bluuebunny/crossref_metadata_2025_split huggingface dataset:
SARS-CoV-2 rapid antibody test results and subsequent risk of hospitalisation and death in 361,801 people
Authors: Whitaker Matthew , Davies Bethan , Atchison Christina , Barclay Wendy , Ashby Deborah , Darzi Ara , Riley Steven , Cooke Graham , Donnelly Christl A. , Chadeau-Hyam Marc , Elliott Paul , Ward Helen 
Published: August 2023

AbstractThe value of SARS-CoV-2 lateral flow immunoassay (LFIA) tests for estimating individual disease risk is unclear. The REACT-2 study in England, UK, obtained self-administered SARS-CoV-2 LFIA test results from 361,801 adults in January-May 2021. Here, we link to routine data on subsequent hospitalisation (to September 2021), and death (to December 2021). Among those who had received one or more vaccines, a negative LFIA is associated with increased risk of hospitalisation with COVID-19 (HR: 2.73 [95% confidence interval: 1.15,6.48]), death (all-cause) (HR: 1.59, 95% CI:1.07, 2.37), and death with COVID-19 as underlying cause (20.6 [1.83,232]). For people designated at high risk from COVID-19, who had received one or more vaccines, there is an additional risk of all-cause mortality of 1.9 per 1000 for those testing antibody negative compared to positive. However, the LFIA does not provide substantial predictive information over and above that which is available from detailed sociodemographic and health-related variables. Nonetheless, this simple test provides a marker which could be a valuable addition to understanding population and individual-level risk.
Zwitterionic microgel preservation platform for circulating tumor cells in whole blood specimen
Authors: Ma Yiming , Zhang Jun , Tian Yunqing , Fu Yihao , Tian Shu , Li Qingsi , Yang Jing , Zhang Lei 
Published: August 2023

AbstractThe immediate processing of whole blood specimen is required in circulating tumor cell-based liquid biopsy. Reliable blood specimen stabilization towards preserving circulating tumor cells can enable more extensive geographic sharing for precise rare-cell technology, but remains challenging due to the fragility and rarity of circulating tumor cells. Herein, we establish a zwitterionic magnetic microgel platform to stabilize whole blood specimen for long-term hypothermic preservation of model circulating tumor cells. We show in a cohort study of 20 cancer patients that blood samples can be preserved for up to 7 days without compromising circulating tumor cell viability and RNA integrity, thereby doubling the viable preservation duration. We demonstrate that the 7-day microgel-preserved blood specimen is able to reliably detect cancer-specific transcripts, similar to fresh blood specimens, while there are up/down expression regulation of 1243 genes in model circulating tumor cells that are preserved by commercial protectant. Mechanistically, we find that the zwitterionic microgel assembly counters the cold-induced excessive reactive oxygen species and platelet activation, as well as extracellular matrix loss-induced cell anoikis, to prevent circulating tumor cell loss in the whole blood sample. The present work could prove useful for the development of blood-based noninvasive diagnostics.
Enabling low-drift flexible perovskite photodetectors by electrical modulation for wearable health monitoring and weak light imaging
Authors: Tang Yingjie , Jin Peng , Wang Yan , Li Dingwei , Chen Yitong , Ran Peng , Fan Wei , Liang Kun , Ren Huihui , Xu Xuehui , Wang Rui , Yang Yang , Zhu Bowen 
Published: August 2023

AbstractMetal halide perovskites are promising for next-generation flexible photodetectors owing to their low-temperature solution processability, mechanical flexibility, and excellent photoelectric properties. However, the defects and notorious ion migration in polycrystalline metal halide perovskites often lead to high and unstable dark current, thus deteriorating their detection limit and long-term operations. Here, we propose an electrical field modulation strategy to significantly reduce the dark current of metal halide perovskites-based flexible photodetector more than 1000 times (from ~5 nA to ~5 pA). Meanwhile, ion migration in metal halide perovskites is effectively suppressed, and the metal halide perovskites-based flexible photodetector shows a long-term continuous operational stability (~8000 s) with low signal drift (~4.2 × 10−4 pA per second) and ultralow dark current drift (~1.3 × 10−5 pA per second). Benefitting from the electrical modulation strategy, a high signal-to-noise ratio wearable photoplethysmography sensor and an active-matrix photodetector array for weak light imaging are successfully demonstrated. This work offers a universal strategy to improve the performance of metal halide perovskites for wearable flexible photodetector and image sensor applications.
Towards layer-selective quantum spin hall channels in weak topological insulator Bi4Br2I2
Authors: Zhong Jingyuan , Yang Ming , Shi Zhijian , Li Yaqi , Mu Dan , Liu Yundan , Cheng Ningyan , Zhao Wenxuan , Hao Weichang , Wang Jianfeng , Yang Lexian , Zhuang Jincheng , Du Yi 
Published: August 2023

