bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estimating the Possible Ion Heating Caused by Alfvén Waves at Venus
Authors: Stenberg Wieser G. , André M. , Nilsson H. , Edberg N. , Persson M. , Rojas Mata S. , Mihalikova M. , Gunell H. , Bader A. , Futaana Y. 
Published: December 2024

AbstractIn the Earth's magnetosphere wave‐particle interaction is a major ion energization process, playing an important role for the atmospheric escape. A common type of ion heating is associated with low‐frequency broadband electric wave fields. For such waves the energy is not concentrated to a certain narrow frequency range and exhibits no peaks or dips in a power spectrum. If there are enough fluctuations close to the ion gyrofrequency the electric field may still come in resonance with gyrating ions and heat them perpendicular to the background magnetic field. We perform a proof‐of‐concept study to investigate if this heating mechanism may contibute significantly to the energization of planetary ions also in the induced magnetosphere of Venus. We assume Alfvénic fluctuations and estimate the electric field spectral density based on magnetic field observations. We find typical estimated electric spectral densities of a few /Hz close to Venus. This corresponds to a heating rate of a few eV/s. We consider an available interaction time of 300 s and conclude that this mechanism could increase the energy of an oxygen ion by about a keV. Observed thermal energies are in the range 100–1,000 eV and thus, resonant wave heating may also be important at Venus.
Vertical Structures of Marine Heatwaves in the South China Sea: Characteristics, Drivers and Impacts on Chlorophyll Concentration
Authors: Yuan Taikang , Zhang Jinrong , Yang Shengmu , Su Qingguo , Zhao Zezheng , Ren Kaijun 
Published: December 2024

AbstractMarine heatwaves (MHWs) are characterized as extreme ocean warming events, which have multifaceted impacts on marine ecosystems. The warming of the ocean associated with MHWs can extend into the deep ocean. In the study, five main types of MHWs in the South China Sea (SCS) are identified with various vertical structures, including shallow, surface‐extension‐reversed, surface‐extension‐intensified, deep, and surface‐extension‐intensified‐reversed. Different types of MHWs have different spread patterns and depths. Shallow and surface‐extension‐reversed MHWs are common in coastal areas, and surface‐extension‐intensified MHW events often occur in deep areas. The vertical structures of MHWs are affected by ocean dynamical processes, particularly vertical processes and horizontal heat advection. These MHWs can alter ocean chlorophyll concentration to varying degrees and locations, contingent on their vertical thermal profiles. Furthermore, an analysis of the impacts of a long‐lived MHW event in the SCS in 2020 revealed that the MHWs could alter chlorophyll concentration. These results help to better understand the physical drivers of localized MHWs and their potential impacts in the context of climate change.
Automatic Detection and Classification of Aurora in THEMIS All‐Sky Images
Authors: Johnson Jeremiah W. , Öztürk Doğacan Su , Hampton Donald , Connor Hyunju K. , Blandin Matthew , Keesee Amy 
Published: December 2024

AbstractWe report a novel machine‐learning algorithm for automatically detecting and classifying aurora in all–sky images (ASI) that is largely trained without requiring ground–truth labels. By including a small number of labeled images, we are able to automatically label all of the approximately 700 million images in the Time History of Events and Macroscale Interactions during Substorms (THEMIS) ASI data set from 2008 to 2022. We use a two–stage approach. In the first stage, we adapt the Simple framework for Contrastive Learning of Representations (SimCLR) algorithm to learn latent representations of THEMIS all–sky images. We then finetune a classifier network on the latent representations our model learns of the manually labeled Oslo aurora THEMIS (OATH) data set. We demonstrate that this two–stage approach achieves excellent classification results on data for which there is no current ML classification benchmark. The outcome of this work will facilitate efficient information retrieval for researchers interested in specific categories of aurora and will enable large scale statistical studies and machine learning analyses of THEMIS all–sky images that have not previously been possible. To demonstrate possible ways to utilize this database, we performed a statistical analysis of the occurrence rates of auroral labels with respect to solar wind parameters, interplanetary magnetic field vector, and geomagnetic indices. We further investigate the occurrence rates of auroral phenomena in the annotated data set and their geoeffectiveness by utilizing the co–located THEMIS ground magnetometer data set.
Channel Mixer Layer: Multimodal Fusion Toward Machine Reasoning for Spatiotemporal Predictive Learning of Ionospheric Total Electron Content
Authors: Liu Peng , Yokoyama Tatsuhiro , Sori Takuya , Yamamoto Mamoru 
Published: December 2024

