bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of Lepidapedon oregonense as the current world’s deepest trematode
Authors: Waki T. , Kumagai T. , Nishino Y. 
Published: May 2024

Abstract
The deepest recorded depth for trematodes currently stands at approximately 6200 m. This depth record was achieved solely through sequence datasets of Lepidapedon sp. obtained from a gastropod. Given that trematodes of this genus typically use fish as definitive hosts, the origin of the trematode sequence was thought to be larval stages. However, the specific species remained unclear owing to the absence of reported adult-stage sequences. In the present study, we definitively identified the deepest trematode as Lepidapedon oregonense by comparing 28S ribosomal DNA sequences from adult worms from the macrourid fish Coelorinchus gilberti with data from the gastropod in the previous study.
Improved GRACE‐FO Gravity Field Solution by Combining Different Accelerometer Transplant Products
Authors: Nie Yufeng , Shen Yunzhong , Chen Jianli , Chen Qiujie 
Published: May 2024

AbstractGravity field solutions determined from the Gravity Recovery and Climate Experiment Follow‐on (GRACE‐FO) are affected by the unexpected performance degradation of one accelerometer onboard, which is circumvented by the accelerometer data transplant (ACT) technique. Three operational ACT products are presently available: JPL‐ACT and JPL‐ACH from NASA Jet Propulsion Laboratory (JPL) and TUG‐ACT from Graz University of Technology (TUG). Considering the heterogeneous qualities of individual ACT products, we propose to combine them to improve the gravity field models after a comprehensive assessment of individual products using a consistent Level‐1B data processing. The combination is carried out on the normal equation of gravity field solutions. Spectral, temporal, and spatial evaluations over the period October 2018 to December 2022 demonstrate that the combined solution significantly reduces the noise relative to solutions using individual ACT products, and the average noise reduction rates over JPL‐ACT range from 5% to 12% with varying post‐processing filters and C20 and C30 coefficient treatments, which are double those of the second‐best JPL‐ACH. Moreover, the C20 estimate exhibits significant improvement in the combined solution with its deviation from the satellite laser ranging (SLR) solution showing a root mean square (RMS) value of 7.6 × 10−11, compared to similar RMS values of 15.9 × 10−11, 12.1 × 10−11, and 14.9 × 10−11 for JPL‐ACT, JPL‐ACH, and TUG‐ACT, respectively. This improvement helps greatly reduce the amplitude of the 161‐day spurious signal over polar regions. For C30, the JPL‐ACT gives degraded estimates with an RMS of differences to SLR of 6.2 × 10−11, while the differences are greatly reduced to 2.6 × 10−11, 2.7 × 10−11 and 3.6 × 10−11 for the combined solution, JPL‐ACH and TUG‐ACT, respectively, approaching the formal error of SLR estimates.
Parameterization of Secondary Ionization Rates and Photoelectron Heating Rates of Venus and Mars
Authors: Liu Zerui , Lei Jiuhou , Yan Maodong , Cao Yu‐tian , Dang Tong , Cui Jun , Zhang Binzheng 
Published: May 2024

AbstractAs a fundamental physical process in the ionosphere, photoionization and the associated photoelectrons play vital roles in determining the ionospheric electron density and temperature for Earth and other planets with atmospheres such as Mars and Venus. The production and transport of ionospheric photoelectrons have been widely examined on Earth, but relatively less studied for other terrestrial planets, such as Mars and Venus. In this study, a two‐stream photoelectron transport model for Mars and Venus is constructed, in which the photoelectron fluxes, photoelectron heating rates, primary and secondary ionization rates are calculated. The simulated photoelectron fluxes agree with Mars Atmosphere and Volatile Evolution (MAVEN) observations at various altitudes, with the input of solar spectrum irradiance, electron density and temperature, neutral density and temperature observed by MAVEN. Moreover, by parametrically fitting the simulation results for various solar zenith angles and solar activities, we obtain empirical parameterized formulas for ionization and heating efficiencies which can potentially be adapted to planetary ionospheric models for the community.
Inter‐Hemispheric Energy Input Into the Ionosphere‐Thermosphere System During Magnetic Storms: What We Can and Cannot Learn From DMSP Observations
Authors: Oliveira Denny M. , Zesta Eftyhia 
Published: May 2024

