EUNIS Habitat Classification: Expert system, characteristic species combinations and distribution maps of European habitats

Aim: The EUNIS Habitat Classification is a widely used reference framework for European habitat types (habitats), but it lacks formal definitions of individual habitats that would enable their unequivocal identification. Our goal was to develop a tool for assigning vegetation‐plot records to the habitats of the EUNIS system, use it to classify a European vegetation‐plot database, and compile statistically‐derived characteristic species combinations and distribution maps for these habitats. Location: Europe. Methods: We developed the classification expert system EUNIS‐ESy, which contains definitions of individual EUNIS habitats based on their species composition and geographic location. Each habitat was formally defined as a formula in a computer language combining algebraic and set‐theoretic concepts with formal logical operators. We applied this expert system to classify 1,261,373 vegetation plots from the European Vegetation Archive (EVA) and other databases. Then we determined diagnostic, constant and dominant species for each habitat by calculating species‐to‐habitat fidelity and constancy (occurrence frequency) in the classified data set. Finally, we mapped the plot locations for each habitat. Results: Formal definitions were developed for 199 habitats at Level 3 of the EUNIS hierarchy, including 25 coastal, 18 wetland, 55 grassland, 43 shrubland, 46 forest and 12 man‐made habitats. The expert system classified 1,125,121 vegetation plots to these habitat groups and 73,188 to other habitats, while 63,064 plots remained unclassified or were classified to more than one habitat. Data on each habitat were summarized in factsheets containing habitat description, distribution map, corresponding syntaxa and characteristic species combination. Conclusions: EUNIS habitats were characterized for the first time in terms of their species composition and distribution, based on a classification of a European database of vegetation plots using the newly developed electronic expert system EUNIS‐ESy. The data provided and the expert system have considerable potential for future use in European nature conservation planning, monitoring and assessment

Cysteine Cathepsin Protease Inhibition: An update on its Diagnostic, Prognostic and Therapeutic Potential in Cancer

In keeping with recent developments in basic research; the importance of the Cathepsins as targets in cancer therapy have taken on increasing importance and given rise to a number of key areas of interest in the clinical setting. In keeping with driving basic research in this area in a translational direction; recent findings have given rise to a number of exciting developments in the areas of cancer diagnosis; prognosis and therapeutic development. As a fast-moving area of research; the focus of this review brings together the latest findings and highlights the translational significance of these developments

Integrative p53, micro-RNA and Cathepsin Protease Co-Regulatory Expression Networks in Cancer

As the direct regulatory role of p53 and some of its isoform proteins are becoming established in modulating gene expression in cancer research, another aspect of this mode of gene regulation that has captured significant interest over the years is the mechanistic interplay between p53 and micro-RNA transcriptional regulation. The input of this into modulating gene expression for some of the cathepsin family members has been viewed as carrying noticeable importance based on their biological effects during normal cellular homeostasis and cancer progression. While this area is still in its infancy in relation to general cathepsin gene regulation, we review the current p53-regulated micro-RNAs that are generating significant interest through their regulation of cathepsin proteases, thereby strengthening the link between activated p53 forms and cathepsin gene regulation. Additionally, we extend our understanding of this developing relationship to how such micro-RNAs are being utilized as diagnostic or prognostic tools and highlight their future uses in conjunction with cathepsin gene expression as potential biomarkers within a clinical setting

BH3-mimetics:recent developments in cancer therapy

Abstract The hopeful outcomes from 30 years of research in BH3-mimetics have indeed served a number of solid paradigms for targeting intermediates from the apoptosis pathway in a variety of diseased states. Not only have such rational approaches in drug design yielded several key therapeutics, such outputs have also offered insights into the integrated mechanistic aspects of basic and clinical research at the genetics level for the future. In no other area of medical research have the effects of such work been felt, than in cancer research, through targeting the BAX-Bcl-2 protein-protein interactions. With these promising outputs in mind, several mimetics, and their potential therapeutic applications, have also been developed for several other pathological conditions, such as cardiovascular disease and tissue fibrosis, thus highlighting the universal importance of the intrinsic arm of the apoptosis pathway and its input to general tissue homeostasis. Considering such recent developments, and in a field that has generated so much scientific interest, we take stock of how the broadening area of BH3-mimetics has developed and diversified, with a focus on their uses in single and combined cancer treatment regimens and recently explored therapeutic delivery methods that may aid the development of future therapeutics of this nature

Target Metabolome Profiling-Based Machine Learning as a Diagnostic Approach for Cardiovascular Diseases in Adults

Metabolomics is a promising technology for the application of translational medicine to cardiovascular risk. Here, we applied a liquid chromatography/tandem mass spectrometry approach to explore the associations between plasma concentrations of amino acids, methylarginines, acylcarnitines, and tryptophan catabolism metabolites and cardiometabolic risk factors in patients diagnosed with arterial hypertension (HTA) (n = 61), coronary artery disease (CAD) (n = 48), and non-cardiovascular disease (CVD) individuals (n = 27). In total, almost all significantly different acylcarnitines, amino acids, methylarginines, and intermediates of the kynurenic and indolic tryptophan conversion pathways presented increased (p< 0.05) in concentration levels during the progression of CVD, indicating an association of inflammation, mitochondrial imbalance, and oxidative stress with early stages of CVD. Additionally, the random forest algorithm was found to have the highest prediction power in multiclass and binary classification patients with CAD, HTA, and non-CVD individuals and globally between CVD and non-CVD individuals (accuracy equal to 0.80 and 0.91, respectively). Thus, the present study provided a complex approach for the risk stratification of patients with CAD, patients with HTA, and non-CVD individuals using targeted metabolomics profiling

sPlot:a new tool for global vegetation analyses

Abstract Aims: Vegetation‐plot records provide information on the presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community‐weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale