bluuebunny/crossref_metadata_2025 huggingface dataset:
Factors Affecting Resiliency Among Volunteers in Disasters: A Systematic Literature Review
Authors: Ghodsi Hasan , Sohrabizadeh Sanaz , Khani Jazani Reaza , Kavousi Amir
Published: November 2020

Objective:

Volunteers need considerable resiliency to cope with formidable challenges during their operations in disaster scenes. The present study was conducted to identify factors affecting the different aspects of resiliency among volunteers in disasters.

Material and Methods:

The databases of Web of Science, Scopus, PubMed, ProQuest, Google Scholar, World Health Organization Library, International Committee of the Red Cross (ICRC) Library, PsycArticles, and SafetyLit were searched until September 29, 2018. The main search terms were resiliency, disaster, humanitarian aid worker, and volunteer.

Results:

A total of 548 documents were obtained and screened based on the inclusion and exclusion criteria. A number of 8 documents was selected for the final analysis. The main factors contributing to the resilience of volunteers at the 3 stages of pre-, during, and post-disasters were classified into 3 groups of individual, environmental, and organizational. Important factors affecting resilience of volunteers in disasters included previous disaster response experience and disaster-related training.

Conclusion:

Resiliency should be deemed integral to relief operations. Considering the main factors affecting volunteers’ resiliency, it is highly suggested that organizations active in humanitarian endeavors explore the factors impacting on resilience among their volunteers via various research methods and seek to select those with higher degrees of resilience in order to avert untoward consequences in their missions.
An Eye on the Future of COVID-19: Prediction of Likely Positive Cases and Fatality in India over a 30-Day Horizon Using the Prophet Model
Authors: Tulshyan Vatsal , Sharma Dolly , Mittal Mamta
Published: November 2020

Objective:

The coronavirus disease (COVID-19) pandemic was initiated in Wuhan Province of mainland China in December 2019 and has spread over the world. This study analyzes the effects of COVID-19 based on likely positive cases and fatality in India during and after the lockdown period from March 24, 2020, to May 24, 2020.

Methods:

Python has been used as the main programming language for data analysis and forecasting using the Prophet model, a time series analysis model. The data set has been preprocessed by grouping together the days for total numbers of cases and deaths on few selected dates and removing missing values present in some states.

Results:

The Prophet model performs better in terms of precision on the real data. Prediction depicts that, during the lockdown, the total cases were rising but in a controlled manner with an accuracy of 87%. After the relaxation of lockdown rules, the predictions have shown an obstreperous situation with an accuracy of 60%.

Conclusion:

The resilience could have been better if the lockdown with strict norms was continued without much relaxation. The situation after lockdown has been found to be uncertain as observed by the experimental study conducted in this work.
Solving the 4NLS with white noise initial data
Authors: Oh Tadahiro , Tzvetkov Nikolay , Wang Yuzhao
Published: November 2020

We construct global-in-time singular dynamics for the (renormalized) cubic fourth-order nonlinear Schrödinger equation on the circle, having the white noise measure as an invariant measure. For this purpose, we introduce the ‘random-resonant / nonlinear decomposition’, which allows us to single out the singular component of the solution. Unlike the classical McKean, Bourgain, Da Prato-Debussche type argument, this singular component is nonlinear, consisting of arbitrarily high powers of the random initial data. We also employ a random gauge transform, leading to random Fourier restriction norm spaces. For this problem, a contraction argument does not work, and we instead establish the convergence of smooth approximating solutions by studying the partially iterated Duhamel formulation under the random gauge transform. We reduce the crucial nonlinear estimates to boundedness properties of certain random multilinear functionals of the white noise.
Sensitivity of midturbinate versus nasopharyngeal swabs for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
Authors: Jamal Alainna J. , Mozafarihashjin Mohammad , Coomes Eric , Anceva-Sami Sofia , Barati Shiva , Crowl Gloria , Faheem Amna , Farooqi Lubna , Kandel Christopher E. , Khan Saman , Li Angel X. , Mistry Henna , Paterson Aimee , Plenderleith Simon , Prost Karren , Poutanen Susan , Powis Jeff , Schryer Renée , Taylor Maureen , Yip Lily , Zhong Xi Zoe , McGeer Allison J. , Mubareka Samira ,   for the Toronto Invasive Bacterial Diseases Network COVID-19 Investigators
Published: November 2020

To compare sensitivity of specimens for COVID-19 diagnosis, we tested 151 nasopharyngeal/midturbinate swab pairs from 117 COVID-19 inpatients using reverse-transcriptase polymerase chain reaction (RT-PCR). Sensitivity was 94% for nasopharyngeal and 75% for midturbinate swabs (P = .0001). In 88 nasopharyngeal/midturbinate pairs with matched saliva, sensitivity was 86% for nasopharyngeal swabs and 88% for combined midturbinate swabs/saliva.
A new classification on parallel Ricci tensor for real hypersurfaces in the complex quadric
Authors: Lee Hyunjin , Suh Young Jin
Published: November 2020

First we introduce the notion of parallel Ricci tensor ${\nabla }\mathrm {Ric}=0$ for real hypersurfaces in the complex quadric Qm = SOm+2/SOmSO2 and show that the unit normal vector field N is singular. Next we give a new classification of real hypersurfaces in the complex quadric Qm = SOm+2/SOmSO2 with parallel Ricci tensor.
Comparison of rule-based and neural network models for negation detection in radiology reports
Authors: Sykes D. , Grivas A. , Grover C. , Tobin R. , Sudlow C. , Whiteley W. , Mcintosh A. , Whalley H. , Alex B.
Published: November 2020