AbstractWe present a long‐term superposed epoch analysis and statistical study with 427 magnetic storms caused by coronal mass ejections and the subsequent magnetospheric energy input into the ionosphere‐thermosphere system. Electron and ion precipitating energy flux data along with plasma drift velocity and magnetic field data (used for Earth‐bound Poynting flux computations) are used in this study. By carefully exploring conjugated inter‐hemispheric energy inputs as a function of storm intensity and seasons, we find that near two‐decades of Defense Meteorological Satellite Program observations indicate that the northern hemisphere (NH) receives slightly more energy than the southern hemisphere (SH) (Poynting flux and integrated electron/ion precipitating energy flux), with the NH receiving more energy as the storm becomes more intense. However, for the Poynting flux case, we find that generally the SH receives more energy when the east‐west component of the interplanetary magnetic field (IMF) becomes highly positive (By ≥ +5 nT), whereas this pattern reverses for cases when IMF By is highly negative (By ≤ −5 nT). The inter‐hemispheric interpretation for electron and ion precipitation energy inputs is ambiguous due to a severe lack of conjugated observations around the midnight sector for both hemispheres.
Targeting tumor suppressor p53 for organ fibrosis therapy
Authors: Bao Yi-Ni , Yang Qiao , Shen Xin-Lei , Yu Wen-Kai , Zhou Li , Zhu Qing-Ru , Shan Qi-Yuan , Wang Zhi-Chao , Cao Gang 
Published: May 2024

AbstractFibrosis is a reparative and progressive process characterized by abnormal extracellular matrix deposition, contributing to organ dysfunction in chronic diseases. The tumor suppressor p53 (p53), known for its regulatory roles in cell proliferation, apoptosis, aging, and metabolism across diverse tissues, appears to play a pivotal role in aggravating biological processes such as epithelial-mesenchymal transition (EMT), cell apoptosis, and cell senescence. These processes are closely intertwined with the pathogenesis of fibrotic disease. In this review, we briefly introduce the background and specific mechanism of p53, investigate the pathogenesis of fibrosis, and further discuss p53’s relationship and role in fibrosis affecting the kidney, liver, lung, and heart. In summary, targeting p53 represents a promising and innovative therapeutic approach for the prevention and treatment of organ fibrosis.
Automatic detection of methane emissions in multispectral satellite imagery using a vision transformer
Authors: Rouet-Leduc Bertrand , Hulbert Claudia 
Published: May 2024

AbstractCurbing methane emissions is among the most effective actions that can be taken to slow down global warming. However, monitoring emissions remains challenging, as detection methods have a limited quantification completeness due to trade-offs that have to be made between coverage, resolution, and detection accuracy. Here we show that deep learning can overcome the trade-off in terms of spectral resolution that comes with multi-spectral satellite data, resulting in a methane detection tool with global coverage and high temporal and spatial resolution. We compare our detections with airborne methane measurement campaigns, which suggests that our method can detect methane point sources in Sentinel-2 data down to plumes of 0.01 km2, corresponding to 200 to 300 kg CH4 h−1 sources. Our model shows an order of magnitude improvement over the state-of-the-art, providing a significant step towards the automated, high resolution detection of methane emissions at a global scale, every few days.
Functional and antigenic characterization of SARS-CoV-2 spike fusion peptide by deep mutational scanning
Authors: Lei Ruipeng , Qing Enya , Odle Abby , Yuan Meng , Gunawardene Chaminda D. , Tan Timothy J. C. , So Natalie , Ouyang Wenhao O. , Wilson Ian A. , Gallagher Tom , Perlman Stanley , Wu Nicholas C. , Wong Lok-Yin Roy 
Published: May 2024

