bluuebunny/crossref_metadata_2025 huggingface dataset:
Phage Display-Based Homing Peptide-Daunomycin Conjugates for Selective Drug Targeting to PANC-1 Pancreatic Cancer
Authors: Dókus Levente E. , Lajkó Eszter , Ranđelović Ivan , Mező Diána , Schlosser Gitta , Kőhidai László , Tóvári József , Mező Gábor
Published: June 2020

The Pancreatic Ductal Adenocarcinoma (PDAC) is one of the most aggressive and dangerous cancerous diseases, leading to a high rate of mortality. Therefore, the development of new, more efficient treatment approaches is necessary to cure this illness. Peptide-based drug targeting provides a new tool for this purpose. Previously, a hexapeptide Cys-Lys-Ala-Ala-Lys-Asn (CKAAKN) was applied efficiently as the homing device for drug-loaded nanostructures in PDAC cells. In this research, Cys was replaced by Ser in the sequence and this new SKAAKN targeting moiety was used in conjugates containing daunomycin (Dau). Five different structures were developed and tested. The results indicated that linear versions with one Dau were not effective on PANC-1 cells in vitro; however, branched conjugates with two Dau molecules showed significant antitumor activity. Differences in the antitumor effect of the conjugates could be explained with the different cellular uptake and lysosomal degradation. The most efficient conjugate was Dau=Aoa-GFLG-K(Dau=Aoa)SKAAKN-OH (conjugate 4) that also showed significant tumor growth inhibition on s.c. implanted PANC-1 tumor-bearing mice with negligible side effects. Our novel results suggest that peptide-based drug delivery systems could be a promising tool for the treatment of pancreatic cancers.
Physiologically-Based Pharmacokinetic (PBPK) Modeling of Buprenorphine in Adults, Children and Preterm Neonates
Authors: Kovar Lukas , Schräpel Christina , Selzer Dominik , Kohl Yvonne , Bals Robert , Schwab Matthias , Lehr Thorsten
Published: June 2020

Buprenorphine plays a crucial role in the therapeutic management of pain in adults, adolescents and pediatric subpopulations. However, only few pharmacokinetic studies of buprenorphine in children, particularly neonates, are available as conducting clinical trials in this population is especially challenging. Physiologically-based pharmacokinetic (PBPK) modeling allows the prediction of drug exposure in pediatrics based on age-related physiological differences. The aim of this study was to predict the pharmacokinetics of buprenorphine in pediatrics with PBPK modeling. Moreover, the drug-drug interaction (DDI) potential of buprenorphine with CYP3A4 and P-glycoprotein perpetrator drugs should be elucidated. A PBPK model of buprenorphine and norbuprenorphine in adults has been developed and scaled to children and preterm neonates, accounting for age-related changes. One-hundred-percent of the predicted AUClast values in adults (geometric mean fold error (GMFE): 1.22), 90% of individual AUClast predictions in children (GMFE: 1.54) and 75% in preterm neonates (GMFE: 1.57) met the 2-fold acceptance criterion. Moreover, the adult model was used to simulate DDI scenarios with clarithromycin, itraconazole and rifampicin. We demonstrate the applicability of scaling adult PBPK models to pediatrics for the prediction of individual plasma profiles. The novel PBPK models could be helpful to further investigate buprenorphine pharmacokinetics in various populations, particularly pediatric subgroups.
Drug Release from a Spherical Matrix: Theoretical Analysis for a Finite Dissolution Rate Affected by Geometric Shape of Dispersed Drugs
Authors: Lin Yung-Sheng , Tsay Ruey-Yug
Published: June 2020

Amending the neglect of finite dissolution in traditional release models, this study proposed a more generalized drug release model considering the simultaneous dissolution and diffusion procedure from a drug-loaded spherical matrix. How the shape factor (n = 0, 1/2, and 2/3 for the planar, cylindrical, and spherical geometry, respectively) of dispersed drug particles affected the release from the matrix was examined for the first time. Numerical solutions of this generalized model were validated by consensus with a short-time analytical solution for planar drugs and by the approach of the diffusion-controlled limits with Higuchi’s model. The drug release rate increases with the ratio of dissolution/diffusion rate (G) and the ratio of solubility/drug loading (K) but decreases with the shape factor of drug particles. A zero-order release profile is identified for planar drugs before starting the surface depletion layer, and also found for cylindrical and spherical dispersed drugs when K and G are small, i.e. the loaded drug is mainly un-dissolved and the drug release rate is dissolution-controlled. It is also shown that for the case of a small G value, the variation of drug release profile, due to the drug particle geometry, becomes prominent. Detailed comparison with the results of the traditional Higuchi’s model indicates that Higuchi’s model can be applied only when G is large because of the assumption of an instantaneous dissolution. For K = 1/101–1/2, the present analysis suggests an error of 33–85% for drug release predicted by Higuchi’s model for G = 100, 14–44% error for G = 101, while a less than 5% error for G ≧ 103.
Development of ErbB2-Targeting Liposomes for Enhancing Drug Delivery to ErbB2-Positive Breast Cancer
Authors: Ueno Sho , Kim Min Woo , Lee Gibok , Park Yong Il , Niidome Takuro , Lee Ruda
Published: June 2020

