Cottonmunksgaard6593

Additionally, the subgroup analysis by ethnicity revealed significant association in Asian, American, and Europeans. Finally, subgroup analysis by East Asian and non-East Asian populations indicated significant associations.

The current meta-analysis revealed that IL4 gene -589C/T polymorphism was a susceptibility risk in both pediatrics and adults in the whole and different ethnic groups.

The current meta-analysis revealed that IL4 gene -589C/T polymorphism was a susceptibility risk in both pediatrics and adults in the whole and different ethnic groups.

Replication studies showed conflicting effects of ABCG2 and SLC2A9 polymorphisms on gout and serum urate. This meta-analysis therefore aimed to pool their effects across studies.

Studies were located from MEDLINE and Scopus from inception to 17th June 2018. Observational studies in adults with any polymorphism in ABCG2 or SLC2A9, and outcome including gout, hyperuricemia, and serum urate were included for pooling. Data extractions were performed by two independent reviewers. Genotype effects were pooled stratified by ethnicity using a mixed-effect logistic model and a multivariate meta-analysis for dichotomous and continuous outcomes.

Fifty-two studies were included in the analysis. For ABCG2 polymorphisms, mainly studied in Asians, carrying 1-2 minor-allele-genotypes of rs2231142 and rs72552713 were respectively about 2.1-4.5 and 2.5-3.9 times higher odds of gout than non-minor-allele-genotypes. The two rs2231142-risk-genotypes also had higher serum urate about 11-18 μmol/l. Conversely, carrying 1-2 minor alleles of rs2231137 was about 36-57% significantly lower odds of gout. For SLC2A9 polymorphisms, mainly studied in Caucasians, carrying 1-2 minor alleles of rs1014290, rs6449213, rs6855911, and rs7442295 were about 25-43%, 31-62%, 33-64%, and 35-65% significantly lower odds of gout than non-minor-allele-genotypes. In addition, 1-2 minor-allele-genotypes of the latter three polymorphisms had significantly lower serum urate about 20-49, 21-51, and 18-54 μmol/l than non-minor-allele-genotypes.

Our findings should be useful in identifying patients at risk for gout and high serum urate and these polymorphisms may be useful in personalized risk scores.

PROSPERO registration number CRD42018105275 .

PROSPERO registration number CRD42018105275 .

Arbuscular mycorrhizal fungi are the most widely distributed mycorrhizal fungi, which can form mycorrhizal symbionts with plant roots and enhance plant stress resistance by regulating host metabolic activities. In this paper, the RNA sequencing and ultra-performance liquid chromatography (UPLC) coupled with tandem mass spectrometry (MS/MS) technologies were used to study the transcriptome and metabolite profiles of the roots of continuously cropped soybeans that were infected with F. mosseae and F. oxysporum. The objective was to explore the effects of F. mosseae treatment on soybean root rot infected with F. oxysporum.

According to the transcriptome profiles, 24,285 differentially expressed genes (DEGs) were identified, and the expression of genes encoding phenylalanine ammonia lyase (PAL), trans-cinnamate monooxygenase (CYP73A), cinnamyl-CoA reductase (CCR), chalcone isomerase (CHI) and coffee-coenzyme o-methyltransferase were upregulated after being infected with F. oxysporum; these changes were key tohe plants to resist diseases. MLN4924 clinical trial This study provides new insights into the molecular mechanism by which AMF alleviates soybean root rot, which is important in agriculture.

The results showed that F. mosseae could alleviate the root rot caused by continuous cropping. The increased activity of some disease-resistant genes and disease-resistant metabolites may partly account for the ability of the plants to resist diseases. This study provides new insights into the molecular mechanism by which AMF alleviates soybean root rot, which is important in agriculture.

Optimality principles have been used to explain the structure and behavior of living matter at different levels of organization, from basic phenomena at the molecular level, up to complex dynamics in whole populations. Most of these studies have assumed a single-criteria approach. Such optimality principles have been justified from an evolutionary perspective. In the context of the cell, previous studies have shown how dynamics of gene expression in small metabolic models can be explained assuming that cells have developed optimal adaptation strategies. Most of these works have considered rather simplified representations, such as small linear pathways, or reduced networks with a single branching point, and a single objective for the optimality criteria.

Here we consider the extension of this approach to more realistic scenarios, i.e. biochemical pathways of arbitrary size and structure. We first show that exploiting optimality principles for these networks poses great challenges due to the complexity of and metabolite concentrations in complex metabolic pathways. Further, we also show how to consider general cost/benefit trade-offs. In this study we have considered metabolic pathways, but this computational framework can also be applied to analyze the dynamics of other complex pathways, such as signal transduction or gene regulatory networks.The introduction of monoclonal antibodies (mAbs) against calcitonin-gene related peptide (CGRP) or CGRP receptors in the treatment of migraine raised concerns on the possible risks associated to the long-term inhibition of CGRP physiological functions. In this proof-of-concept study, we have measured the circulating levels of CGRP in 7 patients with high-frequency episodic migraine receiving the anti-CGRP receptor mAb erenumab for at least 6 months, to test the hypothesis that long-term blockade of CGRP receptors induces an increase in systemic CGRP levels via a classical up-regulation mechanism.Plasma CGRP levels were measured by a validated radioimmunoassay at baseline, and after 1 and 6 months of treatment with erenumab, 70 mg given sc every 4 weeks.We found (data expressed as the means ± SD) 38.34 ± 30.74 pg CGRP/ml of plasma at baseline, 38.19 ± 29.23 pg/ml after 1 month and 53.89 ± 28.03 pg/ml after 6 months of treatment. Thus, the average increase in plasma CGRP levels after 6 months of treatment was about + 40% compared to both baseline and 1-month treatments; such difference was not statistically significant because of high SD values in all groups.