bluuebunny/crossref_metadata_2025_split huggingface dataset:
SARS-CoV-2 spike-ferritin-nanoparticle adjuvanted with ALFQ induces long-lived plasma cells and cross-neutralizing antibodies
Authors: Shrivastava Shikha , Carmen Joshua M. , Lu Zhongyan , Basu Shraddha , Sankhala Rajeshwer S. , Chen Wei-Hung , Nguyen Phuong , Chang William C. , King Jocelyn , Corbitt Courtney , Mayer Sandra , Bolton Jessica S. , Anderson Alexander , Swafford Isabella , Terriquez Guillermo D. , Trinh Hung V. , Kim Jiae , Jobe Ousman , Paquin-Proulx Dominic , Matyas Gary, R. , Gromowski Gregory D. , Currier Jeffrey R. , Bergmann-Leitner Elke , Modjarrad Kayvon , Michael Nelson L. , Joyce M. Gordon , Malloy Allison M. W. , Rao Mangala 
Published: March 2023

AbstractThis study demonstrates the impact of adjuvant on the development of T follicular helper (Tfh) and B cells, and their influence on antibody responses in mice vaccinated with SARS-CoV-2-spike-ferritin-nanoparticle (SpFN) adjuvanted with either Army Liposome Formulation containing QS-21 (SpFN + ALFQ) or Alhydrogel®(SpFN + AH). SpFN + ALFQ increased the size and frequency of germinal center (GC) B cells in the vaccine-draining lymph nodes and increased the frequency of antigen-specific naive B cells. A single vaccination with SpFN + ALFQ resulted in a higher frequency of IL-21-producing-spike-specific Tfh and GC B cells in the draining lymph nodes and spleen, S-2P protein-specific IgM and IgG antibodies, and elicitation of robust cross-neutralizing antibodies against SARS-CoV-2 variants as early as day 7, which was enhanced by a second vaccination. This was associated with the generation of high titer, high avidity binding antibodies. The third vaccination with SpFN + ALFQ elicited high levels of neutralizing antibodies against the Omicron variant. No cross-neutralizing antibodies against Omicron were induced with SpFN + AH. These findings highlight the importance of ALFQ in orchestrating early induction of antigen-specific Tfh and GC B cell responses and long-lived plasma cells in the bone marrow. The early engagement of S-2P specific naive B cells and high titer IgM antibodies shape the development of long-term neutralization breadth.
Optimal design of water reuse networks in cities through decision support tool development and testing
Authors: Calle Eusebi , Martínez David , Buttiglieri Gianluigi , Corominas Lluís , Farreras Miquel , Saló-Grau Joan , Vilà Pere , Pueyo-Ros Josep , Comas Joaquim 
Published: March 2023

AbstractWater scarcity and droughts are an increasing issue in many parts of the world. In the context of urban water systems, the transition to circularity may imply wastewater treatment and reuse. Planning and assessment of water reuse projects require decision-makers evaluating the cost and benefits of alternative scenarios. Manual or semi-automatic approaches are still common practice for planning both drinking and reclaimed water distribution networks. This work illustrates a decision support tool that, based on open data sources and graph theory coupled to greedy optimization algorithms, is able to automatically compute the optimal reclaimed water network for a given scenario. The tool provides not only the maximum amount of served reclaimed water per unit of invested cost, but also the length and diameters of the pipes required, the location and size of storage tanks, the population served, and the construction costs, i.e., everything under the same architecture. The usefulness of the tool is illustrated in two different but complementary cities in terms of size, density, and topography. The construction cost of the optimal water reclaimed network for a city of approximately 100,000 inhabitants is estimated to be in the range of €0.17–0.22/m3 (for a payback period of 30 years).
Control of dynamic sp3-C stereochemistry
Authors: Bismillah Aisha N. , Johnson Toby G. , Hussein Burhan A. , Turley Andrew T. , Saha Promeet K. , Wong Ho Chi , Aguilar Juan A. , Yufit Dmitry S. , McGonigal Paul R. 
Published: March 2023

