bluuebunny/crossref_metadata_2025_split huggingface dataset:
The nature and nurture of network evolution
Authors: Zhou Bin , Holme Petter , Gong Zaiwu , Zhan Choujun , Huang Yao , Lu Xin , Meng Xiangyi 
Published: November 2023

AbstractAlthough the origin of the fat-tail characteristic of the degree distribution in complex networks has been extensively researched, the underlying cause of the degree distribution characteristic across the complete range of degrees remains obscure. Here, we propose an evolution model that incorporates only two factors: the node’s weight, reflecting its innate attractiveness (nature), and the node’s degree, reflecting the external influences (nurture). The proposed model provides a good fit for degree distributions and degree ratio distributions of numerous real-world networks and reproduces their evolution processes. Our results indicate that the nurture factor plays a dominant role in the evolution of social networks. In contrast, the nature factor plays a dominant role in the evolution of non-social networks, suggesting that whether nodes are people determines the dominant factor influencing the evolution of real-world networks.
Direct prediction of gas adsorption via spatial atom interaction learning
Authors: Cui Jiyu , Wu Fang , Zhang Wen , Yang Lifeng , Hu Jianbo , Fang Yin , Ye Peng , Zhang Qiang , Suo Xian , Mo Yiming , Cui Xili , Chen Huajun , Xing Huabin 
Published: November 2023

AbstractPhysisorption relying on crystalline porous materials offers prospective avenues for sustainable separation processes, greenhouse gas capture, and energy storage. However, the lack of end-to-end deep learning model for adsorption prediction confines the rapid and precise screen of crystalline porous materials. Here, we present DeepSorption, a spatial atom interaction learning network that realizes accurate, fast, and direct structure-adsorption prediction with only information of atomic coordinate and chemical element types. The breakthrough in prediction is attributed to the awareness of global structure and local spatial atom interactions endowed by the developed Matformer, which provides the intuitive visualization of atomic-level thinking and executing trajectory in crystalline porous materials prediction. Complete adsorption curves prediction could be performed using DeepSorption with a higher accuracy than Grand canonical Monte Carlo simulation and other machine learning models, a 20-35% decline in the mean absolute error compared to graph neural network CGCNN and machine learning models based on descriptors. Since the established direct associations between raw structure and target functions are based on the understanding of the fundamental chemistry of interatomic interactions, the deep learning network is rationally universal in predicting the different physicochemical properties of various crystalline materials.
Mg-incorporated sorbent for efficient removal of trace CO from H2 gas
Authors: Bang Gina , Jin Seongmin , Kim Hyokyung , Kim Kyung-Min , Lee Chang-Ha 
Published: November 2023

AbstractRemoval of trace CO impurities is an essential step in the utilization of Hydrogen as a clean energy source. While various solutions are currently employed to address this challenge, there is an urgent need to improve their efficiency. Here, we show that a bead-structured Mg, Cu, and Ce-based sorbent, Mg13CuCeOx, demonstrates superior removal capacity of trace CO from H2 with high stability. The incorporation of Mg boosts sorption performance by enhancing the porous structure and Cu+ surface area. Remarkably, compared to existing pelletized sorbents, Mg13CuCeOx exhibits 15.5 to 50 times greater equilibrium capacity under pressures below 10 Pa CO and 31 times longer breakthrough time in removing 50 ppm CO in H2. Energy-efficient oxidative regeneration using air at 120 °C allows its stable sorption performance over 20 cycles. Through in-situ DRIFTS analysis, we elucidate the reaction mechanism that Mg augments the surface OH groups, promoting the formation of bicarbonate and formate species. This study highlights the potential of MgCuCeOx sorbents in advancing the hydrogen economy by effectively removing trace CO from H2.
Origin of outer tropical cyclone rainbands
Authors: Yu Cheng-Ku , Lin Che-Yu , Pun Chi-Hang 
Published: November 2023

