Multiple-quantum 13 C solid-state NMR spectroscopy under moderate magic-angle spinning

Abstract A new method for the excitation and detection of high-order 13 C multiple-quantum (MQ) nuclear magnetic resonance (NMR) signals in solids under magic-angle spinning (MAS) condition is presented. In this experimental scheme, high-order 13 C MQ coherences are generated by relaying several sequentially generated 13 C double-quantum (DQ) coherences in dipolar coupled networks. Numerical simulations and experimental implementations are presented to demonstrate the efficiency of this method under a moderate MAS frequency regime. 13 C MQ signals up to 10-quantum coherences are observed experimentally on the model compound 1-13 C-labeled glycine, at an MAS frequency of 12 kHz

Mobile resistome of human gut and pathogen drives anthropogenic bloom of antibiotic resistance

BACKGROUND:The impact of human activities on the environmental resistome has been documented in many studies, but there remains the controversial question of whether the increased antibiotic resistance observed in anthropogenically impacted environments is just a result of contamination by resistant fecal microbes or is mediated by indigenous environmental organisms. Here, to determine exactly how anthropogenic influences shape the environmental resistome, we resolved the microbiome, resistome, and mobilome of the planktonic microbial communities along a single river, the Han, which spans a gradient of human activities. RESULTS:The bloom of antibiotic resistance genes (ARGs) was evident in the downstream regions and distinct successional dynamics of the river resistome occurred across the spatial continuum. We identified a number of widespread ARG sequences shared between the river, human gut, and pathogenic bacteria. These human-related ARGs were largely associated with mobile genetic elements rather than particular gut taxa and mainly responsible for anthropogenically driven bloom of the downstream river resistome. Furthermore, both sequence- and phenotype-based analyses revealed environmental relatives of clinically important proteobacteria as major carriers of these ARGs. CONCLUSIONS:Our results demonstrate a more nuanced view of the impact of anthropogenic activities on the river resistome: fecal contamination is present and allows the transmission of ARGs to the environmental resistome, but these mobile genes rather than resistant fecal bacteria proliferate in environmental relatives of their original hosts. Video abstract

Correlation between thigh skinfold thickness and physical fitness factors in Korean adults and older individuals

Background: This cross-sectional epidemiological study aimed to compare the differences in physical fitness variables according to the skinfold thickness in the thigh area in adults and Korean older individuals. Methods: We analyzed data from the 2015 National Fitness Survey. A total of 4034 healthy adults (2442 men, 1592 women) with an average age of 38.19 ± 12.41 years and 880 healthy older subjects (369 men, 511 women) with an average age of 72.32 ± 5.49 years participated in this study. The skinfold thickness of the thigh was measured using a skinfold caliper (Dynatron, Dynatronics, USA). The participants underwent physical fitness tests, including the hand squeeze strength test, abdominal curl ups, standing double-leg long jump, 50 m shuttle run, sit and reach, and 20 m shuttle run for adult men and women. Older men and women performed the following tests: hand squeeze strength, abdominal curl ups, sit to stand test, single leg balance (open eyes), sit and reach, Apley scratch test for shoulder mobility, and 6-minute walk test. Independent t-tests and Pearson correlation analyses were used for the analysis. Results: Among the older men, significant differences were found in thigh skinfold thickness (t = –21.122, p < 0.001), abdominal curl ups (t = 2.165, p = 0.031), and sit and reach in men (t = 2.609, p = 0.009), and thigh skinfold (t = –29.611, p < 0.001), and Apley scratch test for shoulder mobility in women (t = –2.120, p = 0.034). There was a significant correlation between thigh skinfold thickness and physical activity (thigh skinfold thickness) in adult men (t = –54.202, p < 0.001), nondominant hand squeeze strength (t = 2.632, p = 0.009), abdominal curl ups (t = 4.292, p < 0.001), sit and reach (t = 3.063, p = 0.002), twenty meters shuttle run (t = 4.657, p < 0.001). However, no significant differences were found in dominant hand squeeze strength, standing double leg long jump, or 50 m shuttle run in men (p < 0.05). In adult women, there was a significant correlation between thigh skinfold thickness and physical activity (thigh skinfold thickness (t = –49.405, p < 0.001), dominant hand squeeze strength (t = 7.789, p < 0.001), nondominant hand squeeze strength (t = 6.944, p < 0.001), abdominal curl ups (t = 5.347, p < 0.001), standing double leg long jump (t = 5.890, p < 0.001), sit and reach (t = 5.384, p < 0.001), twenty meter shuttle run (t = 5.223, p < 0.001). However, no significant differences were found in fifty meter shuttle run in women (p < 0.05). Among older men, only single leg balance and sit and reach were correlated with thigh skinfold (single leg balance r = 0.169, p = 0.01; sit and reach r = –0.201, p = 0.001). In women, only abdominal curl ups, sit and reach, and Apley scratch test correlated with thigh skinfold (abdominal curl ups r = –0.088, p = 0.002; sit and reach r = –0.137, p = 0.002; Apley scratch test r = 0.090, p = 0.041). Conclusions: The effect of thigh skinfold thickness on the level of physical activity was more pronounced in adults than in older subjects. Our findings show that muscle strength and body fat in the lower extremities can affect overall muscle strength, endurance, and balance

Enterovirus 71 Infection with Central Nervous System Involvement, South Korea

We assessed neurologic sequelae associated with an enterovirus 71 (EV71) outbreak in South Korea during 2009. Four of 94 patients had high signal intensities at brainstem or cerebellum on magnetic resonance imaging. Two patients died of cardiopulmonary collapse; 2 had severe neurologic sequelae. Severity and case-fatality rates may differ by EV71 genotype or subgenotype

