Historical data reveal power-law dispersal patterns of invasive aquatic species

Understanding how invasive species spread is of particular concern in the current era of globalisation and rapid environmental change. The occurrence of super-diffusive movements within the context of Lévy flights has been discussed with respect to particle physics, human movements, microzooplankton, disease spread in global epidemiology and animal foraging behaviour. Super-diffusive movements provide a theoretical explanation for the rapid spread of organisms and disease, but their applicability to empirical data on the historic spread of organisms has rarely been tested. This study focuses on the role of long-distance dispersal in the invasion dynamics of aquatic invasive species across three contrasting areas and spatial scales: open ocean (north-east Atlantic), enclosed sea (Mediterranean) and an island environment (Ireland). Study species included five freshwater plant species, Azolla filiculoides, Elodea canadensis, Lagarosiphon major, Elodea nuttallii and Lemna minuta; and ten species of marine algae, Asparagopsis armata, Antithamnionella elegans, Antithamnionella ternifolia, Codium fragile, Colpomenia peregrina, Caulerpa taxifolia, Dasysiphonia sp., Sargassum muticum, Undaria pinnatifida and Womersleyella setacea. A simulation model is constructed to show the validity of using historical data to reconstruct dispersal kernels. Lévy movement patterns similar to those previously observed in humans and wild animals are evident in the re-constructed dispersal pattern of invasive aquatic species. Such patterns may be widespread among invasive species and could be exacerbated by further development of trade networks, human travel and environmental change. These findings have implications for our ability to predict and manage future invasions, and improve our understanding of the potential for spread of organisms including infectious diseases, plant pests and genetically modified organisms.

Small RNAs from plants, bacteria and fungi within the order Hypocreales are ubiquitous in human plasma

Background

The human microbiome plays a significant role in maintaining normal physiology. Changes in its composition have been associated with bowel disease, metabolic disorders and atherosclerosis. Sequences of microbial origin have been observed within small RNA sequencing data obtained from blood samples. The aim of this study was to characterise the microbiome from which these sequences are derived.

Abundant non-human small RNA sequences were identified in plasma and plasma exosomal samples. Assembly of these short sequences into longer contigs was the pivotal novel step in ascertaining their origin by BLAST searches. Most reads mapped to rRNA sequences. The taxonomic profiles of the microbes detected were very consistent between individuals but distinct from microbiomes reported at other sites. The majority of bacterial reads were from the phylum Proteobacteria, whilst for 5 of 6 individuals over 90% of the more abundant fungal reads were from the phylum Ascomycota; of these over 90% were from the order Hypocreales. Many contigs were from plants, presumably of dietary origin.  In addition, extremely abundant small RNAs derived from human Y RNAs were detected.

A characteristic profile of a subset of the human microbiome can be obtained by sequencing small RNAs present in the blood. The source and functions of these molecules remain to be determined, but the specific profiles are likely to reflect health status. The potential to provide biomarkers of diet and for the diagnosis and prognosis of human disease is immense.

COD and NH4-N Estimation in the Inflow of Wastewater Treatment Plants using Machine Learning Techniques

The in-line measurement of COD and NH4-N in the WWTP inflow is crucial for the timely monitoring of biological wastewater treatment processes and for the development of advanced control strategies for optimized WWTP operation. As a direct measurement of COD and NH4-N requires expensive and high maintenance in-line probes or analyzers, an approach estimating COD and NH4-N based on standard and spectroscopic in-line inflow measurement systems using Machine Learning Techniques is presented in this paper. The results show that COD estimation using Radom Forest Regression with a normalized MSE of 0.3, which is sufficiently accurate for practical applications, can be achieved using only standard in-line measurements. In the case of NH4-N, a good estimation using Partial Least Squares Regression with a normalized MSE of 0.16 is only possible based on a combination of standard and spectroscopic in-line measurements. Furthermore, the comparison of regression and classification methods shows that both methods perform equally well in most cases.

Plants Fagonia cretica L. and Hedera nepalensis K. Koch contain natural compounds with potent dipeptidyl peptidase-4 (DPP-4) inhibitory activity

Ethnopharmacological relevance
The two plants investigated here (Fagonia cretica L. and Hedera nepalensis K. Koch) have been previously reported as natural folk medicines for the treatment of diabetes but until now no scientific investigation of potential anti-diabetic effects has been reported. 

Materials and methods
In vitro inhibitory effect of the two tested plants and their five isolated compounds on the dipeptidyl peptidase 4 (DPP-4) was studied for the assessment of anti-diabetic activity. 

Results
A crude extract of Fagonia cretica possessed good inhibitory activity (IC₅₀value: 38.1 μg/ml) which was also present in its n-hexane (FCN), ethyl acetate (FCE) or aqueous (FCA) fractions. A crude extract of Hedera nepalensis (HNC) possessed even higher inhibitory activity (IC₅₀value: 17.2 μg/ml) and this activity was largely retained when further fractionated in either ethyl acetate (HNE; IC₅₀: 34.4 μg/ml) or n-hexane (HNN; 34.2 μg/ml). Bioactivity guided isolation led to the identification of four known compounds (isolated for the first time) from Fagonia cretica: quinovic acid (1), quinovic acid-3β-O-β-d-glycopyranoside (2), quinovic acid-3β-O-β-d-glucopyranosyl-(28→1)-β-d-glucopyranosyl ester (3), and stigmasterol (4) all of which inhibited DPP-4 activity (IC₅₀: 30.7, 57.9, 23.5 and >100 μM, respectively). The fifth DPP-4 inhibitor, the triterpenoid lupeol (5) was identified in Hedera nepalensis (IC₅₀: 31.6 μM). 

Conclusion
The experimental study revealed that Fagonia cretica and Hedera nepalensis contain compounds with significant DPP-4 inhibitory activity which should be further investigated for their anti-diabetic potential.

Burkholderia cenocepacia Lipopolysaccharide Modification and Flagellin Glycosylation Affect Virulence but Not Innate Immune Recognition in Plants

Burkholderia cenocepacia causes opportunistic infections in plants, insects, animals, and humans, suggesting that “virulence” depends on the host and its innate susceptibility to infection. We hypothesized that modifications in key bacterial molecules recognized by the innate immune system modulate host responses to B. cenocepacia. Indeed, modification of lipo- polysaccharide (LPS) with 4-amino-4-deoxy-L-arabinose and flagellin glycosylation attenuates B. cenocepacia infection in Arabi- dopsis thaliana and Galleria mellonella insect larvae. However, B. cenocepacia LPS and flagellin triggered rapid bursts of nitric oxide and reactive oxygen species in A. thaliana leading to activation of the PR-1 defense gene. These responses were drastically reduced in plants with fls2 (flagellin FLS2 host receptor kinase), Atnoa1 (nitric oxide-associated protein 1), and dnd1-1 (reduced production of nitric oxide) null mutations. Together, our results indicate that LPS modification and flagellin glycosylation do not affect recognition by plant receptors but are required for bacteria to establish overt infection.