bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Significance of the Long‐Wavelength Correction for Studies of Baroclinic Tides With SWOT
Authors: Zaron Edward D. 
Published: October 2024

AbstractThe long‐wavelength correction (LWC) of SWOT data is intended to reduce errors related to the stability of the SWOT antenna and its attitude in orbit. The algorithms used to compute the LWC utilize SWOT KaRIn sea surface‐height (SSH) measurements and additional data, and the LWC may absorb geophysical SSH into the correction. Different LWC algorithms are used on the L2 and L3 SWOT products, which are analyzed here during the 1 day repeat (Cal/Val) mission phase lasting approximately 100 days. During this mission phase the SSH anomaly (SSHA) computed using the L3 LWC is much more realistic than the L2 LWC, as shown here by comparing spatial statistics of the L2 and L3 products. The L3 LWC algorithm is nonlinear insofar as it depends on second‐order statistics of the SSHA and multi‐satellite SSHA differences, making it difficult to quantify the extent to which it could absorb baroclinic tidal signals. To overcome this difficulty, a proxy L3 LWC algorithm is developed which mimics the L3 LWC but is strictly linear in the SSHA. The proxy LWC is applied to both idealized waveforms and to the predicted internal tide available on the products, and it is found to absorb 1% or less of the signal variance, leading to corresponding pointwise errors of 10% or less. Because the errors are at longer wavelengths and are significantly smaller amplitude than internal tide signals, the LWC impact on the measurement and interpretation of internal tides with SWOT is expected to be negligible in most applications.
A Global Meta‐Analysis of the Effects of Greenspaces on COVID‐19 Infection and Mortality Rates
Authors: Phogole Bopaki , Yessoufou Kowiyou 
Published: October 2024

AbstractThe COVID‐19 outbreak in 2020 resulted in rapidly rising infection rates with high associated mortality rates. In response, several epidemiological studies aimed to define ways in which the spread and severity of COVID‐19 can be curbed. As a result, there is a steady increase in the evidence linking greenspaces and COVID‐19 impact. However, the evidence of the benefits of greenspaces or greenness to human wellbeing in the context of COVID‐19 is fragmented and sometimes contradictory. This calls for a meta‐analysis of existing studies to clarify the matter. Here, we identified 621 studies across the world on the matter, which were then filtered down to 13 relevant studies for meta‐analysis, covering Africa, Asia, Europe, and the USA. These studies were meta‐analyzed, with the impacts of greenness on COVID‐19 infection rate quantified using regression estimates whereas impacts on mortality rates were measured using mortality rate ratios. We found evidence of significant negative correlations between greenness and both COVID‐19 infection and mortality rates. We further found that the impacts on COVID‐19 infection and related mortality are moderated by year of publication, greenness metrics, sample size, health and political covariates. This clarification has far‐reaching implications for policy development toward the establishment and management of green infrastructure for the benefit of human wellbeing.
Controls on the Stratigraphic Architecture of the US Atlantic Margin: Processes Forming the Accommodation Space
Authors: Lang G. , ten Brink U. S. , Hutchinson D. R. , Mountain G. S. , Schattner U. 
Published: October 2024

AbstractAccommodation space governs the spatial and temporal distributions of sediments in continental margins. Mapping the sedimentation patterns, therefore, offers insights into the solid‐Earth processes that shape accommodation space. We assembled an unprecedented amount of seismic and borehole data along the Eastern North American Margin and used it to divide the margin's sedimentary package into eight chronostratigraphic intervals, identifying temporal shifts in depocenters under the continental shelf, slope, and rise. The Jurassic depocenters follow the syn‐rift structure and its thermal subsidence loci. The Long Island Platform is the only margin segment where the early post‐rift sediment thickness matches subsidence predictions from uniform‐stretching models, whereas in Georges Bank Basin (GBB) and Baltimore Canyon Trough (BCT), sediment thickness is 1.5–3 times higher than predicted, pointing to other factors at play. A margin‐wide Jurassic transient shoulder uplift is inferred from the occurrence of stratigraphic onlaps above thinned crust. Unlike the Jurassic, the Cretaceous and Cenozoic depocenters disregard the inherited subsidence pattern. The accommodation space over the shelf and coastal plain during the Cretaceous was affected by regional isostatic compensation of the sedimentary loads accumulated on the shelf and rise. Accommodation space development in the GBB was interrupted during the Cretaceous after the margin crossed the Great Meteor Hotspot track, resulting in a widespread permanent uplift, erosion, and sediment redistribution. The distribution of anomalous Neogene subsidence in the BCT challenges previous suggestions of mantle dynamic control on the accommodation space and favors flexural downwarping of the shelf by sediment accumulation on the rise.
Modeling of Melting Layer in Cross‐Platforms Radar Observation Operator ZJU‐AERO: Multi‐Stage Melting Particle Model, Scattering Computation, and Bulk Parameterization
Authors: Xie Hejun , Bi Lei , Wang Zheng , Han Wei 
Published: October 2024

