bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation of Sensitization Potential of the Soybean Allergen Gly m 4 by Using Caco-2/Immune Cells Co-Culture Model
Authors: Bogdanov Ivan V. , Finkina Ekaterina I. , Melnikova Daria N. , Ziganshin Rustam H. , Ovchinnikova Tatiana V.
Published: June 2021

The soybean allergen Gly m 4 is known to cause severe allergic reactions including anaphylaxis, unlike other Bet v 1 homologues, which induce mainly local allergic reactions. In the present study, we aimed to investigate whether the food Bet v 1 homologue Gly m 4 can be a sensitizer of the immune system. Susceptibility to gastrointestinal digestion was assessed in vitro. Transport through intestinal epithelium was estimated using the Caco-2 monolayer. Cytokine response of different immunocompetent cells was evaluated by using Caco-2/Immune cells co-culture model. Absolute levels of 48 cytokines were measured by multiplex xMAP technology. It was shown that Gly m 4 can cross the epithelial barrier with a moderate rate and then induce production of IL-4 by mature dendritic cells in vitro. Although Gly m 4 was shown to be susceptible to gastrointestinal enzymes, some of its proteolytic fragments can selectively cross the epithelial barrier and induce production of Th2-polarizing IL-5, IL-10, and IL-13, which may point at the presence of the T-cell epitope among the crossed fragments. Our current data indicate that Gly m 4 can potentially be a sensitizer of the immune system, and intercommunication between immunocompetent and epithelial cells may play a key role in the sensitization process.
Maternal Supply of Both Arachidonic and Docosahexaenoic Acids Is Required for Optimal Neurodevelopment
Authors: Basak Sanjay , Mallick Rahul , Banerjee Antara , Pathak Surajit , Duttaroy Asim K.
Published: June 2021

During the last trimester of gestation and for the first 18 months after birth, both docosahexaenoic acid,22:6n-3 (DHA) and arachidonic acid,20:4n-6 (ARA) are preferentially deposited within the cerebral cortex at a rapid rate. Although the structural and functional roles of DHA in brain development are well investigated, similar roles of ARA are not well documented. The mode of action of these two fatty acids and their derivatives at different structural–functional roles and their levels in the gene expression and signaling pathways of the brain have been continuously emanating. In addition to DHA, the importance of ARA has been much discussed in recent years for fetal and postnatal brain development and the maternal supply of ARA and DHA. These fatty acids are also involved in various brain developmental processes; however, their mechanistic cross talks are not clearly known yet. This review describes the importance of ARA, in addition to DHA, in supporting the optimal brain development and growth and functional roles in the brain.
Timing of Tributyrin Supplementation Differentially Modulates Gastrointestinal Inflammation and Gut Microbial Recolonization Following Murine Ileocecal Resection
Authors: Mocanu Valentin , Park Heekuk , Dang Jerry , Hotte Naomi , Thiesen Aducio , Laffin Michael , Wang Haili , Birch Daniel , Madsen Karen
Published: June 2021

Background: Gastrointestinal surgery imparts dramatic and lasting imbalances, or dysbiosis, to the composition of finely tuned microbial ecosystems. The aim of the present study was to use a mouse ileocecal resection (ICR) model to determine if tributyrin (TBT) supplementation could prevent the onset of microbial dysbiosis or alternatively enhance the recovery of the gut microbiota and reduce gastrointestinal inflammation. Methods: Male wild-type (129 s1/SvlmJ) mice aged 8–15 weeks were separated into single cages and randomized 1:1:1:1 to each of the four experimental groups: control (CTR), preoperative TBT supplementation (PRE), postoperative TBT supplementation (POS), and combined pre- and postoperative supplementation (TOT). ICR was performed one week from baseline assessment with mice assessed at 1, 2, 3, and 4 weeks postoperatively. Primary outcomes included evaluating changes to gut microbial communities occurring from ICR to 4 weeks. Results: A total of 34 mice that underwent ICR (CTR n = 9; PRE n = 10; POS n = 9; TOT n = 6) and reached the primary endpoint were included in the analysis. Postoperative TBT supplementation was associated with an increased recolonization and abundance of anaerobic taxa including Bacteroides thetaiotomicorn, Bacteroides caecimuris, Parabacteroides distasonis, and Clostridia. The microbial recolonization of PRE mice was characterized by a bloom of aerotolerant organisms including Staphylococcus, Lactobacillus, Enteroccaceae, and Peptostreptococcacea. PRE mice had a trend towards decreased ileal inflammation as evidenced by decreased levels of IL-1β (p = 0.09), IL-6 (p = 0.03), and TNF-α (p < 0.05) compared with mice receiving TBT postoperatively. In contrast, POS mice had trends towards reduced colonic inflammation demonstrated by decreased levels of IL-6 (p = 0.07) and TNF-α (p = 0.07). These changes occurred in the absence of changes to fecal short-chain fatty acid concentrations or histologic injury scoring. Conclusions: Taken together, the results of our work demonstrate that the timing of tributyrin supplementation differentially modulates gastrointestinal inflammation and gut microbial recolonization following murine ICR.
A Three-Year Longitudinal Study Comparing Bone Mass, Density, and Geometry Measured by DXA, pQCT, and Bone Turnover Markers in Children with PKU Taking L-Amino Acid or Glycomacropeptide Protein Substitutes
Authors: Daly Anne , Högler Wolfgang , Crabtree Nicola , Shaw Nick , Evans Sharon , Pinto Alex , Jackson Richard , Ashmore Catherine , Rocha Júlio C. , Strauss Boyd J. , Wilcox Gisela , Fraser William D. , Tang Jonathan C. Y. , MacDonald Anita
Published: June 2021