AbstractStereogenic sp3-hybridized carbon centres are fundamental building blocks of chiral molecules. Unlike dynamic stereogenic motifs, such as sp3-nitrogen centres or atropisomeric biaryls, sp3-carbon centres are usually fixed, requiring intermolecular reactions to undergo configurational changes. Here we report the internal enantiomerization of fluxional carbon cages and the consequences of their adaptive configurations for the transmission of stereochemical information. The sp3-carbon stereochemistry of the rigid tricyclic cages is inverted through strain-assisted Cope rearrangements, emulating the low-barrier configurational dynamics typical for sp3-nitrogen inversion or conformational isomerism. This dynamic enantiomerization can be stopped, restarted or slowed by external reagents, while the configuration of the cage is controlled by neighbouring, fixed stereogenic centres. As part of a phosphoramidite–olefin ligand, the fluxional cage acts as a conduit to transmit stereochemical information from the ligand while also transferring its dynamic properties to chiral-at-metal coordination environments, influencing catalysis, ion pairing and ligand exchange energetics.
Recent intensification of wetland methane feedback
Authors: Zhang Zhen , Poulter Benjamin , Feldman Andrew F. , Ying Qing , Ciais Philippe , Peng Shushi , Li Xin 
Published: March 2023

AbstractThe positive response of wetland methane (CH4) emissions to climate change is an important yet uncertain Earth-system feedback that amplifies atmospheric CH4 concentrations. Here, using a wetland model, we report intensified wetland CH4 emissions during 2000–2021, corresponding with 2020 and 2021 being exceptional years of growth. Our results highlight the need for sustained monitoring and observations of global wetland CH4 fluxes to document emerging trends, variability and underlying drivers.
Mechanosensitive extrusion of Enterovirus A71-infected cells from colonic organoids
Authors: Moshiri Jasmine , Craven Ailsa R. , Mixon Sara B. , Amieva Manuel R. , Kirkegaard Karla 
Published: March 2023

AbstractEnterovirus A71 causes severe disease upon systemic infection, sometimes leading to life-threatening neurological dysfunction. However, in most cases infection is asymptomatic and limited to the gastrointestinal tract, where virus is amplified for transmission. Picornaviruses have previously been shown to exit infected cells via either cell lysis or secretion of vesicles. Here we report that entire Enterovirus A71-infected cells are specifically extruded from the apical surface of differentiated human colon organoids, as observed by confocal microscopy. Differential sensitivity to chemical and peptide inhibitors demonstrated that extrusion of virus-infected cells is dependent on force sensing via mechanosensitive ion channels rather than apoptotic cell death. When isolated and used as inoculum, intact virus-containing extruded cells can initiate new infections. In contrast, when mechanical force sensing is inhibited, large amounts of free virus are released. Thus, extrusion of live, virus-infected cells from intact epithelial tissue is likely to benefit both the integrity of host tissues and the protected spread of this faecal–oral pathogen within and between hosts.
Breaking the temporal and frequency congestion of LiDAR by parallel chaos
Authors: Chen Ruixuan , Shu Haowen , Shen Bitao , Chang Lin , Xie Weiqiang , Liao Wenchao , Tao Zihan , Bowers John E. , Wang Xingjun 
Published: March 2023

AbstractThe rising demand for high scanning accuracy and resolution in sensors for self-driving vehicles has led to the rapid development of parallelization in light detection and ranging (LiDAR) technologies. However, for the two major existing LiDAR categories—time-of-flight and frequency-modulated continuous wave—the light sources and measurement principles currently used for parallel detection face severe limitations from time- and frequency-domain congestion, leading to degraded measurement performance and increased system complexity. In this work we introduce a light source—the chaotic microcomb—to overcome this problem. This physical entropy light source exhibits naturally orthogonalized light channels that are immune to any congestion problem. Based on this microcomb state, we demonstrate a new type of LiDAR—parallel chaotic LiDAR—that is interference-free and has a greatly simplified system architecture. Our approach also enables the state-of-the-art ranging performance among parallel LiDARs: millimetre-level ranging accuracy and millimetre-per-second-level velocity resolution. Combining all of these desirable properties, this technology has the potential to reshape the entire LiDAR ecosystem.
Ultracold Feshbach molecules in an orbital optical lattice
Authors: Kiefer Yann , Hachmann Max , Hemmerich Andreas 
Published: March 2023