AbstractOuter tropical cyclone rainbands (TCRs) are a concentrated region of heavy precipitation and hazardous weather within tropical cyclones (TCs). Outer TCRs pose considerable risk to human societies, but their origin remains unresolved. Here, we identify a total of 1029 outer TCRs at their formative stage from 95 TCs and present a large collection of radar observations in order to establish a robust foundation of the natural diversity of rainband origin. The results show the dominance of outer origin for the observed outer TCRs, in distinct contrast to theoretical modeling works of outer TCRs, which propose inner-origin scenarios. Our analysis also suggests that squall-line dynamics are a common, but not the sole, mechanism responsible for outer TCR formation. The nature of preexisting outer precipitation is found to be an important factor to influence the squall-line and non-squall-line outer TCR initiation.
Structure of a membrane-bound menaquinol:organohalide oxidoreductase
Authors: Cimmino Lorenzo , Duarte Américo G. , Ni Dongchun , Ekundayo Babatunde E. , Pereira Inês A. C. , Stahlberg Henning , Holliger Christof , Maillard Julien 
Published: November 2023

AbstractOrganohalide-respiring bacteria are key organisms for the bioremediation of soils and aquifers contaminated with halogenated organic compounds. The major players in this process are respiratory reductive dehalogenases, corrinoid enzymes that use organohalides as substrates and contribute to energy conservation. Here, we present the structure of a menaquinol:organohalide oxidoreductase obtained by cryo-EM. The membrane-bound protein was isolated from Desulfitobacterium hafniense strain TCE1 as a PceA2B2 complex catalysing the dechlorination of tetrachloroethene. Two catalytic PceA subunits are anchored to the membrane by two small integral membrane PceB subunits. The structure reveals two menaquinone molecules bound at the interface of the two different subunits, which are the starting point of a chain of redox cofactors for electron transfer to the active site. In this work, the structure elucidates how energy is conserved during organohalide respiration in menaquinone-dependent organohalide-respiring bacteria.
Cathepsin-facilitated invasion of BMI1-high hepatocellular carcinoma cells drives bile duct tumor thrombi formation
Authors: Xu Lei-Bo , Qin Yu-Fei , Su Liangping , Huang Cheng , Xu Qiuping , Zhang Rui , Shi Xiang-De , Sun Ruipu , Chen Jiali , Song Zhixiao , Jiang Xue , Shang Lihuan , Xiao Gang , Kong Xiangzhan , Liu Chao , Wong Ping-Pui 
Published: November 2023

AbstractBile duct tumor thrombosis (BDTT) is a complication mostly observed in patients with advanced hepatocellular carcinoma (HCC), causing jaundice and associated with poor clinical outcome. However, its underlying molecular mechanism is unclear. Here, we develop spontaneous preclinical HCC animal models with BDTT to identify the role of BMI1 expressing tumor initiating cells (BMI1high TICs) in inducing BDTT. BMI1 overexpression transforms liver progenitor cells into BMI1high TICs, which possess strong tumorigenicity and increased trans-intrahepatic biliary epithelial migration ability by secreting lysosomal cathepsin B (CTSB). Orthotopic liver implantation of BMI1high TICs into mice generates tumors and triggers CTSB mediated bile duct invasion to form tumor thrombus, while CTSB inhibitor treatment prohibits BDTT and extends mouse survival. Clinically, the elevated serum CTSB level determines BDTT incidence in HCC patients. Mechanistically, BMI1 epigenetically up-regulates CTSB secretion in TICs by repressing miR-218-1-3p expression. These findings identify a potential diagnostic and therapeutic target for HCC patients with BDTT.
Database of segmentations and surface models of bones of the entire lower body created from cadaver CT scans
Authors: Fischer Maximilian C. M. 
Published: November 2023

AbstractThe range of applications of digital surface models of the bones in science and industry is wide. Three-dimensional reconstructions of bones are used in biomechanics, biomedical engineering, medical image processing, orthopedics, traumatology, radiology, patient education, anatomy, anthropometry, forensic anthropology, ergonomics, usability and human factors engineering, or accident and injury analysis and prevention. No open access database or repository of skeletal surface models of the full lower extremities exists. Therefore, the objective of this publication was to provide access to consistent complete bone models of the pelvis and lower limbs of multiple subjects, including biometric data. Segmentations and surface models of the bones of the lower extremities of more than twenty subjects were created from open access postmortem whole-body computed tomography scans. The database provides a broad range of applications by giving access to the data of the complete process chain, from the raw medical imaging data through the segmentations to the surface models.
Quantification of rare somatic single nucleotide variants by droplet digital PCR using SuperSelective primers
Authors: Pablo-Fontecha Verónica , Hernández-Illán Eva , Reparaz Andrea , Asensio Elena , Morata Jordi , Tonda Raúl , Lahoz Sara , Parra Carolina , Lozano Juan José , García-Heredia Anabel , Martínez-Roca Alejandro , Beltran Sergi , Balaguer Francesc , Jover Rodrigo , Castells Antoni , Trullàs Ramon , Podlesniy Petar , Camps Jordi 
Published: November 2023