Using natural language processing, it is possible to extract structured information from raw text in the electronic health record (EHR) at reasonably high accuracy. However, the accurate distinction between negated and non-negated mentions of clinical terms remains a challenge. EHR text includes cases where diseases are stated not to be present or only hypothesised, meaning a disease can be mentioned in a report when it is not being reported as present. This makes tasks such as document classification and summarisation more difficult. We have developed the rule-based EdIE-R-Neg, part of an existing text mining pipeline called EdIE-R (Edinburgh Information Extraction for Radiology reports), developed to process brain imaging reports, (https://www.ltg.ed.ac.uk/software/edie-r/) and two machine learning approaches; one using a bidirectional long short-term memory network and another using a feedforward neural network. These were developed on data from the Edinburgh Stroke Study (ESS) and tested on data from routine reports from NHS Tayside (Tayside). Both datasets consist of written reports from medical scans. These models are compared with two existing rule-based models: pyConText (Harkema et al. 2009. Journal of Biomedical Informatics42(5), 839–851), a python implementation of a generalisation of NegEx, and NegBio (Peng et al. 2017. NegBio: A high-performance tool for negation and uncertainty detection in radiology reports. arXiv e-prints, p. arXiv:1712.05898), which identifies negation scopes through patterns applied to a syntactic representation of the sentence. On both the test set of the dataset from which our models were developed, as well as the largely similar Tayside test set, the neural network models and our custom-built rule-based system outperformed the existing methods. EdIE-R-Neg scored highest on F1 score, particularly on the test set of the Tayside dataset, from which no development data were used in these experiments, showing the power of custom-built rule-based systems for negation detection on datasets of this size. The performance gap of the machine learning models to EdIE-R-Neg on the Tayside test set was reduced through adding development Tayside data into the ESS training set, demonstrating the adaptability of the neural network models.
Food advertising during children’s television programmes in Italy
Authors: Gallus Silvano , Borroni Elisa , Stival Chiara , Kaur Sharanpreet , Davoli Sofia , Lugo Alessandra , Effertz Tobias , Garattini Silvio , Scaglioni Silvia
Published: November 2020

Objective:

Previous studies from European countries noted that food products promoted on TV for children did not comply with international guidelines, including the World Health Organization European Nutrient Profile Model (WHO-ENPM) and the EU Pledge Nutrition Criteria (EU-PNC, an initiative developed by leading food companies). We aim to provide new data from Italy.

Design:

Evaluation of Italian TV advertisements. Data on nutritional values for food product advertised were compared with nutritional standards issued by the WHO-ENPM and the EU-PNC.

Setting:

In total, 180 h of TV programmes from six Italian channels, 2016–2017.

Participants:

Eight hundred and ten consecutive advertisements during children’s programmes.

Results:

Out of 810 advertisements, 90 (11·1 %) referred to food products. Among these, 84·5 % of the foods promoted did not meet the WHO-ENPM and 55·6 % the EU-PNC guidelines. Advertisements promoting sweet and salty snacks (i.e. ≥ 70 % of all foods) v. other food products showed higher non-compliance with both the WHO-ENPM (OR: 73·8; 95 % CI: 4·09, 1330) and the EU-PNC (OR: 9·21; 95 % CI: 2·82, 30·1).

Conclusions:

In Italy, most food advertisements during children’s programmes are not compliant with European nutritional standards. Almost all the advertisements for snacks do not meet international guidelines. As the WHO-ENPM guidelines do not propose standards for all the food products, including meals, there is an urgent need to define independent and easy-to-read guidelines for food advertisements targeting children. As a first step towards the complete ban of food advertisements targeting children recommended by other researchers, these guidelines should be enforced by all the TV broadcasts.
Estimation of the IC to CG Ratio Using JEM‐GLIMS and Ground‐Based Lightning Network Data
Authors: Bandholnopparat K. , Sato M. , Adachi T. , Ushio T. , Takahashi Y.
Published: November 2020

The occurrence ratio of intracloud (IC) to cloud‐to‐ground (CG) discharges, which is denoted by Z‐ratio, is the crucial parameter for the studies on the global electric circuit. However, the latitudinal and regional dependences of Z‐ratio are not fully clarified. Therefore, using optical data obtained by the Global Lightning and Sprite Measurements on Japanese Experiment Module (JEM‐GLIMS), we distinguished the lightning discharge type, that is, IC, positive CG (+CG), and negative CG (−CG) discharges, and statistically estimated the Z‐ratio. We analyzed 8,354 lightning events that obtained by JEM‐GLIMS observation and succeeded in identifying 4,431 IC discharges, 597 +CG discharges, and 3,326 −CG discharges. From this result, we calculated the Z‐ratio over many regions around the world and estimated its latitudinal and regional dependences. It is found that the Z‐ratio over the continental area is larger than the oceanic area. We also found that the Z‐ratio significantly decreases with the latitude, which is generally comparable to the results shown in the previous studies. The estimated Z‐ratio varies from 2.9–0.29 from the equator to 50° latitude, and the global mean value is 1.6. The regional dependence of Z‐ratio derived from this study can be combined with the CG lightning data provided by the ground‐based lightning detection networks to estimate the occurrence number of IC discharges. Then, the occurrence number of both IC and CG discharges can be used for calculating a more accurate estimation of the total lightning currents in the global electric circuit.
Stream Dissolved Organic Matter in Permafrost Regions Shows Surprising Compositional Similarities but Negative Priming and Nutrient Effects
Authors: Wologo Ethan , Shakil Sarah , Zolkos Scott , Textor Sadie , Ewing Stephanie , Klassen Jane , Spencer Robert G. M. , Podgorski David C. , Tank Suzanne E. , Baker Michelle A. , O'Donnell Jonathan A. , Wickland Kimberly P. , Foks Sydney S. W. , Zarnetske Jay P. , Lee‐Cullin Joseph , Liu Futing , Yang Yuanhe , Kortelainen Pirkko , Kolehmainen Jaana , Dean Joshua F. , Vonk Jorien E. , Holmes Robert M. , Pinay Gilles , Powell Michaela M. , Howe Jansen , Frei Rebecca J. , Bratsman Samuel P. , Abbott Benjamin W.
Published: November 2020