In patients with phenylketonuria (PKU), treated by diet therapy only, evidence suggests that areal bone mineral density (BMDa) is within the normal clinical reference range but is below the population norm. Aims: To study longitudinal bone density, mass, and geometry over 36 months in children with PKU taking either amino acid (L-AA) or casein glycomacropeptide substitutes (CGMP-AA) as their main protein source. Methodology: A total of 48 subjects completed the study, 19 subjects in the L-AA group (median age 11.1, range 5–16 years) and 29 subjects in the CGMP-AA group (median age 8.3, range 5–16 years). The CGMP-AA was further divided into two groups, CGMP100 (median age 9.2, range 5–16 years) (n = 13), children taking CGMP-AA only and CGMP50 (median age 7.3, range 5–15 years) (n = 16), children taking a combination of CGMP-AA and L-AA. Dual X-ray absorptiometry (DXA) was measured at enrolment and 36 months, peripheral quantitative computer tomography (pQCT) at 36 months only, and serum blood and urine bone turnover markers (BTM) and blood bone biochemistry at enrolment, 6, 12, and 36 months. Results: No statistically significant differences were found between the three groups for DXA outcome parameters, i.e., BMDa (L2–L4 BMDa g/cm2), bone mineral apparent density (L2–L4 BMAD g/cm3) and total body less head BMDa (TBLH g/cm2). All blood biochemistry markers were within the reference ranges, and BTM showed active bone turnover with a trend for BTM to decrease with increasing age. Conclusions: Bone density was clinically normal, although the median z scores were below the population mean. BTM showed active bone turnover and blood biochemistry was within the reference ranges. There appeared to be no advantage to bone density, mass, or geometry from taking a macropeptide-based protein substitute as compared with L-AAs.
Epidemiological Aspects of Maternal and Congenital Toxoplasmosis in Panama
Authors: Flores Carlos , Villalobos-Cerrud Delba , Borace Jovanna , Fábrega Lorena , Norero Ximena , Sáez-Llorens X. , Moreno María Teresa , Restrepo Carlos M. , Llanes Alejandro , Quijada R. Mario , Ladrón De Guevara Mayrene , Guzmán German , de la Guardia Valli , García Anabel , Lucero María F. , Wong Digna , Mcleod Rima , Soberon Mariangela , Caballero E. Zuleima
Published: June 2021

In Panama, epidemiological data on congenital toxoplasmosis are limited, making it difficult to understand the scope of clinical manifestations in the population and factors that may increase the risk of infection. This study provides insight into the epidemiological situation of maternal and congenital toxoplasmosis in Panama and contributing information on the burden of this disease in Central America. Blood samples were collected from 2326 pregnant women and used for the detection of anti-T. gondii antibodies. A high seroprevalence (44.41%) was observed for T. gondii infection in pregnant women from different regions of Panama, with an estimated incidence rate of congenital toxoplasmosis of 3.8 cases per 1000 live births. The main risk factors associated with T. gondii infection using bivariate statistical analysis were an elementary level education and maternal age range of 34-45 years. Multivariate statistical analyses revealed that in some regions (San Miguelito, North and West regions), the number of positive cases correlated with the presence of pets, stray dogs and the consumption of poultry. In other regions (East and Metropolitan regions), the absence of pets was considered a protective factor associated with negative cases, while the presence of stray cats and the age range of 25–34 years did not represent any risk in these regions.
Human Single-Chain Antibodies That Neutralize Elastolytic Activity of Pseudomonas aeruginosa LasB
Authors: Santajit Sirijan , Kong-ngoen Thida , Chongsa-Nguan Manas , Boonyuen Usa , Pumirat Pornpan , Sookrung Nitat , Chaicumpa Wanpen , Indrawattana Nitaya
Published: June 2021

LasB (elastase/pseudolysin) is an injurious zinc-metalloprotease secreted by the infecting Pseudomonas aeruginosa. LasB is recognized as the bacterial key virulence factor for establishment of successful infection, acquisition of nutrients, dissemination, tissue invasion, and immune modulation and evasion. LasB digests a variety of the host tissue proteins, extracellular matrices, as well as components of both innate and adaptive immune systems, including immunoglobulins, complement proteins, and cytokines. Thus, this enzyme is an attractive target for disarming the P. aeruginosa. This study generated human single-chain antibodies (HuscFvs) that can neutralize the elastolytic activity of native LasB by using phage display technology. Gene sequences coding HuscFvs (huscfvs) isolated from HuscFv-displaying phage clones that bound to enzymatically active LasB were sub-cloned to expression plasmids for large scale production of the recombinant HuscFvs by the huscfv-plasmid transformed Escherichia coli. HuscFvs of two transformed E. coli clones, i.e., HuscFv-N42 and HuscFv-N45, neutralized the LasB elastolytic activities in vitro. Computer simulation by homology modeling and molecular docking demonstrated that antibodies presumptively formed contact interfaces with the LasB residues critical for the catalytic activity. Although the LasB neutralizing mechanisms await elucidation by laboratory experiments, the HuscFvs should be tested further towards the clinical application as a novel adjunctive therapeutics to mitigate severity of the diseases caused by P. aeruginosa.
Radiopharmaceutical Formulation and Preclinical Testing of 68Ga-Labeled DOTA-MGS5 for the Regulatory Approval of a First Exploratory Clinical Trial
Authors: Hörmann Anton A. , Klingler Maximilian , Rangger Christine , Mair Christian , Decristoforo Clemens , Uprimny Christian , Virgolini Irene J. , von Guggenberg Elisabeth
Published: June 2021

