bluuebunny/crossref_metadata_2025 huggingface dataset:
Intersection of Data Science and Smart Destinations: A Systematic Review
Authors: Aguirre Montero Alexander , López-Sánchez José Antonio
Published: July 2021

This systematic review adopts a formal and structured approach to review the intersection of data science and smart tourism destinations in terms of components found in previous research. The study period corresponds to 1995–2021 focusing the analysis mainly on the last years (2015–2021), identifying and characterizing the current trends on this research topic. The review comprises documentary research based on bibliometric and conceptual analysis, using the VOSviewer and SciMAT software to analyze articles from the Web of Science database. There is growing interest in this research topic, with more than 300 articles published annually. Data science technologies on which current smart destinations research is based include big data, smart data, data analytics, social media, cloud computing, the internet of things (IoT), smart card data, geographic information system (GIS) technologies, open data, artificial intelligence, and machine learning. Critical research areas for data science techniques and technologies in smart destinations are public tourism marketing, mobility-accessibility, and sustainability. Data analysis techniques and technologies face unprecedented challenges and opportunities post-coronavirus disease-2019 (COVID-19) to build on the huge amount of data and a new tourism model that is more sustainable, smarter, and safer than those previously implemented.
Adapting Blood DNA Methylation Aging Clocks for Use in Saliva Samples With Cell-type Deconvolution
Authors: Galkin Fedor , Kochetov Kirill , Mamoshina Polina , Zhavoronkov Alex
Published: July 2021

DeepMAge is a deep-learning DNA methylation aging clock that measures the organismal pace of aging with the information from human epigenetic profiles. In blood samples, DeepMAge can predict chronological age within a 2.8 years error margin, but in saliva samples, its performance is drastically reduced since aging clocks are restricted by the training set domain. However, saliva is an attractive fluid for genomic studies due to its availability, compared to other tissues, including blood. In this article, we display how cell type deconvolution and elastic net can be used to expand the domain of deep aging clocks to other tissues. Using our approach, DeepMAge’s error in saliva samples was reduced from 20.9 to 4.7 years with no retraining.
The Vernacular and Rural Houses of Agrarian Areas in the Zeta Region, Montenegro
Authors: Skataric Goran , Spalevic Velibor , Popovic Svetislav , Perosevic Nenad , Novicevic Rajko
Published: July 2021

Architectural quality and preservation of rural characteristics is a goal of building design for sustainable environments. The environment has a different function for different societies, creating a large variety of meanings. In the Zeta region of Montenegro, the negative transformation of the rural environment is happening more rapidly than the recording of its traditional built assets. Protection and conservation of traditional rural architecture in this rural region of south-eastern Europe are important to both mitigation of the consequences of unsustainable rural shifts and the preservation of cultural heritage. This research focuses on the meaning of the different dwelling and residential environment features for the residents of the traditional houses of the rural areas of the Zeta region, Montenegro. The aim of the research was to obtain more insight and information on the meaning of architectural and rural design features by exploring the sustainability-related characteristics of traditional rural houses in the so-far insufficiently studied micro-region of the western Balkans to reveal their value and to initiate discussion of the role of heritage regeneration in sustainable rural development. Fifty (50) traditional houses of agrarian and rural areas of the Zeta region of Montenegro were observed and analysed in terms of the building site, space planning of the interior space, and building materials used. The analysis has revealed that many ecological aspects were taken into consideration and different methods were implemented during the construction of the traditional houses of the Zeta region. Taking into consideration the age of those structures, the constructors did not have an in-depth awareness of sustainability theories, and they were acting based on their personal practices and specific environmental requirements. This study’s results can help update a database of sustainability for the traditional architectural heritage of Montenegro, which will enhance the process of creating sustainable buildings without losing the place identity and staying in the same cultural context. Restoration of the traditional houses of the Zeta region of Montenegro, but also of the other rural areas of Montenegro, must in future be defined in a way that enables the preservation of recognized general values and further improvement of environmental quality and climate resilience. Simultaneously, functional reactivation of traditional houses should be understood as a contribution to the sustainable development of the studied region of Montenegro.
Seroprevalence of Toxoplasma gondii and Salmonella in Hunted Wild Boars from Two Different Regions in Switzerland
Authors: Bassi Alessia Maria Giuseppina , Steiner Janine Carmen , Stephan Roger , Nüesch-Inderbinen Magdalena
Published: July 2021

Toxoplasma gondii and Salmonella are zoonotic foodborne pathogens that may be transmitted to humans through the consumption of raw or undercooked meat, including game. The aim of this study was to determine the seroprevalence of T. gondii and Salmonella antibodies in wild boars in two different regions in Switzerland. During the hunting season of 2020, a total of 126 diaphragm muscle samples of hunted wild boars were collected and the meat juice of these samples was analysed for pathogen-specific IgG antibodies using commercial enzyme-linked immunosorbent assay (ELISA) kits. The overall seroprevalences were 35% for T. gondii and 17% for Salmonella, respectively. In general, seropositivity increased with the age of the animals. Seroprevalences of T. gondii were similar for animals from the northern region (29%) to those from the southern region (36.8%), indicating that T. gondii is widespread in the sylvestrian environment. By contrast, Salmonella seropositivity was remarkably higher in wild boars from the north (52%) compared with those from the south (5.3%). The high occurrence of Salmonella may represent a risk of transmission to compatriot domestic animals such free-range farmed pigs as well as to humans. Further, meat of hunted wild boars may present a source of human toxoplasmosis or salmonellosis.
Transport and Recovery of Turbot (Scophthalmus maximus) Sedated with MS-222 and Eugenol: Effects on Intermediary Metabolism and Osmoregulation
Authors: Cao Jie , Wang Qi , Qiu Weiqiang , Mei Jun , Xie Jing
Published: July 2021