Permafrost degradation is delivering bioavailable dissolved organic matter (DOM) and inorganic nutrients to surface water networks. While these permafrost subsidies represent a small portion of total fluvial DOM and nutrient fluxes, they could influence food webs and net ecosystem carbon balance via priming or nutrient effects that destabilize background DOM. We investigated how addition of biolabile carbon (acetate) and inorganic nutrients (nitrogen and phosphorus) affected DOM decomposition with 28‐day incubations. We incubated late‐summer stream water from 23 locations nested in seven northern or high‐altitude regions in Asia, Europe, and North America. DOM loss ranged from 3% to 52%, showing a variety of longitudinal patterns within stream networks. DOM optical properties varied widely, but DOM showed compositional similarity based on Fourier transform ion cyclotron resonance mass spectrometry (FT‐ICR MS) analysis. Addition of acetate and nutrients decreased bulk DOM mineralization (i.e., negative priming), with more negative effects on biodegradable DOM but neutral or positive effects on stable DOM. Unexpectedly, acetate and nutrients triggered breakdown of colored DOM (CDOM), with median decreases of 1.6% in the control and 22% in the amended treatment. Additionally, the uptake of added acetate was strongly limited by nutrient availability across sites. These findings suggest that biolabile DOM and nutrients released from degrading permafrost may decrease background DOM mineralization but alter stoichiometry and light conditions in receiving waterbodies. We conclude that priming and nutrient effects are coupled in northern aquatic ecosystems and that quantifying two‐way interactions between DOM properties and environmental conditions could resolve conflicting observations about the drivers of DOM in permafrost zone waterways.
Simultaneously Formed Wedge‐Like Structures of Different Ion Species Deep in the Inner Magnetosphere
Authors: Ren Jie , Zong Q. G. , Yue C. , Zhou X. Z. , Fu S. Y. , Spence H. E. , Funsten H. O.
Published: November 2020

In this study, ion data from the Helium, Oxygen, Proton, and Electron (HOPE) spectrometers onboard Van Allen Probes reveal the existence of wedge‐like structures of O+, He+, and H+ ions deep in the inner magnetosphere. The behaviors of the wedge‐like structures in terms of temporal evolution, spatial distribution, upper energy limit, as well as dependence on solar wind and different geomagnetic indices are investigated from both event studies of several consecutive orbits on 3 February 2013 and the subsequent statistical analyses using 4 years of data. Unlike the dominant distribution at
–8 in the dayside observed by the polar orbit satellites in previous studies, the wedge‐like structures deep in the equatorial plane of the inner magnetosphere are found mostly at the Mcllwain L shells of
–5 and have a preferential location in the duskside and nightside. The O+ and He+ structures can extend to smaller L shells with higher upper energy limits than the H+ structures, while the upper energy limits of all these particle species show a similar variation tendency with respect to magnetic local time (MLT) and L. Observations indicate that these wedge‐like structures are probably attributed to fresh substorm injections from the outer region.
In Situ Observations of Microphysics, Electric Fields, and Lightning in the Trailing Stratiform Region of a Mesoscale Convective System
Authors: Detwiler Andrew , Kennedy Patrick
Published: November 2020

We use in situ airborne observations to extend a previous analysis by Lang and Rutledge (2008; https://doi.org/10.1029/2006JD007709) of remotely sensed radar and lightning mapping array observations of the 11 June 2000 asymmetric mesoscale convective system (MCS) that moved through the primary observation region of the Severe Thunderstorm Electrification/Precipitation Study in northeastern Colorado and northwestern Kansas. We analyze in detail in situ aircraft observations, radar, and remotely mapped lightning discharges from a portion of the MCS that was starting to produce a bow echo during the time of the aircraft mission. The observations are interpreted to indicate the presence of a rearward and downward‐sloping positive charge layer detraining from a mature cell near the leading convective region. In the convective cell the positive charge region was at an altitude of ~10 km MSL. It then descended rearward, crossing the 6 km MSL altitude plane ~40 km to the rear of the leading convective region. During an 8‐min period, three major lightning discharges initiated in the convective region and propagated rearward into the trailing stratiform region in association with this positive charge layer. Airborne in situ microphysical and electrical observations suggest that the charge layer in the stratiform region of the storm during this period resulted from charge separation in the convective region and transport from there into the stratiform region. Microphysical and meteorological conditions in the stratiform region were not supportive of significant in situ charge separation in this portion of the stratiform region during this time period.
Plant Hydraulic Stress Strategy Improves Model Predictions of the Response of Gross Primary Productivity to Drought Across China
Authors: Wu Haohao , Fu Congsheng , Wu Huawu , Zhang Lingling
Published: November 2020