The new minigastrin analog DOTA-MGS5 is a promising new candidate for targeting cholecystokinin-2 receptor (CCK2R)-expressing tumors. To enable the clinical translation of PET/CT imaging using 68Ga-labeled DOTA-MGS5, different quality and safety aspects need to be considered to comply with the regulatory framework for clinical trial application. The preparation of the radiopharmaceutical was established using a cassette-based automated synthesis unit. Product specifications, including analytical procedures and acceptance criteria, were adopted from Ph. Eur. monographs for other 68Ga-labeled radiopharmaceuticals. Non-clinical studies included receptor affinity and cell uptake studies using two different CCK2R-expressing cell lines, as well as pharmacokinetic biodistribution studies in BALB/c mice for dosimetry calculations and toxicological studies in Wistar rats. The produced masterbatches fulfilled the defined acceptance criteria. DOTA-MGS5, with confirmed affinity to the CCK2R, showed a high specific cell uptake and no interaction with other receptors in vitro when radiolabeled with gallium-68. Favorable in vivo properties were observed in biodistribution and dosimetry studies. An effective dose of ~0.01 mSv/MBq was estimated for humans utilizing OLINDA/EXM software. A maximum peptide dose of 50 µg was established for the initial clinical dose based on the toxicity study in rats. The standardized production of [68Ga]Ga-DOTA-MGS5 using an automated synthesis module and the performed non-clinical safety studies support a first exploratory clinical trial with this new PET imaging agent.
Zebrafish as a Screening Model to Study the Single and Joint Effects of Antibiotics
Authors: Jijie Roxana , Mihalache Gabriela , Balmus Ioana-Miruna , Strungaru Stefan-Adrian , Baltag Emanuel Stefan , Ciobica Alin , Nicoara Mircea , Faggio Caterina
Published: June 2021

The overuse of antibiotics combined with the limitation of wastewater facilities has resulted in drug residue accumulation in the natural environment. Thus, in recent years, the presence of antibiotic residues in the environment has raised concerns over the potential harmful effects on ecosystems and human health. The in vivo studies represent an essential step to study the potential impact induced by pharmaceutical exposure. Due to the limitations of traditional vertebrate model systems, zebrafish (Danio rerio) has recently emerged as a promising animal model to study the toxic effects of drugs and their therapeutic efficacy. The present review summarizes the recent advances made on the toxicity of seven representative classes of antibiotics, namely aminoglycosides, β-lactams, macrolides, quinolones, sulfonamides, tetracyclines and polyether antibiotics, in zebrafish, as well as the combined effects of antibiotic mixtures, to date. Despite a significant amount of the literature describing the impact of single antibiotic exposure, little information exists on the effects of antibiotic mixtures using zebrafish as an animal model. Most of the research papers on this topic have focused on antibiotic toxicity in zebrafish across different developmental stages rather than on their efficacy assessment.
Tumor Microenvironment-Responsive Shell/Core Composite Nanoparticles for Enhanced Stability and Antitumor Efficiency Based on a pH-Triggered Charge-Reversal Mechanism
Authors: Luo Qiuhua , Shi Wen , Wang Puxiu , Zhang Yu , Meng Jia , Zhang Ling
Published: June 2021

High systemic stability and effective tumor accumulation of chemotherapeutic agents are indispensable elements that determine their antitumor efficacy. PEGylation of nanoparticles (NPs) could prolong the retention time in vivo by improving their stability in circulation, but treatment suffers reduced tumor penetration and cellular uptake of nanomedicines. The tumor microenvironment (TME)-responsive NPs maintain their stealth features during circulation and undergo a stimuli-responsive dePEGylation once exposed to the site of action, thereby achieving enhanced internalization in tumor cells. Herein, TME-responsive shell/core composite nanoparticles were prepared and optimized with enhanced stability and tumor intake efficiency. We synthesized 12-hydroxystearic acid-poly (ethylene glycol)-YGRKKRRQRRR (HA-PEG-TAT) as a post-insert apparatus in disulfiram (DSF)-encapsulated naked nanoparticles (N-NPs) in order to form a cationic core (TAT-NPs). Accordingly, the negatively charged poly (glutamate acid)-graft-poly (ethylene glycol) (PGlu-PEG) was further applied to the surface of TAT-NPs as a negative charged shell (PGlu-PEG/TAT-NPs) via the electrostatic interaction between glutamic acids and arginine at the outer ring of the TAT-NPs. PGlu-PEG/TAT-NPs displayed a huge loading capability for DSF with reduced degradation in plasma and exhibited rapid charge reversal when pH decreased from 7.4 to pH 6.5, demonstrating an excellent systemic stability as well as intelligent stimuli-responsive performance within the acidic TME. Furthermore, the in vivo antitumor study revealed that PGlu-PEG/TAT-NPs provided greater antitumor efficacy compared with free DSF and N-NPs with no obvious systemic toxicity. In conclusion, the TME-responsive shell/core composite NPs, consisting of PGlu-PEG and HS-PEG-TAT, could mediate an effective and biocompatible delivery of chemotherapeutic agents with clinical potential.
Dendrimer-Coated Gold Nanoparticles for Efficient Folate-Targeted mRNA Delivery In Vitro
Authors: Mbatha Londiwe Simphiwe , Maiyo Fiona , Daniels Aliscia , Singh Moganavelli
Published: June 2021

