bluuebunny/crossref_metadata_2025_split huggingface dataset:
In Vitroandin SilicoInvestigation of DNA Interaction, Topoisomerase I and II Inhibitory Properties of Polydatin
Authors: Şöhretoğlu Didem , Barut Burak , Sari Suat , Özel Arzu , Kuruüzüm‐Uz Ayşe , Arroo Randolph 
Published: September 2022

AbstractPolydatin or piceid, is the 3‐O‐glucoside of resveratrol and is found abundantly in grapes, peanuts, wine, beer, and cacao products. Although anticancer activity of polydatin was reported before, and potential antiproliferative mechanisms of polydatin have been proposed, its direct effects on DNA and inhibitory potential against topoisomerase enzymes have remained unknown. In this study we aimed to reveal the link between polydatin's effects on DNA and DNA‐topoisomerases and its antiproliferative promise. For this purpose, we evaluated the effects of polydatin on DNA and DNA topoisomerase usingin vitroandin silicotechniques. Polydatin was found to protect DNA against Fenton reaction‐induced damage while not showing any hydrolytic nuclease effect. Further, polydatin inhibited topoisomerase II but not topoisomerase I. According to molecular docking studies, polydatin preferably showed minor groove binding to DNA where the stilbene moiety was important for binding to the DNA‐topoisomerase II complex. As a result, topoisomerase II inhibition might be another anticancer mechanism of polydatin.
The effects of the COVID‐19 pandemic on French‐Canadian adolescents' academic motivation: A follow‐up study
Authors: Smith Jonathan , Guimond Fanny‐Alexandra , St‐Amand Jérôme , Fitzpatrick Caroline , Bergeron Julie , Gagnon Mathieu 
Published: September 2022

AbstractWe previously shared results suggesting that the academic motivation of a sample of French‐Canadian adolescents remained stable from few weeks before the first wave to the second wave of the COVID‐19 pandemic. We here examine if this pattern persisted using data collected at a third time point.
ResNet models for rapid identification of species and geographical origin of wild boletes from Yunnan, and MaxEnt model for delineation of potential distribution
Authors: Chen Xiong , Liu Hong Gao , Li Jie Qing , Wang Yuan Zhong 
Published: September 2022

AbstractYunnan is known for its rich biodiversity and is known as the Wild Mushroom Kingdom. Boletes are a world‐renowned wild edible mushroom, with unique sensory characteristics, nutritional value and medicinal value extraordinary. However, the species and geographical origin of boletes influence their price and quality. In this study, a method was developed to identify species and geographical origin simultaneously. Therefore, Fourier transform near‐infrared (FT‐NIR) data sets of boletes were collected and converted to two‐dimensional correlation spectroscopy (2D‐COS). On this basis, the species and geographic origins of boletes were identified using Residual neural network (ResNet) image analysis model. The results showed that FT‐NIR could identify boletes species and geographical origins, 7000–4000 cm−1 band was more suitable for species identification, 7000–5300 cm−1 band was more suitable for geographical origins identification. In addition, the environmental factors with high contribution to the distribution of boletes were screened based on the maximum entropy (MaxEnt) model. This allows characterization of the potential geographic distribution of boletes. The results showed that precipitation factors played a vital role in its distribution and might even be responsible for the difference in chemical composition.
ATR‐FTIR spectroscopy and chemometric complexity: unfolding the intra‐skeleton variability
Authors: Zupanič Pajnič Irena , Leskovar Tamara , Jerman Ivan 
Published: September 2022

