Linear Size Research Articles

Discovery of A Large-scale Bent Radio Jet in the Merging Cluster A514

We report a discovery of a large-scale bent radio jet in the merging galaxy cluster A514 (z = 0.071). The radio emission originates from the two radio lobes of the active galactic nucleus (AGN) located near the center of the southern subcluster and extends toward the southern outskirts with multiple bends. Its peculiar morphology is characterized by a 400 kpc “bridge,” a 300 kpc “arc,” and a 400 kpc “tail,” which together contribute to its largest linear size of ∼0.7 Mpc. We find that both the flux and spectral features of the emission change with the distance from the AGN. Also, the “bridge” presents a 60% polarized radio emission, which coincided with an X-ray cold front. Based on our multiwavelength observations, we propose that A514 presents a clear case for the redistribution of an old AGN plasma due to merger-driven gas motions. We support our interpretation with idealized cluster merger simulations employing a passive tracer field to represent cosmic-ray electrons and find that merger-driven motions can efficiently create a cloud of these particles in the cluster outskirts, which later can be reaccelerated by the cluster merger shock and produce radio relics.

Dysbiosis of gut microbiota in patients with protein-losing enteropathy after the Fontan procedure

BackgroundThere is a lack of predictive biomarkers for the onset or activity of protein-losing enteropathy (PLE), a Fontan procedure-associated complication. Here, we aimed to identify the gut microbiota composition of patients with active PLE and investigate its relationship with PLE activity. MethodsThis multicenter case–control study involved patients who developed PLE (n = 16) after the Fontan procedure and those who did not (non-PLE; n = 20). Patients with PLE who maintained a serum albumin level of ≥3 g/dL for >1 year were included in the remissive-stage-PLE group (n = 9) and those who did not maintain this level were included in the active-PLE group (n = 7). 16S rRNA gene sequencing analysis of fecal samples was performed using QIIME2 pipeline. Alpha (Shannon and Faith's phylogenetic diversity indices) and beta diversity was assessed using principal coordinate analysis based on unweighted UniFrac distances. ResultsShannon and Faith's phylogenetic diversity indices were lower in the active-PLE group than in the remissive-stage- (q = 0.028 and 0.025, respectively) and non-PLE (q = 0.028 and 0.017, respectively) groups. Analysis of beta diversity revealed a difference in the microbiota composition between the active-PLE and the other two groups. Linear discriminant effect size analysis demonstrated differences in the relative abundance of Bifidobacterium and Granulicatella spp., and Ruminococcus torques between patients with active- and those with remissive-stage-PLE. ConclusionsGut microbiota dysbiosis was observed in patients with active PLE. Changes in the bacterial composition of the gut microbiota and decreased diversity may be associated with the severity of PLE.

Associations between Wastewater Microbiome and Population Smoking Rate Identified Using Wastewater-Based Epidemiology.

Tobacco use is known to cause health damage, partly by changing the mouth, respiratory tract, and gut-related microbiomes. This study aims to identify the associations between the human microbiome detected in domestic wastewater and the population smoking rate. Metagenomic sequencing and a biomarker discovery algorithm were employed to identify microorganisms as potential microbial biomarkers of smoking through wastewater-based epidemiology. Wastewater samples were collected from selected catchments with low and high smoking rates, i.e., 11.2 ± 1.5% and 17.0 ± 1.6%, respectively. Using the linear discriminant analysis effect size (LEfSe) method, Neisseria, Desulfovibrio, Megamonas, Blautia, Fusicatenibacter, Granulicatella and Enterococcus were suggested as potential biomarker microorganisms. A higher abundance of pathogens, including Neisseria, Eikenella and Haemophilus, was associated with the high smoking rate, likely because of their colonization in smoking-disturbed human guts. The identified potential microbial biomarkers reflect the change of the human gut microbiome due to the long-term smoking behavior. The metagenomic analysis also indicates that smoking upregulates microbial gene expression of genetic information processing, environmental information processing, and cell wall peptidoglycan cleavage, while it downregulates amino acid, lipid, and galactose metabolisms. The findings demonstrate the potential of microbial biomarkers for the surveillance of smoking through a wastewater-based epidemiology approach.

A distinctive subgingival microbiome in patients with periodontitis and Alzheimer's disease compared with cognitively unimpaired periodontitis patients.

