bluuebunny/crossref_metadata_2025_split huggingface dataset:
Photo-induced non-volatile VO2 phase transition for neuromorphic ultraviolet sensors
Authors: Li Ge , Xie Donggang , Zhong Hai , Zhang Ziye , Fu Xingke , Zhou Qingli , Li Qiang , Ni Hao , Wang Jiaou , Guo Er-jia , He Meng , Wang Can , Yang Guozhen , Jin Kuijuan , Ge Chen 
Published: April 2022

AbstractIn the quest for emerging in-sensor computing, materials that respond to optical stimuli in conjunction with non-volatile phase transition are highly desired for realizing bioinspired neuromorphic vision components. Here, we report a non-volatile multi-level control of VO2 films by oxygen stoichiometry engineering under ultraviolet irradiation. Based on the reversible regulation of VO2 films using ultraviolet irradiation and electrolyte gating, we demonstrate a proof-of-principle neuromorphic ultraviolet sensor with integrated sensing, memory, and processing functions at room temperature, and also prove its silicon compatible potential through the wafer-scale integration of a neuromorphic sensor array. The device displays linear weight update with optical writing because its metallic phase proportion increases almost linearly with the light dosage. Moreover, the artificial neural network consisting of this neuromorphic sensor can extract ultraviolet information from the surrounding environment, and significantly improve the recognition accuracy from 24% to 93%. This work provides a path to design neuromorphic sensors and will facilitate the potential applications in artificial vision systems.
Fusion of Majorana bound states with mini-gate control in two-dimensional systems
Authors: Zhou Tong , Dartiailh Matthieu C. , Sardashti Kasra , Han Jong E. , Matos-Abiague Alex , Shabani Javad , Žutić Igor 
Published: April 2022

AbstractA hallmark of topological superconductivity is the non-Abelian statistics of Majorana bound states (MBS), its chargeless zero-energy emergent quasiparticles. The resulting fractionalization of a single electron, stored nonlocally as a two spatially-separated MBS, provides a powerful platform for implementing fault-tolerant topological quantum computing. However, despite intensive efforts, experimental support for MBS remains indirect and does not probe their non-Abelian statistics. Here we propose how to overcome this obstacle in mini-gate controlled planar Josephson junctions (JJs) and demonstrate non-Abelian statistics through MBS fusion, detected by charge sensing using a quantum point contact, based on dynamical simulations. The feasibility of preparing, manipulating, and fusing MBS in two-dimensional (2D) systems is supported in our experiments which demonstrate the gate control of topological transition and superconducting properties with five mini gates in InAs/Al-based JJs. While we focus on this well-established platform, where the topological superconductivity was already experimentally detected, our proposal to identify elusive non-Abelian statistics motivates also further MBS studies in other gate-controlled 2D systems.
Soil microbial metabolism on carbon and nitrogen transformation links the crop-residue contribution to soil organic carbon
Authors: Xie Zhihuang , Yu Zhenhua , Li Yansheng , Wang Guanghua , Liu Xiaobing , Tang Caixian , Lian Tengxiang , Adams Jonathan , Liu Junjie , Liu Judong , Herbert Stephen J. , Jin Jian 
Published: April 2022

AbstractThe beneficial effect of crop residue amendment on soil organic carbon (SOC) stock and stability depends on the functional response of soil microbial communities. Here we synchronized microbial metagenomic analysis, nuclear magnetic resonance and plant-15N labeling technologies to gain understanding of how microbial metabolic processes affect SOC accumulation in responses to differences in N supply from residues. Residue amendment brought increases in the assemblage of genes involved in C-degradation profiles from labile to recalcitrant C compounds as well as N mineralization. The N mineralization genes were correlated with the C and N accumulation in the particulate and mineral-associated C pools, and plant-derived aliphatic forms of SOC. Thus, the combined C and N metabolic potential of the microbial community transforms residue into persistent organic compounds, thereby increasing C and N sequestration in stable SOC pools. This study emphasizes potential microbially mediated mechanisms by which residue N affects C sequestration in soils.
Global spatiotemporally continuous MODIS land surface temperature dataset
Authors: Yu Pei , Zhao Tianjie , Shi Jiancheng , Ran Youhua , Jia Li , Ji Dabin , Xue Huazhu 
Published: April 2022