AbstractSpectroscopy of skeletal tissues is increasingly used in various fields, including legal medicine, forensic science and archaeology. As it is fast and technically and financially affordable yet accurate and widely applicable, spectroscopy is often used when investigating skeletal tissues. Despite its usefulness, the heterogeneity of skeletal tissues highly affects their chemical composition and complicates the interpretation of the spectroscopy results. Though the research on the use of spectroscopy and skeletal tissues from various contexts is growing, little is known regarding the differences in the chemometric indices caused by intra‐skeleton variability. The objectives were a comparison of the chemometric indices between teeth and bones, between different bone classes and between the skeletal elements within a bone class as well as an attempt to correlate the observed similarities or differences in chemometric indices to the functional or structural differences of skeletal elements. Different skeletal elements of three individuals were analysed with attenuated total reflectance (ATR)–Fourier transform infrared (FTIR) spectroscopy and compared. Significant differences between the chemometric indices of the bones and teeth were observed and meaningfully correlated with their structural differences. Though more subtle and harder to understand, significant differences were also observed between and within the bone classes and were tentatively correlated with their structural and functional differences. The observed variability agrees with other studies that stress the importance of intra‐skeleton variability, which should be acknowledged when using spectroscopy to investigate skeletal tissues.
Dimorpholinoacetylene and Its Use for the Synthesis of Tetraaminocyclobutadiene Species
Authors: Körner Lukas , Ho Luong Phong , Puchta Ralph , Stanger Amnon , Tamm Matthias 
Published: September 2022

AbstractThe new diaminoacetylene (DAA) dimorpholinoacetylene (3) was prepared from 1,1‐dimorpholinoethene (1) by bromination to form the dibromoketene aminal 2, which upon lithiation afforded 3 through a Fritsch‐Buttenberg‐Wiechell rearrangement. Heating 3 at elevated temperatures resulted in a complete conversion into the dimer 1,1,2,4‐tetramorpholino‐1‐buten‐3‐yne (4), which was used for the synthesis of four‐membered cyclic bent allene (CBA) transition‐metal complexes of the type [(CBA)MLn] (5‐7; MLn=AuCl, RhCl(COD), RhCl(CO)2; CBA=1,3,4,4‐tetramorpholino‐1,2‐cyclobutadiene; COD=1,5‐cyclooctadiene). The reaction of 3 with tetraethylammonium bromide gave 1,2,3,4‐tetramorpholinocyclobutenylium bromide (8), which reacted with bromine to form 1,2,3,4‐tetra(morpholino)cyclobutenediylium bis(tribromide) (9). Compound 9 represents the first fully characterized compound containing a tetraaminocyclobutadiene dication and displays a nearly planar C4N4 core as shown by X‐ray diffraction analysis. Detailed quantum chemical calculations were performed to assess the aromaticity of tetraaminocyclubutadiene dications by employing the Nucleus Independent Chemical Shift (NICS) method and current density analysis.
Recent Advances in Real‐Time Analysis of Electrochemical Reactions by Electrochemical Mass Spectrometry†
Authors: Zhang Xianhao , Zhan Jirui , Yu Zhengyou , Deng Jintao , Li Meixian , Shao Yuanhua 
Published: September 2022

Comprehensive SummaryElectrochemical mass spectrometry (EC‐MS) is a powerful tool to capture and analyze the intermediates and products during electrochemical reactions. This hyphenated technique combines electrochemistry with mass spectrometry using specific apparatuses, which helps researchers study mechanisms of redox reactions by in situ detecting chemical composition changes. Recently, various EC‐MS methods have been applied in a series of electrochemical reactions to reveal the mechanisms, mainly in the areas of electrochemical sensors, organic electrochemistry, and electrocatalysis. In this review, we intend to summarize the recent advances in real‐time analysis of different types of electrochemical reactions by EC‐MS and offer an outlook on the perspectives in these areas.
Elodexanthones A—J, Isoprenylated Xanthone Derivatives with Diverse Skeletons and Bioactivities from Hypericum elodeoides
Authors: Mu Yanbing , Li Yaqi , Li Qiji , Xu Wenjun , Sun Yunpeng , Wang Siyuan , Cui Letian , Kong Lingyi , Luo Jun 
Published: September 2022

