bluuebunny/crossref_metadata_2025 huggingface dataset:
Ketogal Safety Profile in Human Primary Colonic Epithelial Cells and in Mice
Authors: Sodano Federica , Avallone Bice , Tizzano Monica , Fogliano Chiara , Rolando Barbara , Gazzano Elena , Riganti Chiara , Magliocca Salvatore , Cuozzo Mariarosaria , Albrizio Stefania , Calignano Antonio , Cristiano Claudia , Russo Roberto , Rimoli Maria Grazia
Published: November 2021

In our previous studies, a ketorolac–galactose conjugate (ketogal) showed prolonged anti-inflammatory and analgesic activity, causing less gastric ulcerogenic effect and renal toxicity than its parent drug ketorolac. In order to demonstrate the safer profile of ketogal compared to ketorolac, histopathological changes in the small intestine and liver using three staining techniques before and after repeated oral administration in mice with ketorolac or an equimolecular dose of its galactosylated prodrug ketogal were assessed. Cytotoxicity and oxidative stress parameters were evaluated and compared in ketorolac- and ketogal-treated Human Primary Colonic Epithelial cells at different concentrations and incubation times. Evidence of mitochondrial oxidative stress was found after ketorolac treatment; this was attributable to altered mitochondrial membrane depolarization and oxidative stress parameters. No mitochondrial damage was observed after ketogal treatment. In ketorolac-treated mice, severe subepithelial vacuolation and erosion with inflammatory infiltrates and edematous area in the intestinal tissues were noted, as well as alterations in sinusoidal spaces and hepatocytes with foamy cytoplasm. In contrast, treatment with ketogal provided a significant improvement in the morphology of both organs. The prodrug clearly demonstrated a safer profile than its parent drug both in vitro and ex vivo, confirming that ketogal is a strategic alternative to ketorolac.
Network Pharmacology Study and Experimental Confirmation Revealing the Ameliorative Effects of Decursin on Chemotherapy-Induced Alopecia
Authors: Kim Mi Hye , Park Sang Jun , Yang Woong Mo
Published: November 2021

Decursin, a pyranocoumarin compound from the root of Angelica gigas Nakai as a main constituent, has been reported to have various biological activities, including anti-inflammatory, anticancer, and antioxidant effects. This study aimed to predict and confirm the pharmacological relevance of Decursin on chemotherapy-induced alopecia (CIA) with the underlying molecular mechanisms. Decursin-targeted genes were compared with the gene set of alopecia and investigated through functional enrichment analysis. CIA was induced in C57BL/6J mice by injection of cyclophosphamide, and 1, 10, and 100 μM of Decursin were topically treated to depilated dorsal skin. KGF+ expression was detected in the dorsal skin tissues. Based on the predicted results, caspase, PIK3/AKT, and MAPKs protein expressions by Decursin were analyzed in the TNF-α-induced keratinocytes. The Decursin network had 60.20% overlapped genes with the network of alopecia. Biological processes, such as cellular response to chemical stimulus, apoptosis, PI3K-AKT signaling pathway, and MAPK signaling pathway, were derived from the Decursin network. In the Decursin-treated skin, there was morphological hair growth and histological restoration of hair follicles in the CIA mice. The KGF+ fluorescence and protein expressions were significantly increased by Decursin treatment. In addition, caspase-3, -7, and -8 expressions, induced by TNF-α, were dose-dependently decreased along with the inhibition of PI3K, AKT, ERK, and p38 expressions in Decursin-treated keratinocytes. These findings indicated that Decursin would be a potent therapeutic option for hair loss, in response to chemotherapy.
Drug Therapeutic-Use Class Prediction and Repurposing Using Graph Convolutional Networks
Authors: Chipofya Mapopa , Tayara Hilal , Chong Kil To
Published: November 2021

An important stage in the process of discovering new drugs is when candidate molecules are tested of their efficacy. It is reported that testing drug efficacy empirically costs billions of dollars in the drug discovery pipeline. As a mechanism of expediting this process, researchers have resorted to using computational methods to predict the action of molecules in silico. Here, we present a way of predicting the therapeutic-use class of drugs from chemical structures only using graph convolutional networks. In comparison with existing methods which use fingerprints or images as training samples, our approach has yielded better results in all metrics under consideration. In particular, validation accuracy increased from 83–88% to 86–90% for single label tasks. Similarly, the model achieved an accuracy of over 88% on new test data. Finally, our multi-label classification model made new predictions which indicated that some of the drugs could have other therapeutic uses other than those indicated in the dataset. We performed a literature-based evaluation of these predictions and found evidence that validates them. This renders the model a potential tool to be used in search of drugs that are candidates for repurposing.
The Potential Use of Isothermal Amplification Assays for In-Field Diagnostics of Plant Pathogens
Authors: Ivanov Aleksandr V. , Safenkova Irina V. , Zherdev Anatoly V. , Dzantiev Boris B.
Published: November 2021

