Poly[[aqua­(μ2-oxalato)(μ2-2-oxido­pyridinium-3-carboxylato)holmium(III)] monohydrate]

In the title complex, {[Ho(C2O4)(C6H4NO3)(H2O)]·(H2O)}n, the HoIII ion is coordinated by three O atoms from two 2-oxidopyridinium-3-carboxylate ligands, four O atoms from two oxalate ligands and one water mol­ecule in a distorted bicapped trigonal-prismatic geometry. The 2-oxidopyridin­ium-3-carboxylate and oxalate ligands link the HoIII ions into a layer in (100). These layers are further connected by inter­molecular O—H⋯O hydrogen bonds involving the coordinated water mol­ecules to assemble a three-dimensional supra­molecular network. The uncoordin­ated water mol­ecule is involved in N—H⋯O and O—H⋯O hydrogen bonds within the layer

Vertices with the Second Neighborhood Property in Eulerian Digraphs

The Second Neighborhood Conjecture states that every simple digraph has a vertex whose second out-neighborhood is at least as large as its first out-neighborhood, i.e. a vertex with the Second Neighborhood Property. A cycle intersection graph of an even graph is a new graph whose vertices are the cycles in a cycle decomposition of the original graph and whose edges represent vertex intersections of the cycles. By using a digraph variant of this concept, we prove that Eulerian digraphs which admit a simple dicycle intersection graph have not only adhere to the Second Neighborhood Conjecture, but have a vertex of minimum outdegree that has the Second Neighborhood Property.Comment: fixed an error in an earlier version and made structural change

Identification of gene pairs through penalized regression subject to constraints

Abstract Background This article concerns the identification of gene pairs or combinations of gene pairs associated with biological phenotype or clinical outcome, allowing for building predictive models that are not only robust to normalization but also easily validated and measured by qPCR techniques. However, given a small number of biological samples yet a large number of genes, this problem suffers from the difficulty of high computational complexity and imposes challenges to the accuracy of identification statistically. Results In this paper, we propose a parsimonious model representation and develop efficient algorithms for identification. Particularly, we derive an equivalent model subject to a sum-to-zero constraint in penalized linear regression, where the correspondence between nonzero coefficients in these models is established. Most importantly, it reduces the model complexity of the traditional approach from the quadratic order to the linear order in the number of candidate genes, while overcoming the difficulty of model nonidentifiablity. Computationally, we develop an algorithm using the alternating direction method of multipliers (ADMM) to deal with the constraint. Numerically, we demonstrate that the proposed method outperforms the traditional method in terms of the statistical accuracy. Moreover, we demonstrate that our ADMM algorithm is more computationally efficient than a coordinate descent algorithm with a local search. Finally, we illustrate the proposed method on a prostate cancer dataset to identify gene pairs that are associated with pre-operative prostate-specific antigen. Conclusion Our findings demonstrate the feasibility and utility of using gene pairs as biomarkers.https://deepblue.lib.umich.edu/bitstream/2027.42/139017/1/12859_2017_Article_1872.pd

Scientometric trends and knowledge maps of global health systems research

Background: In the last few decades, health systems research (HSR) has garnered much attention with a rapid increase in the related literature. This study aims to review and evaluate the global progress in HSR and assess the current quantitative trends. Methods: Based on data from the Web of Science database, scientometric methods and knowledge visualization techniques were applied to evaluate global scientific production and develop trends of HSR from 1900 to 2012. Results: HSR has increased rapidly over the past 20 years. Currently, there are 28,787 research articles published in 3,674 journals that are listed in 140 Web of Science subject categories. The research in this field has mainly focused on public, environmental and occupational health (6,178, 21.46%), health care sciences and services (5,840, 20.29%), and general and internal medicine (3,783, 13.14%). The top 10 journals had published 2,969 (10.31%) articles and received 5,229 local citations and 40,271 global citations. The top 20 authors together contributed 628 papers, which accounted for a 2.18% share in the cumulative worldwide publications. The most productive author was McKee, from the London School of Hygiene \& Tropical Medicine, with 48 articles. In addition, USA and American institutions ranked the first in health system research productivity, with high citation times, followed by the UK and Canada. Conclusions: HSR is an interdisciplinary area. Organization for Economic Co-operation and Development countries showed they are the leading nations in HSR. Meanwhile, American and Canadian institutions and the World Health Organization play a dominant role in the production, collaboration, and citation of high quality articles. Moreover, health policy and analysis research, health systems and sub-systems research, healthcare and services research, health, epidemiology and economics of communicable and non-communicable diseases, primary care research, health economics and health costs, and pharmacy of hospital have been identified as the mainstream topics in HSR fields. These findings will provide evidence of the current status and trends in HSR all over the world, as well as clues to the impact of this popular topic; thus, helping scientific researchers and policy makers understand the panorama of HSR and predict the dynamic directions of research

Antibacterial Activity and Mode of Action of Mentha arvensis Ethanol Extract against Multidrug-Resistant Acinetobacter baumannii

