bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hyperosmolar expansion medium improves nucleus pulposus cell phenotype
Authors: Laagland Lisanne T. , Bach Frances C. , Creemers Laura B. , Le Maitre Christine L. , Poramba‐Liyanage Deepani W. , Tryfonidou Marianna A. 
Published: August 2022

AbstractBackgroundRepopulating the degenerated intervertebral disc (IVD) with tissue‐specific nucleus pulposus cells (NPCs) has already been shown to promote regeneration in various species. Yet the applicability of NPCs as cell‐based therapy has been hampered by the low cell numbers that can be extracted from donor IVDs and their potentially limited regenerative capacity due to their degenerated phenotype. To optimize the expansion conditions, we investigated the effects of increasing culture medium osmolarity during expansion on the phenotype of dog NPCs and their ability to produce a healthy extracellular matrix (ECM) in a 3D culture model.MethodsDog NPCs were expanded in expansion medium with a standard osmolarity of 300 mOsm/L or adjusted to 400 or 500 mOsm/L in both normoxic and hypoxic conditions. Following expansion, NPCs were cultured in a 3D culture model in chondrogenic culture medium with a standard osmolarity. Read‐out parameters included cell proliferaton rate, morphology, phenotype and healthy ECM production.ResultsIncreasing the expansion medium osmolarity from 300 to 500 mOsm/L resulted in NPCs with a more rounded morphology and a lower cell proliferation rate accompanied by the expression of several healthy NPC and progenitor markers at gene (KRT18, ACAN, COL2, CD73, CD90) and protein (ACAN, PAX1, CD24, TEK, CD73) level. The NPCs expanded at 500 mOsm/L were able to retain most of their phenotypic markers and produce healthy ECM during 3D culture independent of the oxygen level used during expansion.ConclusionsAltogether, our findings show that increasing medium osmolarity during expansion results in an NPC population with improved phenotype, which could enhance the potential of cell‐based therapies for IVD regeneration.
C2‐GAN: Content‐consistent generative adversarial networks for unsupervised domain adaptation in medical image segmentation
Authors: Zhang Zuyu , Li Yan , Shin Byeong‐Seok 
Published: August 2022

AbstractPurposeIn clinical practice, medical image analysis has played a key role in disease diagnosis. One of the important steps is to perform an accurate organ or tissue segmentation for assisting medical professionals in making correct diagnoses. Despite the tremendous progress in the deep learning‐based medical image segmentation approaches, they often fail to generalize to test datasets due to distribution discrepancies across domains. Recent advances aligning the domain gaps by using bi‐directional GANs (e.g., CycleGAN) have shown promising results, but the strict constraints of the cycle consistency hamper these methods from yielding better performance. The purpose of this study is to propose a novel bi‐directional GAN‐based segmentation model with fewer constraints on the cycle consistency to improve the generalized segmentation results.MethodsWe propose a novel unsupervised domain adaptation approach by designing content‐consistent generative adversarial networks () for medical image segmentation. First, we introduce content consistency instead of cycle consistency to relax the constraint of the invertibility map to encourage the synthetic domain generated with a large domain transportation distance. The synthetic domain is thus pulled close to the target domain for the reduction of domain discrepancy. Second, we suggest a novel style transfer loss based on the difference in low‐frequency magnitude to further mitigate the appearance shifts across domains.ResultsWe validate our proposed approach on three public X‐ray datasets, including the Montgomery, JSRT, and Shenzhen datasets. For an accurate evaluation, we randomly divided the images of each dataset into 70% for training, 10% for evaluation, and 20% for testing. The mean Dice was 95.73 ± 0.22%, 95.16 ± 1.42% for JSRT and Shenzhen datasets, respectively. For the recall and precision metrics, our model also achieved better or comparable performance than the state‐of‐the‐art CycleGAN‐based UDA approaches.ConclusionsThe experimental results validate the effectiveness of our method in mitigating the domain gaps and improving generalized segmentation results for X‐ray image segmentation.
Transcultural adaptation and validity of the nurse professional competence scale Korean version for graduating nursing students: An explanatory factor analysis
Authors: Lee Su Jung , Seo Hyun‐Ju , Kim Kye Ha , Kim Jinhee , Kim Hyunlye , Park Jeong‐Min 
Published: August 2022

