bluuebunny/crossref_metadata_2025 huggingface dataset:
Restoration of the Phenotype of Dedifferentiated Rabbit Chondrocytes by Sesquiterpene Farnesol
Authors: Wu Guan-Xuan , Chen Chun-Yu , Wu Chun-Shien , Hwang Lain-Chyr , Yang Shan-Wei , Kuo Shyh-Ming
Published: January 2022

Osteoarthritis (OA) is a joint disorder characterized by the progressive degeneration of articular cartilage. The phenotype and metabolism behavior of chondrocytes plays crucial roles in maintaining articular cartilage function. Chondrocytes dedifferentiate and lose their cartilage phenotype after successive subcultures or inflammation and synthesize collagen I and X (COL I and COL X). Farnesol, a sesquiterpene compound, has an anti-inflammatory effect and promotes collagen synthesis. However, its potent restoration effects on differentiated chondrocytes have seldom been evaluated. The presented study investigated farnesol’s effect on phenotype restoration by examining collagen and glycosaminoglycan (GAG) synthesis from dedifferentiated chondrocytes. The results indicated that chondrocytes gradually dedifferentiated through cellular morphology change, reduced expressions of COL II and SOX9, increased the expression of COL X and diminished GAG synthesis during four passages of subcultures. Pure farnesol and hyaluronan-encapsulated farnesol nanoparticles promote COL II synthesis. GAG synthesis significantly increased 2.5-fold after a farnesol treatment of dedifferentiated chondrocytes, indicating the restoration of chondrocyte functions. In addition, farnesol drastically increased the synthesis of COL II (2.5-fold) and GAG (15-fold) on interleukin-1β-induced dedifferentiated chondrocytes. A significant reduction of COL I, COL X and proinflammatory cytokine prostaglandin E2 was observed. In summary, farnesol may serve as a therapeutic agent in OA treatment.
The Compound (E)-2-Cyano-N,3-diphenylacrylamide (JMPR-01): A Potential Drug for Treatment of Inflammatory Diseases
Authors: da Silva Pablo Rayff , do Espírito Santo Renan Fernandes , Melo Camila de Oliveira , Pachú Cavalcante Fábio Emanuel , Costa Thássia Borges , Barbosa Yasmim Vilarim , e Silva Yvnni M. S. de Medeiros , de Sousa Natália Ferreira , Villarreal Cristiane Flora , de Moura Ricardo Olímpio , dos Santos Vanda Lucia
Published: January 2022

The compound (E)-2-cyano-N,3-diphenylacrylamide (JMPR-01) was structurally developed using bioisosteric modifications of a hybrid prototype as formed from fragments of indomethacin and paracetamol. Initially, in vitro assays were performed to determine cell viability (in macrophage cultures), and its ability to modulate the synthesis of nitrite and cytokines (IL-1β and TNFα) in non-cytotoxic concentrations. In vivo, anti-inflammatory activity was explored using the CFA-induced paw edema and zymosan-induced peritonitis models. To investigate possible molecular targets, molecular docking was performed with the following crystallographic structures: LT-A4-H, PDE4B, COX-2, 5-LOX, and iNOS. As results, we observed a significant reduction in the production of nitrite and IL-1β at all concentrations used, and also for TNFα with JMPR-01 at 50 and 25 μM. The anti-edematogenic activity of JMPR-01 (100 mg/kg) was significant, reducing edema at 2–6 h, similar to the dexamethasone control. In induced peritonitis, JMPR-01 reduced leukocyte migration by 61.8, 68.5, and 90.5% at respective doses of 5, 10, and 50 mg/kg. In silico, JMPR-01 presented satisfactory coupling; mainly with LT-A4-H, PDE4B, and iNOS. These preliminary results demonstrate the strong potential of JMPR-01 to become a drug for the treatment of inflammatory diseases.
High-Flexibility Control of Structured Light with Combined Adaptive Optical Systems
Authors: Grunwald Ruediger , Jurke Mathias , Bock Martin , Liebmann Max , Bruno Binal Poyyathuruthy , Gowda Hitesh , Wallrabe Ulrike
Published: January 2022

Combining the specific advantages of high-resolution liquid-crystal-on-silicon spatial light modulators (LCoS-SLMs) and reflective or refractive micro-electro-mechanical systems (MEMS) presents new prospects for the generation of structured light fields. In particular, adaptive self-apodization schemes can significantly reduce diffraction by low-loss spatial filtering. The concept enables one to realize low-dispersion shaping of nondiffracting femtosecond wavepackets and to temporally switch, modulate or deflect spatially structured beams. Adaptive diffraction management by structured illumination is demonstrated for piezo-based and thermally actuated axicons, spiral phase plates (SPPs) and Fresnel bi-mirrors. Improved non-collinear autocorrelation with angular-tunable Fresnel-bi-mirrors via self-apodized illumination and phase contrast of an SLM is proposed. An extension of the recently introduced nondiffractive Talbot effect to a tunable configuration by combining an SLM and a fluid lens is reported. Experimental results for hexagonal as well as orthogonal array beams are presented.
Metabolic and Physiological Regulation of Aspartic Acid-Mediated Enhancement of Heat Stress Tolerance in Perennial Ryegrass
Authors: Lei Shuhan , Rossi Stephanie , Huang Bingru
Published: January 2022

