bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adsorption of different anionic and cationic dyes by hybrid nanocomposites of carbon nanotube and graphene materials over UiO-66
Authors: Athari Mohammadreza , Fattahi Moslem , Khosravi-Nikou Mohammadreza , Hajhariri Aliasghar 
Published: November 2022

AbstractAmongst many chemical pollutants that cause environmental pollution, the presence of organic dyes in water resources can cause substantial health issues. Thus, owing to their mutagenicity and their adverse effects on human health, environment, and animals, they must be removed from industrial wastewater. In this study, UiO-66 metal–organic framework, as well as composite nanoparticles with carbonaceous materials such as MWCNTs-COOH and graphene oxide (GO) with different molar ratios (2.9 and 5.8 wt.%), were synthesized through solvothermal method since carbonaceous materials are an emerging material that demonstrates improvement in the properties of adsorbents. Then, the synthesized materials were utilized as a solid adsorbent for removing four different dyes including; anionic methyl red (MR), anionic methyl orange (MO), cationic methylene blue (MB), and cationic malachite green (MG) prepared from distilled water. The properties of prepared adsorbents were characterized via X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FESEM), Photoluminescence spectroscopy (PL), Brunauer–Emmett–Teller (BET), as well as surface area analyzer and energy dispersive spectroscopy (EDS-MAP). Further, the influences of various factors including initial concentrations of the dyes and adsorption process time on adsorption of dyes were investigated. Adsorption experiments indicated that synthesized adsorbents exhibited the highest adsorption efficiency towards MR and MO dyes. Moreover, the experimental adsorption results revealed that MWCNTs-UiO-66 nanocomposites could adsorb 98% of MR and MO as well as 72% of MB and 46% of MG. Furthermore, the kinetic and stability of the materials over time were investigated. To reach a clear picture, adsorption experiments demonstrated that the amount of dye uptake on adsorbents was enhanced by increasing the contact time as well as uptake of materials with time were stable for both cationic and anionic dyes. The MR, MO, and MB adsorption isotherms were fitted with the Langmuir and Freundlich models. The Langmuir showed the highest agreement in these dyes and MWCNTs-UiO-66 (2.9 and 5.8 wt.%) exhibited a maximum adsorption capacity of 105.26 mg/g for MR, while the MG isotherm was in line with the Langmuir model.
Species traits determined different responses to “zero-growth” policy in China’s marine fisheries
Authors: Kang Bin , Wang Linlong , Liu Min 
Published: November 2022

AbstractChina remains the largest nation of marine capture fisheries in the world in the last few decades, at the cost of offshore fisheries degradation by overfishing. Although fisheries regulations have become gradually tightened, the recovering evidences are weak and the catch species compositions are far from satisfactory. To explore better and reasonable countermeasures, besides the “zero growth” policy (i.e. the national total fisheries production limitation), five targets with different ecological traits were selected for stock assessment and rebuilding by Monte Carlo Catch-Maximum Sustainable Yield method. The results showed the control of total rather than species catch could not lead to the recovery of fisheries and maintain community function. Individual species showed different responses to overfishing according to their biological characteristics. High trophic level species can be sensitive to overfishing, and difficult to rebuild stocks after collapse. Pelagic small fish resources increased first but eventually decreased under high fishing pressure. Scientific-based restocking can enhance resource recovery. Besides “zero growth” policy, fisheries management should be further refined, in particular for main economic species based on their biological traits, as well as the support of reliable fisheries statistics and regulation implementation in place. To relieve the conflict between rising fishery products demand and falling catches, aquaculture and seeking resources from the high seas and EEZs are supposed to be successful ways, on the premise of taking full account of ecological health, maritime safety, and food security.
The effect of salinity on soil chemical characteristics, enzyme activity and bacterial community composition in rice rhizospheres in Northeastern Thailand
Authors: Sritongon Natthawat , Sarin Pornrapee , Theerakulpisut Piyada , Riddech Nuntavun 
Published: November 2022