This study focused on the anesthetic waterless keep-alive transport technique for turbot. MS-222 and eugenol were used to anesthetize turbot and then the waterless keep-alive transport was conducted. The blood physiological changes and flesh quality changes of turbot were evaluated after cooling and during the simulated waterless transport. The results show that the temperature lowered from 13 to 2 °C, resulting in a decrease in moisture, fat and protein contents of all samples. Compared to the control turbot, the turbots treated with MS-222 and eugenol presented higher pH and glycogen content. During the simulated waterless transport, the pH, ATP and glycogen contents in MS-222- and eugenol-treated turbots decreased and the IMP and lactate levels increased. For the blood biochemical indices, blood glucose, cortisol and urea nitrogen increased with the increase in transport time in MS-222- and eugenol-treated turbots. At sampling time, the changes in blood physiological indices were significantly higher in the control samples than those in the MS-222- and eugenol-treated samples. The results indicate that the turbot samples treated with MS-222 or eugenol could reduce stress during cooling and simulated waterless transport.
Evaluation of Dietary Probiotic (Lactobacillus plantarum BG0001) Supplementation on the Growth Performance, Nutrient Digestibility, Blood Profile, Fecal Gas Emission, and Fecal Microbiota in Weaning Pigs
Authors: Wang Huan , Kim In-Ho
Published: July 2021

A total of 180, 4-week-old crossbred weaning piglets ((Yorkshire × Landrace) × Duroc; 6.67 ± 1.40 kg) were used in a 42 day experiment to evaluate the effect of dietary probiotics (Lactobacillus plantarum BG0001) on growth performance, nutrient digestibility, blood profile, fecal microbiota, and noxious gas emission. All pigs were randomly allotted to one of four treatment diets in a completely randomized block design. Each treatment had nine replicates with five pigs/pen (mixed sex) Designated dietary treatments were as: (1) basal diet (NC), (2) NC + 0.2% antibiotics (chlortetracycline) (PC), (3) NC + 0.1% L. plantarum BG0001 (Lactobacillus plantarum BG0001) (NC1), (4) NC + 0.2% L. plantarum BG0001 (NC2). On d 42, BW and G:F were lower (p < 0.05) in pigs fed NC diet compared with PC diet and probiotic diets. Throughout this experiment, the average daily gain increased (p < 0.05) in pigs when fed with PC and probiotic diets than the NC diet. The average daily feed intake was higher (p < 0.05) in pigs fed PC diet during day 0–7 and 22–42, and probiotic diets during day 0–7 compared with NC diet, respectively. The Lactobacillus count was increased and Escherichia coli count was decreased (p < 0.05) in the fecal microbiota of pigs fed probiotic diets, and E. coli were decreased (p < 0.05) when fed a PC diet compared with the NC diet on day 21. Moreover, the apparent total tract nutrient digestibility, blood profile, and the concentration of noxious gas emission had no negative effects by the probiotic treatments. In conclusion, dietary supplementation with L. plantarum BG0001 significantly improved the growth performance, increased fecal Lactobacillus, and decreased E. coli counts in weaning pigs.
High Granulocyte-Macrophage Colony Stimulating Factor to Interleukin 10 Ratio and Marked Antioxidant Enzyme Activities Predominate in Symptomatic Cattle Naturally Infected with Candidatus Mycoplasma haemobos, Theileria orientalis, Theileria sinensis and Trypanosoma evansi
Authors: Agina Onyinyechukwu Ada , Cheah Kim Tho , Sayuti Nurul Syahirah Ahmad , Shaari Mohd Rosly , Isa Nur Mahiza Md , Ajat Mokrish , Zamri-Saad Mohd , Mazlan Mazlina , Hamzah Hazilawati
Published: July 2021

The aim of this study was to measure the serum proinflammatory (IL-12, GM-CSF & IFN-γ) to anti-inflammatory (IL-10, IL-4) cytokine ratio, oxidant (MDA) level and antioxidant enzyme (SOD; GPx) activities after blood parasite infections. The blood and serum samples were obtained from 130 cattle and screened for identity of the infecting blood parasites by conventional PCR. The following blood parasite species were detected: Candidatus Mycoplasma haemobos (70/130); Theileria orientalis (65/130); Theileria sinensis (32/130); Anaplasma marginale (49/130); Anaplasma platys (7/130); and Trypanosoma evansi (4/130). The GM-CSF/IL-10 ratio showed significantly higher values in all the symptomatic blood parasite infected cattle groups except for symptomatic A. platys infected cattle groups. Anti-inflammatory cytokine immune responses were notable findings in symptomatic and asymptomatic cattle infected with C. M. haemobos and T. orientalis characterized by low serum IL-12:IL-10, IFN-γ:IL-10, IL-12:IL-4 and IFN-γ:IL-4 (p < 0.05). Therefore, high serum GM-CSF:IL:10 in the symptomatic blood parasite infected cattle, low serum IL-12:IL-10, IFN-γ:IL-10, IL-12:IL-4 and IFN-γ:IL-4 ratios in asymptomatic cattle, high MDA level, and increased antioxidant enzyme activities could be useful predictive tools for outcome of natural blood parasite infections in cattle.
Annual Long-Distance Migration Strategies and Home Range of Chinese Sparrowhawk (Accipiter soloensis) from South China
Authors: Min Xiao , Gao Zijing , Lin Yuanfeng , Lu Chang-Hu
Published: July 2021