The nuclear immune receptor RPS4 is required for RRS1SLH1-dependent constitutive defense activation in Arabidopsis thaliana

Plant nucleotide-binding leucine-rich repeat (NB-LRR) disease resistance (R) proteins recognize specific ‘‘avirulent’’ pathogen effectors and activate immune responses. NB-LRR proteins structurally and functionally resemble mammalian Nod-like receptors (NLRs). How NB-LRR and NLR proteins activate defense is poorly understood. The divergently transcribed Arabidopsis R genes, RPS4 (resistance to Pseudomonas syringae 4) and RRS1 (resistance to Ralstonia solanacearum 1), function together to confer recognition of Pseudomonas AvrRps4 and Ralstonia PopP2. RRS1 is the only known recessive NBLRR R gene and encodes a WRKY DNA binding domain, prompting suggestions that it acts downstream of RPS4 for transcriptional activation of defense genes. We define here the early RRS1-dependent transcriptional changes upon delivery of PopP2 via Pseudomonas type III secretion. The Arabidopsis slh1 (sensitive to low humidity 1) mutant encodes an RRS1 allele (RRS1SLH1) with a single amino acid (leucine) insertion in the WRKY DNA-binding domain. Its poor growth due to constitutive defense activation is rescued at higher temperature. Transcription profiling data indicate that RRS1SLH1-mediated defense activation overlaps substantially with AvrRps4- and PopP2-regulated responses. To better understand the genetic basis of RPS4/RRS1-dependent immunity, we performed a genetic screen to identify suppressor of slh1 immunity (sushi) mutants. We show that many sushi mutants carry mutations in RPS4, suggesting that RPS4 acts downstream or in a complex with RRS1. Interestingly, several mutations were identified in a domain C-terminal to the RPS4 LRR domain. Using an Agrobacterium-mediated transient assay system, we demonstrate that the P-loop motif of RPS4 but not of RRS1SLH1 is required for RRS1SLH1 function. We also recapitulate the dominant suppression of RRS1SLH1 defense activation by wild type RRS1 and show this suppression requires an intact RRS1 P-loop. These analyses of RRS1SLH1 shed new light on mechanisms by which NB-LRR protein pairs activate defense signaling, or are held inactive in the absence of a pathogen effector

The First Very Long Baseline Interferometry Image of 44 GHz Methanol Maser with the KVN and VERA Array (KaVA)

We have carried out the first very long baseline interferometry (VLBI) imaging of 44 GHz class I methanol maser (7_{0}-6_{1}A^{+}) associated with a millimeter core MM2 in a massive star-forming region IRAS 18151-1208 with KaVA (KVN and VERA Array), which is a newly combined array of KVN (Korean VLBI Network) and VERA (VLBI Exploration of Radio Astrometry). We have succeeded in imaging compact maser features with a synthesized beam size of 2.7 milliarcseconds x 1.5 milliarcseconds (mas). These features are detected at a limited number of baselines within the length of shorter than approximately 650 km corresponding to 100 Mlambda in the uv-coverage. The central velocity and the velocity width of the 44 GHz methanol maser are consistent with those of the quiescent gas rather than the outflow traced by the SiO thermal line. The minimum component size among the maser features is ~ 5 mas x 2 mas, which corresponds to the linear size of ~ 15 AU x 6 AU assuming a distance of 3 kpc. The brightness temperatures of these features range from ~ 3.5 x 10^{8} to 1.0 x 10^{10} K, which are higher than estimated lower limit from a previous Very Large Array observation with the highest spatial resolution of ~ 50 mas. The 44 GHz class I methanol maser in IRAS 18151-1208 is found to be associated with the MM2 core, which is thought to be less evolved than another millimeter core MM1 associated with the 6.7 GHz class II methanol maser.Comment: 19 pages, 3 figure

Densely Convolutional Spatial Attention Network for nuclei segmentation of histological images for computational pathology

IntroductionAutomatic nuclear segmentation in digital microscopic tissue images can aid pathologists to extract high-quality features for nuclear morphometrics and other analyses. However, image segmentation is a challenging task in medical image processing and analysis. This study aimed to develop a deep learning-based method for nuclei segmentation of histological images for computational pathology.MethodsThe original U-Net model sometime has a caveat in exploring significant features. Herein, we present the Densely Convolutional Spatial Attention Network (DCSA-Net) model based on U-Net to perform the segmentation task. Furthermore, the developed model was tested on external multi-tissue dataset – MoNuSeg. To develop deep learning algorithms for well-segmenting nuclei, a large quantity of data are mandatory, which is expensive and less feasible. We collected hematoxylin and eosin–stained image data sets from two hospitals to train the model with a variety of nuclear appearances. Because of the limited number of annotated pathology images, we introduced a small publicly accessible data set of prostate cancer (PCa) with more than 16,000 labeled nuclei. Nevertheless, to construct our proposed model, we developed the DCSA module, an attention mechanism for capturing useful information from raw images. We also used several other artificial intelligence-based segmentation methods and tools to compare their results to our proposed technique.ResultsTo prioritize the performance of nuclei segmentation, we evaluated the model’s outputs based on the Accuracy, Dice coefficient (DC), and Jaccard coefficient (JC) scores. The proposed technique outperformed the other methods and achieved superior nuclei segmentation with accuracy, DC, and JC of 96.4% (95% confidence interval [CI]: 96.2 – 96.6), 81.8 (95% CI: 80.8 – 83.0), and 69.3 (95% CI: 68.2 – 70.0), respectively, on the internal test data set.ConclusionOur proposed method demonstrates superior performance in segmenting cell nuclei of histological images from internal and external datasets, and outperforms many standard segmentation algorithms used for comparative analysis