AbstractThe spatiotemporal distribution of Total Electron Content (TEC) in ionosphere determines the refractive index of electromagnetic wave leading to the radio signal scintillation and deterioration. Thanks to the development of machine learning for video prediction, spatiotemporal predictive models are applied on the future TEC map prediction based on the graphic features of past frames. However, output result of graphic prediction is unable to properly respond to the external factor variations such as solar or geomagnetic activity. Meanwhile, there is still neither standard data ‐set nor comprehensive evaluation framework for spatiotemporal predictive learning of TEC map sequences leading to the comparisons unfair and insights inconclusive. In this research, a new feature‐level multimodal fusion method named as channel mixer layer for machine reasoning is proposed that can be embedded into the existing advanced spatiotemporal sequence prediction models. Meanwhile, all performance benchmarks are accomplished on the same running environment and newly proposed largest scale data set. Experiment results suggest that the multimodal fusion prediction of existing model backbones by proposed method improves the prediction accuracy up to 15% with almost the same computational complexity compared to that of graphic prediction without auxiliary factors input, having the real‐time inference speed of 34 frames/second and minimum mean absolute error of 0.94/2.63 TEC unit during low/high solar activity period respectively. The channel mixer layer embedded models can respond to the variations of auxiliary external factors more correctly than previous multimodal fusion methods such as concatenation and arithmetic, which is regarded as the evidence of state‐of‐the‐art machine reasoning ability.
Packaged release and targeted delivery of cytokines by migrasomes in circulation
Authors: Jiao Haifeng , Li Xiaopeng , Li Ying , Guo Ziyi , Yang Yuzhuo , Luo Yiqun , Hu Xiaoyu , Yu Li 
Published: December 2024

AbstractIn dynamic systems like the circulatory system, establishing localized cytokine gradients is challenging. Upon lipopolysaccharide (LPS) stimulation, we observed that monocytes release numerous migrasomes enriched with inflammatory cytokines, such as TNF-α and IL-6. These cytokines are transported into migrasomes via secretory carriers, leading to their immediate exocytosis or eventual release from detached migrasomes. We successfully isolated TNF-α and IL-6-enriched, monocyte-derived migrasomes from the blood of LPS-treated mice. Total secretion analysis revealed a substantial amount of TNF-α and IL-6 released in a migrasome-packaged form. Thus, detached, monocyte-derived migrasomes represent a type of extracellular vesicle highly enriched with cytokines. Physiologically, these cytokine-laden migrasomes rapidly accumulate at local sites of inflammation, effectively creating a concentrated source of cytokines. Our research uncovers novel mechanisms for cytokine release and delivery, providing new insights into immune response modulation.
Neutrophils in cancer: from biology to therapy
Authors: Koenderman Leo , Vrisekoop Nienke 
Published: December 2024

AbstractThe view of neutrophils has shifted from simple phagocytic cells, whose main function is to kill pathogens, to very complex cells that are also involved in immune regulation and tissue repair. These cells are essential for maintaining and regaining tissue homeostasis. Neutrophils can be viewed as double-edged swords in a range of situations. The potent killing machinery necessary for immune responses to pathogens can easily lead to collateral damage to host tissues when inappropriately controlled. Furthermore, some subtypes of neutrophils are potent pathogen killers, whereas others are immunosuppressive or can aid in tissue healing. Finally, in tumor immunology, many examples of both protumorigenic and antitumorigenic properties of neutrophils have been described. This has important consequences for cancer therapy, as targeting neutrophils can lead to either suppressed or stimulated antitumor responses. This review will discuss the current knowledge regarding the pro- and antitumorigenic roles of neutrophils, leading to the concept of a confused state of neutrophil-driven pro-/antitumor responses.
Dysregulation of MMP2-dependent TGF-ß2 activation impairs fibrous cap formation in type 2 diabetes-associated atherosclerosis
Authors: Singh Pratibha , Sun Jiangming , Cavalera Michele , Al-Sharify Dania , Matthes Frank , Barghouth Mohammad , Tengryd Christoffer , Dunér Pontus , Persson Ana , Sundius Lena , Nitulescu Mihaela , Bengtsson Eva , Rattik Sara , Engelbertsen Daniel , Orho-Melander Marju , Nilsson Jan , Monaco Claudia , Goncalves Isabel , Edsfeldt Andreas 
Published: December 2024