The response of the terrestrial carbon cycle to droughts, which have recently increased in incidence and severity, is a hot topic in research, but the role played by vegetation water use strategies remains unclear. Both the soil moisture stress (SMS) and plant hydraulic stress (PHS) strategies are used in land surface models, but their performance in simulating the terrestrial carbon cycle and its response to droughts in various climatic zones remains uncertain. In this study, we used Community Land Model Version 5 to simulate gross primary productivity (GPP) across four different climatic subregions of China during 2000–2015 to investigate the roles played by PHS and SMS in the response of GPP to dry events and dry or rainy years in various climate zones. Simulated GPP with the two strategies were overestimated by 2.0–2.3% for the entire China compared to Moderate Resolution Imaging Spectroradiometer (MODIS) data. GPP simulated using PHS configuration fit eddy covariance and MODIS data better than that obtained using SMS across China, except for the Qinghai‐Tibet Plateau. PHS increased simulated GPP by 0.10–0.63 g C m−2 day−1 during dry events across different climatic regions because of root hydraulic lift but decreased GPP by 0.37–0.45 g C m−2 day−1 during growing season in the humid southeastern region because of high atmospheric vapor pressure deficit and root hydraulic descent. Simulations forced by data collected locally in China performed better than those forced by CRUNCEP7 global data at the site but worse at the regional scale, in particular for the Qinghai‐Tibet Plateau.
Nonlinear ionization dynamics of hot dense plasma observed in a laser-plasma amplifier
Authors: Tuitje F. , Martínez Gil P. , Helk T. , Gautier J. , Tissandier F. , Goddet J.-P. , Guggenmos A. , Kleineberg U. , Sebban S. , Oliva E. , Spielmann C. , Zürch M.
Published: November 2020

Understanding the behaviour of matter under conditions of extreme temperature, pressure, density and electromagnetic fields has profound effects on our understanding of cosmologic objects and the formation of the universe. Lacking direct access to such objects, our interpretation of observed data mainly relies on theoretical models. However, such models, which need to encompass nuclear physics, atomic physics and plasma physics over a huge dynamic range in the dimensions of energy and time, can only provide reliable information if we can benchmark them to experiments under well-defined laboratory conditions. Due to the plethora of effects occurring in this kind of highly excited matter, characterizing isolated dynamics or obtaining direct insight remains challenging. High-density plasmas are turbulent and opaque for radiation below the plasma frequency and allow only near-surface insight into ionization processes with visible wavelengths. Here, the output of a high-harmonic seeded laser-plasma amplifier using eight-fold ionized krypton as the gain medium operating at a 32.8 nm wavelength is ptychographically imaged. A complex-valued wavefront is observed in the extreme ultraviolet (XUV) beam with high resolution. Ab initio spatio-temporal Maxwell–Bloch simulations show excellent agreement with the experimental observations, revealing overionization of krypton in the plasma channel due to nonlinear laser-plasma interactions, successfully validating this four-dimensional multiscale model. This constitutes the first experimental observation of the laser ion abundance reshaping a laser-plasma amplifier. The presented approach shows the possibility of directly modelling light-plasma interactions in extreme conditions, such as those present during the early times of the universe, with direct experimental verification.
Anaerobic bacterial degradation of protein and lipid macromolecules in subarctic marine sediment
Authors: Pelikan Claus , Wasmund Kenneth , Glombitza Clemens , Hausmann Bela , Herbold Craig W , Flieder Mathias , Loy Alexander
Published: November 2020

Microorganisms in marine sediments play major roles in marine biogeochemical cycles by mineralizing substantial quantities of organic matter from decaying cells. Proteins and lipids are abundant components of necromass, yet the taxonomic identities of microorganisms that actively degrade them remain poorly resolved. Here, we revealed identities, trophic interactions, and genomic features of bacteria that degraded 13C-labeled proteins and lipids in cold anoxic microcosms containing sulfidic subarctic marine sediment. Supplemented proteins and lipids were rapidly fermented to various volatile fatty acids within 5 days. DNA-stable isotope probing (SIP) suggested Psychrilyobacter atlanticus was an important primary degrader of proteins, and Psychromonas members were important primary degraders of both proteins and lipids. Closely related Psychromonas populations, as represented by distinct 16S rRNA gene variants, differentially utilized either proteins or lipids. DNA-SIP also showed 13C-labeling of various Deltaproteobacteria within 10 days, indicating trophic transfer of carbon to putative sulfate-reducers. Metagenome-assembled genomes revealed the primary hydrolyzers encoded secreted peptidases or lipases, and enzymes for catabolism of protein or lipid degradation products. Psychromonas species are prevalent in diverse marine sediments, suggesting they are important players in organic carbon processing in situ. Together, this study provides new insights into the identities, functions, and genomes of bacteria that actively degrade abundant necromass macromolecules in the seafloor.
Exploring autoantibody signatures in brain tissue from patients with severe mental illness
Authors: Just David , Månberg Anna , Mitsios Nicholas , Stockmeier Craig A. , Rajkowska Grazyna , Uhlén Mathias , Mulder Jan , Feuk Lars , Cunningham Janet L. , Nilsson Peter , Carlström Eva Lindholm
Published: November 2020