Rapid, sensitive, and timely diagnostics are essential for protecting plants from pathogens. Commonly, PCR techniques are used in laboratories for highly sensitive detection of DNA/RNA from viral, viroid, bacterial, and fungal pathogens of plants. However, using PCR-based methods for in-field diagnostics is a challenge and sometimes nearly impossible. With the advent of isothermal amplification methods, which provide amplification of nucleic acids at a certain temperature and do not require thermocyclic equipment, going beyond the laboratory has become a reality for molecular diagnostics. The amplification stage ceases to be limited by time and instruments. Challenges to solve involve finding suitable approaches for rapid and user-friendly plant preparation and detection of amplicons after amplification. Here, we summarize approaches for in-field diagnostics of phytopathogens based on different types of isothermal amplification and discuss their advantages and disadvantages. In this review, we consider a combination of isothermal amplification methods with extraction and detection methods compatible with in-field phytodiagnostics. Molecular diagnostics in out-of-lab conditions are of particular importance for protecting against viral, bacterial, and fungal phytopathogens in order to quickly prevent and control the spread of disease. We believe that the development of rapid, sensitive, and equipment-free nucleic acid detection methods is the future of phytodiagnostics, and its benefits are already visible.
Effects of Edible Coating and Modified Atmosphere Technology on the Physiology and Quality of Mangoes after Low-Temperature Transportation at 13 °C in Vibration Mitigation Packaging
Authors: Wei Saichao , Mei Jun , Xie Jing
Published: November 2021

The mango is an important tropical fruit in the world, but it is easily perishable after harvest. In order to investigate the effect of the compound preservation technology on the physiology and quality of mangoes during transportation and storage, mangoes were treated with different packaging and preservation methods. All mangoes were subjected to simulated transportation by a vibration table for 24 h (180 r/min, 13 °C), and stored at 13 °C. The changes in the color, physicochemical characteristics, quality, and antioxidant-related enzymes of the mangoes were measured. The results show that the shelf life of inflatable bag packing (CK) was only 24 d, while the other treatments could be 30 d. The inflatable bag packing with modified atmosphere packaging (MAP) treatment (HPM) had the lowest yellowing degree (12.5%), disease index (34.4%), and mass loss (2.95%), at 30 d. Compared with the CK, the compound treatment containing MAP prolonged the peak respiration of the mangoes by 6 d and suppressed the increase in the total soluble solids and relative conductivity. Meanwhile, the HPM could effectively maintain moisture content, firmness, titratable acid, vitamin C, and the peroxidase and superoxide dismutase content, indicating that the treatment could maintain the better quality and antioxidation ability of mangoes. In summary, the MAP compound treatment better maintained the commercial characteristics of the mangoes, followed by the edible coating compound treatment. The results provide a theoretical reference for mango cushioning packaging and postharvest storage technology.
First Report of Protective Activity of Paronychia argentea Extract against Tobacco Mosaic Virus Infection
Authors: Abdelkhalek Ahmed , Al-Askar Abdulaziz A. , Alsubaie Maha M. , Behiry Said I.
Published: November 2021

The widespread use of chemical control agents and pesticides for plant-pathogen control has caused many human health and environmental issues. Plant extracts and biocontrol agents have robust antimicrobial activity against different plant pathogens. However, their antiviral activities are still being investigated. In the present study, the methanol extract of Paronychia argentea was characterized and evaluated for its protective activity against the tobacco mosaic virus (TMV) infection in tomato plants under greenhouse conditions at 21 days post-inoculation. The results showed that the foliar application of P. argentea extract (10 µg/mL) enhanced tomato plant growth, resulting in significant increases in shoot and root parameters and total chlorophyll contents. Moreover, a significant reduction in TMV accumulation level in P. argentea-treated plants of 77.88% compared to non-treated plants was reported. Furthermore, induction of systemic resistance with significant elevation in production of antioxidant enzymes (PPO, CAT, and SOD) and transcriptional levels of the pathogenesis-related proteins (PR-1 and PR-7) and polyphenolic genes (CHS and HQT) were also observed. Out of 16 detected compounds, HPLC analysis revealed that the most abundant polyphenolic compounds found in P. argentea extract were gallic acid (5.36 µg/mL), kaempferol (7.39 µg/mL), quercetin (7.44 µg/mL), ellagic acid (7.89 µg/mL), myricetin (8.36 µg/mL), and ferulic acid (8.69 µg/mL). The findings suggest that the use of P. argentea extract as an effective and safe source for the production of bioactive compounds may offer a solution for a promising approach for the management of plant viral infections. To the best of our knowledge, this is the first report of the protective activity of P. argentea extract against plant viral diseases.
Morphological Characterization and DNA Barcoding of Duckweed Species in Saudi Arabia
Authors: Al-Dakhil Mohammed , Alghamdi Salem , Migdadi Hussein , Afzal Muhammad , Ali Ahmed Abdelrahim
Published: November 2021

