bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dengue determinants: Necessities and challenges for universal dengue vaccine development
Authors: Hussain Zahid , Rani Saima , Ma Fanshu , Li Wenjing , Shen Wenqi , Gao Tian , Wang Jine , Pei Renjun 
Published: January 2023

AbstractDengue illness can range from mild illness to life‐threatening haemorrhage. It is an Aedes‐borne infectious disease caused by the dengue virus, which has four serotypes. Each serotype acts as an independent infectious agent. The antibodies against one serotype confer homotypic immunity but temporary protection against heterotypic infection. Dengue has become a growing health concern for up to one third of the world's population. Currently, there is no potent anti‐dengue medicine, and treatment for severe dengue relies on intravenous fluid management and pain medications. The burden of dengue dramatically increases despite advances in vector control measures. These factors underscore the need for a vaccine. Various dengue vaccine strategies have been demonstrated, that is, live attenuated vaccine, inactivated vaccine, DNA vaccine, subunit vaccine, and viral‐vector vaccines, some of which are at the stage of clinical testing. Unfortunately, the forefront candidate vaccine is less than satisfactory, and its performance depends on serostatus and age factors. The lessons from clinical studies depicted ambiguity concerning the efficacy of dengue vaccine. Our study highlighted that viral structural heterogeneity, epitope accessibility, autoimmune complications, genetic variants, genetic diversities, antigen competition, virulence variation, host‐pathogen specific interaction, antibody‐dependent enhancement, cross‐reactive immunity among Flaviviruses, and host‐susceptibility determinants not only influence infection outcomes but also hampered successful vaccine development. This review integrates dengue determinants allocated necessities and challenges, which would provide insight for universal dengue vaccine development.
Trapped Pore Waters in the Open Proton Channel HV1
Authors: Boytsov Danila , Brescia Stefania , Chaves Gustavo , Koefler Sabina , Hannesschlaeger Christof , Siligan Christine , Goessweiner‐Mohr Nikolaus , Musset Boris , Pohl Peter 
Published: January 2023

AbstractThe voltage‐gated proton channel, HV1, is crucial for innate immune responses. According to alternative hypotheses, protons either hop on top of an uninterrupted water wire or bypass titratable amino acids, interrupting the water wire halfway across the membrane. To distinguish between both hypotheses, the water mobility for the putative case of an uninterrupted wire is estimated. The predicted single‐channel water permeability 2.3 × 10−12 cm3 s−1 reflects the permeability‐governing number of hydrogen bonds between water molecules in single‐file configuration and pore residues. However, the measured unitary water permeability does not confirm the predicted value. Osmotic deflation of reconstituted lipid vesicles reveals negligible water permeability of the HV1 wild‐type channel and the D174A mutant open at 0 mV. The conductance of 1400 H+ s−1 per wild‐type channel agrees with the calculated diffusion limit for a ≈2 Å capture radius for protons. Removal of a charged amino acid (D174) at the pore mouth decreases H+ conductance by reducing the capture radius. At least one intervening amino acid contributes to H+ conductance while interrupting the water wire across the membrane.
An In Situ Assembled Trapping Gel Repairs Spinal Cord Injury by Capturing Glutamate and Free Calcium Ions
Authors: Huang Ying , Wang Jialun , Yue Chunyan , Wang Ran , Guo Qiyuan , Wang Tingyu , Wang Daojuan , Dong Hong , Hu Yiqiao , Tao Gaojian , Li Xihan 
Published: January 2023