Aspartate is the most critical amino acid in the aspartate metabolic pathway, which is associated with multiple metabolic pathways, such as protein synthesis, nucleotide metabolism, TCA cycle, glycolysis, and hormone biosynthesis. Aspartate also plays an important role in plant resistance to abiotic stress, such as cold stress, drought stress, salt stress or heavy metal stress. This study found that the chlorophyll content and antioxidant active enzyme content (SOD, CAT, POD and APX) of perennial ryegrass treated with 2 mM aspartate were significantly higher than those treated with water under heat stress. The electrolyte leakage rate, MDA content and peroxide levels (O2− and H2O2) of perennial ryegrass treated with aspartate were significantly lower than those of perennial ryegrass treated with water, indicating that exogenous aspartate increases the content of chlorophyll, maintain the integrity of cell membrane system, and enhances SOD-CAT antioxidant pathway to eliminate the oxidative damage caused by ROS in perennial ryegrass under heat stress. Furthermore, exogenous aspartate could enhance the TCA cycle, the metabolism of the amino acids related to the TCA cycle, and pyrimidine metabolism to enhance the heat tolerance of perennial ryegrass.
Viruses Infecting Trees and Herbs That Produce Edible Fleshy Fruits with a Prominent Value in the Global Market: An Evolutionary Perspective
Authors: Rodríguez-Verástegui Lizette Liliana , Ramírez-Zavaleta Candy Yuriria , Capilla-Hernández María Fernanda , Gregorio-Jorge Josefat
Published: January 2022

Trees and herbs that produce fruits represent the most valuable agricultural food commodities in the world. However, the yield of these crops is not fully achieved due to biotic factors such as bacteria, fungi, and viruses. Viruses are capable of causing alterations in plant growth and development, thereby impacting the yield of their hosts significantly. In this work, we first compiled the world′s most comprehensive list of known edible fruits that fits our definition. Then, plant viruses infecting those trees and herbs that produce fruits with commercial importance in the global market were identified. The identified plant viruses belong to 30 families, most of them containing single-stranded RNA genomes. Importantly, we show the overall picture of the host range for some virus families following an evolutionary approach. Further, the current knowledge about plant-virus interactions, focusing on the main disorders they cause, as well as yield losses, is summarized. Additionally, since accurate diagnosis methods are of pivotal importance for viral diseases control, the current and emerging technologies for the detection of these plant pathogens are described. Finally, the most promising strategies employed to control viral diseases in the field are presented, focusing on solutions that are long-lasting.
Characterization of Possible α-Glucosidase Inhibitors from Trigonella stellata Extract Using LC–MS and In Silico Molecular Docking
Authors: Elwekeel Ahlam , El Amir Dalia , Mohamed Enas I. A. , Amin Elham , Hassan Marwa H. A. , Zaki Mohamed A.
Published: January 2022

The current study accentuates the significance of performing the multiplex approach of LC-HRESIMS, biological activity, and docking studies in drug discovery, taking into consideration a review of the literature. In this regard, the investigation of antioxidant and cytotoxic activities of Trigonella stellata collected from the Egyptian desert revealed a significant antioxidant capacity using DPPH with IC50 = 656.9 µg/mL and a moderate cytotoxicity against HepG2, MCF7, and CACO2, with IC50 values of 53.3, 48.3, and 55.8 µg/mL, respectively. The evaluation of total phenolic and flavonoid contents resulted in 32.8 mg GAE/g calculated as gallic acid equivalent and 5.6 mg RE/g calculated as rutin equivalent, respectively. Chemical profiling of T. stellata extract, using LC-HRESIMS analysis, revealed the presence of 15 metabolites, among which eleven compounds were detected for the first time in this species. Interestingly, in vitro testing of the antidiabetic activity of the alcoholic extract noted an α-glucosidase enzyme inhibitory activity (IC50 = 559.4 µg/mL) better than that of the standard Acarbose (IC50 = 799.9 µg/mL), in addition to a moderate inhibition of the α-amylase enzyme (IC50 = 0.77 µg/mL) compared to Acarbose (IC50 = 0.21 µg/mL). α-Glucosidase inhibition was also virtualized by binding interactions through the molecular docking study, presenting a high binding activity of six flavonoid glycosides, as well as the diterpenoid compound graecumoside A and the alkaloid fenugreekine. Taken together, the conglomeration of LC-HRESIMS, antidiabetic activity, and molecular docking studies shed light on T. stellata as a promising antidiabetic herb.
Experimental Investigation of Unconfined Compression Strength and Microstructure Characteristics of Slag and Fly Ash-Based Geopolymer Stabilized Riverside Soft Soil
Authors: Luo Zhengdong , Luo Biao , Zhao Yufei , Li Xinyu , Su Yonghua , Huang He , Wang Qian
Published: January 2022