Periodontitis is caused by dysbiosis of oral microbes and is associated with increased cognitive decline in Alzheimer's disease (AD), and recently, a potential functional link was proposed between oral microbes and AD. We compared the oral microbiomes of patients with or without AD to evaluate the association between oral microbes and AD in periodontitis. Periodontitis patients with AD (n = 15) and cognitively unimpaired periodontitis patients (CU) (n = 14) were recruited for this study. Each patient underwent an oral examination and neuropsychological evaluation. Buccal, supragingival and subgingival plaque samples were collected, and microbiomes were analysed by next-generation sequencing. Alpha diversity, beta diversity, linear discriminant analysis effect size, analysis of variance-like differential expression analysis and network analysis were used to compare group oral microbiomes. All 29 participants had moderate to severe periodontitis. Group buccal and supragingival samples were indistinguishable, but subgingival samples demonstrated significant alpha and beta diversity differences. Differential analysis showed subgingival samples of the AD group had higher prevalence of Atopobium rimae, Dialister pneumosintes, Olsenella sp. HMT 807, Saccharibacteria (TM7) sp. HMT 348 and several species of Prevotella than the CU group. Furthermore, subgingival microbiome network analysis revealed a distinct, closely connected network in the AD group comprised of various Prevotella spp. and several anaerobic bacteria. A unique microbial composition was discovered in the subgingival region in the AD group. Specifically, potential periodontal pathogens were found to be more prevalent in the subgingival plaque samples of the AD group. These bacteria may possess a potential to worsen periodontitis and other systemic diseases. We recommend that AD patients receive regular, careful dental check-ups to ensure proper oral hygiene management.

Bacterial Population Changes during the Degradation Process of a Lactate (LA)-Enriched Biodegradable Polymer in River Water: LA-Cluster Preferable Bacterial Consortium.

The lactate-based polyester poly[lactate (LA)-co-3-hydroxybutyrate (3HB)], termed LAHB, is a highly transparent and flexible bio-based polymeric material. There are many unknowns regarding its degradation process in riverine environments, especially the changes in bacterial flora that might result from its degradation and the identities of any LAHB-degrading bacteria. LAHB were immersed in the river water samples (A and B), and LAHB degradation was observed in terms of the weight change of the polymer and the microscopic changes on the polymer surfaces. A metagenomic analysis of microorganisms was conducted to determine the effect of LAHB degradation on the aquatic environment. The bacterial flora obtained from beta diversity analysis differed between the two river samples. The river A water sample showed the simultaneous degradation of LA and 3HB even though the copolymer was LA-enriched, suggesting preferable hydrolysis of the LA-enriched segments. In contrast, only 3HB degraded for the LAHB in the river B water sample. The linear discriminant analysis effect size (LEfSe) analysis revealed 14 bacteria that were significantly increased in the river A water sample during LAHB degradation, suggesting that these bacteria preferentially degraded and assimilated LA-clustering polymers. Our metagenomic analysis provides useful insights into the dynamic changes in microbial communities and LA-clustering polymer-degrading bacteria.

Gut microbiota in adults with moyamoya disease: characteristics and biomarker identification.

When it comes to the onset of moyamoya disease (MMD), environmental variables are crucial. Furthermore, there is confusion about the relationship between the gut microbiome, an environmental variable, and MMD. Consequently, to identify the particular bacteria that cause MMD, we examined the gut microbiome of MMD individuals and healthy controls (HC). A prospective case-control investigation was performed from June 2021 to May 2022. The fecal samples of patients with MMD and HC were obtained. Typically, 16S rRNA sequencing was employed to examine their gut microbiota. The QIIME and R softwares were used to examine the data. The linear discriminant analysis effect size analysis was used to determine biomarkers. Multivariate analysis by linear models (MaAsLin)2 were used to find associations between microbiome data and clinical variables. Model performance was assessed using the receiver operating characteristic curve and the decision curve analysis. This investigation involved a total of 60 MMD patients and 60 HC. The MMD group's Shannon and Chao 1 indices were substantially lower than those of the HC cohort. β-diversity was significantly different in the weighted UniFrac distances. At the phylum level, the relative abundance of Fusobacteriota/Actinobacteria was significantly higher/lower in the MMD group than that in the HC group. By MaAsLin2 analysis, the relative abundance of the 2 genera, Lachnoclostridium and Fusobacterium, increased in the MMD group, while the relative abundance of the 2 genera, Bifidobacterium and Enterobacter decreased in the MMD group. A predictive model was constructed by using these 4 genera. The area under the receiver operating characteristic curve was 0.921. The decision curve analysis indicated that the model had usefulness in clinical practice. The gut microbiota was altered in individuals with MMD, and was characterized by increased abundance of Lachnoclostridium and Fusobacterium and decreased abundance of Bifidobacterium and Enterobacter. These 4 genera could be used as biomarkers and predictors in clinical practice.