AbstractThe fusion peptide of SARS-CoV-2 spike protein is functionally important for membrane fusion during virus entry and is part of a broadly neutralizing epitope. However, sequence determinants at the fusion peptide and its adjacent regions for pathogenicity and antigenicity remain elusive. In this study, we perform a series of deep mutational scanning (DMS) experiments on an S2 region spanning the fusion peptide of authentic SARS-CoV-2 in different cell lines and in the presence of broadly neutralizing antibodies. We identify mutations at residue 813 of the spike protein that reduced TMPRSS2-mediated entry with decreased virulence. In addition, we show that an F823Y mutation, present in bat betacoronavirus HKU9 spike protein, confers resistance to broadly neutralizing antibodies. Our findings provide mechanistic insights into SARS-CoV-2 pathogenicity and also highlight a potential challenge in developing broadly protective S2-based coronavirus vaccines.
Alpha-glucans from bacterial necromass indicate an intra-population loop within the marine carbon cycle
Authors: Beidler Irena , Steinke Nicola , Schulze Tim , Sidhu Chandni , Bartosik Daniel , Zühlke Marie-Katherin , Martin Laura Torres , Krull Joris , Dutschei Theresa , Ferrero-Bordera Borja , Rielicke Julia , Kale Vaikhari , Sura Thomas , Trautwein-Schult Anke , Kirstein Inga V. , Wiltshire Karen H. , Teeling Hanno , Becher Dörte , Bengtsson Mia Maria , Hehemann Jan-Hendrik , Bornscheuer Uwe. T. , Amann Rudolf I. , Schweder Thomas 
Published: May 2024

AbstractPhytoplankton blooms provoke bacterioplankton blooms, from which bacterial biomass (necromass) is released via increased zooplankton grazing and viral lysis. While bacterial consumption of algal biomass during blooms is well-studied, little is known about the concurrent recycling of these substantial amounts of bacterial necromass. We demonstrate that bacterial biomass, such as bacterial alpha-glucan storage polysaccharides, generated from the consumption of algal organic matter, is reused and thus itself a major bacterial carbon source in vitro and during a diatom-dominated bloom. We highlight conserved enzymes and binding proteins of dominant bloom-responder clades that are presumably involved in the recycling of bacterial alpha-glucan by members of the bacterial community. We furthermore demonstrate that the corresponding protein machineries can be specifically induced by extracted alpha-glucan-rich bacterial polysaccharide extracts. This recycling of bacterial necromass likely constitutes a large-scale intra-population energy conservation mechanism that keeps substantial amounts of carbon in a dedicated part of the microbial loop.
Financial markets value skillful forecasts of seasonal climate
Authors: Lemoine Derek , Kapnick Sarah 
Published: May 2024

AbstractScientific agencies spend substantial sums producing and improving forecasts of seasonal climate, but they do so without much information about these forecasts’ value in practice. Here we show that financial market participants value the production of seasonal forecasts: options traders price the uncertainty generated by upcoming United States National Oceanic and Atmospheric Administration Winter and El Niño Outlooks. Each outlook affects firms throughout the economy, with total market capitalization of $6 and $13 trillion, respectively. A 1% improvement in the skill of the El Niño Outlook reduces firms’ exposure to a one standard deviation shock by $18 billion and induces traders to spend an additional $2 million hedging the outlook’s news. Firms must not be able to undertake ex-ante adaptation that would eliminate their exposure to the forecasted portion of seasonal climate without imposing substantial costs of its own.
Analysis of nearly 3000 archaeal genomes from terrestrial geothermal springs sheds light on interconnected biogeochemical processes
Authors: Qi Yan-Ling , Chen Ya-Ting , Xie Yuan-Guo , Li Yu-Xian , Rao Yang-Zhi , Li Meng-Meng , Xie Qi-Jun , Cao Xing-Ru , Chen Lei , Qu Yan-Ni , Yuan Zhen-Xuan , Xiao Zhi-Chao , Lu Lu , Jiao Jian-Yu , Shu Wen-Sheng , Li Wen-Jun , Hedlund Brian P. , Hua Zheng-Shuang 
Published: May 2024

AbstractTerrestrial geothermal springs are physicochemically diverse and host abundant populations of Archaea. However, the diversity, functionality, and geological influences of these Archaea are not well understood. Here we explore the genomic diversity of Archaea in 152 metagenomes from 48 geothermal springs in Tengchong, China, collected from 2016 to 2021. Our dataset is comprised of 2949 archaeal metagenome-assembled genomes spanning 12 phyla and 392 newly identified species, which increases the known species diversity of Archaea by ~48.6%. The structures and potential functions of the archaeal communities are strongly influenced by temperature and pH, with high-temperature acidic and alkaline springs favoring archaeal abundance over Bacteria. Genome-resolved metagenomics and metatranscriptomics provide insights into the potential ecological niches of these Archaea and their potential roles in carbon, sulfur, nitrogen, and hydrogen metabolism. Furthermore, our findings illustrate the interplay of competition and cooperation among Archaea in biogeochemical cycles, possibly arising from overlapping functional niches and metabolic handoffs. Taken together, our study expands the genomic diversity of Archaea inhabiting geothermal springs and provides a foundation for more incisive study of biogeochemical processes mediated by Archaea in geothermal ecosystems.
GRouNdGAN: GRN-guided simulation of single-cell RNA-seq data using causal generative adversarial networks
Authors: Zinati Yazdan , Takiddeen Abdulrahman , Emad Amin 
Published: May 2024

