bluuebunny/crossref_metadata_2025_split huggingface dataset:
Population-based heteropolymer design to mimic protein mixtures
Authors: Ruan Zhiyuan , Li Shuni , Grigoropoulos Alexandra , Amiri Hossein , Hilburg Shayna L. , Chen Haotian , Jayapurna Ivan , Jiang Tao , Gu Zhaoyi , Alexander-Katz Alfredo , Bustamante Carlos , Huang Haiyan , Xu Ting 
Published: March 2023

AbstractBiological fluids, the most complex blends, have compositions that constantly vary and cannot be molecularly defined1. Despite these uncertainties, proteins fluctuate, fold, function and evolve as programmed2–4. We propose that in addition to the known monomeric sequence requirements, protein sequences encode multi-pair interactions at the segmental level to navigate random encounters5,6; synthetic heteropolymers capable of emulating such interactions can replicate how proteins behave in biological fluids individually and collectively. Here, we extracted the chemical characteristics and sequential arrangement along a protein chain at the segmental level from natural protein libraries and used the information to design heteropolymer ensembles as mixtures of disordered, partially folded and folded proteins. For each heteropolymer ensemble, the level of segmental similarity to that of natural proteins determines its ability to replicate many functions of biological fluids including assisting protein folding during translation, preserving the viability of fetal bovine serum without refrigeration, enhancing the thermal stability of proteins and behaving like synthetic cytosol under biologically relevant conditions. Molecular studies further translated protein sequence information at the segmental level into intermolecular interactions with a defined range, degree of diversity and temporal and spatial availability. This framework provides valuable guiding principles to synthetically realize protein properties, engineer bio/abiotic hybrid materials and, ultimately, realize matter-to-life transformations.
Structural basis for bacterial energy extraction from atmospheric hydrogen
Authors: Grinter Rhys , Kropp Ashleigh , Venugopal Hari , Senger Moritz , Badley Jack , Cabotaje Princess R. , Jia Ruyu , Duan Zehui , Huang Ping , Stripp Sven T. , Barlow Christopher K. , Belousoff Matthew , Shafaat Hannah S. , Cook Gregory M. , Schittenhelm Ralf B. , Vincent Kylie A. , Khalid Syma , Berggren Gustav , Greening Chris 
Published: March 2023

AbstractDiverse aerobic bacteria use atmospheric H2 as an energy source for growth and survival1. This globally significant process regulates the composition of the atmosphere, enhances soil biodiversity and drives primary production in extreme environments2,3. Atmospheric H2 oxidation is attributed to uncharacterized members of the [NiFe] hydrogenase superfamily4,5. However, it remains unresolved how these enzymes overcome the extraordinary catalytic challenge of oxidizing picomolar levels of H2 amid ambient levels of the catalytic poison O2 and how the derived electrons are transferred to the respiratory chain1. Here we determined the cryo-electron microscopy structure of the Mycobacterium smegmatis hydrogenase Huc and investigated its mechanism. Huc is a highly efficient oxygen-insensitive enzyme that couples oxidation of atmospheric H2 to the hydrogenation of the respiratory electron carrier menaquinone. Huc uses narrow hydrophobic gas channels to selectively bind atmospheric H2 at the expense of O2, and 3 [3Fe–4S] clusters modulate the properties of the enzyme so that atmospheric H2 oxidation is energetically feasible. The Huc catalytic subunits form an octameric 833 kDa complex around a membrane-associated stalk, which transports and reduces menaquinone 94 Å from the membrane. These findings provide a mechanistic basis for the biogeochemically and ecologically important process of atmospheric H2 oxidation, uncover a mode of energy coupling dependent on long-range quinone transport, and pave the way for the development of catalysts that oxidize H2 in ambient air.
Autoregulation of GPCR signalling through the third intracellular loop
Authors: Sadler Fredrik , Ma Ning , Ritt Michael , Sharma Yatharth , Vaidehi Nagarajan , Sivaramakrishnan Sivaraj 
Published: March 2023

