bluuebunny/crossref_metadata_2025 huggingface dataset:
The Resolution in X-ray Crystallography and Single-Particle Cryogenic Electron Microscopy
Authors: Dubach Victor R.A. , Guskov Albert
Published: July 2020

X-ray crystallography and single-particle analysis cryogenic electron microscopy are essential techniques for uncovering the three-dimensional structures of biological macromolecules. Both techniques rely on the Fourier transform to calculate experimental maps. However, one of the crucial parameters, resolution, is rather broadly defined. Here, the methods to determine the resolution in X-ray crystallography and single-particle analysis are summarized. In X-ray crystallography, it is becoming increasingly more common to include reflections discarded previously by traditionally used standards, allowing for the inclusion of incomplete and anisotropic reflections into the refinement process. In general, the resolution is the smallest lattice spacing given by Bragg’s law for a particular set of X-ray diffraction intensities; however, typically the resolution is truncated by the user during the data processing based on certain parameters and later it is used during refinement. However, at which resolution to perform such a truncation is not always clear and this makes it very confusing for the novices entering the structural biology field. Furthermore, it is argued that the effective resolution should be also reported as it is a more descriptive measure accounting for anisotropy and incompleteness of the data. In single particle cryo-EM, the situation is not much better, as multiple ways exist to determine the resolution, such as Fourier shell correlation, spectral signal-to-noise ratio and the Fourier neighbor correlation. The most widely accepted is the Fourier shell correlation using a threshold of 0.143 to define the resolution (so-called “gold-standard”), although it is still debated whether this is the correct threshold. Besides, the resolution obtained from the Fourier shell correlation is an estimate of varying resolution across the density map. In reality, the interpretability of the map is more important than the numerical value of the resolution.
Principal Component Analysis (PCA) for Powder Diffraction Data: Towards Unblinded Applications
Authors: Chernyshov Dmitry , Dovgaliuk Iurii , Dyadkin Vadim , van Beek Wouter
Published: July 2020

We analyze the application of Principal Component Analysis (PCA) for untangling the main contributions to changing diffracted intensities upon variation of site occupancy and lattice dimensions induced by external stimuli. The information content of the PCA output consists of certain functions of Bragg angles (loadings) and their evolution characteristics that depend on external variables like pressure or temperature (scores). The physical meaning of the PCA output is to date not well understood. Therefore, in this paper, the intensity contributions are first derived analytically, then compared with the PCA components for model data; finally PCA is applied for the real data on isothermal gas uptake by nanoporous framework γ –Mg(BH 4 ) 2 . We show that, in close agreement with previous analysis of modulation diffraction, the variation of intensity of Bragg lines and the displacements of their positions results in a series of PCA components. Every PCA extracted component may be a mixture of terms carrying information on the average structure, active sub-structure, and their cross-term. The rotational ambiguities, that are an inherently part of PCA extraction, are at the origin of the mixing. For the experimental case considered in the paper, the extraction of the physically meaningful loadings and scores can only be achieved with a rotational correction. Finally, practical recommendations for non-blind applications, i.e., what boundary conditions to apply for the the rotational correction, of PCA for diffraction data are given.
Ensemble Deep Learning for Cervix Image Selection toward Improving Reliability in Automated Cervical Precancer Screening
Authors: Guo Peng , Xue Zhiyun , Mtema Zac , Yeates Karen , Ginsburg Ophira , Demarco Maria , Long L. Rodney , Schiffman Mark , Antani Sameer
Published: July 2020

Automated Visual Examination (AVE) is a deep learning algorithm that aims to improve the effectiveness of cervical precancer screening, particularly in low- and medium-resource regions. It was trained on data from a large longitudinal study conducted by the National Cancer Institute (NCI) and has been shown to accurately identify cervices with early stages of cervical neoplasia for clinical evaluation and treatment. The algorithm processes images of the uterine cervix taken with a digital camera and alerts the user if the woman is a candidate for further evaluation. This requires that the algorithm be presented with images of the cervix, which is the object of interest, of acceptable quality, i.e., in sharp focus, with good illumination, without shadows or other occlusions, and showing the entire squamo-columnar transformation zone. Our prior work has addressed some of these constraints to help discard images that do not meet these criteria. In this work, we present a novel algorithm that determines that the image contains the cervix to a sufficient extent. Non-cervix or other inadequate images could lead to suboptimal or wrong results. Manual removal of such images is labor intensive and time-consuming, particularly in working with large retrospective collections acquired with inadequate quality control. In this work, we present a novel ensemble deep learning method to identify cervix images and non-cervix images in a smartphone-acquired cervical image dataset. The ensemble method combined the assessment of three deep learning architectures, RetinaNet, Deep SVDD, and a customized CNN (Convolutional Neural Network), each using a different strategy to arrive at its decision, i.e., object detection, one-class classification, and binary classification. We examined the performance of each individual architecture and an ensemble of all three architectures. An average accuracy and F-1 score of 91.6% and 0.890, respectively, were achieved on a separate test dataset consisting of more than 30,000 smartphone-captured images.
Adjunctive Use of Lasers in Peri-Implant Mucositis and Peri-Implantitis Treatment: A Systematic Review
Authors: Chala Marianna , Anagnostaki Eugenia , Mylona Valina , Chalas Anastasios , Parker Steven , Lynch Edward
Published: July 2020