AbstractWeak topological insulators, constructed by stacking quantum spin Hall insulators with weak interlayer coupling, offer promising quantum electronic applications through topologically non-trivial edge channels. However, the currently available weak topological insulators are stacks of the same quantum spin Hall layer with translational symmetry in the out-of-plane direction—leading to the absence of the channel degree of freedom for edge states. Here, we study a candidate weak topological insulator, Bi4Br2I2, which is alternately stacked by three different quantum spin Hall insulators, each with tunable topologically non-trivial edge states. Our angle-resolved photoemission spectroscopy and first-principles calculations show that an energy gap opens at the crossing points of different Dirac cones correlated with different layers due to the interlayer interaction. This is essential to achieve the tunability of topological edge states as controlled by varying the chemical potential. Our work offers a perspective for the construction of tunable quantized conductance devices for future spintronic applications.
Global methane emissions from rivers and streams
Authors: Rocher-Ros Gerard , Stanley Emily H. , Loken Luke C. , Casson Nora J. , Raymond Peter A. , Liu Shaoda , Amatulli Giuseppe , Sponseller Ryan A. 
Published: August 2023

AbstractMethane (CH4) is a potent greenhouse gas and its concentrations have tripled in the atmosphere since the industrial revolution. There is evidence that global warming has increased CH4emissions from freshwater ecosystems1,2, providing positive feedback to the global climate. Yet for rivers and streams, the controls and the magnitude of CH4emissions remain highly uncertain3,4. Here we report a spatially explicit global estimate of CH4emissions from running waters, accounting for 27.9 (16.7–39.7) Tg CH4 per year and roughly equal in magnitude to those of other freshwater systems5,6. Riverine CH4emissions are not strongly temperature dependent, with low average activation energy (EM = 0.14 eV) compared with that of lakes and wetlands (EM = 0.96 eV)1. By contrast, global patterns of emissions are characterized by large fluxes in high- and low-latitude settings as well as in human-dominated environments. These patterns are explained by edaphic and climate features that are linked to anoxia in and near fluvial habitats, including a high supply of organic matter and water saturation in hydrologically connected soils. Our results highlight the importance of land–water connections in regulating CH4supply to running waters, which is vulnerable not only to direct human modifications but also to several climate change responses on land.
Long-molecule scars of backup DNA repair in BRCA1- and BRCA2-deficient cancers
Authors: Setton Jeremy , Hadi Kevin , Choo Zi-Ning , Kuchin Katherine S. , Tian Huasong , Da Cruz Paula Arnaud , Rosiene Joel , Selenica Pier , Behr Julie , Yao Xiaotong , Deshpande Aditya , Sigouros Michael , Manohar Jyothi , Nauseef Jones T. , Mosquera Juan-Miguel , Elemento Olivier , Weigelt Britta , Riaz Nadeem , Reis-Filho Jorge S. , Powell Simon N. , Imieliński Marcin 
Published: August 2023

