bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying Ionospheric Small‐Scale Currents: A Spatial Correlation Study Using Closely‐Spaced Pairs of Ground Magnetometers
Authors: Gottesman Ari S. , Moldwin Mark B. , McCuen Brett A. 
Published: September 2024

AbstractThe occurrence of small‐scale and intense ionospheric currents that can contribute to geomagnetically induced currents have recently been discovered. A difficulty in their characterization is that their signatures are often only observed at single widely spaced (typically 200–400 km) ground geomagnetic stations. These small‐scale structures motivate the examination of the maximum station separation required to fully characterize these small‐scale signatures. We analyze distributions of correlation coefficients between closely spaced mid‐latitude and auroral zone ground magnetometer stations spanning day to month long intervals to assess the separation distance at which geomagnetic signatures appear in only one station. Distributions were analyzed using periods that included low and high geomagnetic activity. We used data from pairs of magnetometer stations across North America within 200 km of each other, all of which were separated primarily latitudinally. Results show that while measurements remain largely similar up to separations of 200 km, large and frequent differences appear starting at around 130 km separation. Larger differences and lower correlations are observed during high geomagnetic activity, while low geomagnetic activity leads to frequent high correlation even past 200 km separation. Small but identifiable differences can appear in magnetometer data from stations as close as 35 km during high geomagnetic activity. We recommend future magnetometer array deployment in the auroral and sub‐auroral zone to have separations of 100–150 km. This enables the monitoring of large scale effects of geomagnetic storms, better temporal and spatial resolution of substorms, and observations of small‐scale current signatures.
Observing a Volatile Organic Compound From a Geostationary Infrared Sounder: HCOOH From FengYun‐4B/GIIRS
Authors: Zeng Zhao‐Cheng , Franco Bruno , Clarisse Lieven , Lee Lu , Qi Chengli , Lu Feng 
Published: September 2024

AbstractFormic acid (HCOOH) is one of the most abundant volatile organic compounds (VOCs) in the Earth's atmosphere and an important source of atmospheric acidity. Here we present the first retrieval of HCOOH from a geostationary orbit using observations from the Geostationary Interferometric Infrared Sounder (GIIRS) on board FengYun‐4B. The results from July 2022 to June 2023 show the monthly variation of the HCOOH distribution in Asia. In addition, we show that FY‐4B/GIIRS effectively tracks HCOOH enhancements from wildfires both during the day and at night. Finally, inter‐comparison with IASI HCOOH data shows good agreement, indicating that FY‐4B/GIIRS observations have comparable sensitivity to IASI. This study is an important first step toward monitoring VOCs from geostationary infrared sounders, including the existing and future GIIRS on board the FY‐4 series and the forthcoming European geostationary infrared sounder (IRS) on board Meteosat Third Generation (MTG).
Disentangling the Impacts of Environmental Factors on Evaporative Fraction Across Climate Regimes
Authors: Han Qiong , Wang Tiejun , Kong Zhe , Dai Yibin , Wang Lichun 
Published: September 2024

AbstractEvaporative fraction (EF) is a useful measure for quantifying land surface energy partitioning processes and determining evaporative regimes; however, its influencing factors remain highly uncertain. Here, global data sets were compiled to disentangle the effects of environmental variables on EF variations along climate and land surface gradients. We found that (a) at annual timescales, ecosystem‐level EF could be expressed as a power law function of aridity index. The relationships of mean annual soil water content (SWC) and leaf area index (LAI) with mean annual EF resembled the traditional evaporative regime theory; (b) at daily timescales, the boosted regression tree method quantitatively revealed that the impacts of environmental variables (including meteorological variables) on EF showed equal importance, especially at humid sites, primarily due to the different response direction and magnitude of latent heat (LE) and sensible heat (H) fluxes to environmental changes. Particularly, the contrasting responses of LE (positive) and H (negative) to SWC, LAI, and relative humidity enhanced the positive effects of those influencing variables on EF; whereas, the correlations between EF and energy‐related factors (i.e., net radiation‐Rn and air temperature‐Ta) deteriorated as both LE and H showed positive response patterns to those variables; (c) meteorological factors were also found to have nonlinear effects on daily EF, further modified by climatic conditions. Rn near 150 W/m2 and Ta near 15°C appeared to be important energy‐partitioning thresholds at drier and humid sites, respectively. Moreover, changing interactions among environmental variables with climates were demonstrated to be important for better explaining EF variations.
Non-canonical translation in cancer: significance and therapeutic potential of non-canonical ORFs, m6A-modification, and circular RNAs
Authors: Deng Xiaoyi , Yu Yanxun V. , Jin Youngnam N. 
Published: September 2024

