bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diverse cloud radiative effects and global surface temperature simulations induced by different ice cloud optical property parameterizations
Authors: Yi Bingqi 
Published: June 2022

AbstractThe representation of ice cloud optical properties in climate models has long been a difficult problem. Very different ice cloud optical property parameterization schemes developed based on very different assumptions of ice particle shape habits, particle size distributions, and surface roughness conditions, are used in various models. It is not clear as to how simulated climate variables are affected by the ice cloud optical property parameterizations. A total of five ice cloud optical property parameterization schemes, including three based on the ice habit mixtures suitable for general ice clouds, mid-latitude synoptic ice clouds, and tropical deep convective ice clouds, and the other two based on single ice habits (smooth hexagonal column and severely roughened column aggregate), are developed under a same framework and are implemented in the National Center for Atmospheric Research Community Atmospheric Model version 5. A series of atmosphere-only climate simulations are carried out for each of the five cases with different ice parameterizations. The differences in the simulated top of the atmosphere shortwave and longwave cloud radiative effects (CREs) are evaluated, and the global averaged net CRE differences among different cases range from − 1.93 to 1.03 Wm−2. The corresponding changes in simulated surface temperature are found to be most prominent on continental regions which amount to several degrees in Kelvin. Our results indicate the importance of choosing a reasonable ice cloud optical property parameterization in climate simulations.
Evaluation of within-host evolution of methicillin-resistant Staphylococcus aureus (MRSA) by comparing cgMLST and SNP analysis approaches
Authors: Lagos Amaya Campillay , Sundqvist Martin , Dyrkell Fredrik , Stegger Marc , Söderquist Bo , Mölling Paula 
Published: June 2022

AbstractWhole genome sequencing (WGS) of methicillin-resistant Staphylococcus aureus (MRSA) provides high-resolution typing, facilitating surveillance and outbreak investigations. The aim of this study was to evaluate the genomic variation rate in MRSA, by comparing commonly used core genome multilocus sequencing (cgMLST) against single nucleotide polymorphism (SNP) analyses. WGS was performed on 95 MRSA isolates, collected from 20 carriers during years 2003–2019. To assess variation and methodological-related differences, two different cgMLST schemes were obtained using Ridom SeqSphere+ and the cloud-based 1928 platform. In addition, two SNP methods, 1928 platform and Northern Arizona SNP Pipeline (NASP) were used. The cgMLST using Ridom SeqSphere+ and 1928 showed a median of 5.0 and 2.0 allele variants/year, respectively. In the SNP analysis, performed with two reference genomes COL and Newman, 1928 showed a median of 13 and 24 SNPs (including presumed recombination) and 3.8 respectively 4.0 SNPs (without recombination) per individual/year. Accordantly, NASP showed a median of 5.5 and 5.8 SNPs per individual/year. In conclusion, an estimated genomic variation rate of 2.0–5.8 genetic events per year (without recombination), is suggested as a general guideline to be used at clinical laboratories for surveillance and outbreak investigations independently of analysis approach used.
Pharmacological thromboprophylaxis as a risk factor for early periprosthetic joint infection following primary total joint arthroplasty
Authors: Pai Fu-Yuan , Chang Wei-Lin , Tsai Shang-Wen , Chen Cheng-Fong , Wu Po-Kuei , Chen Wei-Ming 
Published: June 2022

AbstractVenous thromboembolism (VTE) prophylaxis has been suggested for patients who underwent total join arthroplasty (TJA). However, the morbidity of surgical site complications (SSC) and periprosthetic joint infection (PJI) has not been well evaluated. We aimed to evaluate the impact of VTE prophylaxis on the risk of early postoperative SSC and PJI in a Taiwanese population. We retrospectively reviewed 7511 patients who underwent primary TJA performed by a single surgeon from 2010 through 2019. We evaluated the rates of SSC and PJI in the early postoperative period (30-day, 90-day) as well as 1-year reoperations. Multivariate regression analysis was used to identify possible risk factors associated with SSC and PJI, including age, sex, WHO classification of weight status, smoking, diabetes mellitus (DM), rheumatoid arthritis(RA), Charlson comorbidity index (CCI), history of VTE, presence of varicose veins, total knee or hip arthroplasty procedure, unilateral or bilateral procedure, or receiving VTE prophylaxis or blood transfusion. The overall 90-day rates of SSC and PJI were 1.1% (N = 80) and 0.2% (N = 16). VTE prophylaxis was a risk factor for 90-day readmission for SSC (aOR: 1.753, 95% CI 1.081–2.842), 90-day readmission for PJI (aOR: 3.267, 95% CI 1.026–10.402) and all 90-day PJI events (aOR: 3.222, 95% CI 1.200–8.656). Other risk factors included DM, underweight, obesity, bilateral TJA procedure, younger age, male sex and RA. Pharmacological thromboprophylaxis appears to be a modifiable risk factor for SSC and PJI in the early postoperative period. The increased infection risk should be carefully weighed in patients who received pharmacological VTE prophylaxis.
Method for evaluating the performance of catalytic reactions using renewable-energy-derived materials
Authors: Manaka Yuichi , Nagata Yuki , Kobayashi Keisuke , Kobayashi Daisuke , Nanba Tetsuya 
Published: June 2022