Duckweeds, or Lemnaceae, are widespread aquatic plants. Morphology-based identification of duckweed species is difficult because of their structural complexity. Hence, molecular tools provide significant advantages for characterizing and selecting species or clones for sustainable commercial use. In this study, we collected and characterized ten duckweed isolates from nine different regions in Saudi Arabia (SA). Based on the morphological characterization and phylogenetic analysis of intergenic spacer sequences of chloroplast DNA using six barcoding markers, the clones were classified into three genera, represented by seven species: Lemna gibba L., Lemna minor L., Lemna japonica Landolt, Lemna aequinoctialis Welw., Lemna perpusilla Torr., Spirodela polyryiza (L.) Schleid., and Landoltia punctate G. Mey. Lemna gibba was revealed to be a distinct dominant duckweed species in many regions of SA. Five barcoding markers showed that L. gibba, L. minor, and L. punctata were the most widely distributed species in the country. However, L. punctata, L. perpusilla, and S. polyryiza were the dominant species in the Al-Qassim, Madinah-1, and Madinah-2 regions, respectively. Moreover, the morphological traits revealed variations for these clones, relative to other studied duckweed clones. According to the results obtained in this study, three out of six plastid markers (trnH-psbA, matK, and atpF-atpH) helped to identify the dominant duckweed species in Saudi Arabia. Further evaluation based on adaptability, molecular genetic studies, and functional genomics is needed for these species to be used at the commercial level in Saudi Arabia.
Bio-Based Epoxy Adhesives with Lignin-Based Aromatic Monophenols Replacing Bisphenol A
Authors: Van de Velde Nigel , Javornik Saška , Sever Tilen , Štular Danaja , Šobak Matic , Štirn Žiga , Likozar Blaž , Jerman Ivan
Published: November 2021

A bio-epoxy surface adhesive for adherence of the metal component species to glass substrate with desirable adhesion strength, converted controlled removal upon request, and bio-based resource inclusion was developed. For the development of resin, three different lignin-based aromatic monophenols, guaiacol, cresol, and vanillin, were used in the chemical epoxidation reaction with epichlorohydrin. The forming transformation process was studied by viscoelasticity, in situ FTIR monitoring, and Raman. Unlike other hydroxyl phenyls, guaiacol showed successful epoxide production, and stability at room temperature. Optimization of epoxide synthesis was conducted by varying NaOH concentration or reaction time. The obtained product was characterized by nuclear magnetic resonance and viscosity measurements. For the production of adhesive, environmentally problematic bisphenol A (BPA) epoxy was partially substituted with the environmentally acceptable, optimized guaiacol-based epoxy at 20, 50, and 80 wt.%. Mechanics, rheological properties, and the possibility of adhered phase de-application were assessed on the bio-substitutes and compared to commercially available polyepoxides or polyurethanes. Considering our aim, the sample composed of 80 wt.% bio-based epoxy/20 wt.% BPA thermoset was demonstrated to be the most suitable among those analyzed, as it was characterized by low BPA, desired boundary area and recoverability using a 10 wt.% acetic acid solution under ultrasound.
Assessing the Economic Viability of the Plastic Biorefinery Concept and Its Contribution to a More Circular Plastic Sector
Authors: Roux Megan , Varrone Cristiano
Published: November 2021

It is widely accepted that plastic waste is one of the most urgent environmental concerns the world is currently facing. The emergence of bio-based plastics provides an opportunity to reduce dependency on fossil fuels and transition to a more circular plastics economy. For polyethylene terephthalate (PET), one of the most prevalent plastics in packaging and textiles, two bio-based alternatives exist that are similar or superior in terms of material properties and recyclability. These are polyethylene furanoate (PEF) and polytrimethylene terephthalate (PTT). The overarching aim of this study was to examine the transition from fossil-based to renewable plastics, through the lens of PET upcycling into PEF and PTT. The process for the production of PEF and PTT from three waste feed streams was developed in the SuperPro Designer software and the economic viability assessed via a discounted cumulative cash flow (DCCF) analysis. A techno-economic analysis of the designed process revealed that the minimum selling price (MSP) of second generation-derived PEF and PTT is 3.13 USD/kg, and that utilities and the feedstock used for the production of 2,5-furandicarboxylic acid (FDCA) needed in PEF synthesis contributed the most to the process operating costs. The effect of recycling PEF and PTT through the process at three recycling rates (42%, 50% and 55%) was investigated and it was revealed that increased recycling could reduce the MSP of the 2G bio-plastics (by 48.5%) to 1.61 USD/kg. This demonstrates that the plastic biorefinery, together with increasing recycling rates, would have a beneficial effect on the economic viability of upcycled plastics.
Anion Exchange Membranes with 1D, 2D and 3D Fillers: A Review
Authors: Narducci Riccardo , Sgreccia Emanuela , Knauth Philippe , Di Vona Maria Luisa
Published: November 2021

Hydroxide exchange membrane fuel cells (AEMFC) are clean energy conversion devices that are an attractive alternative to the more common proton exchange membrane fuel cells (PEMFCs), because they present, among others, the advantage of not using noble metals like platinum as catalysts for the oxygen reduction reaction. The interest in this technology has increased exponentially over the recent years. Unfortunately, the low durability of anion exchange membranes (AEM) in basic conditions limits their use on a large scale. We present in this review composite AEM with one-dimensional, two-dimensional and three-dimensional fillers, an approach commonly used to enhance the fuel cell performance and stability. The most important filler types, which are discussed in this review, are carbon and titanate nanotubes, graphene and graphene oxide, layered double hydroxides, silica and zirconia nanoparticles. The functionalization of the fillers is the most important key to successful property improvement. The recent progress of mechanical properties, ionic conductivity and FC performances of composite AEM is critically reviewed.
Characteristic Tearing Energy and Fatigue Crack Propagation of Filled Natural Rubber
Authors: Rong Jigang , Yang Jun , Huang Youjian , Luo Wenbo , Hu Xiaoling
Published: November 2021