AbstractTranslation is a decoding process that synthesizes proteins from RNA, typically mRNA. The conventional translation process consists of four stages: initiation, elongation, termination, and ribosome recycling. Precise control over the translation mechanism is crucial, as dysregulation in this process is often linked to human diseases such as cancer. Recent discoveries have unveiled translation mechanisms that extend beyond typical well-characterized components like the m7G cap, poly(A)-tail, or translation factors like eIFs. These mechanisms instead utilize atypical elements, such as non-canonical ORF, m6A-modification, and circular RNA, as key components for protein synthesis. Collectively, these mechanisms are classified as non-canonical translations. It is increasingly clear that non-canonical translation mechanisms significantly impact the various regulatory pathways of cancer, including proliferation, tumorigenicity, and the behavior of cancer stem cells. This review explores the involvement of a variety of non-canonical translation mechanisms in cancer biology and provides insights into potential therapeutic strategies for cancer treatment.
DDB2 expression lights the way for precision radiotherapy response in PDAC cells, with or without olaparib
Authors: Dardare Julie , Witz Andréa , Betz Margaux , François Aurélie , Lamy Laureline , Husson Marie , Demange Jessica , Rouyer Marie , Lambert Aurélien , Merlin Jean-Louis , Gilson Pauline , Harlé Alexandre 
Published: September 2024

AbstractPancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers. Therapeutic options for PDAC are primarily restricted to surgery in the early stages of the disease or chemotherapy in advanced disease. Only a subset of patients with germline defects in BRCA1/2 genes can potentially benefit from personalized therapy, with the PARP inhibitor olaparib serving as a maintenance treatment for metastatic disease. Although the role of radiotherapy in PDAC remains controversial, the use of radiosensitizers offers hope for improving cancer management. Previously, we have shown that damage-specific DNA binding protein 2 (DDB2) is a potential prognostic and predictive biomarker for chemotherapy response in PDAC. In this study, we investigated the function of DDB2 in radiotherapy response, with and without radiosensitization by olaparib in PDAC cells. Our findings demonstrated DDB2 resistance to radiation effects, thereby improving cell survival and enhancing the repair of ionizing radiation-induced DNA double-strand breaks. We observed that DDB2 expression enhances the cell cycle arrest in the G2 phase by phosphorylating Chk1 and Chk2 cell cycle checkpoints. Additionally, we identified a novel link between DDB2 and PARP1 in the context of radiotherapy, which enhances the expression and activity of PARP1. Our findings highlight the potential of low-DDB2 expression to potentiate the radiosensitization effect of olaparib in PDAC cells. Collectively, this study provides novel insights into the impacts of DDB2 in the radiotherapy response in PDAC, enabling its employment as a potential biomarker to predict resistance to radiation. Furthermore, DDB2 represents a significant step forward in precision radiotherapy by widening the scope of patients who can be benefiting from olaparib as a radiosensitizer. Hence, this research has the potential to enrich the limited use of radiotherapy in the care of patients with PDAC.
Predicting COVID-19 booster immunogenicity against future SARS-CoV-2 variants and the benefits of vaccine updates
Authors: Cromer Deborah , Reynaldi Arnold , Mitchell Ainslie , Schlub Timothy E. , Juno Jennifer A. , Wheatley Adam K. , Kent Stephen J. , Khoury David S. , Davenport Miles P. 
Published: September 2024

