bluuebunny/crossref_metadata_2025 huggingface dataset:
Preclinical Evidence and Possible Mechanisms of Rhodiola rosea L. and Its Components for Ischemic Stroke: A Systematic Review and Meta-Analysis
Authors: Li Yan , Cai Miao , Mao Gen-Xiang , Shu Qin-Fen , Liu Xiao-Bei , Liu Xiao-Li
Published: November 2021

Background:Rhodiola rosea L. has long been used as traditional medicines in Europe and Asia to treat a variety of common conditions and diseases including Alzheimer’s disease, cardiovascular disease, cognitive dysfunctions, cancer, and stroke. Previous studies reported that Rhodiola rosea L. and its components (RRC) improve ischemia stroke in animal models. Here, we conducted a systematic review and meta-analysis for preclinical studies to evaluate the effects of RRC and the probable neuroprotective mechanisms in ischemic stroke.

Methods: Studies of RRC on ischemic stroke animal models were searched in seven databases from inception to Oct 2021. The primary measured outcomes included the neural functional deficit score (NFS), infarct volume (IV), brain water content, cell viability, apoptotic cells, terminal deoxynucleotidyl transferase (TdT)-mediated dUTP-biotin nick end labeling (TUNEL)-positive cells, B-cell lymphoma-2 (Bcl-2) level and tumor necrosis factor-α (TNF-α) level. The secondary outcome measures were possible mechanisms of RRC for ischemic stroke. All the data were analyzed via RevMan version 5.3.

Results: 15 studies involving 345 animals were identified. Methodological quality for each included studies was accessed according to the CAMARADES 10-item checklist. The quality score of studies range from 1 to 7, and the median was 5.53. Pooled preclinical data showed that compared with the controls, RRC could improve NFS (Zea Longa (p < 0.01), modified neurological severity score (mNSS) (p < 0.01), rotarod tests (p < 0.01), IV (p < 0.01), as well as brain edema (p < 0.01). It also can increase cell viability (p < 0.01), Bcl-2 level (p < 0.01) and reduce TNF-α level (p < 0.01), TUNEL-positive cells (p < 0.01), apoptotic cells (p < 0.01).

Conclusion: The findings suggested that RRC can improve ischemia stroke. The possible mechanisms of RRC are largely through antioxidant, anti-apoptosis activities, anti-inflammatory, repressing lipid peroxidation, antigliosis, and alleviating the pathological blood brain barrier damage.
CXCR7 Antagonism Reduces Acute Lung Injury Pathogenesis
Authors: Pouzol Laetitia , Sassi Anna , Baumlin Nadège , Tunis Mélanie , Strasser Daniel S. , Lehembre François , Martinic Marianne M.
Published: November 2021

Loss of control in the trafficking of immune cells to the inflamed lung tissue contributes to the pathogenesis of life-threatening acute lung injury (ALI) and its more severe form, acute respiratory distress syndrome (ARDS). Targeting CXCR7 has been proposed as a potential therapeutic approach to reduce pulmonary inflammation; however, its role and its crosstalk with the two chemokine receptors CXCR3 and CXCR4 via their shared ligands CXCL11 and CXCL12 is not yet completely understood. The present paper aimed to characterize the pathological role of the CXCR3/CXCR4/CXCR7 axis in a murine model of ALI. Lipopolysaccharide (LPS) inhalation in mice resulted in the development of key pathologic features of ALI/ARDS, including breathing dysfunctions, alteration in the alveolar capillary barrier, and lung inflammation. LPS inhalation induced immune cell infiltration into the bronchoalveolar space, including CXCR3+ and CXCR4+ cells, and enhanced the expression of the ligands of these two chemokine receptors. The first-in-class CXCR7 antagonist, ACT-1004-1239, increased levels of CXCL11 and CXCL12 in the plasma without affecting their levels in inflamed lung tissue, and consequently reduced CXCR3+ and CXCR4+ immune cell infiltrates into the bronchoalveolar space. In the early phase of lung inflammation, characterized by a massive influx of neutrophils, treatment with ACT-1004-1239 significantly reduced the LPS-induced breathing pattern alteration. Both preventive and therapeutic treatment with ACT-1004-1239 reduced lung vascular permeability and decreased inflammatory cell infiltrates. In conclusion, these results demonstrate a key pathological role of CXCR7 in ALI/ARDS and highlight the clinical potential of ACT-1004-1239 in ALI/ARDS pathogenesis.
Identification of Glutathione Peroxidase Gene Family in Ricinus communis and Functional Characterization of RcGPX4 in Cold Tolerance
Authors: Wang Xiaoyu , Liu Xuming , An Yong-qiang Charles , Zhang Hongyu , Meng Di , Jin Yanan , Huo Hongyan , Yu Lili , Zhang Jixing
Published: November 2021

