bluuebunny/crossref_metadata_2025 huggingface dataset:
Betel quid: New insights into an ancient addiction
Authors: Stokes Clare , Pino Jose A. , Hagan D. Walker , Torres Gonzalo E. , Phelps Edward A. , Horenstein Nicole A. , Papke Roger L.
Published: August 2022

The use of areca nuts (areca) in the form of betel quids constitutes the fourth most common addiction in the world, associated with high risk for oral disease and cancer. Areca is a complex natural product, making it difficult to identify specific components associated with the addictive and carcinogenic properties. It is commonly believed that the muscarinic agonist arecoline is at the core of the addiction. However, muscarinic receptor activation is not generally believed to support drug‐taking behaviour. Subjective accounts of areca use include descriptions of both sedative and stimulatory effects, consistent with the presence of multiple psychoactive agents. We have previously reported partial agonism of α4‐containing nicotinic acetylcholine receptors by arecoline and subsequent inhibition of those receptors by whole areca broth. In the present study, we report the inhibition of nicotinic acetylcholine receptors and other types of neurotransmitter receptors with compounds of high molecular weight in areca and the ability of low molecular weight areca extract to activate GABA and glutamate receptors. We confirm the presence of a high concentration of GABA and glutamate in areca. Additionally, data also indicate the presence of a dopamine and serotonin transporter blocking activity in areca that could account for the reported stimulant and antidepressant activity. Our data suggest that toxic elements of high molecular weight may contribute to the oral health liability of betel quid use, while two distinct low molecular weight components may provide elements of reward, and the nicotinic activity of arecoline contributes to the physical dependence of addiction.
Robotic‐arm assisted total knee arthroplasty has a learning curve of 16 cases and increased operative time of 12 min
Authors: Tay Mei Lin , Carter Matthew , Zeng Nina , Walker Matthew L. , Young Simon W.
Published: August 2022

Background

Robotic‐arm assisted systems are increasingly used for knee arthroplasty, however introduction of new systems can involve a learning curve. We aimed to define the learning curve in terms of operative time and component placement/sizing of a robotic system for total knee arthroplasty (TKA) in a team of experienced surgeons, and to investigate mid‐term patient outcomes.

Methods

A total of 101 consecutive patients underwent primary robotic‐arm assisted TKA by three surgeons (mean 2 year follow‐up). Operative times, component placement, implant sizing and reoperations were recorded. Cumulative Summation (CUSUM) was used to analyse learning curves. Patient outcomes were compared between learning and proficiency phases.

Results

The learning curve was 16 cases, with a 12‐min increase in operative time (P < 0.01). Once proficiency was achieved, the greatest time reductions were seen for navigation registration (P = 0.003) and bone preparation (P < 0.0001). A learning curve was found with polyethylene (PE) insert sizing (P = 0.01). No differences were found between learning and proficiency groups in terms of implant survival (100% and 97%, respectively, NS) or patient‐reported outcome measures at 2 years (NS).

Conclusion

Introduction of a robotic‐arm assisted system for TKA led to increased operative times for navigation registration and bone preparation, and a learning curve with PE insert sizing. No difference in patient outcomes between learning and proficiency groups at 2 years was found. These findings can inform surgeons' expectations when starting to use robotic‐assisted systems.
Action is needed to tackle the clinical, psychological and socioeconomic impact of perinatal COVID‐19
Authors: Briana Despina D. , Papaevangelou Vassiliki , Malamitsi‐Puchner Ariadne
Published: August 2022

The COVID‐19 pandemic has turned perinatal healthcare into a worldwide public health challenge. Although initial data did not demonstrate pregnancy as a more susceptible period to adverse outcomes of severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) infection, an increasing number of reports now certify maternal illness as a high‐risk condition for the development of maternal–fetal complications. Despite the rarity of SARS‐CoV‐2 vertical transmission, severe maternal illness might induce adverse perinatal and neonatal outcomes. Additionally, perinatal COVID‐19 data may raise concerns about long‐term harmful consequences to the offspring in the framework of non‐communicable diseases. The World Health Organisation, as well as scientific literature, consider the protection of the maternal–fetal dyad against COVID‐19 as a critical issue and, therefore, strongly promote and encourage the vaccination of pregnant and lactating women. Furthermore, the pandemic has triggered an unprecedented recession, leading to historic levels of unemployment and deprivation, while health, societal, economic and gender inequities particularly affecting low‐income and middle‐income countries, have increased. This mini‐review provides an updated brief report on historical, clinical, psychological and socioeconomic aspects of the COVID‐19 pandemic based on 10 lectures presented at the 9th Maria‐Delivoria‐Papadopoulos Perinatal Symposium, held virtually on 19 March 2022.
Systemic exposure to hydroxychloroquine and its relationship with outcome in severely ill COVID‐19 patients in New York City
Authors: Lyashchenko Alex K. , Yu Yifan , McMahon Donald J. , Bies Robert , Yin Michael T. , Cremers Serge
Published: August 2022

Aim

To investigate the relationship between systemic exposure to hydroxychloroquine (HCQ) and its metabolite desethylhydroxychloroquine (DHCQ) and clinical outcome in severely ill patients treated with a standard oral dose regimen of HCQ during the first wave of COVID‐19 in New York City.