Background: The aim of this systematic review is to compare the effectiveness of lasers in the treatment of implant mucositis and peri-implantitis compared to conventional treatment (non-surgical or surgical: resective or regenerative). Methods: Sources of PubMed, Cochrane and Google Scholar search engines were used on articles published from 1997 to 2020 in English, with selected keyword criteria applied. Nine randomized controlled trials (RCTs) were selected. Results: All included studies were considered of “high quality” according to the quality assessment scale. The comparative assessment of the RCTs was done twice for each RCT based on the type of treatment and according to wavelength. There is strong scientific evidence that, regarding non-surgical treatment, adjunct laser application can provide better results only in the short term (three months). Regarding the surgical approach, the method of decontamination plays a subordinate role. All wavelengths/applications presented similar results. Conclusion: Within the limitations of this study, the adjunctive use of lasers in the treatment of peri-implant inflammation is effective for up to three months; there is no strong evidence regarding the long term benefit compared to conventional treatment.
Emotional and Spiritual Intelligence of Future Leaders: Challenges for Education
Authors: Samul Joanna
Published: July 2020

The study was focused on understanding emotional and spiritual intelligence, and leadership linkages. The aim of the study was to explore the relationship between emotional and spiritual intelligence and self-leadership skills of university students in the fields of management, as potential future leaders. The data were collected using three scales: Emotional Intelligence Scale (WLEIS), Spiritual Intelligence Inventory (SISRI-24), and Self-Leadership questionnaire. The study was conducted among 190 university students. The results obtained show that there are connections between emotional and spiritual intelligence and self-leadership. The study may be a good starting point for further research in this field and lead to reflection about spiritual knowledge on the leadership education program.
A Compact C-Band Bandpass Filter with an Adjustable Dual-Band Suitable for Satellite Communication Systems
Authors: Lalbakhsh Ali , Ghaderi Amirhossein , Mohyuddin Wahab , Simorangkir Roy B. V. B. , Bayat-Makou Nima , Ahmad Muhammad Sajjad , Lee Gwan Hui , Kim Kang Wook
Published: July 2020

A narrowband dual-band bandpass filter (BPF) with independently tunable passbands is presented through a systematic design approach. A size-efficient coupling system is proposed with the capability of being integrated with additional resonators without increasing the size of the circuit. Two flag-shaped resonators along with two stepped-impedance resonators are integrated with the coupling system to firstly enhance the quality response of the filter, and secondly to add an independent adjustability feature to the filter. The dual passband of the filter is centered at 4.42 GHz and 7.2 GHz, respectively, with narrow passbands of 2.12% and 1.15%. The lower and upper passbands can be swept independently over 600 MHz and 1000 MHz by changing only one parameter of the filter without any destructive effects on the frequency response. According to United States frequency allocations, the first passband is convenient for mobile communications and the second passband can be used for satellite communications. The filter has very good in- and out-of-band performance with very small passband insertion losses of 0.5 dB and 0.86 dB as well as a relatively strong stopband attenuation of 30 dB and 25 dB, respectively, for the case of lower and upper bands. To verify the proposed approach, a prototype of the filter is fabricated and measured showing a good agreement between numerically calculated and measured results.
Intelligent Load Balancing Techniques in Software Defined Networks: A Survey
Authors: Semong Thabo , Maupong Thabiso , Anokye Stephen , Kehulakae Kefalotse , Dimakatso Setso , Boipelo Gabanthone , Sarefo Seth
Published: July 2020

In the current technology driven era, the use of devices that connect to the internet has increased significantly. Consequently, there has been a significant increase in internet traffic. Some of the challenges that arise from the increased traffic include, but are not limited to, multiple clients on a single server (which can result in denial of service (DoS)), difficulty in network scalability, and poor service availability. One of the solutions proposed in literature, to mitigate these, is the use of multiple servers with a load balancer. Despite their common use, load balancers, have shown to have some disadvantages, like being vendor specific and non-programmable. To address these disadvantages and improve internet traffic, there has been a paradigm shift which resulted in the introduction of software defined networking (SDN). SDN allows for load balancers that are programmable and provides the flexibility for one to design and implement own load balancing strategies. In this survey, we highlight the key elements of SDN and OpenFlow technology and their effect on load balancing. We provide an overview of the various load balancing schemes in SDN. The overview is based on research challenges, existing solutions, and we give possible future research directions. A summary of emulators/mathematical tools commonly used in the design of intelligent load balancing SDN algorithms is provided. Finally, we outline the performance metrics used to evaluate the algorithms.
Fingerprinting of Relational Databases for Stopping the Data Theft
Authors: Al Solami Eesa , Kamran Muhammad , Saeed Alkatheiri Mohammed , Rafiq Fouzia , Alghamdi Ahmed S.
Published: July 2020