LACC1 regulates changes in the intestinal flora in a mouse model of inflammatory bowel disease

BackgroundThe aim of this study was to explore the mechanism whereby LACC1 regulates the intestinal flora in a mouse model of inflammatory bowel disease (IBD).MethodsC57BL/6 and Lacc1−/− mice were used to establish a mouse model of IBD induced by dextran sodium sulfate (DSS). The effects of Lacc1 deletion in mice were evaluated. Changes in the body weight and stool blood were recorded daily. After 7 days of successful modeling, the mice were sacrificed, blood was collected from the eyeballs, the entire colon was dissected and separated, and the length of the colon was measured.ResultsCompared with the wild-type (WT) DSS model group, the Lacc1−/− DSS model group showed a significantly higher disease activity index score (P < 0.05), significantly faster weight loss (P < 0.05), and a significantly shorter colon (P < 0.05), indicating that the colonic mucosal tissue was seriously damaged in the Lacc1−/− DSS model group (P < 0.05). Serum IL-1β, IL-6, TNF-α, and IFN-γ levels were significantly higher in the Lacc1−/− DSS model group than the WT DSS model group. Principal coordinate analysis showed that there were significant microbiome differences between the WT, Lacc1−/−, WT DSS model, and Lacc1−/− DSS model groups (P < 0.05). Linear discriminant analysis effect size analysis showed that under natural conditions, Lacc1−/− mice had significant changes in their intestinal flora compared with control mice (LDA value > 3 or < 3, P < 0.05).ConclusionsLacc1 deletion aggravates DSS-induced IBD in mice.

Three-dimensional X-ray microtomography of the heart of a chick embryo in the early period of embryogenesis

Relevance. The chicken embryo model is ideal for studying the development of the heart, which is the first functioning organ in embryogenesis. Particular attention is drawn to the embryonic period, when the embryonic heart is both functioning and forming, and small deviations in this process can lead to developmental anomalies. The current lack of results of accurate measurements of the morphology of the heart of a chicken embryo requires high-quality visualization, the complexity of which is determined by dynamic changes in the morphology of the heart, small size and complex spatial details of the organ. Threedimensional imaging methods are indispensable tools in this aspect, among which X-ray microtomography has special advantages.Methods. Embryo scanning (4–8 days, embryonic stages HH22–HH34) was performed using a highresolution X-ray microtomograph Skyscan 1176. A 1% solution of phosphoric-tungstic acid was used as a contrast. Post-processing, reconstruction, visualization of 3D-images, morphometry and X-ray density assessment were carried out using software packages DataViewer (1.5.6.2), CTvox (3.3.0r1403), CT-analyser (1.18.4.0).Results. The results obtained consist of three components: 1) general three-dimensional X-ray microtomographic visualization of chicken embryos in the early stages of embryogenesis with the designation of internal organs, allowing to determine the correct location of the heart; 2) microtomography of the heart with the designation of the main structures; 3) morphometric parameters of the embryo, heart and their X-ray density in units of the Hounsfield scale (HU). The methodological approach used has shown high efficiency. With an increase in the linear size of the chicken embryo and internal organs, including the heart, a high level of both general X-ray contrast and diffraction remains. At all the studied stages of the embryonic period of embryogenesis (4–8 days; HH22–HH34), the main visual and quantitative characteristics of cardiac morphogenesis were revealed.

Abnormal Development of Microbiota May Be a Risk Factor for Febrile Urinary Tract Infection in Infancy.