Below the incipient characteristic tearing energy (T0), cracks will not grow in rubber under fatigue loading. Hence, determination of the characteristic tearing energy T0 is very important in the rubber industry. A rubber cutting experiment was conducted to determine the T0, using the cutting method proposed originally by Lake and Yeoh. Then, a fatigue crack propagation experiment on a edge-notched pure shear specimen under variable amplitude loading was studied. A method to obtain the crack propagation rate da/dN from the relationship of the crack propagation length (Δa) with the number of cycles (N) is proposed. Finally, the T0 obtained from the cutting method is compared with the value decided by the fatigue crack propagation experiment. The values of T0 obtained from the two different methods are a little different.
Investigations on Epoxy-Carbamate Foams Modified with Different Flame Retardants for High-Performance Applications
Authors: Kaysser Simon T. , Bethke Christian , Romero Isabel Fernandez , Wei Angeline Wo Weng , Keun Christian A. , Ruckdäschel Holger , Altstädt Volker
Published: November 2021

In transport sectors such as aviation, automotive and railway, materials combining a high lightweight potential with high flame retardant properties are in demand. Polymeric foams are suitable materials as they are lightweight, but often have high flammability. This study focuses on the influence of different flame retardants on the burning behavior of Novolac based epoxy foams using Isophorone Diamine carbamate (B-IPDA) as dual functional curing and blowing agent. The flame retardant properties and possible modifications of these foams are systematically investigated. Multiple flame retardants, representing different flame retardant mechanisms, are used and the effects on the burning behavior as well as mechanical and thermal properties are evaluated. Ammonium polyphosphate (APP), used with a filler degree of 20 wt.% or higher, functions as the best performing flame retardant in this study.
Composited Film of Poly(3,4-ethylenedioxythiophene) and Graphene Oxide as Hole Transport Layer in Perovskite Solar Cells
Authors: Yuan Tian , Li Jin , Wang Shimin
Published: November 2021

It is important to lower the cost and stability of the organic–inorganic hybrid perovskite solar cells (PSCs) for industrial application. The commonly used hole transport materials (HTMs) such as Spiro-OMeTAD, poly[bis(4-phenyl)(2,4,6-trimethylphenyl)amine] (PTAA) and poly(3-hexylthiophene-2,5-diyl) (P3HT) are very expensive. Here, 3,4-ethylenedioxythiophene (EDOT) monomers are in-situ polymerized on the surface of graphene oxide (GO) as PEDOT-GO film. Compared to frequently used polystyrene sulfonic acid (PSS), GO avoids the corrosion of the perovskite and the use of H2O solvent. The composite PEDOT-GO film is between carbon pair electrode and perovskite layer as hole transport layer (HTL). The highest power conversion efficiency (PCE) is 14.09%.
Copolymer Coatings for DNA Biosensors: Effect of Charges and Immobilization Chemistries on Yield, Strength and Kinetics of Hybridization
Authors: Vanjur Luka , Carzaniga Thomas , Casiraghi Luca , Zanchetta Giuliano , Damin Francesco , Sola Laura , Chiari Marcella , Buscaglia Marco
Published: November 2021

The physical–chemical properties of the surface of DNA microarrays and biosensors play a fundamental role in their performance, affecting the signal’s amplitude and the strength and kinetics of binding. We studied how the interaction parameters vary for hybridization of complementary 23-mer DNA, when the probe strands are immobilized on different copolymers, which coat the surface of an optical, label-free biosensor. Copolymers of N, N-dimethylacrylamide bringing either a different type or density of sites for covalent immobilization of DNA probes, or different backbone charges, were used to functionalize the surface of a Reflective Phantom Interface multispot biosensor made of a glass prism with a silicon dioxide antireflective layer. By analyzing the kinetic hybridization curves at different probe surface densities and target concentrations in solution, we found that all the tested coatings displayed a common association kinetics of about 9 × 104 M−1·s−1 at small probe density, decreasing by one order of magnitude close to the surface saturation of probes. In contrast, both the yield of hybridization and the dissociation kinetics, and hence the equilibrium constant, depend on the type of copolymer coating. Nearly doubled signal amplitudes, although equilibrium dissociation constant was as large as 4 nM, were obtained by immobilizing the probe via click chemistry, whereas amine-based immobilization combined with passivation with diamine carrying positive charges granted much slower dissociation kinetics, yielding an equilibrium dissociation constant as low as 0.5 nM. These results offer quantitative criteria for an optimal selection of surface copolymer coatings, depending on the application.
Physical Properties of Thermally Crosslinked Fluorinated Polyimide and Its Application to a Liquid Crystal Alignment Layer
Authors: Ahn Jong-Soo , Park Su Hong , Kwon Na Yeon , Cho Min Ju , Paek Sang-Hyon , Choi Dong Hoon
Published: November 2021

