Interleukin-18 mediates cardiac dysfunction induced by western diet independent of obesity and hyperglycemia in the mouse

Obesity and diabetes are independent risk factors for heart failure and are associated with the consumption of diet rich in saturated fat and sugar, Western diet (WD), known to induce cardiac dysfunction in the mouse through incompletely characterized inflammatory mechanisms. We hypothesized that the detrimental cardiac effects of WD are mediated by interleukin-18 (IL-18), pro-inflammatory cytokine linked to cardiac dysfunction. C57BL/6J wild-type male mice and IL-18 knockout male mice were fed high-saturated fat and high-sugar diet for 8 weeks. We measured food intake, body weight and fasting glycemia. We assessed left ventricular (LV) systolic and diastolic function by Doppler echocardiography and cardiac catheterization. In wild-type mice, WD induced a significant increase in isovolumetric relaxation time, myocardial performance index and left ventricular end-diastolic pressure, reflecting an impairment in diastolic function, paired with a mild reduction in LV ejection fraction. IL-18 KO mice had higher food intake and greater increase in body weight without significant differences in hyperglycemia. Despite displaying greater obesity, IL-18 knockout mice fed with WD for 8 weeks had preserved cardiac diastolic function and higher left ventricular ejection fraction. IL-18 mediates diet-induced cardiac dysfunction, independent of food intake and obesity, thus highlighting a disconnect between the metabolic and cardiac effects of IL-18

PICKING THE BEST NOVEL ORAL ANTICOAGULANT FOR ATRIAL FIBRILLATION: EVIDENCE FROM A WARFARIN-CONTROLLED NETWORK META-ANALYSIS

Warfarin is a mainstay atrial ibrillation (AF) treatment, yet it has a narrow therapeutic window. Novel agents have been successfully tested against warfarin, yet no direct comparison among them is available. We thus performed a pair-wise and warfarin-adjusted network metaanalyses of novel oral anticoagulants for AF

Application of machine learning in SNP discovery

<p>Abstract</p> <p>Background</p> <p>Single nucleotide polymorphisms (SNP) constitute more than 90% of the genetic variation, and hence can account for most trait differences among individuals in a given species. Polymorphism detection software PolyBayes and PolyPhred give high false positive SNP predictions even with stringent parameter values. We developed a machine learning (ML) method to augment PolyBayes to improve its prediction accuracy. ML methods have also been successfully applied to other bioinformatics problems in predicting genes, promoters, transcription factor binding sites and protein structures.</p> <p>Results</p> <p>The ML program C4.5 was applied to a set of features in order to build a SNP classifier from training data based on human expert decisions (True/False). The training data were 27,275 candidate SNP generated by sequencing 1973 STS (sequence tag sites) (12 Mb) in both directions from 6 diverse homozygous soybean cultivars and PolyBayes analysis. Test data of 18,390 candidate SNP were generated similarly from 1359 additional STS (8 Mb). SNP from both sets were classified by experts. After training the ML classifier, it agreed with the experts on 97.3% of test data compared with 7.8% agreement between PolyBayes and experts. The PolyBayes positive predictive values (PPV) (i.e., fraction of candidate SNP being real) were 7.8% for all predictions and 16.7% for those with 100% posterior probability of being real. Using ML improved the PPV to 84.8%, a 5- to 10-fold increase. While both ML and PolyBayes produced a similar number of true positives, the ML program generated only 249 false positives as compared to 16,955 for PolyBayes. The complexity of the soybean genome may have contributed to high false SNP predictions by PolyBayes and hence results may differ for other genomes.</p> <p>Conclusion</p> <p>A machine learning (ML) method was developed as a supplementary feature to the polymorphism detection software for improving prediction accuracies. The results from this study indicate that a trained ML classifier can significantly reduce human intervention and in this case achieved a 5–10 fold enhanced productivity. The optimized feature set and ML framework can also be applied to all polymorphism discovery software. ML support software is written in Perl and can be easily integrated into an existing SNP discovery pipeline.</p

