Polymorphisms in melatonin synthesis pathways: possible influences on depression

Background

It has been reported that rs4446909, a single nucleotide polymorphism (SNP) in the promoter of acetylserotonin methyltransferase (ASMT), influences the expression of the ASMT enzyme. The common G allele is associated with lower ASMT activity, and therefore, diminishes conversion of N-acetylserotonin to melatonin. The G allele was associated with recurrent depressive disorder in a Polish group. ASMT might also affect bipolar relapse, given evidence that N-acetylserotonin might stimulate TRKB receptors, and TRKB may influence mood relapse in bipolar disorder. Additionally, arylalkylamine N-acetyltransferase (AANAT) polymorphisms have been reported associated with depression, perhaps through their influence upon N-acetylserotonin or melatonin synthesis.

Results

To replicate and further explore these ideas, rs4446909 was genotyped in four research groups, as part of a panel of 610 SNPs surveyed by an Illumina Golden Gate assay. In 768 cases with delayed sleep phase disorder or matched controls, rs4446909 was indeed associated with the depressive symptoms on a self-report scale (P = 0.01, R² = 0.007). However, there was no significant association of rs4446909 with self-reported depression in a sleep clinic patient group or with two groups of elderly men and women from multicenter studies, nor was the response to lithium treatment associated with rs4446909 in bipolar patients. No associations of two AANAT SNPs with depression were found.

Conclusions

The evidence did not support a strong influence of rs4446909 upon mood, but the partial replication may be consistent with a modest effect. It is possible that larger or younger subject groups with improved phenotype ascertainment might demonstrate more persuasive replication.     

Screening of quinalphos,trifluralin and dichlorvos residues in fresh water of aquaculture systems in Mekong Delta,Vietnam

To develop an easy and reliable method for detecting pesticides and their residues in the Mekong Delta, a GC‐MS analytical method was developed and validated according to European guidelines (SANTE/11945/2015) for the determination of residues of three pesticides (quinalphos, trifluralin and dichlorvos) in water. The limit of detection (LOD) and the limit of quantification (LOQ) were 0.002 and 0.007 μg/L, respectively, for quinalphos and trifluralin, and 0.016 and 0.053 μg/L, respectively, for dichlorvos and quinalphos. The repeatability, the within‐laboratory reproducibility as well as the trueness met the European criteria. The recovery rate ranged between 72% (for dichlorvos and quinalphos) and 82% (for trifluralin). The developed method was then applied for the analysis of 33 water samples, collected in April 2013, at the beginning of the rainy season in the Mekong Delta in Vietnam. Thirteen samples were from rice field, 10 were collected from cat fish ponds and from red tilapia cages. Results showed that only 9% of total water samples analysed contained residues of pesticides, but only in water from rice fish systems. From the 13 samples taken in these systems, quinalphos was detected in three samples. The other two pesticides were not detected. A comparison between analytical results obtained from GC‐MS and an alternative method, that is GC‐ECD indicated that GC‐ECD is less sensitive than GC‐MS, with LOQ ranging from 0.37 to 1.18 (depending on the pesticide). However, for samples with concentrations above these LOQ, no significant difference was observed between the results obtained from the two analytical methodologies.     

Environmental variability controls recruitment but with different drivers among spawning components in Gulf of St. Lawrence herring stocks

The factors affecting herring recruitment are still poorly understood, complicating the prediction of stock dynamics and the choice of operational management strategies. We investigated effects of intrinsic (SSB) and extrinsic factors (physical and biological environments, including competition and predation) on recruitment of the spring and fall spawning components of each of the two herring stocks occurring in the Gulf of the St. Lawrence between 1971 and 2014. Effects of potential explanatory factors on recruit (age 2) abundance were tested using Generalized Additive Models. Model fit was significantly improved by incorporating both physical and biological environmental variability, but effects of herring SSB and predation were not significant. Indices of zooplankton abundance and phenology explained more variance in recruitment than physical indices. Our results emphasize the dominance of bottom‐up processes over SSB in the regulation of herring recruitment. Environmental variability did not seem to act uniformly on the recruitment of either stock or their respective spawning components. A long‐term trend of decreasing recruitment in spring spawners was associated with a long‐term decline in abundance of cold water copepods. In fall spawners, optimal recruitment was dependent on warmer environmental conditions combined with an adequate supply (species composition and phenology) of zooplankton. These results provide the first empirical evidence that spring and fall spawning herring are adapted to contrasting environmental conditions and shed light on the potential mechanisms linking herring recruitment to key zooplankton community characteristics and phenology. Management strategies can be improved by incorporating this new knowledge on environmental drivers of herring recruitment.     