To solve the issues of insufficient early strength of cement stabilized soil and high resource cost, high reduction cost, and high environmental cost induced by the application of cement, the slag and fly ash-based geopolymer was adopted as the stabilizer to treat riverside soft soil. This study mainly investigated the effects of stabilizer content, slag-to-fly ash ratio, and alkaline activator content on the strength of geopolymer stabilized soils with different curing ages. Unconfined compressive strength (UCS), scanning electron microscope (SEM), and X-ray energy spectrum analysis (EDS) tests were carried out. The results show that the stabilizer content, slag–fly ash ratio, and alkaline activator content have a decisive influence on the UCS of geopolymer-stabilized soil. The mix-proportions scheme of geopolymer stabilized riverside soft soil, with a geopolymer content of 15%, a slag–fly ash ratio of 80:20, and an alkaline activator content of 30%, is considered optimum. It is proven by SEM that the uniformly distributed gelatinous products formed in the geopolymer-stabilized soil bind the soil particles tightly. Moreover, the EDS analysis confirms that the gelatinous products are mainly composed of C-S-H gel and sodium-based aluminosilicate (N-A-S-H).
Antimicrobial Food Packaging Based on Prodigiosin-Incorporated Double-Layered Bacterial Cellulose and Chitosan Composites
Authors: Amorim Lúcia F. A. , Mouro Cláudia , Riool Martijn , Gouveia Isabel C.
Published: January 2022

Nowadays, food packaging systems have shifted from a passive to an active role in which the incorporation of antimicrobial compounds into biopolymers can promote a sustainable way to reduce food spoilage and its environmental impact. Accordingly, composite materials based on oxidized-bacterial cellulose (BC) and poly(vinyl alcohol)-chitosan (PVA-CH) nanofibers were produced by needleless electrospinning and functionalized with the bacterial pigment prodigiosin (PG). Two strategies were explored, in the first approach PG was incorporated in the electrospun PVA-CH layer, and TEMPO-oxidized BC was the substrate for nanofibers deposition (BC/PVA-CH_PG composite). In the second approach, TEMPO-oxidized BC was functionalized with PG, and afterward, the PVA-CH layer was electrospun (BC_PG/PVA-CH composite). The double-layer composites obtained were characterized and the nanofibrous layers displayed smooth fibers with average diameters of 139.63 ± 65.52 nm and 140.17 ± 57.04 nm, with and without pigment incorporation, respectively. FTIR-ATR analysis confirmed BC oxidation and revealed increased intensity at specific wavelengths, after pigment incorporation. Moreover, the moderate hydrophilic behavior, as well as the high porosity exhibited by each layer, remained mostly unaffected after PG incorporation. The composites’ mechanical performance and the water vapor transmission rate (WVTR) evaluation indicated the suitability of the materials for certain food packaging solutions, especially for fresh products. Additionally, the red color provided by the bacterial pigment PG on the external surface of a food packaging material is also a desirable effect, to attract the consumers’ attention, creating a multifunctional material. Furthermore, the antimicrobial activity was evaluated and, PVA-CH_PG, and BC_PG layers exhibited the highest antimicrobial activity against Staphylococcus aureus and Pseudomonas aeruginosa. Thus, the fabricated composites can be considered for application in active food packaging, owing to PG antimicrobial potential, to prevent foodborne pathogens (with PG incorporated into the inner layer of the food packaging material, BC/PVA-CH_PG composite), but also to prevent external contamination, by tackling the exterior of food packaging materials (with PG added to the outer layer, BC_PG/PVA-CH composite).
Taking Advantage of Phosphate Functionalized Waterborne Acrylic Binders to Get Rid of Inhibitors in Direct-to-Metal Paints
Authors: Chimenti Stefano , Cerra Marco , Zanetta Tito , Leiza Jose Ramon , Paulis María
Published: January 2022

In this paper, two phosphate functionalized acrylic binders are formulated to yield direct-to-metal paints without using corrosion inhibitors. The difference between both binders is the addition of polystearylacrylate crystalline nanodomains in one of them, and an amorphous methyl methacylate-co-butyl acrylate copolymer in the other. The water sensitivity, mechanical stability, adhesion, and the performance of the paints against corrosion (high humidity resistance, accelerated weathering, and salt-spray tests) are assessed and compared with a DTM paint formulated from a commercial binder. The performance of both phosphate functionalized paints formulated without corrosion inhibitors in high humidity and weathering tests is superior to the commercial DTM paint formulated without corrosion inhibitors and similar to the DTM paint formulated with them. Furthermore, the paint based on the amorphous copolymer binder provides significantly good performance in the salt spray test (even superior to that of the DTM paint formulated with corrosion inhibitors).
Fabrication of Nanofibers Based on Hydroxypropyl Starch/Polyurethane Loaded with the Biosynthesized Silver Nanoparticles for the Treatment of Pathogenic Microbes in Wounds
Authors: El-Hefnawy Mohamed , Alhayyani Sultan , El-Sherbiny Mohsen , Sakran Mohamed , El-Newehy Mohamed
Published: January 2022

