bluuebunny/crossref_metadata_2025 huggingface dataset:
Association of Wnt Inhibitors, Bone Mineral Density and Lifestyle Parameters in Women with Breast Cancer Treated with Anastrozole Therapy
Authors: Bojanić Kristina , Bilić Ćurčić Ines , Kuna Lucija , Kizivat Tomislav , Smolic Robert , Raguž Lučić Nikola , Kralik Kristina , Šerić Vatroslav , Ivanac Gordana , Tucak-Zorić Sandra , Včev Aleksandar , Smolić Martina
Published: September 2018

Aim: To determine the levels of Wnt inhibitors in patients treated with aromatase inhibitors (AIs) prior to therapy and to investigate their association with bone mineral density (BMD) and lifestyle parameters. Methods: 137 breast cancer patients were divided into a group treated with 1 mg of anastrozole and a group w/o anastrozole therapy. Serum concentrations of sclerostin and dickkopf1 (DKK1) were measured by ELISA. BMD was measured by dual-energy X-ray absorptiometry (DXA). Lifestyle factors were investigated by a self-reported questionnaire. Results: Sclerostin was significantly higher in the AI-treated group (31.8 pmol/L vs. 24.1 pmol/L; p < 0.001), whereas DKK1 was significantly lower in the AI-treated group (24.3 pmol/L vs. 26.02 pmol/L; p < 0.001). Total hip and femoral neck BMD were significantly lower in the AI-treated group. Conclusion: AI treatment was associated with increased levels of sclerostin and decreased levels of DKK1.
Thermoelectric Nanocomposite Foams Using Non-Conducting Polymers with Hybrid 1D and 2D Nanofillers
Authors: Aghelinejad Mohammadmehdi , Leung Siu Ning
Published: September 2018

A facile processing strategy to fabricate thermoelectric (TE) polymer nanocomposite foams with non-conducting polymers is reported in this study. Multilayered networks of graphene nanoplatelets (GnPs) and multi-walled carbon nanotubes (MWCNTs) are deposited on macroporous polyvinylidene fluoride (PVDF) foam templates using a layer-by-layer (LBL) assembly technique. The open cellular structures of foam templates provide a platform to form segregated 3D networks consisting of one-dimensional (1D) and/or two-dimensional (2D) carbon nanoparticles. Hybrid nanostructures of GnP and MWCNT networks synergistically enhance the material system’s electrical conductivity. Furthermore, the polymer foam substrates possess high porosity to provide ultra-low thermal conductivity without compromising the electrical conductivity of the TE nanocomposites. With an extremely low GnP loading (i.e., ~1.5 vol.%), the macroporous PVDF nanocomposites exhibit a thermoelectric figure-of-merit of ~10−3. To the best of our knowledge, this ZT value is the highest value reported for organic TE materials using non-conducting polymers and MWCNT/GnP nanofillers. The proposed technique represents an industrially viable approach to fabricate organic TE materials with enhanced energy conversion efficiencies. The current study demonstrates the potential to develop light-weight, low-cost, and flexible TE materials for green energy generation.
Perovskite Thin Film Consisting with One-Dimensional Nanowires
Authors: Li Xinli , Chen Yongchao , Li Lihua , Huang Jinliang
Published: September 2018

Organic-inorganic hybrid perovskite solar cells had attracted extensive attention due to their high-power conversion efficiency and low cost. The morphology and structure of the light absorption layer are crucially important for the device performance. The one-dimensional or two dimensional nano-structure perovskite material exhibits better optical and electrical properties than three-dimensional bulk perovskite. In this article, the perovskite CH3NH3PbI3 thin films with one-dimensional nanowires structure were prepared while using the solution method with N,N-Dimethylformamide (DMF) and dimethyl sulfoxide (DMSO) mixed solvent under atmospheric environment. During the perovskite thin films growth, the DMSO solvent as a structure directing agent played a guiding role in the formation of nanowires. The effects of DMSO solvent added ratio on the perovskite thin film structure, morphology, optical properties, and the device performance were studied. By changing the ratio of DMSO solvent added can effectively adjust the orientation order and optical properties of the nanowires perovskite thin films. The results showed that the best ratio of DMSO solvent added in the mixed solvent was 10%. The high order orientation of the perovskite thin film with nanowires forest was obtained. It showed the high optical absorption and electrical properties. The perovskite absorption layer presents ordered and dispersed nanowires forest; the device power conversation efficiency is increased by 50% when compared with the perovskite layer presents disordered nanowires.
Graphene-Based Light Sensing: Fabrication, Characterisation, Physical Properties and Performance
Authors: De Sanctis Adolfo , Mehew Jake D. , Craciun Monica F. , Russo Saverio
Published: September 2018

