bluuebunny/crossref_metadata_2025_split huggingface dataset:
Associations between food and beverage purchases and skin carotenoids among diverse small food retail store customers
Authors: Dixon Jocelyn , Stage Virginia C , Truesdale Kimberly P , Wu Qiang , Kolasa Kathryn , Haynes-Maslow Lindsey , McGuirt Jared T , Jilcott Pitts Stephanie 
Published: August 2023

AbstractObjective:To determine if customer purchases at small food stores are associated with healthfulness of the diet as approximated by skin carotenoids.Design:This is a cross-sectional survey of customers in small food stores regarding demographics and food purchases. Food and beverage purchases were classified as ‘healthy’ or ‘non-healthy’ and ‘carotenoid’ v. ‘non-carotenoid’ using a systematic classification scheme. Fruit and vegetable intake was objectively assessed using a non-invasive device to measure skin carotenoids. Associations between variables of interest were examined using Pearson’s correlation coefficients, t tests and multiple linear regression analyses.Setting:Twenty-two small food retail stores in rural (n 7 stores) and urban (n 15) areas of North Carolina.Participants:Customers of small food storesResults:Of study participants (n 1086), 55·1 % were male, 60·0 % were African American/Black and 4·2 % were Hispanic, with a mean age of 43·5 years. Overall, 36 % purchased at least one healthy item, and 7·6 % of participants purchased a carotenoid-containing food/beverage. Healthy foods and beverages purchased included produce, lean meats, 100 % juices, plain popcorn, plain nuts, milk and yogurt. Unhealthy items included non-100 % juices, crackers, chips, candy, cakes and donuts. Purchase of a healthy or carotenoid-containing item was positively associated with skin carotenoid scores (P = 0·002 and 0·006, respectively).Conclusions:A relatively small proportion of customers purchased any healthy or carotenoid-containing foods and beverages, and those who did purchase healthy options had higher skin carotenoid scores. Future research should confirm these findings in different populations.
Snack frequency, size, and energy density are associated with diet quality among US adolescents
Authors: Tripicchio Gina L , Bailey Regan L , Davey Adam , Croce Christina M , Fisher Jennifer Orlet 
Published: August 2023

AbstractObjective:To evaluate snacking and diet quality among US adolescents.Design:Cross-sectional analysis examined snack frequency (snacks/day), size (kcal/snack) and energy density (kcal/g/snack) as predictors of diet quality using the mean of two 24-h dietary recalls. Diet quality was assessed using the Healthy Eating Index (HEI-2015, 0–100), a mean adequacy ratio (MAR, 0–100) for under-consumed nutrients (potassium, fibre, Ca, vitamin D) and mean percentage of recommended limits for over-consumed nutrients (added sugar, saturated fat, Na). Linear regression models examined total snacks, food only snacks and beverage only snacks, as predictors of diet quality adjusting for demographic characteristics and estimated energy reporting accuracy.Setting:2007–2018 National Health and Nutrition Examination Survey.Participants:Adolescents 12–19 years (n 4985).Results:Snack frequency was associated with higher HEI-2015 (β = 0·7 (0·3), P < 0·05) but also with higher intake of over-consumed nutrients (β = 3·0 (0·8), P ≤ 0·001). Snack size was associated with lower HEI (β = –0·005 (0·001), P ≤ 0·001) and MAR (β = –0·005 (0·002), P < 0·05) and higher intake of over-consumed nutrients (β = 0·03 (0·005), P ≤ 0·001). Associations differed for food only and beverage only snacks. Food only snack frequency was associated with higher HEI-2015 (β = 1·7 (0·03), P ≤ 0·001), while food only snack size (β = –0·006 (0·0009), P ≤ 0·001) and food only snack energy density (β = –1·1 (0·2), P ≤ 0·001) were associated with lower HEI-2015. Conversely, beverage only snack frequency (β = 4·4 (2·1) P < 0·05) and beverage only snack size (β = 0·03 (0·01), P ≤ 0·001) were associated with higher intake of over-consumed nutrients.Conclusions:Smaller, frequent, less energy-dense food only snacks are associated with higher diet quality in adolescents; beverages consumed as snacks are associated with greater intake of over-consumed nutrients.
Application of Satellite‐Based Detections of Arctic Bromine Explosion Events Within GEOS‐Chem
Authors: Wales P. A. , Keller C. A. , Knowland K. E. , Pawson S. , Choi S. , Hendrick F. , Van Roozendael M. , Salawitch R. J. , Sulieman R. , Swanson W. F. 
Published: August 2023