AbstractWe introduce GRouNdGAN, a gene regulatory network (GRN)-guided reference-based causal implicit generative model for simulating single-cell RNA-seq data, in silico perturbation experiments, and benchmarking GRN inference methods. Through the imposition of a user-defined GRN in its architecture, GRouNdGAN simulates steady-state and transient-state single-cell datasets where genes are causally expressed under the control of their regulating transcription factors (TFs). Training on six experimental reference datasets, we show that our model captures non-linear TF-gene dependencies and preserves gene identities, cell trajectories, pseudo-time ordering, and technical and biological noise, with no user manipulation and only implicit parameterization. GRouNdGAN can synthesize cells under new conditions to perform in silico TF knockout experiments. Benchmarking various GRN inference algorithms reveals that GRouNdGAN effectively bridges the existing gap between simulated and biological data benchmarks of GRN inference algorithms, providing gold standard ground truth GRNs and realistic cells corresponding to the biological system of interest.
Global mapping and evolution of persistent fronts in Large Marine Ecosystems over the past 40 years
Authors: Xing Qinwang , Yu Haiqing , Wang Hui 
Published: May 2024

AbstractOcean fronts, characterized by narrow zones with sharp changes in water properties, are vital hotspots for ecosystem services and key regulators of regional and global climates. Global change is reshaping the distribution of material and energy in the ocean; however, it remains unclear how fronts have varied in the last few decades. Here, we present a global, fine-scale digital atlas of persistent fronts around Large Marine Ecosystems and demonstrate significant global increases in both their occurrence and intensity. In subtropical regions (around boundary currents and upwelling systems) and polar regions, persistent frontal occurrence and intensity are rapidly increasing, while in tropical regions, they remain stable or slightly decrease. These enhancements may be respectively related to changes in boundary currents, upwelling, and sea ice retreat. This spatially heterogeneous trend holds important implications for the redistribution of front-related ecosystem services and air-sea interactions but has not been captured by representative high-resolution climate projections models or observation-assimilated ocean models.
Enhancing renewable energy certificate transactions through reinforcement learning and smart contracts integration
Authors: He Qingsu , Wang Jinsong , Shi Ruijie , He Yifan , Wu Muqing 
Published: May 2024

Abstract
Given the complexity of issuing, verifying, and trading green power certificates in China, along with the challenges posed by policy changes, ensuring that China’s green certificate market trading system receives proper mechanisms and technical support is crucial. This study presents a green power certificate trading (GC-TS) architecture based on an equilibrium strategy, which enhances the quoting efficiency and multi-party collaboration capability of green certificate trading by introducing Q-learning, smart contracts, and effectively integrating a multi-agent trading Nash strategy. Firstly, we integrate green certificate trading with electricity and carbon asset trading, constructing pricing strategies for the green certificate, carbon, and electricity trading markets; secondly, we design a certificate-electricity-carbon efficiency model based on ensuring the consistency of green certificates, green electricity, and carbon markets; then, to achieve diversified green certificate trading, we establish a multi-agent reinforcement learning game equilibrium model. Additionally, we propose an integrated Nash Q-learning offer with a smart contract dynamic trading joint clearing mechanism. Experiments show that trading prices have increased by 20%, and the transaction success rate by 30 times, with an analysis of trading performance from groups of 3, 5, 7, and 9 trading agents exhibiting high consistency and redundancy. Compared with models integrating smart contracts, it possesses a higher convergence efficiency of trading quotes.
Knowledge attitude and convenience on self-medication practices among university students in Bangladesh exploration using structural equation modeling approach
Authors: Tohan Mortuja Mahamud , Ahmed Faysal , Juie Israt Jahan , Kabir Anamul , Howlader Md. Hasan , Rahman Md. Ashfikur 
Published: May 2024

