanding of OS pathogenesis and the discovery of new potential therapeutic targets. Phase I and II clinical trials are already ongoing, with some promising results for these patients. This article reviews OS pathogenesis and new potential therapeutic targets.     

Increasing the photocatalytic and fungicide activities of Ag3PO4 microcrystals under visible-light irradiation

The present study reports for the first time the performance of silver phosphate (Ag₃PO₄) microcrystals as photocatalyst (degradation of Rodamine B-RhB) and antifungal agent (against Candida albicans–C. albicans) under visible-light irradiation (455 nm). Ag₃PO₄ microcrystals were synthesized by a simple co-precipitation (CP) method at room temperature. The structural and electronic properties of the as-synthetized Ag₃PO₄ have been investigated before and after 4 cycles of RhB degradation under visible light using X-ray diffraction (XRD), micro-Raman spectroscopy, UV–Vis spectrophotometer and field emission scanning electron microscopy (FE-SEM) images. The antifungal activity was analyzed in planktonic cells and 48h-biofilm of C. albicans by colony forming units (CFU) counting, confocal laser and FE-SE microscopies. Statistical analysis was carried out using SPSS software. Morphological and structural modifications of Ag₃PO₄ were observed upon recycling. After 4 recycles, the material maintained its photodegradation property; an eightfold increase in the efficiency of Ag₃PO₄ was observed in planktonic cells and a two fold increase in biofilm when irradiated under visible light. Thus, higher antifungal effectiveness against C. albicans was obtained when associated with visible-light irradiation.     

AKT Inhibitors: The Road Ahead to Computational Modeling-Guided Discovery

AKT, is a serine/threonine protein kinase comprising three isoforms—namely: AKT1, AKT2 and AKT3, whose inhibitors have been recognized as promising therapeutic targets for various human disorders, especially cancer. In this work, we report a systematic evaluation of multi-target Quantitative Structure-Activity Relationship (mt-QSAR) models to probe AKT’ inhibitory activity, based on different feature selection algorithms and machine learning tools. The best predictive linear and non-linear mt-QSAR models were found by the genetic algorithm-based linear discriminant analysis (GA-LDA) and gradient boosting (Xgboost) techniques, respectively, using a dataset containing 5523 inhibitors of the AKT isoforms assayed under various experimental conditions. The linear model highlighted the key structural attributes responsible for higher inhibitory activity whereas the non-linear model displayed an overall accuracy higher than 90%. Both these predictive models, generated through internal and external validation methods, were then used for screening the Asinex kinase inhibitor library to identify the most potential virtual hits as pan-AKT inhibitors. The virtual hits identified were then filtered by stepwise analyses based on reverse pharmacophore-mapping based prediction. Finally, results of molecular dynamics simulations were used to estimate the theoretical binding affinity of the selected virtual hits towards the three isoforms of enzyme AKT. Our computational findings thus provide important guidelines to facilitate the discovery of novel AKT inhibitors.     

Improving process models by mining mappings of low-level events to high-level activities

While it is possible to analyze the run-time behavior of a business process through process mining techniques, in practice there is often a gap between the low-level nature of the events recorded in an event log and the high-level of abstraction at which the process is modeled. This makes it difficult to understand the recorded behavior in terms of the high-level activities in the process model. Also, it makes it difficult to improve the model based on run-time data about the process. In this work we present an approach to mine mappings between the events in the log and the activities in the model. These mappings can be used to generate suggestions of how the process model can be extended in order to capture the behavior recorded in the event log. Using a real-world and publicly available event log, we show how the approach can improve the model in a stepwise manner, until it covers all the behavior recorded in the event log.     

Addressing universal access in social networks: an inclusive search mechanism

Social network services (SNSs) have brought new possibilities and challenges to the design of software environments that respect people’s cultural differences. These systems may represent an opportunity for social and digital inclusion. However, search mechanisms in these systems impose serious barriers for people in the process of acquiring digital literacy. One of the barriers is the difficulty of using the adequate terms/keywords to perform content searches. This paper presents an approach to allow ordinary, non-technology proficient people to access the content of a network through the use of search parameters that make sense to them. The proposal is grounded on Semantic Web technologies (Web ontology) combined with Organizational Semiotics concepts and methods to identify the users’ profile and language. A case study was conducted with the search mechanism integrated into a SNS, and a preliminary evaluation reveals the advantages and drawbacks of the approach.     

Sintering-driven effects on the band gap of (Pb,La)(Ti,Ni)O3 photovoltaic ceramics

In this work, the influence of the sintering temperature on the physical properties of (Pb_0.8La_0.2)(Ti_0.9Ni_0.1)O₃ (PLT-Ni) ceramics is reported. The experimental data revealed that the energy band gap of PLT-Ni ceramics could be tailored from approximately 2.7 to 2.0 eV by changing the sintering temperature from 1100°C to 1250°C. It is demonstrated that the simple substitution of Ti⁴⁺ by Ni²⁺ cations is effective to decrease the intrinsic band gap while increasing the tetragonality factor and the spontaneous polarization. However, the additional red-shift observed in the absorption edge of the PLT-Ni with increasing the sintering temperature was associated with a continuous increase in the oxygen vacancies () amount. It is believed that the impact of the creation of these thermally induced is manifold. The presence of and Ni²⁺ ions generate the Ni²⁺- defect-pairs that promoted both a decrease in the intrinsic band gap and an additional increase of the tetragonality factor, consequently, increasing the spontaneous polarization. The creation of Ni²⁺- defects also changed the local symmetry of Ni²⁺ ions from octahedral to a square pyramid, thus lifting the degeneracy of the Ni²⁺ 3d orbitals. With the increase in the sintering temperature, lower-energy absorbing intraband states were also formed due to an excess of , being responsible for an add-on shoulder in the absorption edge, extending the light absorption curve to longer wavelengths and leading to an additional absorption in “all investigated” spectrum as well.     

Thermotropic polyester: the influence of the spacer on the physical properties

Thermotropic polyesters prepared from series of 4,4-dihydroxy-,w-diphenoxy alkanes and 4,4-dichloroformyl-,w-diphenoxy alkanes are well known. The substitution of a methylenic spacer by an oxyethylenic spacer in the main chain of these polyesters drastically modifies their physical properties, particularly the mesogenic transition temperatures, as can be observed by DSC and thermooptical analysis. The thermal stability and the polymer solubility in common organic solvents of these polymers did not show a significant change. The physical properties of the two thermotropic polyesters prepared in diphenyl ether were evaluated.