bluuebunny/crossref_metadata_2025 huggingface dataset:
Ag-Functionalized Si Nanowire Arrays Aligned Vertically for SERS Detection of Captured Heavy Metal Ions by BSA
Authors: Chiou Ai-Huei , Wei Jun-Luo , Chen Ssu-Han
Published: June 2021

A novel surface-enhanced Raman scattering (SERS)-based probe to capture heavy metal ion (Zn2+) by bovine serum albumin (BSA) using Si-nanowire (SiNW) arrays with silver nanoparticles (AgNPs) was developed. A layer with AgNPs was deposited on the SiNW surface by RF magnetron sputtering for enhancement of SERS signals. Using a high-resolution transmission electron microscope (HRTEM), the observation reveals that the AgNP layer with depths of 30–75 nm was successfully deposited on SiNW arrays. The Ag peaks in EDS and XRD spectra of SiNW arrays confirmed the presence of Ag particles on SiNW arrays. The WCA observations showed a high affinity of the Ag–SiNW arrays immobilized with BSA (water contact angle (WCA) = 87.1°) and ZnSO4 (WCA = 8.8°). The results of FTIR analysis illustrate that the conjugate bonds exist between zinc sulfate (ZnSO4) and –OH groups/–NH groups of BSA. The resulting SiNWs/Ag NPs composite interfaces showed large Raman scattering enhancement for the capture of heavy metal ions by BSA with a detection of 0.1 μM. BSA and ZnSO4 conjugations, illustrating specific SERS spectra with high sensitivity, which suggests great promise in developing label-free biosensors.
A Cascaded Neural Network for Staging in Non-Small Cell Lung Cancer Using Pre-Treatment CT
Authors: Choi Jieun , Cho Hwan-ho , Kwon Junmo , Lee Ho Yun , Park Hyunjin
Published: June 2021

Background and aim: Tumor staging in non-small cell lung cancer (NSCLC) is important for treatment and prognosis. Staging involves expert interpretation of imaging, which we aim to automate with deep learning (DL). We proposed a cascaded DL method comprised of two steps to classification between early- and advanced-stage NSCLC using pretreatment computed tomography. Methods: We developed and tested a DL model to classify between early- and advanced-stage using training (n = 90), validation (n = 8), and two test (n = 37, n = 26) cohorts obtained from the public domain. The first step adopted an autoencoder network to compress the imaging data into latent variables and the second step used the latent variable to classify the stages using the convolutional neural network (CNN). Other DL and machine learning-based approaches were compared. Results: Our model was tested in two test cohorts of CPTAC and TCGA. In CPTAC, our model achieved accuracy of 0.8649, sensitivity of 0.8000, specificity of 0.9412, and area under the curve (AUC) of 0.8206 compared to other approaches (AUC 0.6824–0.7206) for classifying between early- and advanced-stages. In TCGA, our model achieved accuracy of 0.8077, sensitivity of 0.7692, specificity of 0.8462, and AUC of 0.8343. Conclusion: Our cascaded DL model for classification NSCLC patients into early-stage and advanced-stage showed promising results and could help future NSCLC research.
Predicting the Local Response of Esophageal Squamous Cell Carcinoma to Neoadjuvant Chemoradiotherapy by Radiomics with a Machine Learning Method Using 18F-FDG PET Images
Authors: Murakami Yuji , Kawahara Daisuke , Tani Shigeyuki , Kubo Katsumaro , Katsuta Tsuyoshi , Imano Nobuki , Takeuchi Yuki , Nishibuchi Ikuno , Saito Akito , Nagata Yasushi
Published: June 2021

Background: This study aimed to propose a machine learning model to predict the local response of resectable locally advanced esophageal squamous cell carcinoma (LA-ESCC) treated by neoadjuvant chemoradiotherapy (NCRT) using pretreatment 18-fluorodeoxyglucose positron emission tomography (FDG PET) images. Methods: The local responses of 98 patients were categorized into two groups (complete response and noncomplete response). We performed a radiomics analysis using five segmentations created on FDG PET images, resulting in 4250 features per patient. To construct a machine learning model, we used the least absolute shrinkage and selection operator (LASSO) regression to extract radiomics features optimal for the prediction. Then, a prediction model was constructed by using a neural network classifier. The training model was evaluated with 5-fold cross-validation. Results: By the LASSO analysis of the training data, 22 radiomics features were extracted. In the testing data, the average accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve score of the five prediction models were 89.6%, 92.7%, 89.5%, and 0.95, respectively. Conclusions: The proposed machine learning model using radiomics showed promising predictive accuracy of the local response of LA-ESCC treated by NCRT.
Minimax Rates of ℓp-Losses for High-Dimensional Linear Errors-in-Variables Models over ℓq-Balls
Authors: Li Xin , Wu Dongya
Published: June 2021

In this paper, the high-dimensional linear regression model is considered, where the covariates are measured with additive noise. Different from most of the other methods, which are based on the assumption that the true covariates are fully obtained, results in this paper only require that the corrupted covariate matrix is observed. Then, by the application of information theory, the minimax rates of convergence for estimation are investigated in terms of the ℓp(1≤p<∞)-losses under the general sparsity assumption on the underlying regression parameter and some regularity conditions on the observed covariate matrix. The established lower and upper bounds on minimax risks agree up to constant factors when p=2, which together provide the information-theoretic limits of estimating a sparse vector in the high-dimensional linear errors-in-variables model. An estimator for the underlying parameter is also proposed and shown to be minimax optimal in the ℓ2-loss.
Experiences from COVID-19 and Emergency Remote Teaching for Entrepreneurship Education in Engineering Programmes
Authors: Lambert Chris G. , Rennie Allan E. W.
Published: June 2021

