bluuebunny/crossref_metadata_2025_split huggingface dataset:
Consistent changes in the intestinal microbiota of Atlantic salmon fed insect meal diets
Authors: Li Yanxian , Gajardo Karina , Jaramillo-Torres Alexander , Kortner Trond M. , Krogdahl Åshild 
Published: August 2021

Abstract
Background: Being part of fish's natural diets, insects have become a realistic, sustainable feed ingredient for aquaculture. While nutritional values of insects have been extensively studied in various fish species, their impact on the fish microbiota remains to be fully explored. In an 8-week freshwater feeding trial, Atlantic salmon ( Salmo salar ) were fed either a commercially relevant reference diet or an insect meal diet wherein black soldier fly ( Hermetia illucens ) larvae meal comprised 60% of total ingredients. Microbiota of digesta and mucosa origin from the proximal and distal intestine were collected and profiled along with feed and water samples.

Results: The insect meal diet markedly modulated the salmon intestinal microbiota. Overall, the microbial diversity was lower in the digesta of salmon fed the insect meal diet but higher in the mucosa. A group of bacterial genera, dominated by members of the Bacillaceae family, was enriched in salmon fed the insect meal diet, which confirms our previous findings in a seawater feeding trial. We also found that microbiota in the intestine closely resembled that of the feeds but was distinct from the water microbiota. Notably, bacterial genera associated with the diet effects were also present in the feeds.

Conclusions: We conclude that salmon fed the insect meal diets show consistent changes in the intestinal microbiota. The next challenge is to evaluate the extent to which these alterations are attributable to feed microbiota and dietary nutrients and what these changes mean for fish physiology and health.
Application of Deep Learning to Predict RF Heating of Cardiac Leads During Magnetic Resonance Imaging at 1.5 T and 3 T
Authors: Chen Xinlu , Zheng Can , Nguyen Bach Thanh , Sanpitak Pia , Chow Kelvin , Bi Xiaoming , Elahi Behzad , Golestanirad Laleh 
Published: August 2021

Abstract
Purpose: Predicting magnetic resonance imaging (MRI)-induced heating of elongated conductive implants such as leads in cardiovascular implantable electronic devices (CIEDs) is essential to assessing patient safety. Phantom experiments and electromagnetic simulations have been traditionally used to estimate radiofrequency (RF) heating of implants, but they are notably time-consuming. Recently, machine learning has shown promise for fast prediction of RF heating of orthopedic implants, when the position of the implant within the MRI RF coil was predetermined. Here we explored whether deep learning could be applied to predict RF heating of conductive leads with variable positions/orientations during MRI at 1.5 T and 3 T.Methods: Models of 600 cardiac leads with clinically relevant trajectories were generated and electromagnetic simulations were performed to calculate the maximum of 1g-averaged SAR at the tips of lead models during MRI at 1.5 T and 3 T. Deep learning algorithms were trained to predict the maximum SAR at the lead’s tip from the knowledge of coordinates of points along the lead’s trajectory.Results: Despite the large range of SAR values (~200 W/kg-~3300 W/kg), the RMSE of predicted vs ground truth SAR remained at 223W/kg and 206 W/kg, with the R2 scores of 0.89 and 0.85 on the testing set for 1.5 T and 3 T models, respectively.Conclusion: Machine learning shows promise for fast assessment of RF heating of lead-like implants with only the knowledge of the lead’s geometry and MRI RF coil features.
Snp Characteristics and Validation Success in Genome Wide Association Studies
Authors: Gorlova Olga , Xiao Xiangjun , Tsavachidis Spiridon , Amos Christopher I. , Gorlov Ivan P. 
Published: August 2021

