bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of breathing patterns to stabilize cardiovascular changes in physical stress environments : inspiration responds to rapid changes in blood pressure
Authors: Kim Daechang , Baek Seungbin , Kim Seunghui , Im Sanghee , Kim Sungmin 
Published: April 2024

AbstractThe thoracic nerves form a complex neural network that coordinates involuntary muscles such as breathing and the heart. Breathing has various patterns to maintain homeostasis in the human body. This study analyzes changes in the cardiovascular system and breathing patterns induced by stress caused by various mechanical movements performed in daily life and ultimately, the goal is to propose effective breathing patterns and breathing control methods to maintain cardiovascular homeostasis. The participants’ age was 26.97 ± 3.93 years, height was 170.24 ± 8.61 cm, and weight was 65.69 ± 13.55 Kg, and there were 62 men and 38 women. Breathing and electrocardiogram were obtained using HiCard+, a biometric monitoring device. The measured electrocardiogram was analyzed for heartbeat interval, which indicates changes in the cardiovascular system, and standard deviation of normal to normal interval (SDNN) and root mean square of the successive differences (rMSSD), which indicate the activity of the autonomic and parasympathetic nervous systems. For respiration, time changes were analyzed as patterns by calculating inspiration and exhalation times. As a result of this study, rapid changes in blood pressure increased SDNN and rMSSD from 0.053 ± 0.06 and 0.056 ± 0.087 to 0.109 ± 0.114 and 0.125 ± 0.170 s, and induced an increase in spontaneous inspiratory time from 1.46 to 1.51 s (p < 0.05). Ultimately, we hope that the results of this study will be used as a breathing control training technique to prevent and manage rapid cardiovascular changes.
Shear strength of soil by using rice husk ash waste for sustainable ground improvement
Authors: Shehata Abdelmageed Atef Abdelmageed , Owino Alex Otieno , Islam Md. Yachin , Hossain Zakaria 
Published: April 2024

AbstractIn the global construction industry, areas characterized by weak and expansive soils are on the rise, necessitating effective solutions for strength enhancement. Addressing this concern, sustainable soil amendments have gained attention, with rice husk ash (RHA) from rice milling industries being a notable focus. Our experimental study aimed to assess the shear strength of this innovative construction material, introducing a unique approach that considers subgrade layers with minimal cement dosage, including upper, bottom, and double layers a novel contribution yet unexplored in existing literature. In addition to conventional mechanical testing, we employed SEM (Scanning Electron Microscopy) and EDS (Energy-Dispersive X-ray Spectroscopy) analyses to comprehensively explore the treated soils' microstructural and elemental composition aspects. Examining sixteen specimen combinations of weak expansive soil-RHA-cement, varying proportions of RHA (2%, 4%, 6%) and cement (2%, 4%, 6%) were mixed to understand their effects on shear strength parameters. Our findings revealed significant shear strength improvement in each subgrade layer, with specimen 6%RHA6%C in the lower subgrade layer exhibiting the highest cohesive strength at 143 kN/m2. Notably, the double layer configuration, specimen 2%RHA6%C, achieved maximum deviatoric stresses of 383 kN/m2. This novel construction material contributes to effective waste management and presents an innovative engineering solution for sustainable ground improvement, offering promising prospects for future geotechnical advancements.
Hydrological Projections in the Third Pole Using Artificial Intelligence and an Observation‐Constrained Cryosphere‐Hydrology Model
Authors: Long Junshui , Wang Lei , Chen Deliang , Li Ning , Zhou Jing , Li Xiuping , Guo Xiaoyu , Liu Hu , Chai Chenhao , Fan Xinfeng 
Published: April 2024