Methods

We correlated retrospective clinical data with drug exposure prospectively assessed from convenience samples using population pharmacokinetics and Bayesian estimation. Systemic exposure was assessed in 215 patients admitted to ICU or COVID‐ward for whom an interleukin‐6 level was requested and who were still alive 24 hours after the last dose of HCQ. Patients received oral HCQ 600 mg twice daily on day 1 followed by 4 days of 400 mg daily.

Results

Fifty‐three precent of the patients were intubated at 5.4 ± 6.4 days after admission and 26.5% died at an average of 32.2 ± 19.1 days. QTc at admission was 448 ± 34 ms. Systemic exposure to HCQ and DHCQ demonstrated substantial variability. Cumulative area under the serum concentration–time curve up to infinity for HCQ was 71.4 ± 19.3 h mg/L and for DHCQ 56.5 ± 28.3 h mg/L. Variability in systemic exposure was not clearly explained by renal function, liver function or inflammatory state. In turn, systemic exposure did not correlate with intubation status, survival or QTc prolongation.

Conclusion

This study in severely ill patients was not able to find any relationship between systemic exposure to HCQ and DHCQ and clinical outcome at a routine dose regimen and adds to the growing body of evidence that oral HCQ does not alter the course of disease in COVID‐19 patients.
A song of volumes, surfaces and fluxes: The case study of the Central Mallorca Depression (Balearic Promontory) during the Messinian Salinity Crisis
Authors: Raad Fadl , Ebner Ronja , Heida Hanneke , Meijer Paul , Lofi Johanna , Maillard Agnès , Garcia‐Castellanos Daniel
Published: August 2022

The Central Mallorca Depression (CMD) located in the Balearic Promontory (Western Mediterranean) contains a well‐preserved evaporitic sequence belonging to the Messinian Salinity Crisis (MSC) salt giant, densely covered by high‐ and low‐resolution seismic reflection data. It has been proposed recently that the MSC evaporitic sequence in the CMD could be a non‐deformed analogue of the key MSC area represented by the Caltanissetta Basin in Sicily. This presumed similarity makes the CMD an interesting system to better understand the MSC events. Physics‐based box models of the water mixing between sub‐basins, built on conservation of mass of water and salt, help constrain the hydrological conditions under which evaporites formed during the MSC. Those models have been widely used in the literature of the MSC in the past two decades. They have been mostly applied to the Mediterranean Sea as a whole focusing on the Mediterranean–Atlantic connection, or focusing on the influence of the Sicily Sill connecting the Western and Eastern Mediterranean Sea. In this study, we apply a downscaled version of such modelling technique to the CMD. First, we quantify the present‐day volumes of the MSC units. We then use a reconstructed pre‐MSC paleo‐bathymetry to model salinity changes as a function of flux exchanges between the CMD and the Mediterranean. We show that a persistent connection between the CMD and the Mediterranean brine near gypsum saturation can explain volume of Primary Lower Gypsum under a sea level similar to the present. For the halite, on the contrary, we show that the observed halite volume cannot be deposited from a connected CMD‐Mediterranean scenario, suggesting a drawdown of at least 850 m (sill depth) is necessary. Comparison between the deep basin halite volume and that of the CMD shows that it is possible to obtain the observed halite volume in both basins from a disconnected Mediterranean basin undergoing drawdown, although determining the average salinity of the Western Mediterranean basin at the onset of drawdown requires further investigation.
Development and multi‐institutional validation of an artificial intelligence‐based diagnostic system for gastric biopsy
Authors: Abe Hiroyuki , Kurose Yusuke , Takahama Shusuke , Kume Ayako , Nishida Shu , Fukasawa Miyako , Yasunaga Yoichi , Ushiku Tetsuo , Ninomiya Youichiro , Yoshizawa Akihiko , Murao Kohei , Sato Shin’ichi , Kitsuregawa Masaru , Harada Tatsuya , Kitagawa Masanobu , Fukayama Masashi ,   Japan Pathology AI Diagnostics/National Institution of Informatics (JP‐AID/NII) Study Group for Gastric Biopsy Pathology
Published: August 2022

To overcome the increasing burden on pathologists in diagnosing gastric biopsies, we developed an artificial intelligence‐based system for the pathological diagnosis of gastric biopsies (AI‐G), which is expected to work well in daily clinical practice in multiple institutes. The multistage semantic segmentation for pathology (MSP) method utilizes the distribution of feature values extracted from patches of whole‐slide images (WSI) like pathologists’ “low‐power view” information of microscopy. The training dataset included WSIs of 4511 gastric biopsy tissues from 984 patients. In tissue‐level validation, MSP AI‐G showed better accuracy (91.0%) than that of conventional patch‐based AI‐G (PB AI‐G) (89.8%). Importantly, MSP AI‐G unanimously achieved higher accuracy rates (0.946 ± 0.023) than PB AI‐G (0.861 ± 0.078) in tissue‐level analysis, when applied to the cohorts of 10 different institutes (3450 samples of 1772 patients in all institutes, 198–555 samples of 143–206 patients in each institute). MSP AI‐G had high diagnostic accuracy and robustness in multi‐institutions. When pathologists selectively review specimens in which pathologist’s diagnosis and AI prediction are discordant, the requirement of a secondary review process is significantly less compared with reviewing all specimens by another pathologist.
Seeing Through Sounds: Mapping Auditory Dimensions to Data and Charts for People with Visual Impairments
Authors: Wang R. , Jung C. , Kim Y.
Published: August 2022