AbstractAimThe study aimed to assess the validity and reliability of the short‐form Nurse Professional Competence Scale–Korean version (NPC‐K) among Korean nursing students at the point of graduation.DesignThis was a cross‐sectional survey.MethodsThe Nurse Professional Competence scale was translated into Korean using the World Health Organization (WHO) translation method. A total of 195 graduating nursing students participated. Exploratory factor analysis for validity and Cronbach's alpha coefficients for reliability were examined.ResultsFactor analysis showed that five NPC‐K factors accounted for 68.38% of the total variance. Cronbach's alpha for the total scale was 0.97. The NPC‐K has high internal reliability and acceptable construct validity. The content of the scale reflected nursing students' confidence in formal competence requirements based on Korean cultural and educational backgrounds. An accurate assessment of nurse professional competence using the NPC‐K may help nursing academics enhance the quality of education and training.
Convolutional neural network prediction of molecular properties for aerosol chemistry and health effects
Authors: Krüger Matteo , Wilson Jake , Wietzoreck Marco , Bandowe Benjamin A. Musa , Lammel Gerhard , Schmidt Bertil , Pöschl Ulrich , Berkemeier Thomas 
Published: August 2022

AbstractQuinones are chemical compounds commonly found in air particulate matter (PM). Their redox activity can generate reactive oxygen species (ROS) and contribute to the oxidative potential (OP) of PM leading to adverse health effects of aerosols. The quinones' OP and ability to form ROS are linked to their reduction potential (RP, measured in volts), a metric for the tendency to lose electrons in redox reactions. Here, we use convolutional neural networks (CNN) as quantitative structure‐activity relationship (QSAR) models to relate the one‐electron RP of quinones to their molecular structure. For CNN training and testing, a data set of more than 100,000 quinones with associated RP values derived from density functional theory calculations was encoded in simplified molecular input line entry system (SMILES). The best performing CNN model achieved a root mean square error (RMSE) of 0.115 V for an independent test data set and outperformed linear regression models fitted on common molecular descriptors (≥ 0.140 V RMSE). Augmentation methods were newly adapted or applied to support CNN training with smaller data sets, improving RMSE by up to approximately 37% for a data set of 321 molecules. Adjusted for solvent effects, the CNN‐derived RP predictions showed good agreement with experimental data. Using the newly developed method, we identified a subset of atmospherically relevant quinones that are likely to have a high OP and play a role in aerosol health effects, which remains to be further elucidated by experimental studies. We suggest to use the presented machine learning approach in further investigations of atmospheric aerosol chemistry and health effects as well as other studies that require a target‐oriented screening of the properties and effects of large classes of substances.Key Points
Convolutional neural networks can be used to estimate unknown physical and chemical properties of chemical substances and outperform additive group contribution methods.
Augmentation methods aid in the prevalent problem of data availability.
Quinone species detected in the environment are screened for potential relevance in atmospheric chemistry and public health and presented in this study.
Undiagnosed abnormal alanine transaminase levels in vulnerable populations: Impact of sex, race/ethnicity, and body mass
Authors: Kim Rebecca G. , Khalili Mandana 
Published: August 2022

AbstractBackgroundLiver disease is a leading cause of death in the United States and is often initially detected incidentally on lab tests ordered by general practitioners. Alanine transaminase (ALT), a marker of liver inflammation, is commonly ordered and may be abnormal in the setting of elevated body mass index, diabetes and dyslipidemia. Data regarding ALT testing within vulnerable populations are limited. Therefore, the prevalence of ALT testing and abnormal ALT in the absence of known chronic liver disease (CLD) among a safety‐net population were assessed and factors associated with these outcomes were identified.MethodsIn this retrospective longitudinal study of 92,997 patients seen between 01/2017–01/2019 within San Francisco's Safety‐Net Healthcare System, electronic medical records were used to abstract data back to 04/1997. Descriptive analyses and multivariable modeling were performed.ResultsOverall, 59,323 (69%) without known CLD received an ALT test. Age, Black race, Latinx ethnicity, and metabolic factors were associated with higher odds of ALT testing, (p < 0.01). Among those with an abnormal ALT (44%) without known CLD: median age 53 years, 41% male, 19% White, 11% Black, 40% Latinx, 29% Asian/Pacific Islander (API), and 84% overweight/obese. On multivariable analysis, female sex (OR 2.7), Latinx ethnicity (OR 2.6), API race (OR 1.3), overweight/obesity (OR 1.8, OR 2.6), and dyslipidemia (OR 1.3) were associated with abnormal ALT, (p ≤ 0.001).ConclusionsIn the absence of known CLD, women, Latinx, API and persons with excess body weight were associated with greater odds of abnormal ALT. Future longitudinal studies are needed to confirm these differences and to determine if adequate work up for CLD is performed for abnormal ALT levels among at‐risk populations.
Managers and shorebird biologists' perceptions of enforcement and voluntary compliance techniques to increase compliance with dog regulations on beaches
Authors: Dayer Ashley A. , Everly Jillian , Comber Carolyn A. , Gore Meredith L. 
Published: August 2022

Abstract

Disturbance to shorebirds by domestic dogs can cause direct and indirect bird mortality. Dog regulations to minimize disturbance are only effective if people comply with them.

