bluuebunny/crossref_metadata_2025 huggingface dataset:
Unsupervised Clustering of Individuals Sharing Selective Attentional Focus Using Physiological Synchrony
Authors: Stuldreher Ivo V. , Merasli Alexandre , Thammasan Nattapong , van Erp Jan B. F. , Brouwer Anne-Marie
Published: January 2022

Research on brain signals as indicators of a certain attentional state is moving from laboratory environments to everyday settings. Uncovering the attentional focus of individuals in such settings is challenging because there is usually limited information about real-world events, as well as a lack of data from the real-world context at hand that is correctly labeled with respect to individuals' attentional state. In most approaches, such data is needed to train attention monitoring models. We here investigate whether unsupervised clustering can be combined with physiological synchrony in the electroencephalogram (EEG), electrodermal activity (EDA), and heart rate to automatically identify groups of individuals sharing attentional focus without using knowledge of the sensory stimuli or attentional focus of any of the individuals. We used data from an experiment in which 26 participants listened to an audiobook interspersed with emotional sounds and beeps. Thirteen participants were instructed to focus on the narrative of the audiobook and 13 participants were instructed to focus on the interspersed emotional sounds and beeps. We used a broad range of commonly applied dimensionality reduction ordination techniques—further referred to as mappings—in combination with unsupervised clustering algorithms to identify the two groups of individuals sharing attentional focus based on physiological synchrony. Analyses were performed using the three modalities EEG, EDA, and heart rate separately, and using all possible combinations of these modalities. The best unimodal results were obtained when applying clustering algorithms on physiological synchrony data in EEG, yielding a maximum clustering accuracy of 85%. Even though the use of EDA or heart rate by itself did not lead to accuracies significantly higher than chance level, combining EEG with these measures in a multimodal approach generally resulted in higher classification accuracies than when using only EEG. Additionally, classification results of multimodal data were found to be more consistent across algorithms than unimodal data, making algorithm choice less important. Our finding that unsupervised classification into attentional groups is possible is important to support studies on attentional engagement in everyday settings.
Gut-Microbiome Composition in Response to Phenylketonuria Depends on Dietary Phenylalanine in BTBR Pahenu2 Mice
Authors: van der Goot Els , Vink Stefanie N. , van Vliet Danique , van Spronsen Francjan J. , Falcao Salles Joana , van der Zee Eddy A.
Published: January 2022

Phenylketonuria (PKU) is a metabolic disorder caused by a hepatic enzyme deficiency causing high blood and brain levels of the amino acid Phenylalanine (Phe), leading to severe cognitive and psychological deficits that can be prevented, but not completely, by dietary treatment. The behavioral outcome of PKU could be affected by the gut-microbiome-brain axis, as diet is one of the major drivers of the gut microbiome composition. Gut-microbiome alterations have been reported in treated patients with PKU, although the question remains whether this is due to PKU, the dietary treatment, or their interaction. We, therefore, examined the effects of dietary Phe restriction on gut-microbiome composition and relationships with behavioral outcome in mice. Male and female BTBR Pahenu2 mice received either a control diet (normal protein, “high” Phe), liberalized Phe-restricted (33% natural protein restriction), or severe Phe-restricted (75% natural protein restriction) diet with protein substitutes for 10 weeks (n = 14 per group). Their behavioral performance was examined in an open field test, novel and spatial object location tests, and a balance beam. Fecal samples were collected and sequenced for the bacterial 16S ribosomal RNA (rRNA) region. Results indicated that PKU on a high Phe diet reduced Shannon diversity significantly and altered the microbiome composition compared with wild-type animals. Phe-restriction prevented this loss in Shannon diversity but changed community composition even more than the high-Phe diet, depending on the severity of the restriction. Moreover, on a taxonomic level, we observed the highest number of differentially abundant genera in animals that received 75% Phe-restriction. Based on correlation analyses with differentially abundant taxa, the families Entereococacceae, Erysipelotrichaceae, Porphyromonadaceae, and the genus Alloprevotella showed interesting relationships with either plasma Phe levels and/or object memory. According to our results, these bacterial taxa could be good candidates to start examining the microbial metabolic potential and probiotic properties in the context of PKU. We conclude that PKU leads to an altered gut microbiome composition in mice, which is least severe on a liberalized Phe-restricted diet. This may suggest that the current Phe-restricted diet for PKU patients could be optimized by taking dietary effects on the microbiome into account.
Branded Foods Databases as a Tool to Support Nutrition Research and Monitoring of the Food Supply: Insights From the Slovenian Composition and Labeling Information System
Authors: Pravst Igor , Hribar Maša , Žmitek Katja , Blažica Bojan , Koroušić Seljak Barbara , Kušar Anita
Published: January 2022

