bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characteristics of the Spatiotemporal Distribution of Influenza Incidence and Its Driving Factors Among Residents in Mainland China From 2004 to 2018
Authors: Yao Y. R. , Ma K. , Li Y. S. , Tan H. R. , Zhang J. Y. , Zhang Z. M. , Lin Y. S. , Fang F. M. 
Published: November 2024

AbstractInfluenza is an acute respiratory infection that spreads rapidly and widely in densely populated areas with low vaccination coverage. The trends and drivers of the spatial and temporal dynamics of influenza incidence among residents of mainland China have not been systematically studied. This study comprehensively analyses the dynamics and spatial correlation of influenza using long‐term scale data and spatial panel data. It then identifies the interactive process of socio‐economic and natural elements on the incidence of influenza. The highest prevalence of influenza was found in the 0–4 years age group in mainland China (mean prevalence, 67.56/100,000). In addition, influenza in mainland China shows seasonality, with fall and winter being the periods of high incidence. Between 2014 and 2017, influenza incidence was clustered in Hubei and Anhui provinces, and the spatial clustering was statistically significant (Z value > 1.96, P < 0.05). Moreover, the directionality of influenza onset continued to increase each year. Specifically, the clustering of influenza onset was stronger in the northwest‐southeast direction than in the southwest‐northeast direction between 2014 and 2018. The significant role of socioeconomic factors as a primary influence on influenza incidence, while their interaction with natural factors, such as air quality (NOx and PM2.5) and climatic conditions can exacerbate regional outbreaks. This study provides a novel perspective for better prevention and control of influenza disease among mainland Chinese residents.
Simultaneous Infrared Observations of the Jovian Auroral Ionosphere and Thermosphere
Authors: Wang Ruoyan , Stallard Tom S. , Melin Henrik , Baines Kevin H. , Moore Luke , O’Donoghue James , Johnson Rosie E. , Thomas Emma M. , Knowles Katie L. , Tiranti Paola I. , Miller Steve 
Published: November 2024

AbstractSimultaneous observations of and in Jupiter's northern infrared aurora were conducted on 02 June 2017 using Keck‐NIRSPEC to produce polar projection maps of radiance, rotational temperature, column density, and radiance. The temperature variations within the auroral region are K, generally consistent with previous studies, albeit with some structural differences. Known auroral heating sources including particle precipitation, Joule heating, and ion drag have been examined by studying the correlations between each derived quantity, yet no single dominant mechanism can be identified as the main driver for the energetics in Jupiter's northern auroral region. It appears that a complex interaction exists between the heating driven by various mechanisms and the cooling from the thermostat effect. Comparisons between the temperature and the line‐of‐sight ion velocity in the reference frame of (a) the planetary rotation and (b) the neutral atmosphere further suggest that the local thermodynamic equilibrium effect may play an important role in thermospheric heating at Jupiter. Along with previously reported heating events that occurred in both the lower and upper atmosphere, it is speculated that the heating source may originate from an altitude above Jupiter's stratosphere but below the peak altitude of overtone and quadrupole emissions.
Automated Mineralogy Analysis of the Apollo 17 73002 Continuous Core Thin Sections Using QEMSCAN Mapping Techniques
Authors: Bell S. K. , Joy K. H. , Nottingham M. , Tartèse R. , Jones R. H. , Kent J. J. , Shearer C. K. ,   the ANGSA science team
Published: November 2024