Graphene and graphene-based materials exhibit exceptional optical and electrical properties with great promise for novel applications in light detection. However, several challenges prevent the full exploitation of these properties in commercial devices. Such challenges include the limited linear dynamic range (LDR) of graphene-based photodetectors, the lack of efficient generation and extraction of photoexcited charges, the smearing of photoactive junctions due to hot-carriers effects, large-scale fabrication and ultimately the environmental stability of the constituent materials. In order to overcome the aforementioned limits, different approaches to tune the properties of graphene have been explored. A new class of graphene-based devices has emerged where chemical functionalisation, hybridisation with light-sensitising materials and the formation of heterostructures with other 2D materials have led to improved performance, stability or versatility. For example, intercalation of graphene with FeCl 3 is highly stable in ambient conditions and can be used to define photo-active junctions characterized by an unprecedented LDR while graphene oxide (GO) is a very scalable and versatile material which supports the photodetection from UV to THz frequencies. Nanoparticles and quantum dots have been used to enhance the absorption of pristine graphene and to enable high gain thanks to the photogating effect. In the same way, hybrid detectors made from stacked sequences of graphene and layered transition-metal dichalcogenides enabled a class of devices with high gain and responsivity. In this work, we will review the performance and advances in functionalised graphene and hybrid photodetectors, with particular focus on the physical mechanisms governing the photoresponse, the performance and possible future paths of investigation.
A (p,q)-Averaged Hausdorff Distance for Arbitrary Measurable Sets
Authors: Bogoya Johan M. , Vargas Andrés , Cuate Oliver , Schütze Oliver
Published: September 2018

The Hausdorff distance is a widely used tool to measure the distance between different sets. For the approximation of certain objects via stochastic search algorithms this distance is, however, of limited use as it punishes single outliers. As a remedy in the context of evolutionary multi-objective optimization (EMO), the averaged Hausdorff distance Δ p has been proposed that is better suited as an indicator for the performance assessment of EMO algorithms since such methods tend to generate outliers. Later on, the two-parameter indicator Δ p , q has been proposed for finite sets as an extension to Δ p which also averages distances, but which yields some desired metric properties. In this paper, we extend Δ p , q to a continuous function between general bounded subsets of finite measure inside a metric measure space. In particular, this extension applies to bounded subsets of R k endowed with the Euclidean metric, which is the natural context for EMO applications. We show that our extension preserves the nice metric properties of the finite case, and finally provide some useful numerical examples that arise in EMO.
Bioactive Compounds from Marine Organisms: Potential for Bone Growth and Healing
Authors: Carson Matthew A. , Clarke Susan A.
Published: September 2018

Marine organisms represent a highly diverse reserve of bioactives which could aid in the treatment of a wide range of diseases, including various musculoskeletal conditions. Osteoporosis in particular would benefit from a novel and effective marine-based treatment, due to its large disease burden and the inefficiencies of current treatment options. Osteogenic bioactives have been isolated from many marine organisms, including nacre powder derived from molluscan shells and fucoidan—the sulphated polysaccharide commonly sourced from brown macroalgae. Such extracts and compounds are known to have a range of osteogenic effects, including stimulation of osteoblast activity and mineralisation, as well as suppression of osteoclast resorption. This review describes currently known soluble osteogenic extracts and compounds from marine invertebrates and algae, and assesses their preclinical potential.
Direct Transamidation Reactions: Mechanism and Recent Advances
Authors: Acosta-Guzmán Paola , Mateus-Gómez Alejandra , Gamba-Sánchez Diego
Published: September 2018

Amides are undeniably some of the most important compounds in Nature and the chemical industry, being present in biomolecules, materials, pharmaceuticals and many other substances. Unfortunately, the traditional synthesis of amides suffers from some important drawbacks, principally the use of stoichiometric activators or the need to use highly reactive carboxylic acid derivatives. In recent years, the transamidation reaction has emerged as a valuable alternative to prepare amides. The reactivity of amides makes their direct reaction with nitrogen nucleophiles difficult; thus, the direct transamidation reaction needs a catalyst in order to activate the amide moiety and to promote the completion of the reaction because equilibrium is established. In this review, we present research on direct transamidation reactions ranging from studies of the mechanism to the recent developments of more applicable and versatile methodologies, emphasizing those reactions involving activation with metal catalysts.
Deep Learning in Drug Discovery and Medicine; Scratching the Surface
Authors: Dana Dibyendu , Gadhiya Satishkumar , St. Surin Luce , Li David , Naaz Farha , Ali Quaisar , Paka Latha , Yamin Michael , Narayan Mahesh , Goldberg Itzhak , Narayan Prakash
Published: September 2018

The practice of medicine is ever evolving. Diagnosing disease, which is often the first step in a cure, has seen a sea change from the discerning hands of the neighborhood physician to the use of sophisticated machines to use of information gleaned from biomarkers obtained by the most minimally invasive of means. The last 100 or so years have borne witness to the enormous success story of allopathy, a practice that found favor over earlier practices of medical purgatory and homeopathy. Nevertheless, failures of this approach coupled with the omics and bioinformatics revolution spurred precision medicine, a platform wherein the molecular profile of an individual patient drives the selection of therapy. Indeed, precision medicine-based therapies that first found their place in oncology are rapidly finding uses in autoimmune, renal and other diseases. More recently a new renaissance that is shaping everyday life is making its way into healthcare. Drug discovery and medicine that started with Ayurveda in India are now benefiting from an altogether different artificial intelligence (AI)—one which is automating the invention of new chemical entities and the mining of large databases in health-privacy-protected vaults. Indeed, disciplines as diverse as language, neurophysiology, chemistry, toxicology, biostatistics, medicine and computing have come together to harness algorithms based on transfer learning and recurrent neural networks to design novel drug candidates, a priori inform on their safety, metabolism and clearance, and engineer their delivery but only on demand, all the while cataloging and comparing omics signatures across traditionally classified diseases to enable basket treatment strategies. This review highlights inroads made and being made in directed-drug design and molecular therapy.
A Comprehensive In Silico Method to Study the QSTR of the Aconitine Alkaloids for Designing Novel Drugs
Authors: Wang Ming-Yang , Liang Jing-Wei , Olounfeh Kamara Mohamed , Sun Qi , Zhao Nan , Meng Fan-Hao
Published: September 2018