From 2018 to 2019, two Chinese Sparrowhawks (Bird 01, male; Bird 02, female), Accipiter soloensis, were captured and fitted with Global Positioning System (GPS) loggers in order to identify summering and wintering sites, migration routes, and stop-over sites. The Chinese Sparrowhawks were first fitted with backpack solar GPS satellite trackers in China in order to explore their migration routes. The two Chinese Sparrowhawks successfully completed their migration from southern China, through Nanning city of Guangxi province, China, to Vietnam, Laos, Myanmar, Thailand, Malaysia, and Singapore and finally arriving in Indonesia, where they stayed until the March of the following year. They then returned to China along the original route, arriving in Changsha city, Hunan province, China. The two individuals traveled more than 4000–5000 km. For the first time, telemetry data demonstrate, the linkages between their Indonesia wintering sites, their stop-over sites in Southeast Asia, and their breeding/summering sites near south Yangtze River in the south-central part of China. During this long-distance migration, 2653 bird satellite sites were received. The autumn migration durations for the two Chinese Sparrowhawks were 84 days and 50 days, respectively, compared to 83 days and 49 days in spring. The median stop-over duration was 12.7 and 9.3 days, respectively and the median speed of travel was 74.2 km/day during the autumn migration and 73.9 km/day during the spring migration. Furthermore, two and one stop-over sites and one and three stop-over sites were used during the autumn and spring migrations of Chinese Sparrowhawks 01 and 02, respectively. The Chinese Sparrowhawks migrated long distances and used stop-over sites during their migration. Based on the home range analysis, we can conclude that Chinese Sparrowhawks reach their maximum home range in the summer and have multiple nuclear domains.
An Efficient Method for the Euthanasia of Cane Toads (Rhinella marina) under Northern Australian Field Conditions
Authors: Kay Winston , Mawson Peter
Published: July 2021

The euthanasia of cane toads under field conditions presents a number of logistical and animal welfare challenges. One recommended method of control involves the use of carbon dioxide in plastic bags. This paper describes the minimum amount of time (4 h) required to efficiently euthanase toads with a carbon dioxide concentration of 4.96% under field conditions experienced in northern Australia. Discussion is also provided on the issues of safe disposal of biological and plastic waste associated with the application of this method.
Quercetin in Tartary Buckwheat Induces Autophagy against Protein Aggregations
Authors: Ikari Sumiko , Yang Qiang , Lu Shiou-Ling , Liu Yuancai , Hao Feike , Tong Guoqiang , Lu Shiguang , Noda Takeshi
Published: July 2021

Tartary buckwheat is used as an ingredient in flour and tea, as well as in traditional Chinese medicine for its antioxidant effects. Here, we found that an ethanol extract of tartary buckwheat (TBE) potently induced autophagy flux in HeLa cells by suppressing mTORC1 activity, as revealed by dephosphorylation of the mTORC1 substrates Ulk1, S6K, and 4EBP, as well as by the nuclear translocation of transcriptional factor EB. In addition to non-selective bulk autophagy, TBE also induced aggrephagy, which is defined as autophagy against aggregated proteins. Quercetin is a flavonol found at high levels in TBE. We showed that quercetin induced both non-selective bulk autophagy and aggrephagy. These effects were also observed in Huh-7 cells derived from hepatocytes. Thus, aggrephagy induction by TBE and quercetin may relieve alcoholic hepatitis, which is closely linked to the accumulation of protein aggregations called Mallory–Denk bodies.
Almond (Prunus dulcis cv. Casteltermini) Skin Confectionery By-Products: New Opportunity for the Development of a Functional Blackberry (Rubus ulmifolius Schott) Jam
Authors: Loizzo Monica R. , Tundis Rosa , Leporini Mariarosaria , D’Urso Gilda , Gagliano Candela Rossella , Falco Tiziana , Piacente Sonia , Bruno Maurizio , Sottile Francesco
Published: July 2021

This work proposes for the first time a model for reusing almond (Prunus dulcis cv. Casteltermini from Sicily, Southern Italy) skin to formulate a new functional blackberry (Rubus ulmifolius Schott) jam. For this purpose, blackberries were analysed fresh and as jam, traditionally prepared with a minimum fruit amount of 80%. Different percentages of almond skin (20, 15, and 10% w/w) were added to jam. The phytochemical profile of enriched jam was investigated by LC-ESI/LTQOrbitrap/MS analyses. Anthocyanins, hydrolysable tannins, and triterpenoids were identified in a blackberry extract, while proanthocyanidins, flavonoids, and oxylipins were identified in an almond extract. The n-hexane extract of P. dulcis skin, investigated by GC–MS, evidenced linoleic, palmitic, and oleic acids as the main abundant compounds. Samples were investigated for their antioxidant activity using DPPH, ABTS, β-carotene, and FRAP tests. The hypoglycaemic and hypolipidemic effects were studied by α-amylase, α-glucosidase, and lipase inhibitory assays. In order to evaluate the effect of thermal process on enriched jam bioactivity, pasteurisation was applied. An increase in activities for all samples was observed, in particular for jam enriched with 20% w/w of almond skin. Based on obtained data, and supported by sensory analysis, we propose enriched jam as a promising source of compounds useful for preventing diseases associated with oxidative stress.
Impact of EcSOD Perturbations in Cancer Progression
Authors: O’Leary Brianne R. , Carroll Rory S. , Steers Garett J. , Hrabe Jennifer , Domann Frederick E. , Cullen Joseph J.
Published: July 2021

