bluuebunny/crossref_metadata_2025 huggingface dataset:
Adipose-derived mesenchymal stem cell-loaded β-chitin nanofiber hydrogel promote wound healing in rats
Authors: Liu Ying , Liu Yunen , Wu Mi , Zou Rufei , Mao Shun , Cong Peifang , Hou Mingxiao , Jin Hongxu , Zhao Yan , Bao Yongli
Published: January 2022

Because of stem cells are limited by the low efficiency of their cell homing and survival in vivo, cell delivery systems and scaffolds have attracted a great deal of attention for stem cells’ successful clinical practice. β-chitin nanofibers (β-ChNF) were prepared from squid pens in this study. Fourier transform infrared spectroscopy, X-ray diffraction and scanning electron microscopy proved that β-ChNFs with the diameter of 5 to 10 nm were prepared. β-ChNF dispersion became gelled upon the addition of cell culture medium. Cell culture experiments showed that β-ChNFs exhibited negligible cytotoxicity towards ADSCs and L929 cells, and it was found that more exosomes were secreted by the globular ADSCs grown in the β-ChNF hydrogel. The vivo experiments of rats showed that the ADSCs-loaded β-ChNF hydrogel could directly cover the wound surface and significantly accelerate the wound healing and promote the generation of epithelization, granulation tissue and collagen. In addition, the ADSCs-loaded β-ChNF hydrogel clearly regulated the expressions of VEGFR, α-SMA, collagen I and collagen III. Finally, we showed that ADSCs-loaded β-ChNF hydrogel activated the TGFβ/smad signaling. The neutralization of TGFβ markedly reduced Smad phosphorylation and the expressions of TIMP1, VEGFR and α-SMA. Taken together, these findings suggest that ADSCs-loaded β-ChNF hydrogel promises for treating wounds that are challenge to heal via conventional methods.
The effect of a static magnetic field and baicalin or baicalein interactions on amelanotic melanoma cell cultures (C32)
Authors: Synowiec-Wojtarowicz Agnieszka , Pawłowska-Góral Katarzyna , Krawczyk Agata , Gawron Stanisław , Kimsa-Dudek Magdalena
Published: January 2022

Background

Baicalin and baicalein have antioxidant, anti-inflammatory, hepatoprotective and anti-cancer properties. However, it is not known how a static magnetic field will modify these properties. Therefore, the aim of our study was to evaluate the simultaneous exposure of melanoma cells to flavones and the static magnetic fields that are generated by permanent magnets on the gene expression and the activity of the antioxidant enzymes that are associated with the antioxidant defense system.

Methods and results

Melanoma cells that had been treated with baicalin or baicalein were subjected to a static magnetic fields with a moderate induction. The static magnetic field was emitted by permanent magnets and the cell cultures were carried out in special test chambers. The research included determining the activity of the antioxidant enzymes (superoxide dismutase, glutathione peroxidase and catalase) as well as the gene expression profile. The addition of the flavones to the cell cultures at a concentration of 50 µmol/L resulted increase in the expression of the SOD1, SOD2 and GPX1 genes compared to the nontreated cell cultures. Simultaneous exposure of the melanoma cells to static magnetic field and baicalin or baicalein reduced their mRNA levels compared to the cultures to which only baicalin or baicalein had been added. The change in gene expression was accompanied by changes at the protein level associated with an increase in the activity of antioxidant enzymes.

Conclusion

We showed that baicalin or baicalein have anticancer properties by disturbing the redox homeostasis in melanoma cells and also increases the antioxidant system gene expression. There was also an antagonistic interaction between the studied flavones and the static magnetic field, which cause a decrease in the anticancer effects of baicalin or baicalein.
CIN-like TCP13 is essential for plant growth regulation under dehydration stress
Authors: Urano Kaoru , Maruyama Kyonoshin , Koyama Tomotsugu , Gonzalez Nathalie , Inzé Dirk , Yamaguchi-Shinozaki Kazuko , Shinozaki Kazuo
Published: January 2022

Key message

A dehydration-inducible Arabidopsis CIN-like TCP gene, TCP13, acts as a key regulator of plant growth in leaves and roots under dehydration stress conditions.

Plants modulate their shape and growth in response to environmental stress. However, regulatory mechanisms underlying the changes in shape and growth under environmental stress remain elusive. The CINCINNATA (CIN)-like TEOSINTE BRANCHED1/CYCLOIDEA/PCF (TCP) family of transcription factors (TFs) are key regulators for limiting the growth of leaves through negative effect of auxin response. Here, we report that stress-inducible CIN-like TCP13 plays a key role in inducing morphological changes in leaves and growth regulation in leaves and roots that confer dehydration stress tolerance in Arabidopsis thaliana. Transgenic Arabidopsis plants overexpressing TCP13 (35Spro::TCP13OX) exhibited leaf rolling, and reduced leaf growth under osmotic stress. The 35Spro::TCP13OX transgenic leaves showed decreased water loss from leaves, and enhanced dehydration tolerance compared with their control counterparts. Plants overexpressing a chimeric repressor domain SRDX-fused TCP13 (TCP13pro::TCP13SRDX) showed severely serrated leaves and enhanced root growth. Transcriptome analysis of TCP13pro::TCP13SRDX transgenic plants revealed that TCP13 affects the expression of dehydration- and abscisic acid (ABA)-regulated genes. TCP13 is also required for the expression of dehydration-inducible auxin-regulated genes, INDOLE-3-ACETIC ACID5 (IAA5) and LATERAL ORGAN BOUNDARIES (LOB) DOMAIN 1 (LBD1). Furthermore, tcp13 knockout mutant plants showed ABA-insensitive root growth and reduced dehydration-inducible gene expression. Our findings provide new insight into the molecular mechanism of CIN-like TCP that is involved in both auxin and ABA response under dehydration stress.
Representation of symmetry transformations on the sets of tripotents of spin and Cartan factors
Authors: Friedman Yaakov , Peralta Antonio M.
Published: January 2022