Education systems and institutions, often historically considered to be resolute, slow-moving entities transformed virtually overnight during the earlier stages of the COVID-19 pandemic, demonstrating nimbleness in adversity. This paper describes the first-hand experiences of teaching staff and students from a UK university which pivoted to emergency remote teaching for a core second-year module in engineering, focused on entrepreneurship. A range of methods are used including self-reflection, summative, formative, and focus-group student feedback. The paper provides an insight for readers who may be interested in the practical challenges associated with moving from an academic module typically delivered in a face-to-face learning environment accommodating a large student cohort (n = 177), to one that exists entirely in the digital domain. Our results show learning outcomes were fully met despite stark differences in quality of learning environments amongst students. Students reported benefits to remote learning because it offers a blended approach of both asynchronous content and synchronous sessions, with the latter enhancing engagement and providing structure to working weeks. Issues of presence emerged amongst group work: whilst it might be easier to confront some individuals for lack of contribution, it is also easier for those individuals to disengage. There was widespread support for the Microsoft Teams platform amongst students and staff but the former group reported this lacked a social environment in which relationships amongst team members could be nurtured informally, such as was experienced via social media.
Impacts on Head Start Dual Language Learning Children’s Early Science Outcomes
Authors: Rumper Brooke , Frechette Elizabeth , Greenfield Daryl B. , Hirsh-Pasek Kathy
Published: June 2021

The present study examined the roles that language of assessment, language dominance, and teacher language use during instruction play in Dual Language Learner (DLL) science scores. A total of 255 Head Start DLL children were assessed on equated science assessments in English and Spanish. First overall differences between the two languages were examined, then associations between performance on science assessments were compared and related to children’s language dominance, teacher quantity of English and Spanish, and teachers’ academic science language. When examined as a homogeneous group, DLLs did not perform differently on English or Spanish science assessments. However, when examined heterogeneously, Spanish-dominant DLLs performed better on Spanish science assessments. The percentage of English and Spanish used by teachers did not affect children’s science scores. Teachers’ use of Spanish academic science language impacted children’s performance on science assessments, but English did not. The results have implications for the assessment of DLLs and teacher language use during instruction.
Active Balun with Center-Tapped Inductor and Double-Balanced Gilbert Mixer for GNSS Applications
Authors: Pietron Daniel , Borejko Tomasz , Pleskacz Witold Adam
Published: June 2021

A new 1.575 GHz active balun with a classic double-balanced Gilbert mixer for global navigation satellite systems is proposed herein. A simple, low-noise amplifier architecture is used with a center-tapped inductor to generate a differential signal equal in amplitude and shifted in phase by 180°. The main advantage of the proposed circuit is that the phase shift between the outputs is always equal to 180°, with an accuracy of ±5°, and the gain difference between the balun outputs does not change by more than 1.5 dB. This phase shift and gain difference between the outputs are also preserved for all process corners, as well as temperature and voltage supply variations. In the balun design, a band calibration system based on a switchable capacitor bank is proposed. The balun and mixer were designed with a 110 nm CMOS process, consuming only a 2.24 mA current from a 1.5 V supply. The measured noise figure and conversion gain of the balun and mixer were, respectively, NF = 7.7 dB and GC = 25.8 dB in the band of interest.
XLNet-Caps: Personality Classification from Textual Posts
Authors: Wang Ying , Zheng Jiazhuang , Li Qing , Wang Chenglong , Zhang Hanyun , Gong Jibing
Published: June 2021

Personality characteristics represent the behavioral characteristics of a class of people. Social networking sites have a multitude of users, and the text messages generated by them convey a person’s feelings, thoughts, and emotions at a particular time. These social texts indeed record the long-term psychological activities of users, which can be used for research on personality recognition. However, most of the existing deep learning models for multi-label text classification consider long-distance semantics or sequential semantics, but problems such as non-continuous semantics are rarely studied. This paper proposed a deep learning framework that combined XLNet and the capsule network for personality classification (XLNet-Caps) from textual posts. Our personality classification was based on the Big Five personality theory and used the text information generated by the same user at different times. First, we used the XLNet model to extract the emotional features from the text information at each time point, and then, the extracted features were passed through the capsule network to extract the personality features further. Experimental results showed that our model can effectively classify personality and achieve the lowest average prediction error.
Testbed for Experimental Characterization of Indoor Visible Light Communication Channels
Authors: Fortes Miqueas , González Oswaldo
Published: June 2021