AbstractThis study presents an implementation of a new melting layer model in the ZJU‐AERO radar observation operator (Accurate and Efficient Radar Operator designed by ZheJiang University). The proposed model utilizes a coated spheroid to represent melting snow and graupel. It consists of three stages–coating, soaking, and melting–to account for the dielectric and density effects of melting particles. The scattering properties of the melting particles are computed with the Invariant‐Imbedding T‐Matrix (IITM) method, and the results are tabulated as look‐up tables for the radar operator. Regarding the parameterization of bulk optical properties, a flux‐conservation scheme is employed to estimate the size distribution of melting particles. To demonstrate its flexibility and superiority, the single and bulk scattering properties of our multi‐stage melting model are compared against the traditional homogeneous model, which uses the effective medium approximation (EMA). The effectiveness of the multi‐stage melting model has also been assessed by mapping model states in the regional mesoscale model of the China Meteorology Administration (CMA‐MESO) to radar observations. In the microphysics package of CMA‐MESO, the melting process is not explicitly represented, and we assume that melting hydrometeors occur where solid and liquid phases overlap. When compared with observations, the present multi‐stage melting model successfully reproduces melting layer signatures, highlighting its potential for microphysic validation, quantitative precipitation estimations, and data assimilation studies.
An Empirical Parameterization of the Subgrid‐Scale Distribution of Water Vapor in the UTLS for Atmospheric General Circulation Models
Authors: Borella Audran , Vignon Étienne , Boucher Olivier , Rohs Susanne 
Published: October 2024

AbstractTemperature and water vapor are known to fluctuate on multiple scales. In this study 27 years of airborne measurements of temperature and relative humidity from In‐service Aircraft for a Global Observing System (IAGOS) are used to parameterize the distribution of water vapor in the upper troposphere and lower stratosphere. The parameterization is designed to simulate water vapor fluctuations within gridboxes of atmospheric general circulation models (AGCMs) with typical size of a few tens to a few hundred kilometers. The distributions currently used in such models are often not supported by observations at high altitude. More sophisticated distributions are key to represent ice supersaturation, a physical phenomenon that plays a major role in the formation of natural cirrus and contrail cirrus. Here the observed distributions are fitted with a beta law whose parameters are adjusted from the gridbox mean variables. More specifically the standard deviation and skewness of the distributions are expressed as empirical functions of the average temperature and specific humidity, two typical prognostic variables of AGCMs. Thus, the distribution of water vapor is fully parameterized for a use in these models. The new parameterization reproduces the observed distributions with a determination coefficient always greater than 0.917 and with a mean value of 0.997. The parameterization is robust to a selection of various geographical subsets of data and to gridbox sizes varying between 25 and 300 km.
Deep Learning‐Based Precipitation Simulation for Tropical Cyclones, Mesoscale Convective Systems, and Atmospheric Rivers in East Asia
Authors: Zhang Lujia , Zhao Yang , Cen Yiting , Lu Mengqian 
Published: October 2024

AbstractDifferent types of weather events, including tropical cyclones (TCs), mesoscale convective systems (MCSs), and atmospheric rivers (ARs), significantly impact precipitation patterns in East Asia. This study pioneers the application of deep learning (DL) methods, including convolutional neural network, U‐Net, and Attention U‐Net models, to simulate precipitation associated with these weather events. The spatial permutation method is also used to identify key meteorological variables for accurately generating precipitation in DL models. The DL models trained on all timeslots consistently surpass the performance of state‐of‐the‐art numerical simulations, although their efficacy slightly diminishes during extreme weather events. This outperformance is attributed to the appropriate emphasis on key variables that capture precipitation processes, such as low‐level moisture and mid‐level pressure fields. However, new DL models trained separately for TCs, MCSs, and ARs using clipped precipitation as the output does not exceed the performance of the previous DL models. Among all input features, moisture variables contribute the most to precipitation at low intensity, while the importance of other variables increases for more intense precipitation, although some discrepancies vary across models and event types. The spatial results further reveal the detailed locations of variables that are essential for accurately simulating precipitation related to weather events, such as areas of high specific humidity and strong winds. DL models could also acquire useful information from region remote to the events to improve the simulation. Overall, DL models serve as promising tools for simulating and enhancing our understanding of precipitation patterns associated with various weather events in East Asia.
Climate‐Induced Uncertainty in Modeling Gross Primary Productivity From the Light Use Efficiency Approach
Authors: Wang Jiyan , Wang Yong , Xie Xinyao , Zhao Wei , Wu Changlin , Guan Xiaobin , Yang Tao 
Published: October 2024