AbstractThe ongoing evolution of the SARS-CoV-2 virus has led to a move to update vaccine antigens in 2022 and 2023. These updated antigens were chosen and approved based largely on in vitro neutralisation titres against recent SARS-CoV-2 variants. However, unavoidable delays in vaccine manufacture and distribution meant that the updated booster vaccine was no longer well-matched to the circulating SARS-CoV-2 variant by the time of its deployment. Understanding whether the updating of booster vaccine antigens improves immune responses to subsequent SARS-CoV-2 circulating variants is a major priority in justifying future vaccine updates. Here we analyse all available data on the immunogenicity of variants containing SARS-CoV-2 vaccines and their ability to neutralise later circulating SARS-CoV-2 variants. We find that updated booster antigens give a 1.4-fold [95% CI: 1.07–1.82] greater increase in neutralising antibody levels when compared with a historical vaccine immunogen. We then use this to predict the relative protection that can be expected from an updated vaccine even when the circulating variant has evolved away from the updated vaccine immunogen. These findings help inform the rollout of future booster vaccination programmes.
A hierarchical atlas of the human cerebellum for functional precision mapping
Authors: Nettekoven Caroline , Zhi Da , Shahshahani Ladan , Pinho Ana Luísa , Saadon-Grosman Noam , Buckner Randy Lee , Diedrichsen Jörn 
Published: September 2024

AbstractThe human cerebellum is activated by a wide variety of cognitive and motor tasks. Previous functional atlases have relied on single task-based or resting-state fMRI datasets. Here, we present a functional atlas that integrates information from seven large-scale datasets, outperforming existing group atlases. The atlas has three further advantages. First, the atlas allows for precision mapping in individuals: the integration of the probabilistic group atlas with an individual localizer scan results in a marked improvement in prediction of individual boundaries. Second, we provide both asymmetric and symmetric versions of the atlas. The symmetric version, which is obtained by constraining the boundaries to be the same across hemispheres, is especially useful in studying functional lateralization. Finally, the regions are hierarchically organized across three levels, allowing analyses at the appropriate level of granularity. Overall, the present atlas is an important resource for the study of the interdigitated functional organization of the human cerebellum in health and disease.
High power density redox-mediated Shewanella microbial flow fuel cells
Authors: Zhang Leyuan , Zhang Yucheng , Liu Yang , Wang Sibo , Lee Calvin K. , Huang Yu , Duan Xiangfeng 
Published: September 2024

AbstractMicrobial fuel cells utilize exoelectrogenic microorganisms to directly convert organic matter into electricity, offering a compelling approach for simultaneous power generation and wastewater treatment. However, conventional microbial fuel cells typically require thick biofilms for sufficient metabolic electron production rate, which inevitably compromises mass and charge transport, posing a fundamental tradeoff that limits the achievable power density (<1 mW cm−2). Herein, we report a concept for redox-mediated microbial flow fuel cells that utilizes artificial redox mediators in a flowing medium to efficiently transfer metabolic electrons from planktonic bacteria to electrodes. This approach effectively overcomes mass and charge transport limitations, substantially reducing internal resistance. The biofilm-free microbial flow fuel cell thus breaks the inherent tradeoff in dense biofilms, resulting in a maximum current density surpassing 40 mA cm−2 and a highest power density exceeding 10 mW cm−2, approximately one order of magnitude higher than those of state-of-the-art microbial fuel cells.
Concurrent oxygen evolution reaction pathways revealed by high-speed compressive Raman imaging
Authors: Pandya Raj , Dorchies Florian , Romanin Davide , Lemineur Jean-François , Kanoufi Frédéric , Gigan Sylvain , Chin Alex W. , de Aguiar Hilton B. , Grimaud Alexis 
Published: September 2024

AbstractTransition metal oxides are state-of-the-art materials for catalysing the oxygen evolution reaction (OER), whose slow kinetics currently limit the efficiency of water electrolysis. However, microscale physicochemical heterogeneity between particles, dynamic reactions both in the bulk and at the surface, and an interplay between particle reactivity and electrolyte makes probing the OER challenging. Here, we overcome these limitations by applying state-of-the-art compressive Raman imaging to uncover concurrent bias-dependent pathways for the OER in a dense, crystalline electrocatalyst, α-Li2IrO3. By spatially and temporally tracking changes in stretching modes we follow catalytic activation and charge accumulation following ion exchange under various electrolytes and cycling conditions, comparing our observations with other crystalline catalysts (IrO2, LiCoO2). We demonstrate that at low overpotentials the reaction between water and the oxidized catalyst surface is compensated by bulk ion exchange, as usually only found for amorphous, electrolyte permeable, catalysts. At high overpotentials the charge is compensated by surface redox active sites, as in other crystalline catalysts such as IrO2. Hence, our work reveals charge compensation can extend beyond the surface in crystalline catalysts. More generally, the results highlight the power of compressive Raman imaging for chemically specific tracking of microscale reaction dynamics in catalysts, battery materials, or memristors.
Hydroxylated TiO2-induced high-density Ni clusters for breaking the activity-selectivity trade-off of CO2 hydrogenation
Authors: Wang Cong-Xiao , Liu Hao-Xin , Gu Hao , Li Jin-Ying , Lai Xiao-Meng , Fu Xin-Pu , Wang Wei-Wei , Fu Qiang , Wang Feng Ryan , Ma Chao , Jia Chun-Jiang 
Published: September 2024