Abstract
Genome wide association studies (GWASs) have identified tens of thousands of single nucleotide polymorphisms (SNPs) associated with human diseases and characteristics. A significant fraction of GWAS findings can be false positives. The gold standard for true positives is an independent validation. The goal of this study was to identify SNP features associated with validation success. Summary statistics from the Catalog of Published GWASs were used in the analysis. Since our goal was an analysis of reproducibility, we focused on the diseases/phenotypes targeted by at least 10 GWASs. GWASs were arranged in discovery-validation pairs based on the time of publication, with the discovery GWAS published before validation. We used four definitions of the validation success that differ by stringency. Associations of SNP features with validation success were consistent across the definitions. The strongest predictor of SNP validation was the level of statistical significance in the discovery GWAS. The magnitude of the effect size was associated with validation success in a non-linear manner. SNPs with risk allele frequencies in the range 30-70% showed a higher validation success rate compared to rarer or more common SNPs. Missense, 5’UTR, stop gained, and SNPs located in transcription factor binding sites had a higher validation success rate compared to intergeneic, intronic, or synonymous SNPs. There was a positive association between validation success and the level of evolutionary conservation of the sites. In addition, validation success was higher when discovery and validation GWASs targeted the same ethnicity. All predictors of validation success remained significant in a multivariable logistic regression model indicating their independent contribution. To conclude, we identified SNP features predicting validation success of GWAS hits. These features can be used to select SNPs for validation and downstream functional studies.
Application of The AHP Method For Prioritizing Actions To Reduce Risk Associated With Gravitational Mass Movements In Areas Along The Margins of Watercourses of The City of Rio Branco, Brazil.
Authors: Nascimento Ricardo Ribeiro , Marques Eduardo Antônio , Simões Gustavo Ferreira 
Published: August 2021

Abstract
Problems related to gravitational mass movements at the margins of water courses are present in different parts of the world, but in the Amazon, whose hydrological regime has unique characteristics, and whose socioeconomic situation may be considered as underdeveloped, such problems come into sharp focus. Rotational landslides and creeps on the ground are present with high frequency and magnitude in several municipalities in the Western Amazon. Such processes act in association and annually cause significant losses and material damage. In this context, this study proposes the structuring of a decision-making process that aims to assist in the indication of critical areas, as well as proposing possible actions to mitigate risks. The criteria and procedures adopted for risk-mapping in a portion of the urban center of Rio Branco-AC are described, herein. Risk was measured, based on the multicriteria analysis of attributes related to the physical, anthropic environment and the characteristics of the processes considered. The Hierarchical Analysis Method (AHP), was the technique adopted to structure the risk assessment model, which was later integrated into the GIS environment, to allow spatial analysis. The results were presented in the form of cartograms, descriptive tables and graphs, and aim to help control the mapped risks.
Construction of a Prognostic Model Related to Ferroptosis and Iron-Metabolism and the Relationship with the Immune Microenvironment of Gastric Cancer
Authors: Wen Fang , Chen Xiaoxue , Huang Wenjie , Ruan Shuai , Gu Suping , Wang Yulan , Liu Jiatong , Zhou Jiayu , Li Ye , Song Siyuan , Gu Peixing , Liu Shenlin , Shu Peng 
Published: August 2021

Abstract
Background: The diagnosis rate and mortality of gastric cancer (GC) are among the highest in the global, so it is of great significance to predict the survival time of GC patients. Ferroptosis and iron-metabolism make a critical impact on tumor development and are closely linked to the treatment of cancer and the prognosis of patients. However, the predictive value of the genes involved in ferroptosis and iron-metabolism in GC and their effects on immune microenvironment remain to be further clarified.Methods: In this study, the RNA sequence information and general clinical indicators of GC patients were acquired from the public databases. We first systematically screen out 134 DEGs and 13 PRGs related to ferroptosis and iron-metabolism. Then, we identified six PRDEGs (GLS2, MTF1, SLC1A5, SP1, NOX4, and ZFP36) based on the LASSO-penalized Cox regression analysis. The 6-gene prognostic risk model was established in the TCGA cohort and the GC patients were separated into the high- and the low-risk groups through the risk score median value. GEO cohort was used for verification. The expression of PRDEGs was verified by quantitative QPCR.Results: Our study demonstrated that patients in the low-risk group had a higher survival probability compared with those in high-risk group. In addition, univariate and multivariate Cox regression analyses confirmed that the risk score was an independent prediction parameter. The ROC curve analysis and nomogram manifested that the risk model had the high predictive ability and was more sensitive than general clinical features. Furthermore, compared with the high-risk group, the low-risk group had higher TMB and a longer 5-year survival period. In the immune microenvironment of GC, there were also differences in immune function and highly infiltrated immune cells between the two risk groups.Conclusions: The prognostic risk model based on the six genes associated with ferroptosis and iron-metabolism has a good performance for predicting the prognosis of patients with GC. The treatment of cancer by inducing tumor ferroptosis or mediating tumor iron-metabolism, especially combined with immunotherapy, provides a new possibility for individualized treatment of GC patients.
In-plane retrofitting of masonry structures by using GFRP strips in the Bedjoints
Authors: Osmanzadeh Fathollah , Ahani Elshan , Rafezy Behzad , Mousavi Mir Naghi 
Published: August 2021

