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Relative abundance of nitrogen cycling microbes in coral holobionts reflects environmental nitrate availability
No full textRecent research suggests that nitrogen (N) cycling microbes are important for coral holobiont functioning. In particular, coral holobionts may acquire bioavailable N via prokaryotic dinitrogen (N2) fixation or remove excess N via denitrification activity. However, our understanding of environmental drivers on these processes in hospite remains limited. Employing the strong seasonality of the central Red Sea, this study assessed the effects of environmental parameters on the proportional abundances of N cycling microbes associated with the hard corals Acropora hemprichii and Stylophora pistillata. Specifically, we quantified changes in the relative ratio between nirS and nifH gene copy numbers, as a proxy for seasonal shifts in denitrification and N2 fixation potential in corals, respectively. In addition, we assessed coral tissue-associated Symbiodiniaceae cell densities and monitored environmental parameters to provide a holobiont and environmental context, respectively. While ratios of nirS to nifH gene copy numbers varied between seasons, they revealed similar seasonal patterns in both coral species, with ratios closely following patterns in environmental nitrate availability. Symbiodiniaceae cell densities aligned with environmental nitrate availability, suggesting that the seasonal shifts in nirS to nifH gene abundance ratios were probably driven by nitrate availability in the coral holobiont. Thereby, our results suggest that N cycling in coral holobionts probably adjusts to environmental conditions by increasing and/or decreasing denitrification and N2 fixation potential according to environmental nitrate availability. Microbial N cycling may, thus, extenuate the effects of changes in environmental nitrate availability on coral holobionts to support the maintenance of the coral–Symbiodiniaceae symbiosis.We thank KAUST CMOR staff and boat crews for their support with diving operations. We thank Nauras Daraghmeh for his support with re-analysing environmental parameter data.Financial support was provided by KAUST baseline funds to C.R. Voolstra and the German Research Foundation (DFG) grant nos. Wi 2677/9-1 and Wi 2677/16-1 to C.W
Magnetic core-shell nanowires as MRI contrast agents for cell tracking.
No full textBACKGROUND:Identifying the precise location of cells and their migration dynamics is of utmost importance for achieving the therapeutic potential of cells after implantation into a host. Magnetic resonance imaging is a suitable, non-invasive technique for cell monitoring when used in combination with contrast agents. RESULTS:This work shows that nanowires with an iron core and an iron oxide shell are excellent materials for this application, due to their customizable magnetic properties and biocompatibility. The longitudinal and transverse magnetic relaxivities of the core-shell nanowires were evaluated at 1.5 T, revealing a high performance as T2 contrast agents. Different levels of oxidation and various surface coatings were tested at 7 T. Their effects on the T2 contrast were reflected in the tailored transverse relaxivities. Finally, the detection of nanowire-labeled breast cancer cells was demonstrated in T2-weighted images of cells implanted in both, in vitro in tissue-mimicking phantoms and in vivo in mouse brain. Labeling the cells with a nanowire concentration of 0.8 μg of Fe/mL allowed the detection of 25 cells/µL in vitro, diminishing the possibility of side effects. This performance enabled an efficient labelling for high-resolution cell detection after in vivo implantation (~ 10 nanowire-labeled cells) over a minimum of 40 days. CONCLUSIONS:Iron-iron oxide core-shell nanowires enabled the efficient and longitudinal cellular detection through magnetic resonance imaging acting as T2 contrast agents. Combined with the possibility of magnetic guidance as well as triggering of cellular responses, for instance by the recently discovered strong photothermal response, opens the door to new horizons in cell therapy and make iron-iron oxide core-shell nanowires a promising theranostic platform.We thank Sergei Lopatin (Imaging and Characterization Core Lab at KAUST).Research reported in this publication was supported by the King Abdullah University of Science and Technology (KAUST), The Spanish State Research Agency (RETOS Program Grant No. BIO2016-77367-R and SAF2017-87670-R, Maria de Maeztu Units of Excellence Program Grant No. MDM-2017-0720), and the Basque Government (Elkartek KK-2017/00008)
Drought Stress Causes Specific Changes to the Spliceosome and Stress Granule Components