ErbB2 is a type of receptor tyrosine kinase, which is known to be involved in tumorigenesis, tumor aggressiveness, and clinical outcome. ErbB2-targeting therapy using therapeutic antibodies has been successful in breast cancer treatment. However, the need for repeated treatments and the high cost are major disadvantages with monoclonal antibody therapies. Compared with antibodies, peptides are cheap, relatively stable, and have low immunogenicity. We have developed a highly specific cancer-targeting drug delivery system using a targeting peptide to maximize the therapeutic efficiency of rapamycin and to help prevent drug resistance in ErbB2-positive breast cancer. Physicochemical characterization confirmed the successful construction of ErbB2-targeting liposomes (ErbB2Lipo). A comparison of a scrambled peptide (ScrErbB2) with the ErbB2-targeting peptide confirmed that these peptides had similar properties except for the targeting ability. The ErbB2Lipo exhibited higher delivery efficiency in ErbB2 positive BT-474 cells than non-targeting liposomes conjugated with ScrErbB2 (ScrErbB2Lipo). This peptide-targeting strategy has the potential to improve the efficacy of chemotherapy in ErbB2-positive cancers.
Electrospun Eco-Friendly Materials Based on Poly(3-hydroxybutyrate) (PHB) and TiO2 with Antifungal Activity Prospective for Esca Treatment
Authors: Spasova Mariya , Stoilova Olya , Manolova Nevena , Rashkov Iliya , Naydenov Mladen
Published: June 2020

Esca is a type of grapevine trunk disease that severely affects vine yield and longevity. Phaeomoniella chlamydospora (P. chlamydospora) is one of the main fungi associated with esca. The aim of the present study was to obtain eco-friendly materials with potential antifungal activity against P. chlamydospora based on biodegradable and biocompatible poly(3-hydroxybutyrate) (PHB), nanosized TiO2-anatase (nanoTiO2), and chitosan oligomers (COS) by conjunction of electrospinning and electrospraying. One-pot electrospinning of a suspension of nanosized TiO2 nanoparticles in PHB solution resulted in materials in which TiO2 was incorporated within the fibers (design type “in”). Simultaneous electrospinning of PHB solution and electrospraying of the dispersion of nanosized TiO2 in COS solution enabled the preparation of materials consisting of PHB fibers on which TiO2 was deposited on the fibers’ surface (design type “on”). Several methods including scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction analysis (XRD), thermogravimetric analyses (TGA) and water contact angle were utilized to characterize the obtained materials. The incorporation of nanoTiO2 in the PHB fibers, as well as nanoTiO2 deposition onto the surface of the PHB fibers resulted in increased roughness and hydrophobicity of the obtained composite fibrous materials. Moreover, TiO2-on-PHB fibrous material exhibited complete inhibition of fungal growth of P. chlamydospora. Therefore, the obtained eco-friendly fibrous materials based on PHB and nanoTiO2 are promising candidates for protection against esca in agriculture.
Dendrimer Dynamics: A Review of Analytical Theories and Molecular Simulation Methods
Authors: Ganazzoli Fabio , Raffaini Giuseppina
Published: June 2020

The theoretical study of dendrimers is reviewed, considering both analytical approaches and molecular simulation methods. We discuss the effect of molecular symmetry on the degeneracy of the relaxation times, and then the calculation of observable quantities, in particular the intrinsic viscosity, and then the viscoelastic complex modulus and the dynamic structure factor, in comparison with the available experimental data. In particular, the maximum intrinsic viscosity with increasing molar mass is analyzed in some detail. The approximations and/or assumptions of the adopted methods are also described in connection with analogous results for polymer of a different topology, in particular linear and star polymers.
Graphene Nanoplatelets for the Development of Reinforced PLA–PCL Electrospun Fibers as the Next-Generation of Biomedical Mats
Authors: Chiesa Enrica , Dorati Rossella , Pisani Silvia , Bruni Giovanna , Rizzi Laura G. , Conti Bice , Modena Tiziana , Genta Ida
Published: June 2020

Electrospun scaffolds made of nano- and micro-fibrous non-woven mats from biodegradable polymers have been intensely investigated in recent years. In this field, polymer-based materials are broadly used for biomedical applications since they can be managed in high scale, easily shaped, and chemically changed to tailor their specific biologic properties. Nonetheless polymeric materials can be reinforced with inorganic materials to produce a next-generation composite with improved properties. Herein, the role of graphene nanoplatelets (GNPs) on electrospun poly-l-lactide-co-poly-ε-caprolactone (PLA–PCL, 70:30 molar ratio) fibers was investigated. Microfibers of neat PLA–PCL and with different amounts of GNPs were produced by electrospinning and they were characterized for their physicochemical and biologic properties. Results showed that GNPs concentration notably affected the fibers morphology and diameters distribution, influenced PLA–PCL chain mobility in the crystallization process and tuned the mechanical and thermal properties of the electrospun matrices. GNPs were also liable of slowing down copolymer degradation rate in simulated physiological environment. However, no toxic impurities and degradation products were pointed out up to 60 d incubation. Furthermore, preliminary biologic tests proved the ability of the matrices to enhance fibroblast cells attachment and proliferation probably due to their unique 3D-interconnected structure.
Transdermal Composite Microneedle Composed of Mesoporous Iron Oxide Nanoraspberry and PVA for Androgenetic Alopecia Treatment
Authors: Fang Jen-Hung , Liu Che-Hau , Hsu Ru-Siou , Chen Yin-Yu , Chiang Wen-Hsuan , Wang Hui-Min David , Hu Shang-Hsiu
Published: June 2020