Sonification can be an effective medium for people with visual impairments to understand data in visualizations. However, there are no universal design principles that apply to various charts that encode different data types. Towards generalizable principles, we conducted an exploratory experiment to assess how different auditory channels (e.g., pitch, volume) impact the data and visualization perception among people with visual impairments. In our experiment, participants evaluated the intuitiveness and accuracy of the mapping of auditory channels on different data and chart types. We found that participants rated pitch to be the most intuitive, while the number of tappings and the length of sounds yielded the most accurate perception in decoding data. We study how audio channels can intuitively represent different charts and demonstrate that data‐level perception might not directly transfer to chart‐level perception as participants reflect on visual aspects of the charts while listening to audio. We conclude by how future experiments can be designed to establish a robust ranking for creating audio charts.
Reusing Interactive Analysis Workflows
Authors: Gadhave K. , Cutler Z. , Lex A.
Published: August 2022

Interactive visual analysis has many advantages, but an important disadvantage is that analysis processes and workflows cannot be easily stored and reused. This is in contrast to code‐based analysis workflows, which can simply be run on updated datasets, and adapted when necessary. In this paper, we introduce methods to capture workflows in interactive visualization systems for different interactions such as selections, filters, categorizing/grouping, labeling, and aggregation. These workflows can then be applied to updated datasets, making interactive visualization sessions reusable. We demonstrate this specification using an interactive visualization system that tracks interaction provenance, and allows generating workflows from the recorded actions. The system can then be used to compare different versions of datasets and apply workflows to them. Finally, we introduce a Python library that can load workflows and apply it to updated datasets directly in a computational notebook, providing a seamless bridge between computational workflows and interactive visualization tools.
Barrio: Customizable Spatial Neighborhood Analysis and Comparison for Nanoscale Brain Structures
Authors: Troidl Jakob , Cali Corrado , Gröller Eduard , Pfister Hanspeter , Hadwiger Markus , Beyer Johanna
Published: August 2022

High‐resolution electron microscopy imaging allows neuroscientists to reconstruct not just entire cells but individual cell substructures (i.e., cell organelles) as well. Based on these data, scientists hope to get a better understanding of brain function and development through detailed analysis of local organelle neighborhoods. In‐depth analyses require efficient and scalable comparison of a varying number of cell organelles, ranging from two to hundreds of local spatial neighborhoods. Scientists need to be able to analyze the 3D morphologies of organelles, their spatial distributions and distances, and their spatial correlations. We have designed Barrio as a configurable framework that scientists can adjust to their preferred workflow, visualizations, and supported user interactions for their specific tasks and domain questions. Furthermore, Barrio provides a scalable comparative visualization approach for spatial neighborhoods that automatically adjusts visualizations based on the number of structures to be compared. Barrio supports small multiples of spatial 3D views as well as abstract quantitative views, and arranges them in linked and juxtaposed views. To adapt to new domain‐specific analysis scenarios, we allow the definition of individualized visualizations and their parameters for each analysis session. We present an in‐depth case study for mitochondria analysis in neuronal tissue and demonstrate the usefulness of Barrio in a qualitative user study with neuroscientists.
LineageD: An Interactive Visual System for Plant Cell Lineage Assignments based on Correctable Machine Learning
Authors: Hong Jiayi , Trubuil Alain , Isenberg Tobias
Published: August 2022

We describe LineageD—a hybrid web‐based system to predict, visualize, and interactively adjust plant embryo cell lineages. Currently, plant biologists explore the development of an embryo and its hierarchical cell lineage manually, based on a 3D dataset that represents the embryo status at one point in time. This human decision‐making process, however, is time‐consuming, tedious, and error‐prone due to the lack of integrated graphical support for specifying the cell lineage. To fill this gap, we developed a new system to support the biologists in their tasks using an interactive combination of 3D visualization, abstract data visualization, and correctable machine learning to modify the proposed cell lineage. We use existing manually established cell lineages to obtain a neural network model. We then allow biologists to use this model to repeatedly predict assignments of a single cell division stage. After each hierarchy level prediction, we allow them to interactively adjust the machine learning based assignment, which we then integrate into the pool of verified assignments for further predictions. In addition to building the hierarchy this way in a bottom‐up fashion, we also offer users to divide the whole embryo and create the hierarchy tree in a top‐down fashion for a few steps, improving the ML‐based assignments by reducing the potential for wrong predictions. We visualize the continuously updated embryo and its hierarchical development using both 3D spatial and abstract tree representations, together with information about the model's confidence and spatial properties. We conducted case study validations with five expert biologists to explore the utility of our approach and to assess the potential for LineageD to be used in their daily workflow. We found that the visualizations of both 3D representations and abstract representations help with decision making and the hierarchy tree top‐down building approach can reduce assignments errors in real practice.
SimilarityNet: A Deep Neural Network for Similarity Analysis Within Spatio‐temporal Ensembles
Authors: Huesmann Karim , Linsen Lars
Published: August 2022