AbstractThe reverse water gas shift reaction can be considered as a promising route to mitigate global warming by converting CO2 into syngas in a large scale, while it is still challenging for non-Cu-based catalysts to break the trade-off between activity and selectivity. Here, the relatively high loading of Ni species is highly dispersed on hydroxylated TiO2 through the strong Ni and −OH interactions, thereby inducing the formation of rich and stable Ni clusters (~1 nm) on anatase TiO2 during the reverse water gas shift reaction. This Ni cluster/TiO2 catalyst shows a simultaneous high CO2 conversion and high CO selectivity. Comprehensive characterizations and theoretical calculations demonstrate Ni cluster/TiO2 interfacial sites with strong CO2 activation capacity and weak CO adsorption are responsible for its unique catalytic performances. This work disentangles the activity-selectivity trade-off of the reverse water gas shift reaction, and emphasizes the importance of metal−OH interactions on surface.
Generalizability assessment of AI models across hospitals in a low-middle and high income country
Authors: Yang Jenny , Dung Nguyen Thanh , Thach Pham Ngoc , Phong Nguyen Thanh , Phu Vu Dinh , Phu Khiem Dong , Yen Lam Minh , Thy Doan Bui Xuan , Soltan Andrew A. S. , Thwaites Louise , Clifton David A. 
Published: September 2024

AbstractThe integration of artificial intelligence (AI) into healthcare systems within low-middle income countries (LMICs) has emerged as a central focus for various initiatives aiming to improve healthcare access and delivery quality. In contrast to high-income countries (HICs), which often possess the resources and infrastructure to adopt innovative healthcare technologies, LMICs confront resource limitations such as insufficient funding, outdated infrastructure, limited digital data, and a shortage of technical expertise. Consequently, many algorithms initially trained on data from non-LMIC settings are now being employed in LMIC contexts. However, the effectiveness of these systems in LMICs can be compromised when the unique local contexts and requirements are not adequately considered. In this study, we evaluate the feasibility of utilizing models developed in the United Kingdom (a HIC) within hospitals in Vietnam (a LMIC). Consequently, we present and discuss practical methodologies aimed at improving model performance, emphasizing the critical importance of tailoring solutions to the distinct healthcare systems found in LMICs. Our findings emphasize the necessity for collaborative initiatives and solutions that are sensitive to the local context in order to effectively tackle the healthcare challenges that are unique to these regions.
Potent pollen gene regulation by DNA glycosylases in maize
Authors: Zeng Yibing , Somers Julian , Bell Harrison S. , Vejlupkova Zuzana , Kelly Dawe R. , Fowler John E. , Nelms Brad , Gent Jonathan I. 
Published: September 2024

AbstractAlthough DNA methylation primarily represses TEs, it also represses select genes that are methylated in plant body tissues but demethylated by DNA glycosylases (DNGs) in endosperm or pollen. Either one of two DNGs, MATERNAL DEREPRESSION OF R1 (MDR1) or DNG102, is essential for pollen viability in maize. Using single-pollen mRNA sequencing on pollen-segregating mutations in both genes, we identify 58 candidate DNG target genes that account for 11.1% of the wild-type transcriptome but are silent or barely detectable in other tissues. They are unusual in their tendency to lack introns but even more so in their TE-like methylation (teM) in coding DNA. The majority have predicted functions in cell wall modification, and they likely support the rapid tip growth characteristic of pollen tubes. These results suggest a critical role for DNA methylation and demethylation in regulating maize genes with the potential for extremely high expression in pollen but constitutive silencing elsewhere.
BRCA2 stabilises RAD51 and DMC1 nucleoprotein filaments through a conserved interaction mode
Authors: Dunce James M. , Davies Owen R. 
Published: September 2024