The currently-emerging technology demands sharing of data using various channels via the Internet, disks, etc. Some recipients of this data can also become traitors by leaking the important data. As a result, the data breaches due to data leakage are also increasing. These breaches include unauthorized distribution, duplication, and sale. The identification of a guilty agent responsible for such breaches is important for: (i) punishing the culprit; and (ii) preventing the innocent user from accusation and punishment. Fingerprinting techniques provide a mechanism for classifying the guilty agent from multiple recipients and also help to prevent the innocent user from being accused of the data breach. To those ends, in this paper, a novel fingerprinting framework has been proposed using a biometric feature as a digital mark (signature). The use of machine learning has also been introduced to make this framework intelligent, particularly for preserving the data usability. An attack channel has also been used to evaluate the robustness of the proposed scheme. The experimental study was also conducted to demonstrate that the proposed technique is robust against several malicious attacks, such as subset selection attacks, mix and match attacks, collusion attacks, deletion attacks, insertion attacks, and alteration attacks.
Performance Analysis of LDS Multi Access Technique and New 5G Waveforms for V2X Communication
Authors: Khelouani Imane , Elbahhar Fouzia , Elassali Raja , Idboufker Noureddine
Published: July 2020

Low Density Signature (LDS) is an emerging non-orthogonal multiple access (NOMA) technique that has never been evaluated under a vehicular channel in order to simulate the environment of a vehicle to everything (V2X) communication. Moreover, the LDS structure has been combined with only Orthogonal Frequency Division Multiplexing (OFDM) and Filter-Bank Multi-Carrier (FBMC) waveforms to improve its performances. In this paper, we propose new schemes where the LDS structure is combined with Universal Filtered Multi-Carrier (UFMC) and Filtered-OFDM waveforms and the Bit Error Rate (BER) is analysed over a frequency selective channel as a reference and over a vehicular channel to analyse the effect of the Doppler shift on the overall performance.
Source Apportionment and Integrated Assessment Modelling for Air Quality Planning
Authors: De Angelis Elena , Carnevale Claudio , Turrini Enrico , Volta Marialuisa
Published: July 2020

In Northern Italy a large fraction of the population is exposed to PM10 and PM2.5 concentrations that exceed the European limit values and the stricter WHO air quality guidelines. For this reason, in 2017 four Regions (Piemonte, Lombardia, Veneto, and Emilia Romagna) and the national Ministry of the Environment adopted a set of joint measures, namely the “Po Basin air quality plan”. The plan mainly tackles emission from road transport, residential heating, and agriculture. Air quality plans at regional and local scale are usually implemented defining a set of emission abatement measures, starting from experts’ knowledge. The aim of this work is to define a methodology that helps decision makers in air quality planning, combining two different approaches: Source-Apportionment techniques (SA) and Integrated Assessment Modelling (IAM). These techniques have been applied over a domain in Northern Italy to analyze the contribution of emission sources on PM10 concentration and to compute an optimal policy, obtained through a multi-objective optimization approach that minimizes both the PM10 yearly average concentration and the policy implementation costs. The results are compared to the Po Basin air quality plan impacts. The source-apportionment technique and the IAM optimization approach show intervention priorities in three main sectors: residential heating, agriculture, and road transport. The Po Basin air quality plan is effective in reducing PM10 concentrations, but not efficient, as a matter of fact the cost-effective policy at the same cost has a higher impact on air quality and on greenhouse gases emissions reduction.
Landscape Preference for Trees Outside Forests along an Urban–Rural–Natural Gradient
Authors: Di Cristofaro Marco , Sallustio Lorenzo , Sitzia Tommaso , Marchetti Marco , Lasserre Bruno
Published: July 2020

In densely populated areas, essential sources of ecosystem services are represented by green infrastructure, which includes trees outside forests (TOF) that, regardless of their cover extension, are found on agricultural or urban land. This research aims to assess landscape preference for TOF along an urban-rural-natural gradient in relation to different levels of landscape heterogeneity. Analyses are based on the integration of a visual choice experiment (360 respondents) with a GIS-based landscape analysis at regional scale in a Mediterranean region in Central Italy. Main findings revealed that correlation between landscape preference and heterogeneity varies along the urban–rural–natural gradient and on the basis of the spatial configuration of the surrounding landscape. The additional value of TOF to landscape preference is closely and positively linked to the degree of landscape anthropization. Conversely, TOF contribution to landscape preference resulted negative in natural landscapes where they can be perceived as a disturbance of the wilderness. Considering the influence that landscape preference plays on cultural ecosystem services provisioning and, in turn, on decision making processes, our results can support landscape policy and planning in fostering or hampering TOF diffusion depending on the different territorial contexts. These findings endorse the importance of multi-functional approaches in future-oriented strategies, which should mediate between the human preference for TOF, their ecological role and the provision of other services.
Short-Term Recovery of Residual Tree Damage during Successive Thinning Operations
Authors: Tavankar Farzam , Nikooy Mehrdad , Lo Monaco Angela , Latterini Francesco , Venanzi Rachele , Picchio Rodolfo
Published: July 2020