A combined in silico method was developed to predict potential protein targets that are involved in cardiotoxicity induced by aconitine alkaloids and to study the quantitative structure–toxicity relationship (QSTR) of these compounds. For the prediction research, a Protein-Protein Interaction (PPI) network was built from the extraction of useful information about protein interactions connected with aconitine cardiotoxicity, based on nearly a decade of literature and the STRING database. The software Cytoscape and the PharmMapper server were utilized to screen for essential proteins in the constructed network. The Calcium-Calmodulin-Dependent Protein Kinase II alpha (CAMK2A) and gamma (CAMK2G) were identified as potential targets. To obtain a deeper insight on the relationship between the toxicity and the structure of aconitine alkaloids, the present study utilized QSAR models built in Sybyl software that possess internal robustness and external high predictions. The molecular dynamics simulation carried out here have demonstrated that aconitine alkaloids possess binding stability for the receptor CAMK2G. In conclusion, this comprehensive method will serve as a tool for following a structural modification of the aconitine alkaloids and lead to a better insight into the cardiotoxicity induced by the compounds that have similar structures to its derivatives.
Phenolic Compounds in Organic and Aqueous Extracts from Acacia farnesiana Pods Analyzed by ULPS-ESI-Q-oa/TOF-MS. In Vitro Antioxidant Activity and Anti-Inflammatory Response in CD-1 Mice
Authors: Claudia Delgadillo , Mario Cuchillo-Hilario , Arturo Navarro , Omar Noel Medina-Campos , Antonio Nieto , Teresa Ramírez , Zenón Gerardo López-Tecpoyotl , Margarita Díaz , Marsela Alejandra Álvarez-Izazaga , Yessica Rosalina Cruz , Vanessa Sánchez-Quezada , Francisco Enrique Gómez , Torre-Villalvazo Iván , Janette Furuzawa , María del Rayo Camacho-Corona , José Pedraza-Chaverri
Published: September 2018

Background: Acacia farnesiana (AF) pods have been traditionally used to treat dyspepsia, diarrhea and topically for dermal inflammation. Main objectives: (1) investigate the antioxidant activity and protection against oxidative-induced damage of six extracts from AF pods and (2) their capacity to curb the inflammation process as well as to down-regulate the pro-inflammatory mediators. Methods: Five organic extracts (chloroformic, hexanic, ketonic, methanolic, methanolic:aqueous and one aqueous extract) were obtained and analyzed by UPLC-ESI-Q-oa/TOF-MS. Antioxidant activity (DPPH•, ORAC and FRAP assays) and lipid peroxidation (TBARS assay) were performed. Assessment of anti-inflammatory properties was made by the ear edema induced model in CD-1 mice and MPO activity assay. Likewise, histological analysis, IL-1β, IL-6, IL-10, TNF-α, COX measurements plus nitrite and immunohistochemistry analysis were carried out. Results: Methyl gallate, gallic acid, galloyl glucose isomer 1, galloyl glucose isomer 2, galloyl glucose isomer 3, digalloyl glucose isomer 1, digalloyl glucose isomer 2, digalloyl glucose isomer 3, digalloyl glucose isomer 4, hydroxytyrosol acetate, quinic acid, and caffeoylmalic acid were identified. Both organic and aqueous extracts displayed antioxidant activity. All extracts exhibited a positive effect on the interleukins, COX and immunohistochemistry assays. Conclusion: All AF pod extracts can be effective as antioxidant and topical anti-inflammatory agents.
Innovative Extraction Techniques and Hyphenated Instrument Configuration for Complex Matrices Analysis
Authors: Locatelli Marcello , Carradori Simone , Mocan Andrei
Published: September 2018

n/a
Actinofuranones D-I from a Lichen-Associated Actinomycetes, Streptomyces gramineus, and Their Anti-Inflammatory Effects
Authors: Ma Jian , Cao Bixuan , Liu Chengbin , Guan Peipei , Mu Yu , Jiang Yi , Han Li , Huang Xueshi
Published: September 2018

Six new metabolites, actinofuranones D-I (compounds 1–6), were isolated together with three known compounds—JBIR-108 (7), E-975 (8), and E-492 (9)—from a fermentation broth of Streptomyces gramineus derived from the lichen Leptogium trichophorum. The structures of the new compounds 1–6 were established using comprehensive NMR spectroscopic data analysis, as well as UV, IR, and MS data. The anti-inflammatory activity of these isolated compounds were evaluated by examining their ability to inhibit nitric oxide (NO) production in LPS-stimulated RAW 264.7 macrophage cells. Compounds 4, 5, 8, and 9 attenuated the production of NO due to the suppression of the expression of nitric oxide synthase (iNOS) in LPS-induced RAW 264.7 cells. Moreover, 4, 5, 8, and 9 also inhibited LPS-induced release of proinflammatory cytokines interleukin-6 (IL-6) and tumor necrosis factor α (TNF-α).
A Mini Review Focused on the Recent Applications of Graphene Oxide in Stem Cell Growth and Differentiation
Authors: Halim Alexander , Luo Qing , Ju Yang , Song Guanbin
Published: September 2018