There are six different mathematical formulations of the symmetry group in quantum mechanics, among them the set of pure states$${\mathbf {P}}$$P—i.e., the set of one-dimensional projections on a complex Hilbert spaceH– and the orthomodular lattice$${\mathbf {L}}$$Lof closed subspaces ofH. These six groups are isomorphic when the dimension ofHis$$\ge 3$$≥3. The latter hypothesis is absolutely necessary in this identification. For example, the automorphisms group of all bijections preserving orthogonality and the order on$${\mathbf {L}}$$Lidentifies with the bijections on$${\mathbf {P}}$$Ppreserving transition probabilities only if dim$$(H)\ge 3$$(H)≥3. Despite of the difficulties caused by$$M_2({\mathbb {C}})$$M2(C), rank two algebras are used for quantum mechanics description of the spin state of spin-$$\frac{1}{2}$$12particles. However, there is a counterexample for Uhlhorn’s version of Wigner’s theorem for such state space. In this note we prove that in order that the description of the spin will be relativistic, it is not enough to preserve the projection lattice equipped with its natural partial order and orthogonality, but we also need to preserve the partial order set of all tripotents and orthogonality among them (a set which strictly enlarges the lattice of projections). Concretely, letMandNbe two atomic JBW$$^*$$∗-triples not containing rank–one Cartan factors, and let$${\mathcal {U}} (M)$$U(M)and$${\mathcal {U}} (N)$$U(N)denote the set of all tripotents inMandN, respectively. We show that each bijection$$\Phi : {\mathcal {U}} (M)\rightarrow {\mathcal {U}} (N)$$Φ:U(M)→U(N), preserving the partial ordering in both directions, orthogonality in one direction and satisfying some mild continuity hypothesis can be extended to a real linear triple automorphism. This, in particular, extends a result of Molnár to the wider setting of atomic JBW$$^*$$∗-triples not containing rank–one Cartan factors, and provides new models to present quantum behavior.
On coefficient problems for functions starlike with respect to symmetric points
Authors: Zaprawa Paweł
Published: January 2022

The main idea of the study on coefficient problems in various classes of analytic functions (univalent or nonunivalent) is to express the coefficients of functions in a given class by the coefficients of corresponding functions with positive real part. Thus, coefficient functionals can be studied using inequalities known for the class $${\mathcal {P}}$$
P
. Lemmas obtained by Libera and Złotkiewicz and by Prokhorov and Szynal play a special role in this approach. Recently, a new way leading to results on coefficient functionals has been pointed out. This approach is based on relating the coefficients of functions in a given class and the coefficients of corresponding Schwarz functions. In many cases, if we follow this approach, it is easy to predict the exact estimate of the functional and make the appropriate computations. In the proofs of these estimates are used not only classical results (the Schwarz–Pick Lemma or Wiener’s inequality), but also inequalities obtained either recently (e.g. by Efraimidis) or long ago yet almost forgotten (Carlson’s inequality). In this paper, a number of coefficient problems will be solved using the new approach described above. The object of our study is the class of starlike functions with respect to symmetric points associated with the exponential function.
Are the stabilities of stablecoins connected?
Authors: Thanh Binh Nguyen , Hong Thai Nguyen Vu , Pham Huy , Cong Thanh Nguyen , Anh Thu Pham Thi
Published: January 2022

This study analyzes the interconnection of the stability of prominent stablecoins including Tether (USDT), USD Coin (USDC), Paxos Standard (PAX), TrueUSD (TUSD) and DAI from 23/11/2019 to 1/04/2021. We find (i) market price fluctuations vary across stablecoins, (ii) instabilities in USDT and USDC significantly drive those of other stablecoins but less convincing evidence for the reverse impact, and (iii) that increases (decreases) in USDT market prices significantly depress (raise) the market prices of the other stablecoins. Interestingly, the algorithmic stablecoin, DAI, is found to be less stable than its USD-backed counterparts.
Sex-disaggregated data matters: tracking the impact of COVID-19 on the health of women and men
Authors: Hawkes Sarah , Pantazis Athena , Purdie Anna , Gautam Abhishek , Kiwuwa-Muyingo Sylvia , Buse Kent , Tanaka Sonja , Borkotoky Kakoli , Sharma Sneha , Verma Ravi
Published: January 2022

