Fluorescent dye encapsulated ZnO particles with cell-specific toxicity for potential use in biomedical applications

Fluorescein isothiocyanate (FITC)-encapsulated SiO₂ core-shell particles with a nanoscale ZnO finishing layer have been synthesized for the first time as multifunctional “smart” nanostructures. Detailed characterization studies confirmed the formation of an outer ZnO layer on the SiO₂–FITC core. These ~200 nm sized particles showed promise toward cell imaging and cellular uptake studies using the bacterium Escherichia coli and Jurkat cancer cells, respectively. The FITC encapsulated ZnO particles demonstrated excellent selectivity in preferentially killing Jurkat cancer cells with minimal toxicity to normal primary immune cells (18% and 75% viability remaining, respectively, after exposure to 60 μg/ml) and inhibited the growth of both gram-positive and gram-negative bacteria at concentrations ≥250–500 μg/ml (for Staphylococcus aureus and Escherichia coli, respectively). These results indicate that the novel FITC encapsulated multifunctional particles with nanoscale ZnO surface layer can be used as smart nanostructures for particle tracking, cell imaging, antibacterial treatments and cancer therapy.     

Comparison of modified injection molding and conventional machining in biodegradable behavior of perforated cannulated magnesium hip stents

In this study,perforated cannulated magnesium(Mg)hip stents were fabricated via modified Mg injection molding and conventional machining,respectively.Additionally,the stent canal was filled with paraffin to simulate injection of biomaterials.The microstructure,mechanical performance,corrosion behavior,and biocompatibility were comparably studied.Scanning electron microscopy(SEM)and energy dispersive spectroscopy(EDS)showed higher affinity of interstitial element such as oxygen and carbon as consequences of routine molding process.After immersion in SBF,machining stents showed reduced degradation rate and increased deposition of calcium phosphate compared to molding stents.Corrosion resistance was improved via paraffin-filling.Consistently,the hemolysis and in vitro osteoblast cell culture models showed favourable biocompatibility in machining stents compared to molding ones,which was improved by paraffin-filling treatment as well.These results implied that the feasibility of the prepared machining stents as the potential in vivo orthopaedic application where slower degradation is required,which could be enhanced by designing canal-filling injection of biomaterials as well.     

REDFLAG: A Run-timE, Distributed, Flexible, Lightweight, And Generic fault detection service for data-driven wireless sensor applications

Increased interest in wireless sensor networks by scientists and engineers is forcing wireless sensor networking research to focus on application requirements. Data is available as never before in many fields of study; practitioners are now burdened with the challenge of doing data-rich research rather than being data-starved. However, in situ sensors can be prone to errors, links between nodes are often unreliable, and nodes may become unresponsive in harsh environments, leaving to researchers the onerous task of deciphering often anomalous data. Presented here is the REDFLAG fault detection service for wireless sensor applications, a Run-timE, Distributed, Flexible, detector of faults, that is also Lightweight And Generic. REDFLAG addresses the two most worrisome issues in data-driven wireless sensor applications: abnormal data and missing data. REDFLAG exposes faults as they occur by using distributed algorithms in order to conserve energy. Simulation results show that REDFLAG is lightweight both in terms of footprint and required power resources while ensuring satisfactory detection and diagnosis accuracy. Being unrestrictive, REDFLAG is generically available to a myriad of applications and scenarios. As a matter of fact, REDFLAG has been applied into a subsurface contaminant transport model to improve the model performance in the presence of erroneous sensor data.     

EDA: an enhanced dual-active algorithm for location privacy preservation inmobile P2P networks

Various solutions have been proposed to enable mobile users to access location-based services while preserving their location privacy. Some of these solutions are based on a centralized architecture with the participation of a trustworthy third party, whereas some other approaches are based on a mobile peer-to-peer (P2P) architecture. The former approaches suffer from the scalability problem when networks grow large, while the latter have to endure either low anonymization success rates or high communication overheads. To address these issues, this paper deals with an enhanced dual-active spatial cloaking algorithm (EDA) for preserving location privacy in mobile P2P networks. The proposed EDA allows mobile users to collect and actively disseminate their location information to other users. Moreover, to deal with the challenging characteristics of mobile P2P networks, e.g., constrained network resources and user mobility, EDA enables users (1) to perform a negotiation process to minimize the number of duplicate locations to be shared so as to significantly reduce the communication overhead among users, (2) to predict user locations based on the latest available information so as to eliminate the inaccuracy problem introduced by using some out-of-date locations, and (3) to use a latest-record-highest-priority (LRHP) strategy to reduce the probability of broadcasting fewer useful locations. Extensive simulations are conducted for a range of P2P network scenarios to evaluate the performance of EDA in comparison with the existing solutions. Experimental results demonstrate that the proposed EDA can improve the performance in terms of anonymity and service time with minimized communication overhead.     