Comprehensive SummaryElodexanthones A—J (1—10), two pairs of rearranged isoprenylated xanthone enantiomers with an unprecedent 6/6/5/6 tetracyclic core (1—2) along with seven new isoprenylated xanthones (3—9) and a pair of phenylpropanoid xanthones (10), were purified and enantio‐separated from the whole plant of Hypericum elodeoides. Their structures including absolute configurations were characterized by the comprehensive analysis of NMR, HRESIMS, NMR calculations, and ECD calculations. Through Bayer‐Villiger oxidation, Claisen condensation and electrophilic addition, the rearranged skeletons of elodexanthones A—B (1—2) were generated from isoprenylated xanthone precursors. The bioactivities evaluation exhibited that compounds 3, 5, 8—10 showed anti‐inflammatory activity with the IC50 values in the range of 9.53—34.39 μmol/L, and compounds 3—7, and 9 showed notable α‐glucosidase inhibitory activity (IC50: 6.02—257.11 μmol/L).
House price prediction using hedonic pricing model and machine learning techniques
Authors: Zaki John , Nayyar Anand , Dalal Surjeet , Ali Zainab H. 
Published: September 2022

SummaryThe problem with property valuation is that it is extremely complex. It is difficult to objectively model the pricing process or fairly estimate a property value. Many factors can contribute to this complexity such as spatial and time factors. Evaluators and researchers have been trying to model the process for centuries. Up until recently, when computer‐aided valuation systems provided better solutions in the data evaluation and real estate valuation. Nevertheless, they may suffer from low transparency, inaccuracy, and inefficiency. This work explores the ability of machine learning techniques (MLTs) in enhancing economic activities by increasing the accuracy of house price prediction. In this article, XGBoost algorithm has been integrated with outlier sum‐statistic (OS) approach. In the real estate industry, the price of property plays a crucial role in economic growth. The research attempts to predict the price of a house using MLTs. Here, the price of the property is predicted using Extreme Gradient (XG) boosting algorithm and hedonic regression pricing. Both XGBoost and hedonic pricing models use 13 variables as inputs to predict house prices. The contribution of this research lies in the practicality of using XGboost technique to predict house prices. Finally, the accuracy of the prediction algorithms is reported with XGBoosting showing the highest accuracy of 84.1% while the accuracy of the hedonic regression algorithm is 42%.
Estimation of quantitative genetic parameters for dry matter yield and vegetative persistence‐related traits in a white clover training population
Authors: Ehoche O. Grace , Arojju Sai Krishna , Cousins Greig , O'Connor Jessica R. , Maw Brian , Tate Jennifer A. , Lockhart Peter J. , Jahufer M. Z. Zulfi , Griffiths Andrew G. 
Published: September 2022

AbstractWhite clover (Trifolium repens L.), an economically important forage legume in temperate pastures, provides quality herbage and plant‐available nitrogen. Enhancing breeding efforts to improve dry matter (DM) yield and vegetative persistence will increase on‐farm value of this forage. To increase genetic gain for such traits, breeding tools like genomic selection have proven to be highly valuable in other crops. However, its success relies on a sufficiently large training population and key fundamentals of selective breeding, that is, presence of additive variation. We investigated quantitative genetic parameters for spring DM yield and vegetative persistence in a white clover training population comprising 200 half‐sibling (HS) families. This population was established in a replicated cattle‐grazed, mixed‐sward field trial at two contrasting locations and assessed for spring DM yield and stolon‐related vegetative persistence traits over a 3‐yr period. The additive variation and genotype × environment interactions, comprising the effects from year, season, and location were significant (P < .05) for most traits. Narrow‐sense heritability for all traits ranged from low (.13; post‐summer stolon branches) to high (.73; leaf size) and there was a positive phenotypic correlation (.28) between spring DM yield and stolon number. These results indicate that both spring DM yield and persistence can be concurrently improved through selective breeding in the current population. We also demonstrated that applying a high selection pressure produces the highest predicted genetic gain. There is, however, a trade‐off between genetic gain and diversity in the population for the long‐term success of a breeding program.
NAT10: An RNA cytidine transferase regulates fatty acid metabolism in cancer cells
Authors: Dalhat Mahmood Hassan , Mohammed Mohammed Razeeth Shait , Alkhatabi Hind Ali , Rehan Mohd , Ahmad Aamir , Choudhry Hani , Khan Mohammad Imran 
Published: September 2022