Glutathione peroxidases (GPXs) protect cells against damage caused by reactive oxygen species (ROS) and play key roles in regulating many biological processes. Here, five GPXs were identified in the Ricinus communis genome. Phylogenetic analysis displayed that the GPXs were categorized into five groups. Conserved domain and gene structure analyses showed that the GPXs from different plant species harbored four highly similar motifs and conserved exon-intron arrangement patterns, indicating that their structure and function may have been conserved during evolution. Several abiotic stresses and hormone-responsive cis-acting elements existed in the promoters of the RcGPXs. The expression profiles indicated that the RcGPXs varied substantially, and some RcGPXs were coordinately regulated under abiotic stresses. Overexpression of RcGPX4 in Arabidopsis enhanced cold tolerance at seed germination but reduced freezing tolerance at seedlings. The expression of abscisic acid (ABA) signaling genes (AtABI4 and AtABI5), ABA catabolism genes (AtCYP707A1 and AtCYP707A2), gibberellin acid (GA) catabolism gene (AtGA2ox7), and cytokinin (CTK)-inducible gene (AtARR6) was regulated in the seeds of transgenic lines under cold stress. Overexpression of RcGPX4 can disturb the hydrogen peroxide (H2O2) homeostasis through the modulation of some antioxidant enzymes and compounds involved in the GSH-ascorbate cycle in transgenic plants. Additionally, RcGPX4 depended on the MAPK3-ICE1-C-repeat-binding factor (CBF)-COR signal transduction pathway and ABA-dependent pathway to negatively regulate the freezing tolerance of transgenic plants. This study provides valuable information for understanding the potential function of RcGPXs in regulating the abiotic stress responses of castor beans.
The Complete Plastid Genomes of Seven Sargassaceae Species and Their Phylogenetic Analysis
Authors: Li Ruoran , Jia Xuli , Zhang Jing , Jia Shangang , Liu Tao , Qu Jiangyong , Wang Xumin
Published: November 2021

Sargassum is one of the most important genera of the family Sargassaceae in brown algae and is used to produce carrageenan, mannitol, iodine, and other economic substances. Here, seven complete plastid genomes of Sargassum ilicifolium var. conduplicatum, S. graminifolium, S. phyllocystum, S. muticum, S. feldmannii, S. mcclurei, and S. henslowianum were assembled using next-generation sequencing. The sizes of the seven circular genomes ranged from 124,258 to 124,563 bp, with two inverted regions and the same set of plastid genes, including 139 protein-coding genes (PCGs), 28 transfer (t)RNAs, and 6 ribosomal (r)RNAs. Compared with the other five available plastid genomes of Fucales, 136 PCGs were conserved, with two common ones shared with Coccophora langsdorfii, and one with S. fusiforme and S. horneri. The co-linear analysis identified two inversions of trnC(gca) and trnN(gtt) in ten Sargassum species, against S. horneri and C. langsdorfii. The phylogenetic analysis based on the plastid genomes of 55 brown algae (Phaeophyceae) showed four clades, whose ancient ancestor lived around 201.42 million years ago (Mya), and the internal evolutionary branches in Fucales started to be formed 92.52 Mya, while Sargassum species were divided into two subclades 14.33 Mya. Our novel plastid genomes provided evidence for the speciation of brown algae and plastid genomic evolution events.
Awareness of Performance on a Functional Cognitive Performance-Based Assessment Across the Adult Lifespan
Authors: Arora Catherine , Frantz Carina , Toglia Joan
Published: November 2021

As people age, their cognitive skills and ability to complete complex instrumental activities of daily living often decline in subtle ways. Older adults who are aware of these slight cognitive and functional changes spontaneously adapt and implement strategies to maximize performance. On the other hand, older adults with limited self-awareness are less likely to adjust performance or initiate compensatory strategies as they may not recognize the need to do so. This places them at higher risk of functional decline and loss of independence. Research on awareness of functional performance in healthy adults is, however, limited, and there is a paucity of assessment tools available to address questions of awareness and strategy use in functional tasks. We used the Weekly Calendar Planning Activity (WCPA) – a performance-based assessment of functional cognition including measures of awareness and strategy use – to investigate differences in performance, awareness, and strategy use across the adult lifespan. The WCPA requires examinees to schedule appointments into a weekly calendar while following rules designed to increase task demands. Healthy adults (n=342) from ages 18–92 were observed for strategy use and error recognition, while a post-test interview probed participants’ reported strategy use and estimation of accuracy. The discrepancy between participant estimation and actual accuracy provided a measure of online awareness of performance where a larger estimation discrepancy indicated over-estimation of performance. Performance on the WCPA declined across the adult lifespan. Older adults were less likely to use self-monitoring strategies and used less effective strategies overall. Overestimation was associated with use of fewer strategies and lower accuracy in all age groups. Importantly, twice as many older adults overestimated compared to younger adults. Furthermore, the subset of older adults who had good awareness of performance was more likely to use effective strategies, to recognize errors, and achieved accuracy on par with their younger counterparts. Our results emphasize the importance of examining self-awareness of performance and analyzing the strategies used to perform a complex functional task. This information can provide a foundation for early detection of functional decline in aging and for designing interventions to maximize functional independence in aging.
How Audiences Engage With Drama: Identification, Attribution and Moral Approval
Authors: Teasdale Ben , Maguire Laurie , Budelmann Felix , Dunbar R. I. M.
Published: November 2021