Branded foods databases are becoming very valuable not only in nutrition research but also for clinical practice, policymakers, businesses, and general population. In contrast to generic foods, branded foods are marked by rapid changes in the food supply because of reformulations, the introduction of new foods, and the removal of existing ones from the market. Also, different branded foods are available in different countries. This not only complicates the compilation of branded foods datasets but also causes such datasets to become out of date quickly. In this review, we present different approaches to the compilation of branded foods datasets, describe the history and progress of building and updating such datasets in Slovenia, and present data to support nutrition research and monitoring of the food supply. Manufacturers are key sources of information for the compilation of branded foods databases, most commonly through food labels. In Slovenia, the branded food dataset is compiled using standard food monitoring studies conducted at all major retailers. Cross-sectional studies are conducted every few years, in which the food labels of all available branded foods are photographed. Studies are conducted using the Composition and Labeling Information System (CLAS) infrastructure, composed of a smartphone application for data collection and online data extraction and management tool. We reviewed various uses of branded foods datasets. Datasets can be used to assess the nutritional composition of food in the food supply (i.e., salt, sugar content), the use of specific ingredients, for example, food additives, for nutrient profiling, and assessment of marketing techniques on food labels. Such datasets are also valuable for other studies, for example, assessing nutrient intakes in dietary surveys. Additional approaches are also being tested to keep datasets updated between food monitoring studies. A promising approach is the exploitation of crowdsourcing through the mobile application VešKajJeš, which was launched in Slovenia to support consumers in making healthier dietary choices.
1H NMR-Based Chemometrics to Gain Insights Into the Bran of Radiation-Induced Colored Wheat Mutant
Authors: Kil Yun-Seo , Han Ah-Reum , Hong Min-Jeong , Kim Jin-Baek , Park Pil-Hoon , Choi Hyukjae , Nam Joo-Won
Published: January 2022

Recently, wheat has attracted attention as a functional food, rather than a simple dietary energy source. Accordingly, whole-grain intake increases with an understanding of bioactive phytochemicals in bran. The development of colored wheat has drawn more attention to the value of bran owing to its nutritional quality, as well as the antioxidant properties of the colorant. The present 1H NMR-based chemometric study evaluated the compositional improvement of radiation-induced mutants in purple wheat by focusing on the predominant metabolites with high polarity. A total of 33 metabolites, including three choline derivatives, three sugar alcohols, four sugars, 13 amino acids, eight organic acids, and two nucleosides, were identified throughout the 1H NMR spectra, and quantification data were obtained for the identified metabolites via peak shape-based quantification. Principal component and hierarchical cluster analyses were conducted for performing multivariate analyses. The colored original wheat was found to exhibit improvements compared to yellow wheat in terms of the contents of primary metabolites, thus highlighting the importance of conducting investigations of polar metabolites. The chemometrics studies further revealed mutant lines with a compositional enhancement for metabolites, including lysine, proline, acetate, and glycerol.
Integrated Transcriptomic Analysis Reveals a Distinctive Role of YAP1 in Extramedullary Invasion and Therapeutic Sensitivity of Multiple Myeloma
Authors: Zheng Bo , Sun Wei , Yi Ke , Zhang Yajun , Wang Liangzhe , Lan Hongyan , Zhang Chong , Xian Hongming , Li Rong
Published: January 2022

Multiple myeloma (MM) is the second most common hematologic malignancy. There are no standard therapeutic guidelines for extramedullary invasion (EM). We performed a retrospective integrated transcriptomic analysis based on GEO, TCGA, and Oncomine datasets with a total of over 2,500 cases enrolled. GSVA analysis was performed on GSE24080. The external validation cohorts include GSE9782, GSE2658, MMRF-COMPASS, and Oncomine. The data of MGUS to relapsed MM were acquired from GSE6477, GSE5900, and Oncomine. The data of EM were acquired from GSE39683 and GSE66291. Single-cell level transcriptome data of MM and EM were acquired from GSE106218. GSVA analysis revealed that 559 cases could be divided into 2 groups based on the expression of oncogenic pathways with prognostic significances. Group 1 with a specific phenotype of YAP1-MYC+ exhibited an unpromising prognosis. The univariate analysis revealed YAP1 as a tumor suppressor in MM. The activity of DNA repair, glycolysis, and oxidative phosphorylation was significantly higher in YAP1-MYC+ MM, which is in concordance with EM myeloma cells based on single-cell analysis. Furthermore, we discovered that YAP1-MYC+ MM patients exhibited an improved response for IMiD treatment. Collectively, YAP1-MYC+MM patients might suffer a worse prognosis and stronger propensity for EM progression.
Non-Invasive Preoperative Imaging Differential Diagnosis of Intracranial Hemangiopericytoma and Angiomatous Meningioma: A Novel Developed and Validated Multiparametric MRI-Based Clini-Radiomic Model
Authors: Fan Yanghua , Liu Panpan , Li Yiping , Liu Feng , He Yu , Wang Liang , Zhang Junting , Wu Zhen
Published: January 2022

Background

Accurate preoperative differentiation of intracranial hemangiopericytoma and angiomatous meningioma can greatly assist operation plan making and prognosis prediction. In this study, a clini-radiomic model combining radiomic and clinical features was used to distinguish intracranial hemangiopericytoma and hemangioma meningioma preoperatively.

Methods

A total of 147 patients with intracranial hemangiopericytoma and 73 patients with angiomatous meningioma from the Tiantan Hospital were retrospectively reviewed and randomly assigned to training and validation sets. Radiomic features were extracted from MR images, the elastic net and recursive feature elimination algorithms were applied to select radiomic features for constructing a fusion radiomic model. Subsequently, multivariable logistic regression analysis was used to construct a clinical model, then a clini-radiomic model incorporating the fusion radiomic model and clinical features was constructed for individual predictions. The calibration, discriminating capacity, and clinical usefulness were also evaluated.