AbstractHomologous recombination (HR) deficiency is associated with DNA rearrangements and cytogenetic aberrations1. Paradoxically, the types of DNA rearrangements that are specifically associated with HR-deficient cancers only minimally affect chromosomal structure2. Here, to address this apparent contradiction, we combined genome-graph analysis of short-read whole-genome sequencing (WGS) profiles across thousands of tumours with deep linked-read WGS of 46 BRCA1- or BRCA2-mutant breast cancers. These data revealed a distinct class of HR-deficiency-enriched rearrangements called reciprocal pairs. Linked-read WGS showed that reciprocal pairs with identical rearrangement orientations gave rise to one of two distinct chromosomal outcomes, distinguishable only with long-molecule data. Whereas one (cis) outcome corresponded to the copying and pasting of a small segment to a distant site, a second (trans) outcome was a quasi-balanced translocation or multi-megabase inversion with substantial (10 kb) duplications at each junction. We propose an HR-independent replication-restart repair mechanism to explain the full spectrum of reciprocal pair outcomes. Linked-read WGS also identified single-strand annealing as a repair pathway that is specific to BRCA2 deficiency in human cancers. Integrating these features in a classifier improved discrimination between BRCA1- and BRCA2-deficient genomes. In conclusion, our data reveal classes of rearrangements that are specific to BRCA1 or BRCA2 deficiency as a source of cytogenetic aberrations in HR-deficient cells.
Prediction of gestational diabetes mellitus in Asian women using machine learning algorithms
Authors: Kang Byung Soo , Lee Seon Ui , Hong Subeen , Choi Sae Kyung , Shin Jae Eun , Wie Jeong Ha , Jo Yun Sung , Kim Yeon Hee , Kil Kicheol , Chung Yoo Hyun , Jung Kyunghoon , Hong Hanul , Park In Yang , Ko Hyun Sun 
Published: August 2023

AbstractThis study developed a machine learning algorithm to predict gestational diabetes mellitus (GDM) using retrospective data from 34,387 pregnancies in multi-centers of South Korea. Variables were collected at baseline, E0 (until 10 weeks’ gestation), E1 (11–13 weeks’ gestation) and M1 (14–24 weeks’ gestation). The data set was randomly divided into training and test sets (7:3 ratio) to compare the performances of light gradient boosting machine (LGBM) and extreme gradient boosting (XGBoost) algorithms, with a full set of variables (original). A prediction model with the whole cohort achieved area under the receiver operating characteristics curve (AUC) and area under the precision-recall curve (AUPR) values of 0.711 and 0.246 at baseline, 0.720 and 0.256 at E0, 0.721 and 0.262 at E1, and 0.804 and 0.442 at M1, respectively. Then comparison of three models with different variable sets were performed: [a] variables from clinical guidelines; [b] selected variables from Shapley additive explanations (SHAP) values; and [c] Boruta algorithms. Based on model [c] with the least variables and similar or better performance than the other models, simple questionnaires were developed. The combined use of maternal factors and laboratory data could effectively predict individual risk of GDM using a machine learning model.
Entropy generation analysis for mixed convection flow of nanofluid due to vertical plate with chemical reaction effects
Authors: Abdelhameed T. N. 
Published: August 2023

AbstractThe analysis have been presented to observe the optimized flow of Casson nanofluid conveying the applications of external heat generation and mixed convection features. The problem is further influenced by chemical reactive species with order one. The significant of Bejan number is evaluated. A vertically moving with convective heat phenomenon endorsed the flow. The modeled problem is reflected in terms PDE’s which are further simplifies with dimensionless form. The analytical outcomes have been established with implementation of Laplace technique. The graphical impact conveying the different parameters is assessed. The insight of skin friction and Nusselt number is observed via various curves. It is observed that entropy generation enhanced due to porosity parameter and magnetic number. With increasing Casson fluid parameter, the entropy generation decrease. Moreover, the Bejan number decreases for chemical reaction constant.
Modeling and optimization of parallelized immunomagnetic nanopore sorting for surface marker specific isolation of extracellular vesicles from complex media
Authors: Lin Andrew A. , Shen Hanfei , Spychalski Griffin , Carpenter Erica L. , Issadore David 
Published: August 2023

AbstractThe isolation of specific subpopulations of extracellular vesicles (EVs) based on their expression of surface markers poses a significant challenge due to their nanoscale size (< 800 nm), their heterogeneous surface marker expression, and the vast number of background EVs present in clinical specimens (1010–1012 EVs/mL in blood). Highly parallelized nanomagnetic sorting using track etched magnetic nanopore (TENPO) chips has achieved precise immunospecific sorting with high throughput and resilience to clogging. However, there has not yet been a systematic study of the design parameters that control the trade-offs in throughput, target EV recovery, and ability to discard background EVs in this approach. We combine finite-element simulation and experimental characterization of TENPO chips to elucidate design rules to isolate EV subpopulations from blood. We demonstrate the utility of this approach by reducing device background > 10× relative to prior published designs without sacrificing recovery of the target EVs by selecting pore diameter, number of membranes placed in series, and flow rate. We compare TENPO-isolated EVs to those of gold-standard methods of EV isolation and demonstrate its utility for wide application and modularity by targeting subpopulations of EVs from multiple models of disease including lung cancer, pancreatic cancer, and liver cancer.
Beyond 5 GHz excitation of a ZnO-based high-overtone bulk acoustic resonator on SiC substrate
Authors: Panda Padmalochan , Chatterjee Soumyadip , Tallur Siddharth , Laha Apurba 
Published: August 2023