AbstractThe third intracellular loop (ICL3) of the G protein-coupled receptor (GPCR) fold is important for the signal transduction process downstream of receptor activation1–3. Despite this, the lack of a defined structure of ICL3, combined with its high sequence divergence among GPCRs, complicates characterization of its involvement in receptor signalling4. Previous studies focusing on the β2 adrenergic receptor (β2AR) suggest that ICL3 is involved in the structural process of receptor activation and signalling5–7. Here we derive mechanistic insights into the role of ICL3 in β2AR signalling, observing that ICL3 autoregulates receptor activity through a dynamic conformational equilibrium between states that block or expose the receptor’s G protein-binding site. We demonstrate the importance of this equilibrium for receptor pharmacology, showing that G protein-mimetic effectors bias the exposed states of ICL3 to allosterically activate the receptor. Our findings additionally reveal that ICL3 tunes signalling specificity by inhibiting receptor coupling to G protein subtypes that weakly couple to the receptor. Despite the sequence diversity of ICL3, we demonstrate that this negative G protein-selection mechanism through ICL3 extends to GPCRs across the superfamily, expanding the range of known mechanisms by which receptors mediate G protein subtype selective signalling. Furthermore, our collective findings suggest ICL3 as an allosteric site for receptor- and signalling pathway-specific ligands.
The giant diploid faba genome unlocks variation in a global protein crop
Authors: Jayakodi Murukarthick , Golicz Agnieszka A. , Kreplak Jonathan , Fechete Lavinia I. , Angra Deepti , Bednář Petr , Bornhofen Elesandro , Zhang Hailin , Boussageon Raphaël , Kaur Sukhjiwan , Cheung Kwok , Čížková Jana , Gundlach Heidrun , Hallab Asis , Imbert Baptiste , Keeble-Gagnère Gabriel , Koblížková Andrea , Kobrlová Lucie , Krejčí Petra , Mouritzen Troels W. , Neumann Pavel , Nadzieja Marcin , Nielsen Linda Kærgaard , Novák Petr , Orabi Jihad , Padmarasu Sudharsan , Robertson-Shersby-Harvie Tom , Robledillo Laura Ávila , Schiemann Andrea , Tanskanen Jaakko , Törönen Petri , Warsame Ahmed O. , Wittenberg Alexander H. J. , Himmelbach Axel , Aubert Grégoire , Courty Pierre-Emmanuel , Doležel Jaroslav , Holm Liisa U. , Janss Luc L. , Khazaei Hamid , Macas Jiří , Mascher Martin , Smýkal Petr , Snowdon Rod J. , Stein Nils , Stoddard Frederick L. , Stougaard Jens , Tayeh Nadim , Torres Ana M. , Usadel Björn , Schubert Ingo , O’Sullivan Donal Martin , Schulman Alan H. , Andersen Stig Uggerhøj 
Published: March 2023

AbstractIncreasing the proportion of locally produced plant protein in currently meat-rich diets could substantially reduce greenhouse gas emissions and loss of biodiversity1. However, plant protein production is hampered by the lack of a cool-season legume equivalent to soybean in agronomic value2. Faba bean (Vicia fabaL.) has a high yield potential and is well suited for cultivation in temperate regions, but genomic resources are scarce. Here, we report a high-quality chromosome-scale assembly of the faba bean genome and show that it has expanded to a massive 13 Gb in size through an imbalance between the rates of amplification and elimination of retrotransposons and satellite repeats. Genes and recombination events are evenly dispersed across chromosomes and the gene space is remarkably compact considering the genome size, although with substantial copy number variation driven by tandem duplication. Demonstrating practical application of the genome sequence, we develop a targeted genotyping assay and use high-resolution genome-wide association analysis to dissect the genetic basis of seed size and hilum colour. The resources presented constitute a genomics-based breeding platform for faba bean, enabling breeders and geneticists to accelerate the improvement of sustainable protein production across the Mediterranean, subtropical and northern temperate agroecological zones.
Persistent impacts of smoking on resting-state EEG in male chronic smokers and past-smokers with 20 years of abstinence
Authors: Lee Hyeji , Jeon Yoonji , Yoo Cheolin , Seon HeeYoung , Park Jiwon , Hwang Minho , Baek Kwangyeol , Chung Dongil 
Published: March 2023