AbstractThe water resources of the Third Pole (TP), highly sensitive to climate change and glacier melting, significantly impact the water and food security of millions in Asia. However, projecting future spatial‐temporal runoff changes for TP's mountainous basins remains a formidable challenge. Here, we've leveraged the long short‐term memory model (LSTM) to craft a grid‐scale artificial intelligence (AI) model named LSTM‐grid. This model has enabled the production of hydrological projections for the seven major river basins of TP. The LSTM‐grid model integrates monthly precipitation, air temperature, and total glacier mass changes (total_GMC) data at a 0.25‐degree model grid. Training the LSTM‐grid model employed gridded historical monthly runoff and evapotranspiration data sets generated by an observation‐constrained cryosphere‐hydrology model at the headwaters of seven TP river basins during 2000–2017. Our results demonstrate the LSTM grid's effectiveness and usefulness, exhibiting a Nash‐Sutcliffe Efficiency coefficient exceeding 0.92 during the verification periods (2013–2017). Moreover, river basins in the monsoon region exhibited a higher rate of runoff increase compared to those in the westerlies region. Intra‐annual projections indicated notable increases in spring runoff, especially in basins where glacier meltwater significantly contributes to runoff. Additionally, the LSTM‐grid model aptly captures the runoff changes before and after the turning points of glacier melting, highlighting the growing influence of precipitation on runoff after reaching the maximum total_GMC. Therefore, the LSTM‐grid model offers a fresh perspective for understanding the spatiotemporal distribution of water resources in high‐mountain glacial regions by tapping into AI's potential to drive scientific discovery and provide reliable data.
Calculating the High‐Latitude Ionospheric Electrodynamics Using a Machine Learning‐Based Field‐Aligned Current Model
Authors: Gowtam V. Sai , Connor Hyunju , Kunduri Bharat S. R. , Raeder Joachim , Laundal Karl M. , Tulasi Ram S. , Ozturk Dogacan S. , Hampton Donald , Chakraborty Shibaji , Owolabi Charles , Keesee Amy 
Published: April 2024

AbstractWe introduce a new framework called Machine Learning (ML) based Auroral Ionospheric electrodynamics Model (ML‐AIM). ML‐AIM solves a current continuity equation by utilizing the ML model of Field Aligned Currents of Kunduri et al. (2020, https://doi.org/10.1029/2020JA027908), the FAC‐derived auroral conductance model of Robinson et al. (2020, https://doi.org/10.1029/2020JA028008), and the solar irradiance conductance model of Moen and Brekke (1993, https://doi.org/10.1029/92gl02109). The ML‐AIM inputs are 60‐min time histories of solar wind plasma, interplanetary magnetic fields (IMF), and geomagnetic indices, and its outputs are ionospheric electric potential, electric fields, Pedersen/Hall currents, and Joule Heating. We conduct two ML‐AIM simulations for a weak geomagnetic activity interval on 14 May 2013 and a geomagnetic storm on 7–8 September 2017. ML‐AIM produces physically accurate ionospheric potential patterns such as the two‐cell convection pattern and the enhancement of electric potentials during active times. The cross polar cap potentials (ΦPC) from ML‐AIM, the Weimer (2005, https://doi.org/10.1029/2004ja010884) model, and the Super Dual Auroral Radar Network (SuperDARN) data‐assimilated potentials, are compared to the ones from 3204 polar crossings of the Defense Meteorological Satellite Program F17 satellite, showing better performance of ML‐AIM than others. ML‐AIM is unique and innovative because it predicts ionospheric responses to the time‐varying solar wind and geomagnetic conditions, while the other traditional empirical models like Weimer (2005, https://doi.org/10.1029/2004ja010884) designed to provide a quasi‐static ionospheric condition under quasi‐steady solar wind/IMF conditions. Plans are underway to improve ML‐AIM performance by including a fully ML network of models of aurora precipitation and ionospheric conductance, targeting its characterization of geomagnetically active times.
Metasurface array for single-shot spectroscopic ellipsometry
Authors: Wen Shun , Xue Xinyuan , Wang Shuai , Ni Yibo , Sun Liqun , Yang Yuanmu 
Published: April 2024