Latent feature spaces of deep neural networks are frequently used to effectively capture semantic characteristics of a given dataset. In the context of spatio‐temporal ensemble data, the latent space represents a similarity space without the need of an explicit definition of a field similarity measure. Commonly, these networks are trained for specific data within a targeted application. We instead propose a general training strategy in conjunction with a deep neural network architecture, which is readily applicable to any spatio‐temporal ensemble data without re‐training. The latent‐space visualization allows for a comprehensive visual analysis of patterns and temporal evolution within the ensemble. With the use of SimilarityNet, we are able to perform similarity analyses on large‐scale spatio‐temporal ensembles in less than a second on commodity consumer hardware. We qualitatively compare our results to visualizations with established field similarity measures to document the interpretability of our latent space visualizations and show that they are feasible for an in‐depth basic understanding of the underlying temporal evolution of a given ensemble.
Neural Flow Map Reconstruction
Authors: Sahoo S. , Lu Y. , Berger M.
Published: August 2022

In this paper we present a reconstruction technique for the reduction of unsteady flow data based on neural representations of time‐varying vector fields. Our approach is motivated by the large amount of data typically generated in numerical simulations, and in turn the types of data that domain scientists can generate in situ that are compact, yet useful, for post hoc analysis. One type of data commonly acquired during simulation are samples of the flow map, where a single sample is the result of integrating the underlying vector field for a specified time duration. In our work, we treat a collection of flow map samples for a single dataset as a meaningful, compact, and yet incomplete, representation of unsteady flow, and our central objective is to find a representation that enables us to best recover arbitrary flow map samples. To this end, we introduce a technique for learning implicit neural representations of time‐varying vector fields that are specifically optimized to reproduce flow map samples sparsely covering the spatiotemporal domain of the data. We show that, despite aggressive data reduction, our optimization problem — learning a function‐space neural network to reproduce flow map samples under a fixed integration scheme — leads to representations that demonstrate strong generalization, both in the field itself, and using the field to approximate the flow map. Through quantitative and qualitative analysis across different datasets we show that our approach is an improvement across a variety of data reduction methods, and across a variety of measures ranging from improved vector fields, flow maps, and features derived from the flow map.
Exploring How Visualization Design and Situatedness Evoke Compassion in the Wild
Authors: Morais L. , Andrade N. , Sousa D.
Published: August 2022

This work explores how the design and situatedness of data representations affect people's compassion with a case study concerning harassment episodes in a public place. Results contribute to advancing the understanding of how visualizations can evoke emotions and their impact on prosocial behaviors, such as helping people in need. Recent literature examined the effect of different on‐screen data representations on emotion or prosociality, but little has been done concerning visualizations shown in a public place — especially a space contextually relevant to the data — or presented through unconventional media formats such as physical marks. We conducted two in‐the‐wild studies to investigate how different factors affect people's self‐reported compassion and intention to donate. We compared three ways of presenting data about the harassment cases: (1) communicating data only verbally; (2) using a printed poster with aggregated information; and (3) using a physicalization with detailed information about each story. We found that the physicalization influenced people to donate more than only hearing about the data, but it is unclear if the same applied to the poster visualization. Also, passers‐by reported a likely small increase in compassion when they saw the physicalization instead of the poster. We also examined the role of situatedness by showing the physicalization in a site that is not contextually relevant to the data. Our results suggest that people had a similar intention to donate and levels of compassion in both places. Those findings may indicate that using specific visualization designs to support campaigns about sensitive causes (e.g., sexual harassment) can increase the emotional response of passers‐by and may motivate them to help, independently of where the data representation is shown. Finally, this work also informs on the strengths and weaknesses of using research in the wild to evaluate data visualizations in public spaces.
VIBE: A Design Space for VIsual Belief Elicitation in Data Journalism
Authors: Mahajan Shambhavi , Chen Bonnie , Karduni Alireza , Kim Yea‐Seul , Wall Emily
Published: August 2022

The process of forming, expressing, and updating beliefs from data plays a critical role in data‐driven decision making. Effectively eliciting those beliefs has potential for high impact across a broad set of applications, including increased engagement with data and visualizations, personalizing visualizations, and understanding users' visual reasoning processes, which can inform improved data analysis and decision making strategies (e.g., via bias mitigation). Recently, belief‐driven visualizations have been used to elicit and visualize readers' beliefs in a visualization alongside data in narrative media and data journalism platforms such as the New York Times and FiveThirtyEight. However, there is little research on different aspects that constitute designing an effective belief‐driven visualization. In this paper, we synthesize a design space for belief‐driven visualizations based on formative and summative interviews with designers and visualization experts. The design space includes 7 main design considerations, beginning with an assumed data set, then structured according to: from who, why, when, what, and how the belief is elicited, and the possible feedback about the belief that may be provided to the visualization viewer. The design space covers considerations such as the type of data parameter with optional uncertainty being elicited, interaction techniques, and visual feedback, among others. Finally, we describe how more than 24 existing belief‐driven visualizations from popular news media outlets span the design space and discuss trends and opportunities within this space.
Effect of dentine site on resin and cement adaptation tested using X‐ray and electron microscopy to evaluate bond durability and adhesive interfaces
Authors: Weerakoon Arosha Tania , Cooper Crystal , Sokolowski Kamil Andrzej , Meyers Ian Arthur , Thomson David , Ford Pauline Jane , Sexton Christopher , Symons Anne Louise
Published: August 2022