Results

Six significant radiomic features were selected to construct a fusion radiomic model that achieved an area under the curve (AUC) value of 0.900 and 0.900 in the training and validation sets, respectively. A clini-radiomic model that incorporated the radiomic model and clinical features was constructed and showed good discrimination and calibration, with an AUC of 0.920 in the training set and 0.910 in the validation set. The analysis of the decision curve showed that the fusion radiomic model and clini-radiomic model were clinically useful.

Conclusions

Our clini-radiomic model showed great performance and high sensitivity in the differential diagnosis of intracranial hemangiopericytoma and angiomatous meningioma, and could contribute to non-invasive development of individualized diagnosis and treatment for these patients.
TMEM88 Modulates Lipid Synthesis and Metabolism Cytokine by Regulating Wnt/β-Catenin Signaling Pathway in Non-Alcoholic Fatty Liver Disease
Authors: Zhou Huan , Zhu Xingyu , Yao Yan , Su Yue , Xie Jing , Zhu Minhui , He Cuixia , Ding Jiaxiang , Xu Yuanyuan , Shan Rongfang , Wang Ying , Zhao Xiangdi , Ding Yuzhou , Liu Bingyan , Shao Zhonghuan , Liu Yuanyuan , Xu Tao , Xie Yunqiu
Published: January 2022

Objective: To clarify the molecular mechanism of TMEM88 regulating lipid synthesis and metabolism cytokine in NAFLD.

Methods:In vivo, NAFLD model mice were fed by a Methionine and Choline-Deficient (MCD) diet. H&E staining and immunohistochemistry experiments were used to analyze the mice liver tissue. RT-qPCR and Western blotting were used to detect the lipid synthesis and metabolism cytokine. In vitro, pEGFP-C1-TMEM88 and TMEM88 siRNA were transfected respectively in free fat acid (FFA) induced AML-12 cells, and the expression level of SREBP-1c, PPAR-α, FASN, and ACOX-1 were evaluated by RT-qPCR and Western blotting.

Results: The study found that the secretion of PPAR-α and its downstream target ACOX-1 were upregulated, and the secretion of SREBP-1c and its downstream target FASN were downregulated after transfecting with pEGFP-C1-TMEM88. But when TMEM88 was inhibited, the experimental results were opposite to the aforementioned conclusions. The data suggested that it may be related to the occurrence, development, and end of NAFLD. Additionally, the study proved that TMEM88 can inhibit Wnt/β-catenin signaling pathway. Meanwhile, TMEM88 can accelerate the apoptotic rate of FFA-induced AML-12 cells.

Conclusion: Overall, the study proved that TMEM88 takes part in regulating the secretion of lipid synthesis and metabolism cytokine through the Wnt/β-catenin signaling pathway in AML-12 cells. Therefore, TMEM88 may be involved in the progress of NAFLD. Further research will bring new ideas for the study of NAFLD.
Mid-Infrared Frequency Generation via Intermodal Difference Frequency Generation in AlGaAs-On-Insulator Waveguides
Authors: Haines Jack , Gandolfi Marco , Franz Yohann , De Angelis Costantino , Guasoni Massimiliano
Published: January 2022

We investigate theoretically mid-infrared (MIR) generation via difference frequency generation in multimode AlGaAs-on insulator (AlGaAs-OI) waveguides. The large refractive index difference between the AlGaAs core and the silica cladding shrinks the modes size down to the sub-μm2 scale, and, together with AlGaAs strong second-order nonlinear polarization, empowers strong nonlinear effects. As a result, efficient MIR generation is obtained in few-cm long waveguides with sub-μm2 transverse section, where higher order modes are exploited to achieve the phase-matching condition. These observations suggest that multimode AlGaAs-OI waveguides could represent a novel promising platform for on-chip, compact MIR sources.
Advances in “Omics” Approaches for Improving Toxic Metals/Metalloids Tolerance in Plants
Authors: Raza Ali , Tabassum Javaria , Zahid Zainab , Charagh Sidra , Bashir Shanza , Barmukh Rutwik , Khan Rao Sohail Ahmad , Barbosa Fernando , Zhang Chong , Chen Hua , Zhuang Weijian , Varshney Rajeev K.
Published: January 2022