AbstractSpectroscopic ellipsometry is a potent method that is widely adopted for the measurement of thin film thickness and refractive index. Most conventional ellipsometers utilize mechanically rotating polarizers and grating-based spectrometers for spectropolarimetric detection. Here, we demonstrated a compact metasurface array-based spectroscopic ellipsometry system that allows single-shot spectropolarimetric detection and accurate determination of thin film properties without any mechanical movement. The silicon-based metasurface array with a highly anisotropic and diverse spectral response is combined with iterative optimization to reconstruct the full Stokes polarization spectrum of the light reflected by the thin film with high fidelity. Subsequently, the film thickness and refractive index can be determined by fitting the measurement results to a proper material model with high accuracy. Our approach opens up a new pathway towards a compact and robust spectroscopic ellipsometry system for the high throughput measurement of thin film properties.
Exploring the genetic etiology across the continuum of the general psychopathology factor: a Swedish population-based family and twin study
Authors: Liu Yangjun , Lichtenstein Paul , Kotov Roman , Larsson Henrik , D’Onofrio Brian M. , Pettersson Erik 
Published: April 2024

AbstractPsychiatric comorbidity can be accounted for by a latent general psychopathology factor (p factor), which quantifies the variance that is shared to varying degrees by every dimension of psychopathology. It is unclear whether the entire continuum of the p factor shares the same genetic origin. We investigated whether mild, moderate, and extreme elevations on the p factor shared the same genetic etiology by, first, examining the linearity of the association between p factors across siblings (N = 580,891 pairs). Second, we estimated the group heritability in a twin sample (N = 17,170 pairs), which involves testing whether the same genetic variants influence both extreme and normal variations in the p factor. In both samples, the p factor was based on 10 register-based psychiatric diagnoses. Results showed that the association between siblings’ p factors appeared linear, even into the extreme range. Likewise, the twin group heritabilities ranged from 0.42 to 0.45 (95% CI: 0.33–0.57) depending on the thresholds defining the probands (2–3.33 SD beyond the mean; >2 SD beyond the mean; >4.33 SD beyond the mean; and >5.33 SD beyond the mean), and these estimates were highly similar to the estimated individual differences heritability (0.41, 95% CI: 0.39–0.43), indicating that scores above and below these thresholds shared a common genetic origin. Together, these results suggest that the entire continuum of the p factor shares the same genetic origin, with common genetic variants likely playing an important role. This implies, first, genetic risk factors for the aspect that is shared between all forms of psychopathology (i.e., genetic risk factors for the p factor) might be generalizable between population-based cohorts with a higher prevalence of milder cases, and clinical samples with a preponderance of more severe cases. Second, prioritizing low-cost genome-wide association studies capable of identifying common genetic variants, rather than expensive whole genome sequencing that can identify rare variants, may increase the efficiency when studying the genetic architecture of the p factor.
Sorafenib inhibits ossification of the posterior longitudinal ligament by blocking LOXL2-mediated vascularization
Authors: Wang Longqing , Jiang Wenhao , Zhao Siyuan , Xie Dong , Chen Qing , Zhao Qi , Wu Hao , Luo Jian , Yang Lili 
Published: April 2024

AbstractOssification of the Posterior Longitudinal Ligament (OPLL) is a degenerative hyperostosis disease characterized by the transformation of the soft and elastic vertebral ligament into bone, resulting in limited spinal mobility and nerve compression. Employing both bulk and single-cell RNA sequencing, we elucidate the molecular characteristics, cellular components, and their evolution during the OPLL process at a single-cell resolution, and validate these findings in clinical samples. This study also uncovers the capability of ligament stem cells to exhibit endothelial cell-like phenotypes in vitro and in vivo. Notably, our study identifies LOXL2 as a key regulator in this process. Through gain-and loss-of-function studies, we elucidate the role of LOXL2 in the endothelial-like differentiation of ligament cells. It acts via the HIF1A pathway, promoting the secretion of downstream VEGFA and PDGF-BB. This function is not related to the enzymatic activity of LOXL2. Furthermore, we identify sorafenib, a broad-spectrum tyrosine kinase inhibitor, as an effective suppressor of LOXL2-mediated vascular morphogenesis. By disrupting the coupling between vascularization and osteogenesis, sorafenib demonstrates significant inhibition of OPLL progression in both BMP-induced and enpp1 deficiency-induced animal models while having no discernible effect on normal bone mass. These findings underscore the potential of sorafenib as a therapeutic intervention for OPLL.
Pathway-based signatures predict patient outcome, chemotherapy benefit and synthetic lethal dependencies in invasive lobular breast cancer
Authors: Alexander John , Schipper Koen , Nash Sarah , Brough Rachel , Kemp Harriet , Iacovacci Jacopo , Isacke Clare , Natrajan Rachael , Sawyer Elinor , Lord Christopher J. , Haider Syed 
Published: April 2024