Fabrication of electrospun nanofibers based on the blending of modified natural polymer, hydroxyl propyl starch (HPS) as one of the most renewable resources, with synthetic polymers, such as polyurethane (PU) is of great potential for biomedical applications. The as-prepared nanofibers were used as antimicrobial sheets via blending with biosynthesized silver nanoparticles (AgNPs), which were prepared in a safe way with low cost using the extract of Nerium oleander leaves, which acted as a reducing and stabilizing agent as well. The biosynthesized AgNPs were fully characterized by various techniques (UV-vis, TEM, DLS, zeta potential and XRD). The obtained results from UV-vis depicted that the AgNPs appeared at a wavelength equal to 404 nm affirming the preparation of AgNPs when compared with the wavelength of extract (there are no observable peaks). The average particle size of the fabricated AgNPs that mediated with HPS exhibited a very small size (less than 5 nm) with excellent stability (more than −30 mv). In addition, the fabricated nanofibers were also fully characterized and the obtained data proved that the diameter of nanofibers was enlarged with increasing the concentration of AgNPs. Additionally, the findings illustrated that the pore sizes of electrospun sheets were in the range of 75 to 350 nm. The obtained results proved that the presence of HPS displayed a vital role in decreasing the contact angle of PU nanofibers and thus, increased the hydrophilicity of the net nanofibers. It is worthy to mention that the prepared nanofibers incorporated with AgNPs exhibited incredible antimicrobial activity against pathogenic microbes that actually presented in human wounds. Moreover, P. aeruginosa was the most sensitive species to the fabricated nanofibers compared to other tested ones. The minimal inhibitory concentrations (MICs) values of AgNPs-3@NFs against P. aeruginosa, and E. faecalis, were 250 and 500 mg/L within 15 min, respectively.
Solar Desalination Driven by Organic Rankine Cycles (Orc) and Supercritical CO2 Power Cycles: An Update
Authors: Delgado-Torres Agustín M. , García-Rodríguez Lourdes
Published: January 2022

In the field of desalination powered by renewable energies, the use of solar power cycles exhibits some favorable characteristics, such as the possibility of implementing thermal energy storage systems or a multi-generation scheme (e.g., electricity, water, cooling, hydrogen). This article presents a review of the latest design proposals in which two power cycles of great potential are considered: the organic Rankine cycle and the supercritical CO2 power cycle, the latter of growing interest in recent years. The designs found in the literature are grouped into three main types of systems. In the case of solar ORC-based systems, the option of reverse osmosis as a desalination technology is considered in medium-temperature solar systems with storage but also with low-temperature using solar ponds. In the first case, it is also common to incorporate single-effect absorption systems for cooling production. The use of thermal desalination processes is also found in many proposals based on solar ORC. In this case, the usual configuration implies the cycle’s cooling by the own desalination process. This option is also common in systems based on the supercritical CO2 power cycle where MED technology is usually selected. Designs proposals are reviewed and assessed to point out design recommendations.
Solar Carbo-Thermal and Methano-Thermal Reduction of MgO and ZnO for Metallic Powder and Syngas Production by Green Extractive Metallurgy
Authors: Chuayboon Srirat , Abanades Stéphane
Published: January 2022

The solar carbo-thermal and methano-thermal reduction of both MgO and ZnO were performed in a flexible solar reactor operated at low pressure through both batch and continuous operations. The pyro-metallurgical process is an attractive sustainable pathway to convert and store concentrated solar energy into high-value metal commodities and fuels. Substituting fossil fuel combustion with solar energy when providing high-temperature process heat is a relevant option for green extractive metallurgy. In this study, a thermodynamic equilibrium analysis was first performed to compare the thermochemical reduction of MgO and ZnO with solid carbon or gaseous methane, and to determine the product distribution as a function of the operating conditions. The carbo-thermal and methano-thermal reduction of the MgO and ZnO volatile oxides was then experimentally assessed and compared using a directly irradiated cavity-type solar reactor under different operating conditions, varying the type of carbon-based reducing agent (either solid carbon or methane), temperature (in the range 765–1167 °C for ZnO and 991–1550 °C for MgO), total pressure (including both reduced 0.10–0.15 bar and atmospheric ~0.90 bar pressures), and processing mode (batch and continuous operations). The carbo-thermal and methano-thermal reduction reactions yielded gaseous metal species (Mg and Zn) which were recovered at the reactor outlet as fine and reactive metal powders. Reducing the total pressure favored the conversion of both MgO and ZnO and increased the yields of Mg and Zn. However, a decrease in the total pressure also promoted CO2 production because of a shortened gas residence time, especially in the case of ZnO reduction, whereas CO2 formation was negligible in the case of MgO reduction, whatever the conditions. Continuous reactant co-feeding (corresponding to the mixture of metal oxide and carbon or methane) was also performed during the solar reactor operation, revealing an increase in both gas production yields and reaction extent while increasing the reactant feeding rate. The type of carbon reducer influenced the reaction extent, since a higher conversion of both MgO and ZnO was reached when using carbon with a highly available specific surface area for the reactions. The continuous solar process yielded high-purity magnesium and zinc content in the solar-produced metallic powders, thus confirming the reliability, flexibility, and robustness of the solar reactor and demonstrating a promising solar metallurgical process for the clean conversion of both metal oxides and concentrated solar light to value-added chemicals.
Hydrogen Production from Biomass and Organic Waste Using Dark Fermentation: An Analysis of Literature Data on the Effect of Operating Parameters on Process Performance
Authors: Moussa Rita Noelle , Moussa Najah , Dionisi Davide
Published: January 2022

In the context of hydrogen production from biomass or organic waste with dark fermentation, this study analysed 55 studies (339 experiments) in the literature looking for the effect of operating parameters on the process performance of dark fermentation. The effect of substrate concentration, pH, temperature, and residence time on hydrogen yield, productivity, and content in the biogas was analysed. In addition, a linear regression model was developed to also account for the effect of nature and pretreatment of the substrate, inhibition of methanogenesis, and continuous or batch operating mode. The analysis showed that the hydrogen yield was mainly affected by pH and residence time, with the highest yields obtained for low pH and short residence time. High hydrogen productivity was favoured by high feed concentration, short residence time, and low pH. More modest was the effect on the hydrogen content. The mean values of hydrogen yield, productivity, and content were, respectively, 6.49% COD COD−1, 135 mg L−1 d−1, 51% v/v, while 10% of the considered experiments obtained yield, productivity, and content of or higher than 15.55% COD COD−1, 305.16 mg L−1 d−1, 64% v/v. Overall, this study provides insight into how to select the optimum operating conditions to obtain the desired hydrogen production.
Optimization Analysis of Locomotive Diesel Engine Intake System Based on Matlab-Simulink and GT-Power
Authors: Jiang Feng , Cao Wentong , Tan Xueyou , Hu Jie , Zhou Junming , Tan Zedan
Published: January 2022