AbstractThe Apollo 17 73001/73002 double drive tube, collected at the base of the South Massif in the Taurus‐Littrow Valley, was opened in 2019 as part of the Apollo Next Generation Sample Analysis program (ANGSA). A series of continuous thin sections were prepared capturing the full length of the upper portion of the double drive tube (73002). The aim of this study was to use Quantitative Evaluation of Minerals by SCANing electron microscopy (QEMSCAN), to search for clasts of non‐lunar meteoritic origin and to analyze the mineralogy and textures within the core. By highlighting mineral groups associated with meteoritic origins, we identified 232 clasts of interest. The elemental composition of 33 clasts was analyzed using electron microprobe analysis that revealed that all clasts were of lunar origin, suggesting that any meteoritic component in the regolith material we studied is not present in the form of lithic clasts. In the process of searching for meteorite fragments, we also identified a number of clast types including a group with highly magnesian olivine compositions (Fo92.2‐96.5). We extracted raw pixel data to investigate changes in mineralogy with depth, used QEMSCAN processors to separate and group individual clasts based on mineralogy, and determined variations in particle size with depth. Our results show a decreasing abundance of glass and agglutinate clasts with depth, associated with a higher soil maturity in the upper portion of the core. The lack of stratigraphy and dominance of non‐mare clasts is consistent with the landslide origin of the material from the South Massif.
BioRT‐HBV 1.0: A Biogeochemical Reactive Transport Model at the Watershed Scale
Authors: Sadayappan Kayalvizhi , Stewart Bryn , Kerins Devon , Vierbicher Andrew , Zhi Wei , Smykalov Valerie Diana , Shi Yuning , Vis Marc , Seibert Jan , Li Li 
Published: November 2024

AbstractReactive Transport Models (RTMs) are essential tools for understanding and predicting intertwined ecohydrological and biogeochemical processes on land and in rivers. While traditional RTMs have focused primarily on subsurface processes, recent watershed‐scale RTMs have integrated ecohydrological and biogeochemical interactions between surface and subsurface. These emergent, watershed‐scale RTMs are often spatially explicit and require extensive data, computational power, and computational expertise. There is however a pressing need to create parsimonious models that require minimal data and are accessible to scientists with limited computational background. To that end, we have developed BioRT‐HBV 1.0, a watershed‐scale, hydro‐biogeochemical RTM that builds upon the widely used, bucket‐type HBV model known for its simplicity and minimal data requirements. BioRT‐HBV uses the conceptual structure and hydrology output of HBV to simulate processes including advective solute transport and biogeochemical reactions that depend on reaction thermodynamics and kinetics. These reactions include, for example, chemical weathering, soil respiration, and nutrient transformation. The model uses time series of weather (air temperature, precipitation, and potential evapotranspiration) and initial biogeochemical conditions of subsurface water, soils, and rocks as input, and output times series of reaction rates and solute concentrations in subsurface waters and rivers. This paper presents the model structure and governing equations and demonstrates its utility with examples simulating carbon and nitrogen processes in a headwater catchment. As shown in the examples, BioRT‐HBV can be used to illuminate the dynamics of biogeochemical reactions in the invisible, arduous‐to‐measure subsurface, and their influence on the observed stream or river chemistry and solute export. With its parsimonious structure and easy‐to‐use graphical user interface, BioRT‐HBV can be a useful research tool for users without in‐depth computational training. It can additionally serve as an educational tool that promotes pollination of ideas across disciplines and foster a diverse, equal, and inclusive user community.
Impacts of Offline Nonlinear Bias Correction Schemes Using the Machine Learning Technology on the All‐Sky Assimilation of Cloud‐Affected Infrared Radiances
Authors: Zhang Xuewei , Xu Dongmei , Shen Feifei , Min Jinzhong 
Published: November 2024

AbstractBias correction (BC) of the cloud‐affected infrared (IR) radiances is one of the most difficult challenges in the all‐sky data assimilation. This study introduces an offline nonlinear bias correction model based on the machine learning (ML) technology of Random Forest to enhance the impacts of Fengyun‐4A Advanced Geostationary Radiation Imager (AGRI) all‐sky radiance data assimilation. The effects of the developed model were comprehensively evaluated through sensitivity experiments based on the NoBC, BC and modified BC schemes for two super typhoon cases. Among them, the modified BC scheme is designed to extract the features of cloud‐affected systematic biases, which are more prevalent in the all‐sky IR radiance assimilation. Results showed that the modified BC scheme outperforms other schemes in terms of removing the cloud‐impacted systematic bias while retaining the useful meteorological signal. Whereas, those biases were improperly corrected by the original BC scheme when the inputs of a grid point were handled by the ML model site by site without the feature extraction, leading to a non‐Gaussian error distribution. Assimilating those better‐corrected IR radiances in the modified BC experiments would lead to a greater improvement in the analysis of the humidity and cloud ice. Based on the improved initial condition, the positive effects of the modified BC scheme are also evident in the forecasts of atmospheric variables and typhoon systems.
A blood glucose fluctuation-responsive delivery system promotes bone regeneration and the repair function of Smpd3-reprogrammed BMSC-derived exosomes
Authors: Wang Lingxiao , Yang Haoqing , Zhang Chen , Zhang Yue , He Yilin , Liu Yang , Ma Pan , Li Jun , Fan Zhipeng 
Published: November 2024