Messenger RNA (mRNA) is not an attractive candidate for gene therapy due to its instability and has therefore received little attention. Recent studies show the advantage of mRNA over DNA, especially in cancer immunotherapy and vaccine development. This study aimed to formulate folic-acid-(FA)-modified, poly-amidoamine-generation-5 (PAMAM G5D)-grafted gold nanoparticles (AuNPs) and to evaluate their cytotoxicity and transgene expression using the luciferase reporter gene (FLuc-mRNA) in vitro. Nanocomplexes were spherical and of favorable size. Nanocomplexes at optimum nanoparticle:mRNA (w/w) binding ratios showed good protection of the bound mRNA against nucleases and were well tolerated in all cell lines. Transgene expression was significantly (p < 0.0001) higher with FA-targeted, dendrimer-grafted AuNPs (Au:G5D:FA) in FA receptors overexpressing MCF-7 and KB cells compared to the G5D and G5D:FA NPs, decreasing significantly (p < 0.01) in the presence of excess competing FA ligand, which confirmed nanocomplex uptake via receptor mediation. Overall, transgene expression of the Au:G5D and Au:G5D:FA nanocomplexes exceeded that of G5D and G5D:FA nanocomplexes, indicating the pivotal role played by the inclusion of the AuNP delivery system. The favorable properties imparted by the AuNPs potentiated an increased level of luciferase gene expression.
Comparative Analysis of Chloroplast Genomes of Four Medicinal Capparaceae Species: Genome Structures, Phylogenetic Relationships and Adaptive Evolution
Authors: Alzahrani Dhafer A. , Albokhari Enas J. , Yaradua Samaila S. , Abba Abidina
Published: June 2021

This study presents for the first time the complete chloroplast genomes of four medicinal species in the Capparaceae family belonging to two different genera, Cadaba and Maerua (i.e., C. farinosa, C. glandulosa, M. crassifolia and M. oblongifolia), to investigate their evolutionary process and to infer their phylogenetic positions. The four species are considered important medicinal plants, and are used in the treatment of many diseases. In the genus Cadaba, the chloroplast genome ranges from 156,481 bp to 156,560 bp, while that of Maerua ranges from 155,685 bp to 155,436 bp. The chloroplast genome of C. farinosa, M. crassifolia and M. oblongifolia contains 138 genes, while that of C. glandulosa contains 137 genes, comprising 81 protein-coding genes, 31 tRNA genes and 4 rRNA genes. Out of the total genes, 116–117 are unique, while the remaining 19 are replicated in inverted repeat regions. The psbG gene, which encodes for subunit K of NADH dehydrogenase, is absent in C. glandulosa. A total of 249 microsatellites were found in the chloroplast genome of C. farinosa, 251 in C. glandulosa, 227 in M. crassifolia and 233 in M. oblongifolia, the majority of which are mononucleotides A/T found in the intergenic spacer. Comparative analysis revealed variable hotspot regions (atpF, rpoC2, rps19 and ycf1), which can be used as molecular markers for species authentication and as regions for inferring phylogenetic relationships among them, as well as for evolutionary studies. The monophyly of Capparaceae and other families under Brassicales, as well as the phylogenetic positions of the studied species, are highly supported by all the relationships in the phylogenetic tree. The cp genomes reported in this study will provide resources for studying the genetic diversity of Capparaceae, as well as resolving phylogenetic relationships within the family.
A Natural Botanical Product, Resveratrol, Effectively Suppresses Vesicular Stomatitis Virus Infection In Vitro
Authors: Lin Shih-Chao , Zhang Xiang , Lehman Caitlin W. , Pan Han-Chi , Wen Ya , Chen Shiow-Yi
Published: June 2021

Numerous natural phytochemicals such as resveratrol are acknowledged as potent botanical agents in regulating immune responses. However, it is less understood whether such immunomodulatory phytochemicals are appropriate for use as direct treatments in veterinary viral diseases. In the present study, we investigated the efficacy of resveratrol in suppressing vesicular stomatitis virus (VSV) infection. Outbreaks of VSV can cause massive economic loss in poultry and livestock husbandry farming, and VSV treatment is in need of therapeutic development. We utilized a recombinant VSV that expresses green fluorescent protein (GFP) to measure viral replication in cells treated with resveratrol. Our findings revealed that resveratrol treatment affords a protective effect, shown by increased viability and reduced viral replication, as indicated by a reduction in fluorescent signals. Additionally, we found that resveratrol inhibition of VSV infection occurs via suppression of the caspase cascade. Structural analysis also indicated that resveratrol potentially interacts with the active sites of caspase-3 and -7, facilitating antiviral activity. The potential effect of resveratrol on reducing VSV infection in vitro suggests that resveratrol should be further investigated as a potential veterinary therapeutic or prophylactic agent.
Patterned Membranes for Proton Exchange Membrane Fuel Cells Working at Low Humidity
Authors: Fernihough Oliver , Cheshire Holly , Romano Jean-Michel , Ibrahim Ahmed , El-Kharouf Ahmad , Du Shangfeng
Published: June 2021