AbstractSmoking is a severe addictive health risk behavior and notorious for the high likelihood of relapse after attempted cessation. Such an addictive pattern in smoking has been associated with neurobiological changes in the brain. However, little is known whether the neural changes associated with chronic smoking persist after a long period of successful abstinence. To address this question, we examined resting state EEG (rsEEG) in chronic smokers who have been smoking for 20 years or more, past-smokers who have been successfully abstaining for 20 years or more, and never-smokers. Both current-smokers and past-smokers showed significantly decreased relative theta power than never-smokers, showcasing persistent effect of smoking on the brain. Other rsEEG features in alpha frequency band demonstrated distinctive patterns associated with active smoking, such that compared to never-smokers, only current-smokers, but not past-smokers, showed significantly higher relative power, EEG reactivity—power changes between eyes-closed and eyes-open conditions—, and coherence between channels. Furthermore, individual variabilities across these rsEEG biomarkers were accounted for by individuals’ self-reported smoking history and nicotine dependence in current- and past- smokers. These data suggest the persistent effect of smoking on the brain even after sustained remission for 20 years.
Inhibitory effect of 405 nm laser light on bacterial biofilm in urethral stent
Authors: Maknuna Luluil , Tran Van Nam , Lee Byeong-Il , Kang Hyun Wook 
Published: March 2023

AbstractThe clinical use of urethral stents is usually complicated by various adverse effects, including dysuria, fever, and urinary tract infection (UTI). Biofilms (formed by bacteria, such as Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus) adhering to the stent cause UTIs in stented patients (approximately 11%). The undesirable consequences of antibiotics use include bacterial resistance, weight gain, and type 1 diabetes, which occur when antibiotics are used for a long time. We aimed to assess the efficacy of a new optical treatment with a 405 nm laser to inhibit bacterial growth in a urethral stent in vitro. The urethral stent was grown in S. aureus broth media for three days to induce biofilm formation under dynamic conditions. Various irradiation times with the 405 nm laser light were tested (5, 10, and 15 min). The efficacy of the optical treatment on biofilms was evaluated quantitatively and qualitatively. The production of reactive oxygen species helped eliminate the biofilm over the urethral stent after 405 nm irradiation. The inhibition rate corresponded to a 2.2 log reduction of colony-forming units/mL of bacteria after 0.3 W/cm2 of irradiation for 10 min. The treated stent showed a significant reduction in biofilm formation compared with the untreated stent, as demonstrated by SYTO 9 and propidium iodide staining. MTT assays using the CCD-986sk cell line revealed no toxicity after 10 min of irradiation. We conclude that optical treatment with 405 nm laser light inhibits bacterial growth in urethral stents with no or minimal toxicity.
Metabolic reprogramming by Acly inhibition using SB-204990 alters glucoregulation and modulates molecular mechanisms associated with aging
Authors: Sola-García Alejandro , Cáliz-Molina María Ángeles , Espadas Isabel , Petr Michael , Panadero-Morón Concepción , González-Morán Daniel , Martín-Vázquez María Eugenia , Narbona-Pérez Álvaro Jesús , López-Noriega Livia , Martínez-Corrales Guillermo , López-Fernández-Sobrino Raúl , Castillo-Peña Alejandro , Carmona-Marin Lina M. , Martínez-Force Enrique , Yanes Oscar , Vinaixa Maria , López-López Daniel , Reyes José Carlos , Dopazo Joaquín , Martín Franz , Gauthier Benoit R. , Scheibye-Knudsen Morten , Capilla-González Vivian , Martín-Montalvo Alejandro 
Published: March 2023