Fictional storytelling has played an important role in human cultural life since earliest times, and we are willing to invest significant quantities of time, mental effort and money in it. Nonetheless, the psychological mechanisms that make this possible, and how they relate to the mechanisms that underpin real-world social relationships, remain understudied. We explore three factors: identification (the capacity to identify with a character), moral approval and causal attribution with respect to a character’s behaviour in live performances of two plays from the European literary canon. There were significant correlations between the extent to which subjects identified with a character and their moral approval of that character’s behaviour that was independent of the way the play was directed. However, the subjects’ psychological explanations for a character’s behaviour (attribution) were independent of whether or not they identified with, or morally approved of, the character. These data extend previous findings by showing that moral approval plays an important role in facilitating identification even in live drama. Despite being transported by an unfolding drama, audiences do not necessarily become biased in their psychological understanding of why characters behaved as they did. The psychology of drama offers significant insights into the psychological processes that underpin our everyday social world.
Using Neurofeedback to Restore Inter-Hemispheric Imbalance: A Study Protocol for Adults With Dyslexia
Authors: Cancer Alice , Vanutelli Maria Elide , Lucchiari Claudio , Antonietti Alessandro
Published: November 2021

Neurofunctional models of developmental dyslexia (DD) point out disruption of the left-lateralized reading network. In individuals with DD, the left temporo-parietal (TP) regions are underactivated during reading tasks and a dysfunctional activation of the contralateral regions is reported. After a successful reading intervention, left TP lateralization was found to be increased in children with DD. Previous studies measured the effect of modulating the excitability of the left TP cortex using non-invasive brain stimulation (NIBS) in individuals with reading difficulties, showing significant reading improvements. NIBS exclusion criteria and safety guidelines may limit its application in settings without medical supervision and in younger populations. Neurofeedback (NF) training could be an alternative intervention method for modulating the inter-hemispheric balance of the temporal–parietal regions in DD. To date, the effect of NF on reading has been scarcely investigated. Few protocols increasing beta activity in underactivated areas showed improved reading outcomes. However, none of the previous studies designed the NF intervention based on a neurofunctional model of DD. We aim to propose a study protocol for testing the efficacy of a NF training specifically designed for inducing a functional hemispheric imbalance of the tempo-parietal regions in adults with DD. A randomized clinical trial aimed at comparing two experimental conditions is described: (a) Enhancing left beta/theta power ratio NF training in combination with reducing right beta/theta power ratio NF training and (b) sham NF training.

Clinical Trial Registration:www.ClinicalTrials.gov, identifier [NCT04989088].
Face Recognition Brain Functional Connectivity in Patients With Major Depression: A Brain Source Localization Study by ERP
Authors: Lei Lei , Zhang Yu , Song Xiaotong , Liu Penghong , Wen Yujiao , Zhang Aixia , Yang Chunxia , Sun Ning , Liu Zhifen , Zhang Kerang
Published: November 2021

Objective: Patients with major depressive disorder (MDD) presents with face recognition defects. These defects negatively affect their social interactions. However, the cause of these defects is not clear. This study sought to explore whether MDD patients develop facial perceptual processing disorders with characteristics of brain functional connectivity (FC).

Methods: Event-related potential (ERP) was used to explore differences between 20 MDD patients and 20 healthy participants with face and non-face recognition tasks based on 64 EEG parameters. After pre-processing of EEG data and source reconstruction using the minimum-norm estimate (MNE), data were converted to AAL90 template to obtain a time series of 90 brain regions. EEG power spectra were determined using Fieldtrip incorporating a Fast Fourier transform. FC was determined for all pairs of brain signals for theta band using debiased estimate of weighted phase-lag index (wPLI) in Fieldtrip. To explore group differences in wPLI, independent t-tests were performed with p < 0.05 to indicate statistical significance. False discovery rate (FDR) correction was used to adjust p-values.

Results: The findings showed that amplitude induction by face pictures was higher compared with that of non-face pictures both in MDD and healthy control (HC) groups. Face recognition amplitude in MDD group was lower compared with that in the HC group. Two time periods with significant differences were then selected for further analysis. Analysis showed that FC was stronger in the MDD group compared with that in the HC group in most brain regions in both periods. However, only one FC between two brain regions in HC group was stronger compared with that in the MDD group.

Conclusion: Dysfunction in brain FC among MDD patients is a relatively complex phenomenon, exhibiting stronger and multiple connectivity with several brain regions of emotions. The findings of the current study indicate that the brain FC of MDD patients is more complex and less efficient in the initial stage of face recognition.
Complementary and Alternative Medicine for Substance Use Disorders: A Scientometric Analysis and Visualization of Its Use Between 2001 and 2020
Authors: Junyue Jiao , Siyu Chen , Xindong Wang , Qinge Xiao , Jingchun Zeng , Liming Lu , Guohua Lin
Published: November 2021

Background: This study aimed to identify frontiers for further studies via brief understanding in complementary and alternative medicine (CAM) for substance use disorders (SUDs).

Materials and Methods: Publications on the use of CAM for treating SUDs were retrieved from the Web of Science Core Collection from 2001 to 2020 on July 12, 2020, and visualized by CiteSpace V.

Results: A total of 3,807 publications were obtained. The USA, China, and England were the leading research centers. However, India and Pakistan have recently focused on assessing CAM for the treatment of SUDs. Frederick L Altice was found to be the most productive author. Addiction ranked first among the frequently cited journals, which exceeded 1,000. The most common CAM therapies were acupuncture and CAM psychotherapies, such as mindfulness meditation.