AbstractSomatic single-nucleotide variants (SNVs) occur every time a cell divides, appearing even in healthy tissues at low frequencies. These mutations may accumulate as neutral variants during aging, or eventually, promote the development of neoplasia. Here, we present the SP-ddPCR, a droplet digital PCR (ddPCR) based approach that utilizes customized SuperSelective primers aiming at quantifying the proportion of rare SNVs. For that purpose, we selected five potentially pathogenic variants identified by whole-exome sequencing (WES) occurring at low variant allele frequency (VAF) in at-risk colon healthy mucosa of patients diagnosed with colorectal cancer or advanced adenoma. Additionally, two APC SNVs detected in two cancer lesions were added to the study for WES-VAF validation. SuperSelective primers were designed to quantify SNVs at low VAFs both in silico and in clinical samples. In addition to the two APC SNVs in colonic lesions, SP-ddPCR confirmed the presence of three out of five selected SNVs in the normal colonic mucosa with allelic frequencies ≤ 5%. Moreover, SP-ddPCR showed the presence of two potentially pathogenic variants in the distal normal mucosa of patients with colorectal carcinoma. In summary, SP-ddPCR offers a rapid and feasible methodology to validate next-generation sequencing data and accurately quantify rare SNVs, thus providing a potential tool for diagnosis and stratification of at-risk patients based on their mutational profiling.
Natural climate solutions provide robust carbon mitigation capacity under future climate change scenarios
Authors: Marvin David C. , Sleeter Benjamin M. , Cameron D. Richard , Nelson Erik , Plantinga Andrew J. 
Published: November 2023

AbstractNatural climate solutions (NCS) are recognized as an important tool for governments to reduce greenhouse gas emissions and remove atmospheric carbon dioxide. Using California as a globally relevant reference, we evaluate the magnitude of biological climate mitigation potential from NCS starting in 2020 under four climate change scenarios. By mid-century NCS implementation leads to a large increase in net carbon stored, flipping the state from a net source to a net sink in two scenarios. Forest and conservation land management strategies make up 85% of all NCS emissions reductions by 2050, with agricultural strategies accounting for the remaining 15%. The most severe climate change impacts on ecosystem carbon materialize in the latter half of the century with three scenarios resulting in California ecosystems becoming a net source of carbon emissions under a baseline trajectory. However, NCS provide a strong attenuating effect, reducing land carbon emissions 41–54% by 2100 with total costs of deployment of 752–777 million USD annually through 2050. Rapid implementation of a portfolio of NCS interventions provides long-term investment in protecting ecosystem carbon in the face of climate change driven disturbances. This open-source, spatially-explicit framework can help evaluate risks to NCS carbon storage stability, implementation costs, and overall mitigation potential for NCS at jurisdictional scales.
Effects of filler on the microstructure and corrosion of similar and dissimilar gas inert tungsten arc welding aluminum alloys joints
Authors: Gadallah Elshafey Ahmed , El Aal Mohamed Ibrahim Abd , Mohamed Abdelkarim Yousif , El-Fahhar Hossam Hemdan 
Published: November 2023

AbstractWelding of dissimilar aluminum alloys has been widely used in many industrial applications. However, the selection of filler type still attracts significant interest in the welding research area. The present work concerns the effect of filler metal on the microstructure and corrosion of weld joints of dissimilar aluminum alloys. AA 5083 and AA 6082 alloys were welded by tungsten inert gas welding (GTAW) using filler metals ER 4043 and ER 5356. The microstructure observations and the corrosion test of the weld joints were carried out. Solidification cracks were observed in the ER 4043 weld zone, whereas defect-free joints were obtained using a mix filler welding process. A galvanic corrosion was observed on the boundary between the filler rod ER 4043 weld zone and AA 5083 base alloy. From the corrosion standpoint of view, the using of ER 4043 electrodes is not preferred for welding 5000 series aluminum alloys, whereas ER 5356 filler electrode is more favorable than ER 4043 filler electrode either for dissimilar welding of AA 5083 and AA 6082 alloys or individual welding of both aluminum alloys. No galvanic corrosion is observed between ER 4043 fillers and AA 6082 base alloy.
Cryopreservation effect on DNA methylation profile in rainbow trout spermatozoa
Authors: El Kamouh Marina , Brionne Aurélien , Sayyari Amin , Laurent Audrey , Labbé Catherine 
Published: November 2023