Reactive oxygen species (ROS) are a normal byproduct of cellular metabolism and are required components in cell signaling and immune responses. However, an imbalance of ROS can lead to oxidative stress in various pathological states. Increases in oxidative stress are one of the hallmarks in cancer cells, which display an altered metabolism when compared to corresponding normal cells. Extracellular superoxide dismutase (EcSOD) is an antioxidant enzyme that catalyzes the dismutation of superoxide anion (O2−) in the extracellular environment. By doing so, this enzyme provides the cell with a defense against oxidative damage by contributing to redox balance. Interestingly, EcSOD expression has been found to be decreased in a variety of cancers, and this loss of expression may contribute to the development and progression of malignancies. In addition, recent compounds can increase EcSOD activity and expression, which has the potential for altering this redox signaling and cellular proliferation. This review will explore the role that EcSOD expression plays in cancer in order to better understand its potential as a tool for the detection, predicted outcomes and potential treatment of malignancies.
A Data-Driven Based Dynamic Rebalancing Methodology for Bike Sharing Systems
Authors: Cipriano Marco , Colomba Luca , Garza Paolo
Published: July 2021

Mobility in cities is a fundamental asset and opens several problems in decision making and the creation of new services for citizens. In the last years, transportation sharing systems have been continuously growing. Among these, bike sharing systems became commonly adopted. There exist two different categories of bike sharing systems: station-based systems and free-floating services. In this paper, we concentrate our analyses on station-based systems. Such systems require periodic rebalancing operations to guarantee good quality of service and system usability by moving bicycles from full stations to empty stations. In particular, in this paper, we propose a dynamic bicycle rebalancing methodology based on frequent pattern mining and its implementation. The extracted patterns represent frequent unbalanced situations among nearby stations. They are used to predict upcoming critical statuses and plan the most effective rebalancing operations using an entirely data-driven approach. Experiments performed on real data of the Barcelona bike sharing system show the effectiveness of the proposed approach.
Identifying Potential Managerial Personnel Using PageRank and Social Network Analysis: The Case Study of a European IT Company
Authors: Chan Jan Y. K. , Wang Zhihao , Xie Yunbo , Meisel Carlos A. , Meisel Jose D. , Solano Paula , Murillo Heidy
Published: July 2021

Behavioral theory assumes that leaders can be identified by their daily behaviors. Social network analysis helps to understand behavioral patterns within their social networks. This work considers leaders as the managerial personnel of the organization and differentiates managements from non-managerial staff by their behavior with five different types of interactions with PageRank and their attributes in modern organizations. PageRank and word embedding using word2vec with phrases from features are adopted to extract new features for the identification of managerial staff. Both traditional machine learning methods and graph neural networks are utilized with real-world data from an Austrian IT company called Knapp System Integration. Our experimental results show that the proposed new features extracted using PageRank with different types of interactions and word2vec with phrases significantly improve the identification accuracy. We also propose to use graph neural networks as an effective learning algorithm to identify managers from organizations. Our approach can identify managerial staff with an accuracy of around 80%, which demonstrates that managers could be identified through social network analysis. By analyzing the behaviors of members, the proposed method is effective as a performance appraisal tool for organizations. The study facilitates sustainable management by helping organizations to retain managerial talents or to invite potential talents to join the management team.
Emotion Recognition by Correlating Facial Expressions and EEG Analysis
Authors: Aguiñaga Adrian R. , Hernandez Daniel E. , Quezada Angeles , Calvillo Téllez Andrés
Published: July 2021

Emotion recognition is a fundamental task that any affective computing system must perform to adapt to the user’s current mood. The analysis of electroencephalography signals has gained notoriety in studying human emotions because of its non-invasive nature. This paper presents a two-stage deep learning model to recognize emotional states by correlating facial expressions and brain signals. Most of the works related to the analysis of emotional states are based on analyzing large segments of signals, generally as long as the evoked potential lasts, which could cause many other phenomena to be involved in the recognition process. Unlike with other phenomena, such as epilepsy, there is no clearly defined marker of when an event begins or ends. The novelty of the proposed model resides in the use of facial expressions as markers to improve the recognition process. This work uses a facial emotion recognition technique (FER) to create identifiers each time an emotional response is detected and uses them to extract segments of electroencephalography (EEG) records that a priori will be considered relevant for the analysis. The proposed model was tested on the DEAP dataset.
Protective Treatments against Endothelial Glycocalyx Degradation in Surgery: A Systematic Review and Meta-Analysis
Authors: Khan Hasnain Q. R. B. , Reilly Gwendolen C.
Published: July 2021