In this paper, based on the coupling calculation of Simulink software and GT-Power software, an Optimizer model method was proposed for a 16V265H diesel engine to study the effects of different ratios of biodiesel (B0, B10, and B20) on the performance of a 16V265H diesel engine at 1000 rpm and 75% load. Firstly, the four parameters of diesel engine power, BSFC, soot emission, and NOx emission were taken as the result variables of the optimization model. Taking the intake and exhaust timing of the diesel engine as the independent variable of the optimization model, the maximum power, minimum BSFC, and minimum diesel engine emission were studied and analyzed. Finally, the performance parameters were comprehensively analyzed to determine the best intake and exhaust valve timing. Moreover, based on the model optimization, the diesel engine’s BSFC and power performance were compared, and the optimal intake timing scheme for the diesel engine with different biodiesel ratios at 75% operating conditions was obtained. The results showed that the maximum power, optimum BSFC, and minimum emissions of the 16V265H diesel engine with different ratios of biodiesel and different intake valve timing angles were also different. Under 75% load conditions, the BSFC reduction rate was up to 6.32%, and the power increase rate was up to 5.87%. In addition, by optimizing the model with B10 biodiesel and the intake valve timing close to 202°CA and the exhaust valve timing close to 98°CA, the diesel engine had the lowest NOx emission; with B10 biodiesel and the intake timing at 180°CA, the diesel engine had the lowest BSFC; and with B10 biodiesel and the intake valve timing close to 179.5°CA, the diesel engine had the maximum power. In conclusion, the diesel engine is best with B10 biodiesel. This research method can provide a reference for implementing variable intake system technology for the 16V265H diesel engine.
Application of Various Machine Learning Models for Process Stability of Bio-Electrochemical Anaerobic Digestion
Authors: Cheon Ain , Sung Jwakyung , Jun Hangbae , Jang Heewon , Kim Minji , Park Jungyu
Published: January 2022

The application of a machine learning (ML) model to bio-electrochemical anaerobic digestion (BEAD) is a future-oriented approach for improving process stability by predicting performances that have nonlinear relationships with various operational parameters. Five ML models, which included tree-, regression-, and neural network-based algorithms, were applied to predict the methane yield in BEAD reactor. The results showed that various 1-step ahead ML models, which utilized prior data of BEAD performances, could enhance prediction accuracy. In addition, 1-step ahead with retraining algorithm could improve prediction accuracy by 37.3% compared with the conventional multi-step ahead algorithm. The improvement was particularly noteworthy in tree- and regression-based ML models. Moreover, 1-step ahead with retraining algorithm showed high potential of achieving efficient prediction using pH as a single input data, which is plausibly an easier monitoring parameter compared with the other parameters required in bioprocess models.
Standard Flow Multiplexed Proteomics (SFloMPro)—An Accessible Alternative to NanoFlow Based Shotgun Proteomics
Authors: Orsburn Benjamin C. , Miller Sierra D. , Jenkins Conor J.
Published: January 2022

Multiplexed proteomics using isobaric tagging allows for simultaneously comparing the proteomes of multiple samples. In this technique, digested peptides from each sample are labeled with a chemical tag prior to pooling sample for LC-MS/MS with nanoflow chromatography (NanoLC). The isobaric nature of the tag prevents deconvolution of samples until fragmentation liberates the isotopically labeled reporter ions. To ensure efficient peptide labeling, large concentrations of labeling reagents are included in the reagent kits to allow scientists to use high ratios of chemical label per peptide. The increasing speed and sensitivity of mass spectrometers has reduced the peptide concentration required for analysis, leading to most of the label or labeled sample to be discarded. In conjunction, improvements in the speed of sample loading, reliable pump pressure, and stable gradient construction of analytical flow HPLCs has continued to improve the sample delivery process to the mass spectrometer. In this study we describe a method for performing multiplexed proteomics without the use of NanoLC by using offline fractionation of labeled peptides followed by rapid “standard flow” HPLC gradient LC-MS/MS. Standard Flow Multiplexed Proteomics (SFloMPro) enables high coverage quantitative proteomics of up to 16 mammalian samples in about 24 h. In this study, we compare NanoLC and SFloMPro analysis of fractionated samples. Our results demonstrate that comparable data is obtained by injecting 20 µg of labeled peptides per fraction with SFloMPro, compared to 1 µg per fraction with NanoLC. We conclude that, for experiments where protein concentration is not strictly limited, SFloMPro is a competitive approach to traditional NanoLC workflows with improved up-time, reliability and at a lower relative cost per sample.
Potential Tear Biomarkers for the Diagnosis of Parkinson’s Disease—A Pilot Study
Authors: Acera Arantxa , Gómez-Esteban Juan Carlos , Murueta-Goyena Ane , Galdos Marta , Azkargorta Mikel , Elortza Felix , Ruzafa Noelia , Ibarrondo Oliver , Pereiro Xandra , Vecino Elena
Published: January 2022