This study demonstrated the use of a thermally crosslinked polyimide (PI) for the liquid crystal (LC) alignment layer of an LC display (LCD) cell. Polyamic acid was prepared using 4,4′-oxydianiline (ODA) and 4,4′-(hexafluoroisopropylidene) diphthalic anhydride (6FDA). The 6FDA−ODA-based polyimide (PI) prepared by the thermal cyclic dehydration of the polyamic acid (PAA) was soluble in various polar solvents. After forming a thin film by mixing trifunctional epoxide [4-(oxiran-2-ylmethoxy)-N,N-bis(oxiran-2-ylmethyl)aniline] with the 6FDA−ODA-based PAA, it was confirmed that thermal curing at −110 °C caused an epoxy ring opening reaction, which could result in the formation of a networked polyimide not soluble in tetrahydrofuran. The crosslinked PI film showed a higher rigidity than the neat PI films, as measured by the elastic modulus. Furthermore, based on a dynamic mechanical analysis of the neat PI and crosslinked PI films, the glass transition temperatures (Tgs) were 217 and 339 °C, respectively, which provided further evidence of the formation of crosslinking by the addition of the epoxy reagent. After mechanical rubbing using these two PI films, an LC cell was fabricated using an anisotropic PI film as an LC alignment film. LC cells with crosslinked PI layers showed a high voltage holding ratio and low residual direct current voltage. This suggests that the crosslinked PI has good potential for use as an LC alignment layer material in advanced LCD technologies that require high performance and reliability.
Fabrication and Characterization of Polymeric Pharmaceutical Emulgel Co-Loaded with Eugenol and Linalool for the Treatment of Trichophyton rubrum Infections
Authors: Akram Muhammad Abdullah , Khan Barkat Ali , Khan Muhammad Khalid , Alqahtani Ali , Alshahrani Sultan M. , Hosny Khaled M.
Published: November 2021

Trichophyton rubrum (T. rubrum) is the main cause of chronic dermatophytosis which is highly prevalent worldwide. This study was aimed to fabricate and characterize polymeric emulgel of eugenol and linalool for the treatment of T. rubrum infections. Using the slow emulsification method, the emulgel was prepared and characterized for thermodynamic stability, pH analysis, viscosity, spreadability, swelling behavior, %drug content, surface morphology, globules size, polydispersity index, surface charge (mV), thermal behavior, in vitro drug release and XRD studies. Biological activities of emulgel were conducted against T. rubrum in vitro and in vivo. Results indicated that emulgel formulations were thermodynamically stable. The pH of the formulations was within an acceptable range for skin. The viscosity and spreadability were optimum for the better patient compliance. The swelling behavior was 111.10 ± 1.25% after 90 min. The drug content was within the official pharmacopeia limit i.e., 100 ± 10%. The surface morphology revealed by scanning electron microscopy showed a spherical-shaped structure with characteristic larger cracks and wrinkles. The droplet size, PDI, and surface charge of the optimized emulgel were 888.45 ± 8.78 nm, 0.44 and −20.30 mV, respectively. The emulgel released 84.32% of eugenol and 76.93% of linalool after 12 h. There was complete disappearance of the diffraction peaks corresponding to the drugs after XRD analysis. In rabbits, the infection was safely and completely recovered after 12 days and the emulgel produced significant effects (p < 0.05) similar to the standard product Clotrim®. It is concluded that the eugenol–linalool emulgel best described all its physical properties and can be applied topically for the treatment of T. rubrum infections.
Study on Selected Metal-Organic Framework-Based Catalysts for Cycloaddition Reaction of CO2 with Epoxides: A Highly Economic Solution for Carbon Capture and Utilization
Authors: Musa Suleiman Gani , Aljunid Merican Zulkifli Merican , Akbarzadeh Omid
Published: November 2021

The level of carbon dioxide in the atmosphere is growing rapidly due to fossil fuel combustion processes, heavy oil, coal, oil shelter, and exhausts from automobiles for energy generation, which lead to depletion of the ozone layer and consequently result in global warming. The realization of a carbon-neutral environment is the main focus of science and academic researchers of today. Several processes were employed to minimize carbon dioxide in the air, some of which include the utilization of non-fossil sources of energy like solar, nuclear, and biomass-based fuels. Consequently, these sources were reported to have a relatively high cost of production and maintenance. The applications of both homogeneous and heterogeneous processes in carbon capture and storage were investigated in recent years and the focus now is on the conversion of CO2 into useful chemicals and compounds. It was established that CO2 can undergo cycloaddition reaction with epoxides under the influence of special catalysts to give cyclic carbonates, which can be used as value-added chemicals at a different level of pharmaceutical and industrial applications. Among the various catalysts studied for this reaction, metal-organic frameworks are now on the frontline as a potential catalyst due to their special features and easy synthesis. Several metal-organic framework (MOF)-based catalysts were studied for their application in transforming CO2 to organic carbonates using epoxides. Here, we report some recent studies of porous MOF materials and an in-depth discussion of two repeatedly used metal-organic frameworks as a catalyst in the conversion of CO2 to organic carbonates.
Proteome of the Luminal Surface of the Blood–Brain Barrier
Authors: Hill Jennifer J. , Haqqani Arsalan S. , Stanimirovic Danica B.
Published: November 2021