The aim was to explore the body of literature focusing on protective treatments against endothelial glycocalyx degradation in surgery. A comprehensive systematic review of relevant articles was conducted across databases. Inclusion criteria: (1) treatments for the protection of the endothelial glycocalyx in surgery; (2) syndecan-1 used as a biomarker for endothelial glycocalyx degradation. Outcomes analysed: (1) mean difference of syndecan-1 (2) correlation between glycocalyx degradation and inflammation; (3) correlation between glycocalyx degradation and extravasation. A meta-analysis was used to present mean differences and 95% confidence intervals. Seven articles with eight randomised controlled trials were included. The greatest change from baseline values in syndecan-1 concentrations was generally from the first timepoint measured post-operatively. Interventions looked to either dampen the inflammatory response or fluid therapy. Methylprednisolone had the highest mean difference in plasma syndecan-1 concentrations. Ulinastatin showed correlations between alleviation of degradation and preserving vascular permeability. In this systematic review of 385 patients, those treated were more likely than those treated with placebo to exhibit less shedding of the endothelial glycocalyx. Methylprednisolone has been shown to specifically target the transient increase of glycocalyx degradation immediately post-operation and has displayed anti-inflammatory effects. We have proposed suggestions for improved uniformity and enhanced confidence for future randomised controlled trials.
Prediction of COVID-19 from Chest CT Images Using an Ensemble of Deep Learning Models
Authors: Biswas Shreya , Chatterjee Somnath , Majee Arindam , Sen Shibaprasad , Schwenker Friedhelm , Sarkar Ram
Published: July 2021

The novel SARS-CoV-2 virus, responsible for the dangerous pneumonia-type disease, COVID-19, has undoubtedly changed the world by killing at least 3,900,000 people as of June 2021 and compromising the health of millions across the globe. Though the vaccination process has started, in developing countries such as India, the process has not been fully developed. Thereby, a diagnosis of COVID-19 can restrict its spreading and level the pestilence curve. As the quickest indicative choice, a computerized identification framework ought to be carried out to hinder COVID-19 from spreading more. Meanwhile, Computed Tomography (CT) imaging reveals that the attributes of these images for COVID-19 infected patients vary from healthy patients with or without other respiratory diseases, such as pneumonia. This study aims to establish an effective COVID-19 prediction model through chest CT images using efficient transfer learning (TL) models. Initially, we used three standard deep learning (DL) models, namely, VGG-16, ResNet50, and Xception, for the prediction of COVID-19. After that, we proposed a mechanism to combine the above-mentioned pre-trained models for the overall improvement of the prediction capability of the system. The proposed model provides 98.79% classification accuracy and a high F1-score of 0.99 on the publicly available SARS-CoV-2 CT dataset. The model proposed in this study is effective for the accurate screening of COVID-19 CT scans and, hence, can be a promising supplementary diagnostic tool for the forefront clinical specialists.
Human Milk Fat Substitutes from Lard and Hemp Seed Oil Mixtures
Authors: Bryś Joanna , Górska Agata , Ostrowska-Ligęza Ewa , Wirkowska-Wojdyła Magdalena , Bryś Andrzej , Brzezińska Rita , Dolatowska-Żebrowska Karolina , Małajowicz Jolanta , Ziarno Małgorzata , Obranović Marko , Škevin Dubravka
Published: July 2021

This paper discusses our attempt to generate substitutes for human breast milk fat through the interesterification of mixtures composed of lard and hemp (Cannabis sativa) seed oil. The interesterification was run at 60 °C for 2, 4, and 6 h in the presence of Lipozyme RM IM preparation containing a lipase specific for the cleavage of sn-1,3 ester bonds in triacylglycerol molecules. The interesterification products were analyzed regarding their fatty acid composition and distribution in triacylglycerol molecules. In order to assess the quality of the generated substitutes, in the interesterification products the following were determined: acid value, peroxide number, and oxidative stability. The collected data were statistically processed using Tukey’s test. Following the interesterification, the fats revealed an elevated percentage of free fatty acids and primary oxidation products and reduced oxidative stability compared to those of lard. The last of the above-mentioned phenomena could have been due to the incorporation of polyenic fatty acids into the external positions of triacyclglycerols of lard. The interesterification of lard and hemp seed oil allows scientists to acquire substitutes rich in essential fatty acids and similar to human breast milk fat with respect to the distribution of fatty acids in triacylglycerol molecules.
Dielectrophoretic Manipulation of Cell Transfection Efficiency during Electroporation Using a Center Needle Electrode
Authors: Radzevičiūtė Eivina , Murauskas Arūnas , Ruzgys Paulius , Šatkauskas Saulius , Girkontaitė Irutė , Novickij Jurij , Novickij Vitalij
Published: July 2021

Long duration electric pulses are frequently used to facilitate DNA electrotransfer into cells and tissues, while electroporation pulses can be combined with electrophoresis to maximize the transfection efficiency. In this work, we present the dielectrophoresis (DEP)-assisted methodology for electrotransfer of plasmid DNA (3.5 kbp pmaxGFP) into mammalian cells (CHO-K1). A prototype of an electroporation cuvette with center needle electrode for DEP-assisted transfection is presented resulting in a 1.4-fold of transfection efficiency increase compared to the electroporation-only procedure (1.4 kV/cm × 100 µs × 8). The efficiency of transfection has been compared between three DEP frequencies of 1, 100, and 1 MHz. Lastly, the effects of exposure time (1, 3, and 5 min) during the DEP application step have been determined. It is concluded that the proposed methodology and exposure setup allow a significant improvement of transfection efficiency and could be used as an alternative to the currently popular electrotransfection techniques.
Ubiquitous Technologies for Emotion Recognition
Authors: Banos Oresti , Castro Luis A. , Villalonga Claudia
Published: July 2021