Stem cells are undifferentiated cells that can give rise to any types of cells in our body. Hence, they have been utilized for various applications, such as drug testing and disease modeling. However, for the successful of those applications, the survival and differentiation of stem cells into specialized lineages should be well controlled. Growth factors and chemical agents are the most common signals to promote the proliferation and differentiation of stem cells. However, those approaches holds several drawbacks such as the negative side effects, degradation or denaturation, and expensive. To address such limitations, nanomaterials have been recently used as a better approach for controlling stem cells behaviors. Graphene oxide is the derivative of graphene, the first two-dimensional (2D) materials in the world. Recently, due to its extraordinary properties and great biological effects on stem cells, many scientists around the world have utilized graphene oxide to enhance the differentiation potential of stem cells. In this mini review, we highlight the key advances about the effects of graphene oxide on controlling stem cell growth and various types of stem cell differentiation. We also discuss the possible molecular mechanisms of graphene oxide in controlling stem cell growth and differentiation.
Surface Properties of SnO2 Nanowires Deposited on Si Substrate Covered by Au Catalyst Studies by XPS, TDS and SEM
Authors: Kwoka Monika , Lyson-Sypien Barbara , Kulis Anna , Zappa Dario , Comini Elisabetta
Published: September 2018

The surface chemistry and the morphology of SnO2 nanowires of average length and diameter of several µm and around 100 nm, respectively, deposited by vapor phase deposition (VPD) method on Au-covered Si substrate, were studied before and after subsequent air exposure. For this purpose, surface-sensitive methods, including X-ray photoelectron spectroscopy (XPS), thermal desorption spectroscopy (TDS) and the scanning electron microscopy (SEM), were applied. The studies presented within this paper allowed to determine their surface non-stoichiometry combined with the presence of carbon contaminations, in a good correlation with their surface morphology. The relative concentrations of the main components [O]/[Sn]; [C]/[Sn]; [Au]/[Sn], together with the O–Sn; O–Si bonds, were analyzed. The results of TDS remained in a good agreement with the observations from XPS. Moreover, conclusions obtained for SnO2 nanowires deposited with the use of Au catalyst were compared to the previous obtained for Ag-assisted tin dioxide nanowires. The information obtained within these studies is of a great importance for the potential application of SnO2 nanowires in the field of novel chemical nanosensor devices, since the results can provide an interpretation of how aging effects influence gas sensor dynamic characteristics.
Extra Surfactant-Assisted Self-Assembly of Highly Ordered Monolayers of BaTiO3 Nanocubes at the Air–Water Interface
Authors: Itasaka Hiroki , Mimura Ken-Ichi , Kato Kazumi
Published: September 2018

Assembly of nanocrystals into ordered two- or three-dimensional arrays is an essential technology to achieve their application in novel functional devices. Among a variety of assembly techniques, evaporation-induced self-assembly (EISA) is one of the prospective approaches because of its simplicity. Although EISA has shown its potential to form highly ordered nanocrystal arrays, the formation of uniform nanocrystal arrays over large areas remains a challenging subject. Here, we introduce a new EISA method and demonstrate the formation of large-scale highly ordered monolayers of barium titanate (BaTiO3, BT) nanocubes at the air-water interface. In our method, the addition of an extra surfactant to a water surface assists the EISA of BT nanocubes with a size of 15–20 nm into a highly ordered arrangement. We reveal that the compression pressure exerted by the extra surfactant on BT nanocubes during the solvent evaporation is a key factor in the self-assembly in our method. The BT nanocube monolayers transferred to substrates have sizes up to the millimeter scale and a high out-of-plane crystal orientation, containing almost no microcracks and voids.
Magnetic Nanoparticles Applications for Amyloidosis Study and Detection: A Review
Authors: Pansieri Jonathan , Gerstenmayer Matthieu , Lux François , Mériaux Sebastien , Tillement Olivier , Forge Vincent , Larrat Benoit , Marquette Christel
Published: September 2018

Magnetic nanoparticles (MNPs) have great potential in biomedical and clinical applications because of their many unique properties. This contribution provides an overview of the MNPs mainly used in the field of amyloid diseases. The first part discusses their use in understanding the amyloid mechanisms of fibrillation, with emphasis on their ability to control aggregation of amyloidogenic proteins. The second part deals with the functionalization by various moieties of numerous MNPs’ surfaces (molecules, peptides, antibody fragments, or whole antibodies of MNPs) for the detection and the quantification of amyloid aggregates. The last part of this review focuses on the use of MNPs for magnetic-resonance-based amyloid imaging in biomedical fields, with particular attention to the application of gadolinium-based paramagnetic nanoparticles (AGuIX), which have been recently developed. Biocompatible AGuIX nanoparticles show favorable characteristics for in vivo use, such as nanometric and straightforward functionalization. Their properties have enabled their application in MRI. Here, we report that AGuIX nanoparticles grafted with the Pittsburgh compound B can actively target amyloid aggregates in the brain, beyond the blood–brain barrier, and remain the first step in observing amyloid plaques in a mouse model of Alzheimer’s disease.
Effects of Long-Term Walnut Supplementation on Body Weight in Free-Living Elderly: Results of a Randomized Controlled Trial
Authors: Bitok Edward , Rajaram Sujatha , Jaceldo-Siegl Karen , Oda Keiji , Sala-Vila Aleix , Serra-Mir Mercè , Ros Emilio , Sabaté Joan
Published: September 2018