Ultrasound image analysis technology under deep belief networks in evaluation on the effects of diagnosis and chemotherapy of cervical cancer

The purpose of this study was to explore the value of extraction of tumor features in contrast-enhanced ultrasonography (CEUS) images based on the deep belief networks (DBN) for the diagnosis of cervical cancer patients and realize the intelligent evaluation on effects of diagnosis and chemotherapy of the cervical cancer. An automatic extraction algorithm with the time-intensity curve (TIC) was proposed based on Sparse nonnegative matrix factorization (SNMF) in this study, and was applied to the framework of automatic analysis of cervical cancer tumors based on the deep belief networks, to assist doctors in the analysis of cervical cancer tumors. The framework was applied to the real clinical diagnostic data, and the feasibility of the method was verified by comparing the accuracy, sensitivity, and specificity. Later, the parameters of patients’ time to peak (TP), peak intensity (PI), mean transit time (MTT), and area under the curve (AUC) were obtained by drawing TICs, and the changes of p53 protein and ki-67 protein obtained by pathological section staining were analyzed to evaluate the therapeutic effect in the patients. It was found that the proposed model of tumor feature extraction based on the DBN had the higher accuracy (86.36%), sensitivity (83.33%), and specificity (87.50%). The related parameters of TIC curve obtained based on SNMF showed that there was a significant difference in p53 content between tissues with different degrees of disease (p?<?0.05), the PI of poorly differentiated tissues was significantly higher than that of those with high to medium differentiation (p?<?0.05). In addition, PI and AUC of patients after chemotherapy were significantly lower than that before chemotherapy (p?<?0.05), while MTT was significantly higher than that before chemotherapy (p?<?0.05). Therefore, the proposed TIC feature extraction of CEUS images based on SNMF and the automatic tumor classification based on deep learning can be used in the diagnosis and efficacy evaluation of cervical cancer patients.

     

Cation deficiency associated with the chemical exfoliation of lithium cobalt oxide

Compositional changes associated with the chemical exfoliation of lithium cobalt oxide, a layered transition metal oxide, are discussed. Starting from a layered bulk structure, lithium cobalt oxide can undergo chemical exfoliation through a two-step method: treatment with a protic acid, then treatment with tetramethylammonium hydroxide (this intercalates the layered structure and yields exfoliated nanosheets). This work provides an in-depth analysis of compositional and structural changes occurring to the powder upon the first step to exfoliation, treatment with acid, revealing variations in vacancies and valence changes depending on the conditions used. Through coupled analysis of X-ray photoelectron spectroscopy, X-ray diffraction, UV-Vis absorption spectroscopy, and inductively coupled plasma-optical emission spectroscopy data, we illustrate that both lithium and cobalt ions are diffusing out the structure along with the dissolution of full unit cells. As such, nanosheets accessed from the bulk by this exfoliation process should not be considered simply as divisions of the original unit cell. This work provides fundamental insights on the stability of LiCoO₂ and the exfoliation of layered transition metal oxides, beyond the access of individual nanosheets, and is vital to determining structure-property relationships of chemically exfoliated nanosheets (eg, changes in valency which dictate catalytic activity, magnetic susceptibility, etc).     

Bioactive Alkaloids from Plants Poisonous to Livestock in North America

Plants produce a multiplicity of chemical compounds which have a variety of uses including flavors, fragrances, insecticides, dyes, poisons, and pharmaceutical agents. In this review, we focus on plant alkaloids from the genera Delphinium, Lupinus, Conium, Nicotiana, Veratrum, and selected plant endophyte derived alkaloids. Alkaloids discussed include norditerpenoid alkaloids which act as antagonists to block the ligand binding sites of nicotinic acetylcholine receptors and cause acute toxicosis in adult animals which can result in death. The inhibition of fetal movement and resulting fetal defects caused by quinolizidine and piperidine alkaloids, the inhibition of the hedgehog (Hh) signaling pathway by Veratrum alkaloids, and compounds derived from fungal endophytes that form symbioses with plant hosts will be also be discussed. The bioactivity of these alkaloids makes them useful tools for research and in human and veterinary medicine or potentially harmful toxins.     

Remote sensing for detection and monitoring of vegetation affected by oil spills

This study is aimed at demonstrating the application of vegetation spectral techniques for detection and monitoring of the impact of oil spills on vegetation. Vegetation spectral reflectance from Landsat 8 data were used in the calculation of five vegetation indices (normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), adjusted resistant vegetation index 2 (ARVI2), green-infrared index (G-NIR) and green-shortwave infrared (G-SWIR) from the spill sites (SS) and non-spill sites (NSS) in 2013 (pre-oil spill), 2014 (oil spill date) and 2015 (post-oil spill) for statistical comparison. The result shows that NDVI, SAVI, ARVI2, G-NIR and G-SWIR indicated a certain level of significant difference between vegetation condition at the SS and the NSS in December 2013. In December 2014 vegetation conditions indicated higher level of significant difference between the vegetation at the SS and NSS as follows where NDVI, SAVI and ARVI2 with p-value 0.005, G-NIR – p-value 0.01 and G-SWIR p-value 0.05. Similarly, in January 2015 a very significant difference with p-value <0.005. Three indices NDVI, ARVI2 and G-NIR indicated highly significant difference in vegetation conditions with p-value <0.005 between December 2013 and December 2014 at the same sites. Post-spill analysis shows that NDVI and ARVI2 indicated low level of significance difference p-value <0.05 suggesting subtle change in vegetation conditions between December 2014 and January 2015. This technique may help with the real time detection, response and monitoring of oil spills from pipelines for mitigation of pollution at the affected sites in mangrove forests.