No full textThe spliceosome processes RNAs from a pre-RNA state to a mature mRNA thereby influencing RNA availability for translation, localization, and turnover. It consists of complex structures containing RNA-binding proteins (RBPs) essential for post-transcriptional gene expression control. Here we investigate the dynamic modifications of spliceosomal RBPs under stress and in particular drought stress. We do so by mRNA interactome capture in Arabidopsis thaliana using label free quantitation. This approach identified 44 proteins associated with the spliceosome and further 32 proteins associated with stress granules. We noted a high enrichment in the motifs RDRR and RSRSRS that are characteristic of RNA interacting proteins. Identification of splicing factors reflect direct and/or indirect stress induced splicing events that have a direct effect on transcriptome and proteome changes under stress. Furthermore, detection of stress granule components is consistent with transcriptional arrest. Identification of drought induced stress granule components is critical in determining common abiotic stress-induced foci that can have biotechnological applications. This study may therefore open ways to modify plant stress responses at a systems level through the modification of key spliceosome components.The authors would like to thank Marco Chiapello and Mike Deery from the Cambridge Center for Proteomics (CCP), University of Cambridge for their assistance in Mass spectrometry and data analyses discussions, Xiaolan Yu for providing Arabidopsis ecotype Columbia-0 cell suspension cultures. Funding. This work was supported by the Office of Competitive Research Grant Program from the King Abdullah University of Science and Technology (grant no. CRG3-62140383)
Impact of wintertime indoor hygrothermal conditions and adaptation behavior on dry eye syndrome
No full textDry eye syndrome (DES) is a prevalent ocular condition influenced by environmental and behavioral factors, particularly during winter season. Indoor microclimates, primarily shaped by spatial configurations, heating, ventilation and air conditioning (HVAC) systems as well as occupant adaptation strategies, have a significant impact on ocular surface health. However, the combined impact of these factors remains insufficiently explored. This study combines knowledge synthesis with empirical investigation to examine how indoor hygrothermal conditions and occupant adaptation behavior influence DES symptom severity in urban households. A structured questionnaire survey is conducted among 437 residents in Zhengzhou, in the heating transitional region of China. Chi-square test and multiple regression analysis are employed to examine the associations between environmental exposures, adaptation behavior and self-reported DES. Findings suggest that the use of air conditioners (AC) or electric heaters, low humidity, proximity to heating sources and poor ventilation are linked to more severe symptoms. In contrast, those who frequently ventilate, use humidifiers, or remain in thermally stable rooms report milder discomfort. Residential characteristics — such as floor level, room size and orientation — also appear to affect symptom patterns. Shared living settings, often marked by warm, dry poorly ventilated environments and behavioral interdependence, further complicate individual DES experiences. Overall, the study identifies the sensitivity of DES to modifiable indoor environmental and behavioral factors, highlighting the need for targeted hygrothermal and behavioral interventions and calls for interdisciplinary collaboration to develop evidence-based, occupant-centered solutions for healthier residential environments.This work was completed independently without external project-based funding. The authors acknowledge academic support from the China Scholarship Council (202006090005) and the China National Scholarship (BSY202417413, SSY202027004). The authors appreciate Prof. Liping Du from the First Affiliated Hospital of Zhengzhou University for valuable suggestions, to the anonymous participants for their contributions to the survey, and to the Zhongshan Ophthalmic Center of Sun Yat-sen University, whose project “Effect of Laughter Exercise versus 0.1 % Sodium Hyaluronic Acid on Ocular Surface Discomfort in Dry Eye Disease: A Non-Inferiority Randomized Controlled Trial” (https://doi.org/10.1136/bmj-2024-080474) served as partial inspiration for this study
Modeling and state estimation of liquid metal batteries