Glass ionomer (GI) cements and self‐etch (SE) or universal adhesives after etching (ER) adapt variably with dentine. Dentine characteristics vary with depth (deep/shallow), location (central/peripheral), and microscopic site (intertubular/peritubular). To directly compare adhesion to dentine, non‐destructive imaging and testing are required. Here, GI, ER, and SE adapted at different dentine depths, locations, and sites were investigated using micro‐CT, xenon plasma focused ion beam scanning electron microscopy (Xe PFIB‐SEM), and energy dispersive X‐ray spectroscopy (EDS). Extracted molars were prepared to deep or shallow slices and treated with the three adhesives. Micro‐CT was used to compare changes to air volume gaps, following thermocycling, and statistically analysed using a quantile regression model and Fisher's exact test. The three adhesives performed similarly across dentine depths and locations, yet no change or overall increases and decreases in gaps at all dentine depths and locations were measured. The Xe PFIB‐SEM‐milled dentine‐adhesive interfaces facilitated high‐resolution characterization, and element profiling revealed variations across the tooth‐material interfaces. Dentine depth and location had no impact on adhesive durability, although microscopic differences were observed. Here we demonstrate how micro‐CT and Xe PFIB‐SEM can be used to compare variable dental materials without complex multi‐stage specimen preparation to minimize artefacts.
The effect of season, management and endocrinopathies on vitamin D status in horses
Authors: Dosi Miranda C. M. C. , McGorum Bruce C. , Kirton Roxane D. , Cillán‐García Eugenio , Mellanby Richard J. , Keen John A. , Hurst Emma A. , Morgan Ruth A.
Published: August 2022

Background

Vitamin D deficiency is common in humans and is increasingly linked to the pathogenesis of a multitude of diseases including obesity and metabolic syndrome. The biology of vitamin D in horses is poorly described; the relative contribution of the diet and skin synthesis to circulating concentrations is unclear and associations with the endocrine disease have not been explored.

Objectives

To determine the relationship between management, season and endocrine disease and vitamin D status in horses.

Study design

Cross‐sectional cohort study.

Methods

Plasma concentrations of 25‐hydroxyvitamin D2(25(OH)D2) and D3(25(OH)D3) were measured by liquid chromatography‐tandem mass spectrometry in 34 healthy unsupplemented grazing ponies and 22 stabled Thoroughbreds receiving supplementary vitamin D3in feed. A nested group of 18 grazing ponies were sampled on long and short days (>12 and <12 h of light/day) to determine the effect of sunlight exposure. In addition, the relationships between age, sex, adiposity, serum insulin, adrenocorticotropic hormone and vitamin D status were assessed in a mixed group of 107 horses using a linear regression model.

Results

All animals had a measurable level of 25(OH)D2(median 10.7 nmol/L) whilst 25(OH)D3was only detected in Thoroughbreds receiving D3supplementation. Thoroughbreds had lower concentrations of 25(OH)D2than ponies (7.4 vs. 12.6 nmol/L,p < 0.01). In grazing ponies, 25(OH)D2concentrations were significantly higher on long days compared to short days (14.4 vs. 8.7 nmol/L,p < 0.01), whilst 25(OH)D3was undetectable. Measures of increased adiposity, but not basal insulin, were associated with higher 25(OH)D2concentrations, conversely to humans. Increasing ACTH was associated with lower 25(OH)D2(p < 0.01).

Main limitations

Vitamin D2concentrations were not measured in grass or forage.

Conclusions

In horses 25(OH)D2is the predominant vitamin D metabolite, and there is an apparent lack of endogenous vitamin D3production. The relationship between vitamin D and endocrine disorders in horses does not reflect that of other species and warrants further investigation.
Imiquimod‐induced ex vivo model of psoriatic human skin via interleukin‐17A signalling of T cells and Langerhans cells
Authors: Carlos Eduarda Cristina da Silva , Cristovão Gabrielly Alves , Silva Alcimar Alves , Ribeiro Bianca Cristina de Santos , Romana‐Souza Bruna
Published: August 2022

Several in vitro models have been developed to study the mechanisms involved in psoriasis and to screen new antipsoriatic drugs. However, most of them use single‐cell or reconstructed human skin models that did not have complex anatomy of human skin. Thus, this study aimed to create a new model of psoriasis‐like dermatitis using human skin under in vitro conditions. To perform this, human skin explants were topically treated with imiquimod (IMQ) or vehicle for 2, 3 or 6 consecutive days. Some explants were treated with an anti‐psoriatic drug or antibody anti‐interleukin‐17A (IL‐17A). Topical application of IMQ increased total epidermal area, epidermal proliferation and keratinocyte differentiation at 3, 4 or 7 days. The protein levels of CD3 were augmented in the IMQ‐treated human skin explants at 7 days reflecting the activation of T cells. Topical IMQ promoted a higher protein and mRNA levels of IL‐17A in human skin ex vivo. Immunofluorescence analysis showed CD207‐positive Langerhans cells (LCs) and CD3‐positive T cells expressing IL‐17A in IMQ‐treated human skin explants at 7 days. In addition, administration of antibody anti‐IL‐17A or an anti‐psoriatic drug inhibited IMQ‐induced increase in the epidermal thickness in ex vivo human skin at 7 days. In conclusion, topical IMQ application promotes epidermal changes in ex vivo human skin that resemble to human psoriatic skin lesions. Moreover, IMQ‐induced production of IL‐17 by LCs and T cells is critical to development of psoriasis‐like inflammation in our model. This new model is suitable for in vitro screening of antipsoriatic drugs.
Deacetylation kinetics of promising energy crops, hemp and kenaf, for cellulosic ethanol production
Authors: Ju Yebin , Kim In Jung , Kim Suhyeung , Olawuyi Ibukunoluwa Fola , Kim Kyung‐Min , Kim Soo Rin
Published: August 2022