In this study, damage to residual trees during thinning performed by motor-manual felling and whole tree skidding was studied in a loblolly pine (Pinus taeda L.) plantation. Forest intervention was carried out in 2016 and tree wounds were studied and examined over a period of three years. The results indicated that 8% of the residual trees suffered damage, of which 52% was caused by felling operations and 48% by extraction operations. Among the damaged trees, 13% had damage to the root system, 53% to the bole, and 34% to the crown area. The average wound size at the time of occurrence was 71.3 cm2. This was found to be reduced to 54.4 cm2 after a three year period. Wound intensity decreased with higher wound height and increased size. Three years after wound occurrence, only 6.6% were closed, 90.6% were still open, and 2.8% were decayed. The diameter growth in damaged trees was 1.7% lower than in undamaged trees (p > 0.05). Damage to the root system of residual trees reduced diameter growth by 3% (p < 0.05). Intensive wounds (damaged wood) caused a reduction of 22.7% in diameter growth (p < 0.01). In addition, the diameter growth in trees with decayed wounds was 27.4% lower than unwounded trees (p < 0.01). Pre-harvest planning, directional tree felling, marking of the extraction path before logging operations, employment of skilled logging workers, and post-harvest assessment of damaged residual trees are essential implementations in timber plantations.
Acceptance of Fresh Pasta with β-Glucan Addition: Expected Versus Perceived Liking
Authors: Jaworska Danuta , Królak Maria , Przybylski Wiesław , Jezewska-Zychowicz Marzena
Published: July 2020

The aim was to recognize the effect of oat β-glucan fiber addition on expected and perceived liking of fresh pasta. Durum wheat semolina was enriched with oat β-glucan fiber in proportions: 0, 4, 8, 12 and 16% in relation to wheat flour. The evaluation of pasta samples was carried out by a group of 150 consumers and 10 panelists. Consumers evaluated pasta samples to assess the expected and perceived liking and the trained panelists established sensory profile.The consumers’ evaluation of cooked pasta with different oat β-glucan fiber additions showed that the sample with 16% oat β-glucan fiber addition was most liked (6.4 in a 1–9 scale). Consistency between expected and perceived liking increased with the increase in oat β-glucan fiber addition and was the highest for the sample enriched with 16% β-glucan. The sensory profile established by the trained panelists compared with the results of the consumers’ assessment showed that an increase in intensity of bran odor and flavor (up to value 4.08 for odor note and 5.31 for flavor) could have been related to higher perceived liking by the consumers. The increased amount of oat β-glucan fiber powder (16%), which provides fiber-rich products, is a promising ingredient for fresh pasta formulation.
Multiple Correspondence and Hierarchical Cluster Analyses for the Profiling of Fresh Apple Customers Using Data from Two Marketplaces
Authors: Bejaei Masoumeh , Cliff Margaret A. , Singh Amritpal
Published: July 2020

Purchase behavior and preferences for consumers of fresh apples were investigated using a consumer survey conducted at a special-event apple market. Survey respondents were asked to list apple cultivars they had purchased at the retail market and the special-event market. The special-event market offered many uncommon cultivars packed in clear plastic bags with a fixed weight and price. Respondents were also asked to identify their reasons for selection of each apple cultivar and answer demographic questions. A total of 169 customers completed the survey. Profiles of customers were identified using multiple correspondence analysis (MCA) and hierarchical cluster analysis (HCA), and the impact of the change in available apple cultivars on consumers’ purchase behavior was explored. Consumers primarily indicated four main reasons in the selection of their apples: visual appearance, previous experience, taste/aroma, and texture. The first two reasons, evaluated before eating an apple, were loaded on the first MCA dimension, while the last two reasons (i.e., eating quality) were loaded on the second dimension in data from both marketplaces. HCA identified five classes of customers in both markets, and results indicated that similar market segments existed within the two marketplaces, regardless of the availability of apple cultivars.
Non-Targeted Detection of Adulterants in Almond Powder Using Spectroscopic Techniques Combined with Chemometrics
Authors: Faqeerzada Mohammad Akbar , Lohumi Santosh , Joshi Rahul , Kim Moon S. , Baek Insuck , Cho Byoung-Kwan
Published: July 2020

Methods that combine targeted techniques and chemometrics for analyzing food authenticity can only facilitate the detection of predefined or known adulterants, while unknown adulterants cannot be detected using such methods. Therefore, the non-targeted detection of adulterants in food products is currently in great demand. In this study, FT-IR and FT-NIR spectroscopic techniques were used in combination with non-targeted chemometric approaches, such as one-class partial least squares (OCPLS) and data-driven soft independent modeling of class analogy (DD-SIMCA), to detect adulterants in almond powder adulterated with apricot and peanut powders. The reflectance spectra of 100 pure almond powder samples from two different varieties (50 each) were collected to develop a calibration model based on each spectroscopic technique; each model was then evaluated for four independent sets of two varieties of almond powder samples adulterated with different concentrations of apricot and peanut powders. Classification using both techniques was highly sensitive, the OCPLS approach yielded 90–100% accuracy in different varieties of samples with both spectroscopic techniques, and the DD-SIMCA approach achieved the highest accuracy of 100% when used in combination with FT-IR in all validation sets. Moreover, DD-SIMCA, combined with FT-NIR, achieved a detection accuracy between 91% and 100% for the different validation sets and the misclassified samples belong to the 5% and 7% adulteration sets. These results suggest that spectroscopic techniques, combined with one-class classifiers, can be used effectively in the high-throughput screening of potential adulterants in almond powder.
Fabrication of Concentrated Palm Olein-Based Diacylglycerol Oil–Soybean Oil Blend Oil-In-Water Emulsion: In-Depth Study of the Rheological Properties and Storage Stability
Authors: Ng Siou Pei , Khor Yih Phing , Lim Hong Kwong , Lai Oi Ming , Wang Yong , Wang Yonghua , Cheong Ling Zhi , Arbi Nehdi Imededdine , Mansour Lamjed , Ping Tan Chin
Published: July 2020