AbstractThis work reports on the fabrication and characterization of an Au/ZnO/Pt-based high-overtone bulk acoustic resonator (HBAR) on SiC substrates. We evaluate its microwave characteristics comparing with Si substrates for micro-electromechanical applications. Dielectric magnetron sputtering and an electron beam evaporator are employed to develop highly c-axis-oriented ZnO films and metal electrodes. The crystal structure and surface morphology of post-growth layers are characterized using X-ray diffraction, atomic force microscopy, and scanning electron microscopy techniques. HBAR on SiC substrate results in multiple longitudinal bulk acoustic wave resonances up to 7 GHz, with the strongest excited resonances emerging at 5.25 GHz. The value of f.Q (Resonance frequency.Quality factor) parameter obtained using a novel Q approach method for HBAR on SiC substrate is 4.1 $$\times$$
×
10$$^{13}$$

13

Hz, which to the best of our knowledge, is the highest among all reported values for specified ZnO-based devices.
Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images
Authors: An Jeehye , Wendt Leo , Wiese Georg , Herold Tom , Rzepka Norman , Mueller Susanne , Koch Stefan Paul , Hoffmann Christian J. , Harms Christoph , Boehm-Sturm Philipp 
Published: August 2023

AbstractMagnetic resonance imaging (MRI) is widely used for ischemic stroke lesion detection in mice. A challenge is that lesion segmentation often relies on manual tracing by trained experts, which is labor-intensive, time-consuming, and prone to inter- and intra-rater variability. Here, we present a fully automated ischemic stroke lesion segmentation method for mouse T2-weighted MRI data. As an end-to-end deep learning approach, the automated lesion segmentation requires very little preprocessing and works directly on the raw MRI scans. We randomly split a large dataset of 382 MRI scans into a subset (n = 293) to train the automated lesion segmentation and a subset (n = 89) to evaluate its performance. We compared Dice coefficients and accuracy of lesion volume against manual segmentation, as well as its performance on an independent dataset from an open repository with different imaging characteristics. The automated lesion segmentation produced segmentation masks with a smooth, compact, and realistic appearance that are in high agreement with manual segmentation. We report dice scores higher than the agreement between two human raters reported in previous studies, highlighting the ability to remove individual human bias and standardize the process across research studies and centers.
Anchor free based Siamese network tracker with transformer for RGB-T tracking
Authors: Fan Liangsong , Kim Pyeoungkee 
Published: August 2023

AbstractIn recent years, many RGB-THERMAL tracking methods have been proposed to meet the needs of single object tracking under different conditions. However, these trackers are based on ANCHOR-BASED algorithms and feature cross-correlation operations, making it difficult to improve the success rate of target tracking. We propose a siamAFTS tracking network, which is based on ANCHOR-FREE and utilizes a fully convolutional training network with a Transformer module, suitable for RGB-THERMAL target tracking. This model addresses the issue of low success rate in current mainstream algorithms. We also incorporate channel and channel spatial attention modules into the network to reduce background interference on predicted bounding boxes. Unlike current ANCHOR-BASED trackers such as MANET, DAPNet, SGT, and ADNet, the proposed framework eliminates the use of anchor points, avoiding the challenges of anchor hyperparameter tuning and reducing human intervention. Through repeated experiments on three datasets, we ultimately demonstrate the improved success rate of target tracking achieved by our proposed tracking network.
Evaluation of drug-induced liver toxicity of trovafloxacin and levofloxacin in a human microphysiological liver model
Authors: Kaden Tim , Graf Katja , Rennert Knut , Li Ruoya , Mosig Alexander S. , Raasch Martin 
Published: August 2023