Purpose: To evaluate the antibacterial effect of ethanol extract of Mentha arvensis against multi-drug resistant Acinetobacter baumannii using liquid chromatography–mass spectrometry (LC-ESI-MS).Methods: Disc diffusion and microdilution assays were used to evaluate the antibacterial effect of the extract by measuring the zone of inhibition, minimum inhibitory concentration (MIC) and and minimum bacteriocidal concentration (MBC) of the extract against the test bacteria. Scanning electron microscopy (SEM) was employed to evaluate the morphological changes induced by the extract in cellular membrane of the bacteria. Reactive oxygen species (ROS) generation and protein leakage from the bacterial cells induced by the extract were also evaluated.Results: The extract showed dose-dependent growth inhibitory effects against A. baumannii with MIC and MBC of 23.5 and 72.1 μg/mL, respectively. The extract also induced potent ROS generation and protein leakage in A. baumannii bacterial cells. SEM findings revealed that the extract induced potential cellular damage which increased with increasing extract concentration.Conclusion: The ethanol extract of Mentha arvensis is a potent antibacterial agent against A. baumannii and acts by inducing lethal cellular damage to the bacterium.Keywords: Mentha arvensis, Acinetobacter baumannii, Reactive oxygen species, Antibacterial activity, Cellular membrane damag

Modification of atrioventricular node in a special condition treating paroxysmal supraventricular tachycardia

Modification of atrioventricular node is a usual and necessary operation to cure atrioventricular nodal reentrant tachycardia (AVNRT). In this operation, atrioventricular block is the most severe complication and its prevention is of our great concern. This complication always occurs under some special circumstances with potential risk. So, it is very important to realize such conditions, as in this paper. A patient with paroxysmal palpitation for 10 years, aggravating to shortness of breath with chest distress for 1 year; cardiac electrophysiological examination found slow conduction in both antegrade and retrograde paths of reentrant loop, and typical AVNRT could be induced. During effective ablation there was no junctional rhythm. In some special cases, modification of atrioventricular node should not only rely on the junctional rhythm to determine the ablation effect, but also on the time of cardiac electrophysiological examination, as such to avoid the severe complication of atrioventricular block caused by excessive ablation

Biogeographic traits of dimethyl sulfide and dimethylsulfoniopropionate cycling in polar oceans

Background: Dimethyl sulfide (DMS) is the dominant volatile organic sulfur in global oceans. The predominant source of oceanic DMS is the cleavage of dimethylsulfoniopropionate (DMSP), which can be produced by marine bacteria and phytoplankton. Polar oceans, which represent about one fifth of Earth’s surface, contribute significantly to the global oceanic DMS sea-air flux. However, a global overview of DMS and DMSP cycling in polar oceans is still lacking and the key genes and the microbial assemblages involved in DMSP/DMS transformation remain to be fully unveiled. Results: Here, we systematically investigated the biogeographic traits of 16 key microbial enzymes involved in DMS/DMSP cycling in 60 metagenomic samples from polar waters, together with 174 metagenome and 151 metatranscriptomes from non-polar Tara Ocean dataset. Our analyses suggest that intense DMS/DMSP cycling occurs in the polar oceans. DMSP demethylase (DmdA), DMSP lyases (DddD, DddP, and DddK), and trimethylamine monooxygenase (Tmm, which oxidizes DMS to dimethylsulfoxide) were the most prevalent bacterial genes involved in global DMS/DMSP cycling. Alphaproteobacteria (Pelagibacterales) and Gammaproteobacteria appear to play prominent roles in DMS/DMSP cycling in polar oceans. The phenomenon that multiple DMS/DMSP cycling genes co-occurred in the same bacterial genome was also observed in metagenome assembled genomes (MAGs) from polar oceans. The microbial assemblages from the polar oceans were significantly correlated with water depth rather than geographic distance, suggesting the differences of habitats between surface and deep waters rather than dispersal limitation are the key factors shaping microbial assemblages involved in DMS/DMSP cycling in polar oceans. Conclusions: Overall, this study provides a global overview of the biogeographic traits of known bacterial genes involved in DMS/DMSP cycling from the Arctic and Antarctic oceans, laying a solid foundation for further studies of DMS/DMSP cycling in polar ocean microbiome at the enzymatic, metabolic, and processual levels. 6bJ8nkA7sq-T64bgHw5GYLVideo Abstrac

An Autoencoder-Based Deep Learning Method For Genotype Imputation

Genotype imputation has a wide range of applications in genome-wide association study (GWAS), including increasing the statistical power of association tests, discovering trait-associated loci in meta-analyses, and prioritizing causal variants with fine-mapping. In recent years, deep learning (DL) based methods, such as sparse convolutional denoising autoencoder (SCDA), have been developed for genotype imputation. However, it remains a challenging task to optimize the learning process in DL-based methods to achieve high imputation accuracy. To address this challenge, we have developed a convolutional autoencoder (AE) model for genotype imputation and implemented a customized training loop by modifying the training process with a single batch loss rather than the average loss over batches. This modified AE imputation model was evaluated using a yeast dataset, the human leukocyte antigen (HLA) data from the 1,000 Genomes Project (1KGP), and our in-house genotype data from the Louisiana Osteoporosis Study (LOS). Our modified AE imputation model has achieved comparable or better performance than the existing SCDA model in terms of evaluation metrics such as the concordance rate (CR), the Hellinger score, the scaled Euclidean norm (SEN) score, and the imputation quality score (IQS) in all three datasets. Taking the imputation results from the HLA data as an example, the AE model achieved an average CR of 0.9468 and 0.9459, Hellinger score of 0.9765 and 0.9518, SEN score of 0.9977 and 0.9953, and IQS of 0.9515 and 0.9044 at missing ratios of 10% and 20%, respectively. As for the results of LOS data, it achieved an average CR of 0.9005, Hellinger score of 0.9384, SEN score of 0.9940, and IQS of 0.8681 at the missing ratio of 20%. In summary, our proposed method for genotype imputation has a great potential to increase the statistical power of GWAS and improve downstream post-GWAS analyses