AbstractHydrogen produced by electrolysis using electricity derived from renewable energy sources has a fluctuating supply. However, conventional catalyst evaluation methods cannot evaluate catalyst synthesis assuming a fluctuating feedstock. This paper investigates a simple screening method for catalysts that can be used for renewable energy by using a combination of three catalyst evaluation methods: Light-off Performance, equilibrium achievement degree, and maximum ammonia concentration. We examined the combination of evaluation methods and trends for each element, and finally concluded that a three-axis graph combining the three is the easiest graph to obtain the information necessary for catalyst screening intuitively rather than quantitatively.
An interrupted time series analysis of hospital admissions due to alcohol intoxication during the COVID‐19 pandemic in Tehran, Iran
Authors: Hadeiy Seyed Kaveh , Zamani Nasim , McDonald Rebecca , Rezaei Omidvar , Kolahi Ali-Asghar , Gholami Narges , Farnaghi Fariba , Hassanian-Moghaddam Hossein 
Published: June 2022

AbstractThe COVID-19 outbreak affected mental health globally. One of the major concerns following the COVID-19 pandemic was increased incidence of risky behaviors including alcohol consumption. This study evaluates the trend of alcohol poisoning in Loghman-Hakim Hospital (LHH), the main referral center of poisoning in Tehran, during the 2-year period from 1 year prior to 1 year after the onset (February 23rd, 2020) of the COVID-19 epidemic in Iran. All patients admitted with alcohol intoxication from February 23rd, 2019 to February 22nd, 2021 were evaluated and patient data extracted from LHH electronic hospital records. Alcohols were categorized as toxic (methyl alcohol) and non-toxic (ethyl alcohol). Of 2483 patients admitted, 796/14,493 (5.49%) and 1687/13,883 (12.15%) had been hospitalized before and after the onset of the COVID-19 epidemic in Iran, respectively. In total, 140 patients did not survive, of whom 131 (93.6%) were confirmed to have methanol intoxication. Mortality was significantly higher during the outbreak (127 vs 13; P < 0.001; OR: 4.90; CI 95%: 2.75 to 8.73). Among the patients, 503 were younger than age 20. Trend of alcohol intoxication showed increases in children (57 vs 17) and adolescents (246 vs 183) when compared before and after the COVID-19 epidemic outbreak. A total of 955 patients were diagnosed with methanol toxicity which occurred more frequently during the COVID-19 era (877 vs 78; P < 0.001; OR: 10.00; CI 95%: 7.75 to12.82). Interrupted time series analysis (April 2016–February 2021) showed that in the first month of the COVID-19 epidemic (March 2020), there was a significant increase in the alcohol intoxication rate by 13.76% (P < 0.02, CI = [2.42–24.91]). The trend of alcohol intoxication as well as resulting mortality increased in all age groups during the COVID-19 epidemic in Iran, indicating urgent need for the prevention of high-risk alcohol use as well as improved treatment.
Associations between classic psychedelics and nicotine dependence in a nationally representative sample
Authors: Jones Grant , Lipson Joshua , Nock Matthew K. 
Published: June 2022