AbstractSpinal cord injury (SCI) can lead to devastating autonomic dysfunction. One of the most challenging issues for functional repair in SCI is the secondary damage caused by the increased release of glutamate and free Ca2+ from injured cells. Here, an in situ assembled trapping gel (PF‐SA‐GAD) is developed to sweep glutamate and Ca2+, promoting SCI repair. The hydrogel solution is a mixture of recombinant glutamate decarboxylase 67 (rGAD67) protein, sodium alginate (SA), and pluronic F‐127 (PF‐127). After intrathecal administration, temperature‐sensitive PF‐127 promoted in situ gelation. Glutamate (Glu) is captured and decarboxylated by rGAD67 into γ‐aminobutyric acid (GABA). SA reacted with the free Ca2+ to generate gellable calcium alginate. Thereby, this in situ trapping gel retarded secondary neuron injury caused by Glu and free Ca2+ during SCI. In rat models of SCI, PF‐SA‐GAD reduces the lesion volume and inflammatory response after SCI, restores the motor function of rats with SCI. Together, the in situ assembled trapping gel is a long‐term effective and minimally invasive sweeper for the direct elimination of glutamate and Ca2+ from injury lesions and can be a novel strategy for SCI repair by preventing secondary injury.
Ultrahigh Detectivity Broad Spectrum UV Photodetector with Rapid Response Speed Based on p‐β Ga2O3/n‐GaN Heterojunction Fabricated by a Reversed Substitution Doping Method
Authors: Han Yurui , Wang Yuefei , Fu Shihao , Ma Jiangang , Xu Haiyang , Li Bingsheng , Liu Yichun 
Published: January 2023

AbstractAn excellent broad‐spectrum (220–380 nm) UV photodetector, covering the UVA‐UVC wavelength range, with an ultrahigh detectivity of ≈1015 cm Hz1/2 W−1, is reported. It is based on a p‐β Ga2O3/n‐GaN heterojunction, in which p‐β Ga2O3 is synthesized by thermal oxidation of GaN and a heterostructure is constructed with the bottom n‐GaN. XRD shows the oxide layer is (−201) preferred oriented β‐phase Ga2O3 films. SIMS and XPS indicate that the residual N atoms as dopants remain in β Ga2O3. XPS also demonstrates that the Fermi level is 0.2 eV lower than the central level of the band gap, indicating that the dominant carriers are holes and the β Ga2O3 is p‐type conductive. Under a bias of −5 V, the photoresponsivity is 56 and 22 A W−1 for 255 and 360 nm, respectively. Correspondingly, the detectivities reach an ultrahigh value of 2.7 × 1015 cm Hz1/2 W−1 (255 nm) and 1.1 × 1015 cm Hz1/2 W−1 (360 nm). The high performance of this UV photodetector is attributed mainly to the continuous conduction band of the p‐β Ga2O3/n‐GaN heterojunction without a potential energy barrier, which is more helpful for photogenerated electron transport from the space charge region to the n‐type GaN layer.
Active BiVO4 Swimmers Propelled by Depletion Gradients Caused by Photodeposition
Authors: Wittmann Martin , Voigtmann Maximilian , Simmchen Juliane 
Published: January 2023

AbstractArtificial active matter often self‐propels by creating gradients of one or more species or quantities. For chemical swimmers, most frequently either O2 or H+ that are created in certain catalytic reactions are causing the interfacial flows which drive the self‐propulsion. While the palette of reactions is extending constantly, especially toward more bio‐compatible fuels, the depletion of species is often overlooked. Here, the photodeposition of metal species on BiVO4 micro swimmers is considered. During the photodeposition reaction, metal ions are removed from the solution creating a depleted region around the particle. The ability of this depletion to drive active motion of artificial micro swimmers, as well as the influences of different metal ions and counter ions on the motion are investigated and cross compared.
The coral‐inspired steam evaporator for efficient solar desalination via porous and thermal insulation bionic design
Authors: Zhang He , Li Xiaoke , Zheng Size , Wen Jin , Zhou Jiaying , Yang Rui , Luo Wenmei , Yang Liu , Wu Xiaohu 
Published: January 2023

AbstractThe solar‐driven interfacial evaporation (SIE) technology shows great prospects in seawater desalination and sewage treatment, but it is unable to obtain highly efficient and high‐quality clean nontoxic water at low cost. Here, a novel biodegradable hydrogel‐based solar evaporator (BBH‐L) with a bionic coral structure taking Chinese ink as the solar absorber was developed. This evaporator consists of chitosan/polyvinyl alcohol hydrogel and a loofah substrate. The average evaporation rate and efficiency of BBH‐L reach 4.37 kg/(m2·h) and 98.2%, respectively, under one sun illumination (1 kW/m2), which are attributed to its excellent thermal localization and water transporting abilities. Meanwhile, high salt resistance enables BBH‐L to achieve efficient desalination and purification of other unconventional water. Heavy metal ions in seawater can be effectively removed by chelation and forming hydrogen bonds in hydrogels. This study is anticipated to provide new possibilities to enhance evaporation performance and reduce the costs of water treatment systems.
Highly Sensitive Detection of Complicated Mutations of Drug Resistance in Mycobacterium tuberculosis Using a Simple, Accurate, Rapid, and Low‐Cost Tailored‐Design Competitive Wild‐Type Blocking Assay
Authors: Yan Mengqiu , Zhao Zhenzhen , Wu Tao , Liu Tangyuheng , Xu Gaolian , Xu Hong , Ying Binwu 
Published: January 2023