Lignocellulosic hydrolysates contain acetic acid derived from hemicellulose. Acetate released during acid pretreatment interferes with enzymatic saccharification of the biomass and inhibits yeast fermentation, caused by cellular oxidation and stress. This study used alkaline deacetylation prior to acid pretreatment and evaluated its influence on the fermentation performance of Saccharomyces cerevisiae using two different lignocellulosic biomasses, hemp (Cannabis sativa) and kenaf (Hibiscus cannabinus). They are valuable for biofuel production. The maximal acetate removal with minimal sugar loss was obtained with 1% (w/v) NaOH treatment for both biomasses. Deacetylation pretreatment under this condition was effective both in enzymatic saccharification and simultaneous saccharification and fermentation. This resulted in improved ethanol production by xylose‐consuming yeast (S. cerevisiae SR8) by removing 4.7 g/L of acetate from hemp and 6.3 g/L from kenaf, thus resulting in the ethanol productivities of 0.79 and 0.67 g/L‐h from hemp and kenaf, respectively. This suggests that strategies to overcome acetate inhibition are necessary to efficiently use the lignocellulosic biomass as a source for bioenergy production.
Direct and indirect interactions between biochar properties, plant belowground traits, and plant performance
Authors: Honvault Nicolas , Nobile Cécile , Faucon Michel‐Pierre , Firmin Stéphane , Houben David
Published: August 2022

Biochar is more and more widely recognized as a promising agricultural amendment improving yield and ecosystem services in a range of different contexts. However, underlying mechanisms contributing to biochars benefits, notably biochar–root interactions, and their mediation by biochar's diverse properties remain unclear and poorly quantified. This study aimed to examine and quantify the interactions between biochar properties and plant traits and their effect on plant performance. To gain a better understanding of biochar–plant interactions and their role in biochar overall effects, biochars with contrasted physical and chemical properties were applied to soils during a 3‐month greenhouse experiment with barley (Hordeum vulgare L.). Barley biomass as well as several belowground morphological and physiological traits and aboveground traits related to nutrient acquisition were measured. A multivariate structural modeling approach was employed to quantify interactions between biochar properties and plant traits, and their feedback effect on plant biomass. Interactions between biochar chemical and physical properties and barley carboxylate release rate and their contribution to biochar effects were underlined. Among the plant traits examined the release of carboxylate appears as the best proxy to plant biomass following biochar addition, highlighting sparsely reported interactions between total carboxylate release rates and biochar ash content. Multivariate structural modeling offered elements of understanding for the complex interconnected mechanisms involved in biochar influence and their relative contribution. Adopting this approach across a wide range of species and contexts could contribute to ensure more reliable biochar benefits.
The association of the Japan Science and Technology Agency Index of Competence with physical and cognitive function in community‐dwelling older adults
Authors: Shoji Takuro , Fujii Yuya , Tateoka Korin , Tsuji Taishi , Okura Tomohiro
Published: August 2022

Aim

To investigate the association of the Japan Science and Technology Agency Index of Competence with physical and cognitive functions in community‐dwelling older adults.

Methods

This study used the data of 565 community‐dwelling adults aged ≥65 years (mean age: 74.3 ± 5.2 years) from the Kasama Health Checkup for Longevity survey in Japan. The Japan Science and Technology Agency Index of Competence was used to comprehensively evaluate the higher‐level functional capacity and subscale functional capacity: technology usage, information practice, life management and social engagement. Physical functions were assessed using grip strength, the five‐repetition sit‐to‐stand test, 5‐m habitual walking test, one‐leg standing test and hand working test with a pegboard. Cognitive functions were evaluated using the Five‐Cog test consisting of attention, memory ability, visuospatial function, language ability and reasoning ability. Multiple regression analysis was conducted to examine the associations between total Japan Science and Technology Agency Index of Competence score and physical and cognitive functions.

Results

After adjusting for potential confounders, the total Japan Science and Technology Agency Index of Competence score was favorably associated with static balance ability (β = 0.09; B = 0.01; 95% confidence interval: 0.00–0.02), lower limb strength (β = −0.19; B = −0.29; 95% confidence interval: −0.41 to −0.16), walking ability (β = −0.15; B = −0.67; 95% confidence interval: −1.05 to −0.30), hand dexterity (β = −0.13; B = −0.08; 95% confidence interval: −0.14 to −0.03) and overall cognitive function (β = 0.28; B = 0.04; 95% confidence interval: 0.03–0.05).