AbstractQuantum gas systems provide a unique experimental platform to study the crossover between Bose–Einstein condensed molecular pairs and Bardeen–Cooper–Schrieffer superfluidity. The few studies in optical lattices have so far focused on the case when only the lowest Bloch band is populated, thus excluding orbital degrees of freedom. Here we demonstrate the preparation of ultracold Feshbach molecules of fermionic atoms in the second Bloch band of an optical square lattice. We cover a wide range of interaction strengths, including the regime of unitarity in the middle of the crossover. Binding energies and band relaxation dynamics are measured by means of a method resembling mass spectrometry. We find that the longest lifetimes arise for strongly interacting Feshbach molecules at the onset of unitarity. In the case of strong confinement in a deep lattice potential, we observe bound dimers also for negative values of the scattering length, extending previous findings for molecules in the lowest band.
Protein structure prediction with in-cell photo-crosslinking mass spectrometry and deep learning
Authors: Stahl Kolja , Graziadei Andrea , Dau Therese , Brock Oliver , Rappsilber Juri 
Published: March 2023

AbstractWhile AlphaFold2 can predict accurate protein structures from the primary sequence, challenges remain for proteins that undergo conformational changes or for which few homologous sequences are known. Here we introduce AlphaLink, a modified version of the AlphaFold2 algorithm that incorporates experimental distance restraint information into its network architecture. By employing sparse experimental contacts as anchor points, AlphaLink improves on the performance of AlphaFold2 in predicting challenging targets. We confirm this experimentally by using the noncanonical amino acid photo-leucine to obtain information on residue–residue contacts inside cells by crosslinking mass spectrometry. The program can predict distinct conformations of proteins on the basis of the distance restraints provided, demonstrating the value of experimental data in driving protein structure prediction. The noise-tolerant framework for integrating data in protein structure prediction presented here opens a path to accurate characterization of protein structures from in-cell data.
Deep thermal profiling for detection of functional proteoform groups
Authors: Kurzawa Nils , Leo Isabelle Rose , Stahl Matthias , Kunold Elena , Becher Isabelle , Audrey Anastasia , Mermelekas Georgios , Huber Wolfgang , Mateus André , Savitski Mikhail M. , Jafari Rozbeh 
Published: March 2023

AbstractThe complexity of the functional proteome extends considerably beyond the coding genome, resulting in millions of proteoforms. Investigation of proteoforms and their functional roles is important to understand cellular physiology and its deregulation in diseases but challenging to perform systematically. Here we applied thermal proteome profiling with deep peptide coverage to detect functional proteoform groups in acute lymphoblastic leukemia cell lines with different cytogenetic aberrations. We detected 15,846 proteoforms, capturing differently spliced, cleaved and post-translationally modified proteins expressed from 9,290 genes. We identified differential co-aggregation of proteoform pairs and established links to disease biology. Moreover, we systematically made use of measured biophysical proteoform states to find specific biomarkers of drug sensitivity. Our approach, thus, provides a powerful and unique tool for systematic detection and functional annotation of proteoform groups.
Multiomic signatures of body mass index identify heterogeneous health phenotypes and responses to a lifestyle intervention
Authors: Watanabe Kengo , Wilmanski Tomasz , Diener Christian , Earls John C. , Zimmer Anat , Lincoln Briana , Hadlock Jennifer J. , Lovejoy Jennifer C. , Gibbons Sean M. , Magis Andrew T. , Hood Leroy , Price Nathan D. , Rappaport Noa 
Published: March 2023