AbstractDuring polar spring, periods of elevated tropospheric bromine drive near complete removal of surface ozone. These events impact the tropospheric oxidative capacity and are an area of active research with multiple approaches for representing the underlying processes in global models. We present a method for parameterizing emissions of molecular bromine (Br2) over the Arctic using satellite retrievals of bromine monoxide (BrO) from the Ozone Monitoring Instrument (OMI). OMI retrieves column BrO with daily near global coverage, and we use the GEOS‐Chem chemical mechanism, run online within the Goddard Earth Observing System Earth System Model to identify hotspots of BrO likely associated with polar processes. To account for uncertainties in modeling background BrO, hotspots are only identified where the difference between OMI and modeled columns exceeds a statistical threshold. The resulting hotspot columns are a lower‐limit for the portion of OMI BrO attributable to bromine explosion events. While these hotspots are correlated with BrO measured in the lower troposphere over the Arctic Ocean, a case study of missing detections of near‐surface BrO is identified. Daily flux of Br2 is estimated from hotspot columns of BrO using internal model parameters. When the emissions are applied, BrO hotspots are modeled with a 5% low bias. The sensitivity of the resulting ozone simulations to the treatment of background uncertainties in the BrO column is demonstrated. While periods of isolated, large (>50%) decreases in surface ozone are modeled, this technique does not simulate the low ozone observed at coastal stations and consistently underestimates ozone loss during March.
How Ice Particles Increase Mobility of Rock‐Ice Avalanches: Insights From Chute Flows Simulation of Granular Rock‐Ice Mixtures by Discrete Element Method
Authors: Feng Zetao , Fan Xuanmei , Ni Tao , Deng Yu , Zou Chengbin , Zhang Jing , Xu Qiang 
Published: August 2023

AbstractRock‐ice avalanches occurring in cold high‐mountain regions often cause catastrophic damages due to their extremely high mobility. Rock and ice have different physical properties, such as particle size, density, friction, etc., leading to the segregation of rock and ice in the mixture and impacting its mobility. However, how ice affects the mobility of rock‐ice avalanches is still poorly understood. A series of numerical experiments were conducted by using the discrete element method to quantify the effect of rock‐ice particle size ratio and ice content on the particle segregation and mobility of their mixtures. Results show that rock‐ice particle size ratio and volumetric ice content determine the spatial distribution of ice, thereafter affecting the mobility of the rock‐ice mixture by controlling the ratio of particle collision stress and coulomb friction stress. In particular, different from conventional understanding, the ice spatial distribution can have a significantly greater influence on the mixture's mobility compared to the volumetric ice content in some scenarios. This study provides insights into the effect of granular ice on the mobility law in the early phase of rock‐ice avalanches and has important implications for their hazard assessment.
Compact Sub‐Semicircular Axial Gradient Index Lens Synthesized by Metasurfaces: A Promising Solution for Miniaturized Antenna and Subwavelength Focusing Systems
Authors: Wang Yuan‐Chu , Ng Mou Kehn Malcolm 
Published: August 2023

AbstractWe present the design, fabrication, and experimental measurements of an Axial Gradient‐index (AGRIN) flat lens synthesized by 2D periodic metallic patches on a grounded dielectric slab, known as metasurfaces. Metasurfaces can be considered as artificial materials that possess unique characteristics, which mainly revolve around the two‐dimensional distribution of the structure. By manipulating the phase and amplitude of the near‐fields over the surface of the metasurface, specific values of the effective permittivity and permeability can be achieved, thereby regulating the overall field behavior by gaining control of the refractive index that is related to the aforementioned two material parameters. By configuring the refractive index, metasurfaces enable the manipulation of the direction in which electromagnetic waves propagate, as dictated by Snell's law. By varying the geometric dimensions of unit cells in each segment that compose the lens, the gradient refractive index profile required for our AGRIN lens can be achieved. A primary feature of this lens lies with its semicircular structure, in contrast to conventional circular ones. Its perimeter comprises a convex boundary and a straight one. In comparison to traditional circular lenses like the Luneburg lens and Maxwell fisheye lens, our proposed AGRIN lens offers the advantage of being more compact. Despite its smaller area, the AGRIN lens maintains its focusing ability. The AGRIN lens is capable of focusing over 71.75% of the energy from the incident wave onto the focal point. This efficient focusing ability, combined with its reduced size, makes the AGRIN lens highly advantageous for various applications.
Pharmacogenomic testing for antidepressant treatment selection: lessons learned and roadmap forward
Authors: Frye Mark A. , Nemeroff Charles B. 
Published: August 2023