The transdermal delivery of therapeutic agents amplifying a local concentration of active molecules have received considerable attention in wide biomedical applications, especially in vaccine development and medical beauty. Unlike oral or subcutaneous injections, this approach can not only avoid the loss of efficacy of oral drugs due to the liver’s first-pass effect but also reduce the risk of infection by subcutaneous injection. In this study, a magneto-responsive transdermal composite microneedle (MNs) with a mesoporous iron oxide nanoraspberry (MIO), that can improve the drug delivery efficiency, was fabricated by using a 3D printing-molding method. With loading of Minoxidil (Mx, a medication commonly used to slow the progression of hair loss and speed the process of hair regrowth), MNs can break the barrier of the stratum corneum through the puncture ability, and control the delivery dose for treating androgenetic alopecia (AGA). By 3D printing process, the sizes and morphologies of MNs is able to be, easily, architected. The MIOs were embedded into the tip of MNs which can deliver Mx as well as generate mild heating for hair growth, which is potentially attributed by the expansion of hair follicle and drug penetration. Compared to the mice without any treatments, the hair density of mice exhibited an 800% improvement after being treated by MNs with MF at 10-days post-treatment.
Self-Healing Thermoplastic Polyurethane Linked via Host-Guest Interactions
Authors: Jin Changming , Sinawang Garry , Osaki Motofumi , Zheng Yongtai , Yamaguchi Hiroyasu , Harada Akira , Takashima Yoshinori
Published: June 2020

High toughness with self-healing ability has become the ultimate goal in materials research. Herein, thermoplastic polyurethane (TPU) was linked via host-guest (HG) interactions to increase its mechanical properties and self-healing ability. TPU linked via HG interactions was prepared by the step-growth bulk polymerization of hexamethylene diisocyanate (HDI), tetraethylene glycol (TEG), and HG interactions between permethylated amino βCD (PMeAmβCD) and adamantane amine (AdAm). TPU linked with 10 mol% of HG interactions (HG(10)) showed the highest rupture stress and fracture energy (GF) of 11 MPa and 25 MJ·m−3, which are almost 40-fold and 1500-fold, respectively, higher than those of non-functionalized TEG-based TPU (PU). Additionally, damaged HG(10) shows 87% recovery after heated for 7 min at 80 °C, and completely cut HG(10) shows 80% recovery after 60 min of reattachment at same temperature. The HG interactions in TPU are an important factor in stress dispersion, increasing both its mechanical and self-healing properties. The TPU linked via HG interactions has great promise for use in industrial materials in the near future.
Monocomponent Photoinitiators based on Benzophenone-Carbazole Structure for LED Photoinitiating Systems and Application on 3D Printing
Authors: Liu Shaohui , Chen Hong , Zhang Yijun , Sun Ke , Xu Yangyang , Morlet-Savary Fabrice , Graff Bernadette , Noirbent Guillaume , Pigot Corentin , Brunel Damien , Nechab Malek , Gigmes Didier , Xiao Pu , Dumur Frédéric , Lalevée Jacques
Published: June 2020

In this article, different substituents (benzoyl, acetyl, styryl) are introduced onto the carbazole scaffold to obtain 8 novel carbazole derivatives. Interestingly, a benzoyl substituent, connected to a carbazole group, could form a benzophenone moiety, which composes a monocomponent Type II benzophenone-carbazole photoinitiator (PI). The synergetic effect of the benzophenone moiety and the amine in the carbazole moiety is expected to produce high performance photoinitiating systems (PISs) for the free radical photopolymerization (FRP). For different substituents, clear effects on the light absorption properties are demonstrated using UV-Visible absorption spectroscopy. Benzophenone-carbazole PIs can initiate the FRP of acrylates alone (monocomponent Type II photoinitiator behavior). In addition, fast polymerization rates and high function conversions of acrylate are observed when an amine and/or an iodonium salt are added in systems. Benzophenone-carbazole PIs have good efficiencies in cationic photopolymerization (CP) upon LED @ 365 nm irradiation in the presence of iodonium salt. In contrast, other PIs without synergetic effect demonstrate unsatisfied photopolymerization profiles in the same conditions. The best PIS identified for the free radical photopolymerization were used in three-dimensional (3D) printing. Steady state photolysis and fluorescence quenching experiments were carried out to investigate the reactivity and the photochemistry and photophysical properties of PIs. The free radicals, generated from the studied PISs, are detected by the electron spin resonance - spin trapping technique. The proposed chemical mechanisms are provided and the structure/reactivity/efficiency relationships are also discussed. All the results showed that the benzophenone-carbazole PIs have a good application potential, and this work provides a rational design route for PI molecules. Remarkably, BPC2-BPC4, C6, C8 were never synthetized before; therefore, 5 of the 8 compounds are completely new.
Development of a 3D Printed Coating Shell to Control the Drug Release of Encapsulated Immediate-Release Tablets
Authors: Algahtani Mohammed S. , Mohammed Abdul Aleem , Ahmad Javed , Saleh Ehab
Published: June 2020