High performing proton exchange membrane fuel cells (PEMFCs) that can operate at low relative humidity is a continuing technical challenge for PEMFC developers. In this work, micro-patterned membranes are demonstrated at the cathode side by solution casting techniques using stainless steel moulds with laser-imposed periodic surface structures (LIPSS). Three types of patterns, lotus, lines, and sharklet, are investigated for their influence on the PEMFC power performance at varying humidity conditions. The experimental results show that the cathode electrolyte pattern, in all cases, enhances the fuel cell power performance at 100% relative humidity (RH). However, only the sharklet pattern exhibits a significant improvement at 25% RH, where a peak power density of 450 mW cm−2 is recorded compared with 150 mW cm−2 of the conventional flat membrane. The improvements are explored based on high-frequency resistance, electrochemically active surface area (ECSA), and hydrogen crossover by in situ membrane electrode assembly (MEA) testing.
8-Day and Daily Maximum and Minimum Air Temperature Estimation via Machine Learning Method on a Climate Zone to Global Scale
Authors: Zeng Linglin , Hu Yuchao , Wang Rui , Zhang Xiang , Peng Guozhang , Huang Zhenyu , Zhou Guoqing , Xiang Daxiang , Meng Ran , Wu Weixiong , Hu Shun
Published: June 2021

Air temperature (Ta) is a required input in a wide range of applications, e.g., agriculture. Land Surface Temperature (LST) products from Moderate Resolution Imaging Spectroradiometer (MODIS) are widely used to estimate Ta. Previous studies of these products in Ta estimation, however, were generally applied in small areas and with a small number of meteorological stations. This study designed both temporal and spatial experiments to estimate 8-day and daily maximum and minimum Ta (Tmax and Tmin) on three spatial scales: climate zone, continental and global scales from 2009 to 2018, using the Random Forest (RF) method based on MODIS LST products and other auxiliary data. Factors contributing to the relation between LST and Ta were determined based on physical models and equations. Temporal and spatial experiments were defined by the rules of dividing the training and validation datasets for the RF method, in which the stations selected in the training dataset were all included or not in the validation dataset. The RF model was first trained and validated on each spatial scale, respectively. On a global scale, model accuracy with a determination coefficient (R2) > 0.96 and root mean square error (RMSE) < 1.96 °C and R2 > 0.95 and RMSE < 2.55 °C was achieved for 8-day and daily Ta estimations, respectively, in both temporal and spatial experiments. Then the model was trained and cross-validated on each spatial scale. The results showed that the data size and station distribution of the study area were the main factors influencing the model performance at different spatial scales. Finally, the spatial patterns of the model performance and variable importance were analyzed. Both daytime and nighttime LST had a significant contribution in the 8-day Tmax estimation on all the three spatial scales; while their contribution in daily Tmax estimation varied over different continents or climate zones. This study was expected to improve our understanding of Ta estimation in terms of accuracy variations and influencing variables on different spatial and temporal scales. The future work mainly includes identifying underlying mechanisms of estimation errors and the uncertainty sources of Ta estimation from a local to a global scale.
Effect of Lunar Complex Illumination on In Situ Measurements Obtained Using Visible and Near-Infrared Imaging Spectrometer of Chang’E-4
Authors: Xu Jiafei , Wang Meizhu , Lin Honglei , Wang Rong , Feng Qi , Xu Xuesen
Published: June 2021

In-situ measurements of the spectral information on the lunar surface are of significance to study the geological evolution of the Moon. China’s Chang’E-4 (CE-4) Yutu-2 rover has conducted several in-situ spectral explorations on the Moon. The visible and near-infrared imaging spectrometer (VNIS) onboard the rover has acquired a series of in-situ spectra of the regolith at the landing site. In general, the mineralogical research of the lunar surface relies on the accuracy of the in-situ data. However, the spectral measurements of the Yutu-2 rover may be affected by shadows and stray illumination. In this study, we analyzed 106 CE-4 VNIS spectra acquired in the first 24 lunar days of the mission and noted that six of these spectra were affected by the shadows of the rover. Therefore, a method was established to correct the effects of the rover shadow on the spectral measurements. After shadow correction, the FeO content in the affected area is corrected to 14.46 wt.%, which was similar to the result calculated in the normal regolith. Furthermore, according to the visible images, certain areas of the explored sites were noted to be unusually bright. Considering the reflectance, geometric information, and shining patterns of the multi-layer insulation (MLI), we examined the influence of the specular reflection of the MLI on the bright spot regionsd, and found that the five sets of data were likely not affected by the specular reflection of the MLI. The results indicated that the complex illumination considerably influences the in situ spectral data. This study can provide a basis to analyze the VNIS scientific data and help enhance the accuracy of interpretation of the composition at CE-4 landing sites.
The Links between Canopy Solar-Induced Chlorophyll Fluorescence and Gross Primary Production Responses to Meteorological Factors in the Growing Season in Deciduous Broadleaf Forest
Authors: Cheng Xiangfen , Zhou Yu , Hu Meijun , Wang Feng , Huang Hui , Zhang Jinsong
Published: June 2021