Abstract
Type 2 diabetes is associated with cardiovascular disease, possibly due to impaired vascular fibrous repair. Yet, the mechanisms are elusive. Here, we investigate alterations in the fibrous repair processes in type 2 diabetes atherosclerotic plaque extracellular matrix by combining multi-omics from the human Carotid Plaque Imaging Project cohort and functional studies. Plaques from type 2 diabetes patients have less collagen. Interestingly, lower levels of transforming growth factor-ß distinguish type 2 diabetes plaques and, in these patients, lower levels of fibrous repair markers are associated with cardiovascular events. Transforming growth factor-ß2 originates mostly from contractile vascular smooth muscle cells that interact with synthetic vascular smooth muscle cells in the cap, leading to collagen formation and vascular smooth muscle cell differentiation. This is regulated by free transforming growth factor-ß2 which is affected by hyperglycemia. Our findings underscore the importance of transforming growth factor-ß2-driven fibrous repair in type 2 diabetes as an area for future therapeutic strategies.
A core network in the SARS-CoV-2 nucleocapsid NTD mediates structural integrity and selective RNA-binding
Authors: Dhamotharan Karthikeyan , Korn Sophie M. , Wacker Anna , Becker Matthias A. , Günther Sebastian , Schwalbe Harald , Schlundt Andreas 
Published: December 2024

AbstractThe SARS-CoV-2 nucleocapsid protein is indispensable for viral RNA genome processing. Although the N-terminal domain (NTD) is suggested to mediate specific RNA-interactions, high-resolution structures with viral RNA are still lacking. Available hybrid structures of the NTD with ssRNA and dsRNA provide valuable insights; however, the precise mechanism of complex formation remains elusive. Similarly, the molecular impact of nucleocapsid NTD mutations that have emerged since 2019 has not yet been fully explored. Using crystallography and solution NMR, we investigate how NTD mutations influence structural integrity and RNA-binding. We find that both features rely on a core network of residues conserved in Betacoronaviruses, crucial for protein stability and communication among flexible loop-regions that facilitate RNA-recognition. Our comprehensive structural analysis demonstrates that contacts within this network guide selective RNA-interactions. We propose that the core network renders the NTD evolutionarily robust in stability and plasticity for its versatile RNA processing roles.
MamF-like proteins are distant Tic20 homologs involved in organelle assembly in bacteria
Authors: Paulus Anja , Ahrens Frederik , Schraut Annika , Hofmann Hannah , Schiller Tim , Sura Thomas , Becher Dörte , Uebe René 
Published: December 2024

AbstractOrganelle-specific protein translocation systems are essential for organelle biogenesis and maintenance in eukaryotes but thought to be absent from prokaryotic organelles. Here, we demonstrate that MamF-like proteins are crucial for the formation and functionality of bacterial magnetosome organelles. Deletion of mamF-like genes in the Alphaproteobacterium Magnetospirillum gryphiswaldense results in severe defects in organelle positioning, biomineralization, and magnetic navigation. These phenotypic defects result from the disrupted targeting of a subset of magnetosomal proteins that contain C-terminal glycine-rich integral membrane domains. Phylogenetic analyses reveal an ancient evolutionary link between MamF-like proteins and plastidial Tic20. Our findings redefine the molecular roles of MamF-like proteins and suggest that organelle-specific protein targeting systems also play a role in bacterial organelle formation.
Zonation of the Vitis vinifera microbiome in Vino Nobile di Montepulciano PDO production area
Authors: Palladino Giorgia , Nanetti Enrico , Scicchitano Daniel , Cinti Nicolò , Foresto Lucia , Cozzi Alice , Gonzalez Vara Rodriguez Antonio , Interino Nicolò , Fiori Jessica , Turroni Silvia , Candela Marco , Rampelli Simone 
Published: December 2024

