bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of ferromagnetic interlayer exchange coupling on current-induced magnetization switching and Dzyaloshinskii–Moriya interaction in Co/Pt/Co multilayer system
Authors: Grochot Krzysztof , Ogrodnik Piotr , Mojsiejuk Jakub , Mazalski Piotr , Guzowska Urszula , Skowroński Witold , Stobiecki Tomasz 
Published: April 2024

AbstractThis paper investigates the relationship among interlayer exchange coupling (IEC), Dzyaloshinskii–Moriya interaction (DMI), and multilevel magnetization switching within a Co/Pt/Co heterostructure, where varying Pt thicknesses enable control over the coupling strength. Employing Brillouin Light Scattering to quantify the effective DMI, we explore its potential role in magnetization dynamics and multilevel magnetization switching. Experimental findings show four distinct resistance states under an external magnetic field and spin Hall effect related spin current. We explain this phenomenon based on the asymmetry between Pt/Co and Co/Pt interfaces and the interlayer coupling, which, in turn, influences the DMI and subsequently impacts the magnetization dynamics. Numerical simulations, including macrospin, 1D domain wall, and simple spin wave models, further support the experimental observations of multilevel switching and help uncover the underlying mechanisms. Our proposed explanation, supported by magnetic domain observation using polar-magnetooptical Kerr microscopy, offers insights into both the spatial distribution of magnetization and its dynamics for different IECs, thereby shedding light on its interplay with DMI, which may lead to potential applications in storage devices.
Harnessing the intragenomic variability of rRNA operons to improve differentiation of Vibrio species
Authors: Leunda-Esnaola Amaia , Bunin Evgeni , Arrufat Pablo , Pearman Peter B. , Kaberdin Vladimir R. 
Published: April 2024

AbstractAlthough the 16S rRNA gene is frequently used as a phylogenetic marker in analysis of environmental DNA, this marker often fails to distinguish closely related species, including those in the genus Vibrio. Here, we investigate whether inclusion and analysis of 23S rRNA sequence can help overcome the intrinsic weaknesses of 16S rRNA analyses for the differentiation of Vibrio species. We construct a maximum likelihood 16S rRNA gene tree to assess the use of this gene to identify clades of Vibrio species. Within the 16S rRNA tree, we identify the putative informative bases responsible for polyphyly, and demonstrate the association of these positions with tree topology. We demonstrate that concatenation of 16S and 23S rRNA genes increases the number of informative nucleotide positions, thereby overcoming ambiguities in 16S rRNA-based phylogenetic reconstructions. Finally, we experimentally demonstrate that this approach considerably improves the differentiation and identification of Vibrio species in environmental samples.
Artificial intelligence to predict soil temperatures by development of novel model
Authors: Mampitiya Lakindu , Rozumbetov Kenjabek , Rathnayake Namal , Erkudov Valery , Esimbetov Adilbay , Arachchi Shanika , Kantamaneni Komali , Hoshino Yukinobu , Rathnayake Upaka 
Published: April 2024

AbstractSoil temperatures at both surface and various depths are important in changing environments to understand the biological, chemical, and physical properties of soil. This is essential in reaching food sustainability. However, most of the developing regions across the globe face difficulty in establishing solid data measurements and records due to poor instrumentation and many other unavoidable reasons such as natural disasters like droughts, floods, and cyclones. Therefore, an accurate prediction model would fix these difficulties. Uzbekistan is one of the countries that is concerned about climate change due to its arid climate. Therefore, for the first time, this research presents an integrated model to predict soil temperature levels at the surface and 10 cm depth based on climatic factors in Nukus, Uzbekistan. Eight machine learning models were trained in order to understand the best-performing model based on widely used performance indicators. Long Short-Term Memory (LSTM) model performed in accurate predictions of soil temperature levels at 10 cm depth. More importantly, the models developed here can predict temperature levels at 10 cm depth with the measured climatic data and predicted surface soil temperature levels. The model can predict soil temperature at 10 cm depth without any ground soil temperature measurements. The developed model can be effectively used in planning applications in reaching sustainability in food production in arid areas like Nukus, Uzbekistan.
Temporal and fertilizer-dependent dynamics of soil bacterial communities in buckwheat fields under long-term management
Authors: Morigasaki Susumu , Matsui Motomu , Ohtsu Iwao , Doi Yuki , Kawano Yusuke , Nakai Ryosuke , Iwasaki Wataru , Hayashi Hisayoshi , Takaya Naoki 
Published: April 2024