AbstractBlood glucose fluctuation leads to poor bone defect repair in patients with type 2 diabetes (T2DM). Strategies to safely and efficiently improve the bone regeneration disorder caused by blood glucose fluctuation are still a challenge. Neutral sphingophospholipase 2 (Smpd3) is downregulated in jawbone-derived bone marrow mesenchymal stem cells (BMSCs) from T2DM patients. Here, we investigated the effect of Smpd3 on the osteogenic differentiation of BMSCs and utilized exosomes from stem cells overexpressing Smpd3 as the main treatment based on the glucose responsiveness of phenylboronic acid-based polyvinyl alcohol crosslinkers and the protease degradability of gelatin nanoparticles. The combined loading of Smpd3-overexpressing stem cell-derived exosomes (Exos-Smpd3) and nanosilver ions (Ns) to construct a hydrogel delivery system (Exos-Smpd3@Ns) promoted osteogenesis and differentiation of BMSCs in a glucose-fluctuating environment, ectopic osteogenesis of BMSCs in a glucose-fluctuating environment and jawbone regeneration of diabetic dogs in vitro. Mechanistically, Smpd3 promoted the osteogenesis and differentiation of jawbone-derived BMSCs by activating autophagy in the jawbone and inhibiting macrophage polarization and oxidative stress caused by blood glucose fluctuations. These results reveal the role and mechanism of Smpd3 and the Smpd3 overexpression exosome delivery system in promoting BMSC function and bone regeneration under blood glucose fluctuations, providing a theoretical basis and candidate methods for the treatment of bone defects in T2DM patients.
OPA1 and disease-causing mutants perturb mitochondrial nucleoid distribution
Authors: Macuada J. , Molina-Riquelme I. , Vidal G. , Pérez-Bravo N. , Vásquez-Trincado C. , Aedo G. , Lagos D. , Yu-Wai-Man P. , Horvath R. , Rudge T. J. , Cartes-Saavedra B. , Eisner V. 
Published: November 2024

AbstractOptic atrophy protein 1 (OPA1) mediates inner mitochondrial membrane (IMM) fusion and cristae organization. Mutations in OPA1 cause autosomal dominant optic atrophy (ADOA), a leading cause of blindness. Cells from ADOA patients show impaired mitochondrial fusion, cristae structure, bioenergetic function, and mitochondrial DNA (mtDNA) integrity. The mtDNA encodes electron transport chain subunits and is packaged into nucleoids spread within the mitochondrial population. Nucleoids interact with the IMM, and their distribution is tightly linked to mitochondrial fusion and cristae shaping. Yet, little is known about the physio-pathological relevance of nucleoid distribution. We studied the effect of OPA1 and ADOA-associated mutants on nucleoid distribution using high-resolution confocal microscopy. We applied a novel model incorporating the mitochondrial context, separating nucleoid distribution into the array in the mitochondrial population and intramitochondrial longitudinal distribution. Opa1-null cells showed decreased mtDNA levels and nucleoid abundance. Also, loss of Opa1 led to an altered distribution of nucleoids in the mitochondrial population, loss of cristae periodicity, and altered nucleoids to cristae proximity partly rescued by OPA1 isoform 1. Overexpression of WT OPA1 or ADOA-causing mutants c.870+5 G > A or c.2713 C > T in WT cells, showed perturbed nucleoid array in the mitochondria population associated with cristae disorganization, which was partly reproduced in Skeletal muscle-derived fibroblasts from ADOA patients harboring the same mutants. Opa1-null and cells overexpressing ADOA mutants accumulated mitochondria without nucleoids. Interestingly, intramitochondrial nucleoid distribution was only altered in Opa1-null cells. Altogether, our results highlight the relevance of OPA1 in nucleoid distribution in the mitochondrial landscape and at a single-organelle level and shed light on new components of ADOA etiology.
GEFT inhibits the GSDM-mediated proptosis signalling pathway, promoting the progression and drug resistance of rhabdomyosarcoma
Authors: Yang Fan , Xia Tian , Zhao Zhijuan , Lin Jinyang , Zhong Ling , Tang Tian , Liao Degui , Lai Miaoling , Ceng Jiamin , Meng Lian , Li Feng , Liu Chunxia 
Published: November 2024