In this paper, we describe an experimental testbed designed to evaluate indoor visible light communications (VLC) in realistic scenarios. The system is based on a mockup where the location and orientation of the optical receiver can be modified with precision for a static configuration of walls and ceiling lamp arrangements. The system utilizes a timing synchronization method, which is based on evaluating the training sequence periods used for channel response estimation, which enables robust frame synchronization. In addition, an adaptive rate orthogonal frequency-division multiplexing (OFDM) scheme is used to assess the VLC performance throughout the receiver plane emulating a real communication. The preliminary results obtained with this prototype, considering a multiple-input single-output (MISO) scenario, demonstrate that reflection on walls yields a significant increase in data rates, which can be additionally improved if appropriate orientation of the receiver is implemented. However, vertical orientation upward of the optical receiver still constitutes a simple solution but efficient enough. Moreover, a good agreement between simulation and experimental results is observed, which confirms the suitability of the mockup as an experimental testbed for practical evaluation of indoor VLC systems, where system performance for different lamp arrangements and receiver designs, including multi-user communications, can be studied.
Privacy-Preserving Deep Neural Network Methods: Computational and Perceptual Methods—An Overview
Authors: El Saj Raghida , Sedgh Gooya Ehsan , Alfalou Ayman , Khalil Mohamad
Published: June 2021

Privacy-preserving deep neural networks have become essential and have attracted the attention of many researchers due to the need to maintain the privacy and the confidentiality of personal and sensitive data. The importance of privacy-preserving networks has increased with the widespread use of neural networks as a service in unsecured cloud environments. Different methods have been proposed and developed to solve the privacy-preserving problem using deep neural networks on encrypted data. In this article, we reviewed some of the most relevant and well-known computational and perceptual image encryption methods. These methods as well as their results have been presented, compared, and the conditions of their use, the durability and robustness of some of them against attacks, have been discussed. Some of the mentioned methods have demonstrated an ability to hide information and make it difficult for adversaries to retrieve it while maintaining high classification accuracy. Based on the obtained results, it was suggested to develop and use some of the cited privacy-preserving methods in applications other than classification.
Inter- and Intra-Continental Genetic Variation in the Generalist Conifer Wood Saprobic Fungus Phlebiopsis gigantea
Authors: Dovana Francesco , Gonthier Paolo , Garbelotto Matteo
Published: June 2021

Phlebiopsis gigantea (Fr.) Jülich is a well-known generalist conifer wood saprobe and a biocontrol fungus used in several world countries to prevent stump infection by tree pathogenic Heterobasidion fungal species. Previous studies have reported the presence of regional and continental genetic differentiation in host-specific fungi, but the presence of such differentiation for generalist wood saprobes such as P. gigantea has not been often studied or demonstrated. Additionally, little information exists on the distribution of this fungus in western North America. The main purposes of this study were: (I) to assess the presence of P. gigantea in California, (II) to explore the genetic variability of P. gigantea at the intra and inter-continental levels and (III) to analyze the phylogeographic relationships between American and European populations. Seven loci (nrITS, ML5–ML6, ATP6, RPB1, RPB2, GPD and TEF1-α) from 26 isolates of P. gigantea from coniferous forests in diverse geographic distribution and from different hosts were analyzed in this study together with 45 GenBank sequences. One hundred seventy-four new sequences were generated using either universal or specific primers designed in this study. The mitochondrial ML5–ML6 DNA and ATP6 regions were highly conserved and did not show differences between any of the isolates. Conversely, DNA sequences from the ITS, RPB1, RPB2, GPD and TEF1-α loci were variable among samples. Maximum likelihood analysis of GPD and TEF1-α strongly supported the presences of two different subgroups within the species but without congruence or geographic partition, suggesting the presence of retained ancestral polymorphisms. RPB1 and RPB2 sequences separated European isolates from American ones, while the GPD locus separated western North American samples from eastern North American ones. This study reports the presence of P. gigantea in California for the first time using DNA-based confirmation and identifies two older genetically distinct subspecific groups, as well as three genetically differentiated lineages within the species: one from Europe, one from eastern North America and one from California, with the latter presumably including individuals from the rest of western North America. The genetic differentiation identified here among P. gigantea individuals from coniferous forests from different world regions indicates that European isolates of this fungus should not be used in North America (or vice versa), and, likewise, commercially available eastern North American P. gigantea isolates should not be used in western North America forests. The reported lack of host specificity of P. gigantea was documented by the field survey and further reinforces the need to only use local isolates of this biocontrol fungus, given that genetically distinct exotic genotypes of a broad generalist microbe may easily spread and permanently alter the microbial biodiversity of native forest ecosystems.
CFD Model for Aircraft Ground Deicing: Verification and Validation of an Extended Enthalpy-Porosity Technique in Particulate Two Phase Flows
Authors: Ernez Sami , Morency François
Published: June 2021

Researchers have focused in the last five years on modelling the aircraft ground deicing process using CFD (computational fluid dynamics) in order to reduce its costs and pollution. As preliminary efforts, those studies did not model the ice melting nor the diffusion between deicing fluids and water resulting from the melting process. This paper proposes a CFD method to simulate this process filling these gaps. A particulate two-phase flow approach is used to model the spray impact on ice near the contaminated surface. Ice melting is modelled using an extended version of the enthalpy-porosity technique. The water resulting from the melting process is diffused into the deicing fluid forming a single-phase film. This paper presents a new model of the process. The model is verified and validated through three steps. (i) verification of the species transport. (ii) validation of the transient temperature field of a mixture. (iii) validation of the convective heat transfer of an impinging spray. The permeability coefficient of the enthalpy-porosity technique is then calibrated. The proposed model proved to be a suitable candidate for a parametric study of the aircraft ground deicing process. On the validation test cases, the precision of heat transfer prediction exceeds 88%. The model has the ability of predicting the deicing time and the deicing fluid quantities needed to decontaminate a surface.
Co-Encapsulated Synbiotics and Immobilized Probiotics in Human Health and Gut Microbiota Modulation
Authors: Kvakova Monika , Bertkova Izabela , Stofilova Jana , Savidge Tor C.
Published: June 2021