Interrogation of the molecular makeup of the blood–brain barrier (BBB) using proteomic techniques has contributed to the cataloguing and functional understanding of the proteins uniquely organized at this specialized interface. The majority of proteomic studies have focused on cellular components of the BBB, including cultured brain endothelial cells (BEC). Detailed proteome mapping of polarized BEC membranes and their intracellular endosomal compartments has led to an improved understanding of the processes leading to internalization and transport of various classes of molecules across the BBB. Quantitative proteomic methods have further enabled absolute and comparative quantification of key BBB transporters and receptors in isolated BEC and microvessels from various species. However, translational studies further require in vivo/in situ analyses of the proteins exposed on the luminal surface of BEC in vessels under various disease and treatment conditions. In vivo proteomics approaches, both profiling and quantitative, usually rely on ‘capturing’ luminally-exposed proteins after perfusion with chemical labeling reagents, followed by analysis with various mass spectrometry-based approaches. This manuscript reviews recent advances in proteomic analyses of luminal membranes of BEC in vitro and in vivo and their applications in translational studies focused on developing novel delivery methods across the BBB.
Causes and Risk Factor of Post-Traumatic Stress Disorder in Adult Asylum Seekers and Refugees
Authors: AlRefaie Abdullah , Dowrick Christopher
Published: November 2021

Objectives: To assess the causes and risk factors of post-traumatic stress disorder (PTSD) in adult asylum seekers and refugees. To explore whether the causes and risk factors of PTSD between male and female adult refugees/asylum seekers are different. Study design: Systematic review of current literature. Data Sources: PubMed, Web of Science, Scopus and Google Scholar up until February 2019. Method: A structured, systematic search was conducted of the relevant databases. Papers were excluded if they failed to meet the inclusion and exclusion criteria. Afterwards, a qualitative assessment was performed on the selected papers. Results: 12 Studies were included for the final analysis. All papers were either case studies/reports or cross-sectional studies. Traumatic events experienced by refugees/asylum seekers are the most frequently reported pre-migration causes of PTSD development, while acculturative stress is the most common post-migration stressor. There were mixed reports regarding the causes of PTSD between both genders of refugees/asylum seekers. Conclusions: This review’s findings have potential clinical application in terms of helping clinicians to risk stratify refugees/asylum seekers for PTSD development and thus aid in embarking on earlier intervention measures. However, more rigorous research similar to this study is needed for it to be implemented into clinical practice.
Struggle on the Axis: The Advance and Retreat of Buddhist Influences in the Political Axis of Capitals in Medieval China (220–907)
Authors: Xie Yifeng
Published: November 2021

Buddhist influences on the sacred axis of the capital during Medieval China (220–907) underwent a process of starting with little impact during the era of Eastern Han, Caowei, and Western Jin (220–317) to a more prominent influence from the late Southern and Northern Dynasties (386–589) to early Tang (618–907), peaked during the reign of Wu Zetian (690–705), and roughly returned to the layout patterns from the late Southern and Northern Dynasties to early Tang after the death of Wu Zetian. As maintained below, the process appears complex in terms of the interaction between Buddhism and political space throughout early Medieval China. There are roughly two modes of integration and interaction between Buddhist buildings and ritual buildings with Buddhist influences and the political axis of the capital: the first mode can be regarded as a typical mode after its establishment in the late Northern Wei Dynasty. This mode exhibits major Buddhist influences, particularly regarding the huge scale of monasteries and pagodas, and the location of high-rise pagodas as landmarks flanking the political axis of the capital. The second mode should be regarded as an atypical mode occurring during the late period of Emperor Wu of the Liang (464–549, r. 502–549), the period of Northern Qi (550–577), and the reign of Wu Zetian. At this point, Buddhist buildings and imperial ritual buildings with Buddhist characteristics and symbolic meanings were placed directly on the political axis of the capital, close to or located at the core of the palace. This practice was a sign that the influence of Buddhism in the political culture and ideology of the entire empire during these eras of Emperor Wu of the Liang, the Northern Qi, and the reign of Wu Zetian had reached their culmination. Architecture reflected the most intuitive embodiment of an external visual form in presenting the most symbolic image of power. With the decline of political enthusiasm for advocating Buddhism, Buddhist and related buildings no longer occupied the political axis of the capital. Various forces majeure such as natural fires, demolition, and reconstruction by subsequent rulers also led to the demise of Buddhist influence on the pollical axis of capital architecture in subsequent eras.
The Disputed Middle Ground: Tibetan Mādhyamikas on How to Interpret Nāgārjuna and Candrakīrti
Authors: Powers John
Published: November 2021

By the twelfth century, a broad consensus had developed among Tibetan Buddhists: The Middle Way School (Madhyamaka) of Nāgārjuna (c. 2nd century), as interpreted by Candrakīrti (c. 600–650), would be normative in Tibet. However, Tibetans had inherited various trajectories of commentary on Madhyamaka, and schools of thought developed, each with a particular reading. This article will examine some of the major competing philosophical stances, focusing on three figures who represent particularly compelling interpretations, but whose understandings of Madhyamaka are profoundly divergent: Daktsang Sherap Rinchen (1405–1477), Wangchuk Dorjé, the 9th Karmapa (1556–1603), and Purchok Ngawang Jampa (1682–1762). The former two contend that Nāgārjuna’s statement “I have no thesis” (nāsti ca mama pratijñā) means exactly what it says, while the latter advocates what could be termed an “anthropological” approach: Mādhyamikas, when speaking as Mādhyamikas, only report what “the world” says, without taking any stance of their own; but their understanding of Buddhism is based on insight gained through intensive meditation training. This article will focus on how these three philosophers figure in the history of Tibetan Madhyamaka exegesis and how their respective readings of Indic texts incorporate elements of previous work while moving interpretation in new directions.
Biomass Valorization: Sustainable Methods for the Production of Hemicellulolytic Catalysts from Thermoanaerobacterium thermostercoris strain BUFF
Authors: Finore Ilaria , Romano Ida , Leone Luigi , Di Donato Paola , Nicolaus Barbara , Poli Annarita , Lama Licia
Published: November 2021

