bluuebunny/crossref_metadata_2025_split huggingface dataset:
Protein secondary structure in spider silk nanofibrils
Authors: Wang Qijue , McArdle Patrick , Wang Stephanie L. , Wilmington Ryan L. , Xing Zhen , Greenwood Alexander , Cotten Myriam L. , Qazilbash M. Mumtaz , Schniepp Hannes C. 
Published: July 2022

AbstractNanofibrils play a pivotal role in spider silk and are responsible for many of the impressive properties of this unique natural material. However, little is known about the internal structure of these protein fibrils. We carry out polarized Raman and polarized Fourier-transform infrared spectroscopies on native spider silk nanofibrils and determine the concentrations of six distinct protein secondary structures, including β-sheets, and two types of helical structures, for which we also determine orientation distributions. Our advancements in peak assignments are in full agreement with the published silk vibrational spectroscopy literature. We further corroborate our findings with X-ray diffraction and magic-angle spinning nuclear magnetic resonance experiments. Based on the latter and on polypeptide Raman spectra, we assess the role of key amino acids in different secondary structures. For the recluse spider we develop a highly detailed structural model, featuring seven levels of structural hierarchy. The approaches we develop are directly applicable to other proteinaceous materials.
Simulating hyperbolic space on a circuit board
Authors: Lenggenhager Patrick M. , Stegmaier Alexander , Upreti Lavi K. , Hofmann Tobias , Helbig Tobias , Vollhardt Achim , Greiter Martin , Lee Ching Hua , Imhof Stefan , Brand Hauke , Kießling Tobias , Boettcher Igor , Neupert Titus , Thomale Ronny , Bzdušek Tomáš 
Published: July 2022

AbstractThe Laplace operator encodes the behavior of physical systems at vastly different scales, describing heat flow, fluids, as well as electric, gravitational, and quantum fields. A key input for the Laplace equation is the curvature of space. Here we discuss and experimentally demonstrate that the spectral ordering of Laplacian eigenstates for hyperbolic (negatively curved) and flat two-dimensional spaces has a universally different structure. We use a lattice regularization of hyperbolic space in an electric-circuit network to measure the eigenstates of a ‘hyperbolic drum’, and in a time-resolved experiment we verify signal propagation along the curved geodesics. Our experiments showcase both a versatile platform to emulate hyperbolic lattices in tabletop experiments, and a set of methods to verify the effective hyperbolic metric in this and other platforms. The presented techniques can be utilized to explore novel aspects of both classical and quantum dynamics in negatively curved spaces, and to realise the emerging models of topological hyperbolic matter.
A density-based enrichment measure for assessing colocalization in single-molecule localization microscopy data
Authors: Ejdrup Aske L. , Lycas Matthew D. , Lorenzen Niels , Konomi Ainoa , Herborg Freja , Madsen Kenneth L. , Gether Ulrik 
Published: July 2022

AbstractDual-color single-molecule localization microscopy (SMLM) provides unprecedented possibilities for detailed studies of colocalization of different molecular species in a cell. However, the informational richness of the data is not fully exploited by current analysis tools that often reduce colocalization to a single value. Here, we describe a tool specifically designed for determination of co-localization in both 2D and 3D from SMLM data. The approach uses a function that describes the relative enrichment of one molecular species on the density distribution of a reference species. The function reframes the question of colocalization by providing a density-context relevant to multiple biological questions. Moreover, the function visualize enrichment (i.e. colocalization) directly in the images for easy interpretation. We demonstrate the approach’s functionality on both simulated data and cultured neurons, and compare it to current alternative measures. The method is available in a Python function for easy and parameter-free implementation.
Protein shape sampled by ion mobility mass spectrometry consistently improves protein structure prediction
Authors: Turzo SM Bargeen Alam , Seffernick Justin T. , Rolland Amber D. , Donor Micah T. , Heinze Sten , Prell James S. , Wysocki Vicki H. , Lindert Steffen 
Published: July 2022