The use of 3D printing techniques to control drug release has flourished in the past decade, although there is no generic solution that can be applied to the full range of drugs or solid dosage forms. The present study provides a new concept, using the 3D printing technique to print a coating system in the form of shells with various designs to control/modify drug release in immediate-release tablets. A coating system of cellulose acetate in the form of an encapsulating shell was printed through extrusion-based 3D printing technology, where an immediate-release propranolol HCl tablet was placed inside to achieve a sustained drug release profile. The current work investigated the influence of shell composition by using different excipients and also by exploring the impact of shell size on the drug release from the encapsulated tablet. Three-dimensional printed shells with different ratios of rate-controlling polymer (cellulose acetate) and pore-forming agent (D-mannitol) showed the ability to control the amount and the rate of propranolol HCl release from the encapsulated tablet model. The shell-print approach also showed that space/gap available for drug dissolution between the shell wall and the enclosed tablet significantly influenced the release of propranolol HCl. The modified release profile of propranolol HCl achieved through enclosing the tablet in a 3D printed controlled-release shell followed Korsmeyer–Peppas kinetics with non-Fickian diffusion. This approach could be utilized to tailor the release profile of a Biopharmaceutics Classification System (BCS) class I drug tablet (characterized by high solubility and high permeability) to improve patient compliance and promote personalized medicine.
Stimuli-Responsive Polymeric Nanocarriers for Drug Delivery, Imaging, and Theragnosis
Authors: Das Sabya Sachi , Bharadwaj Priyanshu , Bilal Muhammad , Barani Mahmood , Rahdar Abbas , Taboada Pablo , Bungau Simona , Kyzas George Z.
Published: June 2020

In the past few decades, polymeric nanocarriers have been recognized as promising tools and have gained attention from researchers for their potential to efficiently deliver bioactive compounds, including drugs, proteins, genes, nucleic acids, etc., in pharmaceutical and biomedical applications. Remarkably, these polymeric nanocarriers could be further modified as stimuli-responsive systems based on the mechanism of triggered release, i.e., response to a specific stimulus, either endogenous (pH, enzymes, temperature, redox values, hypoxia, glucose levels) or exogenous (light, magnetism, ultrasound, electrical pulses) for the effective biodistribution and controlled release of drugs or genes at specific sites. Various nanoparticles (NPs) have been functionalized and used as templates for imaging systems in the form of metallic NPs, dendrimers, polymeric NPs, quantum dots, and liposomes. The use of polymeric nanocarriers for imaging and to deliver active compounds has attracted considerable interest in various cancer therapy fields. So-called smart nanopolymer systems are built to respond to certain stimuli such as temperature, pH, light intensity and wavelength, and electrical, magnetic and ultrasonic fields. Many imaging techniques have been explored including optical imaging, magnetic resonance imaging (MRI), nuclear imaging, ultrasound, photoacoustic imaging (PAI), single photon emission computed tomography (SPECT), and positron emission tomography (PET). This review reports on the most recent developments in imaging methods by analyzing examples of smart nanopolymers that can be imaged using one or more imaging techniques. Unique features, including nontoxicity, water solubility, biocompatibility, and the presence of multiple functional groups, designate polymeric nanocues as attractive nanomedicine candidates. In this context, we summarize various classes of multifunctional, polymeric, nano-sized formulations such as liposomes, micelles, nanogels, and dendrimers.
Green Highly Clay-Filled Polyethylene Composites as Coating Materials for Cable Industry—A New Application Route of Non-Organophilised Natural Montmorillonites in Polymeric Materials
Authors: Wysocki Stanisław , Kowalczyk Krzysztof , Paszkiewicz Sandra , Figiel Paweł , Piesowicz Elżbieta
Published: June 2020

In order to develop flame retardant and relatively green cable coating materials, polyethylene (PE) was melt blended with 5, 7.5, or 10 wt. % of a natural calcium montmorillonite (C–Ca) pre-dispersed in EBA (ethylene-butyl acrylate copolymer), EVA (ethylene-vinyl acetate copolymer), or mEVA (EVA modified with maleic anhydride). For comparison, an organophilised montmorillonite (CW9) was tested. The main study of composites containing EBA/C–Ca, EVA/C–Ca, and mEVA/CW9 pre-dispersions revealed that both clays were not fully exfoliated in the matrix, however, C–Ca (7.5 wt. %) markedly increased limited oxygen index (LOI) from 18% O2 (PE) up to 22.0% O2. An insignificantly higher LOI value (22.2% O2) was noted for a sample with 10 wt. % of CW9. The fillers did not affect hardness, but spectacularly increased Young’s modulus of the compression-moulded samples (tensile strength and elongation at break values were reduced). Thermal features of the matrix were not unpredictably changed by the clays. Generally, all the tests revealed that PE filled with the chemically untreated natural C–Ca reached similar or better mechanical and thermal features than materials containing the ammonium salt-modified montmorillonite.
Mechanical and Rheological Behaviour of Composites Reinforced with Natural Fibres
Authors: Stanciu Mariana D. , Teodorescu Draghicescu Horatiu , Tamas Florin , Terciu Ovidiu Mihai
Published: June 2020

The paper deals with the mechanical behaviour of natural fibre composites subjected to tensile test and dynamic mechanical analysis (DMA). Three types of natural fibre composites were prepared and tested: wood particle reinforced composites with six different sizes of grains (WPC); hemp mat reinforced composites (HMP) and flax reinforced composite with mixed wood particles (FWPC). The tensile test performed on universal testing machine LS100 Lloyd’s Instrument highlights the elastic properties of the samples, as longitudinal elasticity modulus; tensile rupture; strain at break; and stiffness. The large dispersion of stress–strain curves was noticed in the case of HMP and FWPC by comparison to WPC samples which present high homogeneity of elastic–plastic behaviour. The DMA test emphasized the rheological behaviour of natural fibre composites in terms of energy dissipation of a material under cyclic load. Cole–Cole plots revealed the connection between stored and loss heat energy for studied samples. The mixture of wood particles with a polyester matrix leads to relative homogeneity of composite in comparison with FWPC and HMP samples which is visible from the shape of Cole–Cole curves. The random fibres from the hemp mat structure lead to a heterogeneous nature of composite structure. The elastic and viscous responses of samples depend on the interface between fibres and matrix.
Well-Blended PCL/PEO Electrospun Nanofibers with Functional Properties Enhanced by Plasma Processing
Authors: Kupka Vojtěch , Dvořáková Eva , Manakhov Anton , Michlíček Miroslav , Petruš Josef , Vojtová Lucy , Zajíčková Lenka
Published: June 2020