Growing interest in the development of innovative functional products as ideal carriers for synbiotics, e.g., nutrient bars, yogurt, chocolate, juice, ice cream, and cheese, to ensure the daily intake of probiotics and prebiotics, which are needed to maintain a healthy gut microbiota and overall well-being, is undeniable and inevitable. This review focuses on the modern approaches that are currently being developed to modulate the gut microbiota, with an emphasis on the health benefits mediated by co-encapsulated synbiotics and immobilized probiotics. The impact of processing, storage, and simulated gastrointestinal conditions on the viability and bioactivity of probiotics together with prebiotics such as omega-3 polyunsaturated fatty acids, phytochemicals, and dietary fibers using various delivery systems are considered. Despite the proven biological properties of synbiotics, research in this area needs to be focused on the proper selection of probiotic strains, their prebiotic counterparts, and delivery systems to avoid suppression of their synergistic or complementary effect on human health. Future directions should lead to the development of functional food products containing stable synbiotics tailored for different age groups or specifically designed to fulfill the needs of adjuvant therapy.
Slaughter Conditions and Slaughtering of Pregnant Cows in Southeast Nigeria: Implications to Meat Quality, Food Safety and Security
Authors: Njoga Ugochinyere J. , Njoga Emmanuel O. , Nwobi Obichukwu C. , Abonyi Festus O. , Edeh Henry O. , Ajibo Festus E. , Azor Nichodemus , Bello Abubakar , Upadhyay Anjani K. , Okpala Charles Odilichukwu R. , Korzeniowska Małgorzata , Guiné Raquel P. F.
Published: June 2021

The increase in the slaughter of pregnant cows (SPCs) for meat (except as may be approved by veterinarians on health grounds to salvage the animal) is unethical. SPCs for meat is also counterproductive, detrimental to food security, and may enhance zoonotic disease transmission. In this context, therefore, this current study examined slaughter conditions and the slaughtering of pregnant cows, and the implications for meat quality, food safety, and food security in Southeast Nigeria. The direct observational method was employed to examine the slaughterhouse activities, from when the cattle arrived at the lairage to the post-slaughter stage. A pre-tested and validated closed-ended-questionnaire was used to elicit information on causes of the SPCs and the method of disposal of eviscerated foetuses. Pregnancy status of cows slaughtered was determined by palpation followed by visual examination of the eviscerated and longitudinal incised uteri. The study lasted for six months during which 851 cows out of 1931 slaughtered cattle were surveyed. Assessment/decision-making protocol of slaughterhouse conditions, welfare conditions of slaughter-cattle, reasons for sale or slaughter of pregnant cows, distribution of pregnant cows slaughtered, method of disposal of eviscerated foetuses, and estimated economic losses of SPCs were delineated. Of the 851 cows examined, 17.4% (148/851) were pregnant while 43.2% (64/148) of the total foetuses recovered were in their third trimester. Major reasons adduced for SPCs by proportion of involved respondents were: ignorance of the animals’ pregnancy status (69.7%, 83/119), high demand for beef (61.3%, 73/119), preference for large-sized cattle (47.9%, 57/119), economic hardship (52.1%, 62/119) and diseases conditions (42.9%. 51/119). The conduct of SPCs for meat would not be profitable. This is because within six months, an estimated loss of about 44,000 kg of beef, equivalent to ₦ 70.1 million or $186,400 would be associated with SPCs and the consequential foetal wastages. If losses were to be replicated nationwide across slaughterhouses, 4.3 tons of beef estimated at ₦ 8.6 billion or $23 million would be wasted. Improving slaughter conditions and the welfare of slaughter-cattle in Nigerian slaughterhouses through advocacy, training of slaughterhouse workers, and strict implementation of laws promoting humane slaughter practices is imperative. Preventing SPCs for meat and inhumane slaughter practices at the slaughterhouse would enhance the welfare needs of slaughter cattle, grow the national herd size, and improve meat safety as well as food security.
Analytical Characterization of Water-Soluble Constituents in Olive-Derived By-Products
Authors: Doménech Pablo , Duque Aleta , Higueras Isabel , Fernández José Luis , Manzanares Paloma
Published: June 2021

Olive trees constitute one of the largest agroindustries in the Mediterranean area, and their cultivation generates a diverse pool of biomass by-products such as olive tree pruning (OTP), olive leaves (OL), olive stone (OS), and extracted olive pomace (EOP). These lignocellulosic materials have varying compositions and potential utilization strategies within a biorefinery context. The aim of this work was to carry out an integral analysis of the aqueous extractives fraction of these biomasses. Several analytical methods were applied in order to fully characterize this fraction to varying extents: a mass closure of >80% was reached for EOP, >76% for OTP, >65% for OS, and >52% for OL. Among the compounds detected, xylooligosaccharides, mannitol, 3,4-dihydroxyphenylglycol, and hydroxytyrosol were noted as potential enhancers of the valorization of said by-products. The extraction of these compounds is expected to be more favorable for OTP, OL, and EOP, given their high extractives content, and is compatible with other utilization strategies such as the bioconversion of the lignocellulosic fraction into biofuels and bioproducts.
Determination of Isothiocyanate-Protein Conjugates in a Vegetable-Enriched Bread
Authors: Krell Mareike , Cvancar Lina , Poloczek Michael , Hanschen Franziska S. , Rohn Sascha
Published: June 2021