SNP-PHAGE – High throughput SNP discovery pipeline

BACKGROUND: Single nucleotide polymorphisms (SNPs) as defined here are single base sequence changes or short insertion/deletions between or within individuals of a given species. As a result of their abundance and the availability of high throughput analysis technologies SNP markers have begun to replace other traditional markers such as restriction fragment length polymorphisms (RFLPs), amplified fragment length polymorphisms (AFLPs) and simple sequence repeats (SSRs or microsatellite) markers for fine mapping and association studies in several species. For SNP discovery from chromatogram data, several bioinformatics programs have to be combined to generate an analysis pipeline. Results have to be stored in a relational database to facilitate interrogation through queries or to generate data for further analyses such as determination of linkage disequilibrium and identification of common haplotypes. Although these tasks are routinely performed by several groups, an integrated open source SNP discovery pipeline that can be easily adapted by new groups interested in SNP marker development is currently unavailable. RESULTS: We developed SNP-PHAGE (SNP discovery Pipeline with additional features for identification of common haplotypes within a sequence tagged site (Haplotype Analysis) and GenBank (-dbSNP) submissions. This tool was applied for analyzing sequence traces from diverse soybean genotypes to discover over 10,000 SNPs. This package was developed on UNIX/Linux platform, written in Perl and uses a MySQL database. Scripts to generate a user-friendly web interface are also provided with common queries for preliminary data analysis. A machine learning tool developed by this group for increasing the efficiency of SNP discovery is integrated as a part of this package as an optional feature. The SNP-PHAGE package is being made available open source at . CONCLUSION: SNP-PHAGE provides a bioinformatics solution for high throughput SNP discovery, identification of common haplotypes within an amplicon, and GenBank (dbSNP) submissions. SNP selection and visualization are aided through a user-friendly web interface. This tool is useful for analyzing sequence tagged sites (STSs) of genomic sequences, and this software can serve as a starting point for groups interested in developing SNP markers

Maternal fucosyltransferase 2 status affects the gut bifidobacterial communities of breastfed infants.

BackgroundIndividuals with inactive alleles of the fucosyltransferase 2 gene (FUT2; termed the 'secretor' gene) are common in many populations. Some members of the genus Bifidobacterium, common infant gut commensals, are known to consume 2'-fucosylated glycans found in the breast milk of secretor mothers. We investigated the effects of maternal secretor status on the developing infant microbiota with a special emphasis on bifidobacterial species abundance.ResultsOn average, bifidobacteria were established earlier and more often in infants fed by secretor mothers than in infants fed by non-secretor mothers. In secretor-fed infants, the relative abundance of the Bifidobacterium longum group was most strongly correlated with high percentages of the order Bifidobacteriales. Conversely, in non-secretor-fed infants, Bifidobacterium breve was positively correlated with Bifidobacteriales, while the B. longum group was negatively correlated. A higher percentage of bifidobacteria isolated from secretor-fed infants consumed 2'-fucosyllactose. Infant feces with high levels of bifidobacteria had lower milk oligosaccharide levels in the feces and higher amounts of lactate. Furthermore, feces containing different bifidobacterial species possessed differing amounts of oligosaccharides, suggesting differential consumption in situ.ConclusionsInfants fed by non-secretor mothers are delayed in the establishment of a bifidobacteria-laden microbiota. This delay may be due to difficulties in the infant acquiring a species of bifidobacteria able to consume the specific milk oligosaccharides delivered by the mother. This work provides mechanistic insight into how milk glycans enrich specific beneficial bacterial populations in infants and reveals clues for enhancing enrichment of bifidobacterial populations in at risk populations - such as premature infants

Cardiovascular Complications of COVID-19: Pharmacotherapy Perspective

Coronavirus disease of 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is spreading rapidly the world over. The disease was declared �pandemic� by the World Health Organization. An approved therapy for patients with COVID-19 has yet to emerge; however, there are some medications used in the treatment of SARS-CoV-2 infection globally including hydroxychloroquine, remdesivir, dexamethasone, protease inhibitors, and anti-inflammatory agents. Patients with underlying cardiovascular disease are at increased risk of mortality and morbidity from COVID-19. Moreover, patients with chronic stable states and even otherwise healthy individuals might sustain acute cardiovascular problems due to COVID-19 infection. This article seeks to review the latest evidence with a view to explaining possible pharmacotherapies for the cardiovascular complications of COVID-19 including acute coronary syndrome, heart failure, myocarditis, arrhythmias, and venous thromboembolism, as well as possible interactions between these medications and those currently administered (or under evaluation) in the treatment of COVID-19. © 2020, Springer Science+Business Media, LLC, part of Springer Nature