AbstractSpermatozoa are the cells that are most commonly used for cryopreservation of valuable genetic resources in aquaculture. It is known that fish spermatozoa transmit to the embryo not only their genetic but also their epigenetic profile, especially DNA methylation. Therefore, any alteration of the DNA methylation profile in spermatozoa induces the risk of transmitting epigenetic alterations to the offspring. The aim of this study was to assess the effect of cryopreservation on DNA methylation in rainbow trout spermatozoa. To trigger variable cellular response after freezing–thawing, spermatozoa from mature males were cryopreserved with dimethyl sulfoxide, methanol or glycerol as cryoprotectant. We observed that dimethyl sulfoxide was the best to preserve thawed spermatozoa functions. Methanol only slightly preserved all the cellular parameters, while glycerol failed to protect motility and fertilization ability. The consequences on DNA methylation were assessed using Reduced Representation Bisulfite Sequencing (RRBS). Sperm cryopreservation did not thoroughly impact DNA methylation, although 335–564 differentially methylated cytosines were characterized depending on the cryoprotectant. Very few of them were shared between cryoprotectants, and no correlation with the extent of cellular damage was found. Our study showed that DNA methylation was only slightly altered after sperm cryopreservation, and this may render further analysis of the risk for the progeny very challenging.
External validation of clinical severity scores to guide referral of paediatric acute respiratory infections in resource-limited primary care settings
Authors: Chandna Arjun , Mwandigha Lazaro , Koshiaris Constantinos , Limmathurotsakul Direk , Nosten Francois , Lubell Yoel , Perera-Salazar Rafael , Turner Claudia , Turner Paul 
Published: November 2023

AbstractAccurate and reliable guidelines for referral of children from resource-limited primary care settings are lacking. We identified three practicable paediatric severity scores (the Liverpool quick Sequential Organ Failure Assessment (LqSOFA), the quick Pediatric Logistic Organ Dysfunction-2, and the modified Systemic Inflammatory Response Syndrome) and externally validated their performance in young children presenting with acute respiratory infections (ARIs) to a primary care clinic located within a refugee camp on the Thailand-Myanmar border. This secondary analysis of data from a longitudinal birth cohort study consisted of 3010 ARI presentations in children aged ≤ 24 months. The primary outcome was receipt of supplemental oxygen. We externally validated the discrimination, calibration, and net-benefit of the scores, and quantified gains in performance that might be expected if they were deployed as simple clinical prediction models, and updated to include nutritional status and respiratory distress. 104/3,010 (3.5%) presentations met the primary outcome. The LqSOFA score demonstrated the best discrimination (AUC 0.84; 95% CI 0.79–0.89) and achieved a sensitivity and specificity > 0.80. Converting the scores into clinical prediction models improved performance, resulting in ~ 20% fewer unnecessary referrals and ~ 30–50% fewer children incorrectly managed in the community. The LqSOFA score is a promising triage tool for young children presenting with ARIs in resource-limited primary care settings. Where feasible, deploying the score as a simple clinical prediction model might enable more accurate and nuanced risk stratification, increasing applicability across a wider range of contexts.
Towards a greater engagement of universities in addressing climate change challenges
Authors: Leal Filho Walter , Weissenberger Sebastian , Luetz Johannes M. , Sierra Javier , Simon Rampasso Izabela , Sharifi Ayyoob , Anholon Rosley , Eustachio Joao Henrique Paulinho Pires , Kovaleva Marina 
Published: November 2023