Objective: To assess the effects of chronic walnut consumption on body weight and adiposity in elderly individuals. Methods: The Walnuts and Healthy Aging study is a dual-center (Barcelona, Spain and Loma Linda University (LLU)), 2-year randomized parallel trial. This report concerns only the LLU cohort. Healthy elders (mean age 69 year, 67% women) were randomly assigned to walnut (n = 183) or control diets (n = 173). Subjects in the walnut group received packaged walnuts (28–56 g/day), equivalent to ≈15% of daily energy requirements, to incorporate into their habitual diet, while those in the control group abstained from walnuts. Adiposity was measured periodically, and data were adjusted for in-trial changes in self-reported physical activity. Results: After 2 years, body weight significantly decreased (p = 0.031), while body fat significantly increased (p = 0.0001). However, no significant differences were observed between the control and walnut groups regarding body weight (−0.6 kg and −0.4 kg, respectively, p = 0.67) or body fat (+0.9% and +1.3%, respectively, p = 0.53). Lean body mass, waist circumference, and waist-to-hip ratio remained essentially unchanged. Sensitivity analyses were consistent with the findings of primary analysis. Conclusion: Our findings indicate that walnuts can be incorporated into the daily diet of healthy elders without concern for adverse effects on body weight or body composition.
Functional Calcium Binding Peptides from Pacific Cod (Gadus macrocephalus) Bone: Calcium Bioavailability Enhancing Activity and Anti-Osteoporosis Effects in the Ovariectomy-Induced Osteoporosis Rat Model
Authors: Zhang Kai , Li Bafang , Chen Qianru , Zhang Zhaohui , Zhao Xue , Hou Hu
Published: September 2018

Calcium binding peptides from Pacific cod (Gadus macrocephalus) bone have attracted attention due to their potential effects on bone health. In this study, calcium binding peptides (CBP) were prepared from Pacific cod bone by trypsin and neutral protease. Ultraviolet spectra, circular dichroism (CD), and Fourier transform infrared spectroscopy (FTIR) revealed that carboxyl and amino groups in CBP could bind to Ca2+, and form the peptide-calcium complex (CBP-Ca). Single-pass intestinal perfusion (SPIP) experiments indicated that the intestinal calcium absorption was significantly enhanced (p < 0.01) in CBP-Ca treated Wistar rats. The anti-osteoporosis activity of CBP-Ca was investigated in the ovariectomized (OVX) Wistar rat model. The administration of CBP-Ca significantly (p < 0.01) improved the calcium bioavailability, trabecular bone structure, bone biomechanical properties, bone mineral density, and bone mineralization degree. CBP-Ca notably (p < 0.01) increased serum calcium, however, it remarkably (p < 0.01) reduced the levels of osteocalcin (OCN), bone alkaline phosphatase (BALP), tartrate-resistant acid phosphatase isoform 5b (TRAP5b), and C-telopeptide of type I collagen (CTX-1) in serum. Results suggested that the cod bone derived CBP could bind with calcium, improve the intestinal calcium absorption, calcium bioavailability, and serum calcium, then reduce the bone turnover rate, and thus ameliorate osteoporosis.
Adverse Drug Reactions, Power, Harm Reduction, Regulation and the ADRe Profiles
Authors: Jordan Sue , Logan Patricia , Panes Gerwyn , Vaismoradi Mojtaba , Hughes David
Published: September 2018

The power and influence of healthcare systems comes largely from the ability to prescribe efficacious medicine. However, medicine can sometimes cause harm rather than bring benefits. Systematically checking patients for the adverse effects of medicines, as listed in manufacturers’ literature, would protect patients from iatrogenic harm, but this is rarely undertaken. We argue for the benefits of this approach using the example of the prescription of antipsychotics to older adults. Prescribing antipsychotics to control challenging behaviours associated with dementia is a controversial matter, and regulatory intervention is under discussion. Improved regulatory systems could protect against iatrogenic harm, such as over-sedation, falls, tremor, or drug-induced Parkinsonism. However, measuring the impact and outcomes of regulatory interventions has proved difficult, not least because there are rarely systematic records of all adverse effects of medicines. We indicate how regulatory initiatives to reduce antipsychotic prescribing can be supported by systematic monitoring and documentation of patients’ signs and symptoms of putative adverse drug reactions. Monitoring documentation then provides the rationale and support for professionals’ responses to identified problems. Longitudinal monitoring records would improve understanding of the impact and outcomes of adverse drug reactions (ADRs) on health and wellbeing, and the many costs of ADRs.
Bioinspired Engineering towards Tailoring Advanced Lignin/Rubber Elastomers
Authors: Wang Haixu , Liu Weifeng , Huang Jinhao , Yang Dongjie , Qiu Xueqing
Published: September 2018