AbstractSaline soil is one of the major problems limiting rice productivity in the Northeastern area of Thailand. Thus, the aims of this study were to determine soil physicochemical analysis and soil enzyme activities, and bacterial communities in the rhizosphere of ‘RD 6’ rice grown in salt-affected rice fields. The Ban Thum sample showed the highest electrical conductivity (EC; greater than 6 dS m−1) and total Na, while the EC in other fields were at non- or slightly saline levels. The principal component analysis revealed that soil chemical characteristics and soil enzymes activities explained 73.4% of total variation. Soil enzyme activities including dehydrogenase and fluorescein diacetate (FDA) hydrolysis, and soil characteristics including organic matter (OM) and organic carbon (OC) were significantly negatively correlated to EC. This indicated that these soil properties were adversely impacted by salts. Interestingly, activities of all hydrolytic enzymes were not affected by soil salinity. Bacteria that were able to colonize the rhizosphere soils were Achromobacter cholinophagum, Rhizobium tarimense, and unculturable bacteria. In this regard, study on the relationship of soil chemical characteristics and soil enzyme activities together with bacterial communities provided promising data for assessing rice field soil quality in the future.
Machine learning did not beat logistic regression in time series prediction for severe asthma exacerbations
Authors: de Hond Anne A. H. , Kant Ilse M. J. , Honkoop Persijn J. , Smith Andrew D. , Steyerberg Ewout W. , Sont Jacob K. 
Published: November 2022

AbstractEarly detection of severe asthma exacerbations through home monitoring data in patients with stable mild-to-moderate chronic asthma could help to timely adjust medication. We evaluated the potential of machine learning methods compared to a clinical rule and logistic regression to predict severe exacerbations. We used daily home monitoring data from two studies in asthma patients (development: n = 165 and validation: n = 101 patients). Two ML models (XGBoost, one class SVM) and a logistic regression model provided predictions based on peak expiratory flow and asthma symptoms. These models were compared with an asthma action plan rule. Severe exacerbations occurred in 0.2% of all daily measurements in the development (154/92,787 days) and validation cohorts (94/40,185 days). The AUC of the best performing XGBoost was 0.85 (0.82–0.87) and 0.88 (0.86–0.90) for logistic regression in the validation cohort. The XGBoost model provided overly extreme risk estimates, whereas the logistic regression underestimated predicted risks. Sensitivity and specificity were better overall for XGBoost and logistic regression compared to one class SVM and the clinical rule. We conclude that ML models did not beat logistic regression in predicting short-term severe asthma exacerbations based on home monitoring data. Clinical application remains challenging in settings with low event incidence and high false alarm rates with high sensitivity.
Fibrosis-4 index efficiently predicts chronic hepatitis and liver cirrhosis development based on a large-scale data of general population in Japan
Authors: Yamamichi Nobutake , Shimamoto Takeshi , Okushin Kazuya , Nishikawa Takako , Matsuzaki Hirotaka , Yakabi Seiichi , Takahashi Mami , Wada Ryoichi , Koike Kazuhiko , Fujishiro Mitsuhiro 
Published: November 2022

AbstractA non-invasive method to evaluate the fibrosis stage and the risk stratification of non-alcoholic fatty liver disease (NAFLD) is required. A total of 416,066 generally healthy subjects who underwent health check-ups between 1990 and 2019 were investigated. Fatty liver prevalence greatly increased from the 1990s (21.9%) to the 2000s (37.1%) but showed no considerable change between 2001–2010 (39.2%) and 2011–2019 (35.5%). During the 30 years, the rate of high FIB-4 index (≥2.67) and mean body mass index (BMI) did not markedly change. Fatty liver was significantly associated with BMI, but not with alcohol intake or FIB-4 index. Cox regression analyses for development of chronic hepatitis or liver cirrhosis identified that the risk of developing chronic hepatitis and liver cirrhosis was higher in subjects without fatty liver than in those with it (hazard ratio [HR]=0.09; 95% confidence interval [CI], 0.03–0.22,p <0.001 and HR=0.04; 95% CI, 0.01–0.26,p =0.001, respectively), and much larger in subjects with a high FIB-4 index (≥ 2.67) than in those without it (HR=78.6; 95% CI, 29.0–213.1,p <0.001 and HR=5950.7; 95% CI,761.7–46,491.4,p <0.001, respectively). Adjusted survival curves for Cox proportional hazards regression further reinforced these results. In conclusion, the FIB-4 index is a useful indicator of chronic hepatitis and liver cirrhosis development in the general population.
Adaptive simulation of 3D thermometry maps for interventional MR-guided tumor ablation using Pennes’ bioheat equation and isotherms
Authors: Alpers Julian , Rötzer Maximilian , Gutberlet Marcel , Wacker Frank , Hensen Bennet , Hansen Christian 
Published: November 2022