Parkinson’s disease (PD) is the second most common neurodegenerative disease after Alzheimer’s disease. In this study, the tear proteome profile of patients with idiopathic PD (iPD, n = 24), carriers of the E46K-SNCA mutation (n = 3) and healthy control (CT, n = 27) subjects was analyzed to identify candidate biomarkers for the diagnosis of PD. An observational, prospective and case-control pilot study was carried out, analyzing the participants tear samples by nano-liquid chromatography–mass spectrometry (nLC–MS/MS) and assessing their neurological impairment. The proteomic data obtained are available at ProteomeXchange with identifier 10.6019/PXD028811. These analyses led to the identification of 560 tear proteins, some of which were deregulated in PD patients and that have been implicated in immune responses, inflammation, apoptosis, collagen degradation, protein synthesis, defense, lipid transport and altered lysosomal function. Of these proteins, six were related to neurodegenerative processes and showed a good capacity to classify patients and controls. These findings revealed that certain proteins were upregulated in the tears of PD patients, mainly proteins involved in lysosomal function. Thus, in this study, tear proteins were identified that are implicated in neurodegeneration and that may be related to an aggressive disease phenotype in PD patients.
The German Uranium Miners’ Biobank—A Biobank for OMICs Radiation Research
Authors: Gomolka Maria , Bucher Martin , Duchrow Lukas , Hochstrat Beate , Taeger Dirk , Johnen Georg , Moertl Simone
Published: January 2022

Systematic bio- and databanks are key prerequisites for modern radiation research to investigate radiation response mechanisms in the context of genetic, environmental and lifestyle-associated factors. This report presents the current status of the German Uranium Miners’ Biobank. In 2008, the bio- and databank was established at the Federal Office for Radiation Protection, and the sampling of biological materials from former uranium miners with and without lung cancer was initiated. For this purpose, various biological specimens, such as DNA and RNA, were isolated from blood samples as well as from formalin-fixed paraffin-embedded lung tissue. High-quality biomaterials suitable for OMICs research and the associated data on occupational radiation and dust exposure, and medical and lifestyle data from over 1000 individuals have been stored so far. Various experimental data, e.g., genome-wide SNPs, whole genome transcriptomic and miRNA data, as well as individual chromosomal aberration data from subgroups of biobank samples, are already available upon request for in-depth research on radiation-induced long-term effects, individual radiation susceptibility to lung cancer and radon-induced fingerprints in lung cancer. This biobank is the first systematic uranium miners´ biobank worldwide that is suitable for OMICs research on radiation-exposed workers. It offers the opportunity to link radiation-induced perturbations of biological pathways or processes and putative adverse outcome(s) by OMICs profiling at different biological organization levels.
Isolation, Community and Spirituality: British Muslim Experiences of Ramadan in Lockdown
Authors: Jones-Ahmed Laura
Published: January 2022

Ramadan, the Islamic month of fasting, is typically a time associated with individual worship and communal gatherings as Muslims meet, eat and pray together. In 2020 especially, COVID-19 had a significant impact on the observation of the holy month. With lockdown measures in place, mosques were closed and there were prohibitions on visiting family and friends, making the month an unusual occasion. This paper draws upon qualitative PhD research on Ramadan 2020 in Britain comprising more than 50 Ramadan photo diaries from diverse Muslim participants and follow-up interviews. The findings highlight how participants experienced the benefits of isolation by being able to reflect and connect more with God and via the establishment of “Ramadan corners” in homes, while at the same time missing the mosque and the Muslim community. I further highlight how communal aspects of the holy month were maintained and transformed to suit lockdown conditions, including the use of online activities, praying in congregation at home and sharing food. Emerging from these two facets of Ramadan, I explore ideas of socially dependent spirituality and how participants negotiated communal and individual elements of their spiritual lives. Through the diverse examples discussed, I argue that material, embodied, aesthetic and emotive practices were emphasised in 2020 to recreate a ‘feeling’ of Ramadan when typical expressions of the month were unavailable.
Measurement of Systemic Risk in the Colombian Banking Sector
Authors: Rivera-Escobar Orlando , Escobar John Willmer , Manotas Diego Fernando
Published: January 2022

This paper uses three methodologies for measuring the existence of systemic risk in the Colombian banking system. The determination of its existence is based on implementing three systemic risk measures widely referenced in academic works after the subprime crisis, known as CoVaR, MES and SRISK. Together, the three methodologies were implemented for the case of Colombian Banks during the 2008–2017 period. The findings allow us to establish that the Colombian banking sector did not present a systemic risk scenario, despite having suffered economic losses due to external shocks, mainly due to the subprime crisis. The results and findings show the efficiency of the systemic risk measures implemented in this study as an alternative to measure systemic risk in banking systems.
Fifty Years of Tidewater Glacier Surface Elevation and Retreat Dynamics along the South-East Coast of Spitsbergen (Svalbard Archipelago)
Authors: Kavan Jan , Tallentire Guy D. , Demidionov Mihail , Dudek Justyna , Strzelecki Mateusz C.
Published: January 2022