Emotions play a very important role in how we think and behave. As such, the emotions we feel every day can compel us to act and influence the decisions and plans we make about our lives. Being able to measure, analyze, and better comprehend how or why our emotions may change is thus of much relevance to understand human behavior and its consequences. Despite the great efforts made in the past in the study of human emotions, it is only now with the advent of wearable, mobile, and ubiquitous technologies that we can aim at sensing and recognizing emotions, continuously and in the wild. This Special Issue aims at bringing together the latest experiences, findings, and developments regarding ubiquitous sensing, modeling, and recognition of human emotions.
Nitrous Oxide Emissions from an Alpine Grassland as Affected by Nitrogen Addition
Authors: Wu Yufeng , Gao Xiaopeng , Cao Dengchao , Li Lei , Li Xiangyi , Zeng Fanjiang
Published: July 2021

Nitrogen (N) addition is an important nutrient strategy for alpine grassland in northwestern China to improve productivity for livestock needs. A field experiment was conducted in a semi-arid alpine grassland in northwestern China to investigate the effect of N addition rates on soil N2O emissions over the growing seasons of 2017 and 2018. Treatments included six N addition rates (0, 10, 30, 60, 120, 240 kg N ha−1 y−1), which were applied before each growing season. The N2O fluxes increased with N addition rates and showed different episodic changes between the two growing seasons. In 2017, the maximum N2O flux rate occurred within 2 weeks following N addition. In 2018, however, the maximum N2O flux rate occurred later in the growing season due to a heavy rainfall event. Growing season cumulative N2O emissions ranged between 0.32 and 1.11 kg N ha−1, and increased linearly with N addition rates. Increasing N addition rates over 60 kg N ha−1 yr−1 did not further increase plant above-ground biomass. The inter-annual variability of N2O flux suggests the importance of soil moisture in affecting N2O emissions. It is particularly important to avoid over-applying N nutrients beyond plant needs to reduce its negative effect on the environment while maintaining livestock productivity. The N2O flux rate increased with soil dissolved organic carbon (DOC) and soil pH. These results suggest the optimal N addition rate to the livestock grassland in this region should be 60 kg N ha−1 yr−1.
Raindrop Size Spectrum in Deep Convective Regions of the Americas
Authors: Rivelli Zea Lina , Nesbitt Stephen W. , Ladino Alfonso , Hardin Joseph C. , Varble Adam
Published: July 2021

This study compared drop size distribution (DSD) measurements on the surface, the corresponding properties, and the precipitation modes among three deep convective regions within the Americas. The measurement compilation corresponded to two sites in the midlatitudes: the U.S. Southern Great Plains and Córdoba Province in subtropical South America, as well as to one site in the tropics: Manacapuru in central Amazonia; these are all areas where intense rain-producing systems contribute to the majority of rainfall in the Americas’ largest river basins. This compilation included two types of disdrometers (Parsivel and 2D-Video Disdrometer) that were used at the midlatitude sites and one type of disdrometer (Parsivel) that was deployed at the tropical site. The distributions of physical parameters (such as rain rate R, mass-weighted mean diameter Dm, and normalized droplet concentration Nw) for the raindrop spectra without rainfall mode classification seemed similar, except for the much broader Nw distributions in Córdoba. The raindrop spectra were then classified into a light precipitation mode and a precipitation mode by using a cutoff at 0.5 mm h−1 based on previous studies that characterized the full drop size spectra. These segregated rain modes are potentially unique relative to previously studied terrain-influenced sites. In the light precipitation and precipitation modes, the dominant higher frequency observed in a broad distribution of Nw in both types of disdrometers and the identification of shallow light precipitation in vertically pointing cloud radar data represent unique characteristics of the Córdoba site relative to the others. As a result, the co-variability between the physical parameters of the DSD indicates that the precipitation observed in Córdoba may confound existing methods of determining the rain type by using the drop size distribution.
Assessing Future Drought Conditions over the Iberian Peninsula: The Impact of Using Different Periods to Compute the SPEI
Authors: García-Valdecasas Ojeda Matilde , Romero-Jiménez Emilio , Rosa-Cánovas Juan José , Yeste Patricio , Castro-Díez Yolanda , Esteban-Parra María Jesús , Vicente-Serrano Sergio M. , Gámiz-Fortis Sonia R.
Published: July 2021

Future drought-hazard assessments using standardized indices depend on the period used to calibrate the probability distributions. This appears to be particularly important in a changing climate with significant trends in drought-related variables. This study explores the effect of using different approaches to project droughts, with a focus on changes in drought characteristics (frequency, duration, time spent in drought, and spatial extent), estimated with a calibration period covering recent past and future conditions (self-calibrated indices), and another one that only applies recent-past records (relative indices). The analysis focused on the Iberian Peninsula (IP), a hot-spot region where climate projections indicate significant changes by the end of this century. To do this, a EURO-CORDEX multi-model ensemble under RCP8.5 was used to calculate the Standardized Precipitation-Evapotranspiration Index (SPEI) at both 3- and 12-month timescales. The results suggest that projections of drought characteristics strongly depend on the period used to calibrate the SPEI, particularly at a 12-month timescale. Overall, differences were larger for the near future when relative indices indicated more severe droughts. For the distant future, changes were more similar, although self-calibrated indices revealed more frequent and longer-lasting droughts and the relative ones a drought worsening associated with extremely prolonged drought events.
Effects of Climate Change on Natural-Caused Fire Activity in Western U.S. National Forests
Authors: Heidari Hadi , Arabi Mazdak , Warziniack Travis
Published: July 2021

