A large non-parasitic population of Savalia savaglia (Bertoloni, 1819) in the Boka Kotorska Bay (Montenegro).

The golden coral Savalia savaglia is a long-living ecosystem engineer of Mediterranean circalittoral assemblages, able to induce necrosis of gorgonians' and black corals' coenenchyme and grow on their cleaned organic skeleton. Despite its rarity, in Boka Kotorska Bay (Montenegro) a shallow population of more than 1000 colonies was recorded close to underwater freshwater springs, which create very peculiar environmental conditions. In this context, the species was extremely abundant at two sites, while gorgonians were rare. The abundance and size of S. savaglia colonies and the diversity of the entire benthic assemblage were investigated by photographic sampling in a depth range of 0-35 m. Several living fragments of S. savaglia spread on the sea floor and small settled colonies (< 5 cm high) suggested a high incidence of asexual reproduction and a non-parasitic behaviour of this population. This was confirmed by studying thin sections of the basal portion of the trunk where the central core, generally represented by the remains of the gorgonian host skeleton, was lacking. The S. savaglia population of Boka Kotorska Bay forms the unique Mediterranean assemblage of the species deserving the definition of animal forest. Recently, temporary mitigation measures for anthropogenic impact were issued by the Government of Montenegro. Nevertheless, due to the importance of the sites the establishment of a permanent Marine Protected Area is strongly recommended.

Xylanase Production by Solid-State Fermentation for the Extraction of Xylooligosaccharides from Soybean Hulls§.

Research background: The development of a novel process for the production of xylooligosaccharides (XOS) based on the 4R concept is made possible by the integration of numerous techniques, especially enzymatic modification together with the physical pretreatment of renewable materials. This study aims to integrate the use of agricultural wastes for the production of xylanase by a new strain of Penicillium sp. and value-added products, XOS. Experimental approach: For the production of xylanase, a solid-state fermentation was performed using wheat bran as substrate. To obtain the most active crude extract of xylanase, the time frame of cultivation was first adjusted. Then, the downstream process for xylanase purification was developed by combining different membrane separation units with size exclusion chromatography. Further characterisation included determination of the optimal pH and temperature, determination of the molecular mass of the purified xylanase and analysis of kinetic parameters. Subsequently, the hydrolytic ability of the partially purified xylanase in the hydrolysis of alkali-extracted hemicellulose from soybean hulls was investigated. Results and conclusions: Our results show that Penicillium rubens produced extracellular xylanase at a yield of 21 U/g during solid-state fermentation. Using two ultrafiltration membranes of 10 and 3 kDa in combination with size exclusion chromatography, a yield of 49 % and 13-fold purification of xylanase was achieved. The purified xylanase (35 kDa) cleaved linear bonds ß-(1→4) in beechwood xylan at a maximum rate of 0.64 µmol/(min·mg) and a Michaelis constant of 44 mg/mL. At pH=6 and 45 °C, the purified xylanase showed its maximum activity. The xylanase produced showed a high ability to hydrolyse the hemicellulose fraction isolated from soybean hulls, as confirmed by thin-layer chromatography. In the hydrothermally pretreated hemicellulose hydrolysate, the content of XOS with different degrees of polymerisation was detected, while in the non-pretreated hemicellulose hydrolysate, the content of xylotriose and glucose was confirmed. Novelty and scientific contribution: Future research focusing on the creation of new enzymatic pathways for use in processes to convert renewable materials into value-added products can draw on our findings.

Age, Sex, Body Mass Index, Diet and Menopause Related Metabolites in a Large Homogeneous Alpine Cohort.

Metabolomics in human serum samples provide a snapshot of the current metabolic state of an individuum. Metabolite concentrations are influenced by both genetic and environmental factors. Concentrations of certain metabolites can further depend on age, sex, menopause, and diet of study participants. A better understanding of these relationships is pivotal for the planning of metabolomics studies involving human subjects and interpretation of their results. We generated one of the largest single-site targeted metabolomics data sets consisting of 175 quantified metabolites in 6872 study participants. We identified metabolites significantly associated with age, sex, body mass index, diet, and menopausal status. While most of our results agree with previous large-scale studies, we also found novel associations including serotonin as a sex and BMI-related metabolite and sarcosine and C2 carnitine showing significantly higher concentrations in post-menopausal women. Finally, we observed strong associations between higher consumption of food items and certain metabolites, mostly phosphatidylcholines and lysophosphatidylcholines. Most, and the strongest, relationships were found for habitual meat intake while no significant relationships were found for most fruits, vegetables, and grain products. Summarizing, our results reconfirm findings from previous population-based studies on an independent cohort. Together, these findings will ultimately enable the consolidation of sets of metabolites which are related to age, sex, BMI, and menopause as well as to participants' diet.