No full textLiquid metal batteries (LMBs) represent a promising solution for grid-scale energy storage compared to other battery technologies, due to their low cost, high power density, excellent cyclability, long cycle life, self-healing characteristics, high Coulombic efficiency, and ease of scalability. The operation of an LMB involves multiple physical processes, including electrochemical reactions, mass transfer, heat transfer, fluid flow, etc. These processes are highly coupled and influence each other significantly, resulting in complex and nonlinear system behavior. As a result, accurately modeling and predicting the performance of LMBs under various operating conditions remains a significant challenge. This review highlights recent advances in LMB modeling and state estimation, providing a critical evaluation of existing frameworks in terms of modeling accuracy, computational efficiency, and practical limitations. It concludes by identifying key challenges and recommending future research directions to improve the reliability and practical deployment of LMBs in large-scale renewable energy systems.This paper is an outcome of a larger program (Stor Cortex) to develop intelligent solutions for storage technologies for the ENOWA.NEOM energy systems and was funded by ENOWA.NEOM through a technical consulting services agreement with KAUST. AMBRI INC (USA) provided the LMB cells and the system on rent to ENOWA.NEOM as part of its LDES Pilot Program Evaluation and under a consulting agreement ‘Ambri's Liquid Metal Battery Demo System’, contract number 1110000033
Structure and Smoothness Constrained Dual Networks for MR Bias Field Correction
No full textMR imaging techniques are of great benefit to disease diagnosis. However, due to the limitation of MR devices, significant intensity inhomogeneity often exists in imaging results, which impedes both qualitative and quantitative medical analysis. Recently, several unsupervised deep learning-based models have been proposed for MR image improvement. However, these models merely concentrate on global appearance learning, and neglect constraints from image structures and smoothness of bias field, leading to distorted corrected results. In this paper, novel structure and smoothness constrained dual networks, named S2DNets, are proposed aiming to self-supervised bias field correction. S2DNets introduce piece-wise structural constraints and smoothness of bias field for network training to effectively remove non-uniform intensity and retain much more structural details. Extensive experiments executed on both clinical and simulated MR datasets show that the proposed model outperforms other conventional and deep learning-based models. In addition to comparison on visual metrics, downstream MR image segmentation tasks are also used to evaluate the impact of the proposed model. The source code is available at:https://github.com/LeongDong/S2DNets.This work was supported by the National Natural Science Foundation of China (Nos. 62372135 and 62272135)
Superport networks
No full textWe study multiport networks, common in electrical engineering. They have boundary conditions different from electrical networks: the boundary vertices are split into pairs and the sum of the incoming currents is set to be zero in each pair. If one sets the voltage difference for each pair, then the incoming currents are uniquely determined. We generalize Kirchhoff's matrix-tree theorem to this setup. Different forests now contribute with different signs, making the proof subtle. In particular, we use the formula for the response matrix minors by R. Kenyon–D. Wilson, determinantal identities, and combinatorial bijections. We introduce superport networks, generalizing both ordinary networks and multiport ones.This work is supported by NSF grant DMS-1949896, the Ministry of Science and Higher Education of the Russian Federation (agreement no. 075-15-2022- 287), and Center of Excellence for Generative AI at King Abdullah University of Science and Technology (KAUST)
On free boundary problems shaped by varying singularities
No full textWe start the investigation of free boundary variational models featuring varying singularities. The theory depends strongly on the nature of the singular power γ(x) and how it changes. Under a mild continuity assumption on γ(x), we prove the optimal regularity of minimizers. Such estimates vary point-by-point, leading to a continuum of free boundary geometries. We also conduct an extensive analysis of the free boundary shaped by the singularities. Utilizing a new monotonicity formula, we show that if the singular power γ(x) varies in a W1,n+ fashion, then the free boundary is locally a C1,δ surface, up to a negligible singular set of Hausdorff co-dimension at least 3.This publication is based upon work supported by King Abdullah University of Science and Technology (KAUST) under Award No. ORFS-CRG12-2024-6430.
It was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.