Abstract
Many unreinforced masonry structures were vulnerable in the past earthquakes and required retrofitting. However, the vulnerability of masonry structures could solve by providing numerous retrofitting approaches, scarcity of appropriate methods that may provide a solution for the historical masonry structures with lesser effects on their façade is vehemently sensible. In this study, two one-third scale masonry wall specimens made by clay bricks were tested under constant vertical and cyclic lateral loading. The specimens consist of an unreinforced wall and a wall retrofitted by GFRP strips. This study investigates the seismic behavior of unreinforced masonry walls before and after using GFRP strips on their bedjoints. To this purpose, various patterns of using GFRP strips have been studied by simplified micro-modeling. The consequence indicates that the proposed retrofitting technique could improve the lateral strength and stiffness of the unreinforced masonry wall along with a considerable increase in the energy dissipation and ductility content, which leads to making a change in the behavior of the wall from brittle to ductile failure. The proposed method could apply to the modern historical structures in which cement mortar has been used as an adhesive between the masonry layers.
Dynamics-Based Piecewise Constant Control of Omni-Vehicle
Authors: Moiseev Georgy , Zobova Alexandra 
Published: August 2021

Abstract
In this paper, we consider the dynamics of a mobile vehicle moving under control on a perfectly rough horizontal plane. The vehicle consists of a horizontal platform and three omni-wheels that can rotate independently. An omni-wheel has freely rotating rollers on its rim [1]. We use its simplest model: an omni-wheel on a perfectly rough plane is modelled as a rigid disk with a constraint that its contact point velocity directed perpendicular to the disk's plane. The vehicle is controlled by three direct current motors in wheels' axes. Two terms model torques generated by motors: the rst one is proportional to the voltage, the second one is proportional to the value of the angular velocity of a wheel (counter-electromotive force). We study constant voltage dynamics and boundary-value problems for arbitrary initial and nal mass center coordinates, course angles and their derivatives using a piecewise constant control with one switching point. This problem is reduced to a system of algebraic equations for some specific (symmetric) vehicle model. We numerically model the system and analyze the possibility of optimization. For another vehicle configuration, we get the solution as numerical parametric continuation starting from the solution for the symmetric vehicle.
Vegetation Response to Climate and Climatic Extremes in Northwest Bangladesh: A Quantile Regression Approach
Authors: Uddin Mohammad Ahsan , Kamal A S M Maksud , Shahid Shamsuddin 
Published: August 2021