AbstractThe microbial dimension of the terroir is crucial for wine quality, as microbiomes contribute to plant biofertilization, stress tolerance and pathogen suppression. While microbial terroir can act as a biological signature at large scale, data for local contexts is lacking, hindering the characterization of regional microbial diversity in vineyards. Here, we define the microbial terroir of vineyards across the 12 sub-areas (Additional Geographic Units -AGUs) of the “Consorzio del Vino Nobile di Montepulciano DOCG” PDO area (Italy), a world-renowned wine-producing region. Rhizospheres of Vitis vinifera cultivar Sangiovese and soil samples were collected throughout the 2022 viticultural season and analyzed through an integrated metabarcoding/shotgun metagenomic approach, targeting bacteria and fungi. Wine metabolomics was also perfomed, projecting compositional and functional variations of the microbial terroir at the AGUs level into a corresponding variation in the product metabolic profile. Our findings reveal a unique taxonomic configuration of the Vino Nobile di Montepulciano terroir compared to other vineyards, with microbiomes being “AGU-specific” in taxonomic abundances and plant growth-promoting functions, confirming the potential relevance of characterizing and preserving the microbial terroir to safeguard high-quality traditional wines.
On-surface synthesis of phthalocyanines with extended π-electron systems
Authors: Heuplick Lukas J. , Fan Qitang , Astvatsaturov Dmitriy A. , Dubinina Tatiana V. , Gottfried J. Michael 
Published: December 2024

AbstractExpanded phthalocyanines are a promising class of materials for optoelectronic applications, owing to their unique properties and versatile metal coordination reactivity. The expansion of their π-electron systems and resulting red-shifted absorption are of particular interest for achieving broader applications. Here, we report the on-surface synthesis of metallo-phthalocyanines with extended electron systems and an open-chain polycyanine from ortho-dicarbonitrile precursors on Ag(111) and Au(111), studied by scanning tunneling microscopy (STM) and X-ray photoelectron spectroscopy (XPS). The larger 6,7-di(2-naphthyl)-2,3-naphthalenedicarbonitrile (NND) undergoes spontaneous cyclotetramerization on the Ag(111) surface forming the corresponding silver naphthalocyanines (Ag-NPc), contrasting previous reports where a partially aliphatic ortho-dicarbonitrile precursor formed polycyanine chains. In contrast, monolayers of the smaller 6,7-diphenyl-2,3-naphthalenedicarbonitrile (PND) form the corresponding naphthalocyanine only in the presence of co-adsorbed iron atoms (Fe-NPc). In the absence of iron, PND multilayers form polycyanine chains and Ag-NPc. NND and PND further differ in their reactivity due to the supramolecular behavior of their products. While the larger Ag-NPc aggregates to non-covalent one-dimensional ribbons, the smaller Fe-NPc forms an extended non-covalent two-dimensional network. Our study demonstrates the versatility of on-surface dinitrile tetramerization for the synthesis of π-extended cyclic phthalocyanines and their open-chain polycyanine counterparts.
Structure-based drug design with equivariant diffusion models
Authors: Schneuing Arne , Harris Charles , Du Yuanqi , Didi Kieran , Jamasb Arian , Igashov Ilia , Du Weitao , Gomes Carla , Blundell Tom L. , Lio Pietro , Welling Max , Bronstein Michael , Correia Bruno 
Published: December 2024

AbstractStructure-based drug design (SBDD) aims to design small-molecule ligands that bind with high affinity and specificity to pre-determined protein targets. Generative SBDD methods leverage structural data of drugs with their protein targets to propose new drug candidates. However, most existing methods focus exclusively on bottom-up de novo design of compounds or tackle other drug development challenges with task-specific models. The latter requires curation of suitable datasets, careful engineering of the models and retraining from scratch for each task. Here we show how a single pretrained diffusion model can be applied to a broader range of problems, such as off-the-shelf property optimization, explicit negative design and partial molecular design with inpainting. We formulate SBDD as a three-dimensional conditional generation problem and present DiffSBDD, an SE(3)-equivariant diffusion model that generates novel ligands conditioned on protein pockets. Furthermore, we show how additional constraints can be used to improve the generated drug candidates according to a variety of computational metrics.
SCite‐HRNet: A self‐calibrating efficient network for pose estimation
Authors: Xiang Nan , Rao Xingdi , Yang Wenjing , Chen Jin , Zhu Lifang 
Published: December 2024