AbstractLight use efficiency (LUE) models, along with satellite‐based vegetation maps and climatic reanalysis products as drivers, are effective tools for estimating large‐scale gross primary productivity (GPP). However, the climate‐induced uncertainty in LUE‐based GPP remains poorly understood, particularly the temporal scaling uncertainty from ignored climatic fluctuations. Here, two 1‐hourly reanalysis products, along with site‐based observations, were employed to drive a two‐leaf LUE model at 194 eddy‐covariance (EC) sites. The observation‐driven and reanalysis‐driven GPP at the 1‐hourly resolution were evaluated against EC GPP to illustrate the uncertainty from reanalysis products, with mean absolute deviation (MAD) and Nash‐Sutcliffe efficiency (NSE) as criterion. Moreover, the climate‐induced temporal scaling uncertainty was characterized by comparing distributed GPP (modeled with 1‐hourly resolution climatic drivers) and lumped GPP (modeled with 6‐hourly resolution climatic drivers). At the 1‐hourly resolution, results demonstrated that the reanalysis‐driven GPP showed a weaker relationship with EC GPP (MAD = 0.14 gC m−2h−1, NSE = 0.48) than the observation‐driven GPP (MAD = 0.12 gC m−2h−1, NSE = 0.60), confirming the nonnegligible climate‐induced uncertainty from reanalysis products. Additionally, the climate‐induced uncertainty arising from gridded radiation was found to be significantly larger than that associated with temperature and vapor pressure deficit (VPD). At the 6‐hourly resolution, both the observation‐driven and reanalysis‐driven lumped GPP exhibited a lower relationship with EC GPP (MAD = 0.63 gC m−26h−1, NSE = 0.54) than the corresponding distributed GPP (MAD = 0.57 gC m−26h−1, NSE = 0.59), demonstrating that the climate‐induced temporal scaling uncertainty in 6‐hourly GPP estimates was significantly apparent. This study emphasizes the imperative to refine reanalysis products for more precise capture of short‐term fluctuations and to reduce scaling uncertainties in coarse temporal resolution GPP estimates.
Histone lysine methylation modifiers controlled by protein stability
Authors: Park Sungryul , Cho Jin Hwa , Kim Jeong-Hoon , Kim Jung-Ae 
Published: October 2024

AbstractHistone lysine methylation is pivotal in shaping the epigenetic landscape and is linked to cell physiology. Coordination of the activities of multiple histone lysine methylation modifiers, namely, methyltransferases and demethylases, modulates chromatin structure and dynamically alters the epigenetic landscape, orchestrating almost all DNA-templated processes, such as transcription, DNA replication, and DNA repair. The stability of modifier proteins, which is regulated by protein degradation, is crucial for their activity. Here, we review the current knowledge of modifier-protein degradation via specific pathways and its subsequent impact on cell physiology through epigenetic changes. By summarizing the functional links between the aberrant stability of modifier proteins and human diseases and highlighting efforts to target protein stability for therapeutic purposes, we aim to promote interest in defining novel pathways that regulate the degradation of modifiers and ultimately increase the potential for the development of novel therapeutic strategies.
Extended-depth of field random illumination microscopy, EDF-RIM, provides super-resolved projective imaging
Authors: Mazzella Lorry , Mangeat Thomas , Giroussens Guillaume , Rogez Benoit , Li Hao , Creff Justine , Saadaoui Mehdi , Martins Carla , Bouzignac Ronan , Labouesse Simon , Idier Jérome , Galland Frédéric , Allain Marc , Sentenac Anne , LeGoff Loïc 
Published: October 2024