Tidewater glaciers on the east coast of Svalbard were examined for surface elevation changes and retreat rate. An archival digital elevation model (DEM) from 1970 (generated from aerial images by the Norwegian Polar Institute) in combination with recent ArcticDEM were used to compare the surface elevation changes of eleven glaciers. This approach was complemented by a retreat rate estimation based on the analysis of Landsat and Sentinel-2 images. In total, four of the 11 tidewater glaciers became land-based due to the retreat of their termini. The remaining tidewater glaciers retreated at an average annual retreat rate of 48 m year−1, and with range between 10–150 m year−1. All the glaciers studied experienced thinning in their frontal zones with maximum surface elevation loss exceeding 100 m in the ablation areas of three glaciers. In contrast to the massive retreat and thinning of the frontal zones, a minor increase in ice thickness was recorded in some accumulation areas of the glaciers, exceeding 10 m on three glaciers. The change in glacier geometry suggests an important shift in glacier dynamics over the last 50 years, which very likely reflects the overall trend of increasing air temperatures. Such changes in glacier geometry are common at surging glaciers in their quiescent phase. Surging was detected on two glaciers studied, and was documented by the glacier front readvance and massive surface thinning in high elevated areas.
Four-Dimensional Plant Phenotyping Model Integrating Low-Density LiDAR Data and Multispectral Images
Authors: Rincón Manuel García , Mendez Diego , Colorado Julian D.
Published: January 2022

High-throughput platforms for plant phenotyping usually demand expensive high-density LiDAR devices with computational intense methods for characterizing several morphological variables. In fact, most platforms require offline processing to achieve a comprehensive plant architecture model. In this paper, we propose a low-cost plant phenotyping system based on the sensory fusion of low-density LiDAR data with multispectral imagery. Our contribution is twofold: (i) an integrated phenotyping platform with embedded processing methods capable of providing real-time morphological data, and (ii) a multi-sensor fusion algorithm that precisely match the 3D LiDAR point-cloud data with the corresponding multispectral information, aiming for the consolidation of four-dimensional plant models. We conducted extensive experimental tests over two plants with different morphological structures, demonstrating the potential of the proposed solution for enabling real-time plant architecture modeling in the field, based on low-density LiDARs.
Refined UNet V4: End-to-End Patch-Wise Network for Cloud and Shadow Segmentation with Bilateral Grid
Authors: Jiao Libin , Huo Lianzhi , Hu Changmiao , Tang Ping , Zhang Zheng
Published: January 2022

Remote sensing images are usually contaminated by cloud and corresponding shadow regions, making cloud and shadow detection one of the essential prerequisites for processing and translation of remote sensing images. Edge-precise cloud and shadow segmentation remains challenging due to the inherent high-level semantic acquisition of current neural segmentation fashions. We, therefore, introduce the Refined UNet series to partially achieve edge-precise cloud and shadow detection, including two-stage Refined UNet, v2 with a potentially efficient gray-scale guided Gaussian filter-based CRF, and v3 with an efficient multi-channel guided Gaussian filter-based CRF. However, it is visually demonstrated that the locally linear kernel used in v2 and v3 is not sufficiently sensitive to potential edges in comparison with Refined UNet. Accordingly, we turn back to the investigation of an end-to-end UNet-CRF architecture with a Gaussian-form bilateral kernel and its relatively efficient approximation. In this paper, we present Refined UNet v4, an end-to-end edge-precise segmentation network for cloud and shadow detection, which is capable of retrieving regions of interest with relatively tight edges and potential shadow regions with ambiguous edges. Specifically, we inherit the UNet-CRF architecture exploited in the Refined UNet series, which concatenates a UNet backbone of coarsely locating cloud and shadow regions and an embedded CRF layer of refining edges. In particular, the bilateral grid-based approximation to the Gaussian-form bilateral kernel is applied to the bilateral message-passing step, in order to ensure the delineation of sufficiently tight edges and the retrieval of shadow regions with ambiguous edges. Our TensorFlow implementation of the bilateral approximation is relatively computationally efficient in comparison with Refined UNet, attributed to the straightforward GPU acceleration. Extensive experiments on Landsat 8 OLI dataset illustrate that our v4 can achieve edge-precise cloud and shadow segmentation and improve the retrieval of shadow regions, and also confirm its computational efficiency.
A Novel Imaging Algorithm for High-Resolution Wide-Swath Space-Borne SAR Based on a Spatial-Variant Equivalent Squint Range Model
Authors: Guo Yanan , Wang Pengbo , Chen Jie , Men Zhirong , Cui Lei , Zhuang Lei
Published: January 2022