AbstractSelf-medication is a prevalent practice among university students globally and is a significant public health concern. However, previous research has been limited in scope, focusing primarily on adolescents or the general public, leaving a gap in understanding the causal relationships associated with self-medication; thus, this study aimed to investigate the factors influencing self-medication practices among university students in Bangladesh by developing a comprehensive causal model. Data from 417 students across five public universities were collected using the simple random walk technique by a team of 10 members. The study utilized constructs of knowledge, attitude, and convenience related to self-medication as independent variables, while self-medication practice as the dependent variable. One-way ANOVA and structural equation modeling (SEM) were employed to develop a causal model of self-medication practice among university students in Bangladesh. The findings revealed that students with better medication knowledge and adverse drug reactions (ADRs) were more likely to practice self-medication. A positive attitude towards self-medication and ADRs was also significantly associated with higher self-medication practice scores. Additionally, those who perceived self-medication as convenient and prescribed medication as inconvenient had higher self-medication practice scores. The attitude towards self-medication had the most substantial negative effect on self-medication practice, followed by the inconvenience of prescribed medication and the convenience of self-medication. The model explained 87% of the variance in self-medication practice, indicating a good fit for the data. University students in Bangladesh possess intermediate knowledge of medication and primary knowledge of ADRs. They exhibit a positive attitude towards self-medication and ADRs. Physical convenience favors self-medication, while the inconvenience of prescribed medication contributes to its lower preference. Policymakers should focus on evidence-based guidelines to reduce the extent of unnecessary self-medication practice and to enhance the quantity and accessibility of prescribed medications to address the issue effectively.
Melting temperature mapping method using imperfect-match linear long probes
Authors: Ootsuki Shinya , Niimi Hideki , Ueno Tomohiro , Mori Masashi , Tabata Homare , Minami Hiroshi , Kitajima Isao 
Published: May 2024

AbstractIdentifying pathogenic microorganisms as early as possible is critical for selecting the appropriate antimicrobial therapy in infected patients. We previously reported the development of the Tm mapping method for identifying a broad range of pathogenic bacteria within 3 h of blood collection. However, the Tm mapping identification requires an analytical instrument with a tube-to-tube variation of no more than 0.1 °C, so we can only use a few instruments that have such high thermal accuracy. To address the problem, we developed the improved Tm mapping method using imperfect-match linear long quenching probes (IMLL Q-probes). Using IMLL Q-probes, almost all commercially available analytical instruments can be used for the Tm mapping method. Some bacterial species cannot be narrowed down to one species, but they can at least be narrowed down to the genus level. The Tm mapping method using IMLL Q-probes is useful for deciding on antimicrobial therapy in infected patients.
Characteristics and management of municipal solid waste in Uyo, Akwa Ibom state, Nigeria
Authors: Bassey Uduak , Tom Abasi-ofon , Okono Udemeobong , John Mbetobong , Sinn Maja , Bassey Ayoge , Luke Uduak , Narra Satyanarayana 
Published: May 2024

AbstractIncreased urbanization and population lead to increased consumption of manufactured goods. This ultimately results in increased production of waste. Identifying its composition is crucial for planning an effective solid waste management strategy. This study assesses the characteristics and composition of the waste generated within the Uyo Capital City Development Area of Akwa Ibom State, Nigeria. This is to aid in developing a scientifically supported waste management pilot system for the state. Direct waste sorting and characterization were conducted on the municipal solid waste arriving at the landfill during the study period. Over 50% of the generated wastes are recyclables and composed of plastics, metals, and paper, while the fraction of organic waste is over 30%. Similarly, the waste generation per capita is 1.34 kg/person/day, while the generation forecast over the next ten years is estimated to increase by approximately 40%. Furthermore, over 9,000 surveys were completed by residents to establish a problem statement about the existing waste collection and disposal system, and possible solutions. Importantly, a majority of survey respondents were willing to source-separate their wastes and supported paying a fee for adequate waste collection. This strongly indicates that an integrated waste management system could be established to generate value from the collected waste. Supplementary revenue can be generated through composting, recycling, and land reclamation.