Abstract
ATP-citrate lyase is a central integrator of cellular metabolism in the interface of protein, carbohydrate, and lipid metabolism. The physiological consequences as well as the molecular mechanisms orchestrating the response to long-term pharmacologically induced Acly inhibition are unknown. We report here that the Acly inhibitor SB-204990 improves metabolic health and physical strength in wild-type mice when fed with a high-fat diet, while in mice fed with healthy diet results in metabolic imbalance and moderated insulin resistance. By applying a multiomic approach using untargeted metabolomics, transcriptomics, and proteomics, we determined that, in vivo, SB-204990 plays a role in the regulation of molecular mechanisms associated with aging, such as energy metabolism, mitochondrial function, mTOR signaling, and folate cycle, while global alterations on histone acetylation are absent. Our findings indicate a mechanism for regulating molecular pathways of aging that prevents the development of metabolic abnormalities associated with unhealthy dieting. This strategy might be explored for devising therapeutic approaches to prevent metabolic diseases.
Ribonucleotide reductase subunit switching in hepatoblastoma drug response and relapse
Authors: Brown Anthony , Pan Qingfei , Fan Li , Indersie Emilie , Tian Cheng , Timchenko Nikolai , Li Liyuan , Hansen Baranda S. , Tan Haiyan , Lu Meifen , Peng Junmin , Pruett-Miller Shondra M. , Yu Jiyang , Cairo Stefano , Zhu Liqin 
Published: March 2023

AbstractPrognosis of children with high-risk hepatoblastoma (HB), the most common pediatric liver cancer, remains poor. In this study, we found ribonucleotide reductase (RNR) subunit M2 (RRM2) was one of the key genes supporting cell proliferation in high-risk HB. While standard chemotherapies could effectively suppress RRM2 in HB cells, they induced a significant upregulation of the other RNR M2 subunit, RRM2B. Computational analysis revealed distinct signaling networks RRM2 and RRM2B were involved in HB patient tumors, with RRM2 supporting cell proliferation and RRM2B participating heavily in stress response pathways. Indeed, RRM2B upregulation in chemotherapy-treated HB cells promoted cell survival and subsequent relapse, during which RRM2B was gradually replaced back by RRM2. Combining an RRM2 inhibitor with chemotherapy showed an effective delaying of HB tumor relapse in vivo. Overall, our study revealed the distinct roles of the two RNR M2 subunits and their dynamic switching during HB cell proliferation and stress response.
A graph‐based edge attention gate medical image segmentation method
Authors: Hao Dechen , Li Hualing 
Published: March 2023

AbstractFor the purpose of solving the problems of missing edges and low segmentation accuracy in medical image segmentation, a medical image segmentation network (EAGC_UNet++) based on residual graph convolution UNet++ with edge attention gate (EAG) is proposed in the study. With UNet++ as the backbone network, the idea of graph theory is introduced into the model. First, the dropout residual graph convolution block (DropRes_GCN Block) and the traditional convolution structure in UNet++ are used as encoders. Second, EAGs are adopted so that the model pays more attention to image edge features during decoding. Finally, aiming at the imbalance problem of positive and negative samples in medical image segmentation, a new weighted loss function is introduced to enhance segmentation accuracy. In the experimental part, three datasets (LiTS2017, ISIC2018, COVID‐19 CT scans) were used to evaluate the performances of various models; multiple groups of ablation experiments were designed to verify the effectiveness of each part of the model. The experimental results showed that EAGC_UNet++ had better segmentation performance than the other models under three quantitative evaluation indicators and better solved the problem of missing edges in medical image segmentation.
A novel variational Bayesian adaptive Kalman filter with mismatched process noise covariance matrix
Authors: Liu Xinrui , Xu Hong , Zheng Daikun , Quan Yinghui 
Published: March 2023

AbstractThis paper proposes a novel variational Bayesian (VB) adaptive Kalman filter with mismatched process noise covariance matrix (PNCM). Firstly, this paper explains the reason why the predicted error covariance matrix (PECM) is chosen for variational inference. Secondly, compared with the earlier VB adaptive Kalman filter (VB‐AKF‐Q), the proposed filter calculate the dynamic model of the PECM with its historical estimation information. Therefore, the proposed filter can overcome the influence of mismatched PNCM on the initial value setting of PECM in the VB‐AKF‐Q. Finally, we use the evidence lower bound for the proposed filter and give the convergence criterion on this basis. Some examples with a target tracking simulation are carried out to demonstrate the superiority of the proposed filter.
Neural posterior estimation for exoplanetary atmospheric retrieval
Authors: Vasist Malavika , Rozet François , Absil Olivier , Mollière Paul , Nasedkin Evert , Louppe Gilles 
Published: March 2023