AbstractTobacco use is the single largest cause of preventable death worldwide, but none of the established treatments aimed at smoking cessation work for a majority of smokers. As such, there is an urgent need for interventions capable of reliably treating nicotine addiction. The use of classic psychedelics has been associated with lower odds of many forms of substance dependence. Here we tested whether lifetime use of classic psychedelics (tryptamine, lysergamide, and phenethylamine) is associated with lower odds of current nicotine dependence. We tested these associations in a sample of 214,505 adult participants in the National Survey on Drug Use and Health (2015–2019) using multivariable logistic regression models. Lifetime psilocybin use was associated with reduced odds of odds of current nicotine dependence (aOR 0.87–0.93). Lifetime use of peyote and mescaline also conferred reduced odds of multiple subdomains of a main nicotine dependence measure (Nicotine Dependence Syndrome Scale [NDSS]) (aOR 0.79–0.91). Conversely, lifetime use of LSD was associated with increased odds of nicotine dependence (aOR 1.17–1.24). Psilocybin, mescaline, and peyote use are associated with lowered odds of nicotine dependence. Experimental studies are needed to establish whether these associations are causal. These results make the case for further research into the efficacy of both tryptamine and phenethylamine psychedelics in promoting smoking cessation.
Preparation and in vivo bacteriostatic application of PPDO-coated Ag loading TiO2 nanoparticles
Authors: Ren Tongyan , Feng Chengmin , Dong Jun , Zhu Hong , Wang Bing 
Published: June 2022

AbstractImplant-associated infections limit the clinical application of implants therapy; hence, exploiting strategies to prevent biomaterial-associated infections has become important. Therefore, in this study, a series of poly (p-dioxanone) (PPDO)-coated Ag loading TiO2 nanoparticles (Ag@TiO2-PPDO) was synthesized to be applied as bacteriostatic coating materials that could be easily dispersed in organic solvent and coated onto implantable devices via temperate methods such as electrospraying. The lattice parameters of TiO2 were a = 0.504 nm, b = c = 1.05 nm, alpha = beta = gamma = 90 degree and the size of crystallite was about 13 nm, indicating that part of Ag has been embedded into crystal defects of TiO2. Both XRD and TEM determinations indicated the successful grating of PPDO on the surface of Ag@TiO2. Among Ag@TiO2 nanoparticles with various Ag loading quantities, 12% Ag@TiO2 nanoparticles exhibited relatively higher grafting efficiency and Ag contents on the surface of grafted composites. In addition, 12% Ag@TiO2-PPDO exhibited the best bacteriostatic effect in vitro owing to its higher grafted efficiency and relatively short length of PPDO segments. Subsequently, Ag@TiO2-PPDO was coated on the surface of a poly lactic-co-glycolic acid (PLGA) electrospun membrane via the electrospraying method. Finally, the in vivo bacteriostatic effect of 12% Ag@TiO2-PPDO coating was verified by implanting 12% Ag@TiO2-PPDO-coated PLGA membrane into a rat subcutaneously combined with an injection of Staphylococcus aureus at implanting sites.
A pilot study demonstrating the impact of surgical bowel preparation on intestinal microbiota composition following colon and rectal surgery
Authors: Nalluri-Butz Harika , Bobel Matthew C. , Nugent Julia , Boatman Sonja , Emanuelson Ryan , Melton-Meaux Genevieve , Madoff Robert D. , Jahansouz Cyrus , Staley Christopher , Gaertner Wolfgang B. 
Published: June 2022

AbstractThe intestinal microbiota has been implicated in the pathogenesis of complications following colorectal surgery, yet perioperative changes in gut microbiome composition are poorly understood. The objective of this study was to characterize the perioperative gut microbiome in patients undergoing colonoscopy and colorectal surgery and determine factors influencing its composition. Using Illumina amplicon sequencing coupled with targeted metabolomics, we characterized the fecal microbiota in: (A) patients (n = 15) undergoing colonoscopy who received mechanical bowel preparation, and (B) patients (n = 15) undergoing colorectal surgery who received surgical bowel preparation, composed of mechanical bowel preparation with oral antibiotics, and perioperative intravenous antibiotics. Microbiome composition was characterized before and up to six months following each intervention. Colonoscopy patients had minor shifts in bacterial community composition that recovered to baseline at a mean of 3 (1–13) days. Surgery patients demonstrated substantial shifts in bacterial composition with greater abundances of Enterococcus, Lactobacillus, and Streptococcus. Compositional changes persisted in the early postoperative period with recovery to baseline beginning at a mean of 31 (16–43) days. Our results support surgical bowel preparation as a factor significantly influencing gut microbial composition following colorectal surgery, while mechanical bowel preparation has little impact.
Self-normalized density map (SNDM) for counting microbiological objects
Authors: Graczyk Krzysztof M. , Pawłowski Jarosław , Majchrowska Sylwia , Golan Tomasz 
Published: June 2022

AbstractThe statistical properties of the density map (DM) approach to counting microbiological objects on images are studied in detail. The DM is given by U$$^2$$