The pursuit of high volume and high value-added applications for lignin has been a long-term challenge. In this work, inspired by the energy sacrificial mechanism from biological materials, we developed high-performance lignin/carbon black (CB)/nitrile rubber (NBR) elastomers by constructing a dual-crosslinking network consisting of sulfur covalent bonds and dynamic coordination sacrificial bonds. Lignin was not only used for the substitution of half mass of CB in the NBR elastomer but also served as natural ligands for the Zn-based coordination bonds, providing a significant synergistic coordination enhancement effect. The mechanical performance of the elastomers can be easily manipulated by adjusting the proportion of non-permanent coordination bonds and permanent covalent bonds. Lignin/CB/NBR elastomers with a higher strength and modulus than CB-filled elastomers were obtained while maintaining excellent elasticity. The thermal stability and the high-temperature oil resistance of NBR elastomers were also improved by incorporation of lignin and metal coordination bonds. Overall, this work inspires a new solution for the design of high-performance lignin/rubber elastomers with a high lignin loading content.
Sugar Functionalized Synergistic Dendrimers for Biocompatible Delivery of Nucleic Acid Therapeutics
Authors: Han Shuqin , Ganbold Tsogzolmaa , Bao Qingming , Yoshida Takashi , Baigude Huricha
Published: September 2018

Sugars containing cationic polymers are potential carriers for in vitro and in vivo nucleic acid delivery. Monosaccharides such as glucose and galactose have been chemically conjugated to various materials of synergistic poly-lysine dendrimer systems for efficient and biocompatible delivery of short interfering RNA (siRNA). The synergistic dendrimers, which contain lipid conjugated glucose terminalized lysine dendrimers, have significantly lower adverse impact on cells while maintaining efficient cellular entry. Moreover, the synergistic dendrimers complexed to siRNA induced RNA interference (RNAi) in the cells and profoundly knocked down green fluorescence protein (GFP) as well as the endogenously expressing disease related gene Plk1. The new synergic dendrimers may be promising system for biocompatible and efficient siRNA delivery.
Modeling Permeation through Mixed-Matrix Membranes: A Review
Authors: Monsalve-Bravo Gloria M. , Bhatia Suresh K.
Published: September 2018

Over the past three decades, mixed-matrix membranes (MMMs), comprising an inorganic filler phase embedded in a polymer matrix, have emerged as a promising alternative to overcome limitations of conventional polymer and inorganic membranes. However, while much effort has been devoted to MMMs in practice, their modeling is largely based on early theories for transport in composites. These theories consider uniform transport properties and driving force, and thus models for the permeability in MMMs often perform unsatisfactorily when compared to experimental permeation data. In this work, we review existing theories for permeation in MMMs and discuss their fundamental assumptions and limitations with the aim of providing future directions permitting new models to consider realistic MMM operating conditions. Furthermore, we compare predictions of popular permeation models against available experimental and simulation-based permeation data, and discuss the suitability of these models for predicting MMM permeability under typical operating conditions.
Fluctuation Theory for Upwards Skip-Free Lévy Chains
Authors: Vidmar Matija
Published: September 2018

A fluctuation theory and, in particular, a theory of scale functions is developed for upwards skip-free Lévy chains, i.e., for right-continuous random walks embedded into continuous time as compound Poisson processes. This is done by analogy to the spectrally negative class of Lévy processes—several results, however, can be made more explicit/exhaustive in the compound Poisson setting. Importantly, the scale functions admit a linear recursion, of constant order when the support of the jump measure is bounded, by means of which they can be calculated—some examples are presented. An application to the modeling of an insurance company’s aggregate capital process is briefly considered.
In-Flight Calibration and Performance of the OSIRIS-REx Visible and IR Spectrometer (OVIRS)
Authors: Simon Amy , Reuter Dennis , Gorius Nicolas , Lunsford Allen , Cosentino Richard , Wind Galina , Lauretta Dante ,   The OSIRIS-REx Team
Published: September 2018

Performance of the Origins, Spectral Interpretation, Resource Identification, Security–Regolith Explorer (OSIRIS-REx) Visible and InfraRed Spectrometer (OVIRS) instrument was validated, showing that it met all science requirements during extensive thermal vacuum ground testing. Preliminary instrument radiometric calibration coefficients and wavelength mapping were also determined before instrument delivery and launch using NIST-traceable sources. One year after launch, Earth flyby data were used to refine the wavelength map by comparing OVIRS spectra with atmospheric models. Near-simultaneous data from other Earth-orbiting satellites were used to cross-calibrate the OVIRS absolute radiometric response, particularly at visible wavelengths. Trending data from internal calibration sources and the Sun show that instrument radiometric performance has been stable to better than 1% in the 18 months since launch.
Deep Convolutional Neural Networks for Automated Characterization of Arctic Ice-Wedge Polygons in Very High Spatial Resolution Aerial Imagery
Authors: Zhang Weixing , Witharana Chandi , Liljedahl Anna K. , Kanevskiy Mikhail
Published: September 2018