The present study focused on investigating the storage stability of oil-in-water (O/W) emulsions with high oil volume fractions prepared with palm olein-based diacylglycerol oil (POL-DAG)/soybean oil (SBO) blends at 25 °C. The incorporation of different ratios of oil blends significantly influenced (p < 0.05) the texture, color, droplet size distribution, and rheological parameters of the emulsions. Only emulsions incorporated with 10% to 20% POL-DAG in oil phase exhibited pseudoplastic behavior that fitted the Power Law model well. Furthermore, the O/W emulsions prepared with POL-DAG/SBO blends exhibited elastic properties, with G’ higher than G”. During storage, the emulsion was found to be less solid-like with the increase in tan δ values. All emulsions produced with POL-DAG/SBO blends also showed thixotropic behavior. Optical microscopy revealed that the POL-DAG incorporation above 40% caused aggregated droplets to coalesce and flocculate and, thus, larger droplet sizes were observed. The current results demonstrated that the 20% POL-DAG substituted emulsion was more stable than the control emulsion. The valuable insights gained from this study would be able to generate a lot more possible applications using POL-DAG, which could further sustain the competitiveness of the palm oil industry.
Thermoresponsive Nanogels Based on Different Polymeric Moieties for Biomedical Applications
Authors: Ghaeini-Hesaroeiye Sobhan , Razmi Bagtash Hossein , Boddohi Soheil , Vasheghani-Farahani Ebrahim , Jabbari Esmaiel
Published: July 2020

Nanogels, or nanostructured hydrogels, are one of the most interesting materials in biomedical engineering. Nanogels are widely used in medical applications, such as in cancer therapy, targeted delivery of proteins, genes and DNAs, and scaffolds in tissue regeneration. One salient feature of nanogels is their tunable responsiveness to external stimuli. In this review, thermosensitive nanogels are discussed, with a focus on moieties in their chemical structure which are responsible for thermosensitivity. These thermosensitive moieties can be classified into four groups, namely, polymers bearing amide groups, ether groups, vinyl ether groups and hydrophilic polymers bearing hydrophobic groups. These novel thermoresponsive nanogels provide effective drug delivery systems and tissue regeneration constructs for treating patients in many clinical applications, such as targeted, sustained and controlled release.
Knockout of Pi21 by CRISPR/Cas9 and iTRAQ-Based Proteomic Analysis of Mutants Revealed New Insights into M. oryzae Resistance in Elite Rice Line
Authors: Nawaz Gul , Usman Babar , Peng Haowen , Zhao Neng , Yuan Ruizhi , Liu Yaoguang , Li Rongbai
Published: July 2020

Rice blast (Magnaporthe oryzae) is a devastating disease affecting rice production globally. The development of cultivars with host resistance has been proved to be the best strategy for disease management. Several rice-resistance genes (R) have been recognized which induce resistance to blast in rice but R gene-mediated mechanisms resulting in defense response still need to be elucidated. Here, mutant lines generated through CRISPR/Cas9 based targeted mutagenesis to investigate the role of Pi21 against blast resistance and 17 mutant plants were obtained in T0 generation with the mutation rate of 66% including 26% bi-allelic, 22% homozygous, 12% heterozygous, and 3% chimeric and 17 T-DNA-free lines in T1 generation. The homozygous mutant lines revealed enhanced resistance to blast without affecting the major agronomic traits. Furthermore, comparative proteome profiling was adopted to study the succeeding proteomic regulations, using iTRAQ-based proteomic analysis. We identified 372 DEPs, among them 149 up and 223 were down-regulated, respectively. GO analysis revealed that the proteins related to response to stimulus, photosynthesis, carbohydrate metabolic process, and small molecule metabolic process were up-regulated. The most of DEPs were involved in metabolic, ribosomal, secondary metabolites biosynthesis, and carbon metabolism pathways. 40S ribosomal protein S15 (P31674), 50S ribosomal protein L4, L5, L6 (Q10NM5, Q9ZST0, Q10L93), 30S ribosomal protein S5, S9 (Q6YU81, Q850W6, Q9XJ28), and succinate dehydrogenase (Q9S827) were hub-proteins. The expression level of genes related to defense mechanism, involved in signaling pathways of jasmonic acid (JA), salicylic acid (SA), and ethylene metabolisms were up-regulated in mutant line after the inoculation of the physiological races of M. oryzae as compared to WT. Our results revealed the fundamental value of genome editing and expand knowledge about fungal infection avoidance in rice.
Atypical Genotypes for Canine Agouti Signaling Protein Suggest Novel Chromosomal Rearrangement
Authors: Dreger Dayna , Anderson Heidi , Donner Jonas , Clark Jessica , Dykstra Arlene , Hughes Angela , Ekenstedt Kari
Published: July 2020