Sex and gender matter to health outcomes, but despite repeated commitments to sex-disaggregate data in health policies and programmes, a persistent and substantial absence of such data remains especially in lower-income countries. This represents a missed opportunity for monitoring and identifying gender-responsive, evidence-informed solutions to address a key driver of the pandemic. In this paper we review the availability of national sex-disaggregated surveillance data on COVID-19 and examine trends on the testing-to-outcome pathway. We further analyse the availability of data according to the economic status of the country and investigate the determinants of sex differences, including the national gender inequality status (according to a global index) in each country. Results are drawn from 18 months of global data collection from over 200 countries. We find differences in COVID-19 prevention behaviours and illness outcomes by sex, with lower uptake of vaccination and testing plus an elevated risk of severe disease and death among men. Supporting and maintaining the collection, collation, interpretation and presentation of sex-disaggregated data requires commitment and resources at subnational, national and global levels, but provides an opportunity for identifying and taking gender-responsive action on health inequities. As a first step the global health community should recognise, value and support the importance of sex-disaggregated data for identifying and tackling an inequitable pandemic.
Effects of biochar on soil water retention curves of compacted clay during wetting and drying
Authors: Wong James Tsz Fung , Chow Ka Lai , Chen Xun Wen , Ng Charles Wang Wai , Wong Ming Hung
Published: January 2022

Compacted clay possesses a low water permeability and has been widely used in geo-environmental facilities such as landfill cover systems. Recent studies revealed the potential applications of compacted biochar-amended clay (BAC) as an alternative landfill cover soil. However, the effects of biochar on the soil water retention curves (SWRCs) of clay at low suction are not known. This study can help fill this knowledge gap by measuring the wetting and drying SWRCs of clay and BAC (20% biochar). Soils were compacted in instrumented soil columns and subjected to a wetting and drying cycle, and soil water content and suction were measured along with the soil depth. BAC was saturated faster when compared with clay. Upon drying, the soil water content of clay at 65 mm depth dropped to almost zero, while about 5% of water was retained in BAC. It showed that biochar increased the soil water retention capacity of compacted clay upon drying. SWRCs showed that biochar-clay composite possesses a higher soil water retention capacity at a low soil suction range (< 1000 kPa) compared with clay alone. It revealed the benefits of using compacted biochar-clay composite as a hydraulic barrier to minimize desiccation-induced cracks and potentially promote its serviceability, especially in arid and semi-arid regions. The composite is also a carbon sink material that can reduce landfill gas emissions and pollutant leaching.
Magnetic Fe2O3/biochar composite prepared in a molten salt medium for antibiotic removal in water
Authors: Liang Huagen , Zhu Chenxi , Ji Shan , Kannan Palanisamy , Chen Fu
Published: January 2022

The large-scale use of antibiotics is causing serious water pollution problems, and it is of great significance to develop new technologies to remove antibiotics from water. As an environmentally friendly and economical adsorption material, carbon derived from biomass is a low-cost and feasible material for removing antibiotics in sewage, but the current removal efficiencies are not high enough for large-scale practical application. In this study, poplar wood chips are used as raw material, and a magnetic biochar is prepared by co-pyrolysis of poplar wood chips and FeCl3/CaCl2 mixed molten salt. X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), N2-isothermal adsorption and desorption, X-ray photoelectron spectroscopy (XPS) and scanning electron microscope (SEM) techniques showed the successful synthesis of Fe2O3/bioC composite. In-situ formed Fe2O3 makes the biochar possess the characteristic of superparamagnetic, which is conducive to the recycling of biochar. Due to the etching effect of the molten salts, rough surface was formed on Fe2O3/bioC, resulting in a maximum norfloxacin (NOR) adsorption ability up to 38.77 mg g−1 at pH 6.0. The NOR adsorption behavior on Fe2O3/bioC followed the pseudo second order kinetic model and the equilibrium data was best fitted the Langmuir model. In addition, the adsorption process of NOR on Fe2O3/bioC was thermodynamically spontaneous. The results show that this low-cost and reusable magnetic biochar has the potential for rapid and efficient removal of antibiotic from aqueous solution.
A Novel Power Transformer Fault Diagnosis Model Based on Harris-Hawks-Optimization Algorithm Optimized Kernel Extreme Learning Machine
Authors: Han Xiaohui , Ma Shifeng , Shi Zhewen , An Guoqing , Du Zhenbin , Zhao Chunlin
Published: January 2022

Dissolved gas analysis (DGA) method is widely used to detect the incipient fault of power transformers. This paper presents a novel DGA method for power transformer fault diagnosis based on Harris-Hawks-optimization (HHO) algorithm optimized kernel extreme learning machine (KELM). The non-code ratios of the gases are used as the characterizing vector for the KELM model, and the Harris-Hawks-optimization (HHO) algorithm is introduced to optimize the KELM parameters, which promotes the fault diagnostic performance of KELM. Based on dataset collected from IEC TC 10, the fault diagnosis capability of the proposed method is validated by different characterizing vectors and is compared with conventional KELM and other optimized KELM. Moreover, the generalization ability of the proposed method is confirmed by China DGA data. The results demonstrate that the proposed method is superior to other methods and is more effective and stable for power transformer fault diagnosis with high accuracy.
The Importance of Campaign Promises
Authors: Bonilla Tabitha
Published: January 2022