Conclusion: CAM is gaining attention globally for treating SUDs. CAM psychotherapy and acupuncture are hotspots and deserve further study. Researchers should strengthen peer cooperation in this field.
Intelligent Sensors for Sustainable Food and Drink Manufacturing
Authors: Watson Nicholas J. , Bowler Alexander L. , Rady Ahmed , Fisher Oliver J. , Simeone Alessandro , Escrig Josep , Woolley Elliot , Adedeji Akinbode A.
Published: November 2021

Food and drink is the largest manufacturing sector worldwide and has significant environmental impact in terms of resource use, emissions, and waste. However, food and drink manufacturers are restricted in addressing these issues due to the tight profit margins they operate within. The advances of two industrial digital technologies, sensors and machine learning, present manufacturers with affordable methods to collect and analyse manufacturing data and enable enhanced, evidence-based decision making. These technologies will enable manufacturers to reduce their environmental impact by making processes more flexible and efficient in terms of how they manage their resources. In this article, a methodology is proposed that combines online sensors and machine learning to provide a unified framework for the development of intelligent sensors that work to improve food and drink manufacturers' resource efficiency problems. The methodology is then applied to four food and drink manufacturing case studies to demonstrate its capabilities for a diverse range of applications within the sector. The case studies included the monitoring of mixing, cleaning and fermentation processes in addition to predicting key quality parameter of crops. For all case studies, the methodology was successfully applied and predictive models with accuracies ranging from 95 to 100% were achieved. The case studies also highlight challenges and considerations which still remain when applying the methodology, including efficient data acquisition and labelling, feature engineering, and model selection. This paper concludes by discussing the future work necessary around the topics of new online sensors, infrastructure, data acquisition and trust to enable the widespread adoption of intelligent sensors within the food and drink sector.
Next Generation of Voluntary PRRS Virus Regional Control Programs
Authors: Magalhães Edison S. , Zimmerman Jeffrey J. , Holtkamp Derald J. , Classen Dyneah M. , Groth Douglas D. , Glowzenski Lauren , Philips Reid , Silva Gustavo S. , Linhares Daniel C. L.
Published: November 2021

Porcine reproductive and respiratory syndrome virus (PRRSV) became pandemic in the 1980's and today remains one of the most significant pathogens of the global swine industry. At the herd level, control of PRRSV is complicated by its extreme genetic diversity and its ability to persist in pigs, despite an active immune response. Ultimately, PRRSV control or elimination requires the coordination and active cooperation of producers and veterinarians at the regional level. Early voluntary PRRSV regional control programs focused on routine diagnostic testing and voluntary data-sharing regarding the PRRSV status of participants' herds, but no pre-defined action plans or decision trees were developed to secure project successes (or recover from failures). Given that control of PRRSV is paramount to producer profitability, we propose a coordinated approach for detecting, controlling, and ultimately eliminating wild-type PRRSV from herds participating in regional projects. Fundamental to project success is real-time, multi-platform communication of all data, information, and events that concern the regional project and project participants. New to this approach is the concept of agreed-upon action plans to be implemented by project participants in response to specific events or situations. The simultaneous and coordinated implementation of these strategies allows for early detection of wild-type PRRSV virus introductions and rapid intervention based on agreed-upon response plans. An example is given of a project in progress in the Midwest USA.
A Sustainability Management Model for Local Government: An Explanatory Study
Authors: De Matteis Fabio , Borgonovi Elio
Published: November 2021

Although the scientific debate in the field of business economics is rich in contributions to the subject of sustainability, they mainly focus on a specific aspect represented by sustainability reporting. Consistent with this bibliographic evidence, the aim of this study was to investigate a sustainability management model in local authorities, which, by examining the dimensions of sustainability, goes beyond the focus of reporting highlighted in the literature to consider the entire sustainability cycle (from planning to measurement). To this end, the methodology of the single case study with multiple units of analysis is used, examining the case of an Italian local authority that has experimented with the sustainability management model described in this paper. The analysis of the case leads to some concluding remarks on the strengths and weaknesses of the model, contributing to the scientific debate on sustainability management and providing useful indications for public managers and political decision-makers.
Yield, Economic Benefit, Soil Water Balance, and Water Use Efficiency of Intercropped Maize/Potato in Responses to Mulching Practices on the Semiarid Loess Plateau
Authors: Xie Junhong , Wang Linlin , Li Lingling , Anwar Sumera , Luo Zhuzhu , Zechariah Effah , Kwami Fudjoe Setor
Published: November 2021

Increasing agricultural productivity without undermining further the integrity of the Earth’s environmental systems such as soil water balance are important tasks to ensure food security for an increasing global population in rainfed agriculture. The impact of intercropping maize (Zea mays L.) with potato (Solanum tuberosum L.) on yield, land equivalent ratios (LER), water equivalent ratio (WER), water use, energy output, and net economic return were examined under seven planting systems: potato grown solely or intercropped on the flat field without mulching, maize grown solely or intercropped with potato on ridges or flat field with or without plastic film mulched. The three intercropping systems had 3–13% less water use than the monocropping. Among the intercropped systems, flat field caused more depletion of soil water than ridged field for both years. Compared to monocultures, intercropping with plastic film mulching and ridging significantly increased LER and WER. Meanwhile, intercropping with mulching and ridging significantly increased net economic return and energy output by 8% and 24%, respectively, when compared to monocropping. These results suggest that maize under plastic film mulched ridge-furrow plot intercropped with potato under flat plot without mulching increased energy output, net economic return, and water use efficiency without increasing soil water depletion, which could be an optimal intercropping system for the semiarid farmland on the western Loess Plateau.
Simplified and Hybrid Remote Sensing-Based Delineation of Management Zones for Nitrogen Variable Rate Application in Wheat
Authors: Rokhafrouz Mohammad , Latifi Hooman , Abkar Ali A. , Wojciechowski Tomasz , Czechlowski Mirosław , Naieni Ali Sadeghi , Maghsoudi Yasser , Niedbała Gniewko
Published: November 2021