Genetic progress of upland rice (Oryza sativa L.) lines for disease resistance

The rice crop is affected by diseases throughout its cycle, impacting negatively on grain yield and quality. The control of the disease impact can be accomplished via crop breeding, using highly multiple resistant genotypes. This study aimed to evaluate the efficiency of multiple-character and specific selection of multiple resistance to major culture-associated diseases (neck blast, leaf scald and grain discoloration) in rice lines of the Upland Rice Genetic Breeding Program. The experiments were conducted in 35 sites during 12 agricultural years, where 124 lines were evaluated for the severity of fungal diseases, under natural field conditions. Multiple parameters were calculated based on the diseases´ scores: genetic, phenotypic and environmental variances, heritability, selection gain, renewal rate, and genetic and renewal progress. Genetic variance for the disease resistance was identified in the population, and the selection gain for multiple-character selection was of 3.16 year⁻¹ throughout the breeding process with a renewal rate of over 35%. The programme has showed efficiency in selecting multiple resistant genotypes to the mentioned diseases, highlighting genotypes with high potential for market release.     

Evaluation of plasma inflammatory cytokine concentrations in racing sled dogs

In human athletes significant changes in cytokine concentrations secondary to exercise have been observed. This prospective study evaluated the effect of a multi-day stage sled dog race on plasma concentrations of monocyte chemoattractant protein-1 (MCP-1), tumor necrosis factor-alpha (TNF-α), interleukin-2 (IL-2), interleukin-6 (IL-6), interleukin-8 (IL-8), and interleukin-10 (IL-10). Samples from 20 dogs were harvested prior to and on days 2 and 8 of an 8-day race. Exercise resulted in significantly decreased TNF-α and IL-8 as well as increases of MCP-1, IL-6, and IL-10 concentrations (P-value between 0.01 and < 0.0001 for all parameters). The proportion of values for IL-2 that were below the detection limit increased from 40% on day 0 to 75% on day 2 and decreased on day 8 to 40% (P = 0.04). Racing sled dogs show cytokine-concentration changes that are different from those in humans.     

Determination of microbial biomass and fungal and bacterial distribution in cattle faeces

As an important component of organic fertilizers, animal faeces require methods for determining diet effects on their microbial quality to improve nutrient use efficiency in soil and to decrease gaseous greenhouse emissions to the environment. The objectives of the present study were (i) to apply the chloroform fumigation extraction (CFE) method for determining microbial biomass in cattle faeces, (ii) to determine the fungal cell-membrane component ergosterol, and (iii) to measure the cell-wall components fungal glucosamine and bacterial muramic acid as indices for the microbial community structure. Additionally, ergosterol and amino sugar data provide independent control values for the reliability of the microbial biomass range obtained by the CFE method. A variety of extractant solutions were tested for the CFE method to obtain stable extracts and reproducible microbial biomass C and N values, leading to the replacement of the original 0.5 M K₂SO₄ extractant for 0.05 M CuSO₄. The plausibility of the data was assessed in a 28-day incubation study at 25 °C with cattle faeces of one heifer, where microbial biomass C and N were repeatedly measured together with ergosterol. Here, the microbial biomass indices showed dynamic characteristics and possible shifts in the microbial community. In faeces of five different heifers, the mean microbial biomass C/N ratio was 5.6, the mean microbial biomass to organic C ratio was 2.2%, and the mean ergosterol to microbial biomass C ratio was 1.1‰. Ergosterol and amino sugar analysis revealed a significant contribution of fungi, with a percentage of more than 40% to the microbial community. All three methods are expected to be suitable tools for analysing the quality of cattle faeces.     

Modelling semi-natural habitat area on lowland farms in western Ireland

A significant policy objective is the need for protection of biodiversity not just within designated Natura 2000 sites, but also in areas that occur outside of these sites. However there is a lack of information on existing semi-natural habitat cover on EU farms, making it difficult to assess whether targets for halting the loss of agricultural biodiversity are being met. To achieve these targets, reliable yet easy-to-use methods are needed for accurately identifying priority areas for conservation actions and monitoring biodiversity on a large spatial scale.Remote sensing, farmland statistics and species data have been used in some EU countries to create maps to estimate the extent of semi-natural habitat cover but these are acknowledged as being too broad scale. In this study, we examined a method of fine-scale prediction of the spatial coverage of semi-natural habitats in lowland farms. A generalized additive model (GAM) was used to investigate the relationships between landscape and farm management variables and the lowland farmland habitat biodiversity on 32 farms outside of conservation designations, in a region of western Ireland. Semi-natural habitat cover on lowland farms could be predicted with a model using stocking density, soil diversity and river and stream length. It is proposed that this model could be used to predict the coverage of semi-natural habitats on farms in other regions of Ireland with similar land-use and landscape. A similar modelling approach could be adapted for application in other regions of Ireland and across Europe with different landscapes to predict semi-natural habitat coverage.