Campaign promises are a cornerstone of representative democracy. Candidates make promises to signal to voters their intentions in office and voters evaluate candidates based on those promises. This study unpacks the theorized pathway regarding campaign promises: not whether promises are kept, but what purpose promises serve, what they signal, and how they affect voter decision-making. The author explores the pathways and conditions influencing promises and finds that promises tend to have a polarizing effect on voters' opinions of politicians, attracting similarly-positioned voters and strongly repelling voters who disagree with a candidate's position. In addition, voters perceive promise breakers as less honest and less likely to follow through than candidates who more weakly took the same position. With a wealth of data and fascinating case studies, this book is full of important insights into electoral psychology and the study of promises, campaigning, and representation.
Collective Aquifer Governance
Authors: Jarvis Todd , Wiley Jakob
Published: January 2022

Current models of groundwater governance focus principally on the allocation of water, rather than taking a holistic approach incorporating valuable storage space in the aquifer, as well as the transformative changes in managed recharge of manufactured water, storm water, and carbon. Effective implementation of a more modern approach now calls for rethink of both scale and jurisdictional boundaries. This involves linking public and private aspects of water quantity, water quality, geothermal regulation, property rights, subsurface storage rights, water marketing, water banking, legal jurisdictions, and other components into a single governance document. This style of agreement stands in contrast to the siloed approach currently applied to aquifer resources. Using case studies, and an activity inspired by gaming concepts to explore the incentives, and challenges to aquifer governance approaches, this book demonstrates how application of the principles of unitization agreements to aquifers could provide a new approach to aquifer governance models.
Enfranchisement and Incarceration after the 1965 Voting Rights Act
Authors: EUBANK NICHOLAS , FRESH ADRIANE
Published: January 2022

The 1965 Voting Rights Act (VRA) fundamentally changed the distribution of electoral power in the US South. We examine the consequences of this mass enfranchisement of Black people for the use of the carceral state—police, the courts, and the prison system. We study the extent to which white communities in the US South responded to the end of Jim Crow by increasing the incarceration of Black people. We test this with new historical data on state and county prison intake data by race (~1940–1985) in a series of difference-in-differences designs. We find that states covered by Section 5 of the VRA experienced a differential increase in Black prison admissions relative to those that were not covered and that incarceration varied systematically in proportion to the electoral threat posed by Black voters. Our findings indicate the potentially perverse consequences of enfranchisement when establishment power seeks—and finds—other outlets of social and political control.
On Algorithmic Fairness in Medical Practice
Authors: Grote Thomas , Keeling Geoff
Published: January 2022

The application of machine-learning technologies to medical practice promises to enhance the capabilities of healthcare professionals in the assessment, diagnosis, and treatment, of medical conditions. However, there is growing concern that algorithmic bias may perpetuate or exacerbate existing health inequalities. Hence, it matters that we make precise the different respects in which algorithmic bias can arise in medicine, and also make clear the normative relevance of these different kinds of algorithmic bias for broader questions about justice and fairness in healthcare. In this paper, we provide the building blocks for an account of algorithmic bias and its normative relevance in medicine.
Two Leading Modes in the Evolution of Major Sudden Stratospheric Warmings and Their Distinctive Surface Influence
Authors: Xu Qibo , Chen Wen , Song Lei
Published: January 2022

Height‐time domain empirical orthogonal function (EOF) analysis is conducted to extract the dominant variations in the evolution of sudden stratospheric warming events (SSWs). The EOF1 corresponds to weak (I+) and strong (I−) polar vortex before the onset of SSWs and EOF2 indicates strong (W+) and weak (W−) warming during SSWs. The development of I− SSWs is associated with stronger eddy heat flux contributed by planetary wavenumbers 1 and 2, whereas the I + SSWs is related to wavenumber 1. W + SSWs are linked to both wavenumbers 1 and 2, while the happening of W− SSWs is associated with wavenumber 1. SSWs of I+ and W+ can exert influence on the surface such as negative phase of the North Atlantic Oscillation, which indicates that SSWs with different initial polar vortex states and warming intensities lead to different surface influence. This could help to better predict the tropospheric response following SSWs.
Retrieval of Simultaneous Water‐Level Changes in Small Lakes With InSAR
Authors: Palomino‐Ángel S. , Vázquez R. F. , Hampel H. , Anaya J. A. , Mosquera P. V. , Lyon S. W. , Jaramillo F.
Published: January 2022

Monitoring water level changes is necessary to manage, conserve and restore natural, and anthropogenic lake systems. However, the in‐situ monitoring of lake systems is unfeasible due to limitations of costs and access. Furthermore, current remote sensing methods are restricted to large lakes and low spatial resolutions. We develop a novel approach using subsequential pixel‐wise observations of the Sentinel‐1B sensor based on interferometric synthetic aperture radar to detect water level changes in small lakes. We used 24 small ungauged lakes of the Cajas Massif lake system in Ecuador for development and validation. We found Differential Interferometric Synthetic Aperture Radar (DInSAR)‐derived water level changes across lakes to be consistent with precipitation, capturing the peak of the wet seasons. Furthermore, accumulated water level changes could be explained by differences in lake area among lakes. Although with limitations, this study shows the underutilized potential of DInSAR to understand water level changes in small lakes with current radar data availability.
The Orinoco Low‐Level Jet and the Cross‐Equatorial Moisture Transport Over Tropical South America: Lessons From Seasonal WRF Simulations
Authors: Martinez J. Alejandro , Arias Paola A. , Junquas Clémentine , Espinoza Jhan Carlo , Condom Thomas , Dominguez Francina , Morales José S.
Published: January 2022