Febrile urinary tract infection (fUTI) is common in infants, but specific risk factors for developing it remain unclear. As most fUTIs are caused by ascending infections of intestinal bacteria, dysbiosis-an imbalance in gut microbial communities-may increase fUTI risk. This study was conducted to test the hypothesis that abnormal development of gut microbiota during infancy increases the risk of developing fUTI. Stool samples were collected from 28 infants aged 3-11 months with first-onset fUTI (fUTI group) and 51 healthy infants of the same age (HC group). After bacterial DNA extraction, 16S rRNA expression was measured and the diversity of gut microbiota and constituent bacteria were compared between the two groups. The alpha diversity of gut microbiota (median Shannon index and Chao index) was significantly lower in the fUTI group (3.0 and 42.5) than in the HC group (3.7 and 97.0; p < 0.001). The beta diversity also formed different clusters between the two groups (p < 0.001), suggesting differences in their microbial composition. The linear discriminant analysis effect size showed that the fUTI group proportionally featured significantly more Escherichia-Shigella in the gut microbiota (9.5%) than the HC group (3.1%; p < 0.001). In summary, abnormal gut microbiota development during infancy may increase the risk of fUTI.

Deep mining the mechanical behavior of graphene oxide–cement composites using data-driven artificial intelligence techniques

This study presents a data-mining workflow for mining potential information in graphene oxide-cement composite (GOCC) mechanics datasets using data-driven artificial intelligence techniques for enhancing data integrity and for data augmentation using semi-supervised learning. The obtained prediction models for the compressive, flexural, and tensile strengths of the GOCC had high R2 (0.98, 0.94, and 0.95) and low root mean square error (2.84, 0.80, and 0.34) in the real test set. The interpretability analysis of the black-box model showed that an appropriate GO admixture is critical; the GO thickness and linear size mainly affected its compressive strength and flexural strength, respectively. The 50 elites resulting from the search for the optimal mechanical properties of the GOCC in the developed model constituted the Pareto front, providing a suitable parameter design range for the GOCC. This study is essential for understanding the mechanical laws of GOCC and developing efficient design strategies.

Explore the changes of intestinal flora in patients with coronavirus disease 2019 based on bioinformatics.

Studies have revealed that there were significant changes in intestinal flora composition in patients with coronavirus disease 2019 (COVID-19) compared to non-COVID-19 patients, regardless of whether they were treated with medication. Therefore, a comprehensive study of the intestinal flora of COVID-19 patients is needed to further understand the mechanisms of COVID-19 development. In total, 20 healthy samples and 20 COVID-19 samples were collected in this study. Firstly, alpha diversity and beta diversity were analyzed to assess whether there were difference in species richness and diversity as well as species composition between COVID-19 and control groups. The observed features index, Evenness index, PD index, and Shannon index were utilized to measure alpha diversity. The principal coordinates analysis (PCoA) and non-metric multidimensional scaling (NMDS) were performed to analyzed beta diversity. Linear discriminant analysis Effect Size (LEfSe) was utilized to analyze the variability in the abundance of bacterial taxa from different classification levels. The random forest (RF), Least absolute shrinkage and selection operator (LASSO), and univariate logistic regression were utilized to identify key Amplicon Sequence Variant (ASVs). Finally, the relevant networks of bacterial taxa were created in COVID-19 and control groups, separately. There were more species in the control group than in COVID-19 group. The observed features index, Shannon index, and Evenness index in the control groups were markedly higher than in the COVID-19 group. Therefore, there were marked variations in bacterial taxa composition between the COVID-19 and control groups. The nine bacterial taxa were significantly more abundant in the COVID-19 group, such as g-Streptococcus, f-Streptococcaceae, o-Lactobacillales, c-Bacilli and so on. In the control group, 26 bacterial taxa were significantly more abundant, such as c-Clostrjdia, o-Oscillospirales, f-Ruminococcaceae, etc. The 5 key ASVs were obtained through taking the intersection of the characteristic ASVs obtained by the three algorithms, namely ASV6, ASV53, ASV92, ASV96, and ASV105, which had diagnostic value for COVID-19. The relevance network in the control group was more complex compared to the COVID-19 group. Our findings provide five key ASVs for diagnosis of COVID-19, providing a scientific reference for further studies of COVID-19.

Characteristics of the pulmonary microbiota in patients with mild and severe pulmonary infection.