Canine coat color is a readily observed phenotype of great interest to dog enthusiasts; it is also an excellent avenue to explore the mechanisms of genetics and inheritance. As such, multiple commercial testing laboratories include basic color alleles in their popular screening panels, allowing for the creation of genotyped datasets at a scale not before appreciated in canine genetic research. These vast datasets have revealed rare genotype anomalies that encourage further exploration of color and pattern inheritance. We previously reported the simultaneous presence of greater than two allele variants at the Agouti Signaling Protein (ASIP) locus in a commercial genotype cohort of 11,790 canids. Here we present additional data to characterize the occurrence of anomalous ASIP genotypes. We document the detection of combinations of three or four ASIP allele variants in 17 dog breeds and Dingoes, at within-breed frequencies of 1.32–63.34%. We analyze the potential impact on phenotype that these allele combinations present, and propose mechanisms that could account for the findings, including: gene recombination, duplication, and incorrect causal variant identification. These findings speak to the accuracy of industry-wide protocols for commercial ASIP genotyping and imply that ASIP should be analyzed via haplotype, rather than using only the existing allele hierarchy, in the future.
Genomic Comparison of Insect Gut Symbionts from Divergent Burkholderia Subclades
Authors: Takeshita Kazutaka , Kikuchi Yoshitomo
Published: July 2020

Stink bugs of the superfamilies Coreoidea and Lygaeoidea establish gut symbioses with environmentally acquired bacteria of the genus Burkholderia sensu lato. In the genus Burkholderia, the stink bug-associated strains form a monophyletic clade, named stink bug-associated beneficial and environmental (SBE) clade (or Caballeronia). Recently, we revealed that members of the family Largidae of the superfamily Pyrrhocoroidea are associated with Burkholderia but not specifically with the SBE Burkholderia; largid bugs harbor symbionts that belong to a clade of plant-associated group of Burkholderia, called plant-associated beneficial and environmental (PBE) clade (or Paraburkholderia). To understand the genomic features of Burkholderia symbionts of stink bugs, we isolated two symbiotic Burkholderia strains from a bordered plant bug Physopellta gutta (Pyrrhocoroidea: Largidae) and determined their complete genomes. The genome sizes of the insect-associated PBE (iPBE) are 9.5 Mb and 11.2 Mb, both of which are larger than the genomes of the SBE Burkholderia symbionts. A whole-genome comparison between two iPBE symbionts and three SBE symbionts highlighted that all previously reported symbiosis factors are shared and that 282 genes are specifically conserved in the five stink bug symbionts, over one-third of which have unknown function. Among the symbiont-specific genes, about 40 genes formed a cluster in all five symbionts; this suggests a “symbiotic island” in the genome of stink bug-associated Burkholderia.
Precision and Personalized Medicine: How Genomic Approach Improves the Management of Cardiovascular and Neurodegenerative Disease
Authors: Strianese Oriana , Rizzo Francesca , Ciccarelli Michele , Galasso Gennaro , D’Agostino Ylenia , Salvati Annamaria , Del Giudice Carmine , Tesorio Paola , Rusciano Maria Rosaria
Published: July 2020

Life expectancy has gradually grown over the last century. This has deeply affected healthcare costs, since the growth of an aging population is correlated to the increasing burden of chronic diseases. This represents the interesting challenge of how to manage patients with chronic diseases in order to improve health care budgets. Effective primary prevention could represent a promising route. To this end, precision, together with personalized medicine, are useful instruments in order to investigate pathological processes before the appearance of clinical symptoms and to guide physicians to choose a targeted therapy to manage the patient. Cardiovascular and neurodegenerative diseases represent suitable models for taking full advantage of precision medicine technologies applied to all stages of disease development. The availability of high technology incorporating artificial intelligence and advancement progress made in the field of biomedical research have been substantial to understand how genes, epigenetic modifications, aging, nutrition, drugs, microbiome and other environmental factors can impact health and chronic disorders. The aim of the present review is to address how precision and personalized medicine can bring greater clarity to the clinical and biological complexity of these types of disorders associated with high mortality, involving tremendous health care costs, by describing in detail the methods that can be applied. This might offer precious tools for preventive strategies and possible clues on the evolution of the disease and could help in predicting morbidity, mortality and detecting chronic disease indicators much earlier in the disease course. This, of course, will have a major effect on both improving the quality of care and quality of life of the patients and reducing time efforts and healthcare costs.
Psychological Capital Mediates the Association between Job Stress and Burnout of among Korean Psychiatric Nurses
Authors: Kim Sooyeong , Kweon YoungRan
Published: July 2020