Vegetables of the plant order Brassicales are believed to have health-promoting properties, as they provide high contents of glucosinolates (GLS) and deriving from these, enzymatically and heat-induced breakdown products, such as isothiocyanates (ITC). Besides their positive physiological effects, ITC are electrophilic and can undergo reactions with food components such as proteins. Following the trend of improving traditional food products with GLS-rich ingredients, interactions of ITC with proteins can diminish the properties of both components—protein’s value and functionality as well as ITC’s bioactivity. In vegetable-enriched bread, where cresses (Lepidium sativum L. or Tropaeolum majus L.) are added to the initial dough, together with benzyl cyanide, benzyl isothiocyanate (BITC) is formed during the baking process. The aim of the present study was to investigate the possible migration behavior of the GLS breakdown products and the formation of ITC-wheat protein conjugates. After the baking process, the breads’ proteins were enzymatically hydrolyzed, and the ITC-amino acid conjugates analyzed using a LC-ESI-MS/MS methodology. In all samples, BITC-protein conjugates were detected as thiourea derivatives, while formation of dithiocarbamates could not be detected. The study showed that GLS and their breakdown products such as ITC migrate into the surrounding food matrix and undergo reactions with proteins, which could in turn lead to modified protein properties and reduce the bioavailability of ITC and lysine.
Extraction and Mass Spectrometric Characterization of Terpenes Recovered from Olive Leaves Using a New Adsorbent-Assisted Supercritical CO2 Process
Authors: Suárez Montenegro Zully J. , Álvarez-Rivera Gerardo , Mendiola Jose A. , Ibáñez Elena , Cifuentes Alejandro
Published: June 2021

This work reports the use of GC-QTOF-MS to obtain a deep characterization of terpenoid compounds recovered from olive leaves, which is one of the largest by-products generated by the olive oil industry. This work includes an innovative supercritical CO2 fractionation process based on the online coupling of supercritical fluid extraction (SFE) and dynamic adsorption/desorption for the selective enrichment of terpenoids in the different olive leaves extracts. The selectivity of different commercial adsorbents such as silica gel, zeolite, and aluminum oxide was evaluated toward the different terpene families present in olive leaves. Operating at 30 MPa and 60 °C, an adsorbent-assisted fractionation was carried out every 20 min for a total time of 120 min. For the first time, GC-QTOF-MS allowed the identification of 40 terpenoids in olive leaves. The GC-QTOF-MS results indicate that silica gel is a suitable adsorbent to partially retain polyunsaturated C10 and C15 terpenes. In addition, aluminum oxide increases C20 recoveries, whereas crystalline zeolites favor C30 terpenes recoveries. The different healthy properties that have been described for terpenoids makes the current SFE-GC-QTOF-MS process especially interesting and suitable for their revalorization.
Food Integrity Climate in Food Businesses: Conceptualization, Development, and Validation of a Self-Assessment Tool
Authors: Alrobaish Waeel Salih , Jacxsens Liesbeth , Luning Pieternel A , Vlerick Peter
Published: June 2021

Current scientific research and industry guidelines focus on food safety, aiming to reduce unintentional food contaminations through technological and managerial measures. Due to the deceptive nature of food fraud, the fight to prevent intentional food adulteration and counterfeiting threats requires an approach that goes beyond the common food safety-based strategies and falls into the sphere of food integrity. With food integrity being an emerging discipline, a definition was proposed and the concept of food integrity climate was introduced. A food integrity climate (FIC) self-assessment tool in the form of a questionnaire, with twenty indicators and a five-point Likert rating scale was developed, expert-validated, and tested in practice in a large-scale meat distribution company. The questionnaire was designed to measure the performance level of food integrity in food businesses along the supply chain through managers’ and operators’ perceptions. Minor but interesting differences were found in the food integrity climate perceived between managers and operators as well as among the company’s affiliates. The tool helps food businesses to get a deeper insight on the human dimension behind food integrity through the assessment of five climate components in relation to four food integrity elements, identifying strengths and weaknesses regarding a company’s food integrity climate.
Comprehensive SPME-GC-MS Analysis of VOC Profiles Obtained Following High-Temperature Heating of Pork Back Fat with Varying Boar Taint Intensities
Authors: Burgeon Clément , Markey Alice , Debliquy Marc , Lahem Driss , Rodriguez Justine , Ly Ahmadou , Fauconnier Marie-Laure
Published: June 2021