Climate change, with warming temperatures and shifting precipitation patterns, may increase natural-caused forest fire activity. Increasing natural-caused fires throughout western United States national forests could place people, property, and infrastructure at risk in the future. We used the fine K nearest neighbor (KNN) method coupled with the downscaled Multivariate Adaptive Constructed Analogs (MACA) climate dataset to estimate changes in the rate of natural-caused fires in western United States national forests. We projected changes in the rate of minor and major forest fires from historical (1986–2015) to future (2070–2099) conditions to characterize fire-prone national forests under a range of climate change scenarios. The results indicate that climate change can add to the occurrence of forest fires in western United States national forests, particularly in Rocky Mountain, Pacific Southwest, and Southwestern United States Forest Service regions. Although summer months are projected to have the highest rate of natural-caused forest fire activity in the future, the rate of natural-caused forest fires is likely to increase from August to December in the future compared to the historical conditions. Improved understanding of altered forest fire regimes can help forest managers to better understand the potential effects of climate change on future fire activity and implement actions to attenuate possible negative consequences.
Total Ozone Trends in East Asia from Long-Term Satellite and Ground Observations
Authors: Shin Daegeun , Oh Young-Suk , Seo Wonick , Chung Chu-Yong , Koo Ja-Ho
Published: July 2021

The ozone concentration in the atmosphere has been recovering with the reduction in atmospheric ozone-depleting substances (ODS). However, ODS remain in the atmosphere for long periods, slowing recovery. Furthermore, greenhouse gas-induced climate change complicates ozone recovery. East Asia is a significant contributor to global climate change due to the increase in industrialization and the presence of complex climate conditions. We investigated ozone variations in East Asia using total column ozone data based on satellite and ground observations and compared the results and trends derived from a multi-linear regression (MLR) model. We found that the MLR model has relatively poor explanatory power for recent extraterrestrial and dynamical proxies, but the uncertainty can be reduced using monthly data and atmospheric proxies. The ozone trend in East Asia had the greatest increase in the vicinity of the Korean Peninsula and Manchuria from 1997 to 2017 (~1% per decade). Similarly, the trend derived from Brewer spectrophotometer data was 1.02 ± 1.45% per decade in Pohang and 1.27 ± 0.85% per decade in Seoul. When the analysis period was extended to 2020, the impact of atmospheric variability was greater, suggesting that recent climate change can increasingly contribute to total ozone variability.
Application of a Generalized Secant Method to Nonlinear Equations with Complex Roots
Authors: Sidi Avram
Published: July 2021

The secant method is a very effective numerical procedure used for solving nonlinear equations of the form f(x)=0. In a recent work (A. Sidi, Generalization of the secant method for nonlinear equations. Appl. Math. E-Notes, 8:115–123, 2008), we presented a generalization of the secant method that uses only one evaluation of f(x) per iteration, and we provided a local convergence theory for it that concerns real roots. For each integer k, this method generates a sequence {xn} of approximations to a real root of f(x), where, for n≥k, xn+1=xn−f(xn)/pn,k′(xn), pn,k(x) being the polynomial of degree k that interpolates f(x) at xn,xn−1,…,xn−k, the order sk of this method satisfying 1<sk<2. Clearly, when k=1, this method reduces to the secant method with s1=(1+5)/2. In addition, s1<s2<s3<⋯, such that limk→∞sk=2. In this note, we study the application of this method to simple complex roots of a function f(z). We show that the local convergence theory developed for real roots can be extended almost as is to complex roots, provided suitable assumptions and justifications are made. We illustrate the theory with two numerical examples.
Positive Solvability for Conjugate Fractional Differential Inclusion of (k, n − k) Type without Continuity and Compactness
Authors: Salem Ahmed , Al-Dosari Aeshah
Published: July 2021

The monotonicity of multi-valued operators serves as a guideline to prove the existence of the results in this article. This theory focuses on the existence of solutions without continuity and compactness conditions. We study these results for the (k,n−k) conjugate fractional differential inclusion type with λ>0,1≤k≤n−1.
Stochastic Simulations as a Tool for Assessing Signal Fidelity in Gene Expression in Synthetic Promoter Design
Authors: Righetti Elena , Uluşeker Cansu , Kahramanoğulları Ozan
Published: July 2021