The microtopography associated with ice-wedge polygons governs many aspects of Arctic ecosystem, permafrost, and hydrologic dynamics from local to regional scales owing to the linkages between microtopography and the flow and storage of water, vegetation succession, and permafrost dynamics. Wide-spread ice-wedge degradation is transforming low-centered polygons into high-centered polygons at an alarming rate. Accurate data on spatial distribution of ice-wedge polygons at a pan-Arctic scale are not yet available, despite the availability of sub-meter-scale remote sensing imagery. This is because the necessary spatial detail quickly produces data volumes that hamper both manual and semi-automated mapping approaches across large geographical extents. Accordingly, transforming big imagery into ‘science-ready’ insightful analytics demands novel image-to-assessment pipelines that are fueled by advanced machine learning techniques and high-performance computational resources. In this exploratory study, we tasked a deep-learning driven object instance segmentation method (i.e., the Mask R-CNN) with delineating and classifying ice-wedge polygons in very high spatial resolution aerial orthoimagery. We conducted a systematic experiment to gauge the performances and interoperability of the Mask R-CNN across spatial resolutions (0.15 m to 1 m) and image scene contents (a total of 134 km2) near Nuiqsut, Northern Alaska. The trained Mask R-CNN reported mean average precisions of 0.70 and 0.60 at thresholds of 0.50 and 0.75, respectively. Manual validations showed that approximately 95% of individual ice-wedge polygons were correctly delineated and classified, with an overall classification accuracy of 79%. Our findings show that the Mask R-CNN is a robust method to automatically identify ice-wedge polygons from fine-resolution optical imagery. Overall, this automated imagery-enabled intense mapping approach can provide a foundational framework that may propel future pan-Arctic studies of permafrost thaw, tundra landscape evolution, and the role of high latitudes in the global climate system.
Time-Varying SAR Interference Suppression Based on Delay-Doppler Iterative Decomposition Algorithm
Authors: Su Jia , Tao Haihong , Tao Mingliang , Xie Jian , Wang Yuexian , Wang Ling
Published: September 2018

Narrow-band interference (NBI) and Wide-band interference (WBI) are critical issues for synthetic aperture radar (SAR), which degrades the imaging quality severely. Since some complex signals can be modeled as linear frequency modulated (LFM) signals within a short time, LFM-WBI and NBI are mainly discussed in this paper. Due to its excellent energy concentration and useful properties (i.e., auto-terms pass through the origin of Delay-Doppler plane while cross-terms are away from it), a novel nonparametric interference suppression method using Delay-Doppler iterative decomposition algorithm is proposed. This algorithm consists of three stages. First, we present signal synthesis method (SSM) from ambiguity function (AF) and cross ambiguity function (CAF) based on the matrix rearrangement and eigenvalue decomposition. Compared with traditional SSM from Wigner distribution (WD), the proposed SSM can synthesize a signal faster and more accurately. Then, based on unique properties in Delay-Doppler domain, a mask algorithm is applied for interference identification and extraction using Radon and its inverse transformation. Finally, a signal iterative decomposition algorithm (IDA) is utilized to subtract the largest interference from the received signal one by one. After that, a well-focused SAR imagery is obtained by conventional imaging methods. The simulation and measured data results demonstrate that the proposed algorithm not only suppresses interference efficiently but also preserves the useful information as much as possible.
Potential of Cost-Efficient Single Frequency GNSS Receivers for Water Vapor Monitoring
Authors: Krietemeyer Andreas , Ten Veldhuis Marie-claire , Van der Marel Hans , Realini Eugenio , Van de Giesen Nick
Published: September 2018

Dual-frequency Global Navigation Satellite Systems (GNSSs) enable the estimation of Zenith Tropospheric Delay (ZTD) which can be converted to Precipitable Water Vapor (PWV). The density of existing GNSS monitoring networks is insufficient to capture small-scale water vapor variations that are especially important for extreme weather forecasting. A densification with geodetic-grade dual-frequency receivers is not economically feasible. Cost-efficient single-frequency receivers offer a possible alternative. This paper studies the feasibility of using low-cost receivers to increase the density of GNSS networks for retrieval of PWV. We processed one year of GNSS data from an IGS station and two co-located single-frequency stations. Additionally, in another experiment, the Radio Frequency (RF) signal from a geodetic-grade dual-frequency antenna was split to a geodetic receiver and two low-cost receivers. To process the single-frequency observations in Precise Point Positioning (PPP) mode, we apply the Satellite-specific Epoch-differenced Ionospheric Delay (SEID) model using two different reference network configurations of 50–80 km and 200–300 km mean station distances, respectively. Our research setup can distinguish between the antenna, ionospheric interpolation, and software-related impacts on the quality of PWV retrievals. The study shows that single-frequency GNSS receivers can achieve a quality similar to that of geodetic receivers in terms of RMSE for ZTD estimations. We demonstrate that modeling of the ionosphere and the antenna type are the main sources influencing the ZTD precision.
Tracking Fine-Scale Structural Changes in Coastal Dune Morphology Using Kite Aerial Photography and Uncertainty-Assessed Structure-from-Motion Photogrammetry
Authors: Duffy James P. , Shutler Jamie D. , Witt Matthew J. , DeBell Leon , Anderson Karen
Published: September 2018