A study of the simulation of the Orinoco Low‐Level Jet (OLLJ) and the cross‐equatorial moisture transport over tropical South America using the Weather Research and Forecasting (WRF) model is presented. The focus is on the diurnal cycle and monthly means during one December‐January‐February (DJF) season (2003–2004). The sensitivity of the OLLJ and cross‐equatorial moisture transport to the representation of surface fluxes and turbulence is explored by using two different Land Surface Models (LSM) and three Planetary Boundary Layer (PBL) schemes. Different LSMs produce large differences in the sensible heat flux over the Orinoco basin, but no substantial differences in the flow at the entrance of the OLLJ. However, these changes in surface fluxes were associated with a change in the low‐level pressure gradient between the Orinoco and Amazon basins, and with up to 10% change in the simulated cross‐equatorial moisture transport. The largest effects from different PBL schemes were found in the low‐level flow near the Andes cordillera, and on the low‐level southward cross‐equatorial flow during the daytime. One of the PBL schemes exhibited a reduced moisture transport on the eastern flank of the Andes but enhanced southward transport around the core of the cross‐equatorial moisture flux. Another PBL scheme produced a stronger net cross‐equatorial moisture transport, with enhanced precipitation over the Andes‐Amazon region by up to 30% during the afternoon and up to 13% in the daily mean. Improved observations over the region are needed to evaluate which combination best represents the flow.
Looking to the Skies: Realising the Combined Potential of Drones and Thermal Infrared Imagery to Advance Hydrological Process Understanding in Headwaters
Authors: Dugdale Stephen J. , Klaus Julian , Hannah David M.
Published: January 2022

In river systems, headwater networks contain the vast majority of the stream length. Thus, climate and land‐use change in headwaters have disproportionate impacts on downstream ecosystems and societies that rely on them. Despite decades of hydrological research, difficulties in observing hydrological properties across scales means that scientific knowledge of processes driving streamflow in headwaters remains limited. However, the recent emergence of two complementary technologies, drones and thermal infrared (TIR) remote sensing, has potential to collect data at scales and resolutions needed to advance hydrological process understanding in headwaters. In this commentary, we explain how drone‐based TIR can offer unique high‐resolution observations of surface connectivity and headwater network dynamics across multiple spatio‐temporal scales. We explore the current state‐of‐the‐art of drones and TIR imaging in the hydrological sciences, highlighting the potential benefits but also steps that will need to be taken to release these technologies' full potential. We finish by contending that drone‐based TIR is particularly well‐placed to bridge the current gap between field (point) observations and model simulations to provide the improved hydrological understanding needed for a changing world.
Faster than expected Rubisco deactivation in shade reduces cowpea photosynthetic potential in variable light conditions
Authors: Taylor Samuel H. , Gonzalez-Escobar Emmanuel , Page Rhiannon , Parry Martin A. J. , Long Stephen P. , Carmo-Silva Elizabete
Published: January 2022

Cowpea is the major source of vegetable protein for rural populations in sub-Saharan Africa and average yields are not keeping pace with population growth. Each day, crop leaves experience many shade events and the speed of photosynthetic adjustment to this dynamic environment strongly affects daily carbon gain. Rubisco activity is particularly important because it depends on the speed and extent of deactivation in shade and recovers slowly on return to sun. Here, direct biochemical measurements showed a much faster rate of Rubisco deactivation in cowpea than prior estimates inferred from dynamics of leaf gas exchange in other species1–3. Shade-induced deactivation was driven by decarbamylation, and half-times for both deactivation in shade and activation in saturating light were shorter than estimates from gas exchange (≤53% and 79%, respectively). Incorporating these half-times into a model of diurnal canopy photosynthesis predicted a 21% diurnal loss of productivity and suggests slowing Rubisco deactivation during shade is an unexploited opportunity for improving crop productivity.
Enhanced corrosion resistance of additively manufactured stainless steel by modification of feedstock
Authors: Vukkum V. B. , Christudasjustus J. , Darwish A. A. , Storck S. M. , Gupta R. K.
Published: January 2022

Additive manufacturing (AM) is an emerging technology to produce engineering components. However, the major challenge in the practical application of AM is the inconsistent properties of additively manufactured components. This research presents a strategy of feedstock modification to improve the corrosion performance of selective laser melted (SLM) 316L stainless steel (SS). Modified feedstock powders were produced by ball-milling of commercial-316LSS powder with 1wt.% chromium nitride (CrN). The SLM coupons produced from modified feedstock powders (SLM-316L/CrN) exhibited significantly improved corrosion performance, as evident from the high pitting and repassivation potentials and absence of metastable pitting. The microstructural characterization revealed fine oxide-inclusions comprising Si, Mn, and S in SLM-316L and only Si and Mn in SLM-316L/CrN. The absence of sulfur-containing oxide-inclusions in SLM-316L/CrN and refined cellular structure, and the change in chemical composition were attributed to corrosion resistance enhancement due to the CrN addition.
An EPA database on the effects of engineered nanomaterials-NaKnowBase
Authors: Boyes William K. , Beach Bradley , Chan Gayle , Thornton B. Lila M. , Harten Paul , Mortensen Holly M.
Published: January 2022