Genetic and Metabolic Determinants of Atrial Fibrillation in a General Population Sample: The CHRIS Study.

Atrial fibrillation (AF) is a supraventricular arrhythmia deriving from uncoordinated electrical activation with considerable associated morbidity and mortality. To expand the limited understanding of AF biological mechanisms, we performed two screenings, investigating the genetic and metabolic determinants of AF in the Cooperative Health Research in South Tyrol study. We found 110 AF cases out of 10,509 general population individuals. A genome-wide association scan (GWAS) identified two novel loci (p-value < 5 × 10-8) around SNPs rs745582874, next to gene PBX1, and rs768476991, within gene PCCA, with genotype calling confirmed by Sanger sequencing. Risk alleles at both SNPs were enriched in a family detected through familial aggregation analysis of the phenotype, and both rare alleles co-segregated with AF. The metabolic screening of 175 metabolites, in a subset of individuals, revealed a 41% lower concentration of lysophosphatidylcholine lysoPC a C20:3 in AF cases compared to controls (p-adj = 0.005). The genetic findings, combined with previous evidence, indicate that the two identified GWAS loci may be considered novel genetic rare determinants for AF. Considering additionally the association of lysoPC a C20:3 with AF by metabolic screening, our results demonstrate the valuable contribution of the combined genomic and metabolomic approach in studying AF in large-scale population studies.

Detection of apple proliferation disease in Malus × domestica by near infrared reflectance analysis of leaves.

In this study near infrared spectroscopical analysis of dried and ground leaves was performed and combined with a multivariate data analysis to distinguish 'Candidatus Phytoplasma mali' infected from non-infected apple trees (Malus × domestica). The bacterium is the causative agent of Apple Proliferation, one of the most threatening diseases in commercial apple growing regions. In a two-year study, leaves were sampled from three apple orchards, at different sampling events throughout the vegetation period. The spectral data were analyzed with a principal component analysis and classification models were developed. The model performance for the differentiation of Apple Proliferation diseased from non-infected trees increased throughout the vegetation period and gained best results in autumn. Even with asymptomatic leaves from infected trees a correct classification was possible indicating that the spectral-based method provides reliable results even if samples without visible symptoms are analyzed. The wavelength regions that contributed to the differentiation of infected and non-infected trees could be mainly assigned to a reduction of carbohydrates and N-containing organic compounds. Wet chemical analyses confirmed that N-containing compounds are reduced in leaves from infected trees. The results of our study provide a valuable indication that spectral analysis is a promising technique for Apple Proliferation detection in future smart farming approaches.

Aroma Investigation of New and Standard Apple Varieties Grown at Two Altitudes Using Gas Chromatography-Mass Spectrometry Combined with Sensory Analysis.

The aromatic profile of apples constitutes important information for the characterization and description of local products. Apple flavor is determined by perception in mouth and aroma; while the first is mainly defined by sugars and organic acids, aroma is a complex mixture of many volatile organic compounds (VOCs) whose composition is often specific to the variety. Headspace-solid phase microextraction gas chromatography coupled with mass spectrometry (HS-SPME-GC-MS) allows for the detection of detailed information of volatile constituents. In this study, eleven apple varieties (Braeburn, Fuji, Gala, Golden Delicious, Coop 39-Crimson Crisp®, Dalinette-Choupette®, Fujion, CIV323-Isaaq®, Coop43-Juliet®, SQ159-Natyra®, UEB32642-Opal®) grown in two pedoclimatic locations at different altitudes in South Tyrol (Italy) (ca. 225 m and ca. 650 m a.s.l.) were investigated. Thirty-eight VOCs were identified and combined with sensory analysis results (from 11 trained panelist) to characterize the aroma of new and standard apple varieties with a special focus on pedoclimatic location differences. The study shows strong diversification of the varieties based on their VOC profiles and sensory attributes, as expected. Moreover, investigating how the pedoclimatic location at different altitudes can influence the apple aroma profile, we identified twelve VOCs involved in these differences and provided a deeper investigation on how different altitudes can influence the apple aroma composition and perceptions combining the analytical and sensory parameters.