Solar-induced chlorophyll fluorescence (SIF) is a hopeful indicator, which along with remote sensing, is used to measure the photosynthetic efficiency and gross primary production (GPP) of vegetation in regional terrestrial ecosystems. Studies have found a significant linear correlation between SIF and GPP in a variety of ecosystems. However, this relationship has mainly been established using SIF and GPP data derived from satellite remote sensing and continuous ground-based observations, respectively, which are difficult to accurately match. To overcome this, some studies have begun to use tower-based automatic observation instruments to study the changes of near-surface SIF and GPP. This study conducts continuous simultaneous observation of SIF, carbon flux, and meteorological factors on the forest canopy of a cork oak plantation during the growing season to explore how meteorological factors impact on canopy SIF and its relationship with GPP. This research found that the canopy SIF has obvious diurnal and day-to-day variations during the growing season but overall is relatively stable. Furthermore, SIF is greatly affected by incident radiation in different weather conditions and can change daily. Meteorological factors have a major role in the relationship between SIF and GPP; overall, the relationship shows a significant linear regression on the 30 min scale, but weakens when aggregating to the diurnal scale. Photosynthetically active radiation (PAR) drives SIF on a daily basis and changes the relationship between SIF and GPP on a seasonal timescale. As PAR increases, the daily slopes of the linear regressions between SIF and GPP decrease. On the 30 min timescale, both SIF and GPP increase with PAR until it reaches 1250 μmol·m−2·s−1; subsequently, SIF continues to increase while GPP decreases and they show opposite trends. Soil moisture and vapor pressure deficit influence SIF and GPP, respectively. Our findings demonstrate that meteorological factors affect the relationship between SIF and GPP, thereby enhancing the understanding of the mechanistic link between chlorophyll fluorescence and photosynthesis.
A Quantitative Validation of Multi-Modal Image Fusion and Segmentation for Object Detection and Tracking
Authors: LaHaye Nicholas , Garay Michael J. , Bue Brian D. , El-Askary Hesham , Linstead Erik
Published: June 2021

In previous works, we have shown the efficacy of using Deep Belief Networks, paired with clustering, to identify distinct classes of objects within remotely sensed data via cluster analysis and qualitative analysis of the output data in comparison with reference data. In this paper, we quantitatively validate the methodology against datasets currently being generated and used within the remote sensing community, as well as show the capabilities and benefits of the data fusion methodologies used. The experiments run take the output of our unsupervised fusion and segmentation methodology and map them to various labeled datasets at different levels of global coverage and granularity in order to test our models’ capabilities to represent structure at finer and broader scales, using many different kinds of instrumentation, that can be fused when applicable. In all cases tested, our models show a strong ability to segment the objects within input scenes, use multiple datasets fused together where appropriate to improve results, and, at times, outperform the pre-existing datasets. The success here will allow this methodology to be used within use concrete cases and become the basis for future dynamic object tracking across datasets from various remote sensing instruments.
Extensibility of U-Net Neural Network Model for Hydrographic Feature Extraction and Implications for Hydrologic Modeling
Authors: Stanislawski Lawrence V. , Shavers Ethan J. , Wang Shaowen , Jiang Zhe , Usery E. Lynn , Moak Evan , Duffy Alexander , Schott Joel
Published: June 2021

Accurate maps of regional surface water features are integral for advancing ecologic, atmospheric and land development studies. The only comprehensive surface water feature map of Alaska is the National Hydrography Dataset (NHD). NHD features are often digitized representations of historic topographic map blue lines and may be outdated. Here we test deep learning methods to automatically extract surface water features from airborne interferometric synthetic aperture radar (IfSAR) data to update and validate Alaska hydrographic databases. U-net artificial neural networks (ANN) and high-performance computing (HPC) are used for supervised hydrographic feature extraction within a study area comprised of 50 contiguous watersheds in Alaska. Surface water features derived from elevation through automated flow-routing and manual editing are used as training data. Model extensibility is tested with a series of 16 U-net models trained with increasing percentages of the study area, from about 3 to 35 percent. Hydrography is predicted by each of the models for all watersheds not used in training. Input raster layers are derived from digital terrain models, digital surface models, and intensity images from the IfSAR data. Results indicate about 15 percent of the study area is required to optimally train the ANN to extract hydrography when F1-scores for tested watersheds average between 66 and 68. Little benefit is gained by training beyond 15 percent of the study area. Fully connected hydrographic networks are generated for the U-net predictions using a novel approach that constrains a D-8 flow-routing approach to follow U-net predictions. This work demonstrates the ability of deep learning to derive surface water feature maps from complex terrain over a broad area.
Understanding the Diversity of Urban–Rural Fringe Development in a Fast Urbanizing Region of China
Authors: Li Guoyu , CAO Yu , He Zhichao , He Ju , Cao Yu , Wang Jiayi , Fang Xiaoqian
Published: June 2021