AbstractPharmacogenomic technology is a developing field with enthusiastic interest and broad application potential. Three large, controlled studies have been published exploring the benefit of pharmacogenomically guided antidepressant treatment selection. Though all three studies did not show significant benefit of using this technology, these studies laid the foundation for further research that should address the limitations of this previous research and currently available commercial platforms. Future research needs to include large scale pharmacogenomic trials with GWAS analytics across diverse groups with attention to cost-effectiveness models, particularly for cases of treatment resistance and polypharmacy. The application of results from these large scale pharmacogenomic trials must also include exploring optimal EHR user interface design.
Brain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data
Authors: Fuscà Marco , Siebenhühner Felix , Wang Sheng H. , Myrov Vladislav , Arnulfo Gabriele , Nobili Lino , Palva J. Matias , Palva Satu 
Published: August 2023

AbstractNeuronal oscillations and their synchronization between brain areas are fundamental for healthy brain function. Yet, synchronization levels exhibit large inter-individual variability that is associated with behavioral variability. We test whether individual synchronization levels are predicted by individual brain states along an extended regime of critical-like dynamics – the Griffiths phase (GP). We use computational modelling to assess how synchronization is dependent on brain criticality indexed by long-range temporal correlations (LRTCs). We analyze LRTCs and synchronization of oscillations from resting-state magnetoencephalography and stereo-electroencephalography data. Synchronization and LRTCs are both positively linearly and quadratically correlated among healthy subjects, while in epileptogenic areas they are negatively linearly correlated. These results show that variability in synchronization levels is explained by the individual position along the GP with healthy brain areas operating in its subcritical and epileptogenic areas in its supercritical side. We suggest that the GP is fundamental for brain function allowing individual variability while retaining functional advantages of criticality.
Getting personal with epigenetics: towards individual-specific epigenomic imputation with machine learning
Authors: Hawkins-Hooker Alex , Visonà Giovanni , Narendra Tanmayee , Rojas-Carulla Mateo , Schölkopf Bernhard , Schweikert Gabriele 
Published: August 2023

AbstractEpigenetic modifications are dynamic mechanisms involved in the regulation of gene expression. Unlike the DNA sequence, epigenetic patterns vary not only between individuals, but also between different cell types within an individual. Environmental factors, somatic mutations and ageing contribute to epigenetic changes that may constitute early hallmarks or causal factors of disease. Epigenetic modifications are reversible and thus promising therapeutic targets for precision medicine. However, mapping efforts to determine an individual’s cell-type-specific epigenome are constrained by experimental costs and tissue accessibility. To address these challenges, we developed eDICE, an attention-based deep learning model that is trained to impute missing epigenomic tracks by conditioning on observed tracks. Using a recently published set of epigenomes from four individual donors, we show that transfer learning across individuals allows eDICE to successfully predict individual-specific epigenetic variation even in tissues that are unmapped in a given donor. These results highlight the potential of machine learning-based imputation methods to advance personalized epigenomics.
Phenotypically complex living materials containing engineered cyanobacteria
Authors: Datta Debika , Weiss Elliot L. , Wangpraseurt Daniel , Hild Erica , Chen Shaochen , Golden James W. , Golden Susan S. , Pokorski Jonathan K. 
Published: August 2023