AbstractDrug-induced liver injury induced by already approved substances is a major threat to human patients, potentially resulting in drug withdrawal and substantial loss of financial resources in the pharmaceutical industry. Trovafloxacin, a broad-spectrum fluoroquinolone, was found to have unexpected side effects of severe hepatotoxicity, which was not detected by preclinical testing. To address the limitations of current drug testing strategies mainly involving 2D cell cultures and animal testing, a three-dimensional microphysiological model of the human liver containing expandable human liver sinusoidal endothelial cells, monocyte-derived macrophages and differentiated HepaRG cells was utilized to investigate the toxicity of trovafloxacin and compared it to the structurally-related non-toxic drug levofloxacin. In the model, trovafloxacin elicited vascular and hepatocellular toxicity associated with pro-inflammatory cytokine release already at clinically relevant concentrations, whereas levofloxacin did not provoke tissue injury. Similar to in vivo, cytokine secretion was dependent on a multicellular immune response, highlighting the potential of the complex microphysiological liver model for reliably detecting drug-related cytotoxicity in preclinical testing. Moreover, hepatic glutathione depletion and mitochondrial ROS formation were elucidated as intrinsic toxicity mechanisms contributing to trovafloxacin toxicity.
Effect of maternal serum magnesium and calcium levels on umbilical glial fibrillary acidic protein levels in preterm labor
Authors: Santoso Dhanny Primantara Johari , Nugrahani Annisa Dewi , Siddiq Amillia , Pramatirta Akhmad Yogi , Aziz Muhammad Alamsyah , Irianti Setyorini , Pribadi Adhi , Anwar Anita Deborah , Effendi Jusuf Sulaeman 
Published: August 2023

AbstractMagnesium can prevent astrocyte cell death and Glial Fibrillary Acidic Protein (GFAP) secretion as inflammatory marker in preterm delivery. This study was performed to analyze differences in umbilical cord GFAP levels in preterm labor given magnesium sulfate (MgSO4) as treatment group and control group and analyze the correlation between magnesium and calcium levels with umbilical GFAP levels. This quasi-experimental study was performed on 68 patients at Dr. Hasan Sadikin General Hospital from February-June 2021 consisting of 34 patients in each group. Maternal-umbilical cord magnesium levels, calcium levels, and GFAP levels were examined using ELISA test. The result was statistically measured by IBM SPSS 24.0. We found that there was a significant difference between maternal and umbilical magnesium levels and GFAP umbilical cord blood levels between the treatment and the control group (P < 0.05) in which GFAP level was higher in the control group. The multivariate analysis showed no significant relevance between mother magnesium and calcium level to umbilical cord GFAP level in the MgSO4 group. As conclusions, umbilical cord blood GFAP levels in preterm labor given MgSO4 were lower than in preterm deliveries who were not given MgSO4. There was no correlation between magnesium, calcium, and GFAP levels in the treatment group.
Association of the human gut microbiota with vascular stiffness
Authors: Cuadrat Rafael R. C. , Goris Tobias , Birukov Anna , Eichelmann Fabian , Andrade Bruno G. N. , Bang Corinna , Franke Andre , Wittenbecher Clemens , Schulze Matthias B. 
Published: August 2023

AbstractGut microbiota metabolites have been mechanistically linked to inflammatory pathway activation and atherosclerosis, which are major causes of vascular stiffness (VS). Aiming to investigate if the gut microbiome might be involved in VS development, we performed a cross-sectional study (n = 3,087), nested within the population-based European Prospective Investigations into Cancer and Nutrition (EPIC) Potsdam. We investigated the correlation of the gut microbiota (alpha diversity and taxa abundance) with 3 vascular stiffness measures: carotid-femoral (PWV), aortic augmentation index (AIX) and ankle-brachial index (ABI). Shannon index was not significantly associated with VS but the number of observed Amplicon Sequence Variants (ASV) was positively associated with PWV and AIX. We found a total of 19 ASVs significantly associated with at least one VS measure in multivariable-adjusted models. One ASV (classified as Sutterella wadsworthensis) was associated with 2 VS measures, AIX (− 0.11 ± 0.04) and PWV (-0.14 ± 0.03). Other examples of ASVs associated with VS were Collinsella aerofaciens, previously reported to be affected by diet and Bacteroides uniformis, commercially available as probiotics. In conclusion, our study suggests a potential role of individual components of the gut microbiota in the aetiology of VS.