Non‐compliance is a universal problem in biodiversity conservation, with an associated body of applicable social science from the field of conservation criminology. We apply the lens of this literature to better understand non‐compliance with dog regulations on beaches along the Atlantic Flyway of the U.S. and the role of law enforcement and voluntary compliance techniques (e.g. persuasive communications, behavioural alternatives) in fostering compliance.

Through in‐depth interviews with 27 land managers and shorebird biologists experienced in creating and/or implementing regulations to reduce disturbance to shorebirds, we found that non‐compliance is a challenge that law enforcement alone is inadequate to address.

Managers are working to overcome these challenges with law enforcement through training law enforcement officers, as well as voluntary compliance approaches, such as conducting on‐site stewardship programs led largely by volunteers, placing educational signage at sites, and highlighting alternative areas to walk dogs.

The early stages of the COVID‐19 pandemic in the U.S. increased dog walking on beaches and exacerbated the issue of non‐compliance and lack of enforcement, while the capacity for educational and stewardship programs was also limited.

We conclude by recommending that managers and biologists tackle non‐compliance with multiple and concurrent strategies along a spectrum from enforcement to voluntary compliance techniques, while also better studying the efficacy of these approaches. We also highlight the importance of continuing to track the ongoing challenges to compliance with biodiversity conservation regulations due to the COVID‐19 pandemic.

Read the free Plain Language Summary for this article on the Journal blog.
Aminolysis of polyesters for cracking and structure clarifying: A review
Authors: Rabiei Navid , Kish Mohammad Haghighat 
Published: August 2022

AbstractCracking of polyester bottles and recycling the waste, which is of concern in the current research works have their roots in the environmental stress cracking and the physical structural analysis, which has been the subject of a huge number of research reports, that are collected in the present review. Polyesters are polymers of high importance in industry and academia, and amines are versatile chemicals that are used for different purposes. The reaction of polyester with amines has been used to reveal structure, improve the properties of products, convert polyesters waste into benign materials, enhance biocompatibility, and so on. The research works reported on the aminolysis of polyesters (PET, PCL, PLA, PTT, PBT, PHB, PEN, PEA) for structure and morphological determination, etching, and stress cracking are critically reviewed. The chemistry and mechanism of the reactions of aminolysis of an ester or a polyester are well documented, and a vast amount of useful information is available. There is a need for further research to answer the remaining questions on the intermediates. Solutions of amines act as environmental stress‐cracking agents, may induce crystallization, and probably it can dissolve and remove a certain amount of disordered regions as well. In the subject of stress cracking that can help the elucidation of the process of aging, it is not yet clear how cracks patterns and sizes (from nano up to micro size) observed on the surface of polyester products depend on the thermal and mechanical history of the samples, and it is not known how to produce cracked patterns according to a pre‐planned design on the surfaces of polyester articles. To make polyesters more useful and safe the structure must be revealed in order to get benefit from the structure–property relations.
Registration of ‘Epoch’ hard red winter wheat
Authors: Baenziger P. S. , Frels K. A. , Boehm J. , Belamkar V. , Rose D. J. , Xu L. , Wegulo S. N. , Regassa T. , Easterly A. C. , Creech C. F. , Santra D. K. , Klein R. N. , Jin Y. , Kolmer J. , Chen M.‐S. , Guttieri M. J. , Bai G. , El‐Basyoni Salah I. , Masterson S. D. , Poland J. 
Published: August 2022