Abstract
Background
Invasive Lobular Carcinoma (ILC) is a morphologically distinct breast cancer subtype that represents up to 15% of all breast cancers. Compared to Invasive Breast Carcinoma of No Special Type (IBC-NST), ILCs exhibit poorer long-term outcome and a unique pattern of metastasis. Despite these differences, the systematic discovery of robust prognostic biomarkers and therapeutically actionable molecular pathways in ILC remains limited.

Methods
Pathway-centric multivariable models using statistical machine learning were developed and tested in seven retrospective clinico-genomic cohorts (n = 996). Further external validation was performed using a new RNA-Seq clinical cohort of aggressive ILCs (n = 48).

Results and conclusions
mRNA dysregulation scores of 25 pathways were strongly prognostic in ILC (FDR-adjusted P < 0.05). Of these, three pathways including Cell-cell communication, Innate immune system and Smooth muscle contraction were also independent predictors of chemotherapy response. To aggregate these findings, a multivariable machine learning predictor called PSILC was developed and successfully validated for predicting overall and metastasis-free survival in ILC. Integration of PSILC with CRISPR-Cas9 screening data from breast cancer cell lines revealed 16 candidate therapeutic targets that were synthetic lethal with high-risk ILCs. This study provides interpretable prognostic and predictive biomarkers of ILC which could serve as the starting points for targeted drug discovery for this disease.
Complex activity and short-term plasticity of human cerebral organoids reciprocally connected with axons
Authors: Osaki Tatsuya , Duenki Tomoya , Chow Siu Yu A. , Ikegami Yasuhiro , Beaubois Romain , Levi Timothée , Nakagawa-Tamagawa Nao , Hirano Yoji , Ikeuchi Yoshiho 
Published: April 2024

AbstractAn inter-regional cortical tract is one of the most fundamental architectural motifs that integrates neural circuits to orchestrate and generate complex functions of the human brain. To understand the mechanistic significance of inter-regional projections on development of neural circuits, we investigated an in vitro neural tissue model for inter-regional connections, in which two cerebral organoids are connected with a bundle of reciprocally extended axons. The connected organoids produced more complex and intense oscillatory activity than conventional or directly fused cerebral organoids, suggesting the inter-organoid axonal connections enhance and support the complex network activity. In addition, optogenetic stimulation of the inter-organoid axon bundles could entrain the activity of the organoids and induce robust short-term plasticity of the macroscopic circuit. These results demonstrated that the projection axons could serve as a structural hub that boosts functionality of the organoid-circuits. This model could contribute to further investigation on development and functions of macroscopic neuronal circuits in vitro.
Risks posed by invasive species to the provision of ecosystem services in Europe
Authors: Gallardo Belinda , Bacher Sven , Barbosa Ana Marcia , Gallien Laure , González-Moreno Pablo , Martínez-Bolea Víctor , Sorte Cascade , Vimercati Giovanni , Vilà Montserrat 
Published: April 2024

AbstractInvasive species significantly impact biodiversity and ecosystem services, yet understanding these effects at large spatial scales remains a challenge. Our study addresses this gap by assessing the current and potential future risks posed by 94 invasive species to seven key ecosystem services in Europe. We demonstrate widespread potential impacts, particularly on outdoor recreation, habitat maintenance, crop provisioning, and soil and nitrogen retention. Exposure to invasive species was higher in areas with lower provision of ecosystem services, particularly for regulating and cultural services. Exposure was also high in areas where ecosystem contributions to crop provision and nitrogen retention were at their highest. Notably, regions vital for ecosystem services currently have low invasion suitability, but face an average 77% increase in potential invasion area. Here we show that, while high-value ecosystem service areas at the highest risk represent a small fraction of Europe (0-13%), they are disproportionally important for service conservation. Our study underscores the importance of monitoring and protecting these hotspots to align management strategies with international biodiversity targets, considering both invasion vulnerability and ecosystem service sustainability.
Enhancements of electric field and afterglow of non-equilibrium plasma by Pb(ZrxTi1−x)O3 ferroelectric electrode
Authors: Xu Yijie , Liu Ning , Lin Ying , Mao Xingqian , Zhong Hongtao , Chang Ziqiao , Shneider Mikhail N. , Ju Yiguang 
Published: April 2024