Lung infection is a global health problem associated with high morbidity and mortality and increasing rates of hospitalization. The correlation between pulmonary microecology and infection severity remains unclear. Therefore, the purpose of this study was to investigate the differences in lung microecology and potential biomarkers in patients with mild and severe pulmonary infection. Patients with pulmonary infection or suspected infection were divided into the mild group (140 cases) and the severe group (80 cases) according to pneomonia severity index (PSI) scores. Here, we used metagenomic next-generation sequencing (mNGS) to detect DNA mainly from bronchoalveolar lavage fluid (BALF) collected from patients to analyze changes in the lung microbiome of patients with different disease severity. We used the mNGS to analyze the pulmonary microecological composition in patients with pulmonary infection. The results of alpha diversity and beta diversity analysis showed that the microbial composition between mild and severe groups was similar on the whole. The dominant bacteria were Acinetobacter, Bacillus, Mycobacterium, Staphylococcus, and Prevotella, among others. Linear discriminant analysis effect size (LEfSe) results showed that there were significant differences in virus composition between the mild and severe patients, especially Simplexvirus and Cytomegalovirus, which were prominent in the severe group. The random forest model screened 14 kinds of pulmonary infection-related pathogens including Corynebacterium, Mycobacterium, Streptococcus, Klebsiella, and Acinetobacter. In addition, it was found that Rothia was negatively correlated with Acinetobacter, Mycobacterium, Bacillus, Enterococcus, and Klebsiella in the mild group through co-occurrence network, while no significant correlation was found in the severe group. Here, we describe the composition and diversity of the pulmonary microbiome in patients with pulmonary infection. A significant increase in viral replication was found in the severe group, as well as a significant difference in microbial interactions between patients with mild and severe lung infections, particularly the association between the common pathogenic bacteria and Rothia. This suggests that both pathogen co-viral infection and microbial interactions may influence the course of disease. Of course, more research is needed to further explore the specific mechanisms by which microbial interactions influence disease severity.

Associations of the gut microbiome with psychoneurological symptom cluster in women with gynecologic cancers: a longitudinal study.

The present study aimed to evaluate the associations between the gut microbiome and psychoneurological symptoms (PNS) cluster in women with gynecologic cancers over time. In this secondary data analysis, 19 women with cervical and endometrial cancers treated with radiotherapy were followed at pre-treatment, 6-8 weeks, and 6 months post-treatment. To measure symptoms, Functional Assessment of Cancer Therapy-General (FACT-G) and Patient Health Questionnaire-9 (PHQ-9) were used. An average Z score of at least three out of five symptoms was computed as the PNS cluster total score. Rectal swabs were also collected at the same time points and sequenced using 16S rRNA V4 regions. The Kruskal-Wallis and permutational multivariable analysis of variance tests were used to compare α- and β-diversity between patients with high and low PNS cluster. The linear discriminant analysis effect size (LEfSe) tested taxa differences between study groups. Also, the linear mixed-effect model was used to evaluate the association of the gut microbiome and the PNS cluster over cancer treatment. The patients' mean age was 58 years, 47% Black, 52% single/divorced, and 66% had college or above education. Among the participants, 63% had endometrial cancer with stage I disease. There was a different taxonomy profile between patients with high and low PNS. Patients with high PNS had a lower α-diversity than those with low PNS (Shannon, p = 0.03, evenness, p = 0.03). The mixed effects model results showed that low α-diversity and abundance of Fusicatenibacter and Ruminococcus were associated with high PNS cluster over cancer treatment. The association between the gut microbiome and PNS cluster suggest that the gut microbiota plays a role in developing the PNS cluster. Future larger studies are required to shed light on the gut microbiota role in symptom development in gynecologic cancer patients.

Temporal and Spatial Characterization of Sediment Bacterial Communities from Lake Wetlands in a Plain River Network Region

Sediment bacterial communities are a vital component of microbial communities in aquatic and terrestrial ecosystems and they play a critical role in lake wetlands. We aimed to investigate the effect of season, depth and regional environmental factors on the composition and diversity of bacterial communities in a plain river network area from Taihu Basin. The millions of Illumina reads (16S rRNA gene amplicons) at the surface 25 cm inside samples of the study area were examined using a technically consistent approach. Results from the diversity index, relative abundance, principal component analysis (PCA), redundancy analysis (RDA) and linear discriminant analysis effect size (LEfSe) analysis indicated that the diversity of the bacterial community in summer was generally higher than in other seasons. Proteobacteria were the most abundant phylum in the sediment samples in different seasons (43.15–57.41%) and different layers (39.66–77.97%); the autumn sediments were enriched with Firmicutes (5.67%) and Chloroflexi (12.5%); in all four seasons the sediments were enriched with Betaproteobacteria (14.98–23.45%), Gammaproteobacteria (11.98–14.36%) and Deltaproteobacteria (8.68–14.45%). In the bottom sediments (10–25 cm), Chloroflexi were abundant (average value 10.42%), while Bacteroidetes was the dominant phylum in the surface sediments; redundancy analysis found that total phosphorus (TP) (p = 0.036) was the main environmental factor influencing the sediment bacterial community in different layers. This study provides a reference for further understanding the effects of seasonal changes on sediment microorganisms in lake wetlands.