AbstractBRCA2 is essential for DNA repair by homologous recombination in mitosis and meiosis. It interacts with recombinases RAD51 and DMC1 to facilitate the formation of nucleoprotein filaments on resected DNA ends that catalyse recombination-mediated repair. BRCA2’s BRC repeats bind and disrupt RAD51 and DMC1 filaments, whereas its PhePP motifs bind recombinases and stabilise their nucleoprotein filaments. However, the mechanism of filament stabilisation has hitherto remained unknown. Here, we report the crystal structure of a BRCA2-DMC1 complex, revealing how core interaction sites of PhePP motifs bind to recombinases. The interaction mode is conserved for RAD51 and DMC1, which selectively bind to BRCA2’s two distinct PhePP motifs via subtly divergent binding pockets. PhePP motif sequences surrounding their core interaction sites protect nucleoprotein filaments from BRC-mediated disruption. Hence, we report the structural basis of how BRCA2’s PhePP motifs stabilise RAD51 and DMC1 nucleoprotein filaments for their essential roles in mitotic and meiotic recombination.
Vitessce: integrative visualization of multimodal and spatially resolved single-cell data
Authors: Keller Mark S. , Gold Ilan , McCallum Chuck , Manz Trevor , Kharchenko Peter V. , Gehlenborg Nils 
Published: September 2024

Abstract
Multiomics technologies with single-cell and spatial resolution make it possible to measure thousands of features across millions of cells. However, visual analysis of high-dimensional transcriptomic, proteomic, genome-mapped and imaging data types simultaneously remains a challenge. Here we describe Vitessce, an interactive web-based visualization framework for exploration of multimodal and spatially resolved single-cell data. We demonstrate integrative visualization of millions of data points, including cell-type annotations, gene expression quantities, spatially resolved transcripts and cell segmentations, across multiple coordinated views. The open-source software is available at http://vitessce.io.
A chromosome-scale reference genome of grasspea (Lathyrus sativus)
Authors: Vigouroux Marielle , Novák Petr , Oliveira Ludmila Cristina , Santos Carmen , Cheema Jitender , Wouters Roland H. M. , Paajanen Pirita , Vickers Martin , Koblížková Andrea , Vaz Patto Maria Carlota , Macas Jiří , Steuernagel Burkhard , Martin Cathie , Emmrich Peter M. F. 
Published: September 2024

AbstractGrasspea (Lathyrus sativus L.) is an underutilised but promising legume crop with tolerance to a wide range of abiotic and biotic stress factors, and potential for climate-resilient agriculture. Despite a long history and wide geographical distribution of cultivation, only limited breeding resources are available. This paper reports a 5.96 Gbp genome assembly of grasspea genotype LS007, of which 5.03 Gbp is scaffolded into 7 pseudo-chromosomes. The assembly has a BUSCO completeness score of 99.1% and is annotated with 31719 gene models and repeat elements. This represents the most contiguous and accurate assembly of the grasspea genome to date.
High-throughput dataset of impurity adsorption on common catalysts in biomass upgrading applications
Authors: Nolen Michelle A. , Tacey Sean A. , Arellano-Treviño Martha A. , Van Allsburg Kurt M. , Farberow Carrie A. 
Published: September 2024

AbstractAn extensive dataset consisting of adsorption energies of pernicious impurities present in biomass upgrading processes on common catalysts and support materials has been generated. This work aims to inform catalyst and process development for the conversion of biomass-derived feedstocks to fuels and chemicals. A high-throughput workflow was developed to execute density functional theory calculations for a diverse set of atomic (Al, B, Ca, Cl, Fe, K, Mg, Mn, N, Na, P, S, Si, Zn) and molecular (COS, H2S, HCl, HCN, K2O, KCl, NH3) species on 35 unique surfaces for transition-metal (Ag, Au, Co, Cu, Fe, Ir, Ni, Pd, Pt, Re, Rh, Ru) and metal-oxide (Al2O3, MgO, anatase-TiO2, rutile-TiO2, ZnO, ZrO2) catalysts and supports. Approximately 3,000 unique adsorption geometries and corresponding adsorption energies were obtained.