Conclusions

Physical and cognitive functions are important for maintaining higher‐level functional capacity. Geriatr Gerontol Int 2022; 22: 753–758.
A prospective multicenter study on cutaneous reactions reported after SinopharmCOVID‐19 vaccination
Authors: Shawky Ahmed , Elrewiny Emad M. , Gharib Khaled , Sallam Manar , Mansour Mofreh , Rageh Mahmoud A.
Published: August 2022

Background

The new coronavirus COVID‐19 pandemic has had an unprecedented impact on global health and economic growth. A widely used vaccine is the weakened inactivated severe acute respiratory syndrome‐coronavirus‐2 (SARS‐CoV‐2) virus (Sinopharm). Following major SARS‐CoV‐2 vaccination campaigns, cutaneous symptoms are on the rise.

Methods

This study is a prospective observational study evaluating cutaneous reactions and time of recovery after Sinopharm vaccination. The cases involved were over the age of 18. The data were anonymized. On the registry's vaccine section, we tracked vaccination dates, skin reactions, and recovery times. All respondents who reported only a cutaneous reaction to the first vaccination dose received a follow‐up contact asking about a second vaccination dose cutaneous reaction.

Results

The study included 4560 cases. The mean age of all studied cases was 41.2 ± 6.1 years. There were dermatologic complications in 1190 patients (26.1%). There was induration at the injection site in 495 patients (10.9%), urticaria in 210 patients (4.6%), morbilliform eruption in 375 patients (8.2%), flare of skin site in 105 patients (2.3%), and angioedema in 105 patients (2.3%). The mean recovery days in all studied patients were 2.92 ± 0.94 days with a minimum recovery period of 2 days and a maximum of 7 days.

Conclusions

Because Sinopharm's cutaneous reactions are frequently mild and self‐limiting, vaccination should not be discouraged based on these findings. If the first vaccine dose creates a cutaneous reaction, there is no need to skip the second dose.
Evaluation of the effect of sage seed gum (Salvia macrosiphon) conjugation on physicochemical and antimicrobial properties of egg white protein
Authors: Ghani Ali , Tabibiazar Mahnaz , Mahmoudzadeh Maryam , Golchinfar Zahra , Rad Aziz Homayouni
Published: August 2022

Sage seed gum (SSG), a galactomannan hydrocolloid, possesses excellent thickening, stabilising and antimicrobial properties. This study aimed to investigate the effect of SSG conjugation on the functional, antimicrobial and antioxidant properties of EWP. EWP‐SSG conjugates were prepared by dry heat treatment of EWP‐SSG mixture at 60 °C and 79% relative humidity for 3‐, 5‐, 7‐ and 10‐day incubation. Interaction of reducing‐end SSG with amino groups of EWP was confirmed by melanoidin compounds content, free amino groups (FAG), Fourier transform infrared (FT‐IR), sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS‐PAGE) and scanning electron microscopy (SEM). The results indicated solubility, foaming capacity, foaming stability, emulsification activity index and emulsification stability index remarkably increased after 5 days of incubation. Conjugation led to enhanced antimicrobial activity in 10‐day conjugated samples, so higher antibacterial activity against Bacillus cereus and Staphylococcus aureus was obtained compared with antibiotic disc. Comparison of emulsions (O/W) stabilised by 5‐day conjugate, EWP‐SSG mixture and unmodified EWP revealed better physical stability behaviour in 5‐day conjugate against ionic, pH and thermal stresses, suggesting its potential application in different food processing conditions. The findings showed dry heat‐treated SSG‐EWP conjugate could enhance the functional, antioxidant and antimicrobial properties of EWP.
Gender differences in the experience of burnout and its correlates among Chinese psychiatric nurses during the COVID‐19 pandemic: A large‐sample nationwide survey
Authors: Zhang Ling , Li Mengdie , Yang Yating , Xia Lei , Min Kaiyuan , Liu Tingfang , Liu Yuanli , Kaslow Nadine J. , Liu Daphne Y. , Tang Yi‐lang , Jiang Feng , Liu Huanzhong
Published: August 2022

Psychiatric nurses often experience burnout and other mental health symptoms. However, few studies have examined these phenomena and gender‐specific associated factors during the COVID‐19 pandemic. We surveyed a national sample of psychiatric nurses (N = 8971) from 41 tertiary psychiatric hospitals in China as part of a large national survey conducted during the pandemic. The Maslach Burnout Inventory‐Human Service Survey was used to assess burnout and the Depression, Anxiety, and Stress Scale‐21 was used to assess mental health symptoms. Binary logistic regression analyses were used to explore factors associated with burnout in the entire sample and separately by gender. The overall prevalence of burnout was 27.27%, with the rate in male psychiatric nurses (32.24%) being significantly higher than that in female psychiatric nurses (25.97%). Many key demographic factors (such as the male gender and marital status), work‐related variables (such as a mid‐level professional title, having an administrative position, longer working hours, more monthly night shifts, and the perceived negative impact of the COVID‐19 pandemic on medical work) were significantly associated with burnout in the whole sample. Moreover, burnout was associated with depression, anxiety, and stress symptoms in the whole sample. Gender‐specific factors associated with burnout were also identified: burnout was associated with night shifts in male psychiatric nurses, whereas it was associated with single or married marital status, a mid‐level professional title, and having an administrative position among female psychiatric nurses. The high rates of burnout and mental health symptoms in psychiatric nurses need attention from hospital administrators. While mental health symptoms, longer working hours, and the perceived impact of COVID‐19 are associated with burnout in both genders, gender‐specific factors also warrant special attention when developing gender‐specific interventions.
Does income moderate basic relationship processes?
Authors: Johnson Matthew D. , Stanley Scott M. , Rhoades Galena K.
Published: August 2022

Objective

This study explores whether household income moderates the predictive association from adaptive processes (positive and negative interactions and commitment), enduring vulnerabilities (psychological distress), and stressors (financial strain) to future relationship satisfaction?