This study examined the mediating effect of psychological capital in the relationship between job stress and burnout of psychiatric nurses. The participants were 108 psychiatric nurses working in three psychiatric hospitals located in South Korea. Data were collected from 10 August to 15 September 2018 using self-report questionnaires. Data were analyzed using descriptive statistics, t-test, one-way ANOVA, Pearson’s correlation coefficient, and multiple linear regression by IBM SPSS 24.0 program. In addition, a bootstrapping test using the SPSS PROCESS macro was conducted to test the statistical significance of the mediating effect. There was significant correlation between job stress, psychological capital, and burnout. Psychological capital showed partial mediating effects in the relationship between job stress and burnout. Job stress explained 29.7% of the variance in burnout, and the model including job stress and psychological capital explained 49.6% of the variance in burnout. The bootstrapping showed that psychological capital was a significant sub-parameter and decreased job stress and burnout (LLCI = −0.1442, ULCI = −0.3548). These findings suggest that psychiatric nurses’ burnout can be reduced by implementing various health care programs designed to increase psychological capital.
Antidiabetic Agents for Treatment of Parkinson’s Disease: A Meta-Analysis
Authors: Wang Shu-Yi , Wu Shey-Lin , Chen Ta-Cheng , Chuang Chieh-Sen
Published: July 2020

Background: Clinical and epidemiological studies suggest that two of the most common geriatric diseases, type 2 diabetes and Parkinson’s disease (PD), are linked. These studies notably suggest that treatment of insulin resistance in type 2 diabetes may beneficially modify the pathophysiology of PD and help to maintain motor and nonmotor function. In this meta-analysis, we evaluate the efficacy of new antidiabetic agents in the treatment of PD. Methods: We systematically searched PubMed, Medline, ProQuest, ScienceDirect, ClinicalKey, and Cochrane Library from the date of their inception until 15 March 2020. Multiple efficacy parameters were compared between treatment groups. The results are expressed as mean differences with 95% confidence intervals (CIs) in a random-effects model. Results: A meta-analysis of the data extracted from three randomized control trials revealed that treatment with exenatide yielded significant improvements in scores on the Unified Parkinson’s Disease Rating Scale Part I (UPDRS-I) (−0.438, 95% CI, −0.828 to −0.048, p = 0.028), UPDRS Part IV (UPDRS-IV) (−0.421, 95% CI, −0.811 to −0.032, p = 0.034) and the Mattis Dementia Rating Scale (MDRS) (−0.595, 95% CI, −1.038 to −0.151, p = 0.009). At the 12-month follow-up, the UPDRS Part III (UPDRS-III) scores in the off-medication phase revealed significant improvements in patients using exenatide (−0.729; 95% CI, −1.233 to −0.225, p = 0.005). Treatment with pioglitazone did not yield significant improvements in UPDRS, MDRS, or Parkinson’s Disease Questionnaire scores. Conclusion: This meta-analysis suggests that exenatide use is associated with the alleviation of cognitive, motor and nonmotor symptoms. However, long-term studies with a large sample size of patients with PD of varying severity are required.
Changes in the Type of Sports Activity Due to COVID-19: Hypochondriasis and the Intention of Continuous Participation in Sports
Authors: Choi Chulhwan , Bum Chul-Ho
Published: July 2020

This study focused on empirically analyzing sport activity participants’ perceptions of hypochondriasis caused by fear of infection and changes in continuous participatory behavior patterns. To this end, a comparative analysis was conducted with a focus on the forms of participation and age of sport activity participants. For the final comparative analysis, a 2 × 3 factorial multivariate analysis of variance was conducted after confirming the validity and reliability of data based on 229 questionnaires collected from healthy respondents who have never been infected with COVID-19. The results showed statistically significant differences between worry about illness, which is a subscale of hypochondriasis, disease phobia, thanatophobia, and intent to continue according to age. Statistically significant differences were also found when considering the type of sport for worry about illness, which is a subscale of hypochondriasis, disease phobia, symptom preoccupation, and intent to continue. Furthermore, interaction effects between the two independent variables, i.e., age and type of sport, were found for disease phobia, a subscale of hypochondriasis, and thanatophobia. In summary, age and type of sport, which are important factors for the COVID-19 infection and symptoms, were found to affect the sport activity patterns. These results proved that COVID-19 may have caused the participants to have different perceptions depending on their characteristics and change their form of continuous participation. These findings will provide useful data for predicting the perception and behavioral patterns of sports participants if diseases like COVID-19 occur in the future. They also show how to live a healthy life through exercise.
How Much Space Is Required? Effect of Distance, Content, and Color on External Human–Machine Interface Size
Authors: Rettenmaier Michael , Schulze Jonas , Bengler Klaus
Published: July 2020

The communication of an automated vehicle (AV) with human road users can be realized by means of an external human–machine interface (eHMI), such as displays mounted on the AV’s surface. For this purpose, the amount of time needed for a human interaction partner to perceive the AV’s message and to act accordingly has to be taken into account. Any message displayed by an AV must satisfy minimum size requirements based on the dynamics of the road traffic and the time required by the human. This paper examines the size requirements of displayed text or symbols for ensuring the legibility of a message. Based on the limitations of available package space in current vehicle models and the ergonomic requirements of the interface design, an eHMI prototype was developed. A study involving 30 participants varied the content type (text and symbols) and content color (white, red, green) in a repeated measures design. We investigated the influence of content type on content size to ensure legibility from a constant distance. We also analyzed the influence of content type and content color on the human detection range. The results show that, at a fixed distance, text has to be larger than symbols in order to maintain legibility. Moreover, symbols can be discerned from a greater distance than text. Color had no content overlapping effect on the human detection range. In order to ensure the maximum possible detection range among human road users, an AV should display symbols rather than text. Additionally, the symbols could be color-coded for better message comprehension without affecting the human detection range.
Structure: Function Studies of the Cytosolic, Mo- and NAD+-Dependent Formate Dehydrogenase from Cupriavidus necator
Authors: Hille Russ , Young Tynan , Niks Dimitri , Hakopian Sheron , Tam Timothy K. , Yu Xuejun , Mulchandani Ashok , Blaha Gregor M.
Published: July 2020