AbstractIon mobility (IM) mass spectrometry provides structural information about protein shape and size in the form of an orientationally-averaged collision cross-section (CCSIM). While IM data have been used with various computational methods, they have not yet been utilized to predict monomeric protein structure from sequence. Here, we show that IM data can significantly improve protein structure determination using the modelling suite Rosetta. We develop the Rosetta Projection Approximation using Rough Circular Shapes (PARCS) algorithm that allows for fast and accurate prediction of CCSIM from structure. Following successful testing of the PARCS algorithm, we use an integrative modelling approach to utilize IM data for protein structure prediction. Additionally, we propose a confidence metric that identifies near native models in the absence of a known structure. The results of this study demonstrate the ability of IM data to consistently improve protein structure prediction.
Dynamics of competing SARS-CoV-2 variants during the Omicron epidemic in England
Authors: Eales Oliver , de Oliveira Martins Leonardo , Page Andrew J. , Wang Haowei , Bodinier Barbara , Tang David , Haw David , Jonnerby Jakob , Atchison Christina , Ashby Deborah , Barclay Wendy , Taylor Graham , Cooke Graham , Ward Helen , Darzi Ara , Riley Steven , Elliott Paul , Donnelly Christl A. , Chadeau-Hyam Marc 
Published: July 2022

AbstractThe SARS-CoV-2 pandemic has been characterised by the regular emergence of genomic variants. With natural and vaccine-induced population immunity at high levels, evolutionary pressure favours variants better able to evade SARS-CoV-2 neutralising antibodies. The Omicron variant (first detected in November 2021) exhibited a high degree of immune evasion, leading to increased infection rates worldwide. However, estimates of the magnitude of this Omicron wave have often relied on routine testing data, which are prone to several biases. Using data from the REal-time Assessment of Community Transmission-1 (REACT-1) study, a series of cross-sectional surveys assessing prevalence of SARS-CoV-2 infection in England, we estimated the dynamics of England’s Omicron wave (from 9 September 2021 to 1 March 2022). We estimate an initial peak in national Omicron prevalence of 6.89% (5.34%, 10.61%) during January 2022, followed by a resurgence in SARS-CoV-2 infections as the more transmissible Omicron sub-lineage, BA.2 replaced BA.1 and BA.1.1. Assuming the emergence of further distinct variants, intermittent epidemics of similar magnitudes may become the ‘new normal’.
Microbial biofilms for electricity generation from water evaporation and power to wearables
Authors: Liu Xiaomeng , Ueki Toshiyuki , Gao Hongyan , Woodard Trevor L. , Nevin Kelly P. , Fu Tianda , Fu Shuai , Sun Lu , Lovley Derek R. , Yao Jun 
Published: July 2022

AbstractEmploying renewable materials for fabricating clean energy harvesting devices can further improve sustainability. Microorganisms can be mass produced with renewable feedstocks. Here, we demonstrate that it is possible to engineer microbial biofilms as a cohesive, flexible material for long-term continuous electricity production from evaporating water. Single biofilm sheet (~40 µm thick) serving as the functional component in an electronic device continuously produces power density (~1 μW/cm2) higher than that achieved with thicker engineered materials. The energy output is comparable to that achieved with similar sized biofilms catalyzing current production in microbial fuel cells, without the need for an organic feedstock or maintaining cell viability. The biofilm can be sandwiched between a pair of mesh electrodes for scalable device integration and current production. The devices maintain the energy production in ionic solutions and can be used as skin-patch devices to harvest electricity from sweat and moisture on skin to continuously power wearable devices. Biofilms made from different microbial species show generic current production from water evaporation. These results suggest that we can harness the ubiquity of biofilms in nature as additional sources of biomaterial for evaporation-based electricity generation in diverse aqueous environments.
Phosphatidylinositol-4-phosphate controls autophagosome formation in Arabidopsis thaliana
Authors: Gomez Rodrigo Enrique , Chambaud Clément , Lupette Josselin , Castets Julie , Pascal Stéphanie , Brocard Lysiane , Noack Lise , Jaillais Yvon , Joubès Jérôme , Bernard Amélie 
Published: July 2022