Abstract‘Epoch’ (Reg. no. CV‐1195, PI 699379) hard red winter wheat (Triticum aestivum L.) was developed cooperatively by the Nebraska Agricultural Experiment Station and the USDA‐ARS and released in February 2021 by the developing institutions. It was selected from the cross ‘Hitch’/NW03666. The pedigree of NW03666 is N94S097KS/NE93459. The cross was made in 2009. The F1 generation was grown in Yuma, AZ, in 2010, and the F2 to F3 generations were advanced using the bulk breeding method at Mead, NE, in 2010–2011 to 2011–2012. In 2012–2013, single F3‐derived F4 rows were planted for selection. From 2015 on, Epoch was tested under rainfed or irrigated conditions in single replicate trials with replicated checks (2015) and in replicated alpha lattice trials (2015–2020). There was no further selection in Epoch other than to remove off‐types thereafter. Epoch was selected using both phenotypic and genomic selection for its ability to survive the winter, short stature with strong straw strength, agronomic performance under irrigation, resistance to diseases, and end‐use quality. Epoch seems to be narrowly adapted to irrigated production fields in Nebraska. The name Epoch was chosen because it marks the transition of leadership in the UNL Wheat breeding project from P. Stephen Baenziger to the new wheat breeder, Katherine A. Frels; hence, it marks the end of one era and the beginning of the next.
Crystal structure of Methanococcus jannaschii dihydroorotase
Authors: Vitali Jacqueline , Nix Jay C. , Newman Haley E. , Colaneri Michael J. 
Published: August 2022

AbstractIn this paper, we report the structural analysis of dihydroorotase (DHOase) from the hyperthermophilic and barophilic archaeon Methanococcus jannaschii. DHOase catalyzes the reversible cyclization of N‐carbamoyl‐l‐aspartate to l‐dihydroorotate in the third step of de novo pyrimidine biosynthesis. DHOases form a very diverse family of enzymes and have been classified into types and subtypes with structural similarities and differences among them. This is the first archaeal DHOase studied by x‐ray diffraction. Its structure and comparison with known representatives of the other subtypes help define the structural features of the archaeal subtype. The M. jannaschii DHOase is found here to have traits from all subtypes. Contrary to expectations, it has a carboxylated lysine bridging the two Zn ions in the active site, and a long catalytic loop. It is a monomeric protein with a large β sandwich domain adjacent to the TIM barrel. Loop 5 is similar to bacterial type III and the C‐terminal extension is long.
Toxicity and risk assessment of nine pesticides on nontarget natural predator Harmonia axyridis (Coleoptera: Coccinellidae)
Authors: Cheng Shenhang , Yu Caihong , Xue Mingming , Wang Xiaojun , Chen Liping , Nie Dongxing , Zhang Nan , Zhang Jia , Hou Yanhua , Lin Ronghua 
Published: August 2022

AbstractBACKGROUNDHarmonia axyridis (Coleoptera: Coccinellidae) is a beneficial predatory arthropod in the agricultural ecosystem. For the success and development of integrated pest management strategies, it is essential to assess the toxicity risks of commonly used pesticides to nontarget arthropods.RESULTSThe glass tube residue method was used to determine the risk of nine pesticides to H. axyridis after second‐instar exposure. To assess the potential risk of the selected pesticides, the pre‐adult LR50 values were calculated by the hazard quotient (HQ) method. The LR50 (application rate causing 50% mortality) values of imidacloprid, dinotefuran, thiamethoxam, acetamiprid, bifenthrin, and dimethoate were 0.44, 0.82, 0.10, 0.05, 0.04, and 0.21 g a.i. ha−1, respectively, showing unacceptable risk to H. axyridis after exposure to in and off field. However, emamectin benzoate and two fungicides, tebuconazole and myclobutanil, posed a low risk to H. axyridis and their HQ values were less than the trigger value of 5.CONCLUSIONSThe four neonicotinoid insecticides (imidacloprid, dinotefuran, thiamethoxam, and acetamiprid), pyrethroid bifenthrin, and organophosphorus dimethoate showed a high risk to H. axyridis. Emamectin benzoate, tebuconazole, and myclobutanil showed a low risk to H. axyridis under both exposure scenarios. The results provide critical scientific evidence to guide future regulation of pesticide management practices and protection of nontarget arthropods like H. axyridis. © 2022 Society of Chemical Industry.
Organ‐On‐A‐Chip Models of the Blood–Brain Barrier: Recent Advances and Future Prospects
Authors: Kawakita Satoru , Mandal Kalpana , Mou Lei , Mecwan Marvin Magan , Zhu Yangzhi , Li Shaopei , Sharma Saurabh , Hernandez Ana Lopez , Nguyen Huu Tuan , Maity Surjendu , de Barros Natan Roberto , Nakayama Aya , Bandaru Praveen , Ahadian Samad , Kim Han‐Jun , Herculano Rondinelli Donizetti , Holler Eggehard , Jucaud Vadim , Dokmeci Mehmet Remzi , Khademhosseini Ali 
Published: August 2022