The US EPA Office of Research and Development (ORD) has conducted a research program assessing potential risks of emerging materials and technologies, including engineered nanomaterials (ENM). As a component of that program, a nanomaterial knowledge base, termed “NaKnowBase”, was developed containing the results of published ORD research relevant to the potential environmental and biological actions of ENM. The experimental data address issues such as ENM release into the environment; fate, transport and transformations in environmental media; exposure to ecological species or humans; and the potential for effects on those species. The database captures information on the physicochemical properties of ENM tested, assays performed and their parameters, and the results obtained. NaKnowBase (NKB) is a relational SQL database, and may be queried either with SQL code or through a user-friendly web interface. Filtered results may be output in spreadsheet format for subsequent user-defined analyses. Potential uses of the data might include input to quantitative structure-activity relationships (QSAR), meta-analyses, or other investigative approaches.
Droplet evaporation on porous fabric materials
Authors: Gonçalves Marta , Kim Jin Young , Kim Yeseul , Rubab Najaf , Jung Narina , Asai Takeshi , Hong Sungchan , Weon Byung Mook
Published: January 2022

Droplet evaporation on porous materials is a complex dynamic that occurs with spontaneous liquid imbibition through pores by capillary action. Here, we explore water dynamics on a porous fabric substrate with in-situ observations of X-ray and optical imaging techniques. We show how spreading and wicking lead to water imbibition through a porous substrate, enhancing the wetted surface area and consequently promoting evaporation. These sequential dynamics offer a framework to understand the alterations in the evaporation due to porosity for the particular case of fabric materials and a clue of how face masks interact with respiratory droplets.
Variation in excess all-cause mortality by age, sex, and province during the first wave of the COVID-19 pandemic in Italy
Authors: Henry Nathaniel J. , Elagali Ahmed , Nguyen Michele , Chipeta Michael Give , Moore Catrin E.
Published: January 2022

Although previous evidence suggests that the infection fatality rate from COVID-19 varies by age and sex, and that transmission intensity varies geographically within countries, no study has yet explored the age-sex-space distribution of excess mortality associated with the COVID pandemic. By applying the principles of small-area estimation to existing model formulations for excess mortality, this study develops a novel method for assessing excess mortality across small populations and assesses the pattern of COVID excess mortality by province, year, week, age group, and sex in Italy from March through May 2020. We estimate that 53,200 excess deaths occurred across Italy during this time period, compared to just 35,500 deaths where COVID-19 was registered as the underlying cause of death. Out of the total excess mortality burden, 97% of excess deaths occurred among adults over age 60, and 68% of excess deaths were concentrated among adults over age 80. The burden of excess mortality was unevenly distributed across the country, with just three of Italy’s 107 provinces accounting for 32% of all excess mortality. This method for estimating excess mortality can be adapted to other countries where COVID-19 diagnostic capacity is still insufficient, and could be incorporated into public health rapid response systems.
Audiovisual integration in the Mauthner cell enhances escape probability and reduces response latency
Authors: Martorell Nicolás , Medan Violeta
Published: January 2022

Fast and accurate threat detection is critical for animal survival. Reducing perceptual ambiguity by integrating multiple sources of sensory information can enhance perception and reduce response latency. However, studies addressing the link between behavioral correlates of multisensory integration and its underlying neural basis are rare. Fish that detect an urgent threat escape with an explosive behavior known as C-start. The C-start is driven by an identified neural circuit centered on the Mauthner cell, an identified neuron capable of triggering escapes in response to visual and auditory stimuli. Here we demonstrate that goldfish can integrate visual looms and brief auditory stimuli to increase C-start probability. This multisensory enhancement is inversely correlated to the salience of the stimuli, with weaker auditory cues producing a proportionally stronger multisensory effect. We also show that multisensory stimuli reduced C-start response latency, with most escapes locked to the presentation of the auditory cue. We make a direct link between behavioral data and its underlying neural mechanism by reproducing the behavioral data with an integrate-and-fire computational model of the Mauthner cell. This model of the Mauthner cell circuit suggests that excitatory inputs integrated at the soma are key elements in multisensory decision making during fast C-start escapes. This provides a simple but powerful mechanism to enhance threat detection and survival.
Green electrochemical method for the synthesis of nitro and azo derivatives based on mefenamic acid
Authors: Amooshahi Parvaneh , Khazalpour Sadegh , Amani Ameneh , Masoumi Hossein
Published: January 2022