AbstractThis study integrated bacterial community and soil chemicals to characterize the soil ecosystem in an open upland field managed by six controlled fertilizer programs using the minimum amount of pesticides. Amplicon sequencing the 16S rRNA gene revealed that inorganic nitrogen fertilizer and compost altered the diversity and structure of the soil bacterial community throughout buckwheat (Fagopyrum esculentum Moench ‘Hitachiakisoba’) cultivation. The bacterial community comprised three clusters that contained bacteria that are prevalent in soils fertilized with nitrogen (cluster 1, 340 taxa), without nitrogen and compost (cluster 2, 234 taxa), and with compost-fertilized (cluster 3, 296 taxa). Cluster 2 contained more taxa in Actinobacteriota and less in Acidobacteriota, and cluster 3 contained more taxa in Gemmatimonadota compared with the other clusters. The most frequent taxa in cluster 1 were within the Chloroflexi phylum. The bacterial community structure correlated with soil chemical properties including pH, total organic carbon, SO42−, soluble Ca2+. A co-occurrence network of bacterial taxa and chemicals identified key bacterial groups comprising the center of a community network that determined topology and dynamics of the network. Temporal dynamics of the bacterial community structure indicated that Burkholderiales were associated with buckwheat ripening, indicating plant-bacteria interaction in the ecosystem.
Association of natriuretic peptides and receptor activity with cardio-metabolic health at middle age
Authors: Prickett Timothy C. R. , Espiner Eric A. , Pearson John F. 
Published: April 2024

AbstractNatriuretic peptides (NP) have multiple actions benefitting cardiovascular and metabolic health. Although many of these are mediated by Guanylyl Cyclase (GC) receptors NPR1 and NPR2, their role and relative importance in vivo is unclear. The intracellular mediator of NPR1 and NPR2, cGMP, circulates in plasma and can be used to examine relationships between receptor activity and tissue responses targeted by NPs. Plasma cGMP was measured in 348 participants previously recruited in a multidisciplinary community study (CHALICE) at age 50 years at a single centre. Associations between bio-active NPs and bio-inactive aminoterminal products with cGMP, and of cGMP with tissue response, were analysed using linear regression. Mediation of associations by NPs was assessed by Causal Mediation Analysis (CMA). ANP’s contribution to cGMP far exceed those of other NPs. Modelling across three components (demographics, NPs and cardiovascular function) shows that ANP and CNP are independent and positive predictors of cGMP. Counter intuitively, findings from CMA imply that in specific tissues, NPR1 responds more to BNP stimulation than ANP. Collectively these findings align with longer tissue half-life of BNP, and direct further therapeutic interventions towards extending tissue activity of ANP and CNP.
Identification and clinicopathological analysis of potential p73-regulated biomarkers in colorectal cancer via integrative bioinformatics
Authors: Bareja Chanchal , Dwivedi Kountay , Uboveja Apoorva , Mathur Ankit , Kumar Naveen , Saluja Daman 
Published: April 2024

AbstractThis study aims to decipher crucial biomarkers regulated by p73 for the early detection of colorectal cancer (CRC) by employing a combination of integrative bioinformatics and expression profiling techniques. The transcriptome profile of HCT116 cell line p53$$^{-/-}$$