2

-Net. Two statistical methods for deep neural networks are utilized: the bootstrap and the Monte Carlo (MC) dropout. The detailed analysis of the uncertainties for the DM predictions leads to a deeper understanding of the DM model’s deficiencies. Based on our investigation, we propose a self-normalization module in the network. The improved network model, called Self-Normalized Density Map (SNDM), can correct its output density map by itself to accurately predict the total number of objects in the image. The SNDM architecture outperforms the original model. Moreover, both statistical frameworks—bootstrap and MC dropout—have consistent statistical results for SNDM, which were not observed in the original model. The SNDM efficiency is comparable with the detector-base models, such as Faster and Cascade R-CNN detectors.
Rbfox1 expression in amacrine cells is restricted to GABAergic and VGlut3 glycinergic cells
Authors: Gu Lei , Caprioli Joseph , Piri Natik 
Published: June 2022

Abstract
Rbfox1 is a multifunctional RNA-binding protein that regulates alternative splicing, transcription, mRNA stability, and translation. Rbfox1 is an important regulator of gene networks involved in neurogenesis and neuronal function. Disruption of Rbfox function has been associated with several neurodevelopmental and neuropsychiatric disorders. We have shown earlier that Rbfox1 is expressed in retinal ganglion and amacrine cells (ACs) and that its down-regulation in adult mouse retinas leads to deficiency of depth perception. In the present study, we used several markers of ACs, including gamma-aminobutyric acid (GABA), choline acetyltransferase (ChAT), neuropeptide Y (NPY), glycine transporter (GlyT1), and vesicular glutamate transporter 3 (VGlut3) to identify types of ACs that express Rbfox1. Expression of Rbfox1 was observed predominantly in GABAergic ACs located in the inner nuclear layer (INL) and ganglion cell layer (GCL). All GABAergic/cholinergic starburst ACs and virtually all NPY-positive GABAergic ACs were also Rbfox1-positive. Among glycinergic ACs, a sparse population of Rbfox1/VGlut3-positive cells was identified, indicating that Rbfox1 is expressed in a very small population of glycinergic ACs. These data contribute to our understanding about molecular differences between various types of amacrine cells and the cell-specific gene networks regulated by Rbfox1.
L-Glutamine alleviates osteoarthritis by regulating lncRNA-NKILA expression through the TGF-β1/SMAD2/3 signalling pathway
Authors: Ma Xiao , Cai Dechao , Zhu Yakun , Zhao Yao , Shang Xianbo , Wang Chen , Zhang Haotian , Bian Ashuai , Yu Haoran , Cheng Wendan 
Published: June 2022

Abstract
Osteoarthritis (OA) is a heterogeneous condition characterized by cartilage degradation, subchondral sclerosis, and osteophyte formation, and accompanied by the generation of pro-inflammatory mediators and degradation of extracellular matrix. The current treatment for early OA is focused on the relief of symptoms, such as pain, but this treatment cannot delay the pathological process. L-Glutamine (L-Gln), which has anti-inflammatory and anti-apoptotic effects, is the most abundant amino acid in human blood. However, its role in OA has not been systematically studied. Therefore, the objective of this work was to explore the therapeutic effect and molecular mechanism of L-Gln on OA. In vitro, we found that L-Gln could up-regulate the expression of the long non-coding RNA NKILA, which is regulated by the transforming growth factor-β1/SMAD2/3 pathway, and inhibit the activity of nuclear factor-κB, thereby decreasing the expression of nitric oxide synthase, cyclooxygenase-2, and matrix metalloproteinase-13 (MMP-13). This led to a reduction in the generation of nitrous oxide, prostaglandin E-2, tumour necrosis factor-α, and degradation of the extracellular matrix (i.e. aggrecan and collagen II) in rat OA chondrocytes. Moreover, intragastric administration of L-Gln reduced the degradation of cartilage tissue and expression of MMP-13 in a rat OA model. L-Gln also relieved the clinical symptoms in some patients with early knee joint OA. These findings highlight that L-Gln is a potential therapeutic drug to delay the occurrence and development of OA.
Direct recognition of pathogen effectors by plant NLR immune receptors and downstream signalling
Authors: Chen Jian , Zhang Xiaoxiao , Rathjen John P. , Dodds Peter N. 
Published: June 2022