In recent years, studies have shown higher prevalence of autoantibodies in patients with schizophrenia compared to healthy individuals. This study applies an untargeted and a targeted affinity proteomics approach to explore and characterize the autoantibody repertoire in brain tissues from 73 subjects diagnosed with schizophrenia and 52 control subjects with no psychiatric or neurological disorders. Selected brain tissue lysates were first explored for IgG reactivity on planar microarrays composed of 11,520 protein fragments representing 10,820 unique proteins. Based on these results of ours and other previous studies of autoantibodies related to psychosis, we selected 226 fragments with an average length of 80 amino acids, representing 127 unique proteins. Tissue-based analysis of IgG reactivities using antigen suspension bead arrays was performed in a multiplex and parallel fashion for all 125 subjects. Among the detected autoantigens, higher IgG reactivity in subjects with schizophrenia, as compared to psychiatrically healthy subjects, was found against the glutamate ionotropic receptor NMDA type subunit 2D (anti-GluN2D). In a separate cohort with serum samples from 395 young adults with a wider spectrum of psychiatric disorders, higher levels of serum autoantibodies targeting GluN2D were found when compared to 102 control individuals. By further validating GluN2D and additional potential autoantigens, we will seek insights into how these are associated with severe mental illnesses.
The genomic timeline of cichlid fish diversification across continents
Authors: Matschiner Michael , Böhne Astrid , Ronco Fabrizia , Salzburger Walter
Published: November 2020

Cichlid fishes are celebrated for their vast taxonomic, phenotypic, and ecological diversity; however, a central aspect of their evolution — the timeline of their diversification — remains contentious. Here, we generate draft genome assemblies of 14 species representing the global cichlid diversity and integrate these into a new phylogenomic hypothesis of cichlid and teleost evolution that we time-calibrate with 58 re-evaluated fossil constraints and a new Bayesian model accounting for fossil-assignment uncertainty. Our results support cichlid diversification long after the breakup of the supercontinent Gondwana and lay the foundation for precise temporal reconstructions of the exceptional continental cichlid adaptive radiations.
Synthetic strategies of supported atomic clusters for heterogeneous catalysis
Authors: Rong Hongpan , Ji Shufang , Zhang Jiatao , Wang Dingsheng , Li Yadong
Published: November 2020

Supported atomic clusters with uniform metal sites and definite low-nuclearity are intermediate states between single-atom catalysts (SACs) and nanoparticles in size. Benefiting from the presence of metal–metal bonds, supported atomic clusters can trigger synergistic effects among every metal atom, which contributes to achieving unique catalytic properties different from SACs and nanoparticles. However, the scalable and precise synthesis and atomic-level insights into the structure–properties relationship of supported atomic clusters is a great challenge. This perspective presents the latest progress of the synthesis of supported atomic clusters, highlights how the structure affects catalytic properties, and discusses the limitations as well as prospects.
Fibronectin-based nanomechanical biosensors to map 3D surface strains in live cells and tissue
Authors: Shiwarski Daniel J. , Tashman Joshua W. , Tsamis Alkiviadis , Bliley Jaci M. , Blundon Malachi A. , Aranda-Michel Edgar , Jallerat Quentin , Szymanski John M. , McCartney Brooke M. , Feinberg Adam W.
Published: November 2020

Mechanical forces are integral to cellular migration, differentiation and tissue morphogenesis; however, it has proved challenging to directly measure strain at high spatial resolution with minimal perturbation in living sytems. Here, we fabricate, calibrate, and test a fibronectin (FN)-based nanomechanical biosensor (NMBS) that can be applied to the surface of cells and tissues to measure the magnitude, direction, and strain dynamics from subcellular to tissue length-scales. The NMBS is a fluorescently-labeled, ultra-thin FN lattice-mesh with spatial resolution tailored by adjusting the width and spacing of the lattice from 2–100 µm. Time-lapse 3D confocal imaging of the NMBS demonstrates 2D and 3D surface strain tracking during mechanical deformation of known materials and is validated with finite element modeling. Analysis of the NMBS applied to single cells, cell monolayers, and Drosophila ovarioles highlights the NMBS’s ability to dynamically track microscopic tensile and compressive strains across diverse biological systems where forces guide structure and function.
High-dimensional super-resolution imaging reveals heterogeneity and dynamics of subcellular lipid membranes
Authors: Zhanghao Karl , Liu Wenhui , Li Meiqi , Wu Zihan , Wang Xiao , Chen Xingye , Shan Chunyan , Wang Haoqian , Chen Xiaowei , Dai Qionghai , Xi Peng , Jin Dayong
Published: November 2020

Lipid membranes are found in most intracellular organelles, and their heterogeneities play an essential role in regulating the organelles’ biochemical functionalities. Here we report a Spectrum and Polarization Optical Tomography (SPOT) technique to study the subcellular lipidomics in live cells. Simply using one dye that universally stains the lipid membranes, SPOT can simultaneously resolve the membrane morphology, polarity, and phase from the three optical-dimensions of intensity, spectrum, and polarization, respectively. These high-throughput optical properties reveal lipid heterogeneities of ten subcellular compartments, at different developmental stages, and even within the same organelle. Furthermore, we obtain real-time monitoring of the multi-organelle interactive activities of cell division and successfully reveal their sophisticated lipid dynamics during the plasma membrane separation, tunneling nanotubules formation, and mitochondrial cristae dissociation. This work suggests research frontiers in correlating single-cell super-resolution lipidomics with multiplexed imaging of organelle interactome.
Voltage-driven motion of nitrogen ions: a new paradigm for magneto-ionics
Authors: de Rojas Julius , Quintana Alberto , Lopeandía Aitor , Salguero Joaquín , Muñiz Beatriz , Ibrahim Fatima , Chshiev Mairbek , Nicolenco Aliona , Liedke Maciej O. , Butterling Maik , Wagner Andreas , Sireus Veronica , Abad Llibertat , Jensen Christopher J. , Liu Kai , Nogués Josep , Costa-Krämer José L. , Menéndez Enric , Sort Jordi
Published: November 2020