AbstractThe ultimate aim of fluorescence microscopy is to achieve high-resolution imaging of increasingly larger biological samples. Extended depth of field presents a potential solution to accelerate imaging of large samples when compression of information along the optical axis is not detrimental to the interpretation of images. We have implemented an extended depth of field (EDF) approach in a random illumination microscope (RIM). RIM uses multiple speckled illuminations and variance data processing to double the resolution. It is particularly adapted to the imaging of thick samples as it does not require the knowledge of illumination patterns. We demonstrate highly-resolved projective images of biological tissues and cells. Compared to a sequential scan of the imaged volume with conventional 2D-RIM, EDF-RIM allows an order of magnitude improvement in speed and light dose reduction, with comparable resolution. As the axial information is lost in an EDF modality, we propose a method to retrieve the sample topography for samples that are organized in cell sheets.
Excitation-wavelength-dependent persistent luminescence from single-component nonstoichiometric CaGaxO4:Bi for dynamic anti-counterfeiting
Authors: Liu Bo-Mei , Lin Yue , Liu Yingchun , Lou Bibo , Ma Chong-Geng , Zhang Hui , Wang Jing 
Published: October 2024

AbstractMaterials capable of dynamic persistent luminescence (PersL) within the visible spectrum are highly sought after for applications in display, biosensing, and information security. However, PersL materials with eye-detectable and excitation-wavelength-dependent characteristics are rarely achieved. Herein, a nonstoichiometric compound CaGaxO4:Bi (x < 2) is present, which demonstrates ultra-long, color-tunable PersL. The persistent emission wavelength can be tuned by varying the excitation wavelength, enabling dynamic color modulation from the green to the orange region within the visible spectrum. Theoretical calculations, in conjunction with experimental observations, are utilized to elucidate the thermodynamic charge transitions of various defect states, thereby providing insights into the relationship between Bi3+ emitters, traps, and multicolored PersL. Furthermore, the utility of color-tunable PersL materials and flexible devices is showcased for use in visual sensing of invisible ultraviolet light, multicolor display, information encryption, and anti-counterfeiting. These discoveries create new opportunities to develop smart photoelectric materials with dynamically controlled PersL for various applications.
Autism spectrum disorder-like behaviors induced by hyper-glutamatergic NMDA receptor signaling through hypo-serotonergic 5-HT1A receptor signaling in the prefrontal cortex in mice exposed to prenatal valproic acid
Authors: Kurahashi Hitomi , Kunisawa Kazuo , Tanaka Kenji F. , Kubota Hisayoshi , Hasegawa Masaya , Miyachi Mai , Moriya Yuka , Hasegawa Yoichi , Nagai Taku , Saito Kuniaki , Nabeshima Toshitaka , Mouri Akihiro 
Published: October 2024

AbstractAutism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by repetitive behaviors, social deficits, and cognitive impairments. Maternal use of valproic acid (VPA) during pregnancy is associated with an increased risk of ASD in offspring. The prevailing pathophysiological hypothesis for ASD involves excitation/inhibition (E/I) imbalances and serotonergic dysfunction. Here, we investigated the association between glutamatergic-serotonergic neuronal interactions and ASD-like behaviors in mice exposed to prenatal VPA. Prenatal VPA exposure induced excessive repetitive self-grooming behavior and impaired social behavior and object recognition memory in young adult period. Prenatal VPA mice showed hyper-glutamatergic function (increase in basal extracellular glutamate levels and CaMKII phosphorylation) and hypo-serotonergic function (decrease in 5-hydroxyindoleacetic acid and stimulation-induced serotonin [5-HT] release, but an increase in 5-HT transporter expression) in the prefrontal cortex. Treatment with a low-affinity NMDA receptor antagonist (memantine), a selective 5-HT reuptake inhibitor (fluoxetine), and a 5-HT1A receptor agonist (tandospirone) attenuated both the increase in CaMKII phosphorylation and ASD-like behavior of prenatal VPA mice. Opto-genetic activation of the serotonergic neuronal system attenuated impairments in social behavior and object recognition memory in prenatal VPA mice. WAY-100635—a 5-HT1A receptor antagonist—antagonized the effect of fluoxetine on impaired social behavior and object recognition memory. These results suggest that E/I imbalance and ASD-like behavior are associated with hypo-serotonergic receptor signaling through 5-HT1A receptors in prenatal VPA mice.
Quiescent cancer cells induced by high-density cultivation reveals cholesterol-mediated survival and lung metastatic traits
Authors: Liu Xingyang , Min Qinjie , Cheng Xinxin , Zhang Weimin , Wu Qingnan , Chen Xu , Lv Mengzhu , Liu Siqi , Zhao Huihui , Yang Di , Tai Yidi , Lei Xiao , Wang Yan , Zhan Qimin 
Published: October 2024

Abstract
Background
The metastatic cascade, a multifaceted and highly aggressive process, is the primary cause of mortality. The survival of quiescent cancer cells in circulatory system during metastasis is crucial, yet our comprehension is constrained by the absence of universally accepted quiescent cancer models.