Electrochemical study of mefenamic acid (MFA) was carried out with details in water/ethanol mixture by the various voltammetric techniques. The results showed that the oxidation of MFA is highly dependent on pH and follows the Eir mechanism. The EpA1-pH diagram plotted based on the differential pulse voltammograms shows two linear segments, 66 and 26 mV/pH slope. Also, the diffusion coefficient and the surface excess, Ӷ* of MFA in aqueous buffered solution, determined by using the single potential-step chronoamperometry and chronocoulometry methods. Electrochemical nitration of MFA in an aqueous solution and the presence of nitrite ion (1) were both investigated by the cyclic voltammetry and controlled-potential coulometry techniques. Our results indicate that the oxidized form of MFA participates in a Michael-type addition reaction with nitrite ion (1) to form the corresponding Nitromefenamic acids (MFA-4-NO2 and MFA-5-NO2). Also, in another part, a computational study based on the density functional theory (DFT/B3LYP) was performed for the prediction of the best possible pathway in the nucleophilic addition of nitrite ion (1). The electrochemical reduction of produced nitromefenamic acids was investigated using cyclic voltammetry and controlled-potential coulometry techniques. Eventually, two new azo derivatives have been generated via electroreduction of produced nitromefenamic acids and conduction of diazotization reaction, respectively. Both nitro and azo products are approved as paints.
Genome-wide methylation analyses identifies Non-coding RNA genes dysregulated in breast tumours that metastasise to the brain
Authors: Pangeni Rajendra P. , Olivaries Ivonne , Huen David , Buzatto Vannessa C. , Dawson Timothy P. , Ashton Katherine M. , Davis Charles , Brodbelt Andrew R. , Jenkinson Michael D. , Bièche Ivan , Yang Lu , Latif Farida , Darling John L. , Warr Tracy J. , Morris Mark R.
Published: January 2022

Brain metastases comprise 40% of all metastatic tumours and breast tumours are among the tumours that most commonly metastasise to the brain, the role that epigenetic gene dysregulation plays in this process is not well understood. We carried out 450 K methylation array analysis to investigate epigenetically dysregulated genes in breast to brain metastases (BBM) compared to normal breast tissues (BN) and primary breast tumours (BP). For this, we referenced 450 K methylation data for BBM tumours prepared in our laboratory with BN and BP from The Cancer Genome Atlas. Experimental validation on our initially identified genes, in an independent cohort of BP and in BBM and their originating primary breast tumours using Combined Bisulphite and Restriction Analysis (CoBRA) and Methylation Specific PCR identified three genes (RP11-713P17.4, MIR124-2, NUS1P3) that are hypermethylated and three genes (MIR3193, CTD-2023M8.1 and MTND6P4) that are hypomethylated in breast to brain metastases. In addition, methylation differences in candidate genes between BBM tumours and originating primary tumours shows dysregulation of DNA methylation occurs either at an early stage of tumour evolution (in the primary tumour) or at a later evolutionary stage (where the epigenetic change is only observed in the brain metastasis). Epigentic changes identified could also be found when analysing tumour free circulating DNA (tfcDNA) in patient’s serum taken during BBM biopsies. Epigenetic dysregulation of RP11-713P17.4, MIR3193, MTND6P4 are early events suggesting a potential use for these genes as prognostic markers.
A neurophysiologically interpretable deep neural network predicts complex movement components from brain activity
Authors: Kumar Neelesh , Michmizos Konstantinos P.
Published: January 2022

The effective decoding of movement from non-invasive electroencephalography (EEG) is essential for informing several therapeutic interventions, from neurorehabilitation robots to neural prosthetics. Deep neural networks are most suitable for decoding real-time data but their use in EEG is hindered by the gross classes of motor tasks in the currently available datasets, which are solvable even with network architectures that do not require specialized design considerations. Moreover, the weak association with the underlying neurophysiology limits the generalizability of modern networks for EEG inference. Here, we present a neurophysiologically interpretable 3-dimensional convolutional neural network (3D-CNN) that captured the spatiotemporal dependencies in brain areas that get co-activated during movement. The 3D-CNN received topography-preserving EEG inputs, and predicted complex components of hand movements performed on a plane using a back-drivable rehabilitation robot, namely (a) the reaction time (RT) for responding to stimulus (slow or fast), (b) the mode of movement (active or passive, depending on whether there was an assistive force provided by the apparatus), and (c) the orthogonal directions of the movement (left, right, up, or down). We validated the 3D-CNN on a new dataset that we acquired from an in-house motor experiment, where it achieved average leave-one-subject-out test accuracies of 79.81%, 81.23%, and 82.00% for RT, active vs. passive, and direction classifications, respectively. Our proposed method outperformed the modern 2D-CNN architecture by a range of 1.1% to 6.74% depending on the classification task. Further, we identified the EEG sensors and time segments crucial to the classification decisions of the network, which aligned well with the current neurophysiological knowledge on brain activity in motor planning and execution tasks. Our results demonstrate the importance of biological relevance in networks for an accurate decoding of EEG, suggesting that the real-time classification of other complex brain activities may now be within our reach.
Geometry of rare regions behind Griffiths singularities in random quantum magnets
Authors: Kovács István A. , Iglói Ferenc
Published: January 2022