Magneto-ionics, understood as voltage-driven ion transport in magnetic materials, has largely relied on controlled migration of oxygen ions. Here, we demonstrate room-temperature voltage-driven nitrogen transport (i.e., nitrogen magneto-ionics) by electrolyte-gating of a CoN film. Nitrogen magneto-ionics in CoN is compared to oxygen magneto-ionics in Co3O4. Both materials are nanocrystalline (face-centered cubic structure) and show reversible voltage-driven ON-OFF ferromagnetism. In contrast to oxygen, nitrogen transport occurs uniformly creating a plane-wave-like migration front, without assistance of diffusion channels. Remarkably, nitrogen magneto-ionics requires lower threshold voltages and exhibits enhanced rates and cyclability. This is due to the lower activation energy for ion diffusion and the lower electronegativity of nitrogen compared to oxygen. These results may open new avenues in applications such as brain-inspired computing or iontronics in general.
Myeloid Krüppel-like factor 2 is a critical regulator of metabolic inflammation
Authors: Sweet David R. , Vasudevan Neelakantan T. , Fan Liyan , Booth Chloe E. , Keerthy Komal S. , Liao Xudong , Vinayachandran Vinesh , Takami Yoichi , Tugal Derin , Sharma Nikunj , Chan E. Ricky , Zhang Lilei , Qing Yulan , Gerson Stanton L. , Fu Chen , Wynshaw-Boris Anthony , Sangwung Panjamaporn , Nayak Lalitha , Holvoet Paul , Matoba Keiichiro , Lu Yuan , Zhou Guangjin , Jain Mukesh K.
Published: November 2020

Substantial evidence implicates crosstalk between metabolic tissues and the immune system in the inception and progression of obesity. However, molecular regulators that orchestrate metaflammation both centrally and peripherally remains incompletely understood. Here, we identify myeloid Krüppel-like factor 2 (KLF2) as an essential regulator of obesity and its sequelae. In mice and humans, consumption of a fatty diet downregulates myeloid KLF2 levels. Under basal conditions, myeloid-specific KLF2 knockout mice (K2KO) exhibit increased feeding and weight gain. High-fat diet (HFD) feeding further exacerbates the K2KO metabolic disease phenotype. Mechanistically, loss of myeloid KLF2 increases metaflammation in peripheral and central tissues. A combination of pair-feeding, bone marrow-transplant, and microglial ablation implicate central and peripheral contributions to K2KO-induced metabolic dysfunction observed. Finally, overexpression of myeloid KLF2 protects mice from HFD-induced obesity and insulin resistance. Together, these data establish myeloid KLF2 as a nodal regulator of central and peripheral metabolic inflammation in homeostasis and disease.
Corrosion inhibition of copper in ferric chloride solutions with organic inhibitors
Authors: Sisso Omer , Dor Snir , Eliyahu David , Sabatani Eyal , Eliaz Noam
Published: November 2020

Ferric chloride (FeCl3) has widespread use as an etchant in the PCB industry and for photochemical machining. Although the corrosion process of copper in FeCl3is well known, the use of organic inhibitors of copper corrosion in FeCl3solutions has not been reported. Such inhibition may allow microfabrication of special PCB designs and electrochemical sensors. Here, we investigate the inhibition of copper corrosion by FeCl3(0.10 or 2.46 M) solutions with organic inhibitors. The most promising inhibitors are identified, investigated in 0.01 M FeCl3solution using electrochemical techniques at different temperatures and exposure times, and the modified surfaces of copper are characterized by a variety of techniques in order to determine the inhibition mechanism. 5-methyl-1H-benzotriazole (MBTA, 65 mM) and 1H-benzotriazole (BTA, 65 mM) are found to be the most attractive inhibitors, with inhibition efficiencies between 96.5% and 99.5% at room temperature, depending on the exposure time and the measurement technique.
Smoke and Alcohol Free with EHealth and Rewards (SAFER) pregnancy study: a before−after study protocol
Authors: Breunis Leonieke J. , de Kroon Marlou L. A. , Laureij Lyzette T. , de Jong-Potjer Lieke , Steegers Eric A. P. , Been Jasper V.
Published: November 2020

Despite existing interventions, tobacco smoking and alcohol consumption during pregnancy are common. The Smoke and Alcohol Free with EHealth and Rewards (SAFER) pregnancy intervention combines monthly group sessions, access to a web-based platform and incentives upon biochemically validated cessation for a maximum duration of 6 months to promote cessation of smoking and alcohol use before and during pregnancy. To inform development of the SAFER pregnancy intervention, two focus groups with the target population were held beforehand, with results reported here alongside the final SAFER pregnancy study protocol. In a before−after study we aim to include 66 women who are pregnant or have a wish to become pregnant and who smoke and/or consume alcohol (i.e. target population of the SAFER pregnancy intervention). The primary outcome measure is cessation of smoking and/or alcohol use at 34−38 weeks of gestation, or after six group sessions if women did not become pregnant during the study period. Secondary outcomes focus on the barriers and facilitators for implementation of the SAFER pregnancy intervention.
QM-symex, update of the QM-sym database with excited state information for 173 kilo molecules
Authors: Liang Jiechun , Ye Shuqian , Dai Tianshu , Zha Ziyue , Gao Yuechen , Zhu Xi
Published: November 2020