Food safety has emerged as a high-urgency matter for sustainable agricultural production. Toxic metal contamination of soil and water significantly affects agricultural productivity, which is further aggravated by extreme anthropogenic activities and modern agricultural practices, leaving food safety and human health at risk. In addition to reducing crop production, increased metals/metalloids toxicity also disturbs plants’ demand and supply equilibrium. Counterbalancing toxic metals/metalloids toxicity demands a better understanding of the complex mechanisms at physiological, biochemical, molecular, cellular, and plant level that may result in increased crop productivity. Consequently, plants have established different internal defense mechanisms to cope with the adverse effects of toxic metals/metalloids. Nevertheless, these internal defense mechanisms are not adequate to overwhelm the metals/metalloids toxicity. Plants produce several secondary messengers to trigger cell signaling, activating the numerous transcriptional responses correlated with plant defense. Therefore, the recent advances in omics approaches such as genomics, transcriptomics, proteomics, metabolomics, ionomics, miRNAomics, and phenomics have enabled the characterization of molecular regulators associated with toxic metal tolerance, which can be deployed for developing toxic metal tolerant plants. This review highlights various response strategies adopted by plants to tolerate toxic metals/metalloids toxicity, including physiological, biochemical, and molecular responses. A seven-(omics)-based design is summarized with scientific clues to reveal the stress-responsive genes, proteins, metabolites, miRNAs, trace elements, stress-inducible phenotypes, and metabolic pathways that could potentially help plants to cope up with metals/metalloids toxicity in the face of fluctuating environmental conditions. Finally, some bottlenecks and future directions have also been highlighted, which could enable sustainable agricultural production.
Challenges and Perspectives in the Epigenetics of Climate Change-Induced Forests Decline
Authors: García-García Isabel , Méndez-Cea Belén , Martín-Gálvez David , Seco José Ignacio , Gallego Francisco Javier , Linares Juan Carlos
Published: January 2022

Forest tree species are highly vulnerable to the effects of climate change. As sessile organisms with long generation times, their adaptation to a local changing environment may rely on epigenetic modifications when allele frequencies are not able to shift fast enough. However, the current lack of knowledge on this field is remarkable, due to many challenges that researchers face when studying this issue. Huge genome sizes, absence of reference genomes and annotation, and having to analyze huge amounts of data are among these difficulties, which limit the current ability to understand how climate change drives tree species epigenetic modifications. In spite of this challenging framework, some insights on the relationships among climate change-induced stress and epigenomics are coming. Advances in DNA sequencing technologies and an increasing number of studies dealing with this topic must boost our knowledge on tree adaptive capacity to changing environmental conditions. Here, we discuss challenges and perspectives in the epigenetics of climate change-induced forests decline, aiming to provide a general overview of the state of the art.
Cost-Effectiveness of Public Health Measures to Control COVID-19 in China: A Microsimulation Modeling Study
Authors: Wang Qiang , Shi Naiyang , Huang Jinxin , Yang Liuqing , Cui Tingting , Ai Jing , Ji Hong , Xu Ke , Ahmad Tauseef , Bao Changjun , Jin Hui
Published: January 2022

This study aimed to assess the cost-effectiveness of various public health measures in dealing with coronavirus disease 2019 (COVID-19) in China. A stochastic agent-based model was used to simulate the progress of the COVID-19 outbreak in scenario I (imported one case) and scenario II (imported four cases) with a series of public health measures. The main outcomes included the avoided infections and incremental cost-effectiveness ratios (ICERs). Sensitivity analyses were performed to assess uncertainty. The results indicated that isolation-and-quarantine averted the COVID-19 outbreak at the lowest ICERs. The joint strategy of personal protection and isolation-and-quarantine averted one more case than only isolation-and-quarantine with additional costs. The effectiveness of isolation-and-quarantine decreased with lowering quarantine probability and increasing delay time. The strategy that included community containment would be cost-effective when the number of imported cases was >65, or the delay time of the quarantine was more than 5 days, or the quarantine probability was below 25%, based on current assumptions. In conclusion, isolation-and-quarantine was the most cost-effective intervention. However, personal protection combined with isolation-and-quarantine was the optimal strategy for averting more cases. The community containment could be more cost-effective as the efficiency of isolation-and-quarantine drops and the imported cases increases.
Detecting COVID-19-Related Fake News Using Feature Extraction
Authors: Khan Suleman , Hakak Saqib , Deepa N. , Prabadevi B. , Dev Kapal , Trelova Silvia
Published: January 2022

Since its emergence in December 2019, there have been numerous posts and news regarding the COVID-19 pandemic in social media, traditional print, and electronic media. These sources have information from both trusted and non-trusted medical sources. Furthermore, the news from these media are spread rapidly. Spreading a piece of deceptive information may lead to anxiety, unwanted exposure to medical remedies, tricks for digital marketing, and may lead to deadly factors. Therefore, a model for detecting fake news from the news pool is essential. In this work, the dataset which is a fusion of news related to COVID-19 that has been sourced from data from several social media and news sources is used for classification. In the first step, preprocessing is performed on the dataset to remove unwanted text, then tokenization is carried out to extract the tokens from the raw text data collected from various sources. Later, feature selection is performed to avoid the computational overhead incurred in processing all the features in the dataset. The linguistic and sentiment features are extracted for further processing. Finally, several state-of-the-art machine learning algorithms are trained to classify the COVID-19-related dataset. These algorithms are then evaluated using various metrics. The results show that the random forest classifier outperforms the other classifiers with an accuracy of 88.50%.
A Preliminary Study on the Abnormal Deaths and Work Burden of Chinese Physicians: A Mixed Method Analysis and Implications for Smart Hospital Management
Authors: Liang Jun , He Yunfan , Fan Linye , Nuo Mingfu , Shen Dongxia , Xu Jie , Zheng Xu , Wang Tong , Qian Hui , Lei Jianbo
Published: January 2022

Background: The population of Chinese physicians is frequently threatened by abnormal death, including death by overwork or homicide. This is not only a health problem, but also a social problem that has attracted the attention of both hospitals and the government.