AbstractMultiomic profiling can reveal population heterogeneity for both health and disease states. Obesity drives a myriad of metabolic perturbations and is a risk factor for multiple chronic diseases. Here we report an atlas of cross-sectional and longitudinal changes in 1,111 blood analytes associated with variation in body mass index (BMI), as well as multiomic associations with host polygenic risk scores and gut microbiome composition, from a cohort of 1,277 individuals enrolled in a wellness program (Arivale). Machine learning model predictions of BMI from blood multiomics captured heterogeneous phenotypic states of host metabolism and gut microbiome composition better than BMI, which was also validated in an external cohort (TwinsUK). Moreover, longitudinal analyses identified variable BMI trajectories for different omics measures in response to a healthy lifestyle intervention; metabolomics-inferred BMI decreased to a greater extent than actual BMI, whereas proteomics-inferred BMI exhibited greater resistance to change. Our analyses further identified blood analyte–analyte associations that were modified by metabolomics-inferred BMI and partially reversed in individuals with metabolic obesity during the intervention. Taken together, our findings provide a blood atlas of the molecular perturbations associated with changes in obesity status, serving as a resource to quantify metabolic health for predictive and preventive medicine.
Validated names for experimental studies on race and ethnicity
Authors: Crabtree Charles , Kim Jae Yeon , Gaddis S. Michael , Holbein John B. , Guage Cameron , Marx William W. 
Published: March 2023

AbstractA large and fast-growing number of studies across the social sciences use experiments to better understand the role of race in human interactions, particularly in the American context. Researchers often use names to signal the race of individuals portrayed in these experiments. However, those names might also signal other attributes, such as socioeconomic status (e.g., education and income) and citizenship. If they do, researchers would benefit greatly from pre-tested names with data on perceptions of these attributes; such data would permit researchers to draw correct inferences about the causal effect of race in their experiments. In this paper, we provide the largest dataset of validated name perceptions to date based on three different surveys conducted in the United States. In total, our data include over 44,170 name evaluations from 4,026 respondents for 600 names. In addition to respondent perceptions of race, income, education, and citizenship from names, our data also include respondent characteristics. Our data will be broadly helpful for researchers conducting experiments on the manifold ways in which race shapes American life.
A kinematic, imaging and electromyography dataset for human muscular manipulability index prediction
Authors: Hernández Óscar G. , Lopez-Castellanos Jose M. , Jara Carlos A. , Garcia Gabriel J. , Ubeda Andres , Morell-Gimenez Vicente , Gomez-Donoso Francisco 
Published: March 2023

AbstractHuman Muscular Manipulability is a metric that measures the comfort of an specific pose and it can be used for a variety of applications related to healthcare. For this reason, we introduce KIMHu: a Kinematic, Imaging and electroMyography dataset for Human muscular manipulability index prediction. The dataset is comprised of images, depth maps, skeleton tracking data, electromyography recordings and 3 different Human Muscular Manipulability indexes of 20 participants performing different physical exercises with their arm. The methodology followed to acquire and process the data is also presented for future replication. A specific analysis framework for Human Muscular Manipulability is proposed in order to provide benchmarking tools based on this dataset.
A dataset for medical instructional video classification and question answering
Authors: Gupta Deepak , Attal Kush , Demner-Fushman Dina 
Published: March 2023

AbstractThis paper introduces a new challenge and datasets to foster research toward designing systems that can understand medical videos and provide visual answers to natural language questions. We believe medical videos may provide the best possible answers to many first aid, medical emergency, and medical education questions. Toward this, we created the and datasets and introduce the tasks of Medical Video Classification (MVC) and Medical Visual Answer Localization (MVAL), two tasks that focus on cross-modal (medical language and medical video) understanding. The proposed tasks and datasets have the potential to support the development of sophisticated downstream applications that can benefit the public and medical practitioners. Our datasets consist of 6,117 fine-grained annotated videos for the MVC task and 3,010 questions and answers timestamps from 899 videos for the MVAL task. These datasets have been verified and corrected by medical informatics experts. We have also benchmarked each task with the created and datasets and propose the multimodal learning methods that set competitive baselines for future research.
EUBUCCO v0.1: European building stock characteristics in a common and open database for 200+ million individual buildings
Authors: Milojevic-Dupont Nikola , Wagner Felix , Nachtigall Florian , Hu Jiawei , Brüser Geza Boi , Zumwald Marius , Biljecki Filip , Heeren Niko , Kaack Lynn H. , Pichler Peter-Paul , Creutzig Felix 
Published: March 2023