Treatment and Response Factors in Muscle Activation during Spinal Manipulation.

The forces applied during a spinal manipulation produce a neuromuscular response in the paraspinal muscles. A systematic evaluation of the factors involved in producing this muscle activity provides a clinical insight. The purpose of this study is to quantify the effect of treatment factors (manipulation sequence and manipulation site) and response factors (muscle layer, muscle location, and muscle side) on the neuromuscular response to spinal manipulation. The surface and indwelling electromyographies of 8 muscle sites were recorded during lumbar side-lying manipulations in 20 asymptomatic participants. The effects of the factors on the number of muscle responses and the muscle activity onset delays were compared using mixed-model linear regressions, effect sizes, and equivalence testing. The treatment factors did not reveal statistical differences between the manipulation sequences (first or second) or manipulation sites (L3 or SI) in the number of muscle responses (p = 0.11, p = 0.28, respectively), or in muscle activity onset delays (p = 0.35 p = 0.35, respectively). There were significantly shorter muscle activity onset delays in the multifidi compared to the superficial muscles (p = 0.02). A small effect size of side (d = 0.44) was observed with significantly greater number of responses (p = 0.02) and shorter muscle activity onset delays (p < 0.001) in the muscles on the left side compared to the right. The location, layer, and side of the neuromuscular responses revealed trends of decreasing muscle response rates and increasing muscle activity onset delays as the distance from the manipulation site increased. These results build on the body of work suggesting that the specificity of manipulation site may not play a role in the neuromuscular response to spinal manipulation-at least within the lumbar spine. In addition, these results demonstrate that multiple manipulations performed in similar areas (L3 and S1) do not change the response significantly, as well as contribute to the clinical understanding that the muscle response rate is higher and with a shorter delay, the closer it is to the manipulation.

Gut Microbiome and Lipidome Signatures in Irritable Bowel Syndrome Patients from a Low-Income, Food-Desert Area: A Pilot Study.

Irritable bowel syndrome (IBS) is a common gastroenterological disorder with triggers such as fructose. We showed that our IBS patients suffering from socioeconomic challenges have a significantly high consumption of high-fructose corn syrup (HFCS). Here, we characterize gut microbial dysbiosis and fatty acid changes, with respect to IBS, HFCS consumption, and socioeconomic factors. Fecal samples from IBS patients and healthy controls were subjected to microbiome and lipidome analyses. We assessed phylogenetic diversity and community composition of the microbiomes, and used linear discriminant analysis effect size (LEfSe), analysis of compositions of microbiomes (ANCOM) on highly co-occurring subcommunities (modules), least absolute shrinkage and selection operator (LASSO) on phylogenetic isometric log-ratio transformed (PhILR) taxon abundances to identify differentially abundant taxa. Based on a Procrustes randomization test, the microbiome and lipidome datasets correlated significantly (p = 0.002). Alpha diversity correlated with economic factors (p < 0.001). Multiple subsets of the phylogenetic tree were associated with HFCS consumption (p < 0.001). In IBS patients, relative abundances of potentially beneficial bacteria such as Monoglobaceae, Lachnospiraceae, and Ruminococcaceae were lower (p = 0.007), and Eisenbergiella, associated with inflammatory disorders, was higher. In IBS patients, certain saturated fatty acids were higher and unsaturated fatty acids were lower (p < 0.05). Our study aims first to underscore the influence of HFCS consumption and socioeconomic factors on IBS pathophysiology, and provides new insights that inform patient care.