Biodegradable composite nanofibers were electrospun from poly(ε-caprolactone) (PCL) and poly(ethylene oxide) (PEO) mixtures dissolved in acetic and formic acids. The variation of PCL:PEO concentration in the polymer blend, from 5:95 to 75:25, revealed the tunability of the hydrolytic stability and mechanical properties of the nanofibrous mats. The degradation rate of PCL/PEO nanofibers can be increased compared to pure PCL, and the mechanical properties can be improved compared to pure PEO. Although PCL and PEO have been previously reported as immiscible, the electrospinning into nanofibers having restricted dimensions (250–450 nm) led to a microscopically mixed PCL/PEO blend. However, the hydrolytic stability and tensile tests revealed the segregation of PCL into few-nanometers-thin fibrils in the PEO matrix of each nanofiber. A synergy phenomenon of increased stiffness appeared for the high concentration of PCL in PCL/PEO nanofibrous mats. The pure PCL and PEO mats had a Young’s modulus of about 12 MPa, but the mats made of high concentration PCL in PCL/PEO solution exhibited 2.5-fold higher values. The increase in the PEO content led to faster degradation of mats in water and up to a 20-fold decrease in the nanofibers’ ductility. The surface of the PCL/PEO nanofibers was functionalized by an amine plasma polymer thin film that is known to increase the hydrophilicity and attach proteins efficiently to the surface. The combination of different PCL/PEO blends and amine plasma polymer coating enabled us to tune the surface functionality, the hydrolytic stability, and the mechanical properties of biodegradable nanofibrous mats.
Innovation in Tigernut (Cyperus Esculentus L.) Milk Production: In Situ Hydrolysis of Starch
Authors: Djomdi  , Hamadou Bakari , Gibert Olivier , Tran Thierry , Delattre Cedric , Pierre Guillaume , Michaud Philippe , Ejoh Richard , Ndjouenkeu Robert
Published: June 2020

Tigernut tubers (Cyperus esculentus) are used for the production of vegetable milk, commonly known as “Horchata de chufa” in Spain. The presence of starch in the tuber limits the yield of the milk, since this carbohydrate gelatinizes during the pasteurization of the milk and leads to the considerable solidification of this drink. The present work aims to improve the yields and extraction practice of the milk by an in situ hydrolysis of starch, using exogenous amylases of industrial or vegetable origin. The obtained results show that sprouting improves the extraction yields of tigernut milk, which goes from 50% to about 70%. This improvement in milk yield corresponds to a hydrolysis of about 35% of the starch in the tuber. The use of exogenous amylases leads to starch hydrolysis rates of 45% and 70%, respectively, for amylolytic extracts from sprouted tigernut tubers and amylase, with the corollary of a natural increase in the sweetness of milk. This technical approach makes it possible to produce a naturally sweetened tigernut milk which easily lends itself to pasteurization without a significant increase in viscosity.
Solid-Contact Potentiometric Sensors Based on Stimulus-Responsive Imprinted Polymers for Reversible Detection of Neutral Dopamine
Authors: H. Kamel Ayman , Amr Abd El-Galil E. , Ashmawy Nashwa H. , Galal Hoda R. , Al-Omar Mohamed A. , Sayed Ahmed Y. A.
Published: June 2020

Herein, we present for the first time a novel potentiometric sensor based on the stimulus-responsive molecularly imprinted polymer (MIP) as a selective receptor for neutral dopamine determination. This smart receptor can change its capabilities to recognize according to external environmental stimuli. Therefore, MIP-binding sites can be regenerated in the polymeric membrane by stimulating with stimulus after each measurement. Based on this effect, reversible detection of the analyte via potentiometric transduction can be achieved. MIPs based on 4-vinylphenylboronic acid as the functional monomer were prepared as the selective receptor. This monomer can successfully bind to dopamine via covalent binding and forming a five- or six-membered cyclic ester in a weakly alkaline aqueous solution. In acidic medium, the produced ester dissociates and regenerates new binding sites in the polymeric membrane. The proposed smart sensor exhibited fast response and good sensitivity towards dopamine with a limit of detection 0.15 µM over the linear range 0.2–10 µM. The selectivity pattern of the proposed ISEs was also evaluated and revealed an enhanced selectivity towards dopamine over several phenolic compounds. Constant-current chronopotentiometry is used for evaluating the short-term potential stability of the proposed ISEs. The obtained results confirm that the stimulus-responsive MIPs provide an attractive way towards reversible MIP-based electrochemical sensors designation.
Hydrophilic Submicron Nanogel Particles for Specific Recombinant Proteins Extraction and Purification
Authors: Levourch Gaëlle , Lebaz Noureddine , Elaissari Abdelhamid
Published: June 2020