AbstractThe human brain and central nervous system (CNS) present unique challenges in drug development for neurological diseases. One major obstacle is the blood–brain barrier (BBB), which hampers the effective delivery of therapeutic molecules into the brain while protecting it from blood‐born neurotoxic substances and maintaining CNS homeostasis. For BBB research, traditional in vitro models rely upon Petri dishes or Transwell systems. However, these static models lack essential microenvironmental factors such as shear stress and proper cell–cell interactions. To this end, organ‐on‐a‐chip (OoC) technology has emerged as a new in vitro modeling approach to better recapitulate the highly dynamic in vivo human brain microenvironment so‐called the neural vascular unit (NVU). Such BBB‐on‐a‐chip models have made substantial progress over the last decade, and concurrently there has been increasing interest in modeling various neurological diseases such as Alzheimer's disease and Parkinson's disease using OoC technology. In addition, with recent advances in other scientific technologies, several new opportunities to improve the BBB‐on‐a‐chip platform via multidisciplinary approaches are available. In this review, an overview of the NVU and OoC technology is provided, recent progress and applications of BBB‐on‐a‐chip for personalized medicine and drug discovery are discussed, and current challenges and future directions are delineated.
Ultrathin Pd3Pt1Rh0.1 Nanorings with Strong C−C Bond Breaking Ability for the Ethanol Oxidation Reaction
Authors: Tian Hao , Zhu Runxi , Deng Peilin , Li Jing , Huang Wei , Chen Qi , Su Ya‐Qiong , Jia Chunman , Liu Zhongxin , Shen Yijun , Tian Xinlong 
Published: August 2022

AbstractEthanol as a fuel for direct ethanol fuel cells (DEFCs) has the advantages of being highly energetic, environmentally friendly, and low−cost, while the slow anodic ethanol oxidation reaction (EOR), intermediate poisoning effect, and incomplete oxidation of ethanol became obstacles to the development of DEFCs. Herein, a 2D ternary cyclic Pd3Pt1Rh0.1 nanorings (NRs) catalyst with efficient EOR performance is prepared via a facile one−pot solvothermal approach, and systematic studies are carried out to reveal the mechanisms of the enhanced performance and C−C bond selectivity. In particular, the optimized catalyst exhibits impressive mass activity, stability, toxicity resistance, and C−C bond cleavage ability. It's proposed that the considerable performance is attributed to the unique hollow structure, providing abundant active sites. The high toxicity resistance is not only attributed to the electronic modulation of the catalyst material by Rh atoms, but also depends on the excellent water activation properties of Rh, which contribute to the removal of intermediates, such as CO. In addition, the density functional theory calculations showed that the introduction of Rh significantly enhances the C−C bond cleavage ability of the catalyst, further improving the EOR activity.
Synergistic Effects in Ultrafine Molybdenum–Tungsten Bimetallic Carbide Hollow Carbon Architecture Boost Hydrogen Evolution Catalysis and Lithium‐Ion Storage
Authors: Yan Meng , Zhao Zejun , Wang Teng , Chen Rui , Zhou Chenming , Qin Yifan , Yang Shuai , Zhang Mingchang , Yang Yong 
Published: August 2022

AbstractConstructing hierarchical heterostructures is considered a useful strategy to regulate surface electronic structure and improve the electrochemical kinetics. Herein, the authors develop a hollow architecture composed of MoC1‐x and WC1‐x carbide nanoparticles and carbon matrix for boosting electrocatalytic hydrogen evolution and lithium ions storage. The hybridization of ultrafine nanoparticles confined in the N‐doped carbon nanosheets provides an appropriate hydrogen adsorption free energy and abundant boundary interfaces for lithium intercalation, leading to the synergistically enhanced composite conductivity. As a proof of concept, the as‐prepared catalyst exhibits outstanding and durable electrocatalytic performance with a low overpotential of 103 and 163 mV at 10 mA cm−2, as well as a Tafel slope of 58 and 90 mV dec−1 in alkaline electrolyte and acid electrolyte, respectively. Moreover, evaluated as an anode for a lithium‐ion battery, the as‐resulted sample delivers a rate capability of 1032.1 mA h g−1 at 0.1 A g−1. This electrode indicates superior cyclability with a capability of 679.1 mA h g−1 at 5 A g−1 after 4000 cycles. The present work provides a strategy to design effective and stable bimetallic carbide composites as superior electrocatalysts and electrode materials.