Abstract
The present study assessed the vegetation response to climate in the water-stressed northwest Bangladesh (NWB). The quantile regression analysis was employed to evaluate the effect of climate and climatic extremes on vegetation. The nonparametric correlation analysis was used to assess the climatic influence on vegetation for various time lags. Besides, the modified Mann-Kendall (MMK) test was conducted to understand the changes in climate and vegetation to anticipate the climate change impacts on vegetation. Satellite estimation of Normalized Difference Vegetation Index (NDVI) and observed rainfall and temperature data collected from five locations of the study area for the period 1982-2018 was used for this purpose. The results revealed a negative effect of rainfall, a positive impact of maximum temperature on vegetation in monsoon and a positive influence on minimum temperature on vegetation in winter. Quantile regression analysis revealed a significant negative influence of extreme rainfall and a positive impact of maximum temperature on vegetation for the whole NWB. Overall, the study revealed a greater influence of temperature than rainfall on vegetation change in the region. The trend analysis revealed a reduction in rainfall (-2.56 mm/decade) and a rise in temperature (0.176ºC/decade), and thus, an increase in vegetation (0.014 per decade). The results indicate the positive effect of climate change on vegetation, positively impacting the environment and water resources in the study area.
Prediction of Death Anxiety Based on Body Image Concerns Mediated by Disease Perception in Patients With Breast Cancer
Authors: Salmanian Kefayat , Marashian Fatemeh Sadat 
Published: August 2021

Abstract
Background

Fear of death and its associated anxiety are among the effective factors of mental health in patients with cancer. The present study aimed to predict death anxiety based on body image concerns mediated by disease perception in patients with breast cancer.
Methods

In this descriptive correlation study, Templer's Death Anxiety Scale, Littleton’s Body Image Concern Inventory, and Broadbent's Brief Illness Perception Questionnaire were used to collect data. The statistical population included all patients with breast cancer in Abadan city in 2020 who referred to medical centers for six months. A total of 200 of which were selected as the sample of the study using convenience sampling. The proposed model was evaluated using path analysis with AMOS software.
Results

The results showed that there was a significant association between body image and disease perception (β = 0.33, P = 0.001), and death anxiety (β = 0.57, P = 0.001), and between disease perception and death anxiety (β = 0.39, P = 0.001). There was a relationship between body image and death anxiety through the mediating role of disease perception in patients with breast cancer (P = 0.009).
Conclusion

According to the results of the study, the relationship of body image with death anxiety through the mediation of disease perception had a good fit and is an important step in identifying the factors affecting the death anxiety of patients with breast cancer.
Coexistence Patterns and Diversity in A Trait-Based Metacommunity On An Environmental Gradient
Authors: Mohammed Mozzamil , Blasius Bernd , Ryabov Alexey 
Published: August 2021

Abstract
The dynamics of trait-based metacommunities have attracted much attention, but not much is known about how dispersal and spatial environmental variability mutually interact with each other to drive coexistence patterns and diversity. Here, we present a spatially-explicit model of resource competition in a metacommunity on a one- dimensional environmental gradient. We find that both the strength of dispersal and the range of spatial environmental variability affect coexistence patterns, spatial structure, trait distribution and local and regional diversity. Without dispersal, species are sorted according to their optimal growth conditions on the gradient. With the onset of dispersal source-sink effects are initiated, which increases the effects of environmental filtering and interspecific competition and generates trait lumping, so that only a few species from an environment-defined trait range can survive. Interestingly, for very large dispersal rates the system becomes spatially homogeneous, but nevertheless two species at the extreme ends of the trait-off curve can coexist for large environmental variability. Local species richness follows a classic hump-shaped dependence on dispersal rate, while local and regional diversity exhibit a pronounced peak for intermediate values of the environmental variability. Our findings provide important insights into the factors that shape the structure of trait-based metacommunities.
Reciprocal causation mixture model for robust mendelian randomization analysis using genome-scale summary data
Authors: Liu Zipeng , Qin Yiming , Wu Tian , Tubbs Justin , Baum Larry , Mak Timothy , Li Miaoxin , Zhang Yan , Sham Pak 
Published: August 2021