Boar taint detection is a major concern for the pork industry. Currently, this taint is mainly detected through a sensory evaluation. However, little is known about the entire volatile organic compounds (VOCs) profile perceived by the assessor. Additionally, many research groups are working on the development of new rapid and reliable detection methods, which include the VOCs sensor-based methods. The latter are susceptible to sensor poisoning by interfering molecules produced during high-temperature heating of fat. Analyzing the VOC profiles obtained by solid phase microextraction gas chromatography–mass spectrometry (SPME-GC-MS) after incubation at 150 and 180 °C helps in the comprehension of the environment in which boar taint is perceived. Many similarities were observed between these temperatures; both profiles were rich in carboxylic acids and aldehydes. Through a principal component analysis (PCA) and analyses of variance (ANOVAs), differences were highlighted. Aldehydes such as (E,E)-nona-2,4-dienal exhibited higher concentrations at 150 °C, while heating at 180 °C resulted in significantly higher concentrations in fatty acids, several amide derivatives, and squalene. These differences stress the need for standardized parameters for sensory evaluation. Lastly, skatole and androstenone, the main compounds involved in boar taint, were perceived in the headspace at these temperatures but remained low (below 1 ppm). Higher temperature should be investigated to increase headspace concentrations provided that rigorous analyses of total VOC profiles are performed.
Current Knowledge on Beetroot Bioactive Compounds: Role of Nitrate and Betalains in Health and Disease
Authors: Milton-Laskibar Iñaki , Martínez J. Alfredo , Portillo María P.
Published: June 2021

An increase in the prevalence of noncommunicable chronic diseases has been occurring in recent decades. Among the deaths resulting from these conditions, cardiovascular diseases (CVD) stand out as the main contributors. In this regard, dietary patterns featuring a high content of vegetables and fruits, such as the Mediterranean and the DASH diets, are considered beneficial, and thus have been extensively studied. This has resulted in growing interest in vegetable-derived ingredients and food-supplements that may have potential therapeutic properties. Among these supplements, beetroot juice, which is obtained from the root vegetable Beta vulgaris, has gained much attention. Although a significant part of the interest in beetroot juice is due to its nitrate (NO3−) content, which has demonstrated bioactivity in the cardiovascular system, other ingredients with potential beneficial properties such as polyphenols, pigments and organic acids are also present. In this context, the aim of this review article is to analyze the current knowledge regarding the benefits related to the consumption of beetroot and derived food-supplements. Therefore, this article focuses on nitrate and betalains, which are considered to be the major bioactive compounds present in beetroot, and thus in the derived dietary supplements.
Nondestructive Analysis of Internal Quality in Pears with a Self-Made Near-Infrared Spectrum Detector Combined with Multivariate Data Processing
Authors: Wu Xin , Li Guanglin , He Fengyun
Published: June 2021

The consumption of pears has increased, thanks not only to their delicious and juicy flavor, but also their rich nutritional value. Traditional methods of detecting internal qualities (e.g., soluble solid content (SSC), titratable acidity (TA), and taste index (TI)) of pears are reliable, but they are destructive, time-consuming, and polluting. It is necessary to detect internal qualities of pears rapidly and nondestructively by using near-infrared (NIR) spectroscopy. In this study, we used a self-made NIR spectrum detector with an improved variable selection algorithm, named the variable stability and cluster analysis algorithm (VSCAA), to establish a partial least squares regression (PLSR) model to detect SSC content in snow pears. VSCAA is a variable selection method based on the combination of variable stability and cluster analysis to select the infrared spectrum variables. To reflect the advantages of VSCAA, we compared the classical variable selection methods (synergy interval partial least squares (SiPLS), genetic algorithm (GA), successive projections algorithm (SPA), and bootstrapping soft shrinkage (BOSS)) to extract useful wavelengths. The PLSR model, based on the useful variables selected by SiPLS-VSCAA, was optimal for measuring SSC in pears, and the correlation coefficient of calibration (Rc), root mean square error of cross validation (RMSECV), correlation coefficient of prediction (Rp), root mean square error of prediction (RMSEP), and residual predictive deviation (RPD) were 0.942, 0.198%, 0.936, 0.222%, and 2.857, respectively. Then, we applied these variable selection methods to select the characteristic wavelengths for measuring the TA content and TI value in snow pears. The prediction PLSR models, based on the variables selected by GA-BOSS to measure TA and that by GA-VSCAA to detect TI, were the best models, and the Rc, RMSECV, Rp and RPD were 0.931, 0.124%, 0.912, 0.151%, and 2.434 and 0.968, 0.080%, 0.968, 0.089%, and 3.775, respectively. The results showed that the self-made NIR-spectrum detector based on a portable NIR spectrometer with multivariate data processing was a good tool for rapid and nondestructive analysis of internal quality in pears.
Analysis of Worldwide Carrier Frequency and Predicted Genetic Prevalence of Autosomal Recessive Congenital Hypothyroidism Based on a General Population Database
Authors: Park Kyung-Sun
Published: June 2021

To assess how genomic information of the general population reflects probabilities of developing diseases and the differences in those probabilities among ethnic groups, a general population database was analyzed with an example of congenital hypothyroidism. Twelve candidate genes that follow an autosomal recessive inheritance pattern in congenital hypothyroidism (SLC5A5, TPO, TG, IYD, DUOXA2, DUOX2, TSHR, SLC26A7, GLIS3, FOXE1, TSHB, TRHR) in the gnomAD database (v2.1.1) were analyzed. The carrier frequency (CF) and predicted genetic prevalence (pGP) were estimated. The total CF in the overall population was 3.6%. DUOX2 showed the highest CF (1.8%), followed by TG (0.46%), TPO (0.44%), TSHR (0.31%), SLC26A7 (0.144%), DUOXA2 (0.141%), IYD (0.08%), SLC5A5 (0.06%), TRHR (0.059%), GLIS3 (0.059%), TSHB (0.04%), and FOXE1 (0%). The pGP in the overall population was 10.01 individuals per 100,000 births (1:9992). The highest pGP was in the East Asian population at 52.48 per 100,000 births (1:1905), followed by Finnish (35.96), Non-Finnish European (9.56), African/African American (4.0), Latino/Admixed American (3.89), South Asian (3.56), and Ashkenazi Jewish (1.81) groups. Comparing the pGP with the real incidence of congenital hypothyroidism, the pGP in East Asian populations was highly consistent with the real incidence.
Epigenetic Modification of Death Receptor Genes for TRAIL and TRAIL Resistance in Childhood B-Cell Precursor Acute Lymphoblastic Leukemia
Authors: Watanabe Atsushi , Miyake Kunio , Akahane Koshi , Goi Kumiko , Kagami Keiko , Yagita Hideo , Inukai Takeshi
Published: June 2021