The design and development of synthetic biology applications in a workflow often involve connecting modular components. Whereas computer-aided design tools are picking up in synthetic biology as in other areas of engineering, the methods for verifying the correct functioning of living technologies are still in their infancy. Especially, fine-tuning for the right promoter strength to match the design specifications is often a lengthy and expensive experimental process. In particular, the relationship between signal fidelity and noise in synthetic promoter design can be a key parameter that can affect the healthy functioning of the engineered organism. To this end, based on our previous work on synthetic promoters for the E. coli PhoBR two-component system, we make a case for using chemical reaction network models for computational verification of various promoter designs before a lab implementation. We provide an analysis of this system with extensive stochastic simulations at a single-cell level to assess the signal fidelity and noise relationship. We then show how quasi-steady-state analysis via ordinary differential equations can be used to navigate between models with different levels of detail. We compare stochastic simulations with our full and reduced models by using various metrics for assessing noise. Our analysis suggests that strong promoters with low unbinding rates can act as control tools for filtering out intrinsic noise in the PhoBR context. Our results confirm that even simpler models can be used to determine promoters with specific signal to noise characteristics.
Why Is Aneuploidy Associated with Favorable Outcome in Neuroblastoma?
Authors: Tonini Gian Paolo
Published: July 2021

Neuroblastoma is a pediatric cancer, onset with localized as well as metastatic disease. Localized tumors usually show a high content of aneuploid cells. It is suggested that aneuploid cells with numerical copy number variation (CNV) are generated by chromosome instability (CIN). Patients with a localized tumor respond well to the therapy and show a good outcome. On the contrary, patients with a metastatic tumor have worse outcomes and the cells with structural CNV show high levels of CIN. It is proposed that a favorable outcome in patients with localized disease is associated to the grade of CIN.
Erratum: Debons et al. Magnetic Field Alignment, a Perspective in the Engineering of Collagen-Silica Composite Biomaterials. Biomolecules 2021, 11, 749
Authors: Debons Nicolas , Matsumoto Kenta , Hirota Noriyuki , Coradin Thibaud , Ikoma Toshiyuki , Aimé Carole
Published: July 2021

In the original article, there was a mistake published in Figure 2 [...]
Clinically Applicable Cyclotron-Produced Gallium-68 Gives High-Yield Radiolabeling of DOTA-Based Tracers
Authors: Jussing Emma , Milton Stefan , Samén Erik , Moein Mohammad Mahdi , Bylund Lovisa , Axelsson Rimma , Siikanen Jonathan , Tran Thuy A.
Published: July 2021

By using solid targets in medical cyclotrons, it is possible to produce large amounts of 68GaCl3. Purification of Ga3+ from metal ion impurities is a critical step, as these metals compete with Ga3+ in the complexation with different chelators, which negatively affects the radiolabeling yields. In this work, we significantly lowered the level of iron (Fe) impurities by adding ascorbate in the purification, and the resulting 68GaCl3could be utilized for high-yield radiolabeling of clinically relevant DOTA-based tracers. 68GaCl3 was cyclotron-produced and purified with ascorbate added in the wash solutions through the UTEVA resins. The 68Ga eluate was analyzed for radionuclidic purity (RNP) by gamma spectroscopy, metal content by ICP-MS, and by titrations with the chelators DOTA, NOTA, and HBED. The 68GaCl3eluate was utilized for GMP-radiolabeling of the DOTA-based tracers DOTATOC and FAPI-46 using an automated synthesis module. DOTA chelator titrations gave an apparent molar activity (AMA) of 491 ± 204 GBq/µmol. GMP-compliant syntheses yielded up to 7 GBq/batch [68Ga]Ga-DOTATOC and [68Ga]Ga-FAPI-46 (radiochemical yield, RCY ~ 60%, corresponding to ten times higher compared to generator-based productions). Full quality control (QC) of 68Ga-labelled tracers showed radiochemically pure and stable products at least four hours from end-of-synthesis.
MCN-CPI: Multiscale Convolutional Network for Compound–Protein Interaction Prediction
Authors: Wang Shuang , Jiang Mingjian , Zhang Shugang , Wang Xiaofeng , Yuan Qing , Wei Zhiqiang , Li Zhen
Published: July 2021

In the process of drug discovery, identifying the interaction between the protein and the novel compound plays an important role. With the development of technology, deep learning methods have shown excellent performance in various situations. However, the compound–protein interaction is complicated and the features extracted by most deep models are not comprehensive, which limits the performance to a certain extent. In this paper, we proposed a multiscale convolutional network that extracted the local and global features of the protein and the topological feature of the compound using different types of convolutional networks. The results showed that our model obtained the best performance compared with the existing deep learning methods.
Predictive Antibiotic Susceptibility Testing by Next-Generation Sequencing for Periprosthetic Joint Infections: Potential and Limitations
Authors: Lüftinger Lukas , Ferreira Ines , Frank Bernhard J. H. , Beisken Stephan , Weinberger Johannes , von Haeseler Arndt , Rattei Thomas , Hofstaetter Jochen G. , Posch Andreas E. , Materna Arne
Published: July 2021

Joint replacement surgeries are one of the most frequent medical interventions globally. Infections of prosthetic joints are a major health challenge and typically require prolonged or even indefinite antibiotic treatment. As multidrug-resistant pathogens continue to rise globally, novel diagnostics are critical to ensure appropriate treatment and help with prosthetic joint infections (PJI) management. To this end, recent studies have shown the potential of molecular methods such as next-generation sequencing to complement established phenotypic, culture-based methods. Together with advanced bioinformatics approaches, next-generation sequencing can provide comprehensive information on pathogen identity as well as antimicrobial susceptibility, potentially enabling rapid diagnosis and targeted therapy of PJIs. In this review, we summarize current developments in next generation sequencing based predictive antibiotic susceptibility testing and discuss potential and limitations for common PJI pathogens.