AbstractThe metastasis or recurrence of rhabdomyosarcoma (RMS) is the primary cause of tumour-related deaths. Patients with high-risk RMS have poor prognosis with a 5-year overall survival rate of 20–30%. The lack of specific drug-targeted therapy and chemotherapy resistance are the main reasons for treatment failure. Drugs or molecular target inhibitors can induce the pyroptosis of tumour cells or increase their sensitivity to chemotherapy, making pyroptosis an effective strategy for antitumour therapies. Pyroptosis is mediated by gasdermin (GSDM) family members. Here, we found that the expression of NLRP3, caspase-1, caspase-3, GSDMD and GSDME in RMS was remarkably lower than that in skeletal muscle tissues. Nigericin and dactinomycin in RMS cells achieved their regulatory effect on pyroptosis through the NLRP3/caspase-1/GSDMD pathway and caspase-3/GSDME pathway, respectively. Necrosulfonamide reversed the pyroptosis-related changes induced by nigericin, and siGSDME converted the dactinomycin-induced pyroptosis into apoptosis. Additionally, GEFT inhibited the GSDMD and GSDME pyroptosis pathways, thereby promoting the progression and drug resistance of RMS. Mouse xenograft and tumour analysis confirmed that nigericin and dactinomycin can effectively improve the therapeutic effect of RMS by activating the pyroptosis pathway. To the best of our knowledge, this study was the first to focus on pyroptosis in RMS. Overall, our investigation demonstrated that nigericin and dactinomycin play therapeutic roles in tumours by promoting RMS cell pyroptosis. Interference with GEFT and drug combination can exert a great inhibitory effect on tumours.
Iron’s role in soil organic carbon (de)stabilization in mangroves under land use change
Authors: Ruiz Francisco , Bernardino Angelo Fraga , Queiroz Hermano Melo , Otero Xosé Luis , Rumpel Cornelia , Ferreira Tiago Osório 
Published: November 2024

AbstractMangroves are coastal hotspots for carbon storage and yet face multiple threats from anthropogenic activities. Here we explore the role of iron-mediated organomineral interactions (FeOMIs) in soil organic carbon (SOC) stabilization and their sensitivity to land use change (LUC) in Amazonian mangroves. We show that Fe oxides protect more labile SOC fractions, which would otherwise be vulnerable to biological degradation, with poorly crystalline Fe oxides being the most effective phase for SOC retention. Despite the fragile equilibrium of FeOMI under dynamic redox conditions in mangroves, this balance sustains approximately 8% of total SOC. The studied LUC scenario led to massive loss of FeOMIs as less crystalline phases were either degraded or transformed into more crystalline ones, losing the efficiency in retaining SOC. The conversion of mangroves to pastures and shrimp ponds, which are pervasive globally, triggers important biogeochemical changes, with major implications for the carbon sequestration potential of mangrove soils.
Roles of SNORD115 and SNORD116 ncRNA clusters during neuronal differentiation
Authors: Helwak Aleksandra , Turowski Tomasz , Spanos Christos , Tollervey David 
Published: November 2024

AbstractIn the snoRNA host gene SNHG14, 29 consecutive introns each generate SNORD116, and 48 tandem introns encode SNORD115. Loss of SNORD116 expression, but not of SNORD115, is linked to the neurodevelopmental disease Prader-Willi syndrome. SNORD116 and SNORD115 resemble box C/D small nucleolar RNAs (snoRNAs) but lack known targets. Both were strongly accumulated during neuronal differentiation, but with distinct mechanisms: Increased host-gene expression for SNORD115 and apparent stabilization for SNORD116. For functional characterization we created cell lines specifically lacking the expressed, paternally inherited, SNORD115 or SNORD116 cluster. Analyses during neuronal development indicates changes in RNA stability and protein synthesis. These data suggest that the loss of SNORD116 enhances some aspects of developmental timing of neuronal cells. Altered mRNAs include MAGEL2, causal in the PWS-like disorder Schaaf-Yang syndrome. Comparison of SNORD115 and SNORD116 mutants identifies small numbers of altered mRNAs and ncRNAs. These are enriched for functions potentially linked to PWS phenotypes and include protocadherins, which are key cell signalling factors during neurodevelopment.
Programmable spatial magnetization stereolithographic printing of biomimetic soft machines with thin-walled structures
Authors: Meng Xianghe , Li Shishi , Shen Xingjian , Tian Chenyao , Mao Liyang , Xie Hui 
Published: November 2024