AbstractMinimally-invasive thermal ablation procedures have become clinically accepted treatment options for tumors and metastases. Continuous and reliable monitoring of volumetric heat distribution promises to be an important condition for successful outcomes. In this work, an adaptive bioheat transfer simulation of 3D thermometry maps is presented. Pennes’ equation model is updated according to temperature maps generated by uniformly distributed 2D MR phase images rotated around the main axis of the applicator. The volumetric heat diffusion and the resulting shape of the ablation zone can be modelled accurately without introducing a specific heat source term. Filtering the temperature maps by extracting isotherms reduces artefacts and noise, compresses information of the measured data and adds physical a priori knowledge. The inverse heat transfer for estimating values of the simulated tissue and heating parameters is done by reducing the sum squared error between these isotherms and the 3D simulation. The approach is evaluated on data sets consisting of 13 ex vivo bio protein phantoms, including six perfusion phantoms with simulated heat sink effects. Results show an overall average Dice score of 0.89 ± 0.04 (SEM < 0.01). The optimization of the parameters takes 1.05 ± 0.26 s for each acquired image. Future steps should consider the local optimization of the simulation parameters instead of a global one to better detect heat sinks without a priori knowledge. In addition, the use of a proper Kalman filter might increase robustness and accuracy if combined with our method.
Experimental climate change impacts on Baltic coastal wetland plant communities
Authors: Bergamo T. F. , Ward R. D. , Joyce C. B. , Villoslada M. , Sepp K. 
Published: November 2022

AbstractCoastal wetlands provide a range of important ecosystem services, yet they are under threat from a range of stressors including climate change. This is predominantly as a result of alterations to the hydroregime and associated edaphic factors. We used a three-year mesocosm experiment to assess changes in coastal plant community composition for three plant communities in response to altered water level and salinity scenarios. Species richness and abundance were calculated by year and abundance was plotted using rank abundance curves. The permutational multivariate analysis of variance with Bray–Curtis dissimilarity was used to examine differences among treatments in plant community composition. A Non-metric Multi-dimensional Scaling analysis (NMDS) was used to visualize the responses of communities to treatments by year. Results showed that all three plant communities responded differently to altered water levels and salinity. Species richness and abundance increased significantly in an Open Pioneer plant community while Lower and Upper Shore plant communities showed less change. Species abundances changed in all plant communities with shifts in species composition significantly influenced by temporal effects and treatment. The observed responses to experimentally altered conditions highlight the need for conservation of these important ecosystems in the face of predicted climate change, since these habitats are important for wading birds and livestock grazing.
Differentiation of action mechanisms between natural and synthetic repellents through neuronal electroantennogram and proteomic in Aedes aegypti (Diptera: Culicidae)
Authors: Portilla Pulido Johan Sebastián , Urbina Duitama Diana Lizeth , Velasquez-Martinez María Carolina , Mendez-Sanchez Stelia Carolina , Duque Jonny Edward 
Published: November 2022