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p73$$^{+/+}$$

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and p53$$^{-/-}$$

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p73 knockdown was performed to identify differentially expressed genes (DEGs). This was corroborated with three CRC tissue expression datasets available in Gene Expression Omnibus. Further analysis involved KEGG and Gene ontology to elucidate the functional roles of DEGs. The protein-protein interaction (PPI) network was constructed using Cytoscape to identify hub genes. Kaplan–Meier (KM) plots along with GEPIA and UALCAN database analysis provided the insights into the prognostic and diagnostic significance of these hub genes. Machine/deep learning algorithms were employed to perform TNM-stage classification. Transcriptome profiling revealed 1289 upregulated and 1897 downregulated genes. When intersected with employed CRC datasets, 284 DEGs were obtained. Comprehensive analysis using gene ontology and KEGG revealed enrichment of the DEGs in metabolic process, fatty acid biosynthesis, etc. The PPI network constructed using these 284 genes assisted in identifying 20 hub genes. Kaplan–Meier, GEPIA, and UALCAN analyses uncovered the clinicopathological relevance of these hub genes. Conclusively, the deep learning model achieved TNM-stage classification accuracy of 0.78 and 0.75 using 284 DEGs and 20 hub genes, respectively. The study represents a pioneer endeavor amalgamating transcriptomics, publicly available tissue datasets, and machine learning to unveil key CRC-associated genes. These genes are found relevant regarding the patients’ prognosis and diagnosis. The unveiled biomarkers exhibit robustness in TNM-stage prediction, thereby laying the foundation for future clinical applications and therapeutic interventions in CRC management.
Differential expression and global analysis of miR156/SQUAMOSA promoter binding-like proteins (SPL) module in oat
Authors: Mehtab-Singh  , Tripathi Rajiv K. , Bekele Wubishet A. , Tinker Nicholas A. , Singh Jaswinder 
Published: April 2024

AbstractSQUAMOSA promoter binding-like proteins (SPLs) are important transcription factors that influence growth phase transition and reproduction in plants. SPLs are targeted by miR156 but the SPL/miR156 module is completely unknown in oat. We identified 28 oat SPL genes (AsSPLs) distributed across all 21 oat chromosomes except for 4C and 6D. The oat- SPL gene family represented six of eight SPL phylogenetic groups, with no AsSPLs in groups 3 and 7. A novel oat miR156 (AsmiR156) family with 21 precursors divided into 7 groups was characterized. A total of 16 AsSPLs were found to be targeted by AsmiR156. Intriguingly, AsSPL3s showed high transcript abundance during early inflorescence (GS-54), as compared to the lower abundance of AsmiR156, indicating their role in reproductive development. Unravelling the SPL/miR156 regulatory hub and alterations in expression patterns of AsSPLs could provide an essential toolbox for genetic improvement in the cultivated oat.
Experiments as Code and its application to VR studies in human-building interaction
Authors: Aguilar Leonel , Gath-Morad Michal , Grübel Jascha , Ermatinger Jasper , Zhao Hantao , Wehrli Stefan , Sumner Robert W. , Zhang Ce , Helbing Dirk , Hölscher Christoph 
Published: April 2024

AbstractExperiments as Code (ExaC) is a concept for reproducible, auditable, debuggable, reusable, & scalable experiments. Experiments are a crucial tool to understand Human-Building Interactions (HBI) and build a coherent theory around it. However, a common concern for experiments is their auditability and reproducibility. Experiments are usually designed, provisioned, managed, and analyzed by diverse teams of specialists (e.g., researchers, technicians, engineers) and may require many resources (e.g., cloud infrastructure, specialized equipment). Although researchers strive to document experiments accurately, this process is often lacking. Consequently, it is difficult to reproduce these experiments. Moreover, when it is necessary to create a similar experiment, the “wheel is very often reinvented”. It appears easier to start from scratch than trying to reuse existing work. Thus valuable embedded best practices and previous experiences are lost. In behavioral studies, such as in HBI, this has contributed to the reproducibility crisis. To tackle these challenges, we propose the ExaC paradigm, which not only documents the whole experiment, but additionally provides the automation code to provision, deploy, manage, and analyze the experiment. To this end, we define the ExaC concept, provide a taxonomy for the components of a practical implementation, and provide a proof of concept with an HBI desktop VR experiment that demonstrates the benefits of its “as code” representation, that is, reproducibility, auditability, debuggability, reusability, & scalability.
Linking ecosystems to public health based on combination of social and ecological systems
Authors: Khosravi Mashizi Azam , Sharafatmandrad Mohsen 
Published: April 2024