Enhancing digital and precision agriculture is currently inevitable to overcome the economic and environmental challenges of the agriculture in the 21st century. The purpose of this study was to generate and compare management zones (MZ) based on the Sentinel-2 satellite data for variable rate application of mineral nitrogen in wheat production, calculated using different remote sensing (RS)-based models under varied soil, yield and crop data availability. Three models were applied, including (1) a modified “RS- and threshold-based clustering”, (2) a “hybrid-based, unsupervised clustering”, in which data from different sources were combined for MZ delineation, and (3) a “RS-based, unsupervised clustering”. Various data processing methods including machine learning were used in the model development. Statistical tests such as the Paired Sample T-test, Kruskal–Wallis H-test and Wilcoxon signed-rank test were applied to evaluate the final delineated MZ maps. Additionally, a procedure for improving models based on information about phenological phases and the occurrence of agricultural drought was implemented. The results showed that information on agronomy and climate enables improving and optimizing MZ delineation. The integration of prior knowledge on new climate conditions (drought) in image selection was tested for effective use of the models. Lack of this information led to the infeasibility of obtaining optimal results. Models that solely rely on remote sensing information are comparatively less expensive than hybrid models. Additionally, remote sensing-based models enable delineating MZ for fertilizer recommendations that are temporally closer to fertilization times.
DeepPaSTL: Spatio-Temporal Deep Learning Methods for Predicting Long-Term Pasture Terrains Using Synthetic Datasets
Authors: Rangwala Murtaza , Liu Jun , Ahluwalia Kulbir Singh , Ghajar Shayan , Dhami Harnaik Singh , Tracy Benjamin F. , Tokekar Pratap , Williams Ryan K.
Published: November 2021

Effective management of dairy farms requires an accurate prediction of pasture biomass. Generally, estimation of pasture biomass requires site-specific data, or often perfect world assumptions to model prediction systems when field measurements or other sensory inputs are unavailable. However, for small enterprises, regular measurements of site-specific data are often inconceivable. In this study, we approach the estimation of pasture biomass by predicting sward heights across the field. A convolution based sequential architecture is proposed for pasture height predictions using deep learning. We develop a process to create synthetic datasets that simulate the evolution of pasture growth over a period of 30 years. The deep learning based pasture prediction model (DeepPaSTL) is trained on this dataset while learning the spatiotemporal characteristics of pasture growth. The architecture purely learns from the trends in pasture growth through available spatial measurements and is agnostic to any site-specific data, or climatic conditions, such as temperature, precipitation, or soil condition. Our model performs within a 12% error margin even during the periods with the largest pasture growth dynamics. The study demonstrates the potential scalability of the architecture to predict any pasture size through a quantization approach during prediction. Results suggest that the DeepPaSTL model represents a useful tool for predicting pasture growth both for short and long horizon predictions, even with missing or irregular historical measurements.
The Uptake and Deconjugation of Androstenone Sulfate in the Adipose Tissue of the Boar
Authors: Bone Christine , Squires E. James
Published: November 2021

Boars express high testicular levels of sulfotransferase enzymes, and consequently, the boar taint causing compound androstenone predominantly circulates as a steroid sulfate. Androstenone sulfate is suspected to function as a steroid reservoir that can be deconjugated to provide a source of free androstenone for accumulation. Therefore, the purpose of this study was to characterize the uptake and deconjugation of androstenone sulfate in the adipose tissue of the boar. Real-time PCR was used to quantify the expression of steroid sulfatase (STS) and several organic anion transporting polypeptides (OATPs) in the adipose tissue. Additionally, [3H]-androstenone sulfate was incubated with adipocytes or supernatant from homogenized fat to assess steroid uptake and conversion, respectively. A positive correlation existed between OATP-B expression and androstenone sulfate uptake (r = 0.86, p = 0.03), as well as between STS expression and androstenone sulfate conversion (r = 0.76, p < 0.001). Moreover, fat androstenone concentrations were positively correlated (r = 0.85, p < 0.001) with androstenone sulfate conversion and tended to increase with STS expression in early maturing boars. This suggests that androstenone sulfate uptake and deconjugation are mediated by OATP-B and STS, respectively, which may influence the development of boar taint in early maturing animals.
The Effect of Maternal Behavior around Calving on Reproduction and Wellbeing of Zebu Type Cows and Calves
Authors: Orihuela Agustín , Galina Carlos S.
Published: November 2021