AbstractLand surface temperature (LST) plays a critical role in land surface processes. However, as one of the effective means for obtaining global LST observations, remote sensing observations are inherently affected by cloud cover, resulting in varying degrees of missing data in satellite-derived LST products. Here, we propose a solution. First, the data interpolating empirical orthogonal functions (DINEOF) method is used to reconstruct invalid LSTs in cloud-contaminated areas into ideal, clear-sky LSTs. Then, a cumulative distribution function (CDF) matching-based method is developed to correct the ideal, clear-sky LSTs to the real LSTs. Experimental results prove that this method can effectively reconstruct missing LST data and guarantee acceptable accuracy in most regions of the world, with RMSEs of 1–2 K and R values of 0.820–0.996 under ideal, clear-sky conditions and RMSEs of 4–7 K and R values of 0.811–0.933 under all weather conditions. Finally, a spatiotemporally continuous MODIS LST dataset at 0.05° latitude/longitude grids is produced based on the above method.
Drivers of tropical forest loss between 2008 and 2019
Authors: Laso Bayas Juan Carlos , See Linda , Georgieva Ivelina , Schepaschenko Dmitry , Danylo Olga , Dürauer Martina , Bartl Hedwig , Hofhansl Florian , Zadorozhniuk Roman , Burianchuk Maksym , Sirbu Flavius , Magori Brigitte , Blyshchyk Kateryna , Blyshchyk Volodymyr , Rabia Ahmed Harb , Pawe Chandra Kant , Su Yuan-Fong , Ahmed Merajuddin , Panging Kripal , Melnyk Oleksandr , Vasylyshyn Olesia , Vasylyshyn Roman , Bilous Andrii , Bilous Svitlana , Das Krishna , Prestele Reinhard , Pérez-Hoyos Ana , Bungnamei Khangsembou , Lashchenko Andrii , Lakyda Maryna , Lakyda Ivan , Serediuk Oleksandr , Domashovets Galyna , Yurchuk Yuriy , Koper Michèle , Fritz Steffen 
Published: April 2022

AbstractDuring December 2020, a crowdsourcing campaign to understand what has been driving tropical forest loss during the past decade was undertaken. For 2 weeks, 58 participants from several countries reviewed almost 115 K unique locations in the tropics, identifying drivers of forest loss (derived from the Global Forest Watch map) between 2008 and 2019. Previous studies have produced global maps of drivers of forest loss, but the current campaign increased the resolution and the sample size across the tropics to provide a more accurate mapping of crucial factors leading to forest loss. The data were collected using the Geo-Wiki platform (www.geo-wiki.org) where the participants were asked to select the predominant and secondary forest loss drivers amongst a list of potential factors indicating evidence of visible human impact such as roads, trails, or buildings. The data described here are openly available and can be employed to produce updated maps of tropical drivers of forest loss, which in turn can be used to support policy makers in their decision-making and inform the public.
A global map of planting years of plantations
Authors: Du Zhenrong , Yu Le , Yang Jianyu , Xu Yidi , Chen Bin , Peng Shushi , Zhang Tingting , Fu Haohuan , Harris Nancy , Gong Peng 
Published: April 2022

AbstractPlantation is an important land use type that differs from natural forests and affects the economy and the environment. Tree age is one of the key factors used to quantify the impact of plantations. However, there is a lack of datasets explicitly documenting the planting years of global plantations. Here we used time-series Landsat archive from 1982 to 2020 and the LandTrendr algorithm to generate global maps of planting years based on the global plantation extent products in Google Earth Engine (GEE) platform. The datasets developed in this study are in a GeoTIFF format with 30-meter spatial resolution by recording gridded specie types and planting years of global plantations. The derived dataset could be used for yield prediction of tree crops and social and ecological cost-benefit analysis of plantations.
AB-DB: Force-Field parameters, MD trajectories, QM-based data, and Descriptors of Antimicrobials
Authors: Gervasoni Silvia , Malloci Giuliano , Bosin Andrea , Vargiu Attilio V. , Zgurskaya Helen I. , Ruggerone Paolo 
Published: April 2022