AbstractBackgroundN‐4 cytidine acetylation (ac4C) is an epitranscriptomics modification catalyzed by N‐acetyltransferase 10 (NAT10); important for cellular mRNA stability, rRNA biogenesis, cell proliferation and epithelial to mesenchymal transition (EMT). However, whether other crucial pathways are regulated by NAT10‐dependent ac4C modification in cancer cells remains unclear. Therefore, in this study, we explored the impact of NAT10 depletion in cancer cells using unbiased RNA‐seq.MethodsHigh‐throughput sequencing of knockdown NAT10 in cancer cells was conducted to identify enriched pathways. Acetylated RNA immunoprecipitation‐seq (acRIP‐seq) and RIP‐PCR were used to map and determine ac4C levels of RNA. Exogenous palmitate uptake assay was conducted to assess NAT10 knockdown cancer cells using Oil Red O staining and lipid content analysis. Gas‐chromatography–tandem mass spectroscopy (GC/MS) was used to perform untargeted lipidomics.ResultsHigh‐throughput sequencing of NAT10 knockdown in cancer cells revealed fatty acid (FA) metabolism as the top enriched pathway through the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis in differentially downregulated genes. FA metabolic genes such as ELOLV6, ACSL1, ACSL3, ACSL4, ACADSB and ACAT1 were shown to be stabilised via NAT10‐dependent ac4C RNA acetylation. Additionally, NAT10 depletion was shown to significantly reduce the levels of overall lipid content, triglycerides and total cholesterol. Further, NAT10 depletion in palmitate‐loaded cancer cells showed decrease in ac4C levels across the RNA transcripts of FA metabolic genes. In untargeted lipidomics, 496 out of 2 279 lipids were statistically significant in NAT10 depleted cancer cells, of which pathways associated with FA metabolism are the most enriched.ConclusionsConclusively, our results provide novel insights into the impact of NAT10‐mediated ac4C modification as a crucial regulatory factor during FA metabolism and showed the benefit of targeting NAT10 for cancer treatment.
Flow‐rule integration for quality of service enhancement in software‐defined vehicular network
Authors: Praveen kumar Karunanithi , Sivanesan Perumal , Thirumurugan Rajendran 
Published: September 2022

SummaryA software‐defined vehicular network (SDVN) is a concern, where roadside units are connected, and a massive amount of data is accumulated at the software‐defined network (SDN) switches, leading to the flow table overflow problem. Existing works are concentrated more on flow‐rule aggregation in a fast manner at the switches, which impacts quality of service (QoS) at SDVN. QoS‐wise flexible OpenFlow‐rule integration method is proposed to address the challenges of OpenFlow‐table overflow problem in SDN controller switches. By having minimal impact on the QoS of the vehicular network, it reduces the number of OpenFlow rules using a key‐based mechanism. However, we note that choosing a QoS path from numerous paths is important by considering the OpenFlow‐table usage at the switches. Based on this, a flexible‐fit heuristic approach is proposed, which considers the insertions of OpenFlow rule besides with congestion flow rule‐capacity switch on a path while reducing the cumulative number of OpenFlow rules in SDVN. Experimental results of this scheme show that it decreases average end‐to‐end time delay and packet dropping by 37% and 14%, respectively. Compared with the existing scheme, the average network throughput increases by 22%, and also it has a comparable improvement in the reduction of OpenFlow rules at the switches of SDVN.
Caching of popular content at F‐RAN for mmWave new radio
Authors: Aldalbahi Adel , Jasim Mohammed A. , Bouzguenda Mounir , Enshasy Hesham , Sumsudeen Rajamohamed , Siasi Nazli 
Published: September 2022