The territories between urban and rural areas, also called urban–rural fringe, commonly present inherent instability and notable heterogeneity. However, investigating the multifaceted urban–rural fringe phenomenon based on large-scale identification has yet to be undertaken. In this study, we adopted a handy clustering-based method by incorporating multidimensional urbanization indicators to understand how the urban–rural fringe development vary across space and shift over time in the Yangtze River Delta Urban Agglomeration, China. The results show that (1) the growth magnitude of urban–rural fringe areas was greater than urban areas, whereas their growth rate was remarkably lower. (2) The landscape dynamics of urban–rural fringe varied markedly between fast-developing and slow-developing cities. Peripheral sprawl, inter-urban bridge, and isolated growth were the representative development patterns of urban–rural fringe in this case. (3) Urban–rural fringe development has predominantly occurred where cultivated land is available, and significant inter-provincial differences and tendency shifts have been found in the land cover change processes therein. Our findings indicate that the urban–rural fringe development should be considered as a stage-dependent and place-specific process. This work extends previous knowledge by unraveling the diversity of urban–rural fringe in a fast urbanizing region, and can provide insights into reorienting the spatial planning and land use management within the urban–rural interface.
Assessment of Polymer Atmospheric Correction Algorithm for Hyperspectral Remote Sensing Imagery over Coastal Waters
Authors: Soppa Mariana A. , Silva Brenner , Steinmetz François , Keith Darryl , Scheffler Daniel , Bohn Niklas , Bracher Astrid
Published: June 2021

Spaceborne imaging spectroscopy, also called hyperspectral remote sensing, has shown huge potential to improve current water colour retrievals and, thereby, the monitoring of inland and coastal water ecosystems. However, the quality of water colour retrievals strongly depends on successful removal of the atmospheric/surface contributions to the radiance measured by satellite sensors. Atmospheric correction (AC) algorithms are specially designed to handle these effects, but are challenged by the hundreds of narrow spectral bands obtained by hyperspectral sensors. In this paper, we investigate the performance of Polymer AC for hyperspectral remote sensing over coastal waters. Polymer is, in nature, a hyperspectral algorithm that has been mostly applied to multispectral satellite data to date. Polymer was applied to data from the Hyperspectral Imager for the Coastal Ocean (HICO), validated against in situ multispectral (AERONET-OC) and hyperspectral radiometric measurements, and its performance was compared against that of the hyperspectral version of NASA’s standard AC algorithm, L2gen. The match-up analysis demonstrated very good performance of Polymer in the green spectral region. The mean absolute percentage difference across all the visible bands varied between 16% (green spectral region) and 66% (red spectral region). Compared with L2gen, Polymer remote sensing reflectances presented lower uncertainties, greater data coverage, and higher spectral similarity to in situ measurements. These results demonstrate the potential of Polymer to perform AC on hyperspectral satellite data over coastal waters, thus supporting its application in current and future hyperspectral satellite missions.
Improvement of RTT Fairness Problem in BBR Congestion Control Algorithm by Gamma Correction
Authors: Pan Wansu , Li Xiaofeng , Tan Haibo , Xu Jinlin , Li Xiru
Published: June 2021

Google proposed the bottleneck bandwidth and round-trip propagation time (BBR), which is a new congestion control algorithm. BBR creates a network path model by measuring the available bottleneck bandwidth and the minimum round-trip time (RTT) to maximize delivery rate and minimize latency. However, some studies have shown that there are serious RTT fairness problems in the BBR algorithm. The flow with longer RTT will consume more bandwidth and the flows with shorter RTT will be severely squeezed or even starved to death. Moreover, these studies pointed out that even small RTT differences will lead to the throughput of BBR flows being unfair. In order to solve the problem of RTT fairness, an improved algorithm BBR-gamma correction (BBR-GC) is proposed. BBR-GC algorithm takes RTT as feedback information, and then uses the gamma correction function to fit the adaptive pacing gain. This approach can make different RTT flows compete for bandwidth more fairly, thus alleviating the RTT fairness issue. The simulation results of Network Simulator 3 (NS3) show that that BBR-GC algorithm cannot only ensure the channel utilization, but also alleviate the RTT fairness problem of BBR flow in different periods. Through the BBR-GC algorithm, RTT fairness is improved by 50% and the retransmission rate is reduced by more than 26%, compared with that of the original BBR in different buffer sizes.
Three-Way Junction-Induced Isothermal Amplification with High Signal-to-Background Ratio for Detection of Pathogenic Bacteria
Authors: Kim Jung , Kim Seokjoon , Hwang Sung , Yoon Tae , Park Jung , Lee Eun , Woo Jisu , Park Ki
Published: June 2021

The consumption of water and food contaminated by pathogens is a major cause of numerous diseases and deaths globally. To control pathogen contamination and reduce the risk of illness, a system is required that can quickly detect and monitor target pathogens. We developed a simple and reproducible strategy, termed three-way junction (3WJ)-induced transcription amplification, to detect target nucleic acids by rationally combining 3WJ-induced isothermal amplification with a light-up RNA aptamer. In principle, the presence of the target nucleic acid generates a large number of light-up RNA aptamers (Spinach aptamers) through strand displacement and transcription amplification for 2 h at 37 °C. The resulting Spinach RNA aptamers specifically bind to fluorogens such as 3,5-difluoro-4-hydroxybenzylidene imidazolinone and emit a highly enhanced fluorescence signal, which is clearly distinguished from the signal emitted in the absence of the target nucleic acid. With the proposed strategy, concentrations of target nucleic acids selected from the genome of Salmonellaenterica serovar Typhi (S. Typhi) were quantitatively determined with high selectivity. In addition, the practical applicability of the method was demonstrated by performing spike-and-recovery experiments with S. Typhi in human serum.
Pixel-Level Fatigue Crack Segmentation in Large-Scale Images of Steel Structures Using an Encoder–Decoder Network
Authors: Dong Chuanzhi , Li Liangding , Yan Jin , Zhang Zhiming , Pan Hong , Catbas Fikret Necati
Published: June 2021