Coastal dunes are globally-distributed dynamic ecosystems that occur at the land-sea interface. They are sensitive to disturbance both from natural forces and anthropogenic stressors, and therefore require regular monitoring to track changes in their form and function ultimately informing management decisions. Existing techniques employing satellite or airborne data lack the temporal or spatial resolution to resolve fine-scale changes in these environments, both temporally and spatially whilst fine-scale in-situ monitoring (e.g., terrestrial laser scanning) can be costly and is therefore confined to relatively small areas. The rise of proximal sensing-based Structure-from-Motion Multi-View Stereo (SfM-MVS) photogrammetric techniques for land surface surveying offers an alternative, scale-appropriate method for spatially distributed surveying of dune systems. Here we present the results of an inter- and intra-annual experiment which utilised a low-cost and highly portable kite aerial photography (KAP) and SfM-MVS workflow to track sub-decimetre spatial scale changes in dune morphology over timescales of between 3 and 12 months. We also compare KAP and drone surveys undertaken at near-coincident times of the same dune system to test the KAP reproducibility. Using a Monte Carlo based change detection approach (Multiscale Model to Model Cloud Comparison (M3C2)) which quantifies and accounts for survey uncertainty, we show that the KAP-based survey technique, whilst exhibiting higher x, y, z uncertainties than the equivalent drone methodology, is capable of delivering data describing dune system topographical change. Significant change (according to M3C2); both positive (accretion) and negative (erosion) was detected across 3, 6 and 12 months timescales with the majority of change detected below 500 mm. Significant topographic changes as small as ~20 mm were detected between surveys. We demonstrate that portable, low-cost consumer-grade KAP survey techniques, which have been employed for decades for hobbyist aerial photography, can now deliver science-grade data, and we argue that kites are well-suited to coastal survey where winds and sediment might otherwise impede surveys by other proximal sensing platforms, such as drones.
Smartphone-Based Microfluidic Colorimetric Sensor for Gaseous Formaldehyde Determination with High Sensitivity and Selectivity
Authors: Guo Xiao-Liang , Chen Yan , Jiang Hong-Lan , Qiu Xian-Bo , Yu Du-Li
Published: September 2018

Formaldehyde is one of the most dangerous air pollutants, which can cause sick building syndrome. Thus, it is very crucial to precisely determine formaldehyde with a low cost and simple operation. In this paper, a smartphone-based microfluidic colorimetric sensor is devised for gaseous formaldehyde determination with high sensitivity and selectivity. Specifically, a novel microfluidic chip is proposed based on the 4-aminohydrazine-5-mercapto-1,2,4-triazole (AHMT) method to determine formaldehyde; the chip consists of two reagent reservoirs, one reaction reservoir and a mixing column. In this design to prevent the fluid from flowing out while letting the gas molecule in, a hydrophobic porous poly tetra fluoroethylene (PTFE) membrane is put on the top of the reaction reservoir. Using the microfluidic chip sensor, a smartphone-based formaldehyde determination system is developed, which makes the measuring process automated and simple. As per the experiment results, the limit-of-detection (LOD) of the system is as low as 0.01 ppm, which is much lower than the maximum exposure concentration (0.08 ppm) recommended by the World Health Organization (WHO). Moreover, the sensor is hardly affected by acetaldehyde, volatile organic compounds (VOCs) or acidic-alkaline, which shows great selectivity. Finally, the performance of the proposed sensor is verified by using it for the determination of formaldehyde in a newly decorated house.
Consumers’ Preference and Factors Influencing Offal Consumption in Amathole District Eastern Cape, South Africa
Authors: Alao Babatunde Oluwasegun , Falowo Andrew Bamidele , Chulayo Amanda , Muchenje Voster
Published: September 2018

This study was conducted to determine the consumers’ perceptions and factors influencing offal meat consumption in Amathole District in the Eastern Cape Province of South Africa. A total of 202 consumers from Amathole District were randomly sampled from three municipalities. The study revealed that consumers were more influenced by the freshness, price, and availability of the product and these factors determine the point of purchase. The most preferred purchase-point for offal meat in this study was butchery. However, sheep offal was more preferred to cattle offal. The point of purchase, however, remains a prominent factor among other factors that could influence decision making for any consumer. When it comes to offal meat, the results showed that the majority of consumers purchased more liver, intestine, and tripe, which is because they are often sold in a combo at the butchery. Furthermore, it was revealed that consumers have nutritional knowledge of the offal meat products before making their purchase but health reasons emerged as a factor that the consumers considered the least at the point of purchase.
Prefiguring Sustainability through Participatory Action Research Experiences for Undergraduates: Reflections and Recommendations for Student Development
Authors: Trott Carlie D. , Weinberg Andrea E. , Sample McMeeking Laura B.
Published: September 2018

PAR-based UREs are undergraduate research experiences (UREs)—built into university-community partnerships—that apply principles of participatory action research (PAR) towards addressing community-defined challenges. In this paper, we advance PAR-based UREs as an action-oriented framework through which higher education institutions can simultaneously enact and advance the United Nations sustainable development agenda, while cultivating student development. We draw upon interdisciplinary scholarship on sustainable development and PAR, as well as empirical findings from a pilot program, to accomplish dual goals. First, through the lens of six Sustainable Development Goal (SDG) clusters, we explore the synergies between undergraduate PAR engagement and sustainable development, explaining how PAR-based UREs can prefigure and facilitate SDG achievement by promoting cross-sector collaboration and supporting diverse stakeholder engagement through community-driven research and action. Second, within each SDG cluster, we offer complementary reflections and recommendations around the design and implementation of PAR-based UREs towards advancing students’ skills and abilities as: (1) Community Collaborators (and Learners); (2) Community-Engaged Researchers; (3) (Interdisciplinary) Scholars; (4) Agents of Change; (5) (Sustainable) Co-Innovators; and (6) Institutional Representatives. Finally, we discuss the critical role of higher education institutions in minimizing structural barriers to PAR-based URE implementation, given their prefigurative and practical potential for both SDG achievement and student development.