AbstractAntibiotic resistance is a major threat to public health. The development of chemo-informatic tools to guide medicinal chemistry campaigns in the efficint design of antibacterial libraries is urgently needed. We present AB-DB, an open database of all-atom force-field parameters, molecular dynamics trajectories, quantum-mechanical properties, and curated physico-chemical descriptors of antimicrobial compounds. We considered more than 300 molecules belonging to 25 families that include the most relevant antibiotic classes in clinical use, such as β-lactams and (fluoro)quinolones, as well as inhibitors of key bacterial proteins. We provide traditional descriptors together with properties obtained with Density Functional Theory calculations. Noteworthy, AB-DB contains less conventional descriptors extracted from μs-long molecular dynamics simulations in explicit solvent. In addition, for each compound we make available force-field parameters for the major micro-species at physiological pH. With the rise of multi-drug-resistant pathogens and the consequent need for novel antibiotics, inhibitors, and drug re-purposing strategies, curated databases containing reliable and not straightforward properties facilitate the integration of data mining and statistics into the discovery of new antimicrobials.
Improved calibration of electrochemical aptamer-based sensors
Authors: Downs Alex M. , Gerson Julian , Leung Kaylyn K. , Honeywell Kevin M. , Kippin Tod , Plaxco Kevin W. 
Published: April 2022

AbstractElectrochemical aptamer-based (EAB) sensors support the real-time, high frequency measurement of pharmaceuticals and metabolites in-situ in the living body, rendering them a potentially powerful technology for both research and clinical applications. Here we explore quantification using EAB sensors, examining the impact of media selection and temperature on measurement performance. Using freshly-collected, undiluted whole blood at body temperature as both our calibration and measurement conditions, we demonstrate accuracy of better than ± 10% for the measurement of our test bed drug, vancomycin. Comparing titrations collected at room and body temperature, we find that matching the temperature of calibration curve collection to the temperature used during measurements improves quantification by reducing differences in sensor gain and binding curve midpoint. We likewise find that, because blood age impacts the sensor response, calibrating in freshly collected blood can improve quantification. Finally, we demonstrate the use of non-blood proxy media to achieve calibration without the need to collect fresh whole blood.
A deep learning model (FociRad) for automated detection of γ-H2AX foci and radiation dose estimation
Authors: Wanotayan Rujira , Chousangsuntorn Khaisang , Petisiwaveth Phasit , Anuttra Thunchanok , Lertchanyaphan Waritsara , Jaikuna Tanwiwat , Jangpatarapongsa Kulachart , Uttayarat Pimpon , Tongloy Teerawat , Chousangsuntorn Chousak , Boonsang Siridech 
Published: April 2022

AbstractDNA double-strand breaks (DSBs) are the most lethal form of damage to cells from irradiation. γ-H2AX (phosphorylated form of H2AX histone variant) has become one of the most reliable and sensitive biomarkers of DNA DSBs. However, the γ-H2AX foci assay still has limitations in the time consumed for manual scoring and possible variability between scorers. This study proposed a novel automated foci scoring method using a deep convolutional neural network based on a You-Only-Look-Once (YOLO) algorithm to quantify γ-H2AX foci in peripheral blood samples. FociRad, a two-stage deep learning approach, consisted of mononuclear cell (MNC) and γ-H2AX foci detections. Whole blood samples were irradiated with X-rays from a 6 MV linear accelerator at 1, 2, 4 or 6 Gy. Images were captured using confocal microscopy. Then, dose–response calibration curves were established and implemented with unseen dataset. The results of the FociRad model were comparable with manual scoring. MNC detection yielded 96.6% accuracy, 96.7% sensitivity and 96.5% specificity. γ-H2AX foci detection showed very good F1 scores (> 0.9). Implementation of calibration curve in the range of 0–4 Gy gave mean absolute difference of estimated doses less than 1 Gy compared to actual doses. In addition, the evaluation times of FociRad were very short (< 0.5 min per 100 images), while the time for manual scoring increased with the number of foci. In conclusion, FociRad was the first automated foci scoring method to use a YOLO algorithm with high detection performance and fast evaluation time, which opens the door for large-scale applications in radiation triage.
Bacteriocinogenic probiotic bacteria isolated from an aquatic environment inhibit the growth of food and fish pathogens
Authors: Pereira Wellison Amorim , Piazentin Anna Carolina M. , de Oliveira Rodrigo Cardoso , Mendonça Carlos Miguel N. , Tabata Yara Aiko , Mendes Maria Anita , Fock Ricardo Ambrósio , Makiyama Edson Naoto , Corrêa Benedito , Vallejo Marisol , Villalobos Elias Figueroa , de S. Oliveira Ricardo Pinheiro 
Published: April 2022