Objective: This study aims to analyze the characteristics of abnormal death in physicians in Chinese hospitals from 2007 to 2020 and to investigate the relationship between abnormal death and physician workload, in order to provide information for policy makers and request improvement technologies.

Methods: A mixed research method was used. In order to ensure accuracy and completeness, a relatively comprehensive search was conducted using multiple heterogeneous data sources on the abnormal death of physicians in Chinese hospitals from 2007 to 2020. The collected cases were then descriptively analyzed using the work-related overwork death risk concept framework and the deductive grounded theory approach. In addition, the workload of physicians was calculated between 2007 and 2019 based on three important workload indicators.

Results: Between 2007 and 2020, 207 abnormal death events of physicians on the Chinese mainland were publicly reported. Among the 207 victims, the majority (~79%) died from overwork or sudden death. The number of victims who were men was 5.5 times higher than that of women, and victims were between the ages of 31–50 years. These physicians mainly belonged to the departments of surgery, anesthesiology, internal medicine, and orthopedics. Further analysis of the direct causes of death in cases of overwork death showed that 51 physicians (31.1%) died from cardiogenic diseases. Additionally, the per capita workload of physicians in China increased drastically by about 42% from 2007 to 2019, far exceeding physician workloads in Europe, Asia, and Australia (number of inpatients per physician in 2017: 72 vs. 55, 50, 45). The analysis revealed that there was a strong correlation between the number of abnormal deaths of physicians in China and the number of inpatients per physician (r = 0.683, P = 0.01).

Conclusion: High-intensity working conditions may be positively correlated with the number of abnormal deaths among physicians. Smart hospital technologies have the potential to alleviate this situation.
Configuring ADAS Platforms for Automotive Applications Using Metaheuristics
Authors: McLean Shane D. , Juul Hansen Emil Alexander , Pop Paul , Craciunas Silviu S.
Published: January 2022

Modern Advanced Driver-Assistance Systems (ADAS) combine critical real-time and non-critical best-effort tasks and messages onto an integrated multi-core multi-SoC hardware platform. The real-time safety-critical software tasks have complex interdependencies in the form of end-to-end latency chains featuring, e.g., sensing, processing/sensor fusion, and actuating. The underlying real-time operating systems running on top of the multi-core platform use static cyclic scheduling for the software tasks, while the communication backbone is either realized through PCIe or Time-Sensitive Networking (TSN). In this paper, we address the problem of configuring ADAS platforms for automotive applications, which means deciding the mapping of tasks to processing cores and the scheduling of tasks and messages. Time-critical messages are transmitted in a scheduled manner via the timed-gate mechanism described in IEEE 802.1Qbv according to the pre-computed Gate Control List (GCL) schedule. We study the computation of the assignment of tasks to the available platform CPUs/cores, the static schedule tables for the real-time tasks, as well as the GCLs, such that task and message deadlines, as well as end-to-end task chain latencies, are satisfied. This is an intractable combinatorial optimization problem. As the ADAS platforms and applications become increasingly complex, such problems cannot be optimally solved and require problem-specific heuristics or metaheuristics to determine good quality feasible solutions in a reasonable time. We propose two metaheuristic solutions, a Genetic Algorithm (GA) and one based on Simulated Annealing (SA), both creating static schedule tables for tasks by simulating Earliest Deadline First (EDF) dispatching with different task deadlines and offsets. Furthermore, we use a List Scheduling-based heuristic to create the GCLs in platforms featuring a TSN backbone. We evaluate the proposed solution with real-world and synthetic test cases scaled to fit the future requirements of ADAS systems. The results show that our heuristic strategy can find correct solutions that meet the complex timing and dependency constraints at a higher rate than the related work approaches, i.e., the jitter constraints are satisfied in over 6 times more cases, and the task chain constraints are satisfied in 41% more cases on average. Our method scales well with the growing trend of ADAS platforms.
Fungi of the “Bark Side”
Authors: Magyar Donát , Van Stan John T. , Sridhar Kandikere R.
Published: January 2022

You may not pay much attention to fungi growing on the bark of trees in your neighborhood, but there are many fungal species that scientists know have joined the “bark side.” The fungi living on bark do many interesting and surprising things. For example, bark fungi may prowl the bark in search of resources or new habitats. Fungi create tiny versions of themselves, called spores, which can use “the force” (of nature, like blowing wind, or flowing water) to move from one place to another on the bark. In this article, we introduce the microscopic war waging on the bark of your neighborhood trees, and present some of the fungi warriors of the bark side. We describe how some fungal spores use the force to stalk the bark (and beyond) during storms and discuss why fungi-bark interactions are another important reason to preserve and protect our trees.
How Can Dogs and Cats Help to Cure Human Cancers?
Authors: Bongiovanni Laura , Bergman Philip J. , de Bruin Alain
Published: January 2022