Role of Interleukin-1 in Radiation-Induced Cardiomyopathy

Thoracic X-ray therapy (XRT), used in cancer treatment, is associated with increased risk of heart failure. XRT-mediated injury to the heart induces an inflammatory response leading to cardiomyopathy. The aim of this study was to determine the role of interleukin (IL)-1 in response to XRT injury to the heart and on the cardiomyopathy development in the mouse. Female mice with genetic deletion of the IL-1 receptor type I (IL-1R1 knockout mice [IL-1R1 KO]) and treatment with recombinant human IL-1 receptor antagonist anakinra, 10 mg/kg twice daily for 7 d, were used as independent approaches to determine the role of IL-1. Wild-type (wt) or IL-1R1 KO mice were treated with a single session of XRT (20 or 14 gray [Gy]). Echocardiography (before and after isoproterenol challenge) and left ventricular (LV) catheterization were performed to evaluate changes in LV dimensions and function. Masson’s trichrome was used to assess myocardial fibrosis and pericardial thickening. After 20 Gy, the contractile reserve was impaired in wt mice at d 3, and the LV ejection fraction (EF) was reduced after 4 months when compared with sham-XRT. IL-1R1 KO mice had preserved contractile reserve at 3 d and 4 months and LVEF at 4 months after XRT. Anakinra treatment for 1 d before and 7 d after XRT prevented the impairment in contractile reserve. A significant increase in LV end-diastolic pressure, associated with increased myocardial interstitial fibrosis and pericardial thickening, was observed in wt mice, as well as in IL-1R1 KO–or anakinra-treated mice. In conclusion, induction of IL-1 by XRT mediates the development of some, such as the contractile impairment, but not all aspects of the XRT-induced cardiomyopathy, such as myocardial fibrosis or pericardial thickening

Signatures of selection and environmental adaptation across the goat genome post-domestication

Background: Since goat was domesticated 10,000 years ago, many factors have contributed to the differentiation of goat breeds and these are classified mainly into two types: (i) adaptation to different breeding systems and/or purposes and (ii) adaptation to different environments. As a result, approximately 600 goat breeds have developed worldwide; they differ considerably from one another in terms of phenotypic characteristics and are adapted to a wide range of climatic conditions. In this work, we analyzed the AdaptMap goat dataset, which is composed of data from more than 3000 animals collected worldwide and genotyped with the CaprineSNP50 BeadChip. These animals were partitioned into groups based on geographical area, production uses, available records on solid coat color and environmental variables including the sampling geographical coordinates, to investigate the role of natural and/or artificial selection in shaping the genome of goat breeds. Results: Several signatures of selection on different chromosomal regions were detected across the different breeds, sub-geographical clusters, phenotypic and climatic groups. These regions contain genes that are involved in important biological processes, such as milk-, meat- or fiber-related production, coat color, glucose pathway, oxidative stress response, size, and circadian clock differences. Our results confirm previous findings in other species on adaptation to extreme environments and human purposes and provide new genes that could explain some of the differences between goat breeds according to their geographical distribution and adaptation to different environments. Conclusions: These analyses of signatures of selection provide a comprehensive first picture of the global domestication process and adaptation of goat breeds and highlight possible genes that may have contributed to the differentiation of this species worldwide

De novo assembly of the cattle reference genome with single-molecule sequencing.

BackgroundMajor advances in selection progress for cattle have been made following the introduction of genomic tools over the past 10-12 years. These tools depend upon the Bos taurus reference genome (UMD3.1.1), which was created using now-outdated technologies and is hindered by a variety of deficiencies and inaccuracies.ResultsWe present the new reference genome for cattle, ARS-UCD1.2, based on the same animal as the original to facilitate transfer and interpretation of results obtained from the earlier version, but applying a combination of modern technologies in a de novo assembly to increase continuity, accuracy, and completeness. The assembly includes 2.7 Gb and is &gt;250× more continuous than the original assembly, with contig N50 &gt;25 Mb and L50 of 32. We also greatly expanded supporting RNA-based data for annotation that identifies 30,396 total genes (21,039 protein coding). The new reference assembly is accessible in annotated form for public use.ConclusionsWe demonstrate that improved continuity of assembled sequence warrants the adoption of ARS-UCD1.2 as the new cattle reference genome and that increased assembly accuracy will benefit future research on this species