AbstractThe conditions of aquatic environments have a great influence on the microbiota of several animals, many of which are a potential source of microorganisms of biotechnological interest. In this study, bacterial strains isolated from aquatic environments were bioprospected to determine their probiotic profile and antimicrobial effect against fish and food pathogens. Two isolates, identified via 16S rRNA sequencing as Lactococcus lactis (L1 and L2) and one as Enterococcus faecium 135 (EF), produced a bacteriocin-like antimicrobial substance (BLIS), active against Listeria monocytogenes, Salmonella Choleraesuis and Salmonella Typhimurium. Antimicrobial activity of BLIS was reduced when exposed to high temperatures and proteolytic enzymes (trypsin, pepsin, papain and pancreatin). All strains were sensitive to 7 types of antibiotics (vancomycin, clindamycin, streptomycin, gentamicin, chloramphenicol, rifampicin and ampicillin), exhibited a high rate of adherence to Caco-2 cells and expressed no hemolysin and gelatinase virulence factors. EF showed some resistance at pH 2.5 and 3.0, and L2/EF showed higher resistance to the action of bile salts. Finally, the presence of bacteriocin genes encoding for proteins, including Nisin (L1 and L2), Enterocin A, B, P, and Mundticin KS (EF) was detected. The molecular and physiological evidence suggests that the bacterial isolates in this study could be used as natural antimicrobial agents and may be considered safe for probiotic application.
Tissue clearing may alter emission and absorption properties of common fluorophores
Authors: Eliat Farsam , Sohn Rebecca , Renner Henrik , Kagermeier Theresa , Volkery Stefan , Brinkmann Heike , Kirschnick Nils , Kiefer Friedemann , Grabos Martha , Becker Katharina , Bedzhov Ivan , Schöler Hans R. , Bruder Jan M. 
Published: April 2022

AbstractIn recent years, 3D cell culture has been gaining a more widespread following across many fields of biology. Tissue clearing enables optical analysis of intact 3D samples and investigation of molecular and structural mechanisms by homogenizing the refractive indices of tissues to make them nearly transparent. Here, we describe and quantify that common clearing solutions including benzyl alcohol/benzyl benzoate (BABB), PEG-associated solvent system (PEGASOS), immunolabeling-enabled imaging of solvent-cleared organs (iDISCO), clear, unobstructed brain/body imaging cocktails and computational analysis (CUBIC), and ScaleS4 alter the emission spectra of Alexa Fluor fluorophores and fluorescent dyes. Clearing modifies not only the emitted light intensity but also alters the absorption and emission peaks, at times to several tens of nanometers. The resulting shifts depend on the interplay of solvent, fluorophore, and the presence of cells. For biological applications, this increases the risk for unexpected channel crosstalk, as filter sets are usually not optimized for altered fluorophore emission spectra in clearing solutions. This becomes especially problematic in high throughput/high content campaigns, which often rely on multiband excitation to increase acquisition speed. Consequently, researchers relying on clearing in quantitative multiband excitation experiments should crosscheck their fluorescent signal after clearing in order to inform the proper selection of filter sets and fluorophores for analysis.
Magnetic UiO-66 functionalized with 4,4′-diamino-2,2′-stilbenedisulfonic as a highly recoverable acid catalyst for the synthesis of 4H-chromenes in green solvent
Authors: Khodabakhshi Mohammad Reza , Baghersad Mohammad Hadi 
Published: April 2022

AbstractAccording to 4H-chromenes importance, we synthesized a novel magnetic UiO-66 functionalized with 4,4′-diamino-2,2′-stilbenedisulfonic as an efficient and reusable solid acid catalyst for synthesizing 4H-chromene skeletons via a one-pot three components reaction in a green solvent. The structure of the synthesized catalyst was confirmed by various techniques including FT-IR, XRD, BET, TGA, TEM, EDX, and SEM, and also the product yields were obtained in 83–96% of yields for all the reactions and under mild conditions. The reported procedure presents an environmentally friendly approach for synthesizing a significant number of 4H-chromene derivatives. Correspondingly, MOF-based catalyst makes it easy to separate from reaction media and reuse in the next runs.
Identifying influential spreaders in complex networks for disease spread and control
Authors: Wei Xiang , Zhao Junchan , Liu Shuai , Wang Yisi 
Published: April 2022