AbstractThe field of engineered living materials lies at the intersection of materials science and synthetic biology with the aim of developing materials that can sense and respond to the environment. In this study, we use 3D printing to fabricate a cyanobacterial biocomposite material capable of producing multiple functional outputs in response to an external chemical stimulus and demonstrate the advantages of utilizing additive manufacturing techniques in controlling the shape of the fabricated photosynthetic material. As an initial proof-of-concept, a synthetic riboswitch is used to regulate the expression of a yellow fluorescent protein reporter in Synechococcus elongatus PCC 7942 within a hydrogel matrix. Subsequently, a strain of S. elongatus is engineered to produce an oxidative laccase enzyme; when printed within a hydrogel matrix the responsive biomaterial can decolorize a common textile dye pollutant, indigo carmine, potentially serving as a tool in environmental bioremediation. Finally, cells are engineered for inducible cell death to eliminate their presence once their activity is no longer required, which is an important function for biocontainment and minimizing environmental impact. By integrating genetically engineered stimuli-responsive cyanobacteria in volumetric 3D-printed designs, we demonstrate programmable photosynthetic biocomposite materials capable of producing functional outputs including, but not limited to, bioremediation.
Impact of hierarchical water dipole orderings on the dynamics of aqueous salt solutions
Authors: Shi Rui , Cooper Anthony J. , Tanaka Hajime 
Published: August 2023

AbstractIons exhibit highly ion-specific complex behaviours when solvated in water, which remains a mystery despite the fundamental importance of ion solvation in nature, science, and technology. Here we explain these ion-specific properties by the ion-induced hierarchical dipolar, translational, and bond-orientational orderings of ion hydration shell under the competition between ion-water electrostatic interactions and inter-water hydrogen bonding. We first characterise this competition by a new length λHB(q), explaining the ion-specific effects on solution dynamics. Then, by continuously tuning ion size and charge, we find that the bond-orientational order of the ion hydration shell highly develops for specific ion size and charge combinations. This ordering drastically stabilises the hydration shell; its degree changes the water residence time around ions by 11 orders of magnitude for main-group ions. These findings are fundamental to ionic processes in aqueous solutions, providing a physical principle for electrolyte design and application.
Discovering conservation laws using optimal transport and manifold learning
Authors: Lu Peter Y. , Dangovski Rumen , Soljačić Marin 
Published: August 2023

AbstractConservation laws are key theoretical and practical tools for understanding, characterizing, and modeling nonlinear dynamical systems. However, for many complex systems, the corresponding conserved quantities are difficult to identify, making it hard to analyze their dynamics and build stable predictive models. Current approaches for discovering conservation laws often depend on detailed dynamical information or rely on black box parametric deep learning methods. We instead reformulate this task as a manifold learning problem and propose a non-parametric approach for discovering conserved quantities. We test this new approach on a variety of physical systems and demonstrate that our method is able to both identify the number of conserved quantities and extract their values. Using tools from optimal transport theory and manifold learning, our proposed method provides a direct geometric approach to identifying conservation laws that is both robust and interpretable without requiring an explicit model of the system nor accurate time information.
Enhancing quantum teleportation efficacy with noiseless linear amplification
Authors: Zhao Jie , Jeng Hao , Conlon Lorcán O. , Tserkis Spyros , Shajilal Biveen , Liu Kui , Ralph Timothy C. , Assad Syed M. , Lam Ping Koy 
Published: August 2023

AbstractQuantum teleportation constitutes a fundamental tool for various applications in quantum communication and computation. However, state-of-the-art continuous-variable quantum teleportation is restricted to moderate fidelities and short-distance configurations. This is due to unavoidable experimental imperfections resulting in thermal decoherence during the teleportation process. Here we present a heralded quantum teleporter able to overcome these limitations through noiseless linear amplification. As a result, we report a high fidelity of 92% for teleporting coherent states using a modest level of quantum entanglement. Our teleporter in principle allows nearly complete removal of loss induced onto the input states being transmitted through imperfect quantum channels. We further demonstrate the purification of a displaced thermal state, impossible via conventional deterministic amplification or teleportation approaches. The combination of high-fidelity coherent state teleportation alongside the purification of thermalized input states permits the transmission of quantum states over significantly long distances. These results are of both practical and fundamental significance; overcoming long-standing hurdles en route to highly-efficient continuous-variable quantum teleportation, while also shining new light on applying teleportation to purify quantum systems from thermal noise.
Fabrication of p-type 2D single-crystalline transistor arrays with Fermi-level-tuned van der Waals semimetal electrodes
Authors: Song Seunguk , Yoon Aram , Jang Sora , Lynch Jason , Yang Jihoon , Han Juwon , Choe Myeonggi , Jin Young Ho , Chen Cindy Yueli , Cheon Yeryun , Kwak Jinsung , Jeong Changwook , Cheong Hyeonsik , Jariwala Deep , Lee Zonghoon , Kwon Soon-Yong 
Published: August 2023