Consensus Clustering of temporal profiles for the identification of metabolic markers of pre-diabetes in childhood (EarlyBird 73).

In longitudinal clinical studies, methodologies available for the analysis of multivariate data with multivariate methods are relatively limited. Here, we present Consensus Clustering (CClust) a new computational method based on clustering of time profiles and posterior identification of correlation between clusters and predictors. Subjects are first clustered in groups according to a response variable temporal profile, using a robust consensus-based strategy. To discover which of the remaining variables are associated with the resulting groups, a non-parametric hypothesis test is performed between groups at every time point, and then the results are aggregated according to the Fisher method. Our approach is tested through its application to the EarlyBird cohort database, which contains temporal variations of clinical, metabolic, and anthropometric profiles in a population of 150 children followed-up annually from age 5 to age 16. Our results show that our consensus-based method is able to overcome the problem of the approach-dependent results produced by current clustering algorithms, producing groups defined according to Insulin Resistance (IR) and biological age (Tanner Score). Moreover, it provides meaningful biological results confirmed by hypothesis testing with most of the main clinical variables. These results position CClust as a valid alternative for the analysis of multivariate longitudinal data.

Metabolic Differences between Dogs of Different Body Sizes.

INTRODUCTION: The domesticated dog, Canis lupus familiaris, has been selectively bred to produce extreme diversity in phenotype and genotype. Dogs have an immense diversity in weight and height. Specific differences in metabolism have not been characterized in small dogs as compared to larger dogs. OBJECTIVES: This study aims to identify metabolic, clinical, and microbiota differences between small and larger dogs. METHODS: Gas chromatography/mass spectrometry, liquid chromatography/tandem mass spectrometry, clinical chemistry analysis, dual-energy X-ray absorptiometry, and 16S pyrosequencing were used to characterize blood metabolic, clinical, and fecal microbiome systems, respectively. Eighty-three canines from seven different breeds, fed the same kibble diet for 5 weeks, were used in the study. RESULTS: 449 metabolites, 16 clinical parameters, and 6 bacteria (at the genus level) were significantly different between small and larger dogs. Hierarchical clustering of the metabolites yielded 8 modules associated with small dog size. CONCLUSION: Small dogs had a lower antioxidant status and differences in circulating amino acids. Some of the amino acid differences could be attributed to differences in microflora. Additionally, analysis of small dog metabolites and clinical parameters reflected a network which strongly associates with kidney function.

Mapping the Atomistic Structure of Graded Core/Shell Colloidal Nanocrystals.

Engineering the compositional gradient for core/shell semiconductor nanocrystals improves their optical properties. To date, however, the structure of graded core/shell nanocrystal emitters has only been qualitatively described. In this paper, we demonstrate an approach to quantify nanocrystal structure, selecting graded Ag-In-Se/ZnSe core/shell nanocrystals as a proof-of-concept material. A combination of multi-energy small-angle X-ray scattering and electron microscopy techniques enables us to establish the radial distribution of ZnSe with sub-nanometer resolution. Using ab initio shape-retrieval analysis of X-ray scattering spectra, we further determine the average shape of nanocrystals. These results allow us to generate three-dimensional, atomistic reconstructions of graded core/shell nanocrystals. We use these reconstructions to calculate solid-state Zn diffusion in the Ag-In-Se nanocrystals and the lattice mismatch between nanocrystal monolayers. Finally, we apply these findings to propose design rules for optimal shell structure and record-luminescent core/shell nanocrystals.

Climatic and geographical dependence of the H, C and O stable isotope ratios of Italian wine.

In this study, we investigated the relationship between (D/H)1, (D/H)2 and δ(13)C of ethanol and δ(18)O of water in wine, and variables describing the climate and the geography of the production area, using exploratory visualisation tools, regression analysis and linear modelling. For the first time, a large amount of data (around 4000 wine samples collected over 11 years in Italy) and all the official isotopic parameters, as well as a large number of significant climatic and geographical descriptors (date of harvest, latitude, longitude, elevation, distance from the sea, amount of precipitation, maximum daily temperature, minimum daily temperature, mean daily temperature, δ(18)O and δ(2)H of precipitation) were considered. δ(18)O, followed by (D/H)1, was shown to have the strongest relationship with climate and location. The dominant variables were latitude, with a negative relationship, δ(18)O and δ(2)H of precipitation and temperature, both with positive relationships. The identified correlations and models could be used to predict the isotopic composition of authentic wines, offering increased possibilities for detecting fraud and mislabelling.