AbstractIdentifying influential spreaders is an important task in controlling the spread of information and epidemic diseases in complex networks. Many recent studies have indicated that the identification of influential spreaders is dependent on the spreading dynamics. Finding a general optimal order of node importance ranking is difficult because of the complexity of network structures and the physical background of dynamics. In this paper, we use four metrics, namely, betweenness, degree, H-index, and coreness, to measure the central attributes of nodes for constructing the disease spreading models and target immunization strategies. Numerical simulations show that spreading processes based on betweenness centrality lead to the widest range of propagation and the smallest epidemic threshold for all six networks (including four real networks and two BA scale-free networks generated according to Barabasi–Albert algorithm). The target immunization strategy based on the betweenness centrality of nodes is the most effective for BA scale-free networks but displays poor immune effect for real networks in identifying the most important spreaders for disease control. The immunization strategy based on node degrees is the most effective for the four real networks. Findings show that the target immune strategy based on the betweenness centrality of nodes works best for standard scale-free networks, whereas that based on node degrees works best for other nonstandard scale-free networks. The results can provide insights into understanding the different metrics of measuring node importance in disease transmission and control.
Structural basis to repurpose boron-based proteasome inhibitors Bortezomib and Ixazomib as β-lactamase inhibitors
Authors: Perbandt Markus , Werner Nadine , Prester Andreas , Rohde Holger , Aepfelbacher Martin , Hinrichs Winfried , Betzel Christian 
Published: April 2022

Abstractβ-lactamases are a major cause of rapidly emerging and spreading antibiotic resistance. Currently β-lactamase inhibitors (BLIs) in clinical use act only on Ambler Class A, C and some class D lactamases. The urgent need to identify new BLIs recently lead to FDA approval of boron-based compounds BLIs, e.g. Vaborbactam. The boron-based proteasome inhibitors Bortezomib and Ixazomib are used in cancer therapy as multiple myeloma drugs but they also bind to Ser-/Thr- proteases. In this study we show the crystal structures of the β-lactamase CTX-M-14 with covalently bound Bortezomib and Ixazomib at high resolutions of 1.3 and 1.1 Å, respectively. Ixazomib is well defined in electron density whereas Bortezomib show some disorder which corresponds to weaker inhibition efficiency observed for Ixazomib. Both inhibitors mimic the deacylation transition state of β-lactam hydrolysis, because they replace the deacylating water molecule. We further investigate differences in binding of Bortezomib/Ixazomib to CTX-M-14 and its target proteases as well as known β-lactamase drugs. Our findings can help to use Bortezomib/Ixazomib as lead compounds for development of new BLIs.
Depression and cardiovascular disease are not linked by high blood pressure: findings from the SAPALDIA cohort
Authors: Obas Katrina A. , Kwiatkowski Marek , Schaffner Emmanuel , Lang Undine E. , Stolz Daiana , Eze Ikenna C. , Imboden Medea , Probst-Hensch Nicole 
Published: April 2022

AbstractDepression and cardiovascular disease (CVD) are main contributors to the global disease burden and are linked. Pathophysiological pathways through increased blood pressure (BP) are a common focus in studies aiming to explain the relationship. However, studies to date have not differentiated between the predictive effect of depression on the course of BP versus hypertension diagnosis. Hence, we aimed to elucidate this relationship by incorporating these novel aspects in the context of a cohort study. We included initially normotensive participants (n = 3214) from the second (2001–2003), third (2009–2011), and fourth (2016–2018) waves of the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA). We defined depression based on physician diagnosis, depression treatment and/or SF-36 Mental Health score < 50. The prospective association between depression and BP change was quantified using multivariable censored regression models, and logistic regression for the association between depression and incident hypertension diagnosis. All models used clustered robust standard errors to account for repeat measurements. The age-related increase in systolic BP was slightly lower among people with depression at baseline (β = − 2.08 mmHg/10 years, 95% CI − 4.09 to − 0.07) compared to non-depressed. A similar trend was observed with diastolic BP (β = − 0.88 mmHg/10 years, 95% CI − 2.15 to 0.39), albeit weaker and not statistically significant. Depression predicted the incidence of hypertension diagnosis (OR 1.86, 95% CI 1.33 to 2.60). Our findings do not support the hypothesis that depression leads to CVD by increasing BP. Future research on the role of depression in the pathway to hypertension and CVD is warranted in larger cohorts, taking into account healthcare utilization as well as medication for depression and hypertension.