DJA is supported by CNPq grant 427070/2016-3 and grant 2019/0014 from Paraíba State Research Foundation (FAPESQ).
JMU is partially supported by UID/00324 - Centre for Mathematics of the University of Coimbra.
ET is partially supported by the Grayce B. Kerr Chair funds at Oklahoma State University.
We are deeply grateful to the referee for an exceptionally careful and insightful report. The comments and suggestions were of great help and substantially improved the manuscript
Preparation of Ti3C2TxMXene-based copper/cobalt composites for electrocatalytic ammonia synthesis
No full textMXenes represent exceptionally promising electrocatalytic materials for ammonia synthesis, owing to their outstanding electrical conductivity, modifiable surface functional groups, exceptional hydrophilicity, high specific surface area, and electronegative surface characteristics. In this investigation, we systematically demonstrate that the persistent challenge of Cu and Co nanoparticle agglomeration can be effectively addressed through the in-situ growth of bimetallic CuCo nanoparticles on Ti3C2TxMXene nanosheets. This innovative approach significantly enlarges the electrochemically active surface area, maximizes the exposure of catalytically active sites, and optimizes mass transport properties, consequently leading to substantially enhanced electrocatalytic performance for ammonia synthesis. Among the series of CuxCoy/MXene composites developed, the Cu2Co1/MXene hybrid catalyst demonstrates superior nitrate reduction reaction (NO3RR) activity, achieving remarkable performance metrics including: An exceptional ammonia yield rate of 2.73 mg cm−2 h−1 at an applied potential of −0.85 V versus RHE, a high Faradaic efficiency of 72.05 %, and outstanding selectivity reaching 90.6 %. These breakthrough results establish new benchmarks for MXene-based electrocatalysts in sustainable ammonia production.S.T. acknowledge the financial support from the National Natural Science Foundation of China (Grant number 52203092) and the Natural Science Foundation of Jiangxi Province, China (Grant No. 20232BAB204026). We thank for the resources from KAUST. J.T.acknowledge financial support from the National Natural Science Foundation of China (No. 22279115) and the Fundamental Research Funds for the Provincial Universities of Zhejiang (RF-A2023005)
A Causal-Holistic Adaptive Intervention Network for Tailoring Automated Coronary Artery Disease Diagnosis to Individual Patients
No full textGiven the global prevalence and high mortality of coronary artery disease (CAD), automated CAD diagnosis should evolve toward personalized methods to maximize its clinical value. However, existing techniques have been limited to artery-level prediction, lacking patient-level causality and failing to effectively account for individual patient confounders. In this work, for the first time, we introduce a Causal-Holistic Adaptive Intervention Network (CAIN) that tailors personalized CAD diagnosis for individual patients. CAIN generates semantic representations at both the patient and artery dual-levels for each case, constructing a holistic causal graph that captures individual-specific characteristics. It then implements adaptive causal intervention based on the patient’s specific condition, using dynamically updated and differentiated intervention variables. Experimental results on CCTA scans from 602 patients and 6,830 coronary branches across three clinical centers show that CAIN outperforms state-of-the-art methods, offering personalized clinical guidance. The source code is available at (https://github.com/PerceptionComputingLab/CAIN).This work was supported by the National Natural Science Foundation of China (Nos. 62372135 and 62272135), the King Abdullah University of Science and Technology (KAUST) Office of Research Administration (ORA) under Award No. REI/1/5234-01-01, REI/1/5414-01-01, REI/1/5289-01-01, REI/1/5404-0101, REI/1/5992-01-01, URF/1/4663-01-01, Center of Excellence for Smart Health (KCSH), under award number 5932, Center of Excellence on Generative AI, under award number 5940, Heilongjiang Provincial Key Research and Development Plan 2024ZX12C23, 2023ZX02C10, 2022ZX01A30, and GA23C007, Hunan Provincial Key Research and Development Plan 2023SK2060, Jiangsu Provincial Key Research and Development Plan BE2023081, and the Natural Science Foundation of Heilongjiang Province under Grant LH2024F019