AbstractMany higher education institutions around the world are engaged in efforts to tackle climate change. This takes place by not only reducing their own carbon footprint but also by educating future leaders and contributing valuable research and expertise to the global effort to combat climate change. However, there is a need for studies that identify the nature of their engagement on the topic, and the extent to which they are contributing towards addressing the many problems associated with climate change. Against this background, this paper describes a study that consisted of a review of the literature and the use of case studies, which outline the importance of university engagement in climate change and describe its main features. The study identified the fact that even though climate change is a matter of great relevance to universities, its coverage in university programmes is not as wide as one could expect. Based on the findings, the paper also lists the challenges associated with the inclusion of climate change in university programmes. Finally, it describes some of the measures which may be deployed in order to maximise the contribution of higher education towards handling the challenges associated with a changing climate.
Structure–activity studies of Streptococcus pyogenes enzyme SpyCEP reveal high affinity for CXCL8 in the SpyCEP C-terminal
Authors: Pearson Max , Haslam Carl , Fosberry Andrew , Jones Emma J. , Reglinski Mark , Reeves Lucy , Edwards Robert J. , Lawrenson Richard Ashley , Brown Jonathan C. , Mossakowska Danuta , Pease James Edward , Sriskandan Shiranee 
Published: November 2023

AbstractThe Streptococcus pyogenes cell envelope protease (SpyCEP) is vital to streptococcal pathogenesis and disease progression. Despite its strong association with invasive disease, little is known about enzymatic function beyond the ELR+ CXC chemokine substrate range. As a serine protease, SpyCEP has a catalytic triad consisting of aspartate (D151), histidine (H279), and serine (S617) residues which are all thought to be mandatory for full activity. We utilised a range of SpyCEP constructs to investigate the protein domains and catalytic residues necessary for enzyme function. We designed a high-throughput mass spectrometry assay to measure CXCL8 cleavage and applied this for the first time to study the enzyme kinetics of SpyCEP. Results revealed a remarkably low Michaelis-Menton constant (KM) of 82 nM and a turnover of 1.65 molecules per second. We found that an N-terminally-truncated SpyCEP C-terminal construct containing just the catalytic dyad of H279 and S617 was capable of cleaving CXCL8 with a similar KM of 55 nM, albeit with a reduced substrate turnover of 2.7 molecules per hour, representing a 2200-fold reduction in activity. We conclude that the SpyCEP C-terminus plays a key role in high affinity substrate recognition and binding, but that the N-terminus is required for full catalytic activity.
Network diffusion model reveals recovery multipliers and heterogeneous spatial effects in post-disaster community recovery
Authors: Liu Chia-Fu , Mostafavi Ali 
Published: November 2023

AbstractCommunity recovery from hazards occurs through various diffusion processes within social and spatial networks of communities. Existing knowledge regarding the diffusion of recovery in community socio-spatial networks, however, is rather limited. To bridge this gap, we created a network diffusion model to characterize the unfolding of population activity recovery in spatial networks of communities. In particular, this study aims to answer the research question “To what extent can the diffusion model capture the spatial patterns of recovery?” Using population activity recovery data derived from location-based information associated with 2017 Hurricane Harvey in the Houston area, we parameterized the threshold-based network diffusion model using the genetic algorithm and then simulated the recovery diffusion process. The results show that the spatial effects of recovery are rather heterogeneous across different areas; some spatial areas demonstrate a greater spatial effect in their recovery. Also, the results show that low-income and minority areas are community recovery multipliers; with faster recovery in these areas corresponding to accelerated recovery for the entire community. Hence, prioritizing these areas in resource allocation during recovery has the potential to accelerate could expedite the recovery of the entire community’s recovery process while promoting recovery equality and equity.
Impacts of morphology parameters on the risk of rupture in intracranial aneurysms: statistical and computational analyses
Authors: Wang Yujing , Jin Jing , Chen Jie , Chen Peng , Abdollahi Seyyed Amirreza 
Published: November 2023

AbstractThe hemodynamic analysis of the blood stream inside the cerebral aneurysms reveals the risk of the aneurysm rupture. In addition, the high risk region prone to rupture would be determined by the hemodynamic analysis of the blood. In present article, computational fluid dynamic is used for the investigation of the hemodynamic effects on the aneurysm wall and risk of rupture. This study tries to find the connection between the risk of rupture with three geometrical features of aneurysm i.e., Ellipsoid Max semi-axis, Size ratio and Tortuosity. Statistical analysis is done over 30 different ruptured /unruptured ICA aneurysms to find meaningful relation between selected geometrical factors and rupture risk. The hemodynamic analysis is done over four distinct aneurysm models to attain more details on effects of chosen geometrical factors. The results of simulations indicate that the Ellipsoid Max semi-axis have meaningful impacts on the risk of rupture.