The behaviors associated with domestic cattle such as maternal care are quite similar to those behaviors observed in wild ungulates. These behaviors allow the cow to bond with her calf, protect and provide it with nourishment and ultimately reduce the bond at weaning. Although maternal behavior is an important factor influencing the survival and early development of the newborn calf, Zebu type cows around calving have not been studied extensively. Herein, we consider the four main aspects of maternal behavior in cattle and particularly Bos indicus cows and calves. Firstly, we provide a brief description of the behavior of cows around parturition and the behavior of the first stages of the calves’ lives. In the second part, the protective behavior of the mother is analyzed. Subsequently, examples of animal welfare implications followed by an analysis of some factors that affect calf survival, including mother experience and weather conditions, are discussed, and in the last part, reproduction along with some peculiarities of reproductive behavior, and the wellbeing of mother and calves are examined. We concluded that knowledge of maternal behavior of Zebu type cows around calving and interactions with calves might contribute to an enhanced reproductive efficiency of the mother and the welfare of the calf.
Composition of Fecal Microbiota in Grazing and Feedlot Angus Beef Cattle
Authors: Zhang Zhimin , Yang Li , He Yang , Luo Xinmao , Zhao Shaokang , Jia Xianbo
Published: November 2021

This study is to investigate the difference in bovine fecal microbiota between grazing and feedlot Angus cattle. Fecal samples were collected from six Angus cattle grazed on grassland and six Angus cattle fed on a feedlot. The fecal bacterial community was analyzed by high-throughput sequencing of 16S rRNA gene. Sequencing of the V3–V4 region totally produced 1,113,170 effective tages that were computationally clustered into 775 operational taxonomic units (OTUs). These 775 OTUs were taxonomically assigned to bacterial 12 phyla, 19 classes, 25 orders, 54 families, 141 genera, and 145 species. The dominant phyla were Firmicutes and Bacteroidetes. There was similar species richness between grazing and feedlot Angus beef, while higher species diversity was observed in feedlot Angus beef. The relative abundance of Firmicutes, Cyanobacteria, Elusimicrobia and Patescibacteria was significantly different between grazing and feedlot Angus beef (p < 0.05). At a genus level, five microbiotas were significantly different between the two groups and all belonged to the Firmicutes phylum. These significant differences in microbiota composition between grazing and feedlot Angus beef may have an impact on the meat quality of Angus beef.
Interdental Plaque Microbial Community Changes under In Vitro Violet LED Irradiation
Authors: Wang Dan , Nambu Takayuki , Tanimoto Hiroaki , Iwata Naohiro , Yoshikawa Kazushi , Okinaga Toshinori , Yamamoto Kazuyo
Published: November 2021

Oral microbiome dysbiosis has important links to human health and disease. Although photodynamic therapy influences microbiome diversity, the specific effect of violet light irradiation remains largely unknown. In this study, we analyzed the effect of violet light-emitting diode (LED) irradiation on interdental plaque microbiota. Interdental plaque was collected from 12 human subjects, exposed to violet LED irradiation, and cultured in a specialized growth medium. Next-generation sequencing of the 16S ribosomal RNA genes revealed that α-diversity decreased, whereas β-diversity exhibited a continuous change with violet LED irradiation doses. In addition, we identified several operational taxonomic units that exhibited significant shifts during violet LED irradiation. Specifically, violet LED irradiation led to a significant reduction in the relative abundance of Fusobacterium species, but a significant increase in several species of oral bacteria, such as Veillonella and Campylobacter. Our study provides an overview of oral plaque microbiota changes under violet LED irradiation, and highlights the potential of this method for adjusting the balance of the oral microbiome without inducing antibiotic resistance.
Potential of Industrial Pineapple (Ananas comosus (L.) Merrill) By-Products as Aromatic and Antioxidant Sources
Authors: Valdés García Arantzazu , Domingo Martínez María Isabel , Ponce Landete Mercedes , Prats Moya María Soledad , Beltrán Sanahuja Ana
Published: November 2021

Pineapple is meanly commercially processed. However, it is a fruit that generates a high proportion of nonedible wastes, which are rich in antioxidant compounds and have a varied aromatic profile. These characteristics turn these by-products into potential agri-food waste that can be revalued and applied in different fields such as medical, pharmaceutical, or food applications. The aim of the present work was the characterization and extraction of the volatile compounds present in two pineapple by-products (peel and core) and the subsequent evaluation of their antioxidant capacity. For this purpose, the analysis of the aromatic profile of both by-products has been carried out using the headspace solid-phase microextraction technique coupled to gas chromatography with a mass spectrometry detector (HS-SPME-GC-MS). The optimization of the extraction conditions of the volatile compounds has been validated using a Box–Behnken experimental design. In addition, a quantitative analysis was carried out to determine the contents of two important volatiles in pineapple wastes, isopentyl, and ethyl acetate. Moreover, the estimation of the antioxidant capacity of the subproducts extracts was carried out using different methods All the antioxidant assays demonstrated that pineapple subproducts are rich in easily extractable antioxidants with possible applications in the food industry.
Hyponatremia and Oxidative Stress
Authors: Fibbi Benedetta , Marroncini Giada , Anceschi Cecilia , Naldi Laura , Peri Alessandro
Published: November 2021