Processing and selection of fruits and vegetables generate high quantities of wastes that represent an economic and environmental issue for the agroindustry sector. According to the so-called “biorefinery” approach, this biomass can be exploited for the recovery of value-added molecules. In this study, the residues of industrial processing of tomato (Lycopersicon esculentum variety “Hybrid Rome”), fennel (Foeniculum vulgare), potato (Solanum tuberosum) and carrot (Daucus carota) were used as sole carbon sources to support cheap and sustainable microbial growth as well as the production of secondary metabolites (hydrogen and ethanol) by Thermoanaerobacterium thermostercoris strain BUFF, a thermophilic anaerobic microorganism isolated from buffalo-dung compost. Moreover, the use of hemicellulolytic enzymes of T. thermostercoris was assayed in the bioconversion reaction of the polymer fraction extracted from the rhizome of giant reed (Arundo donax) and of the leaves and stems of cardoon (Cynara cardunculus), dedicated non-food crops employed in energy supply.
Spatial Downscaling of MODIS Snow Cover Observations Using Sentinel-2 Snow Products
Authors: Revuelto Jesús , Alonso-González Esteban , Gascoin Simon , Rodríguez-López Guillermo , López-Moreno Juan Ignacio
Published: November 2021

Understanding those processes in which snow dynamics has a significant influence requires long-term and high spatio-temporal resolution observations. While new optical space-borne sensors overcome many previous snow cover monitoring limitations, their short temporal length limits their application in climatological studies. This work describes and evaluates a probabilistic spatial downscaling of MODIS snow cover observations in mountain areas. The approach takes advantage of the already available high spatial resolution Sentinel-2 snow observations to obtain a snow probability occurrence, which is then used to determine the snow-covered areas inside partially snow-covered MODIS pixels. The methodology is supported by one main hypothesis: the snow distribution is strongly controlled by the topographic characteristics and this control has a high interannual persistence. Two approaches are proposed to increase the 500 m resolution MODIS snow cover observations to the 20 m grid resolution of Sentinel-2. The first of these computes the probability inside partially snow-covered MODIS pixels by determining the snow occurrence frequency for the 20 m Sentinel-2 pixels when clear-sky conditions occurred for both platforms. The second approach determines the snow probability occurrence for each Sentinel-2 pixel by computing the number of days in which snow was observed on each grid cell and then dividing it by the total number of clear-sky days per grid cell. The methodology was evaluated in three mountain areas in the Iberian Peninsula from 2015 to 2021. The 20 m resolution snow cover maps derived from the two probabilistic methods provide better results than those obtained with MODIS images downscaled to 20 m with a nearest-neighbor method in the three test sites, but the first provides superior performance. The evaluation showed that mean kappa values were at least 10% better for the two probabilistic methods, improving the scores in one of these sites by 25%. In addition, as the Sentinel-2 dataset becomes longer in time, the probabilistic approaches will become more robust, especially in areas where frequent cloud cover resulted in lower accuracy estimates.
Improved Oriented Object Detection in Remote Sensing Images Based on a Three-Point Regression Method
Authors: Wu Falin , He Jiaqi , Zhou Guopeng , Li Haolun , Liu Yushuang , Sui Xiaohong
Published: November 2021

Object detection in remote sensing images plays an important role in both military and civilian remote sensing applications. Objects in remote sensing images are different from those in natural images. They have the characteristics of scale diversity, arbitrary directivity, and dense arrangement, which causes difficulties in object detection. For objects with a large aspect ratio and that are oblique and densely arranged, using an oriented bounding box can help to avoid deleting some correct detection bounding boxes by mistake. The classic rotational region convolutional neural network (R2CNN) has advantages for text detection. However, R2CNN has poor performance in the detection of slender objects with arbitrary directivity in remote sensing images, and its fault tolerance rate is low. In order to solve this problem, this paper proposes an improved R2CNN based on a double detection head structure and a three-point regression method, namely, TPR-R2CNN. The proposed network modifies the original R2CNN network structure by applying a double fully connected (2-fc) detection head and classification fusion. One detection head is for classification and horizontal bounding box regression, the other is for classification and oriented bounding box regression. The three-point regression method (TPR) is proposed for oriented bounding box regression, which determines the positions of the oriented bounding box by regressing the coordinates of the center point and the first two vertices. The proposed network was validated on the DOTA-v1.5 and HRSC2016 datasets, and it achieved a mean average precision (mAP) of 3.90% and 15.27%, respectively, from feature pyramid network (FPN) baselines with a ResNet-50 backbone.
Earthquake Vulnerability Assessment for Urban Areas Using an ANN and Hybrid SWOT-QSPM Model
Authors: Alizadeh Mohsen , Zabihi Hasan , Rezaie Fatemeh , Asadzadeh Asad , Wolf Isabelle D. , Langat Philip K , Khosravi Iman , Beiranvand Pour Amin , Mohammad Nataj Milad , Pradhan Biswajeet
Published: November 2021