Context. Retrieving the physical parameters from spectroscopic observations of exoplanets is key to understanding their atmospheric properties. Exoplanetary atmospheric retrievals are usually based on approximate Bayesian inference and rely on sampling-based approaches to compute parameter posterior distributions. Accurate or repeated retrievals, however, can result in very long computation times due to the sequential nature of sampling-based algorithms.
Aims. We aim to amortize exoplanetary atmospheric retrieval using neural posterior estimation (NPE), a simulation-based inference algorithm based on variational inference and normalizing flows. In this way, we aim (i) to strongly reduce inference time, (ii) to scale inference to complex simulation models with many nuisance parameters or intractable likelihood functions, and (iii) to enable the statistical validation of the inference results.
Methods. We evaluated NPE on a radiative transfer model for exoplanet spectra (petitRADTRANS), including the effects of scattering and clouds. We trained a neural autoregressive flow to quickly estimate posteriors and compared against retrievals computed with MultiNest.
Results. We find that NPE produces accurate posterior approximations while reducing inference time down to a few seconds. We demonstrate the computational faithfulness of our posterior approximations using inference diagnostics including posterior predictive checks and coverage, taking advantage of the quasi-instantaneous inference time of NPE. Our analysis confirms the reliability of the approximate posteriors produced by NPE.
Conclusions. The inference results produced by NPE appear to be accurate and reliable, establishing this algorithm as a promising approach for atmospheric retrieval. Its main benefits come from the amortization of posterior inference: once trained, inference does not require on-the-fly simulations and can be repeated several times for many observations at a very low computational cost. This enables efficient, scalable, and testable atmospheric retrieval.
Robust construction of differential emission measure profiles using a regularized maximum likelihood method
Authors: Massa Paolo , Emslie A. Gordon , Hannah Iain G. , Kontar Eduard P. 
Published: March 2023

Context.Extreme-ultraviolet (EUV) observations provide considerable insight into evolving physical conditions in the active solar atmosphere. For a prescribed density and temperature structure, it is straightforward to construct the corresponding differential emission measure profileξ(Τ), such thatξ(Τ) dTis proportional to the emissivity from plasma in the temperature range [T,T+ dT]. Here we study the inverse problem of obtaining a validξ(T) profile from a set of EUV spectral line intensities observed at a pixel within a solar image.Aims.Our goal is to introduce and develop a regularized maximum likelihood (RML) algorithm designed to address the mathematically ill-posed problem of constructing differential emission measure profiles from a discrete set of EUV intensities in specified wavelength bands, specifically those observed by the Atmospheric Imaging Assembly (AIA) on the NASA Solar Dynamics Observatory.Methods.The RML method combines features of maximum likelihood and regularized approaches used by other authors. It is also guaranteed to produce a positive definite differential emission measure profile.Results.We evaluate and compare the effectiveness of the method against other published algorithms, using both simulated data generated from parametric differential emission profile forms, and AIA data from a solar eruptive event on 2010 November 3. Similarities and differences between the differential emission measure profiles and maps reconstructed by the various algorithms are discussed.Conclusions.The RML inversion method is mathematically rigorous, computationally efficient, and produces acceptable measures of performance in the following three key areas: fidelity to the data, accuracy in the reconstruction, and robustness in the presence of data noise. As such, it shows considerable promise for computing differential emission measure profiles from datasets of discrete spectral lines.
Untere und mittlere gastrointestinale Blutung
Authors: Albert Jörg G. , Grün Kira , Sarrazin Christoph 
Published: March 2023

ZusammenfassungBlutungen aus dem Gastrointestinaltrakt werden in obere, mittlere und untere gastrointestinale Blutung unterschieden. Die Diagnostik kann eine Herausforderung sein und ist eine Domäne der Koloskopie, der Kapselendoskopie oder der flexiblen Enteroskopieverfahren. Als endoskopische Therapieoptionen stehen die Injektionstherapie, Metallclips, eine thermische Behandlung sowie die Gummibandligatur zur Verfügung, eine chirurgische Resektion ist nur selten erforderlich.