In biomedical diagnosis and bionanotechnologies, the extraction and purification of proteins and protein derivatives are of great interest. In fact, to purify recombinant proteins for instance, new methodologies and well appropriate material supports need to be established and also to be evaluated. In this work, hydrophilic nanohydrogel particles were prepared for recombinant proteins extraction for purification purpose. The prepared nanohydrogel polymer-based particles are hydrophilic below the volume phase transition temperature (TVPT) and dehydrated above the TVPT, due to the thermally sensitive poly(N-alkyl acrylamide) and poly(N-alkyl methacrylamide) derivatives. Then, the use of heavy metal ions in the presence of such functional particles should specifically capture recombinant proteins (i.e., proteins bearing a poly(histidine) part). In order to understand and to optimize the specific capture and the purification of recombinant proteins, various parameters have been investigated as a systematic study. Firstly, the adsorption was investigated as a function of pH and protein concentration. According to high hydration of the prepared nanohydrogel, no marked adsorption was observed. Secondly, the effect of pH was investigated and found to be the driven parameter affecting the metal ions immobilization and the recombinant proteins complexation. As a result, high protein complexation was observed at basic pH compared to non-complexation at acidic pH medium. The immobilized proteins via complexation were released by changing the pH. This decomplexation seems to be effective but depends on fixation conditions and particle surface structure.
An Innovative Method for the Recycling of Waste Carbohydrate-Based Flours
Authors: Esposito Corcione Carola , Striani Raffaella , Ferrari Francesca , Visconti Paolo , Rizzo Daniela , Greco Antonio
Published: June 2020

This work represents an innovative study that, for the first time, explores the possibility to use waste flours to produce thermoplastic polymeric bio-films. To the best of our knowledge, this is the first time that waste flours, derived from bakeries, pizzerias or pasta factories, have been proposed for the production of bio-polymers, as a replacement of neat starch. To this aim, durum waste flour derived from a pasta factory, soft waste flour derived from pizzerias and neat maize starch used as control material were firstly analyzed from dimensional, morphological and chemical points of view. Afterwards, waste flour films were produced by the addition of a nature-based plasticizer, glycerol. Mechanical characterization of the plasticized thermoplastic films, produced by compression molding, evidenced low performances, even in the case of the neat maize starch. In order to improve the mechanical properties, the possibility to include polylactic acid and cardanol-based plasticizer was also investigated. Mass transport properties of all the produced bio-films were investigated by measuring their water vapor permeability and hygroscopic absorption. The durability properties of the bio-films were assessed by accelerated ageing tests, while the bio-degradability of the waste-based films was evaluated by measuring the solubility and the degradation in water. The physicochemical analyses of the novel bio-films evidenced good mechanical properties; specifically, the waste-based films showed a lower hygroscopic absorption and water solubility than those of the blends containing neat starch.
Eco Friendly Approach for Synthesis, Characterization and Biological Activities of Milk Protein Stabilized Silver Nanoparticles
Authors: Pandey Sadanand , De Klerk Corli , Kim Joonwoo , Kang Misook , Fosso-Kankeu Elvis
Published: June 2020

Today, the overall occurrence of re-emerging and rising illnesses has been a serious load on economies as well as public health. Here, we describe a simple, nontoxic and eco-friendly method for the synthesis of milk protein (MP)-stabilized silver nanoparticles (MP-s-AgNPs) using ultrahigh-temperature full cream milk. Highly stable AgNPs were prepared with a fair control over their size, without using any reducing or stabilizing agent, and their formation was attributed to the presence of the MP casein. Ag+ ion reduction was possibly caused by the MPs. The synthesized MP-s-AgNPs were characterized in detail by ultraviolet-visible spectroscopy, Fourier-transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy, transmission electron microscopy and dynamic light scattering. MP-s-AgNPs showed inhibitory activity against both Gram-positive (Bacillus subtilis and Staphylococcus aureus) and Gram-negative microorganisms (Salmonella typhi and Escherichia coli). Moreover, MP-s-AgNPs were found to be more toxic to bacteria than to fungi (Aspergillus fumigatus, Aspergillus ochraceus and Penicillium chrysogenum).
JL-GFDN: A Novel Gabor Filter-Based Deep Network Using Joint Spectral-Spatial Local Binary Pattern for Hyperspectral Image Classification
Authors: Zhang Tao , Zhang Puzhao , Zhong Weilin , Yang Zhen , Yang Fan
Published: June 2020

The traditional local binary pattern (LBP, hereinafter we also call it a two-dimensional local binary pattern 2D-LBP) is unable to depict the spectral characteristics of a hyperspectral image (HSI). To cure this deficiency, this paper develops a joint spectral-spatial 2D-LBP feature (J2D-LBP) by averaging three different 2D-LBP features in a three-dimensional hyperspectral data cube. Subsequently, J2D-LBP is added into the Gabor filter-based deep network (GFDN), and then a novel classification method JL-GFDN is proposed. Different from the original GFDN framework, JL-GFDN further fuses the spectral and spatial features together for HSI classification. Three real data sets are adopted to evaluate the effectiveness of JL-GFDN, and the experimental results verify that (i) JL-GFDN has a better classification accuracy than the original GFDN; (ii) J2D-LBP is more effective in HSI classification in comparison with the traditional 2D-LBP.
The Fusion of Spectral and Structural Datasets Derived from an Airborne Multispectral Sensor for Estimation of Pasture Dry Matter Yield at Paddock Scale with Time
Authors: Karunaratne Senani , Thomson Anna , Morse-McNabb Elizabeth , Wijesingha Jayan , Stayches Dani , Copland Amy , Jacobs Joe
Published: June 2020