AbstractSoft machines respond to external magnetic stimuli with targeted shape changes and motions due to anisotropic magnetization, showing great potential in biomimetic applications. However, mimicking biological functionalities, particularly the complex hollow structures of organs and their dynamic behaviors, remains challenging. Here, we develop a printing method based on three-dimensional uniform magnetic field-assisted stereolithography to fabricate thin-walled soft machines with internal cavities and programmable magnetization. This printing technique employs Halbach arrays and an electromagnetic solenoid to generate an adjustable uniform magnetic field (up to 80 millitesla), efficiently orienting ferromagnetic particles, followed by solidification with patterned ultraviolet light. A support strategy and optimized material composition enhance printing stability and success rates. Our developed method enables fabrication of magnetic-driven soft machines capable of peristaltic propulsion, unidirectional fluid transport, periodic pumping action, and intake-expulsion deformation. These structures, achieving hollow ratios as high as 0.92 and enabling parallel manufacturing, highlight this technique’s considerable potential for biomedical applications by emulating complex biological behaviors and functions.
First principles methodology for studying magnetotransport in narrow gap semiconductors with ZrTe5 example
Authors: Pi Hanqi , Zhang Shengnan , Xu Yang , Fang Zhong , Weng Hongming , Wu Quansheng 
Published: November 2024

AbstractThe origin of resistivity peak and sign reversal of Hall resistivity in ZrTe5 has long been debated. Despite various theories proposed to explain these unique transport properties, there’s a lack of comprehensive first principles studies. In this work, we employ first principles calculations and Boltzmann transport theory to explore transport properties of narrow-gap semiconductors across varying temperatures and doping levels within the relaxation time approximation. We simulate the temperature-sensitive chemical potential and relaxation time in semiconductors through proper approximations, then extensively analyze ZrTe5’s transport behaviors with and without an applied magnetic field. Our results reproduce crucial experimental observations such as the zero-field resistivity anomaly, nonlinear Hall resistivity with sign reversal, and non-saturating magnetoresistance at high temperatures, without introducing topological phases and/or correlation interactions. Our approach provides a systematic understanding based on multi-carrier contributions and Fermi surface geometry, and could be extended to other narrow-gap semiconductors to explore novel transport properties.
Predictive model for abdominal liposuction volume in patients with obesity using machine learning in a longitudinal multi-center study in Korea
Authors: Sang Hyunji , Park Jaeyu , Kim Soeun , Lee Myeongcheol , Lee Hojae , Lee Sun-Ho , Yon Dong Keon , Rhee Sang Youl 
Published: November 2024

Abstract
This study aimed to develop and validate a machine learning (ML)-based model for predicting liposuction volumes in patients with obesity. This study used longitudinal cohort data from 2018 to 2023 from five nationwide centers affiliated with 365MC Liposuction Hospital, the largest liposuction hospitals in Korea. Fifteen variables related to patient profiles were integrated and applied to various ML algorithms, including random forest, support vector, XGBoost, decision tree, and AdaBoost regressors. Performance evaluation employed mean absolute error (MAE), root mean square error (RMSE), and R-squared (R2) score. Feature importance and RMSE importance analyses were performed to compare the influence of each feature on prediction performance. A total of 9,856 were included in the final analysis. The random forest regressor model best predicted the liposuction volume (MAE, 0.197, RMSE, 0.249, R2, 0.792). Body fat mass and waist circumference were the most important features of the random forest regressor model (feature importance 71.55 and 13.21, RMSE importance 0.201 and 0.221, respectively). Leveraging this model, a web-based application was developed to suggest ideal liposuction volumes. These findings could be used in clinical practice to enhance decision-making and tailor surgical interventions to individual patient needs, thereby improving overall surgical efficacy and patient satisfaction.