Multiple imaging of the quasar 2005 + 403 formed by anisotropic scattering

ABSTRACT We report on the low Galactic latitude (b = 4${_{.}^{\circ}}$3) quasar 2005 + 403, the second active galactic nuclei, in which we detected a rare phenomenon of multiple imaging induced by refractive-dominated scattering. The manifestation of this propagation effect is revealed at different frequencies (≲ 8 GHz) and epochs of Very Long Baseline Array (VLBA) observations. The pattern formed by anisotropic scattering is stretched out along the line of constant Galactic latitude with a local position angle, PA ≈ 40° showing 1–2 sub-images, often on either side of the core. Analysing the multifrequency VLBA data ranging from 1.4 to 43.2 GHz, we found that both the angular size of the apparent core component and the separation between the primary and secondary core images follow a wavelength squared dependence, providing convincing evidence for a plasma scattering origin for the multiple imaging. Based on the Owens Valley Radio Observatory long-term monitoring data at 15 GHz obtained for 2005 + 403, we identified the characteristic flux density excursions occurred in 2019 April and May and attributed to an extreme scattering event (ESE) associated with the passage of a plasma lens across the line of sight. Modelling the ESE, we determined that the angular size of the screen is 0.4 mas and it drifts with the proper motion of 4.4 mas yr−1. Assuming that the scattering screen is located in the highly turbulent Cygnus region, the transverse linear size and speed of the lens with respect to the observer are 0.7 au and 37 km s−1, respectively.

Exploration of visual variable guidance in outdoor augmented reality geovisualization

ABSTRACTThe visual perception of augmented reality (AR) geovisualization is significantly different from traditional controllable 2D and 3D visualization. In this study, we extended the rendering styles of color variables to include natural material color (NMC) and illuminating material color (IMC) and extended the size to include linear size (LS) and angular size (AS). Outdoor AR geovisualization user experiments were conducted, examining the guidance characteristics of five static variables (NMC, IMC, shape, AS, LS) and two dynamic variables (vibration, flicker). The results showed that the two dynamic variables provided the highest guidance, and among all the static variables, the order of guidance was shape, IMC, AS, NMC, and finally LS. This is a new finding that is different from the color, size, and shape guidance order in 2D visualization and the color, shape, and size order in 3D visualization. The results could be utilized to guide the selection of visual variables for symbol design in AR geovisualization.

Analysis of the influence of host lifestyle (coffee consumption, drinking, and smoking) on Korean oral microbiome

If a DNA sample collected in the field is old or degraded, short tandem repeat analysis is difficult to perform, a representative analysis method currently used for individual identification. Given that microorganisms exist everywhere and within the human body, in similar amounts to human cells, microbial analysis could be used to identify individuals even in cases in which human DNA-based identification is difficult. Research has demonstrated that the types of microorganisms within the human body differ depending on various internal or external factors, such as body part or bodily fluid type, lifestyle, geographical area of residence, sex, and age. In this study, we aimed to examine the relationship between lifestyle factors and the composition and diversity of the oral microbiome in individuals living in Korea. We collected 43 saliva samples from Korean individuals and analyzed the oral microbiome and its variations due to external factors, such as coffee consumption, drinking, and smoking. Linear discriminant analysis effect size revealed that Oribacterium, Campylobacter, and Megasphaera were abundant in coffee consumers, whereas Saccharimonadales, Clostridia, and Catonella were abundant in alcohol non-drinkers. We found increased levels of Stomatobaculum in the saliva of smokers, compared with that of non-smokers. Thus, our analysis revealed characteristic microorganisms for each parameter that was evaluated (coffee consumption, smoking, drinking). Consequently, our study provides insight into the oral microbiome in the Korean population and lays the foundation for developing the Korean Forensic Microbiome Database.

Host-specific signatures of the respiratory microbiota in domestic animals

While the importance of respiratory microbiota in maintaining respiratory health is increasingly recognized, we still lack a comprehensive understanding of the unique characteristics of respiratory microbiota specific to individual hosts. This study aimed to address this gap by analyzing publicly available 16S rRNA gene datasets from various domestic animals (cats, dogs, pigs, donkeys, chickens, sheep, and cattle) to identify host-specific signatures of respiratory microbiota. The findings revealed that cattle and pigs exhibited the highest Shannon diversity index and observed features, indicating a greater microbial variety compared to other animals. Discriminant analysis demonstrated distinct composition of respiratory microbiota across different animals, with no overlapping abundant taxa. The linear discriminant analysis effect size highlighted prevalent host-specific microbiota signatures in different animal species. Moreover, the composition and diversity of respiratory microbiota were significantly influenced by various factors such as individual study, health status, and sampling sites within the respiratory tract. While associations between host and respiratory microbiota have been uncovered, the relative contributions of host and environment in the selection of respiratory microbiota and their impact on host fitness remain unclear. Further investigations involving diverse hosts are necessary to fully comprehend the significance of host-microbial coevolution in maintaining respiratory health.