High-Resolution Wide-Swath (HRWS) is an important development direction of space-borne Synthetic Aperture Radar (SAR). The two-dimensional spatial variation of the Doppler parameters is the most significant characteristic of the sliding spotlight space-borne SAR system under the requirements of HRWS. Therefore, the compensation of the two-dimensional spatial variation is the most challenging problem faced in the imaging of HRWS situations. The compensatory approach is then proposed to address this problem in this paper. The spatial distribution of the Doppler parameters for the HRWS space-borne SAR data in the sliding spotlight working mode is firstly analyzed, based on which a Spatial-Variant Equivalent Slant Range Model (SV-ESRM) is put forward to accurately formulate the range history for the distributed target. By introducing an azimuth-varying term, the SV-ESRM can precisely describe the range history for not only central targets but also marginal targets, which is more adaptive to the HRWS space-borne SAR requirements. Based on the SV-ESRM, a Modified Hybrid Correlation Algorithm (MHCA) for HRWS space-borne SAR imaging is derived to focus the full-scene data on one single imaging processing. A Doppler phase perturbation incorporated with the sub-aperture method is firstly performed to eliminate the azimuth variation of the Doppler parameters and remove the Doppler spectrum aliasing. Then, an advanced hybrid correlation is employed to achieve the precise differential Range Cell Migration (RCM) correction and Doppler phase compensation. A range phase perturbation method is also utilized to eliminate the range profile defocusing caused by range-azimuth coupling for marginal targets. Finally, a de-rotation processing is performed to remove the azimuth aliasing and the residual azimuth-variance and obtain the precisely focused SAR image. Simulation shows that the SAR echoes for a 20 km × 20 km scene with a 0.25 m resolution in both the range and azimuth directions could be focused precisely via one single imaging processing, which validates the feasibility of the proposed algorithm.
Integration of Surface Reflectance and Aerosol Retrieval Algorithms for Multi-Resolution Aerosol Optical Depth Retrievals over Urban Areas
Authors: Bilal Muhammad , Mhawish Alaa , Ali Md. Arfan , Nichol Janet E. , Leeuw Gerrit de , Khedher Khaled Mohamed , Mazhar Usman , Qiu Zhongfeng , Bleiweiss Max P. , Nazeer Majid
Published: January 2022

The SEMARA approach, an integration of the Simplified and Robust Surface Reflectance Estimation (SREM) and Simplified Aerosol Retrieval Algorithm (SARA) methods, was used to retrieve aerosol optical depth (AOD) at 550 nm from a Landsat 8 Operational Land Imager (OLI) at 30 m spatial resolution, a Terra-Moderate Resolution Imaging Spectroradiometer (MODIS) at 500 m resolution, and a Visible Infrared Imaging Radiometer Suite (VIIRS) at 750 m resolution over bright urban surfaces in Beijing. The SEMARA approach coupled (1) the SREM method that is used to estimate the surface reflectance, which does not require information about water vapor, ozone, and aerosol, and (2) the SARA algorithm, which uses the surface reflectance estimated by SREM and AOD measurements obtained from the Aerosol Robotic NETwork (AERONET) site (or other high-quality AOD) as the input to estimate AOD without prior information on the aerosol optical and microphysical properties usually obtained from a look-up table constructed from long-term AERONET data. In the present study, AOD measurements were obtained from the Beijing AERONET site. The SEMARA AOD retrievals were validated against AOD measurements obtained from two other AERONET sites located at urban locations in Beijing, i.e., Beijing_RADI and Beijing_CAMS, over bright surfaces. The accuracy and uncertainties/errors in the AOD retrievals were assessed using Pearson’s correlation coefficient (r), root mean squared error (RMSE), relative mean bias (RMB), and expected error (EE = ± 0.05 ± 20%). EE is the envelope encompassing both absolute and relative errors and contains 68% (±1σ) of the good quality retrievals based on global validation. Here, the EE of the MODIS Dark Target algorithm at 3 km resolution is used to report the good quality SEMARA AOD retrievals. The validation results show that AOD from SEMARA correlates well with AERONET AOD measurements with high correlation coefficients (r) of 0.988, 0.980, and 0.981; small RMSE of 0.08, 0.09, and 0.08; and small RMB of 4.33%, 1.28%, and −0.54%. High percentages of retrievals, i.e., 85.71%, 91.53%, and 90.16%, were within the EE for Landsat 8 OLI, MODIS, and VIIRS, respectively. The results suggest that the SEMARA approach is capable of retrieving AOD over urban areas with high accuracy and small errors using high to medium spatial resolution satellite remote sensing data. This approach can be used for aerosol monitoring over bright urban surfaces such as in Beijing, which is frequently affected by severe dust storms and haze pollution, to evaluate their effects on public health.
A New Method for Continuous Monitoring of Black and Odorous Water Body Using Evaluation Parameters: A Case Study in Baoding
Authors: Zhou Xueying , Huang Zhaoqiang , Wan Youchuan , Ni Bin , Zhang Yalong , Li Siwei , Wang Mingwei , Wu Tong
Published: January 2022

Water is an important factor in human survival and development. With the acceleration of urbanization, the problem of black and odorous water bodies has become increasingly prominent. It not only affects the living environment of residents in the city, but also threatens their diet and water quality. Therefore, the accurate monitoring and management of urban black and odorous water bodies is particularly important. At present, when researching water quality issues, the methods of fixed-point sampling and laboratory analysis are relatively mature, but the time and labor costs are relatively high. However, empirical models using spectral characteristics and different water quality parameters often lack universal applicability. In addition, a large number of studies on black and odorous water bodies are qualitative studies of water body types, and there are few spatially continuous quantitative analyses. Quantitative research on black and odorous waters is needed to identify the risk of health and environmental problems, as well as providing more accurate guidance on mitigation and treatment methods. In order to achieve this, a universal continuous black and odorous water index (CBOWI) is proposed that can classify waters based on evaluated parameters as well as quantitatively determine the degree of pollution and trends. The model of CBOWI is obtained by partial least squares machine learning through the parameters of the national black and odorous water classification standard. The fitting accuracy and monitoring accuracy of the model are 0.971 and 0.738, respectively. This method provides a new means to monitor black and odorous waters that can also help to improve decision-making and management.