AbstractEstablishing simple, rapid, and highly sensitive molecular assays is crucial for timely diagnosis and effective treatment of drug‐resistant tuberculosis. However, current genotypic drug susceptibility testing (DST) still encounters enormous challenges including lower sensitivity than phenotypic DST and insufficient accuracy. Herein, a simple, low‐cost, multiplex real‐time polymerase chain reaction‐based assay is established to achieve highly sensitive detection of low‐abundant mutants through competitive wild‐type blocking (COWTB). Analytical performance of the COWTB assay can achieve 1% or even 0.1% mutants under background of 10 000 wild‐type genomes/test. Furthermore, clinical practice feasibility is evaluated to identify resistance to rifampicin (RIF), isoniazid (INH), and streptomycin (SM) on 92 actual clinical samples, its sensitivity is 93.8% for RIF and 100% for INH and SM, and specificity is 100% each for RIF, INH, and SM when using DNA sequencing as the reference standard. In comparison, the sensitivity of reverse dot blotting assay commonly used in clinics is 93.8%, 90.0%, and 84.6%, and the specificity is 96.1%, 98.6%, and 100% for RIF, INH, and SM, respectively. Importantly, the COWTB assay can also be applicable for other drug‐resistant mutations and pave a promising detection strategy to fill the gap between phenotypic and genotypic DST for detecting low‐abundant drug‐resistant M. tuberculosis.
Engineering a Synthetic RNA Segregation System
Authors: Hürtgen Daniel , Mascarenhas Judita , Vibhute Mahesh A. , Weise Laura I. , Mayr Viktoria S. , Sourjik Victor , Mutschler Hannes 
Published: January 2023

AbstractCells possess a number of active segregation machineries for both chromosomal and large extrachromosomal DNA elements to avoid stochastic loss during cell division. In contrast, system that can be exploited for active, general segregation of RNA molecules including mRNAs or self‐replicating RNA constructs are currently lacking. Here, we present an artificial RNA segregation system derived from the bacterial type II ParMRC plasmid segregation system and the RNA coliphage MS2. We show that fusing the partition protein ParR with the MS2 RNA coat protein enables specific binding to microbeads decorated with RNA‐repeats of the archetypical MS2 RNA operator hairpin. Addition of the actin homologue ParM protein triggers efficient and rapid microbeads segregation via ATP‐dependent ParM polymerization. Our new RNA partitioning system could be used for specific localization of mRNAs and/or the stable maintenance of self‐replicating RNA vectors in various contexts such as living and artificial cells.
Computational Social Science for Public Policy
Authors: Margetts Helen , Dorobantu Cosmina 
Published: January 2023

AbstractComputational Social Science (CSS), which brings together the power of computational methods and the analytical rigour of the social sciences, has the potential to revolutionise policymaking. This growing field of research can help governments take advantage of large-scale data on human behaviour and provide policymakers with insights into where policy interventions are needed, which interventions are most likely to be effective, and how to avoid unintended consequences. In this chapter, we show how Computational Social Science can improve policymaking by detecting, measuring, predicting, explaining, and simulating human behaviour. We argue that the improvements that CSS can bring to government are conditional on making ethical considerations an integral part of the process of scientific discovery. CSS has an opportunity to reveal bias and inequalities in public administration and a responsibility to tackle them by taking advantage of research advancements in ethics and responsible innovation. Finally, we identify the primary factors that prevented Computational Social Science from realising its full potential during the Covid-19 pandemic and posit that overcoming challenges linked to limited data flows, siloed models, and rigid organisational structures within government can usher in a new era of policymaking.
Computational Climate Change: How Data Science and Numerical Models Can Help Build Good Climate Policies and Practices
Authors: Tavoni Massimo 
Published: January 2023