Fatigue cracks are critical types of damage in steel structures due to repeated loads and distortion effects. Fatigue crack growth may lead to further structural failure and even induce collapse. Efficient and timely fatigue crack detection and segmentation can support condition assessment, asset maintenance, and management of existing structures and prevent the early permit post and improve life cycles. In current research and engineering practices, visual inspection is the most widely implemented approach for fatigue crack inspection. However, the inspection accuracy of this method highly relies on the subjective judgment of the inspectors. Furthermore, it needs large amounts of cost, time, and labor force. Non-destructive testing methods can provide accurate detection results, but the cost is very high. To overcome the limitations of current fatigue crack detection methods, this study presents a pixel-level fatigue crack segmentation framework for large-scale images with complicated backgrounds taken from steel structures by using an encoder-decoder network, which is modified from the U-net structure. To effectively train and test the images with large resolutions such as 4928 × 3264 pixels or larger, the large images were cropped into small images for training and testing. The final segmentation results of the original images are obtained by assembling the segment results in the small images. Additionally, image post-processing including opening and closing operations were implemented to reduce the noises in the segmentation maps. The proposed method achieved an acceptable accuracy of automatic fatigue crack segmentation in terms of average intersection over union (mIOU). A comparative study with an FCN model that implements ResNet34 as backbone indicates that the proposed method using U-net could give better fatigue crack segmentation performance with fewer training epochs and simpler model structure. Furthermore, this study also provides helpful considerations and recommendations for researchers and practitioners in civil infrastructure engineering to apply image-based fatigue crack detection.
Alignment-Free Sensing Module for Absolute and Incremental Lines in Linear Positioning System Based on Tunneling-Magnetoresistance Sensors
Authors: Lee Chia-Chang , Yen Yu-Shen , Lai Chih-Huang
Published: June 2021

An alignment-free sensing module for the positioning system based on tunneling magnetoresistive (TMR) sensors with an absolute-incremental-integrated scale is demonstrated. The sensors of the proposed system for both lines consist of identical layer stacks; therefore, all sensors can be fabricated in identical processes from thin film deposition to device patterning on a single substrate. Consequently, the relative position of the sensors can be predefined at the lithography stage and the alignment error between sensors caused by the manual installation is completely eliminated. Different from the existing sensing scheme for incremental lines, we proposed to utilize the magnetic tunnel junctions with a perpendicular anisotropy reference layer and an in-plane anisotropy sensing layer. The sensors are placed parallel to the scale plane with magnetization of the sensing layer in the plane, which show the capability of polarity detection for the absolute line and reveal sinusoidal output signal for the incremental line. Furthermore, due to the large signal of TMR, the working distance can be further improved compared with conventional sensors. In addition, the cost of the positioning system is expected to be lowered, since all the sensors are fabricated in the same process without extra installation. Our design may pave a new avenue for the positioning system based on a magnetic detection scheme.
A Data-Driven Scheme for Fault Detection of Discrete-Time Switched Systems
Authors: Zhao Hao , Luo Hao , Wu Yunkai
Published: June 2021

This paper is concerned with the fault detection issue for a class of discrete-time switched systems via the data-driven approach. For the fault detection of switched systems, it is inevitable to consider the mode matching problem between the activated subsystem and the executed residual generator since the mode mismatching may cause a false fault alarm in all probability. Frequently, studies assume that the switching laws are available to the residual generator, by which the residual generator keeps the same mode as the system plant and then the mode mismatching is excluded. However, this assumption is conservative and impractical because many switching laws are hard to acquire in practical applications. This work focuses on the case of switched systems with unavailable switching laws. In view of the unavailability of switching information, the mode recognition is considered for the fault detection process and meanwhile, sufficient conditions are presented for the mode distinguishability. Moreover, a novel decision logic for the fault detection is proposed, based on which new algorithms are established for the data-driven realization. Finally, a benchmark case on a three-tank system is used to illustrate the feasibility and usefulness of the obtained results.
Automatic Visual Attention Detection for Mobile Eye Tracking Using Pre-Trained Computer Vision Models and Human Gaze
Authors: Barz Michael , Sonntag Daniel
Published: June 2021

Processing visual stimuli in a scene is essential for the human brain to make situation-aware decisions. These stimuli, which are prevalent subjects of diagnostic eye tracking studies, are commonly encoded as rectangular areas of interest (AOIs) per frame. Because it is a tedious manual annotation task, the automatic detection and annotation of visual attention to AOIs can accelerate and objectify eye tracking research, in particular for mobile eye tracking with egocentric video feeds. In this work, we implement two methods to automatically detect visual attention to AOIs using pre-trained deep learning models for image classification and object detection. Furthermore, we develop an evaluation framework based on the VISUS dataset and well-known performance metrics from the field of activity recognition. We systematically evaluate our methods within this framework, discuss potentials and limitations, and propose ways to improve the performance of future automatic visual attention detection methods.