Like their owners, dogs and cats can be affected by several types of cancer, and some types are very similar to those seen in people. Unfortunately, there is still no cure for several types of cancer. How can humans’ best friends help? If a new therapy to fight cancer works well in pets, it is likely to also be effective in people with the same type of cancer. Scientists, medical doctors, and animal doctors are working together to develop new therapies that destroy cancer cells and save patients. Since the characteristics of certain types of cancer are very similar between humans and pets, new medicines that work in pet dogs or cats may also benefit human patients. Studying these “human-like” cancers in pets may speed up the development of effective anti-cancer drugs and will help to cure not only more dogs and cats, but also people with cancer.
Modeling and Experimental Research of One Kind of New Planar Vortex Actuator Based on Shape Memory Alloy
Authors: Kong Xiangsen , Gu Yilei , Wu Jiajun , Yang Yang , Shen Xing
Published: January 2022

In order to alleviate the problems of complex structure and low reliability of traditional Shape Memory Alloy (SMA) rotary actuator, a planar vortex actuator (PVA) based on SMA material was proposed to directly output torque and angular displacement. Based on the calculation method of PVA and the constitutive model of the phase transition equation of SMA, the mechanical model is established, and the pre-tightening torque, temperature, output torque, and rotation angle are obtained. The relationship expression between the tests has verified the mechanical model. The results show that the relationship between the excitation temperature and the output torque, the coefficient of determination between the calculated value and the tested value, is 0.938, the minimum error is 0.46%, and the maximum error is 49.8%. In the relationship between angular displacement and torque, the coefficient of determination between the calculated value and the test value is 0.939, the maximum error is 58.5%, and the minimum error is 28.0%. The test results show that the calculated values of mechanical model and experimental data have similar representation form.
An Intelligent Process to Estimate the Nonlinear Behaviors of an Elasto-Plastic Steel Coil Damper Using Artificial Neural Networks
Authors: Chang Seongkyu , Cho Sung Gook
Published: January 2022

This study developed a nonlinear behavior prediction model for elasto-plastic steel coil dampers (SCDs) using artificial neural networks (ANN). To train the ANN, first, the input and output data of the behavior of the elasto-plastic SCD was prepared. This study utilized the design parameters and load–displacement curves of the SCD to train the ANN. The elasto-plastic load–displacement curve of the SCD was obtained from simulation results using an ANSYS workbench. The design parameters (wire diameter, internal diameter, number of active windings, yield strength) of the SCD were defined as the input patterns, while the yield deformation, first stiffness, and second stiffness were output patterns. During learning of the neural network model, 60 datasets of the SCD were used as the learning pattern, and the remaining 21 were used to verify the model. Although this study used a small number of learning patterns, the ANN predicted accurate results for yield displacement, first stiffness, and second stiffness. In this study, the ANN was found to perform very well, predicting the nonlinear response of the SCD, compared with the values obtained from a finite element analysis program.
Analysis of a Low-Speed Drive System Using Intelligent Materials
Authors: Toader Vasile Eusebiu , Milici Laurențiu Dan , Ungureanu Constantin , Bejenar Ciprian , Grosu Oana Vasilica
Published: January 2022

This paper presents a low speed drive system with a simple and reliable construction, which can be used in an area where there is no power supply (isolated areas, forests, agricultural fields, etc.) and which operates on the basis of two heat sources, one from solar radiation and one provided by water. Alternatively, this system can be used to recover energy from wastewater from industry. The operation and role of the parameters that can influence the value of the rotation speed of the drive system are analyzed through a simulation, maintaining a constant speed in the case of the prototype is achieved through the control system because in real situations the temperature of heat sources can vary within certain limits. The models and tests performed highlight the parameters of the analyzed drive system and the limits of the range in which its speed can vary.
The Role of Insect Cytochrome P450s in Mediating Insecticide Resistance
Authors: Ye Min , Nayak Bidhan , Xiong Lei , Xie Chao , Dong Yi , You Minsheng , Yuchi Zhiguang , You Shijun
Published: January 2022

In many organisms, cytochrome P450 enzymes are the primary detoxifying enzymes. Enhanced P450 activity can be mediated by the emergence of new genes, increased transcription due to mutations in the promoter regions, changes in enzyme structures and functions due to mutations in protein-coding regions, or changes in post-translational modifications; all of these changes are subject to insecticide selection pressure. Multiple signalling pathways and key effector molecules are involved in the regulation of insect P450s. Increased P450 activity is a key mechanism inducing insect resistance. Hence, downregulation of selected P450s is a promising strategy to overcome this resistance. Insect P450 inhibitors that act as insecticide synergists, RNA interference to induce P450 gene silencing, and the use of transgenic insects and crops are examples of strategies utilized to overcome resistance. This article reviews the latest advances in studies related to insect P450s-mediated agrochemical resistance, with focuses on the regulatory mechanisms and associated pest management strategies. Future investigations on the comprehensive regulatory pathways of P450-mediated detoxification, identification of key effectors, and downregulation strategies for P450s will ecologically, economically, and practically improve pest management.
The Host-Plant Origin Affects the Morphological Traits and the Reproductive Behavior of the Aphid Parasitoid Aphelinus mali
Authors: Peñalver-Cruz Ainara , Jaloux Bruno , Lavandero Blas
Published: January 2022