Hyponatremia, i.e., the presence of a serum sodium concentration ([Na+]) < 136 mEq/L, is the most frequent electrolyte imbalance in the elderly and in hospitalized patients. Symptoms of acute hyponatremia, whose main target is the central nervous system, are explained by the “osmotic theory” and the neuronal swelling secondary to decreased extracellular osmolality, which determines cerebral oedema. Following the description of neurological and systemic manifestations even in mild and chronic hyponatremia, in the last decade reduced extracellular [Na+] was associated with detrimental effects on cellular homeostasis independently of hypoosmolality. Most of these alterations appeared to be elicited by oxidative stress. In this review, we focus on the role of oxidative stress on both osmolality-dependent and -independent impairment of cell and tissue functions observed in hyponatremic conditions. Furthermore, basic and clinical research suggested that oxidative stress appears to be a common denominator of the degenerative processes related to aging, cancer progression, and hyponatremia. Of note, low [Na+] is able to exacerbate multiple manifestations of senescence and to decrease progression-free and overall survival in oncologic patients.
Editorial for Special Issue “Environmental Factors Shaping the Soil Microbiome”
Authors: Anandham Rangasamy , Sa Tongmin
Published: November 2021

Soil is a complex system consisting of various abiotic and biotic factors interacting among themselves in a particular time period. These biotic factors are particularly affected by a large number of disturbances or perturbations occurring in the micro-niches. Soil microbiome is the paramount biotic factor responsible for nutrient cycling that in turn determines soil health and quality. However, there are limitations in studying soil systems as there are a number of unknown boxes that need to be checked before understanding their full-fledged contribution to the environment. The microbial diversity in the soil can be affected by salinity, contaminant, fertilization, nutrient accumulation, and cultivation practices. Additionally, plants can also benefit from these changes in microbial community composition, and novel microbial isolates can be used for enhancing their growth under various stress conditions. Collectively, this Special Issue includes various studies that determine key abiotic and biotic factors that can result in changes in microbial community composition in the soil system. These studies are carried out in specified environmental niches rather than microcosms, which provides a broader context in which to understand microbial dynamics.
A New General Type-2 Fuzzy Predictive Scheme for PID Tuning
Authors: Tavoosi Jafar , Shirkhani Mohammadamin , Abdali Ali , Mohammadzadeh Ardashir , Nazari Mostafa , Mobayen Saleh , Asad Jihad H. , Bartoszewicz Andrzej
Published: November 2021

The proportional-integral-derivative controller is widely used in various industrial applications. But, in many noisy problems the strong methods are needed to optimize the proportional-integral-derivative parameters. In this paper, a novel method is introduced for adjusting the proportional-integral-derivative parameters through the model predictive control and generalized type-2 fuzzy-logic systems. The rules of suggested fuzzy system are online adjusted and the parameters of proportional-integral-derivative are tuned based on the fuzzy model such that a cost function to be minimized. The designed controller is applied on continuous stirred tank reactor and the performance is compared with other traditional approaches. The main advantages are that the accuracy is improved by online modeling and optimization and a predictive scheme is added to the conventional proportional-integral-derivative controller.
Methods for Weighting Decisions to Assist Modelers and Decision Analysts: A Review of Ratio Assignment and Approximate Techniques
Authors: Ezell Barry , Lynch Christopher , Hester Patrick
Published: November 2021

Computational models and simulations often involve representations of decision-making processes. Numerous methods exist for representing decision-making at varied resolution levels based on the objectives of the simulation and the desired level of fidelity for validation. Decision making relies on the type of decision and the criteria that is appropriate for making the decision; therefore, decision makers can reach unique decisions that meet their own needs given the same information. Accounting for personalized weighting scales can help to reflect a more realistic state for a modeled system. To this end, this article reviews and summarizes eight multi-criteria decision analysis (MCDA) techniques that serve as options for reaching unique decisions based on personally and individually ranked criteria. These techniques are organized into a taxonomy of ratio assignment and approximate techniques, and the strengths and limitations of each are explored. We compare these techniques potential uses across the Agent-Based Modeling (ABM), System Dynamics (SD), and Discrete Event Simulation (DES) modeling paradigms to inform current researchers, students, and practitioners on the state-of-the-art and to enable new researchers to utilize methods for modeling multi-criteria decisions.
CFD Based Non-Dimensional Characterization of Energy Dissipation Due to Verticle Slosh
Authors: Wright Michael Dennis , Gambioli Francesco , Malan Arnaud George
Published: November 2021

We present the CFD based non-dimensional characterization of violent slosh induced energy dissipation due a tank under vertical excitation. Experimentally validated CFD is used for this purpose as an ideally suited and versatile tool. It is thus first demonstrated that a weakly compressible VoF based CFD scheme is capable of computing violent slosh induced energy dissipation with high accuracy. The resulting CFD based energy analysis further informs that the main source of energy dissipation during violent slosh is due liquid impact. Next, a functional relationship characterising slosh induced energy dissipation is formulated in terms of fluid physics based non-dimensional numbers. These comprised contact angle and liquid–gas density ratio as well as Reynolds, Weber and Froude numbers. The Froude number is found the most significant in characterising verticle violent slosh induced energy dissipation (in the absence of significant phase change). The validated CFD is consequently employed to develop scaling laws (curve fits) which quantify energy dissipation as a function of the most important fluid physics non-dimensional numbers. These newly developed scaling laws show for the first time that slosh induced energy dissipation may be expressed as a quadratic function of Froude number and as a linear function of liquid–gas density ratio. Based on the aforementioned it is postulated that violent slosh induced energy dissipation may be expressed as a linear function of tank kinetic energy. The article is concluded by demonstrating the practical use of the novel CFD derived non-dimensional scaling laws to infer slosh induced energy dissipation for ideal experiments (with exact fluid physics similarity to the full scale Aircraft) from (non-ideal) slosh experiments.
Predicting Ethanol Steam Reforming Products of Au-Cu Supported over Nano-Shaped CeO2 Using the Johnsen Measure in PLS
Authors: Zhi Chen , Tahir Muhammad , Mehmood Tahir
Published: November 2021