AbstractNatural-based compounds with repellent activity arise nowadays with the possibility to replace commercial synthetic repellents wholly or partially, such as N,N-Diethyl-m-toluamide (DEET). It is due to DEET's demonstrated toxicity and cutaneous irritation for human beings. Besides, research recommends avoiding using it with kids and pregnant women. The search for a repellent product implies early stages of detailed research that resolve the modes of action against the target insect. Therefore the objective of the current study was to analyze neuronal electrophysiological signals and olfactory system protein expression when the Aedes aegypti mosquito with exposition to natural-based repellents. Adult females of Ae. aegypti of Rockefeller strain were exposed to specific concentrations of repellent compounds like geranyl acetate, α-bisabolol, nerolidol, and DEET. The neuronal effect was measured by electroantennography technique, and the effect of exposure to either DEET or a mixture of natural molecules on protein expression was determined with 2D-PAGE followed by MALDI-TOF-mass spectrometry (MS). This approach revealed that DEET affected proteins related to synapses and ATP production, whereas natural-based repellents increased transport, signaling, and detoxification proteins. The proteomic and electrophysiology experiments demonstrated that repellent exposure disrupts ionic channel activity and modifies neuronal synapse and energy production processes.
Amoxicillin and thiamphenicol treatments may influence the co-selection of resistance genes in the chicken gut microbiota
Authors: Laconi Andrea , Tolosi Roberta , Mughini-Gras Lapo , Cuccato Matteo , Cannizzo Francesca Tiziana , Piccirillo Alessandra 
Published: November 2022

AbstractThe aim of this study was to assess the dynamics of microbial communities and antimicrobial resistance genes (ARGs) in the chicken gut following amoxicillin and thiamphenicol treatments and potential co-selection of ARGs. To this purpose, the microbial community composition, using 16S rRNA NGS, and the abundance of ARGs conferring resistance to β-lactams and phenicols, using qPCRs, were determined. Results revealed that the administered antimicrobials did not significantly reduce the gut microbiota diversity, but changed its composition, with taxa (e.g. Gallibacterium and Megamonas) being enriched after treatment and replacing other bacteria (e.g. Streptococcus and Bifidobacterium). Positive correlations were found between ARGs (e.g. cmlA, blaCMY-2, and blaSHV) and the relative abundance of specific taxa (e.g. Lactobacillus and Subdoligranulum). The selective pressure exerted by both amoxicillin and thiamphenicol resulted in an increased abundance of ARGs conferring resistance to β-lactams (e.g. blaTEM-1, blaSHV, and blaCTX-M1-like) and phenicols (e.g. floR and cmlA). These findings, together with the co-occurrence of genes conferring resistance to the two antimicrobial classes (e.g. blaTEM-1 and cmlA), suggest a possible interaction among antimicrobials on resistance emergence, possibly due to the presence of mobile genetic elements (MGEs) carrying multiple resistance determinants.
Early CD4+ T cell responses induced by the BNT162b2 SARS-CoV-2 mRNA vaccine predict immunological memory
Authors: Bai Jie , Chiba Asako , Murayama Goh , Kuga Taiga , Yahagi Yoshiyuki , Tabe Yoko , Tamura Naoto , Miyake Sachiko 
Published: November 2022

AbstractLongitudinal studies have revealed large interindividual differences in antibody responses induced by SARS-CoV-2 mRNA vaccines. Thus, we performed a comprehensive analysis of adaptive immune responses induced by three doses of the BNT162b2 SARS-CoV-2 mRNA vaccines. The responses of spike-specific CD4+ T cells, CD8+ T cells and serum IgG, and the serum neutralization capacities induced by the two vaccines declined 6 months later. The 3rd dose increased serum spike IgG and neutralizing capacities against the wild-type and Omicron spikes to higher levels than the 2nd dose, and this was supported by memory B cell responses, which gradually increased after the 2nd dose and were further enhanced by the 3rd dose. The 3rd dose moderately increased the frequencies of spike-specific CD4+ T cells, but the frequencies of spike-specific CD8+ T cells remained unchanged. T cells reactive against the Omicron spike were 1.3-fold fewer than those against the wild-type spike. The early responsiveness of spike-specific CD4+ T, circulating T follicular helper cells and circulating T peripheral helper cells correlated with memory B cell responses to the booster vaccination, and early spike-specific CD4+ T cell responses were also associated with spike-specific CD8+ T cell responses. These findings highlight the importance of evaluating cellular responses to optimize future vaccine strategies.
Dry etching of ternary metal carbide TiAlC via surface modification using floating wire-assisted vapor plasma
Authors: Nguyen Thi-Thuy-Nga , Shinoda Kazunori , Hamamura Hirotaka , Maeda Kenji , Yokogawa Kenetsu , Izawa Masaru , Ishikawa Kenji , Hori Masaru 
Published: November 2022