AbstractAutophagy is an intracellular degradation mechanism critical for plant acclimation to environmental stresses. Central to autophagy is the formation of specialized vesicles, the autophagosomes, which target and deliver cargo to the lytic vacuole. How autophagosomes form in plant cells remains poorly understood. Here, we uncover the importance of the lipid phosphatidylinositol-4-phosphate in autophagy using pharmacological and genetical approaches. Combining biochemical and live-microscopy analyses, we show that PI4K activity is required for early stages of autophagosome formation. Further, our results show that the plasma membrane-localized PI4Kα1 is involved in autophagy and that a substantial portion of autophagy structures are found in proximity to the PI4P-enriched plasma membrane. Together, our study unravels critical insights into the molecular determinants of autophagy, proposing a model whereby the plasma membrane provides PI4P to support the proper assembly and expansion of the phagophore thus governing autophagosome formation in Arabidopsis.
Fusion protein strategies for cryo-EM study of G protein-coupled receptors
Authors: Zhang Kaihua , Wu Hao , Hoppe Nicholas , Manglik Aashish , Cheng Yifan 
Published: July 2022

AbstractSingle particle cryogenic-electron microscopy (cryo-EM) is used extensively to determine structures of activated G protein-coupled receptors (GPCRs) in complex with G proteins or arrestins. However, applying it to GPCRs without signaling proteins remains challenging because most receptors lack structural features in their soluble domains to facilitate image alignment. In GPCR crystallography, inserting a fusion protein between transmembrane helices 5 and 6 is a highly successful strategy for crystallization. Although a similar strategy has the potential to broadly facilitate cryo-EM structure determination of GPCRs alone without signaling protein, the critical determinants that make this approach successful are not yet clear. Here, we address this shortcoming by exploring different fusion protein designs, which lead to structures of antagonist bound A2A adenosine receptor at 3.4 Å resolution and unliganded Smoothened at 3.7 Å resolution. The fusion strategies explored here are likely applicable to cryo-EM interrogation of other GPCRs and small integral membrane proteins.
A three-dimensional flow model of screen channel liquid acquisition devices for propellant management in microgravity
Authors: Wang Zheng , Yang Guang , Wang Ye , Jin Xin , Zhuan Rui , Zhang Hao , Wu Jingyi 
Published: July 2022

AbstractScreen channel liquid acquisition devices (LADs) are among the most promising technologies for separating liquid and vapor phases in propellant storage tanks under microgravity conditions and thus ensuring vapor-free propellant supply to spacecraft engines. However, the prediction of the critical flow rate of a screen channel LAD relies on the full understanding of the three dimensional distribution of injection velocity. In this study, the flow characteristics at the entrance region of the LAD were investigated via particle image velocimetry (PIV) technique and numerical simulations under various working conditions. The experimental results illustrated that the velocity component normal to the porous woven mesh is non-uniform in both streamwise and spanwise directions of channel flow and that this phenomenon has a significant influence on the critical flow rate. Hence, a model that accounts for the three-dimensional flow field was proposed to predict the critical flow rate. The average error in the critical flow rate, which was determined by comparing the proposed model’s predictions and the experimental results, was less than 8.4%.
Automatic scoring of COVID-19 severity in X-ray imaging based on a novel deep learning workflow
Authors: Danilov Viacheslav V. , Litmanovich Diana , Proutski Alex , Kirpich Alexander , Nefaridze Dato , Karpovsky Alex , Gankin Yuriy 
Published: July 2022