Here, we report recent progress our laboratories have made in understanding the maturation and reaction mechanism of the cytosolic and NAD+-dependent formate dehydrogenase from Cupriavidus necator. Our recent work has established that the enzyme is fully capable of catalyzing the reverse of the physiological reaction, namely, the reduction of CO2 to formate using NADH as a source of reducing equivalents. The steady-state kinetic parameters in the forward and reverse directions are consistent with the expected Haldane relationship. The addition of an NADH-regenerating system consisting of glucose and glucose dehydrogenase increases the yield of formate approximately 10-fold. This work points to possible ways of optimizing the reverse of the enzyme’s physiological reaction with commercial potential as an effective means of CO2 remediation. New insight into the maturation of the enzyme comes from the recently reported structure of the FdhD sulfurase. In E. coli, FdhD transfers a catalytically essential sulfur to the maturing molybdenum cofactor prior to insertion into the apoenzyme of formate dehydrogenase FdhF, which has high sequence similarity to the molybdenum-containing domain of the C. necator FdsA. The FdhD structure suggests that the molybdenum cofactor may first be transferred from the sulfurase to the C-terminal cap domain of apo formate dehydrogenase, rather than being transferred directly to the body of the apoenzyme. Closing of the cap domain over the body of the enzymes delivers the Mo-cofactor into the active site, completing the maturation of formate dehydrogenase. The structural and kinetic characterization of the NADH reduction of the FdsBG subcomplex of the enzyme provides further insights in reversing of the formate dehydrogenase reaction. Most notably, we observe the transient formation of a neutral semiquinone FMNH·, a species that has not been observed previously with holoenzyme. After initial reduction of the FMN of FdsB by NADH to the hydroquinone (with a kred of 680 s−1 and Kd of 190 µM), one electron is rapidly transferred to the Fe2S2 cluster of FdsG, leaving FMNH·. The Fe4S4 cluster of FdsB does not become reduced in the process. These results provide insight into the function not only of the C. necator formate dehydrogenase but also of other members of the NADH dehydrogenase superfamily of enzymes to which it belongs.
Floral Resources for Trissolcus japonicus, a Parasitoid of Halyomorpha halys
Authors: McIntosh Hanna R. , Skillman Victoria P. , Galindo Gracie , Lee Jana C.
Published: July 2020

The egg parasitoid Trissolcus japonicus is the main candidate for classical biocontrol of the invasive agricultural pest Halyomorpha halys. The efficacy of classical biocontrol depends on the parasitoid’s survival and conservation in the agroecosystem. Most parasitoid species rely on floral nectar as a food source, thus identifying nectar sources for T. japonicus is critical. We evaluated the impact of eight flowering plant species on T. japonicus survival in the lab by exposing unfed wasps to flowers inside vials. We also measured the wasps’ nutrient levels to confirm feeding and energy storage using anthrone and vanillin assays adapted for T. japonicus. Buckwheat, cilantro, and dill provided the best nectar sources for T. japonicus by improving median survival by 15, 3.5, and 17.5 days compared to water. These three nectar sources increased wasps’ sugar levels, and cilantro and dill also increased glycogen levels. Sweet alyssum, marigold, crimson clover, yellow mustard, and phacelia did not improve wasp survival or nutrient reserves. Further research is needed to determine if these flowers maintain their benefits in the field and whether they will increase the parasitism rate of H. halys.
Pain and Oral-Health-Related Quality of Life in Orthodontic Patients During Initial Therapy with Conventional, Low-Friction, and Lingual Brackets and Aligners (Invisalign): A Prospective Clinical Study
Authors: Antonio-Zancajo Laura , Montero Javier , Albaladejo Alberto , Oteo-Calatayud Maria Dolores , Alvarado-Lorenzo Alfonso
Published: July 2020

The aim of this study was to compare pain and its relationship with the oral quality of life of patients with different types of orthodontic appliances: conventional and conventional low-friction brackets, lingual brackets, and aligners. A prospective clinical study was carried out with a sample size of 120 patients (54 men, 66 women) divided into 4 groups of 30 patients each. The modified McGill questionnaire was used to measure pain at 4, 8, and 24 h and 2, 3, 4, 5, 6, and 7 days after the start of treatment, and the Oral Health Impact Profile-14 (OHIP-14) questionnaire was used to measure the oral-health-related quality of life (OHRQoL) in the first month of treatment. The maximum peak of pain was obtained between 24 and 48 h of treatment. It was found that patients in the lingual orthodontic group described lower levels of pain at all times analyzed, and their scores in the total OHIP-14 indicated less impact on their oral quality of life (1.3 ± 1.2, p < 0.01) compared with the other groups analyzed. There was little difference with the aligners group (Invisalign) (1.7 ± 1.9, p < 0.01). The technique used influences the pain and quality of life of patients at the start of orthodontic treatment.