AbstractPromotion of public health is one of the most important benefits of ecosystems. Nevertheless, the relationship between ecosystems and social health’ needs is not well understood. Therefore, a study was done to investigate the potential of natural (forests and rangelands) and artificial (urban parks and gardens) ecosystems in ensuring the five dimensions of public health (i.e. physical, mental, spiritual, social and environmental) in the social systems (urban and rural societies). Therefore, 47 health indicators were used in order to relate different ecosystems and social’ needs to five dimensions of public health through questionnaire. The results indicated that natural ecosystems had the greatest potential in providing mental, spiritual and environmental health due to ecological characteristics of wilderness and aesthetic. The artificial ecosystems had the greatest potential in providing physical and social health due to their easy access. However, there was a match between social health’ needs and ecosystem potential in the rural areas. The study highlighted the need for promotion of ecological indicators related to mental health in urban areas by enhancing silence and aesthetic in artificial ecosystems. Presented framework can provide comprehensive information on the weaknesses and strengths of different ecosystems to promote public health based on social needs and fixing the weaknesses of artificial ecosystems in urban areas.
Long-term oncologic outcomes of unselected triple-negative breast cancer patients according to BRCA1/2 mutations
Authors: Park Woong Ki , Chung Soo Yeon , Jung You Jin , Ha Changhee , Kim Jong-Won , Nam Seok Jin , Kim Seok Won , Yu Jonghan , Chae Byung Joo , Lee Jeong Eon , Kim Sung-Won , Ryu Jai Min ,   Korean Hereditary Breast Cancer Study Group
Published: April 2024

AbstractTriple-negative breast cancer (TNBC) patients are more likely to have BRCA1/2 mutations, with a prevalence rate of about 10–20%. Although several studies have analyzed the oncologic outcomes between BRCA1/2 carriers and non-carriers, the impact on breast cancer patients is still unclear. A retrospective review was performed to determine the long-term outcomes of TNBC patients, focusing on the impact of BRCA1/2 mutations. A total of 953 TNBC patients who underwent primary breast cancer surgery from June 2008 to January 2016 were included. We examined long-term outcomes, including contralateral breast cancer (CBC) incidence, recurrence patterns, and survival rates over a median follow-up of 80.9 months (range 3–152 months). 122 patients (12.8%) had BRCA1/2 mutations. BRCA1/2 mutation carriers were significantly younger at diagnosis and more likely to have a family history of breast/ovarian cancer. CBC incidence at 60, 120, and 150 months was significantly higher in BRCA1/2 mutation carriers compared to non-carriers (P = 0.0250, 0.0063, and 0.0184, respectively). However, there were no significant differences in disease-free survival, overall survival, breast cancer-specific survival, or distant-metastasis-free survival between the two groups. BRCA1/2 mutation status was a significant risk factor for CBC (HR = 6.242, P < 0.0001). Interestingly, among 29 patients with CBC recurrence, 24 patients (82.8%) had recurring TNBC subtype and among the CBC recurrence patients, 19 patients (65.5%) resumed chemotherapy. In the TNBC subtype, appropriate genetic testing and counseling are pivotal for surgical decisions like risk-reducing mastectomy (RRM). Furthermore, long-term surveillance is warranted, especially in BRCA1/2 carriers who did not receive RRM.
Superlattice assembly strategy of small noble metal nanoparticles for surface-enhanced Raman scattering
Authors: Yao Chang , Yan Wuwen , Dong Ronglu , Dou Shaobin , Yang Liangbao 
Published: April 2024

AbstractThe self-assembly of noble metal nanoparticles into periodic structures has been a theme of great interest for surface-enhanced Raman scattering (SERS) and use in functional devices. However, small nanoparticle self-assembly faces numerous challenges in tunability, referring to controlling their structural properties like structure, gaps, and arrangement. These issues highlight the need for further research and development to enhance the tunability and stability of self-assembled small nanoparticles. Here, we report a general centimeter-scale superlattice assembly strategy for noble metal nanoparticles less than 15 nm in size. Not only is this monolayer superlattice assembly generally applicable to different kinds and sizes of noble metal nanoparticles, but also, the crystal plane spacing can also be quickly and conveniently controlled by changing the ethanol concentration. SERS results reveal that optimized superlattice membranes of noble metal nanoparticles possess high detection sensitivity and ordered hot spots. Therefore, our strategy offers prospects for high-performance SERS substrates based on small noble metal nanoparticle superlattices.
Generative AI tools can enhance climate literacy but must be checked for biases and inaccuracies
Authors: Atkins Carmen , Girgente Gina , Shirzaei Manoochehr , Kim Junghwan 
Published: April 2024