AbstractComputational social science can help advance climate policy and help solve the climate crises. To do so, several steps need to be overcome to make the best use of the wealth of data and variety of models available to evaluate climate change policies. Here, we review the state of the art of numerical modelling and data science methods applied to policy evaluation. We emphasize that significant progress has been made but that critical social and economic phenomena—especially related to climate justice—are not yet fully captured and thus limit the predictivity and usefulness of computational approaches. We posit that the integration of statistical and numerical approaches is key to developing a new impact evaluation science that overcomes the traditional divide between ex ante and ex post approaches.
Digital Epidemiology
Authors: Mejova Yelena 
Published: January 2023

AbstractComputational social science has had a profound impact on the study of health and disease, mainly by providing new data sources for all of the primary Ws—what, who, when, and where—in order to understand the final “why” of disease. Anonymized digital trace data bring a new level of detail to contact networks, search engine and social media logs allow for the now-casting of symptoms and behaviours, and media sharing informs the formation of attitudes pivotal in health decision-making. Advances in computational methods in network analysis, agent-based modelling, as well as natural language processing, data mining, and time series analysis allow both the extraction of fine-grained insights and the construction of abstractions over the new data sources. Meanwhile, numerous challenges around bias, privacy, and ethics are being negotiated between data providers, academia, the public, and policymakers in order to ensure the legitimacy of the resulting insights and their responsible incorporation into the public health decision-making. This chapter outlines the latest research on the application of computational social science to epidemiology and the data sources and computational methods involved and spotlights ongoing efforts to address the challenges in its integration into policymaking.
Improving CBCT image quality to the CT level using RegGAN in esophageal cancer adaptive radiotherapy
Authors: Wang Hao , Liu Xiao , Kong Lingke , Huang Ying , Chen Hua , Ma Xiurui , Duan Yanhua , Shao Yan , Feng Aihui , Shen Zhenjiong , Gu Hengle , Kong Qing , Xu Zhiyong , Zhou Yongkang 
Published: January 2023

Abstract
Objective
This study aimed to improve the image quality and CT Hounsfield unit accuracy of daily cone-beam computed tomography (CBCT) using registration generative adversarial networks (RegGAN) and apply synthetic CT (sCT) images to dose calculations in radiotherapy.

Methods
The CBCT/planning CT images of 150 esophageal cancer patients undergoing radiotherapy were used for training (120 patients) and testing (30 patients). An unsupervised deep-learning method, the 2.5D RegGAN model with an adaptively trained registration network, was proposed, through which sCT images were generated. The quality of deep-learning-generated sCT images was quantitatively compared to the reference deformed CT (dCT) image using mean absolute error (MAE), root mean square error (RMSE) of Hounsfield units (HU), and peak signal-to-noise ratio (PSNR). The dose calculation accuracy was further evaluated for esophageal cancer radiotherapy plans, and the same plans were calculated on dCT, CBCT, and sCT images.

Results
The quality of sCT images produced by RegGAN was significantly improved compared to the original CBCT images. ReGAN achieved image quality in the testing patients with MAE sCT vs. CBCT: 43.7 ± 4.8 vs. 80.1 ± 9.1; RMSE sCT vs. CBCT: 67.2 ± 12.4 vs. 124.2 ± 21.8; and PSNR sCT vs. CBCT: 27.9 ± 5.6 vs. 21.3 ± 4.2. The sCT images generated by the RegGAN model showed superior accuracy on dose calculation, with higher gamma passing rates (93.3 ± 4.4, 90.4 ± 5.2, and 84.3 ± 6.6) compared to original CBCT images (89.6 ± 5.7, 85.7 ± 6.9, and 72.5 ± 12.5) under the criteria of 3 mm/3%, 2 mm/2%, and 1 mm/1%, respectively.