AbstractManipulating surface charge, electric field, and plasma afterglow in a non-equilibrium plasma is critical to control plasma-surface interaction for plasma catalysis and manufacturing. Here, we show enhancements of surface charge, electric field during breakdown, and afterglow by ferroelectric barrier discharge. The results show that the ferroelectrics manifest spontaneous electric polarization to increase the surface charge by two orders of magnitude compared to discharge with an alumina barrier. Time-resolved in-situ electric field measurements reveal that the fast polarization of ferroelectrics enhances the electric field during the breakdown in streamer discharge and doubles the electric field compared to the dielectric barrier discharge. Moreover, due to the existence of surface charge, the ferroelectric electrode extends the afterglow time and makes discharge sustained longer when alternating the external electric field polarity. The present results show that ferroelectric barrier discharge offers a promising technique to tune plasma properties for efficient plasma catalysis and electrified manufacturing.
Fuzzy recognition by the prokaryotic transcription factor HigA2 from Vibrio cholerae
Authors: Hadži San , Živič Zala , Kovačič Matic , Zavrtanik Uroš , Haesaerts Sarah , Charlier Daniel , Plavec Janez , Volkov Alexander N. , Lah Jurij , Loris Remy 
Published: April 2024

AbstractDisordered protein sequences can exhibit different binding modes, ranging from well-ordered folding-upon-binding to highly dynamic fuzzy binding. The primary function of the intrinsically disordered region of the antitoxin HigA2 from Vibrio cholerae is to neutralize HigB2 toxin through ultra-high-affinity folding-upon-binding interaction. Here, we show that the same intrinsically disordered region can also mediate fuzzy interactions with its operator DNA and, through interplay with the folded helix-turn-helix domain, regulates transcription from the higBA2 operon. NMR, SAXS, ITC and in vivo experiments converge towards a consistent picture where a specific set of residues in the intrinsically disordered region mediate electrostatic and hydrophobic interactions while “hovering” over the DNA operator. Sensitivity of the intrinsically disordered region to scrambling the sequence, position-specific contacts and absence of redundant, multivalent interactions, point towards a more specific type of fuzzy binding. Our work demonstrates how a bacterial regulator achieves dual functionality by utilizing two distinct interaction modes within the same disordered sequence.
Nonlocality activation in a photonic quantum network
Authors: Villegas-Aguilar Luis , Polino Emanuele , Ghafari Farzad , Quintino Marco Túlio , Laverick Kiarn T. , Berkman Ian R. , Rogge Sven , Shalm Lynden K. , Tischler Nora , Cavalcanti Eric G. , Slussarenko Sergei , Pryde Geoff J. 
Published: April 2024

AbstractBell nonlocality refers to correlations between two distant, entangled particles that challenge classical notions of local causality. Beyond its foundational significance, nonlocality is crucial for device-independent technologies like quantum key distribution and randomness generation. Nonlocality quickly deteriorates in the presence of noise, and restoring nonlocal correlations requires additional resources. These often come in the form of many instances of the input state and joint measurements, incurring a significant resource overhead. Here, we experimentally demonstrate that single copies of Bell-local states, incapable of violating any standard Bell inequality, can give rise to nonlocality after being embedded into a quantum network of multiple parties. We subject the initial entangled state to a quantum channel that broadcasts part of the state to two independent receivers and certify the nonlocality in the resulting network by violating a tailored Bell-like inequality. We obtain these results without making any assumptions about the prepared states, the quantum channel, or the validity of quantum theory. Our findings have fundamental implications for nonlocality and enable the practical use of nonlocal correlations in real-world applications, even in scenarios dominated by noise.