Diversifying agroecosystems through habitat management inside or outside production fields can provide alternative hosts and/or prey for natural enemies. In semi-natural habitats, parasitoids may find alternative host-plant complexes (HPC) that could allow their development when pest hosts are scarce in the field. However, morphological and physiological differences between alternative and targeted HPCs could affect the preference and fitness of the parasitoids, possibly altering their efficacy in regulating pests. In the present study, we examined two Aphelinus mali parasitoid populations developing on Eriosoma lanigerum from two host plants (Malus domestica-apple trees and Pyracantha coccinea). We hypothesized that A. mali from both HPCs will show different life history traits and behaviors because primary and alternative host-plants are known to induce variations in parasitoid biological performance. Our findings indicate that A. mali originating from E. lanigerum on P. coccinea parasitized more aphids and are smaller than those originating from E. lanigerum on apple. Furthermore, these parasitoids did not significantly vary their ability to attack and oviposit apple E. lanigerum, suggesting that P. coccinea could function as a suitable banker plant for A. mali. We discuss the potential use of P. coccinea in conservation biological control of E. lanigerum in apple orchards.
Delineation of Management Zones in Hedgerow Almond Orchards Based on Vegetation Indices from UAV Images Validated by LiDAR-Derived Canopy Parameters
Authors: Martínez-Casasnovas José A. , Sandonís-Pozo Leire , Escolà Alexandre , Arnó Jaume , Llorens Jordi
Published: January 2022

One of the challenges in orchard management, in particular of hedgerow tree plantations, is the delineation of management zones on the bases of high-precision data. Along this line, the present study analyses the applicability of vegetation indices derived from UAV images to estimate the key structural and geometric canopy parameters of an almond orchard. In addition, the classes created on the basis of the vegetation indices were assessed to delineate potential management zones. The structural and geometric orchard parameters (width, height, cross-sectional area and porosity) were characterized by means of a LiDAR sensor, and the vegetation indices were derived from a UAV-acquired multispectral image. Both datasets summarized every 0.5 m along the almond tree rows and were used to interpolate continuous representations of the variables by means of geostatistical analysis. Linear and canonical correlation analyses were carried out to select the best performing vegetation index to estimate the structural and geometric orchard parameters in each cross-section of the tree rows. The results showed that NDVI averaged in each cross-section and normalized by its projected area achieved the highest correlations and served to define potential management zones. These findings expand the possibilities of using multispectral images in orchard management, particularly in hedgerow plantations.
Interruption of Seed Dormancy and In Vitro Germination of the Halophile Emerging Crop Suaeda edulis (Chenopodiaceae)
Authors: Costa-Becheleni Francyelli Regina , Troyo-Diéguez Enrique , Nieto-Garibay Alejandra , Bustamante-Salazar Luis Alejandro , García-Galindo Hugo Sergio , Murillo-Amador Bernardo
Published: January 2022

Suaeda edulis (Flores Olvera & Noguez) is a halophile species that grows in saline environments, with concomitant difficulties to germinate and reproduce. Once a null germination under a salinity gradient or fresh water was observed, a plant-growth bioregulator (BioR) was applied to interrupt dormancy and improve germination in vitro. This BioR is composed of gibberellins and adjuvant regulators; and 12.5, 25.0, and 37.5 mg L−1 of gibberellins with immersion at 24, 48, and 72 h were assayed. Most of the normality and homoscedasticity tests were favorable, except in three of 24 cases. On the germination percentage (transformed values), the dose 25.0 mg L−1 reflected the highest values of 5.5 and 6.0 units at 48 and 72 h. For the mean germination time, the highest level of 37.5 mg L−1 at 24 h reflected the best response. For the germination rate, the best one was 25 mg L−1 at 48 h, reaching 12% per day, but for the germination speed coefficient, the best value was observed with 25.0 mg L−1 at 24 h. It was concluded that to improve germination of S. edulis seeds, it is necessary to assess a dose-gradient of gibberellins, starting at 25.0 mg L−1, with higher values to break dormancy.
The Effect of TIBA and NPA on Shoot Regeneration of Cannabis sativa L. Epicotyl Explants
Authors: Dreger Mariola , Szalata Milena
Published: January 2022

Industrial hemp (Cannabis sativa L., family Cannabaceae) is a multi-purpose crop, used in the production of food, nutraceuticals, cosmetics and medicines. Therefore, development of new varieties with specific chemical profiles is necessary. In vitro culture methods could be complementary to conventional breeding and a useful tool for large-scale propagation. Strong apical dominance is considered as one of the factors contributing to the recalcitrance of industrial hemp in shoot proliferation. In this study, we tested the polar transport inhibitors N-1-naphtylphtalamic acid (NPA) and 2,3,5-triiodobenzoic acid (TIBA) to enhance shoot regeneration as the result of suppression of apical dominance and to develop in vitro protocols for Diana, Finola and Fedora 17 cultivars. Shoot tips derived from epicotyls were cultivated on Murashige and Skoog medium (MS) supplemented with meta-topolin (mT) and NPA, and also thidiazuron (TDZ) with a combination of TIBA and NPA. The results showed that the combination of TDZ with NPA (1–5 mg L−1) and TDZ with TIBA (0.5–2.5 mg L−1) increased the response of explants and the multiplication rate, but the effect was genotype-dependent and malformations were observed. To optimize the developed protocol, a two-step procedure with shortened time of exposure to inhibitors and reduced concentrations of them was applied. Shoots were rooted on media containing indole-3-butyric acid (IBA) and then successfully acclimatized. The obtained results will be useful in micropropagation of recalcitrant industrial hemp varieties.
Development of an Automatic Irrigation Method Using an Image-Based Irrigation System for High-Quality Tomato Production
Authors: Zhao Fei , Yoshida Hideo , Goto Eiji , Hikosaka Shoko
Published: January 2022