Background

Theory and research have long conceptualized socioeconomic status as a predictor of couple relations, but recent work questions whether socioeconomic status may moderate basic couple relationship processes.

Method

This study used data from a U.S. national sample of 927 adults aged 18–34 years in a cohabiting (marital or nonmarital) different‐sex partnership (66% female; 22% non‐White; 47% earned a high school diploma or GED as their highest education credential) surveyed five times at 4‐ to 6‐month intervals. A series of latent curve models with structured residuals were used to examine between‐ and within‐person associations.

Results

Robust between‐persons associations emerged consistent with prior literature (e.g., those with more positive and less negative interactions, higher commitment, lower psychological distress, and less financial strain reported higher relationship satisfaction). One robust longitudinal association emerged at the within‐person level: higher than typical negative interactions predicted intraindividual decreases in future relationship satisfaction. Within‐person associations were more evident in the cross‐section: at times when positive interactions and commitment were higher than one's own average and negative interactions and psychological distress were lower than average, relationship satisfaction was also higher than average. Income did not moderate any links with future relationship satisfaction.

Conclusion

Results suggest that basic longitudinal processes in relationships operate consistently across income level.
Parenting stress, maternal depression and child mental health in a Melbourne cohort before and during the COVID‐19 pandemic
Authors: Galbally Megan , Watson Stuart J , Lewis Andrew J , van IJzendoorn Marinus H
Published: August 2022

Aim

This paper aims to examine the maternal and child mental health and parenting outcomes in the context of COVID‐19 pandemic conditions using a sample from Melbourne, Australia – a city exposed to one of the longest lockdowns world‐wide in response to the pandemic.

Methods

This study utilises observational data from a prospective, pregnancy cohort, Mercy Pregnancy Emotional Wellbeing Study and includes 468 women and their children followed up in Melbourne to 3–4 years postpartum pre‐COVID pandemic and compared to those followed up during the COVID‐19 pandemic.

Results

When compared to mothers followed up at 3–4 years postpartum pre‐pandemic, those followed up during the COVID‐19 pandemic showed higher depressive symptoms with a steep incline in their symptom trajectory (EMMdifference = 1.72, Bonferroni‐corrected P < 0.01, d = 0.35) and had a three times higher risk of scoring 13 or above on the EPDS (aRR = 3.22, Bonferroni‐corrected P < 0.01). Although this increase was not associated with the variation in the duration of exposure to pandemic conditions, the steep increase in depressive symptoms was more pronounced in those with pre‐existing depressive disorders. There was no difference in parenting stress or adjusted childhood mental health symptoms or disorder.

Conclusions

Our findings highlight the vulnerability of those with pre‐existing clinical mental health disorders and the need for adequate clinical care for this vulnerable group. Equally, our study indicates the possibility that  parenting and early childhood mental health outcomes, at least in the short term, may be resilient.
Diversity, migration routes, and worldwide population genetic structure of Lecanosticta acicola, the causal agent of brown spot needle blight
Authors: Laas Marili , Adamson Kalev , Barnes Irene , Janoušek Josef , Mullett Martin S. , Adamčíková Katarína , Akiba Mitsuteru , Beenken Ludwig , Braganca Helena , Bulgakov Timur S. , Capretti Paolo , Cech Thomas , Cleary Michelle , Enderle Rasmus , Ghelardini Luisa , Jankovský Libor , Markovskaja Svetlana , Matsiakh Iryna , Meyer Joana B. , Oskay Funda , Piškur Barbara , Raitelaitytė Kristina , Sadiković Dušan , Drenkhan Rein
Published: August 2022

Lecanosticta acicola is a pine needle pathogen causing brown spot needle blight that results in premature needle shedding with considerable damage described in North America, Europe, and Asia. Microsatellite and mating type markers were used to study the population genetics, migration history, and reproduction mode of the pathogen, based on a collection of 650 isolates from 27 countries and 26 hosts across the range of L. acicola. The presence of L. acicola in Georgia was confirmed in this study. Migration analyses indicate there have been several introduction events from North America into Europe. However, some of the source populations still appear to remain unknown. The populations in Croatia and western Asia appear to originate from genetically similar populations in North America. Intercontinental movement of the pathogen was reflected in an identical haplotype occurring on two continents, in North America (Canada) and Europe (Germany). Several shared haplotypes between European populations further suggests more local pathogen movement between countries. Moreover, migration analyses indicate that the populations in northern Europe originate from more established populations in central Europe. Overall, the highest genetic diversity was observed in south‐eastern USA. In Europe, the highest diversity was observed in France, where the presence of both known pathogen lineages was recorded. Less than half of the observed populations contained mating types in equal proportions. Although there is evidence of some sexual reproduction taking place, the pathogen spreads predominantly asexually and through anthropogenic activity.