In many-body systems with quenched disorder, dynamical observables can be singular not only at the critical point, but in an extended region of the paramagnetic phase as well. These Griffiths singularities are due to rare regions, which are locally in the ordered phase and contribute to a large susceptibility. Here, we study the geometrical properties of rare regions in the transverse Ising model with dilution or with random couplings and transverse fields. In diluted models, the rare regions are percolation clusters, while in random models the ground state consists of a set of spin clusters, which are calculated by the strong disorder renormalization method. We consider the so called energy cluster, which has the smallest excitation energy and calculate its mass and linear extension in one-, two- and three-dimensions. Both average quantities are found to grow logarithmically with the linear size of the sample. Consequently, the energy clusters are not compact: for the diluted model they are isotropic and tree-like, while for the random model they are quasi-one-dimensional.
Hippophae rhamnoides L. leaf and twig extracts as rich sources of nutrients and bioactive compounds with antioxidant activity
Authors: Kubczak Małgorzata , Khassenova Ainur B. , Skalski Bartosz , Michlewska Sylwia , Wielanek Marzena , Skłodowska Maria , Aralbayeva Araylim N. , Nabiyeva Zhanar S. , Murzakhmetova Maira K. , Zamaraeva Maria , Bryszewska Maria , Ionov Maksim
Published: January 2022

Plants have served for centuries as sources of compounds useful for human health such as antioxidant, anti-diabetic and antitumor agents. They are also rich in nutrients that improve the human diet. Growing demands for these compounds make it important to seek new sources for them.Hippophae rhamnoidesL. is known as a plant with health-promoting properties. In this study we investigated the chemical composition and biological properties of bioactive components of ethanol extracts from leaves and twigs ofH. rhamnoidesL. Chemical components such as the total content of phenolic compounds, vitamins and amino acids and the antioxidant activities of these compounds in cellular and cell-free systems were assessed. The results suggest that the studied extracts are rich in bioactive compounds with potent antioxidant properties. Cytotoxicity and hemotoxicity assays showed that the extracts had low toxicity on human cells over the range of concentrations tested. Interaction with human serum albumin was investigated and conformational changes were observed. Our results indicate that leaf and twig extracts ofH. rhamnoidesL. should be considered as a non-toxic source of bioactive compounds which may be of interest to the food, pharmaceutical and cosmetic industries.
Clinical characterization and possible pathophysiological causes of the Deventilation Syndrome in COPD
Authors: Schellenberg Mavi Dorothea , Imach Sandra , Iberl Gabriele , Kirchner Marietta , Herth Felix , Trudzinski Franziska
Published: January 2022

In daily routine, many COPD patients report early onset augmented dyspnea following use of NIV (Deventilation Syndrome, DVS) as a negative side-effect. The aim of this study is the clinical characterization and concrete definition of DVS. This monocenter prospective observational study collected demographic, physiologic and symptomatic data from 67 in-patients with severe COPD Gold III–IV and chronic hypercapnic failure before, during and after use of an established NIV. During their inpatient follow-up, we examined patients during the first hour after termination of nocturnal NIV. DVS was defined by the authors as an increase of ≥ 2 points on the Borg scale during the first 30 min in patients who reported repeated dyspnea after the use of NIV. We monitored cardiovascular and respiratory data and measured diaphragm excursion. Subjective dyspnea was documented by use of the Borg scale and questionnaires. In addition, respirator and demographic data were collected. DVS occurred in 58% of our COPD patient collective, showing predominant emphysema phenotype. Patients with DVS were more severely ill than non-DVS concerning bronchial obstruction (FEV1 0.6 vs. 0.8 l, p < 0.05) and hypercapnia during spontaneous breathing (pre NIV pCO2: 54.5 vs. 49.3 mmHg, p < 0.02). DVS patients showed significantly higher respiratory rates (RR) (20.1 vs. 18.1/min p < 0.05) after termination of NIV. This trial characterizes and defines early onset augmented dyspnea after the use of NIV, referred to as DVS. It is hereby brought to attention as a frequent side effect of long-term home ventilation and possible pathophysiologic mechanisms are elucidated.
A novel graph mining approach to predict and evaluate food-drug interactions
Authors: Rahman Md. Mostafizur , Vadrev Srinivas Mukund , Magana-Mora Arturo , Levman Jacob , Soufan Othman
Published: January 2022

Food-drug interactions (FDIs) arise when nutritional dietary consumption regulates biochemical mechanisms involved in drug metabolism. This study proposes FDMine, a novel systematic framework that models the FDI problem as a homogenous graph. Our dataset consists of 788 unique approved small molecule drugs with metabolism-related drug-drug interactions and 320 unique food items, composed of 563 unique compounds. The potential number of interactions is 87,192 and 92,143 for disjoint and joint versions of the graph. We defined several similarity subnetworks comprising food-drug similarity, drug-drug similarity, and food-food similarity networks. A unique part of the graph involves encoding the food composition as a set of nodes and calculating a content contribution score. To predict new FDIs, we considered several link prediction algorithms and various performance metrics, including the precision@top (top 1%, 2%, and 5%) of the newly predicted links. The shortest path-based method has achieved a precision of 84%, 60% and 40% for the top 1%, 2% and 5% of FDIs identified, respectively. We validated the top FDIs predicted using FDMine to demonstrate its applicability, and we relate therapeutic anti-inflammatory effects of food items informed by FDIs. FDMine is publicly available to support clinicians and researchers.