In this study, we developed an automatic irrigation method using an image-based irrigation system for high-quality tomato production in a greenhouse by investigating effects of a diurnal periodic cycle of irrigation on the photosynthesis, growth, yield, and fruit quality of tomatoes. The diurnal periodic cycle in a moderate wilting–full recovery treatment (MR) with a medium threshold value was more frequent than that in a severe wilting–full recovery treatment (SR) with a high threshold value. Mean daily maximum wilting ratios for MR and SR were 7.2% and 11.3%, respectively, when wilting ratios were set to threshold values of 7% and 14%, respectively. Total irrigation amounts in MR and SR were similar and lower than that in the untreated control. Net photosynthetic rate decreased under water stress, with values in MR being higher than that in SR, and recovered rapidly to more than 90% of its maximum value following irrigation. Plant growth and fruit yield per plant in MR and SR were lower than that in the control. Water stress treatment could improve fruit quality when it commenced at the anthesis stage or early fruit development stage. Total irrigation amount was a more important parameter than the threshold value for controlling the growth, yield, and fruit quality of tomatoes.
Effect of Up-Converting Luminescent Nanoparticles with Increased Quantum Yield Incorporated into the Fluoropolymer Matrix on Solanum lycopersicum Growth
Authors: Yanykin Denis V. , Burmistrov Dmitriy E. , Simakin Alexander V. , Ermakova Julia A. , Gudkov Sergey V.
Published: January 2022

The influence of light conversion induced by glasses coated with up-converting luminescent nanoparticles on Solanum lycopersicum cultivation was studied. Nanoparticles of Sr0.46Ba0.50Yb0.02Er0.02F2.04 solid solution were used as the up-converting luminophore. These nanoparticles were able to transform IR radiation into visible light (λem = 660 nm with minor peaks at 545 nm and 525 nm). By applying the “variable” chlorophyll fluorescence (ΔF), it was shown that the cultivation of tomatoes under the photoconversion glasses stimulated changes in the rate of plant adaptation to ultraviolet radiation. The restoration time of values of effective quantum yield of photosystem II photochemical reactions and photochemical quenching of chlorophyll fluorescence (reflecting disappearance of imbalance between photosynthetic electron transport and the utilization of NADPH) was reduced from three weeks to three days in the case of control and photoconversion films, respectively. As a result, plants grown under photoconversion glass had an increased leaf number (12.5%), total leaf area (33%), stem length (35%) and chlorophyll content in the leaves (two-fold). It is assumed that an increase in the proportion of red light in the growing spectrum has a positive effect on photosynthetic activity and plant growth.
Phytotoxic Effects of Selected Herbal Extracts on the Germination, Growth and Metabolism of Mustard and Oilseed Rape
Authors: Rys Magdalena , Saja-Garbarz Diana , Skoczowski Andrzej
Published: January 2022

The use of plants that have high allelopathic potential as natural herbicides in the form of aqueous extracts is gaining popularity in environmentally friendly agriculture. Usually, their effect on the germination and growth of weeds is investigated. However, less attention is paid to the effect of the allelopathic compounds from extracts on cultivated plants. Therefore, the aim of this study was to evaluate the impact of herbal extracts that have allelopathic properties on selected physiological and biochemical processes of two plants of great economic importance—white mustard (Sinapis alba L.) and oilseed rape (Brassica napus L. var. oleifera). The extracts were prepared from mountain arnica (Arnica montana L.), ribwort (Plantago lanceolata L.), hypericum (Hypericum perforatum L.), common milfoil (Achillea millefolium L.), sunflower (Helianthus annuus L.) and sage (Salvia officinalis L.). The germination of white mustard and oilseed rape was most inhibited by the extracts that were prepared from sage and sunflower. Additionally, in the germinating plants, the sunflower extracts increased the membrane permeability, which indicates membrane injuries. The metabolic changes in the plants were monitored using isothermal calorimetry and FT-Raman spectroscopy. The total heat production, which provided information about the metabolic activity of the white mustard and oilseed rape, was decreased the most by the sage extract but generally all of the tested extracts disturbed the shape of the heat emission curves compared to the water control. The impact of the allelopathic compounds that are present in the herbal extracts on the metabolism of the seedlings was clearly visible on the FT-Raman spectra—in the fatty acids and flavonoids range, confirmed using a cluster analysis. In conclusion, the herbal extracts from medicinal plants that have herbicidal activity could be used as a natural herbicide for weed control, but since they may also have negative impacts on cultivated plants, preliminary tests are advisable to find the extract from the species that has the least negative effect on a protected crop.