Abstract
Plants deploy extracellular and intracellular immune receptors to sense and restrict pathogen attacks. Rapidly evolving pathogen effectors play crucial roles in suppressing plant immunity but are also monitored by intracellular nucleotide-binding, leucine-rich repeat immune receptors (NLRs), leading to effector-triggered immunity (ETI). Here, we review how NLRs recognize effectors with a focus on direct interactions and summarize recent research findings on the signalling functions of NLRs. Coiled-coil (CC)-type NLR proteins execute immune responses by oligomerizing to form membrane-penetrating ion channels after effector recognition. Some CC-NLRs function in sensor–helper networks with the sensor NLR triggering oligomerization of the helper NLR. Toll/interleukin-1 receptor (TIR)-type NLR proteins possess catalytic activities that are activated upon effector recognition-induced oligomerization. Small molecules produced by TIR activity are detected by additional signalling partners of the EDS1 lipase-like family (enhanced disease susceptibility 1), leading to activation of helper NLRs that trigger the defense response.
Similarity‐based adversarial knowledge distillation using graph convolutional neural network
Authors: Lee Sungjun , Kim Sejun , Kim Seong Soo , Seo Kisung 
Published: June 2022

AbstractThis letter presents an adversarial knowledge distillation based on graph convolutional neural network. For knowledge distillation, many methods have been proposed in which the student model individually and independently imitates the output of the teacher model on the input data. Our method suggests the application of a similarity matrix to consider the relationship among output vectors, compared to the other existing approaches. The similarity matrix of the output vectors is calculated and converted into a graph structure, and a generative adversarial network using graph convolutional neural network is applied. We suggest similarity‐based knowledge distillation in which a student model simultaneously imitates both of output vector and similarity matrix of the teacher model. We evaluate our method on ResNet, MobileNet and Wide ResNet using CIFAR‐10 and CIFAR‐100 datasets, and our results outperform results of the baseline model and other existing knowledge distillations like KLD and DML.
Hybridrekonstruktion der Brust nach Mastektomie
Authors: Momeni Arash 
Published: June 2022

ZusammenfassungDie Herausforderung nach Mastektomie ist die sichere Rekonstruktion der Brust von
adäquater Größe und Form, welche weich, symmetrisch und
sensibel ist („6 S“: size, shape, symmetry, softness,
sensation, safety). Traditionell wurden Patientinnen zwei rekonstruktive
Verfahren angeboten, nämlich die Implantat-basierte vs. autologe
Brustrekonstruktion. Obgleich dieses binäre Vorgehen für die
Mehrzahl der Patientinnen adäquat ist, so verbleibt ein Anteil,
für welche dieser recht einfache Entscheidungsalgorithmus keine optimale
Lösung darstellt. Hier bietet die Hybdridrekonstruktion, d. h.
die Kombination von Implantat und mikrochirurgischer Lappenplastik, die
Möglichkeit Patientinnen eine individualisierte Rekonstruktion
anzubieten, welche die einzelnen Limitationen der traditionellen Verfahren durch
Kombination vermeidet. Insofern erweitert die Hybridrekonstruktion das
Indikationsspektrum der mikrochirurgischen Brustrekonstruktion und stellt die
Vorteile der autologen Brustrekonstruktion einer größeren
Patientenpopulation zur Verfügung. In diesem Beitrag wird das operative
Vorgehen der Hybridrekonstruktion vorgestellt mitsamt einer Diskussion wichtiger
Parameter, inklusive der Implantatloge, Zeitpunkt der Implantatplatzierung,
sowie Einfluss der Radiatio.
Infektionsausbruch bei deutschen und finnischen Soldaten während des 2. Weltkriegs im Östlichen Lappland – Erstbeschreibung der Hantavirus-Erkrankung im deutschen Sprachraum
Authors: Mustonen Jukka , Henttonen Heikki , Vaheri Antti , Zöller Lothar , Krüger Detlev H. 
Published: June 2022

ZusammenfassungVor 8 Jahrzehnten erschien in der Deutschen Medizinischen Wochenschrift ein Bericht über ein „schlammfieberähnliches Krankheitsbild bei deutschen Truppen in Lappland“ im Zusammenhang mit einem im Kriegsjahr 1942 beobachteten Ausbruchsgeschehen. Die Beschreibung dieses Krankheitsbildes, das damals über 1000 Soldaten betraf, dürfte die älteste Beschreibung der Hantavirus-Erkrankung im deutschen Sprachraum sein. Heute ist die Hantavirus-Erkrankung, in Nord- und Mitteleuropa auch als Nephropathia epidemica bekannt, eine der häufigsten meldepflichtigen Viruserkrankungen in Deutschland und Finnland.