Abstract
Mendelian randomization (MR) using GWAS summary statistics has become a popular method to infer causal relationships across complex diseases. However, the widespread pleiotropy observed in GWAS has made the selection of valid instrumental variables (IVs) problematic, leading to possible violations of MR assumptions and thus potentially invalid inferences concerning causation. Furthermore, current MR methods can examine causation in only one direction, so that two separate analyses are required for bi-directional analysis. In this study, we propose a novel strategy, MRCI (Mixture model Reciprocal Causation Inference), to estimate reciprocal causation between two phenotypes simultaneously using the genome-scale summary statistics of the two phenotypes and reference linkage disequilibrium (LD) information. Simulation studies, including strong correlated pleiotropy, showed that MRCI obtained nearly unbiased estimates of causation in both directions, and correct Type I error rates under the null hypothesis. In applications to real GWAS data, MRCI detected significant bi-directional and uni-directional causal influences between common diseases and putative risk factors.
Application of a Portable Home Ventilator for Treating Flail Chest After Cardiopulmonary Resuscitation: A Case Report
Authors: Lee Dong Hyup , Lee Young Uk , Jung Tae-Eun 
Published: August 2021

Abstract
Background Unexpected cardiopulmonary resuscitation and subsequent flail chest are rare in cardiac surgery patients. A patient with a flail chest frequently requires long-term mechanical ventilator care. Early application of portable home ventilator (PHV) might be a useful treatment. Case presentationA 61-year-old female who underwent cardiac surgery had unexpected cardiopulmonary resuscitation with a flail chest. For treating her flail chest, portable home ventilator was applied with several respiratory rehabilitations. ConclusionWe think PHV is useful and alternative treatment for inappropriate for surgical fixation in flail chest patients.
Tryptophan Metabolism Induced by TDO2 Promotes Prostatic Cancer Chemotherapy Resistance in a Ahr/C-Myc Dependent Manner
Authors: Li Fan , Zhao ZHENYU , Zhang ZONGBIAO , ZHANG YAN , GUAN WEI 
Published: August 2021

Abstract
Background: Tumor cells exhibit enhanced metabolism of nutrients to satisfy the demand of sustained proliferation in vivo. Seminal reports have presented evidence that tryptophan (Trp) metabolic reprogramming induced by aberrant indoleamine 2,3-dioxygenases could promote tumor development in several cancer types. However, the underlying mechanism of Trp metabolism associated tumor progression is not fully understood.Materials and methods: Prostatic cell lines LNCaP and VCaP were purchased from the Cell Bank of the Chinese Academy of Sciences (China). Human prostatic tumor tissue samples were obtained from the Tongji Hospital. Female NOD-SCID mice (6~8 weeks) were purchased from Huafukang Co. (China) and raised in SPF room. Commercial kits and instruments were used for cell apoptosis analysis, real-time PCR, western blotting, ELISA analysis and other experiments.Result: Comparing the tumor tissues from prostatic cancer patients, we found elevated expression of tryptophan 2，3-dioxygenase 2 (TDO2), and elevated Trp metabolism in chemo-resistant tumor tissues. In vitro, overexpression of TDO2 significantly promoted the Trp metabolism in prostatic cancer cell lines LNCaP and VCap, resulting in the multidrug resistance development. Mechanistically, we demonstrated that Trp metabolite kynurenine (Kyn) promoted the upregulation and nuclear translocation of transcription factor aryl hydrocarbon receptor (AhR). Subsequently, AhR collaborated with NF-κB to facilitate the activation of c-Myc. In turn, c-Myc promoted the up-regulation of ATP-binding cassette (ABC) transporters and Trp transporters, thereby contributing to chemoresistance and strengthened Trp metabolism in prostatic cancer. Interrupt of Trp/TDO2/Kyn/AhR/c-Myc loop with c-Myc inhibitor Mycro-3 efficiently suppressed the chemoresistance and improved the outcome of chemotherapy, which described a new strategy in clinical prostatic cancer treatment. Conclusion：Our study demonstrates that elevated TOD2 expression promoted Trp metabolism and metabolite Kyn production, thus resulting in the activation of AhR/c-Myc/ABC-SLC transporters signaling pathway. Interrupt of Trp metabolism/c-Myc loop efficiently suppressed the drugs resistance induced by TDO2, which represented potential target to improve the outcome in drug-resistant prostatic cancer treatment.