In the research field of material science, quantum chemistry database plays an indispensable role in determining the structure and properties of new material molecules and in deep learning in this field. A new quantum chemistry database, the QM-sym, has been set up in our previous work. The QM-sym is an open-access database focusing on transition states, energy, and orbital symmetry. In this work, we put forward the QM-symex with 173-kilo molecules. Each organic molecular in the QM-symex combines with the Cnh symmetry composite and contains the information of the first ten singlet and triplet transitions, including energy, wavelength, orbital symmetry, oscillator strength, and other quasi-molecular properties. QM-symex serves as a benchmark for quantum chemical machine learning models that can be effectively used to train new models of excited states in the quantum chemistry region as well as contribute to further development of the green energy revolution and materials discovery.
The ongoing nutrition transition thwarts long-term targets for food security, public health and environmental protection
Authors: Bodirsky Benjamin Leon , Dietrich Jan Philipp , Martinelli Eleonora , Stenstad Antonia , Pradhan Prajal , Gabrysch Sabine , Mishra Abhijeet , Weindl Isabelle , Le Mouël Chantal , Rolinski Susanne , Baumstark Lavinia , Wang Xiaoxi , Waid Jillian L. , Lotze-Campen Hermann , Popp Alexander
Published: November 2020

The nutrition transition transforms food systems globally and shapes public health and environmental change. Here we provide a global forward-looking assessment of a continued nutrition transition and its interlinked symptoms in respect to food consumption. These symptoms range from underweight and unbalanced diets to obesity, food waste and environmental pressure. We find that by 2050, 45% (39–52%) of the world population will be overweight and 16% (13–20%) obese, compared to 29% and 9% in 2010 respectively. The prevalence of underweight approximately halves but absolute numbers stagnate at 0.4–0.7 billion. Aligned, dietary composition shifts towards animal-source foods and empty calories, while the consumption of vegetables, fruits and nuts increases insufficiently. Population growth, ageing, increasing body mass and more wasteful consumption patterns are jointly pushing global food demand from 30 to 45 (43–47) Exajoules. Our comprehensive open dataset and model provides the interfaces necessary for integrated studies of global health, food systems, and environmental change. Achieving zero hunger, healthy diets, and a food demand compatible with environmental boundaries necessitates a coordinated redirection of the nutrition transition. Reducing household waste, animal-source foods, and overweight could synergistically address multiple symptoms at once, while eliminating underweight would not substantially increase food demand.
Comprehensive ESI-Q TRAP-MS/MS based characterization of metabolome of two mango (Mangifera indica L) cultivars from China
Authors: Tan Lin , Jin Zhiqiang , Ge Yu , Nadeem Habibullah , Cheng Zhihao , Azeem Farrukh , Zhan Rulin
Published: November 2020

Polyphenols based bioactive compounds from vegetables and fruits are known for impressive antioxidant activity. Ingestion of these antioxidants may promote human health against cardiovascular diseases and cancer. Mango is a popular tropical fruit with special taste, high nutritional value and health-enhancing metabolites. The aim was to investigate the diversity of phytochemicals between two mango cultivars of china at three stages of fruit maturity. We used ESI-QTRAP-MS/MS approach to characterize comprehensively the metabolome of two mango cultivars named Hongguifei (HGF) and Tainong (TN). HPLC was used to quantify selected catechin based phenolic compounds. Moreover, real-time qPCR was used to study the expression profiles of two key genes (ANR and LAR) involved in proanthocyanidin biosynthesis from catechins and derivatives. A total of 651 metabolites were identified, which include at least 257 phenolic compounds. Higher number of metabolites were differentially modulated in peel as compared to pulp. Overall, the relative quantities of amino acids, carbohydrates, organic acids, and other metabolites were increased in the pulp of TN cultivar. While the contents of phenolic compounds were relatively higher in HGF cultivar. Moreover, HPLC based quantification of catechin and derivatives exhibited cultivar specific variations. The ANR and LAR genes exhibited an opposite expression profile in both cultivars. Current study is the first report of numerous metabolites including catechin-based derivatives in mango fruit. These findings open novel possibilities for the use of mango as a source of bioactive compounds.
Synthesis of lignin-derived nitrogen-doped carbon as a novel catalyst for 4-NP reduction evaluation
Authors: Liu Yun , Xu Huanghui , Yu Hongfei , Yang Haihua , Chen Tao
Published: November 2020

In this study, nitrogen-doped carbon (NC) was fabricated using lignin as carbon source and g-C3N4 as sacrificial template and nitrogen source. The structural properties of as-prepared NC were characterized by TEM, XRD, FT-IR, Raman, XPS and BET techniques. Attractively, NC has proved efficient for reducing 4-nitrophenol (4-NP) to 4-aminophenol (4-AP) using NaBH4 as hydrogen donor with high apparent rate constant (kapp = 4.77 min−1) and specific mass activity (s = 361 mol kgcat−1 h−1), which values are superior to the previously reported catalysts in the literature. Density functional theory (DFT) calculations demonstrate that four kinds of N dopants can change the electronic structure of the adjacent carbon atoms and contribute to their catalytic properties dependant on N species, however, graphitic N species has much greater contribution to 4-NP adsorption and catalytic reduction. Furthermore, The preliminary mechanism of this transfer hydrogenation reaction over as-prepared NC is proposed on the basis of XPS and DFT data. Astoundingly, NC has excellent stability and reusability of six consecutive runs without loss of catalytic activity. These findings open up a vista to engineer lignin-derived NC as metal-free catalyst for hydrogenation reaction.
A combined transcriptomic approach to identify candidates for an anti-tick vaccine blocking B. afzelii transmission
Authors: Trentelman Jos J. A. , Sima Radek , Krezdorn Nicolas , Tomás-Cortázar Julen , Barriales Diego , Takumi Katsuhisa , Butler Joe M. , Sprong Hein , Klouwens Michelle J. , Urbanova Veronika , Mahmood Sazzad , Winter Peter , Kopacek Petr , Anguita Juan , Hajdusek Ondrej , Hovius Joppe W.
Published: November 2020