AbstractBuilding stock management is becoming a global societal and political issue, inter alia because of growing sustainability concerns. Comprehensive and openly accessible building stock data can enable impactful research exploring the most effective policy options. In Europe, efforts from citizen and governments generated numerous relevant datasets but these are fragmented and heterogeneous, thus hindering their usability. Here, we present eubucco v0.1, a database of individual building footprints for ~202 million buildings across the 27 European Union countries and Switzerland. Three main attributes – building height, construction year and type – are included for respectively 73%, 24% and 46% of the buildings. We identify, collect and harmonize 50 open government datasets and OpenStreetMap, and perform extensive validation analyses to assess the quality, consistency and completeness of the data in every country. eubucco v0.1 provides the basis for high-resolution urban sustainability studies across scales – continental, comparative or local studies – using a centralized source and is relevant for a variety of use cases, e.g., for energy system analysis or natural hazard risk assessments.
Survey data on preferences and attitudes towards participatory irrigation management in India and Pakistan
Authors: Cooper Bethany , Crase Lin , Burton Michael , Pham Hung Duy 
Published: March 2023

AbstractThe data described in this paper were collected from four jurisdictions in south Asia, Assam and Bihar in India and Punjab and Sindh in Pakistan. The data were collected from farmer households involved in surface water irrigation with the aim of understanding the merits of participatory irrigation management (PIM) in different settings in south Asia. The data were collected using four structured survey instruments, which comprised three paper-based surveys and one online survey collected via tablets. This data can be used by researchers to empirically analyze: overall institutional performance and its relationship to agro-economic variables; drivers of compliance; gender differences and their impact on participation in water groups and perceptions of performance; preferred charging regimes and broader institutional arrangements for managing water at the local level. These data are unique, having been collected simultaneously across the four jurisdictions.
Chinese industrial air pollution emissions based on the continuous emission monitoring systems network
Authors: Tang Ling , Jia Min , Yang Junai , Li Ling , Bo Xin , Mi Zhifu 
Published: March 2023

AbstractAs the world’s largest industrial producer, China has generated large amount of industrial atmospheric pollution, particularly for particulate matter (PM), SO2 and NOx emissions. A nationwide, time-varying, and up-to-date air pollutant emission inventory by industrial sources has great significance to understanding industrial emission characteristics. Here, we present a nationwide database of industrial emissions named Chinese Industrial Emissions Database (CIED), using the real smokestack concentrations from China’s continuous emission monitoring systems (CEMS) network during 2015–2018 to enhance the estimation accuracy. This hourly, source-level CEMS data enables us to directly estimate industrial emission factors and absolute emissions, avoiding the use of many assumptions and indirect parameters that are common in existing research. The uncertainty analysis of CIED database shows that the uncertainty ranges are quite small, within ±7.2% for emission factors and ±4.0% for emissions, indicating the reliability of our estimates. This dataset provides specific information on smokestack concentrations, emissions factors, activity data and absolute emissions for China’s industrial emission sources, which can offer insights into associated scientific studies and future policymaking.
An intracochlear electrocochleography dataset - from raw data to objective analysis using deep learning
Authors: Schuerch Klaus , Wimmer Wilhelm , Dalbert Adrian , Rummel Christian , Caversaccio Marco , Mantokoudis Georgios , Gawliczek Tom , Weder Stefan 
Published: March 2023

AbstractElectrocochleography (ECochG) measures electrophysiological inner ear potentials in response to acoustic stimulation. These potentials reflect the state of the inner ear and provide important information about its residual function. For cochlear implant (CI) recipients, we can measure ECochG signals directly within the cochlea using the implant electrode. We are able to perform these recordings during and at any point after implantation. However, the analysis and interpretation of ECochG signals are not trivial. To assist the scientific community, we provide our intracochlear ECochG data set, which consists of 4,924 signals recorded from 46 ears with a cochlear implant. We collected data either immediately after electrode insertion or postoperatively in subjects with residual acoustic hearing. This data descriptor aims to provide the research community access to our comprehensive electrophysiological data set and algorithms. It includes all steps from raw data acquisition to signal processing and objective analysis using Deep Learning. In addition, we collected subject demographic data, hearing thresholds, subjective loudness levels, impedance telemetry, radiographic findings, and classification of ECochG signals.