AbstractIn this study, we propose a two-stage workflow used for the segmentation and scoring of lung diseases. The workflow inherits quantification, qualification, and visual assessment of lung diseases on X-ray images estimated by radiologists and clinicians. It requires the fulfillment of two core stages devoted to lung and disease segmentation as well as an additional post-processing stage devoted to scoring. The latter integrated block is utilized, mainly, for the estimation of segment scores and computes the overall severity score of a patient. The models of the proposed workflow were trained and tested on four publicly available X-ray datasets of COVID-19 patients and two X-ray datasets of patients with no pulmonary pathology. Based on a combined dataset consisting of 580 COVID-19 patients and 784 patients with no disorders, our best-performing algorithm is based on a combination of DeepLabV3 + , for lung segmentation, and MA-Net, for disease segmentation. The proposed algorithms’ mean absolute error (MAE) of 0.30 is significantly reduced in comparison to established COVID-19 algorithms; BS-net and COVID-Net-S, possessing MAEs of 2.52 and 1.83 respectively. Moreover, the proposed two-stage workflow was not only more accurate but also computationally efficient, it was approximately 11 times faster than the mentioned methods. In summary, we proposed an accurate, time-efficient, and versatile approach for segmentation and scoring of lung diseases illustrated for COVID-19 and with broader future applications for pneumonia, tuberculosis, pneumothorax, amongst others.
Clinical and prognostic implications of rim restriction following glioma surgery
Authors: Berger Assaf , Tzarfati Garry Gali , Serafimova Marga , Valdes Pablo , Meller Aaron , Korn Akiva , Levy Naomi Kahana , Aviram Daniel , Ram Zvi , Grossman Rachel 
Published: July 2022

AbstractRim restriction surrounding the resection cavity of glioma is often seen on immediate post-op diffusion-weighted imaging (DWI). The etiology and clinical impact of rim restriction are unknown. We evaluated the incidence, risk factors and clinical consequences of this finding. We evaluated patients that underwent surgery for low-grade glioma (LGG) and glioblastoma (GBM) without stroke on post-operative imaging. Analyses encompassed pre- and postoperative clinical, radiological, intraoperative monitoring, survival, functional and neurocognitive outcomes. Between 2013 and 2017, 63 LGG and 209 GBM patients (272 in total) underwent surgical resection and were included in our cohort. Post-op rim restriction was demonstrated in 68 patients, 32% (n = 20) of LGG and 23% (n = 48) of GBM patients. Risk factors for restriction included temporal tumors in GBM (p = 0.025) and insular tumors in LGG (p = 0.09), including longer surgery duration in LGG (p = 0.008). After a 1-year follow-up, LGG patients operated on their dominant with post-op restriction had a higher rate of speech deficits (46 vs 9%, p = 0.004). Rim restriction on postoperative imaging is associated with longer duration of glioma surgery and potentially linked to brain retraction. It apparently has no direct clinical consequences, but is linked to higher rates of speech deficits in LGG dominant-side surgeries.
Social determinants and lifestyle factors for brain health: implications for risk reduction of cognitive decline and dementia
Authors: Röhr Susanne , Pabst Alexander , Baber Ronny , Engel Christoph , Glaesmer Heide , Hinz Andreas , Schroeter Matthias L. , Witte A. Veronica , Zeynalova Samira , Villringer Arno , Löffler Markus , Riedel-Heller Steffi G. 
Published: July 2022

AbstractSubstantial evidence indicates a huge potential for risk reduction of cognitive decline and dementia based on modifiable health and lifestyle factors. To maximize the chances for risk reduction, it is useful to investigate associations of social determinants and lifestyle for brain health. We computed the “LIfestyle for BRAin health” (LIBRA) score for baseline participants of the Leipzig Research Centre for Civilization Diseases (LIFE) Adult Study, a population-based urban cohort in Germany. LIBRA predicts dementia in midlife and early late life populations, comprising 12 modifiable risk factors (heart disease, kidney disease, diabetes, obesity, hypertension, hypercholesterolemia, alcohol consumption, smoking, physical inactivity, diet, depression, cognitive inactivity). Associations of social determinants (living situation, marital status, social isolation, education, net equivalence income, occupational status, socioeconomic status/SES, employment) with LIBRA were inspected using age- and sex-adjusted multivariable linear regression analysis. Z-standardization and sampling weights were applied. Participants (n = 6203) were M = 57.4 (SD = 10.6, range 40–79) years old and without dementia, 53.0% were women. Except for marital status, all considered social determinants were significantly associated with LIBRA. Beta coefficients for the association with higher LIBRA scores were most pronounced for low SES (β = 0.80, 95% CI [0.72–0.88]; p < 0.001) and middle SES (β = 0.55, 95% CI [0.47–0.62]; p < 0.001). Social determinants, particularly socioeconomic factors, are associated with lifestyle for brain health, and should thus be addressed in risk reduction strategies for cognitive decline and dementia. A social-ecological public health perspective on risk reduction might be more effective and equitable than focusing on individual lifestyle behaviors alone.
Isolated effects of patellar resurfacing in total knee arthroplasty and their relation to native patellar geometry
Authors: Sauer Adrian , Thorwaechter Christoph , Dupraz Ingrid , Maas Allan , Steinbrueck Arnd , Grupp Thomas M. , Woiczinski Matthias 
Published: July 2022