SummaryFog computing allows for local data processing at the edge of the network. This allows for reduced link delays between mobile users and access points. Here, fog nodes are collocated with radio remote heads (RRHs) to provide local processing capabilities, that is, creating fog radio access network (F‐RAN) that can support ultralow latency for cellular networks that operate on millimeter wave (mmWave) bands. Here, mobile stations (MS) demand various network functions (NFs) that correspond to different service requests. Hence, it is critical to study function popularity and allow content caching at the F‐RAN. Given the limited resources at the fog nodes, it is important to efficiently manage the resources to improve network operations and enhance the capacity at reduced delays and cost. Therefore, caching in mmWave F‐RAN requires node allocation that can accommodate the highest number of cached functions. Hence, this paper proposes a novel node placement scheme that leverages Nelder–Mead meta‐heuristic. Results show that the proposed scheme yields in reduced delay, cost, and power and energy consumption.
Cognitive bias modification training of attention and interpretation to reduce expectations of social rejection in adolescents with eating disorders: A small efficacy randomized controlled trial
Authors: Rowlands Katie , Beaty Taryn , Simic Mima , Grafton Ben , Hirsch Colette , Treasure Janet , Cardi Valentina 
Published: September 2022

AbstractObjectiveThis study aimed to investigate whether a computerized cognitive bias modification training delivered remotely would reduce expectations of rejection in adolescents with eating disorders.MethodSixty‐seven adolescents aged 12–18 (99.5% female) with an eating disorder diagnosis (94% anorexia nervosa) and receiving specialist treatment were recruited. Participants were randomized to an intervention condition (n = 37) which included treatment as usual (TAU) supplemented by nine sessions of online cognitive bias modification training for social stimuli (CBMT + TAU), or a control condition (n = 30), which included TAU only. Participants were invited to complete assessments at baseline and post‐intervention.ResultsIn the intervention condition, 22/37 participants completed six or more training sessions and post‐intervention measures, the pre‐defined criteria to be considered “completers.” In the control condition, 28/30 participants completed the post‐intervention measures. Participants who completed the intervention displayed a significantly greater reduction in negative interpretations of ambiguous social scenarios, with a medium effect size (p = .048, ηp2 = .090), and eating disorder psychopathology, with a medium effect size (p = .027, ηp2 = .105), compared to participants in the control condition. No significant between‐group differences were found on emotional response to criticism, and anxiety and depression symptoms post‐intervention (ps > .05; small effect sizes).DiscussionEnhancing treatment as usual with CBMT targeting expectations of social rejection might be feasible and effective to reduce expectations of social rejection and eating disorder psychopathology in adolescents with eating disorders. Training adaptations might be necessary to impact on emotional processing and comorbid psychological distress.Public SignificanceAdolescents with eating disorders who completed a brief (4‐week) online cognitive training intervention, alongside their usual treatment, reported greater reductions in expectations of social rejection and eating disorder psychopathology after the intervention, compared to a separate group of patients who received their usual treatment only. This brief and accessible intervention may be a helpful treatment adjunct for adolescents with eating disorders.
Speciation genomics and the role of depth in the divergence of rockfishes (Sebastes) revealed through Pool‐seq analysis of enriched sequences
Authors: Olivares‐Zambrano Daniel , Daane Jacob , Hyde John , Sandel Michael W. , Aguilar Andres 
Published: September 2022

AbstractSpeciation in the marine environment is challenged by the wide geographic distribution of many taxa and potential for high rates of gene flow through larval dispersal mechanisms. Depth has recently been proposed as a potential driver of ecological divergence in fishes, and yet it is unclear how adaptation along these gradients' shapes genomic divergence. The genus Sebastes contains numerous species pairs that are depth‐segregated and can provide a better understanding of the mode and tempo of genomic diversification. Here, we present exome data on two species pairs of rockfishes that are depth‐segregated and have different degrees of divergence: S. chlorostictus–S. rosenblatti and S. crocotulus–S. miniatus. We were able to reliably identify “islands of divergence” in the species pair with more recent divergence (S. chlorostictus–S. rosenblatti) and discovered a number of genes associated with neurosensory function, suggesting a role for this pathway in the early speciation process. We also reconstructed demographic histories of divergence and found the best supported model was isolation followed by asymmetric secondary contact for both species pairs. These results suggest past ecological/geographic isolation followed by asymmetric secondary contact of deep to shallow species. Our results provide another example of using rockfish as a model for studying speciation and support the role of depth as an important mechanism for diversification in the marine environment.