AbstractDry etching of ternary metal carbides TiAlC has been first developed by transferring from wet etching to dry etching using a floating wire (FW)-assisted Ar/ammonium hydroxide vapor plasma. FW-assisted non-halogen vapor plasma generated at medium pressure can produce high-density reactive radicals (NH, H, and OH) for TiAlC surface modifications such as hydrogenation and methylamination. A proposed mechanism for dry etching of TiAlC is considered with the formation of the volatile products from the modified layer.
Effects of protein intake from an energy-restricted diet on the skeletal muscle composition of overweight and obese rats
Authors: Tian Ying , Huan Yuping , Chen Lihong , Peng Suwen , He Zhiyan , Wang Qian 
Published: November 2022

AbstractExcess weight and obesity are often associated with ectopic adipose tissue accumulation in skeletal muscles. Intermuscular adipose tissue (IMAT) impairs muscle quality and reduces insulin-stimulated skeletal muscle glucose uptake. Although energy restriction and high protein intake can decrease IMAT, the effects and mechanisms of protein intake from an energy-restricted diet on protein and fat masses in skeletal muscle have received little attention. After establishing a diet-induced overweight and obese Sprague-Dawley rat model (half male and half female), rats were divided into five groups: normal control (NC; normal weight, general maintenance diet), model control (MC; overweight and obesity, high-fat diet), energy-restricted low protein (LP; overweight and obesity, 60% energy intake of NC, general maintenance diet), energy-restricted normal protein (NP; overweight and obesity, 60% energy intake of NC, high-protein diet 1), and energy-restricted high protein (HP; overweight and obesity, 60% energy intake of NC, high-protein diet 2). After 8 weeks, plasma and skeletal muscle (quadriceps femoris and gastrocnemius) samples were collected. Plasma levels of glucose, triglycerides, and hormones were analyzed, while contents of protein, fat, and factors associated with their synthesis and degradation were evaluated in skeletal muscles. Plasma concentrations of hormones contrasted protein and fat contents in skeletal muscles. Fat weights and contents of quadriceps femoris and gastrocnemius muscles in the NP group were significantly lower compared with LP and HP groups (P < 0.05). Moreover, concentrations of factors associated with the degradation of muscle fat were significantly higher in the NP group compared with LP and HP groups (P < 0.05). During energy restriction, protein intake equal to that of a normal protein diet increased lipolysis of quadriceps femoris and gastrocnemius muscles in rats of both sexes.
A COVID-19 model incorporating variants, vaccination, waning immunity, and population behavior
Authors: LaJoie Zachary , Usherwood Thomas , Sampath Shailen , Srivastava Vikas 
Published: November 2022

AbstractVaccines for COVID-19 have allowed countries to combat the spread of the disease. However, new variants have resulted in significant spikes in cases and raised severe health and economic concerns. We present a COVID-19 model to predict coupled effects of vaccine multiple-dose roll-out strategies, vaccine efficacy, waning immunity, population level of caution, sense of safety, under-reporting of cases, and highly prevalent variants such as the Delta (B.1.617.2) and Omicron (B.1.1.529). The modeling framework can incorporate new variants as they emerge to give critical insights into the new cases and guide public policy decision-making concerning vaccine roll-outs and reopening strategies. The model is shown to recreate the history of COVID-19 for five countries (Germany, India, Japan, South Africa, and the United States). Parameters for crucial aspects of the pandemic, such as population behavior, new variants, vaccination, and waning immunity, can be adjusted to predict pandemic scenarios. The model was used to conduct trend analysis to simulate pandemic dynamics taking into account the societal level of caution, societal sense of safety, and the proportions of individuals vaccinated with first, second, and booster doses. We used the results of serological testing studies to estimate the actual number of cases across countries. The model allows quantification of otherwise hard to quantify aspects such as the infectious power of variants and the effectiveness of government mandates and population behavior. Some example cases are presented by investigating the competitive nature of COVID variants and the effect of different vaccine distribution strategies between immunity groups.