AbstractHigh-performance p-type two-dimensional (2D) transistors are fundamental for 2D nanoelectronics. However, the lack of a reliable method for creating high-quality, large-scale p-type 2D semiconductors and a suitable metallization process represents important challenges that need to be addressed for future developments of the field. Here, we report the fabrication of scalable p-type 2D single-crystalline 2H-MoTe2 transistor arrays with Fermi-level-tuned 1T’-phase semimetal contact electrodes. By transforming polycrystalline 1T’-MoTe2 to 2H polymorph via abnormal grain growth, we fabricated 4-inch 2H-MoTe2 wafers with ultra-large single-crystalline domains and spatially-controlled single-crystalline arrays at a low temperature (~500 °C). Furthermore, we demonstrate on-chip transistors by lithographic patterning and layer-by-layer integration of 1T’ semimetals and 2H semiconductors. Work function modulation of 1T’-MoTe2 electrodes was achieved by depositing 3D metal (Au) pads, resulting in minimal contact resistance (~0.7 kΩ·μm) and near-zero Schottky barrier height (~14 meV) of the junction interface, and leading to high on-state current (~7.8 μA/μm) and on/off current ratio (~105) in the 2H-MoTe2 transistors.
Identification of scaffold proteins for improved endogenous engineering of extracellular vesicles
Authors: Zheng Wenyi , Rädler Julia , Sork Helena , Niu Zheyu , Roudi Samantha , Bost Jeremy P. , Görgens André , Zhao Ying , Mamand Doste R. , Liang Xiuming , Wiklander Oscar P. B. , Lehto Taavi , Gupta Dhanu , Nordin Joel Z. , EL Andaloussi Samir 
Published: August 2023

AbstractExtracellular vesicles (EVs) are gaining ground as next-generation drug delivery modalities. Genetic fusion of the protein of interest to a scaffold protein with high EV-sorting ability represents a robust cargo loading strategy. To address the paucity of such scaffold proteins, we leverage a simple and reliable assay that can distinguish intravesicular cargo proteins from surface- as well as non-vesicular proteins and compare the EV-sorting potential of 244 candidate proteins. We identify 24 proteins with conserved EV-sorting abilities across five types of producer cells. TSPAN2 and TSPAN3 emerge as lead candidates and outperform the well-studied CD63 scaffold. Importantly, these engineered EVs show promise as delivery vehicles in cell cultures and mice as demonstrated by efficient transfer of luminal cargo proteins as well as surface display of different functional entities. The discovery of these scaffolds provides a platform for EV-based engineering.
SONAR enables cell type deconvolution with spatially weighted Poisson-Gamma model for spatial transcriptomics
Authors: Liu Zhiyuan , Wu Dafei , Zhai Weiwei , Ma Liang 
Published: August 2023

AbstractRecent advancements in spatial transcriptomic technologies have enabled the measurement of whole transcriptome profiles with preserved spatial context. However, limited by spatial resolution, the measured expressions at each spot are often from a mixture of multiple cells. Computational deconvolution methods designed for spatial transcriptomic data rarely make use of the valuable spatial information as well as the neighboring similarity information. Here, we propose SONAR, a Spatially weighted pOissoN-gAmma Regression model for cell-type deconvolution with spatial transcriptomic data. SONAR directly models the raw counts of spatial transcriptomic data and applies a geographically weighted regression framework that incorporates neighboring information to enhance local estimation of regional cell type composition. In addition, SONAR applies an additional elastic weighting step to adaptively filter dissimilar neighbors, which effectively prevents the introduction of local estimation bias in transition regions with sharp boundaries. We demonstrate the performance of SONAR over other state-of-the-art methods on synthetic data with various spatial patterns. We find that SONAR can accurately map region-specific cell types in real spatial transcriptomic data including mouse brain, human heart and human pancreatic ductal adenocarcinoma. We further show that SONAR can reveal the detailed distributions and fine-grained co-localization of immune cells within the microenvironment at the tumor-normal tissue margin in human liver cancer.