AbstractThe isolated effects of patellar resurfacing on patellar kinematics are rarely investigated. Nonetheless, knowing more about these effects could help to enhance present understanding of the emergence of kinematic improvements or deteriorations associated with patellar resurfacing. The aim of this study was to isolate the effects of patellar resurfacing from a multi-stage in vitro study, where kinematics after total knee arthroplasty before and after patellar resurfacing were recorded. Additionally, the influence of the native patellar geometry on these effects was analysed. Eight fresh frozen specimens were tested successively with different implant configurations on an already established weight bearing knee rig. The patello-femoral kinematics were thereby measured using an ultrasonic measurement system and its relation to the native patellar geometries was analysed. After patellar resurfacing, the specimen showed a significantly medialized patellar shift. This medialization of the patellar tracking was significantly correlated to the lateral facet angle of the native patella. The patellar shift after patellar resurfacing is highly influenced by the position of the patellar button and the native lateral patellar facet angle. As a result, the ideal medio-lateral position of the patellar component is affected by the geometry of the native patella.
Deficiency of mature B cells does not alter the atherogenic response to castration in male mice
Authors: Wilhelmson Anna S. , Johansson Inger , Fogelstrand Linda , Fagman Johan Bourghardt , Arnal Jean-Francois , Karlsson Mikael C. I. , Tivesten Åsa 
Published: July 2022

AbstractTestosterone deficiency in men is associated with increased atherosclerosis burden and increased cardiovascular risk. In male mice, testosterone deficiency induced by castration increases atherosclerosis as well as mature B cell numbers in spleen. As B cells are potentially pro-atherogenic, we hypothesized that there may be a link between these effects. To address whether mature B cell deficiency alter the atherogenic response to castration, we studied B cell-deficient μMT and genotype control male mice on an atherosclerosis-prone Apoe−/− background that were castrated or sham-operated pre-pubertally and fed a high-fat diet between 8 and 16 weeks of age to accelerate atherosclerosis development. Genotype did not affect the effects of castration on body weight or weights of fat depots and there were no differences in serum cholesterol levels across the four groups. Atherosclerosis assessed by quantification of lesion area in serial sections of the aortic root was significantly increased by castration and by the μMT mutation, with no significant interaction between genotype and surgery. In conclusion, castration evokes a similar atherogenic response in B cell-deficient μMT and control mice. These data suggest that atherogenesis following castration is unrelated to the effects of androgens on mature B cell numbers.
Modeling innovation in the cryptocurrency ecosystem
Authors: Marzo Giordano De , Pandolfelli Francesco , Servedio Vito D. P. 
Published: July 2022

AbstractBlockchains are among the most relevant emerging technologies of recent times and, according to many, they will have a central role in shaping the future of our society. Since the introduction of Bitcoin in 2009, the first notorious blockchain system bound to a cryptocurrency, the blockchain ecosystem has experienced a huge growth, driven by innovations both in conceptual and algorithmic terms, and in the creation of a large number of new cryptocoins. New blockchains and their associated cryptocoins, emerge mostly as the result of forking already existing projects. Here, we show that the appearance of new cryptocoins can be well described by a sub-linear power-law (Heaps’ law) of the total crypto-market capitalization. At the same time, we propose a model that well reproduces the evolution of the cryptocurrency ecosystem. Our model suggests that each cryptocurrency triggers, on average, the creation of ca. 1.58 novel cryptocoins, a result confirmed by the analysis of the Bitcoin historical forking tree. Moreover, we deduce that the largest cryptocurrency, nowadays Bitcoin, will comprise around the 50% of the whole crypto-market and that this fraction is going to stabilize in the near future, provided that the present fundamental macro-economic conditions do not change radically.