AbstractIn the face of climate change, climate literacy is becoming increasingly important. With wide access to generative AI tools, such as OpenAI’s ChatGPT, we explore the potential of AI platforms for ordinary citizens asking climate literacy questions. Here, we focus on a global scale and collect responses from ChatGPT (GPT-3.5 and GPT-4) on climate change-related hazard prompts over multiple iterations by utilizing the OpenAI’s API and comparing the results with credible hazard risk indices. We find a general sense of agreement in comparisons and consistency in ChatGPT over the iterations. GPT-4 displayed fewer errors than GPT-3.5. Generative AI tools may be used in climate literacy, a timely topic of importance, but must be scrutinized for potential biases and inaccuracies moving forward and considered in a social context. Future work should identify and disseminate best practices for optimal use across various generative AI tools.
MH‐HMR: Human mesh recovery from monocular images via multi‐hypothesis learning
Authors: Xuan Haibiao , Zhang Jinsong , Lai Yu‐Kun , Li Kun 
Published: April 2024

AbstractRecovering 3D human meshes from monocular images is an inherently ill‐posed and challenging task due to depth ambiguity, joint occlusion, and truncation. However, most existing approaches do not model such uncertainties, typically yielding a single reconstruction for one input. In contrast, the ambiguity of the reconstruction is embraced and the problem is considered as an inverse problem for which multiple feasible solutions exist. To address these issues, the authors propose a multi‐hypothesis approach, multi‐hypothesis human mesh recovery (MH‐HMR), to efficiently model the multi‐hypothesis representation and build strong relationships among the hypothetical features. Specifically, the task is decomposed into three stages: (1) generating a reasonable set of initial recovery results (i.e., multiple hypotheses) given a single colour image; (2) modelling intra‐hypothesis refinement to enhance every single‐hypothesis feature; and (3) establishing inter‐hypothesis communication and regressing the final human meshes. Meanwhile, the authors take further advantage of multiple hypotheses and the recovery process to achieve human mesh recovery from multiple uncalibrated views. Compared with state‐of‐the‐art methods, the MH‐HMR approach achieves superior performance and recovers more accurate human meshes on challenging benchmark datasets, such as Human3.6M and 3DPW, while demonstrating the effectiveness across a variety of settings. The code will be publicly available at https://cic.tju.edu.cn/faculty/likun/projects/MH‐HMR.
Current Topics from the Revised German S2k Guideline on Diagnosis and Treatment of Venous Thromboembolism
Authors: Linnemann Birgit , Klamroth Robert 
Published: April 2024

AbstractIt is an honor and a great pleasure for us to be guest editors for this special issue of Hämostaseologie – Progress in Haemostasis, which addresses important issues surrounding the complex of venous thromboembolism (VTE). In February 2023, the revised guideline on “Diagnostics and Therapy of Venous Thrombosis and Pulmonary Embolism” has been published on the website of the Association of the Scientific Medical Societies in Germany (AWMF)1. This guideline was drawn up under the leadership of the German Society of Angiology (DGA), and representatives of 17 scientific societies contributed to its content. As an S2k guideline, its recommendations are consensus based and are the result of a systematic review and evaluation of current evidence and consideration of the benefits and harms of diagnostic and therapeutic options. In this special issue, guideline authors provide a comprehensive overview of selected guideline topics which might be of clinical relevance to our readers and our community of haemostaseologists.
Progress on the Synthesis and Applications of Aminals: Scaffolds for Molecular Diversity
Authors: Rippel Rafael , Ferreira Luísa M. , Branco Paula S. 
Published: April 2024

AbstractAminals, characterized by a central carbon linking two nitrogen atoms, are versatile building blocks in modern chemistry. This review addresses a literature gap by exploring the synthesis and applications of aminals, with a focus on drug discovery and molecular diversity. Beyond medicinal chemistry, aminals find applications as key components in bioactive compounds and as versatile tools in materials chemistry. The review covers fundamental characteristics, synthetic methodologies, stability, and applications, emphasizing alternative synthetic methods to the well-established aldehyde–amine condensation. This inclusive exploration provides insights into diverse synthetic pathways that expand the versatility of the aminal scaffold.1	Introduction2	The Aminal Group3	Aminal Synthesis3.1	Metal-Free Approaches3.2	Metal-Catalyzed Approaches3.3	Photoredox Methodologies3.4	Via Rearrangements3.5	Via Decarboxylative Coupling4	Aminals as Synthetic Tools5	Synthesis of Aminal-Containing Natural Products6	Aminal-Based Materials7	Conclusions