Conclusion
The proposed deep-learning RegGAN model seems promising for generation of high-quality sCT images from stand-alone thoracic CBCT images in an efficient way and thus has the potential to support CBCT-based esophageal cancer adaptive radiotherapy.
Kinder- und Jugendgesundheit in der Klimakrise
Authors: Eichinger Michael , Andreas Marike , Hoeppe Alice , Nisius Katja , Rink Katharina 
Published: January 2023

ZusammenfassungKinder und Jugendliche sind aufgrund ihrer Physiologie und längerer Expositionszeiten besonders von den gesundheitlichen Folgen der Klimakrise betroffen. Darüber hinaus wird die Klimakrise ohne Gegenmaßnahmen vorbestehende gesundheitliche Ungleichheiten verschärfen, da Kinder und Jugendliche aus Familien mit niedrigem sozioökonomischen Status und schlechterem Gesundheitszustand besonders stark von den gesundheitlichen Folgen der Klimakrise betroffen sind.Die Klimakrise wirkt sich über zahlreiche Mechanismen auf die Gesundheit von Kindern und Jugendlichen aus, wobei jedes Organsystem betroffen sein kann. Extremwetterereignisse gehen u. a. mit einem erhöhten Risiko für Hitzschläge, Elektrolytstörungen, Verletzungen und psychische Erkrankungen einher. Der Temperaturanstieg führt zu veränderten Ausbreitungsgebieten von Krankheitsvektoren, die u. a. die Erreger der Borreliose oder des West-Nil-Fiebers übertragen. Im Bereich der psychischen Gesundheit stehen Klimaangst und die psychischen Auswirkungen von Extremwetterereignissen im Vordergrund.Zahlreiche Maßnahmen in den Bereichen Klimaschutz und Klimafolgenanpassung haben zugleich positive Effekte auf die Gesundheit und werden daher als Win-Win-Lösungen bezeichnet (z. B. aktiver Transport, Ausweitung urbaner Grünflächen). Kinder- und Jugendärzt:innen können einen wichtigen Beitrag zu Prävention und adäquater Behandlung von klimawandelassoziierten Erkrankungen leisten, indem sie u. a. in U‑Untersuchungen Win-Win-Lösungen adressieren und klimawandelbedingte Belastungsfaktoren in der Anamnese berücksichtigen. Darüber hinaus können sie durch ihr Engagement in Organen der ärztlichen Selbstverwaltung (z. B. Etablierung nachhaltiger Anlagestrategien in ärztlichen Versorgungswerken) oder durch die Umsetzung von Maßnahmen in Gesundheitseinrichtungen aktiv zum Klimaschutz beitragen.
Identification of major quantitative trait loci and candidate genes for seed weight in soybean
Authors: Xu Mengge , Kong Keke , Miao Long , He Jianbo , Liu Tengfei , Zhang Kai , Yue Xiuli , Jin Ting , Gai Junyi , Li Yan 
Published: January 2023

Abstract
Key message
Four major quantitative trait loci for 100-seed weight were identified in a soybean RIL population under five environments, and the most likely candidate genes underlying these loci were identified.

Abstract
Seed weight is an important target of soybean breeding. However, the genes underlying the major quantitative trait loci (QTL) controlling seed weight remain largely unknown. In this study, a soybean population of 300 recombinant inbred lines (RILs) derived from a cross between PI595843 (PI) and WH was used to map the QTL and identify candidate genes for seed weight. The RIL population was genotyped through whole genome resequencing, and phenotyped for 100-seed weight under five environments. A total of 38 QTL were detected, and four major QTL, each explained at least 10% of the variation in 100-seed weight, were identified. Six candidate genes within these four major QTL regions were identified by analyses of their tissue expression patterns, gene annotations, and differential gene expression levels in soybean seeds during four developmental stages between two parental lines. Further sequence variation analyses revealed a C to T substitution in the first exon of the Glyma.19G143300, resulting in an amino acid change between PI and WH, and thus leading to a different predicted kinase domain, which might affect its protein function. Glyma.19G143300 is highly expressed in soybean seeds and encodes a leucine-rich repeat receptor-like protein kinase (LRR-RLK). Its predicted protein has typical domains of LRR-RLK family, and phylogenetic analyses reveled its similarity with the known LRR-RLK protein XIAO (LOC_Os04g48760), which is involved in controlling seed size. The major QTL and candidate genes identified in this study provide useful information for molecular breeding of new soybean cultivars with desirable seed weight.