Immunotherapies specific for B-cell precursor acute lymphoblastic leukemia (BCP-ALL), such as anti-CD19 chimeric antigen receptor (CAR) T-cells and blinatumomab, have dramatically improved the therapeutic outcome in refractory cases. In the anti-leukemic activity of those immunotherapies, TNF-related apoptosis-inducing ligand (TRAIL) on cytotoxic T-cells plays an essential role by inducing apoptosis of the target leukemia cells through its death receptors (DR4 and DR5). Since there are CpG islands in the promoter regions, hypermethylation of the DR4 and DR5 genes may be involved in resistance of leukemia cells to immunotherapies due to TRAIL-resistance. We analyzed the DR4 and DR5 methylation status in 32 BCP-ALL cell lines by sequencing their bisulfite PCR products with a next-generation sequencer. The DR4 and DR5 methylation status was significantly associated with the gene and cell-surface expression levels and the TRAIL-sensitivities. In the clinical samples at diagnosis (459 cases in the NOPHO study), both DR4 and DR5 genes were unmethylated in the majority of cases, whereas methylated in several cases with dic(9;20), MLL-rearrangement, and hypodiploidy, suggesting that evaluation of methylation status of the DR4 and DR5 genes might be clinically informative to predict efficacy of immunotherapy in certain cases with such unfavorable karyotypes. These observations provide an epigenetic rational for clinical efficacy of immunotherapy in the vast majority of BCP-ALL cases.
SMRT and Illumina RNA Sequencing and Characterization of a Key NAC Gene LoNAC29 during the Flower Senescence in Lilium oriental ‘Siberia’
Authors: Luo Jing , Li Ruirui , Xu Xintong , Niu Hairui , Zhang Yujie , Wang Caiyun
Published: June 2021

Lily (Lilium spp.) is an important cut flower around the world. Flower senescence in lilies is characterized by the wilting and abscission of tepals, which results in a decrease in flower quality and huge economic loss. However, the mechanism underlying flower senescence in lilies is largely unknown. In this study, single-molecule, real-time (SMRT) and Illumina sequencing were carried out in L. oriental ‘Siberia’. Sequencing yielded 73,218 non-redundant transcripts, with an N50 of 3792 bp. These data were further integrated with three published transcriptomes through cogent analysis, which yielded 62,960 transcripts, with an increase in N50 of 3935 bp. Analysis of differentially expressed genes showed that 319 transcription factors were highly upregulated during flower senescence. The expression of twelve NAC genes and eleven senescence-associated genes (SAGs) showed that LoNAC29 and LoSAG39 were highly expressed in senescent flowers. Transient overexpression of LoNAC29 and LoSAG39 in tepals of lily notably accelerated flower senescence, and the promoter activity of LoSAG39 was strongly induced by LoNAC29. This work supported new evidence for the molecular mechanism of flower senescence and provided better sequence data for further study in lilies.
Utility of EFEMP1 in the Prediction of Oncologic Outcomes of Urothelial Carcinoma
Authors: Chen Tzu-Ju , Chan Ti-Chun , Li Wan-Shan , Li Chien-Feng , Ke Hung-Lung , Wei Yu-Ching , Wu Wen-Jeng , Li Wei-Ming
Published: June 2021

Urothelial carcinoma (UC) of the upper tract (UTUC) and urinary bladder (UBUC) is a heterogeneous malignancy. Through transcriptomic profiling of the Gene Expression Omnibus UBUC dataset (GSE31684), we discovered that epidermal growth factor-containing fibulin-like extracellularmatrix protein 1 (EFEMP1) was the most upregulated gene during metastatic development. EFEMP1 is an important component of basement membranes and acts as an enzyme regulator in extracellular matrix biology. Initially, evaluation of EFEMP1 mRNA expression in 50 UBUCs showed significantly upregulated levels in high stage UC. We further validated the clinical significance of EFEMP1 in 340 UTUC and 295 UBUC using immunohistochemistry, evaluated by H-score. High EFEMP1 immunoexpression significantly correlated with high pathologic stage, high histological grade, lymph node metastasis, vascular invasion, perineural invasion and high mitosis (all p < 0.05). After adjusting for established clinicopathological factors, EFEMP1 expression status retained its prognostic impact on disease-specific survival and metastasis-free survival in UTUC and UBUC (all p < 0.01). Furthermore, Ingenuity Pathway Analysis showed that actin cytoskeleton signaling, tumor microenvironment pathway and mitochondrial dysfunction were significantly enriched by EFEMP1 dysregulation. In conclusion, high EFEMP1 expression was associated with adverse pathological features in UC and independently predicted worse outcomes, suggesting its roles in clinical decision-making and risk stratification.
Genetic Risk Profiling Associated with Recurrent Unprovoked Venous Thromboembolism
Authors: Hodeib Hossam , Youssef Amira , Allam Alzahraa A. , Selim Amal , Tawfik Mohamed A. , Abosamak Mohammed F. , Esam Ahmed , Abd Elghafar Mohamed S. , Samir Sameh , ELshora Ola A.
Published: June 2021