AbstractIn order to tackle the challenge of capturing long‐range spatial dependencies among joints, a novel self‐calibrated lightweight high‐resolution network (SCite‐HRNet), which is grounded on the lightweight high‐resolution network is introduced. A self‐calibrated segmentation convolution is first designed to extract and amalgamate contextual information across various scales, thereby addressing the issue of excessive computation engendered by stacked convolution kernels in conventional convolution methods. Next, a multi‐scale channel attention mechanism designed to extract structural information while filtering out unnecessary channel details is introduced. Ultimately, these two methodologies are incorporated into a multi‐scale information aggregation module and embed this module into the high‐resolution network. This allows the network to maintain exceptionally efficient computation while effectively managing information across various scales. Empirical results indicate that SCite‐HRNet achieves remarkable performance on both the COCO dataset and the challenging average precision (AP)‐10K dataset.
A broadband beam‐steerable Fabry–Pérot antenna employing water‐based reconfigurable partially reflective surface
Authors: Yan Jiali , Liu Zhiming , Zhou Huilin , Wang Yuhao , Xu Hao 
Published: December 2024

AbstractA novel broadband water‐based Fabry–Pérot (FP) antenna with beam‐steerable technology is proposed. The antenna consists of a water‐based reconfigurable partially reflective surface (RPRS) and a source antenna. The proposed water‐based RPRS has 13 columns of microfluidic channels inside. The water‐based RPRS achieved 1‐D beam steering by regulating phase distribution through the injection of water into its microfluidic channels. The antenna has exhibited a 10‐dB impedance bandwidth from 5.07 to 6.46 GHz (a fractional bandwidth of 24.1%). This design achieves a beam steering from −11° to +11° in the elevation plane, with measured realised gains over 10 dBi. To verify the correctness of the design, an antenna prototype was fabricated. The measured results are in good agreement with the simulated results, confirming the accuracy of the design principle. The measured results demonstrate that the main beam of the antenna prototype tilts to −12° in the broadside direction.
Determining stellar properties of massive stars in NGC346 in the SMC with a Bayesian statistic technique
Authors: Rickard M. J. , Hainich R. , Pauli D. , Hamann W.-R. , Oskinova L. M. , Prinja R. K. , Ramachandran V. , Todt H. , Schösser E. C. , Sander A. A. C. , Zeidler P. 
Published: December 2024

Context. NGC 346 is a young cluster with numerous hot OB stars. It is part of the Small Magellanic Cloud (SMC), and has an average metallicity that is one-seventh of the Milky Way’s. A detailed study of its stellar content provides a unique opportunity to understand the stellar and wind properties of massive stars in low-metallicity environments, and enables us to improve our understanding of star formation and stellar evolution.
Aims. The fundamental stellar parameters defining a star’s spectral appearance are its effective surface temperature, surface gravity, and projected rotational velocity. Unfortunately, these parameters cannot be obtained independently from only H and He spectral features as they are partially degenerate. With this work we aim to overcome this degeneracy by applying a newly developed Bayesian statistic technique that can fit these three parameters simultaneously.
Methods. Multi-epoch optical spectra are used in combination with a Bayesian statistic technique to fit stellar properties based on a publicly available grid of synthetic spectra of stellar atmospheres. The use of all of the multi-epoch observations simultaneously allows the identification of binaries.
Results. The stellar parameters for 34 OB stars within the core of NGC 346 are derived and presented here. By the use of both He I and He II lines, the partial degeneracy between the stellar parameters of effective surface temperature, surface gravity, and projected rotational velocity is overcome. A lower limit to the binary fraction of the sample of stars is found to be at least 46%.
Conclusions. Based on comparisons with analysis conducted on an overlapping sample of stars within NGC 346, the Bayesian statistic technique approach is shown to be a viable method to measure stellar parameters for hot massive stars in low-metallicity environments even when only low-resolution spectra are available.