This study aimed to develop empirical pasture dry matter (DM) yield prediction models using an unmanned aerial vehicle (UAV)-borne sensor at four flying altitudes. Three empirical models were developed using features generated from the multispectral sensor: Structure from Motion only (SfM), vegetation indices only (VI), and in combination (SfM+VI) within a machine learning modelling framework. Four flying altitudes were tested (25 m, 50 m, 75 m and 100 m) and based on independent model validation, combining features from SfM+VI outperformed the other models at all heights. However, the importance of SfM-based features changed with altitude, with limited importance at 25 m but at all higher altitudes SfM-based features were included in the top 10 features in a variable importance plot. Based on the independent validation results, data generated at 25 m flying altitude reported the best model performances with model accuracy of 328 kg DM/ha. In contrast, at 100 m flying altitude, the model reported an accuracy of 402 kg DM/ha which demonstrates the potential of scaling up this technology at farm scale. The spatial-temporal maps provide valuable information on pasture DM yield and DM accumulation of herbage mass over the time, supporting on-farm management decisions.
Automatic Extraction of Road Points from Airborne LiDAR Based on Bidirectional Skewness Balancing
Authors: Martínez Sánchez Jorge , Fernández Rivera Francisco , Cabaleiro Domínguez José Carlos , López Vilariño David , Fernández Pena Tomás
Published: June 2020

Road extraction from Light Detection and Ranging (LiDAR) has become a hot topic over recent years. Nevertheless, it is still challenging to perform this task in a fully automatic way. Experiments are often carried out over small datasets with a focus on urban areas and it is unclear how these methods perform in less urbanized sites. Furthermore, some methods require the manual input of critical parameters, such as an intensity threshold. Aiming to address these issues, this paper proposes a method for the automatic extraction of road points suitable for different landscapes. Road points are identified using pipeline filtering based on a set of constraints defined on the intensity, curvature, local density, and area. We focus especially on the intensity constraint, as it is the key factor to distinguish between road and ground points. The optimal intensity threshold is established automatically by an improved version of the skewness balancing algorithm. Evaluation was conducted on ten study sites with different degrees of urbanization. Road points were successfully extracted in all of them with an overall completeness of 93%, a correctness of 83%, and a quality of 78%. These results are competitive with the state-of-the-art.
Using Deep Learning to Count Albatrosses from Space: Assessing Results in Light of Ground Truth Uncertainty
Authors: Bowler Ellen , Fretwell Peter T. , French Geoffrey , Mackiewicz Michal
Published: June 2020

Many wildlife species inhabit inaccessible environments, limiting researchers ability to conduct essential population surveys. Recently, very high resolution (sub-metre) satellite imagery has enabled remote monitoring of certain species directly from space; however, manual analysis of the imagery is time-consuming, expensive and subjective. State-of-the-art deep learning approaches can automate this process; however, often image datasets are small, and uncertainty in ground truth labels can affect supervised training schemes and the interpretation of errors. In this paper, we investigate these challenges by conducting both manual and automated counts of nesting Wandering Albatrosses on four separate islands, captured by the 31 cm resolution WorldView-3 sensor. We collect counts from six observers, and train a convolutional neural network (U-Net) using leave-one-island-out cross-validation and different combinations of ground truth labels. We show that (1) interobserver variation in manual counts is significant and differs between the four islands, (2) the small dataset can limit the networks ability to generalise to unseen imagery and (3) the choice of ground truth labels can have a significant impact on our assessment of network performance. Our final results show the network detects albatrosses as accurately as human observers for two of the islands, while in the other two misclassifications are largely caused by the presence of noise, cloud cover and habitat, which was not present in the training dataset. While the results show promise, we stress the importance of considering these factors for any study where data is limited and observer confidence is variable.
Remotely Sensed Urban Surface Ecological Index (RSUSEI): An Analytical Framework for Assessing the Surface Ecological Status in Urban Environments
Authors: Firozjaei Mohammad Karimi , Fathololoumi Solmaz , Weng Qihao , Kiavarz Majid , Alavipanah Seyed Kazem
Published: June 2020

Urban Surface Ecological Status (USES) reflects the structure and function of an urban ecosystem. USES is influenced by the surface biophysical, biochemical, and biological properties. The assessment and modeling of USES is crucial for sustainability assessment in support of achieving sustainable development goals such as sustainable cities and communities. The objective of this study is to present a new analytical framework for assessing the USES. This analytical framework is centered on a new index, Remotely Sensed Urban Surface Ecological index (RSUSEI). In this study, RSUSEI is used to assess the USES of six selected cities in the U.S.A. To this end, Landsat 8 images, water vapor products, and the National Land Cover Database (NLCD) land cover and imperviousness datasets are downloaded for use. Firstly, Land Surface Temperature (LST), Wetness, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Soil Index (NDSI) are derived by remote sensing methods. Then, RSUSEI is developed by the combination of NDVI, NDSI, Wetness, LST, and Impervious Surface Cover (ISC) with Principal Components Analysis (PCA). Next, the spatial variations of USES across the cities are evaluated and compared. Finally, the association degree of each parameter in the USES modeling is investigated. Results show that the spatial variability of LST, ISC, NDVI, NDSI, and Wetness is heterogeneous within and between cities. The mean (standard deviation) value of RSUSEI for Minneapolis, Dallas, Phoenix, Los Angeles, Chicago and Seattle yielded 0.58 (0.16), 0.54 (0.17), 0.47 (0.19), 0.63 (0.21), 0.50 (0.17), and 0.44 (0.19), respectively. For all the cities, PC1 included more than 93% of the surface information, which is contributed by greenness, moisture, dryness, heat, and imperviousness. The highest and lowest mean values of RSUSEI are found in “Developed, High intensity” (0.76) and “Developed, Open Space” (0.35) lands, respectively. The mean correlation coefficient between RSUSEI and LST, ISC, NDVI, NDSI, and Wetness, is 0.47, 0.97, −0.31, 0.17, and −0.27, respectively. The statistical significance of these correlations is confirmed at 95% confidence level. These results suggest that the association degree of ISC in USES modeling is the highest, despite the differences in land cover and biophysical characteristics in the cities. RSUSEI could be very useful in modeling and comparing USES across cities with different geographical, climatic, environmental, and biophysical conditions and can also be used for assessing urban sustainability over space and time.
Assessment of Remotely Sensed and Modelled Soil Moisture Data Products in the U.S. Southern Great Plains
Authors: Jiang Bo , Su Hongbo , Liu Kai , Chen Shaohui
Published: June 2020