Introduction: Venous thromboembolism (VTE), including deep vein thrombosis (DVT) and/or pulmonary embolism (PE), is a common, acute, multifactorial disease with a five-years cumulative incidence of recurrence of approximately 25%. Actually, no single genetic defect can predict the risk of recurrence of VTE. Therefore, individual genetic risk profiling could be useful for the prediction of VTE recurrence. Aim of the study: To assess the combined effect of the common prothrombotic genotypes on the risk of recurrence of VTE in recently diagnosed unprovoked VTE patients. Patients and methods: This population based, prospective follow-up study was carried out from January 2015 to December 2020 in (internal medicine, cardiovascular medicine and anesthesia and ICU departments, Tanta University Hospital, Egypt) on 224 recently diagnosed unprovoked VTE patients. Whole blood was collected by standard venipuncture at the time of admission prior to the beginning of anticoagulant therapy. Genomic DNA was extracted and was genotyped for the 5-SNPs Genetic risk score (GRS), previously validated for first venous thrombosis (FVL rs6025, PTM rs1799963, ABO rs8176719, FGG rs2066865 and FXI rs2036914). Results: The main important finding in the present study was that patients having ≥3 risk alleles were associated with higher risk of VTE recurrence compared to those having ≤2 risk alleles (the reference group) (HR 2.5, 95% CI 1.48–4.21) (p = 0.001). Patients with GRS ≥ 3 had a significantly shorter time recurrence free survival (43.07 months) compared to the low risk group of patients with GRS (0–2) (p < 0.001). Conclusion: GRS model could be an effective and useful model in risk stratification of VTE patients, and genetic risk profiling of VTE patients could be used for the prediction of recurrence of VTE.
New Bird Sexing Strategy Developed in the Order Psittaciformes Involves Multiple Markers to Avoid Sex Misidentification: Debunked Myth of the Universal DNA Marker
Authors: Kroczak Aleksandra , Wołoszyńska Magdalena , Wierzbicki Heliodor , Kurkowski Marcin , Grabowski Krzysztof Aleksander , Piasecki Tomasz , Galosi Livio , Urantówka Adam Dawid
Published: June 2021

Sexing of birds is indispensable for scientific, breeding and conservation programs but is difficult in many species and is particularly problematic in the case of nestlings showing no sexual dimorphism. Most useful and efficient methods of sex determination are based on unique features of the Z and W sex chromosomes detected via PCR to distinguish males (ZZ) and females (ZW). During the last twenty-five years researchers searched for the universal marker capable of sexing a maximally wide spectrum of species in a single PCR assay. We screened the phylogenetically representative set of 135 Psittaciformes species including 59 species sexed for the first time. Two known (P2P8, CHD1iA) PCR markers and four additional W/Z polymorphisms (CHD1iE, CHD1i16, CHD1i9 and NIPBLi16) located within the Chromo Helicase DNA binding CHD1 or the Nipped-B homolog NIPBL genes were applied. We present the electrophoretic patterns obtained for the PCR products of the analyzed markers including most typical and atypical patterns allowing sex determination, as well as those obtained when the given marker failed in sexing. Technical aspects of molecular sex determination are discussed: the optimization of amplification conditions, direct PCR and potential misinterpretations. A truly universal marker has not been found, and therefore, we propose a sexing strategy based on multiple CHD1i16, NIPBLi16, CHD1i9 and CHD1iE markers. This new strategy confirms the sex of a given bird with at least two markers detecting independent Z/W polymorphisms, reduces the number of necessary PCR reactions and minimizes the risk of sex misidentification.
Laboratory Evaluation of Mechanical Properties of Draupne Shale Relevant for CO2 Seal Integrity
Authors: Soldal Magnus , Skurtveit Elin , Choi Jung Chan
Published: June 2021

The mechanical integrity of caprocks overlying injection formations is one of the key factors for safe storage of carbon dioxide in geological formations. Undrained effects caused by CO2 injection on strength and elastic parameters should be properly considered in the operational design to avoid fracture creation, fault reactivation and unwanted surface uplift. This study presents results from eleven undrained triaxial compression tests and one oedometer test on the Draupne shale, which is the main caprock of the Smeaheia site in the North Sea, to extract parameters relevant for seal integrity. Tests have been performed on samples oriented perpendicular to and parallel with the horizontal layering of the rock to study the effects of sample orientation relative to the loading direction. Results from undrained triaxial tests showed only minor effects of sample orientation on friction and cohesion. However, when loading during undrained shearing was parallel with layering (horizontal samples), measured Young’s modulus was roughly 1.4 times higher than for the vertical samples. Undrained shearing of vertical samples generated 30–50% more excess pore pressure than for horizontal samples with similar consolidation stress owing to more volume compaction of vertical samples. With apparent pre-consolidation stress determined from a high-stress oedometer test, the normalized undrained shear strength was found to correlate well with the overconsolidation ratio following the SHANSEP (Stress History and Normalized Soil Engineering Properties) procedure.