Hydrogen fuel cells have long been regarded as a more environmentally friendly alternative to traditional fossil fuels. Ethanol steam reforming (ESR) is a promising long-term, safe method of producing carbon-neutral hydrogen. ESR products are (CeCO2) support generate hydrogen (H2) with byproducts such as carbon dioxide (CO2) and carbon monoxide (CO). The researchers are interested in the quantification and estimation of syngas components. The current article introduces the Johnsen index-based measure in partial least squares (PLS) for predicting ESR products with cube, polyhydra, and rod morphologies, based on FTIR. The proposed method makes use of existing filter measures such as loading weights, variable importance on projection, and significant correlation. The proposed PLS measures based on the Johnsen index outperform the existing methods for predicting ESR products based on FTIR spectroscopic data. For (H2) conversion percent prediction with cube and polyhedra morphologies, the functional compounds (C-O), (C=O), (CH), and (C-H,=CH2) are common. Similarly, the functional compound (s-RCH=CHR) is frequently used for (H2) conversion percent prediction with polyhedra and rod morphologies. Moreover, on simulated data, the proposed Johnsen measure in PLS demonstrates higher sensitivity and accuracy. Furthermore, the proposed Johnsen measure in PLS identifies influential wavenumbers that map over the functional compounds.
Consequences of Deep Rolling at Elevated Temperature on Near-Surface and Fatigue Properties of High-Manganese TWIP Steel X40MnCrAl19-2
Authors: Wegener Thomas , Krochmal Marcel , Oevermann Torben , Niendorf Thomas
Published: November 2021

Due to pronounced work-hardening induced by the complex interplay of deformation mechanisms such as dislocation slip, twinning and/or martensitic phase transformation, high-manganese steels represent a class of materials well-suited for mechanical surface treatment. In the present study, the fatigue behavior of a high-mangsanese steel showing twinning-induced plasticity (TWIP) effect at room temperature (RT) was investigated after deep rolling at 550 °C. Results are compared to a former study discussing the behavior after RT deep rolling. Evolution of the near-surface microstructure was analyzed by scanning electron microscopy (SEM), microhardness measurements and residual stress depth profiles obtained by X-ray diffraction (XRD). Both uniaxial tensile tests and uniaxial tension-compression fatigue tests have been conducted in order to rationalize the macroscopic material behavior. Following deep rolling at 550 °C, SEM measurements employing electron backscatter diffraction (EBSD) revealed a heavily deformed surface layer as well as localized deformation twinning. Specimens showed inferior hardness and residual stress depth profiles when compared to RT deep rolled counterparts. Tensile tests indicated no difference between the conditions considered. Fatigue properties however were improved. Such behavior is rationalized by a more stable residual stress state induced by dynamic strain aging.
Numerical Study of Thermophoresis on Mass Transfer from Natural Convection Flow over a Vertical Porous Medium with Variable Wall Heat Fluxes
Authors: Huang Jian-Sheng
Published: November 2021

This study investigates heat and mass transfer under natural convection flow along a vertical permeable surface with variable wall heat fluxes through a porous medium. The non-Darcian model is employed for the medium. The effects of suction/blowing, inertia, buoyancy ratio, exponent of heat flux, position parameter, Schmidt number, and thermophoresis are considered. The governing equations of continuity, momentum, energy, and concentration are solved by adopting similarity transformation and Runge–Kutta integration with a shooting technique. Results of interest, such as velocity, temperature, and concentration profiles related to local Nusselt and Sherwood numbers, are obtained for the selected buoyancy ratio at different magnitudes of the thermophoretic effect. The numerical solutions help us to realize the gas diffusion phenomena and control the transport technology.
Mathematical Analysis of Non-Isothermal Reaction–Diffusion Models Arising in Spherical Catalyst and Spherical Biocatalyst
Authors: Tripathi Vivek Mani , Srivastava Hari Mohan , Singh Harendra , Swarup Chetan , Aggarwal Sudhanshu
Published: November 2021

The theory of dynamical systems and their widespread applications involve, for example, the Lane–Emden-type equations which are known to arise in initial- and boundary-value problems with singularity at the time t=0. The main objective of this paper is to make use of some mathematical analytic tools and techniques in order to numerically solve some reaction–diffusion equations, which arise in spherical catalysts and spherical biocatalysts, by applying the Chebyshev spectral collocation method. The proposed scheme has good accuracy. The results are demonstrated by means of illustrative graphs and numerical tables. The accuracy of the proposed method is verified by a comparison with the results which are derived by using analytical methods.