Effects of diet,habitat, and phylogeny on the fecal microbiome of wild African savanna (Loxodonta africana) and forest elephants (L. cyclotis)

The gut microbiome, or the community of microorganisms inhabiting the digestive tract, is often unique to its symbiont and, in many animal taxa, is highly influenced by host phylogeny and diet. In this study, we characterized the gut microbiome of the African savanna elephant (Loxodonta africana) and the African forest elephant (Loxodonta cyclotis), sister taxa separated by 2.6–5.6 million years of independent evolution. We examined the effect of host phylogeny on microbiome composition. Additionally, we examined the influence of habitat types (forest versus savanna) and diet types (crop‐raiding versus noncrop‐raiding) on the microbiome within L. africana. We found 58 bacterial orders, representing 16 phyla, across all African elephant samples. The most common phyla were Firmicutes, Proteobacteria, and Bacteroidetes. The microbiome of L. africana was dominated by Firmicutes, similar to other hindgut fermenters, while the microbiome of L. cyclotis was dominated by Proteobacteria, similar to more frugivorous species. Alpha diversity did not differ across species, habitat type, or diet, but beta diversity indicated that microbial communities differed significantly among species, diet types, and habitat types. Based on predicted KEGG metabolic pathways, we also found significant differences between species, but not habitat or diet, in amino acid metabolism, energy metabolism, and metabolism of terpenoids and polyketides. Understanding the digestive capabilities of these elephant species could aid in their captive management and ultimately their conservation.     

The K+ Channel KCa3.1 as a Novel Target for Idiopathic Pulmonary Fibrosis

Background

Idiopathic pulmonary fibrosis (IPF) is a common, progressive and invariably lethal interstitial lung disease with no effective therapy. We hypothesised that K_Ca3.1 K⁺ channel-dependent cell processes contribute to IPF pathophysiology.

Methods

K_Ca3.1 expression in primary human lung myofibroblasts was examined using RT-PCR, western blot, immunofluorescence and patch-clamp electrophysiology. The role of K_Ca3.1 channels in myofibroblast proliferation, wound healing, collagen secretion and contraction was examined using two specific and distinct K_Ca3.1 blockers (TRAM-34 and ICA-17043 [Senicapoc]).

Results

Both healthy non fibrotic control and IPF-derived human lung myofibroblasts expressed K_Ca3.1 channel mRNA and protein. K_Ca3.1 ion currents were elicited more frequently and were larger in IPF-derived myofibroblasts compared to controls. K_Ca3.1 currents were increased in myofibroblasts by TGFβ1 and basic FGF. K_Ca3.1 was expressed strongly in IPF tissue. K_Ca3.1 pharmacological blockade attenuated human myofibroblast proliferation, wound healing, collagen secretion and contractility in vitro, and this was associated with inhibition of TGFβ1-dependent increases in intracellular free Ca²⁺.

Conclusions

K_Ca3.1 activity promotes pro-fibrotic human lung myofibroblast function. Blocking K_Ca3.1 may offer a novel approach to treating IPF with the potential for rapid translation to the clinic.     

Visualizing the Topical Structure of the Medical Sciences: A Self-Organizing Map Approach

Background

We implement a high-resolution visualization of the medical knowledge domain using the self-organizing map (SOM) method, based on a corpus of over two million publications. While self-organizing maps have been used for document visualization for some time, (1) little is known about how to deal with truly large document collections in conjunction with a large number of SOM neurons, (2) post-training geometric and semiotic transformations of the SOM tend to be limited, and (3) no user studies have been conducted with domain experts to validate the utility and readability of the resulting visualizations. Our study makes key contributions to all of these issues.

Methodology

Documents extracted from Medline and Scopus are analyzed on the basis of indexer-assigned MeSH terms. Initial dimensionality is reduced to include only the top 10% most frequent terms and the resulting document vectors are then used to train a large SOM consisting of over 75,000 neurons. The resulting two-dimensional model of the high-dimensional input space is then transformed into a large-format map by using geographic information system (GIS) techniques and cartographic design principles. This map is then annotated and evaluated by ten experts stemming from the biomedical and other domains.

Conclusions

Study results demonstrate that it is possible to transform a very large document corpus into a map that is visually engaging and conceptually stimulating to subject experts from both inside and outside of the particular knowledge domain. The challenges of dealing with a truly large corpus come to the fore and require embracing parallelization and use of supercomputing resources to solve otherwise intractable computational tasks. Among the envisaged future efforts are the creation of a highly interactive interface and the elaboration of the notion of this map of medicine acting as a base map, onto which other knowledge artifacts could be overlaid.     

Population dynamics and the evolution of antifungal drug resistance in Candida albicans

Candida albicans is an important human fungal pathogen. Resistance to all major antifungal agents has been observed in clinical isolates of Candida spp. and is a major clinical challenge. The rise and expansion of drug-resistant mutants during exposure to antifungal agents occurs through a process of adaptive evolution, with potentially complex population dynamics. Understanding the population dynamics during the emergence of drug resistance is important for determining the fundamental principles of how fungal pathogens evolve for resistance. While few detailed reports that focus on the population dynamics of C. albicans currently exist, several important features on the population structure and adaptive landscape can be elucidated from existing evolutionary studies in in vivo and in vitro systems.