Ixodes ricinus is the vector for Borrelia afzelii, the predominant cause of Lyme borreliosis in Europe, whereas Ixodes scapularis is the vector for Borrelia burgdorferi in the USA. Transcription of several I. scapularis genes changes in the presence of B. burgdorferi and contributes to successful infection. To what extend B. afzelii influences gene expression in I. ricinus salivary glands is largely unknown. Therefore, we measured expression of uninfected vs. infected tick salivary gland genes during tick feeding using Massive Analysis of cDNA Ends (MACE) and RNAseq, quantifying 26.179 unique transcripts. While tick feeding was the main differentiator, B. afzelii infection significantly affected expression of hundreds of transcripts, including 465 transcripts after 24 h of tick feeding. Validation of the top-20 B. afzelii-upregulated transcripts at 24 h of tick feeding in ten biological genetic distinct replicates showed that expression varied extensively. Three transcripts could be validated, a basic tail protein, a lipocalin and an ixodegrin, and might be involved in B. afzelii transmission. However, vaccination with recombinant forms of these proteins only marginally altered B. afzelii infection in I. ricinus-challenged mice for one of the proteins. Collectively, our data show that identification of tick salivary genes upregulated in the presence of pathogens could serve to identify potential pathogen-blocking vaccine candidates.
Multicellular contractility contributes to the emergence of mesothelioma nodules
Authors: Tarnoki-Zach Julia , Stockhammer Paul , Isai Dona Greta , Mehes Elod , Szeder Balint , Kovacs Ildiko , Bugyik Edina , Paku Sandor , Berger Walter , Thomas Sufi Mary , Neufeld Zoltan , Dome Balazs , Hegedus Balazs , Czirok Andras
Published: November 2020

Malignant pleural mesothelioma (MPM) has an overall poor prognosis and unsatisfactory treatment options. MPM nodules, protruding into the pleural cavity may have growth and spreading dynamics distinct that of other solid tumors. We demonstrate that multicellular aggregates can develop spontaneously in the majority of tested MPM cell lines when cultured at high cell density. Surprisingly, the nodule-like aggregates do not arise by excessive local cell proliferation, but by myosin II-driven cell contractility. Prominent actin cables, spanning several cells, are abundant both in cultured aggregates and in MPM surgical specimens. We propose a computational model for in vitro MPM nodule development. Such a self-tensioned Maxwell fluid exhibits a pattern-forming instability that was studied by analytical tools and computer simulations. Altogether, our findings may underline a rational for targeting the actomyosin system in MPM.
A novel patient-derived orthotopic xenograft (PDOX) mouse model of highly-aggressive liver metastasis for identification of candidate effective drug-combinations
Authors: Zhang Zhiying , Hu Kaiwen , Miyake Kentaro , Kiyuna Tasuku , Oshiro Hiromichi , Wangsiricharoen Sintawat , Kawaguchi Kei , Higuchi Takashi , Razmjooei Sahar , Miyake Masuyo , Chawla Sant P. , Singh Shree Ram , Hoffman Robert M.
Published: November 2020

Liver metastasis is a recalcitrant disease that usually leads to death of the patient. The present study established a unique patient-derived orthotopic xenograft (PDOX) nude mouse model of a highly aggressive liver metastasis of colon cancer. The aim of the present study was to demonstrate proof-of-concept that candidate drug combinations could significantly inhibit growth and re-metastasis of this recalcitrant tumor. The patient’s liver metastasis was initially established subcutaneously in nude mice and the subcutaneous tumor tissue was then orthotopically implanted in the liver of nude mice to establish a PDOX model. Two studies were performed to test different drugs or drug combination, indicating that 5-fluorouracil (5-FU) + irinotecan (IRI) + bevacizumab (BEV) and regorafenib (REG) + selumetinib (SEL) had significantly inhibited liver metastasis growth (p = 0.013 and p = 0.035, respectively), and prevented liver satellite metastasis. This study is proof of concept that a PDOX model of highly aggressive colon-cancer metastasis can identify effective drug combinations and that the model has future clinical potential.
DNN-assisted statistical analysis of a model of local cortical circuits
Authors: Zhang Yaoyu , Young Lai-Sang
Published: November 2020

In neuroscience, computational modeling is an effective way to gain insight into cortical mechanisms, yet the construction and analysis of large-scale network models—not to mention the extraction of underlying principles—are themselves challenging tasks, due to the absence of suitable analytical tools and the prohibitive costs of systematic numerical exploration of high-dimensional parameter spaces. In this paper, we propose a data-driven approach assisted by deep neural networks (DNN). The idea is to first discover certain input-output relations, and then to leverage this information and the superior computation speeds of the well-trained DNN to guide parameter searches and to deduce theoretical understanding. To illustrate this novel approach, we used as a test case a medium-size network of integrate-and-fire neurons intended to model local cortical circuits. With the help of an accurate yet extremely efficient DNN surrogate, we revealed the statistics of model responses, providing a detailed picture of model behavior. The information obtained is both general and of a fundamental nature, with direct application to neuroscience. Our results suggest that the methodology proposed can be scaled up to larger and more complex biological networks when used in conjunction with other techniques of biological modeling.