Soil moisture (SM) plays a crucial role in the water and energy flux exchange between the atmosphere and the land surface. Remote sensing and modeling are two main approaches to obtain SM over a large-scale area. However, there is a big difference between them due to algorithm, spatial-temporal resolution, observation depth and measurement uncertainties. In this study, an assessment of the comparison of two state-of-the-art remotely sensed SM products, Soil Moisture Active Passive (SMAP) and European Space Agency Climate Change Initiative (ESACCI), and one land surface modeled dataset from the North American Land Data Assimilation System project phase 2 (NLDAS-2), were conducted using 17 permanent SM observation sites located in the Southern Great Plains (SGP) in the U.S. We first compared the daily mean SM of three products with in-situ measurements; then, we decompose the raw time series into a short-term seasonal part and anomaly by using a moving smooth window (35 days). In addition, we calculate the daily spatial difference between three products based on in-situ data and assess their temporal evolution. The results demonstrate that (1) in terms of temporal correlation R, the SMAP (R = 0.78) outperforms ESACCI (R = 0.62) and NLDAS-2 (R = 0.72) overall; (2) for the seasonal component, the correlation R of SMAP still outperforms the other two products, and the correlation R of ESACCI and NLDAS-2 have not improved like the SMAP; as for anomaly, there is no difference between the remotely sensed and modeling data, which implies the potential for the satellite products to capture the variations of short-term rainfall events; (3) the distribution pattern of spatial bias is different between the three products. For NLDAS-2, it is strongly dependent on precipitation; meanwhile, the spatial distribution of bias represents less correlation with the precipitation for two remotely sensed products, especially for the SMAP. Overall, the SMAP was superior to the other two products, especially when the SM was of low value. The difference between the remotely sensed and modeling products with respect to the vegetation type might be an important reason for the errors.
Residual Group Channel and Space Attention Network for Hyperspectral Image Classification
Authors: Wu Peida , Cui Ziguan , Gan Zongliang , Liu Feng
Published: June 2020

Recently, deep learning methods based on three-dimensional (3-D) convolution have been widely used in the hyperspectral image (HSI) classification tasks and shown good classification performance. However, affected by the irregular distribution of various classes in HSI datasets, most previous 3-D convolutional neural network (CNN)-based models require more training samples to obtain better classification accuracies. In addition, as the network deepens, which leads to the spatial resolution of feature maps gradually decreasing, much useful information may be lost during the training process. Therefore, how to ensure efficient network training is key to the HSI classification tasks. To address the issue mentioned above, in this paper, we proposed a 3-DCNN-based residual group channel and space attention network (RGCSA) for HSI classification. Firstly, the proposed bottom-up top-down attention structure with the residual connection can improve network training efficiency by optimizing channel-wise and spatial-wise features throughout the whole training process. Secondly, the proposed residual group channel-wise attention module can reduce the possibility of losing useful information, and the novel spatial-wise attention module can extract context information to strengthen the spatial features. Furthermore, our proposed RGCSA network only needs few training samples to achieve higher classification accuracies than previous 3-D-CNN-based networks. The experimental results on three commonly used HSI datasets demonstrate the superiority of our proposed network based on the attention mechanism and the effectiveness of the proposed channel-wise and spatial-wise attention modules for HSI classification. The code and configurations are released at Github.com.
Model for Wireless Magnetoelastic Strain Sensors
Authors: Bastos Eduardo S. , Bormio-Nunes Cristina , Clarke Thomas G. R. , Missell Frank P.
Published: June 2020

This paper describes a magnetoelastic strain sensor based on the ∆E effect and discusses some materials used in its construction. A polycrystalline Fe–Al–B alloy with good quality magnetoelastic properties was used as the transducer and glued to the test object, either brass plates or rods of SAE 1010 steel. The strain-dependent magnetic field of the transducer changes the operating point of the resonator, a strip of field-annealed Metglas 2826MB3, resulting in a modification of its resonant frequency. A model was developed to simulate the strain-dependent magnetic field acting on the resonator and thus to calculate curves of resonant frequency vs. deformation. With the help of this model, differences in the shape of the frequency vs. strain curve can be understood. For a sensor with resonant frequency of 60.5 kHz glued to a rod of SAE 1010 steel, a total resonant frequency variation ∆f ~7 kHz was observed for a deformation of 1100 ppm. The geometry of this sensor is especially favorable for the remote monitoring of a steel surface, such as the wires of the tensile armor of a marine riser.