Method
We developed a quiescent cancer cell model using high-density cultivation. Based on the scRNA-seq analysis, IP-MS, metabolomics, mouse lung metastasis models, cholesterol assay, PLA and other molecular experiments, we explored the molecular mechanism. Immunofluorescence, atomic force microscope, FluidFM, and shear stress stimulation were used to analyze the cytoskeleton and membrane properties contributing to mechanical force resistance.

Result
We established a quiescent cancer cell model induced by high-density cultivation. Single-cell RNA sequencing (scRNA-seq) analysis reveals that CDC25A plays a crucial role in the transition to quiescence, with its expression significantly elevated in the quiescent state. Depletion of CDC25A leads to an increased proliferative capacity, and reduced metastasis under high-density conditions. Mechanistically, upregulated CDC25A in quiescent cells enhances cholesterol metabolism via endosome pathways, leading to cell cycle arrest. This increase in cholesterol reinforces the cytoskeleton, alters membrane properties, and improves resistance to mechanical forces in circulatory system.

Conclusion
CDC25A significantly increased the cholesterol metabolism through endosome pathway in quiescent cancer cells, leading to the significant changes in cytoskeleton and membrane properties so as to enhance the resistance of mechanical force in circulatory system, facilitating lung metastasis.
Four Core Genotypes mice harbour a 3.2MB X-Y translocation that perturbs Tlr7 dosage
Authors: Panten Jasper , Del Prete Stefania , Cleland James P. , Saunders Lauren M. , van Riet Job , Schneider Anja , Ginno Paul , Schneider Nina , Koch Marie-Luise , Chen Xuqi , Gerstung Moritz , Stegle Oliver , Arnold Arthur P. , Turner James M. A. , Heard Edith , Odom Duncan T. 
Published: October 2024

AbstractThe Four Core Genotypes (FCG) is a mouse model system used to disentangle the function of sex chromosomes and hormones. We report that a copy of a 3.2 MB region of the X chromosome has translocated to the YSry- chromosome and thus increased the expression of X-linked genes including the single-stranded RNA sensor and autoimmune disease mediator Tlr7. This previously-unreported X-Y translocation complicates the interpretation of studies reliant on C57BL/6J FCG mice.
LRRTM2 controls presynapse nano-organization and AMPA receptor sub-positioning through Neurexin-binding interface
Authors: Liouta Konstantina , Lubas Malgorzata , Venugopal Vasika , Chabbert Julia , Jeannière Caroline , Diaz Candice , Munier Matthieu , Tessier Béatrice , Claverol Stéphane , Favereaux Alexandre , Sainlos Matthieu , de Wit Joris , Letellier Mathieu , Thoumine Olivier , Chamma Ingrid 
Published: October 2024

AbstractSynapses are organized into nanocolumns that control synaptic transmission efficacy through precise alignment of postsynaptic neurotransmitter receptors and presynaptic release sites. Recent evidence show that Leucine-Rich Repeat Transmembrane protein LRRTM2, highly enriched and confined at synapses, interacts with Neurexins through its C-terminal cap, but the role of this binding interface has not been explored in synapse formation and function. Here, we develop a conditional knock-out mouse model (cKO) to address the molecular mechanisms of LRRTM2 regulation, and its role in synapse organization and function. We show that LRRTM2 cKO specifically impairs excitatory synapse formation and function in mice. Surface expression, synaptic clustering, and membrane dynamics of LRRTM2 are tightly controlled by selective motifs in the C-terminal domain. Conversely, the N-terminal domain controls presynapse nano-organization and postsynapse AMPAR sub-positioning and stabilization through the recently identified Neurexin-binding interface. Thus, we identify LRRTM2 as a central organizer of pre- and post- excitatory synapse nanostructure through interaction with presynaptic Neurexins.