Tabriz city in NW Iran is a seismic-prone province with recurring devastating earthquakes that have resulted in heavy casualties and damages. This research developed a new computational framework to investigate four main dimensions of vulnerability (environmental, social, economic and physical). An Artificial Neural Network (ANN) Model and a SWOT-Quantitative Strategic Planning Matrix (QSPM) were applied. Firstly, a literature review was performed to explore indicators with significant impact on aforementioned dimensions of vulnerability to earthquakes. Next, the twenty identified indicators were analyzed in ArcGIS, a geographic information system (GIS) software, to map earthquake vulnerability. After classification and reclassification of the layers, standardized maps were presented as input to a Multilayer Perceptron (MLP) and Self-Organizing Map (SOM) neural network. The resulting Earthquake Vulnerability Maps (EVMs) showed five categories of vulnerability ranging from very high, to high, moderate, low and very low. Accordingly, out of the nine municipality zones in Tabriz city, Zone one was rated as the most vulnerable to earthquakes while Zone seven was rated as the least vulnerable. Vulnerability to earthquakes of residential buildings was also identified. To validate the results data were compared between a Multilayer Perceptron (MLP) and a Self-Organizing Map (SOM). The scatter plots showed strong correlations between the vulnerability ratings of the different zones achieved by the SOM and MLP. Finally, the hybrid SWOT-QSPM paradigm was proposed to identify and evaluate strategies for hazard mitigation of the most vulnerable zone. For hazard mitigation in this zone we recommend to diligently account for environmental phenomena in designing and locating of sites. The findings are useful for decision makers and government authorities to reconsider current natural disaster management strategies.
Learning to Identify Illegal Landfills through Scene Classification in Aerial Images
Authors: Torres Rocio Nahime , Fraternali Piero
Published: November 2021

Illegal landfills are uncontrolled disposals of waste that cause severe environmental and health risk. Discovering them as early as possible is of prominent importance for preventing hazards, such as fire pollution and leakage. Before the digital era, the only means to detect illegal waste dumps was the on site inspection of potentially suspicious sites, a procedure extremely costly and impossible to scale to a vast territory. With the advent of Earth observation technology, scanning the territory via aerial images has become possible. However, manual image interpretation remains a complex and time-consuming task that requires expert skill. Photo interpretation can be partially automated by embedding the expert knowledge within a data driven classifier trained with samples provided by human annotators. In this paper, the detection of illegal landfills is formulated as a multi-scale scene classification problem. Scene elements positioning and spatial relations constitute hints of the presence of illegal waste dumps. A dataset of ≈3000 images (20 cm resolution per pixel) was created with the help of expert photo interpreters. A combination of ResNet50 and Feature Pyramid Network (FPN) elements accounting for different object scales achieves 88% precision with an 87% of recall in a test area. The results proved the feasibility of applying convolutional neural networks for scene classification in this scenario to optimize the process of waste dumps detection.
A Meta-Learning Approach of Optimisation for Spatial Prediction of Landslides
Authors: Pradhan Biswajeet , Sameen Maher Ibrahim , Al-Najjar Husam A. H. , Sheng Daichao , Alamri Abdullah M. , Park Hyuck-Jin
Published: November 2021

Optimisation plays a key role in the application of machine learning in the spatial prediction of landslides. The common practice in optimising landslide prediction models is to search for optimal/suboptimal hyperparameter values in a number of predetermined hyperparameter configurations based on an objective function, i.e., k-fold cross-validation accuracy. However, the overhead of hyperparameter optimisation can be prohibitive, especially for computationally expensive algorithms. This paper introduces an optimisation approach based on meta-learning for the spatial prediction of landslides. The proposed approach is tested in a dense tropical forested area of Cameron Highlands, Malaysia. Instead of optimising prediction models with a large number of hyperparameter configurations, the proposed approach begins with promising configurations based on several basic and statistical meta-features. The proposed meta-learning approach was tested based on Bayesian optimisation as a hyperparameter tuning algorithm and random forest (RF) as a prediction model. The spatial database was established with a total of 63 historical landslides and 15 conditioning factors. Three RF models were constructed based on (1) default parameters as suggested by the sklearn library, (2) parameters suggested by the Bayesian optimisation (BO), and (3) parameters suggested by the proposed meta-learning approach (BO-ML). Based on five-fold cross-validation accuracy, the Bayesian method achieved the best performance for both the training (0.810) and test (0.802) datasets. The meta-learning approach achieved slightly lower accuracies than the Bayesian method for the training (0.769) and test (0.800) datasets. Similarly, based on F1-score and area under the receiving operating characteristic curves (AUROC), the models with optimised parameters either by the Bayesian or meta-learning methods produced more accurate landslide susceptibility assessment than the model with the default parameters. In the present approach, instead of learning from scratch, the meta-learning would begin with hyperparameter configurations optimal for the most similar previous datasets, which can be considerably helpful and time-saving for landslide modelings.