Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions

80% of arable land in Africa has low soil fertility and suffers from physical soil problems. Additionally, significant amounts of nutrients are lost every year due to unsustainable soil management practices. This is partially the result of insufficient use of soil management knowledge. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was established in 2008. Over the period 2008–2014, the AfSIS project compiled two point data sets: the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site database. These data sets contain over 28 thousand sampling locations and represent the most comprehensive soil sample data sets of the African continent to date. Utilizing these point data sets in combination with a large number of covariates, we have generated a series of spatial predictions of soil properties relevant to the agricultural management—organic carbon, pH, sand, silt and clay fractions, bulk density, cation-exchange capacity, total nitrogen, exchangeable acidity, Al content and exchangeable bases (Ca, K, Mg, Na). We specifically investigate differences between two predictive approaches: random forests and linear regression. Results of 5-fold cross-validation demonstrate that the random forests algorithm consistently outperforms the linear regression algorithm, with average decreases of 15–75% in Root Mean Squared Error (RMSE) across soil properties and depths. Fitting and running random forests models takes an order of magnitude more time and the modelling success is sensitive to artifacts in the input data, but as long as quality-controlled point data are provided, an increase in soil mapping accuracy can be expected. Results also indicate that globally predicted soil classes (USDA Soil Taxonomy, especially Alfisols and Mollisols) help improve continental scale soil property mapping, and are among the most important predictors. This indicates a promising potential for transferring pedological knowledge from data rich countries to countries with limited soil data.     

Systems pathology analysis identifies neurodegenerative nature of age‐related vitreoretinal interface diseases

Aging is a phenomenon that is associated with profound medical implications. Idiopathic epiretinal membrane (iEMR) and macular hole (MH) are the major vision‐threatening vitreoretinal diseases affecting millions of aging people globally, making these conditions an important public health issue. iERM is characterized by fibrous tissue developing on the surface of the macula, which leads to biomechanical and biochemical macular damage. MH is a small breakage in the macula and is associated with many ocular conditions. Although several individual factors and pathways are suggested, a systems pathology level understanding of the molecular mechanisms underlying these disorders is lacking. Therefore, we performed mass spectrometry‐based label‐free quantitative proteomics analysis of the vitreous proteomes from patients with iERM and MH to identify the key proteins, as well as the multiple interconnected biochemical pathways, contributing to the development of these diseases. We identified a total of 1,014 unique proteins, many of which are linked to inflammation and the complement cascade, revealing the inflammation processes in retinal diseases. Additionally, we detected a profound difference in the proteomes of iEMR and MH compared to those of diabetic retinopathy with macular edema and rhegmatogenous retinal detachment. A large number of neuronal proteins were present at higher levels in the iERM and MH vitreous, including neuronal adhesion molecules, nervous system development proteins, and signaling molecules, pointing toward the important role of neurodegenerative component in the pathogenesis of age‐related vitreoretinal diseases. Despite them having marked similarities, several unique vitreous proteins were identified in both iERM and MH, from which candidate targets for new diagnostic and therapeutic approaches can be provided.     

Regulation of TLR2 Expression and Function in Human Airway Epithelial Cells

Toll-like receptor (TLR1–6) mRNAs are expressed in normal human bronchial epithelial cells with higher basal levels of TLR3. TLR2 mRNA and plasma membrane protein expression was enhanced by pretreatment with Poly IC, a synthetic double-stranded RNA (dsRNA) known to activate TLR3. Poly IC also enhanced mRNA expression of adaptor molecules (MyD88 and TIRAP) and coreceptors (Dectin-1 and CD14) involved in TLR2 signaling. Additionally, mRNA expression of TLR3 and dsRNA-sensing proteins MDA5 and RIG-I increased following Poly IC treatment. In contrast, basal mRNA expression of TLR5 and TLR2 coreceptor CD36 was reduced by 77% and 62%, respectively. ELISA of apical and basolateral solutions from Poly IC-stimulated monolayers revealed significantly higher levels of IL-6 and GM-CSF compared with the TLR2 ligand PAM₃CSK₄. Pretreatment with anti-TLR2 blocking antibody inhibited the PAM₃CSK₄-induced increase in IL-6 secretion after Poly IC exposure. An increase in IL-6 secretion was also observed in cells stimulated with Alternaria extract after pretreatment with Poly IC. However, IL-6 secretion was not stimulated by zymosan or lipothechoic acid (LTA). These data demonstrated that upregulation of TLR2 following exposure to dsRNA enhances functional responses of the airway epithelium to certain (PAM₃CSK₄), but not all (zymosan, LTA) TLR2 ligands and that this is likely due to differences in coreceptor expression.     

TLR3 activation evokes IL-6 secretion, autocrine regulation of Stat3 signaling and TLR2 expression in human bronchial epithelial cells

Human bronchial epithelial cells exposed to synthetic double-stranded RNA (poly I:C) exhibited increased IL-6 and RANTES secretion and TLR2 expression that was inhibited following TLR3 silencing. Increased NF-κB and Stat3 phosphorylation were detected after poly I:C exposure and pretreatment with neutralizing antibody targeting IL-6 receptor α (IL-6Rα -nAb) or blocking Jak2 and Stat3 activity inhibited Stat3 phosphorylation. TLR2 up-regulation by poly I:C was also reduced by IL-6Rα-nAb and inhibitors of Jak2, Stat3 and NF-κB phosphorylation, whereas RANTES secretion was unaffected, but abolished following NF-κB inhibition. Treatment with exogenous IL-6 failed to increase TLR2. These findings demonstrate that TLR3 activation differentially regulates TLR expression through autocrine signaling involving IL-6 secretion, IL-6Rα activation and subsequent phosphorylation of Stat3. The results also indicate that NF-κB and Stat3 are required for TLR3-dependent up-regulation of TLR2 and that its delayed expression was due to a requirement for IL-6-dependent Stat3 activation.     

Diversity of medium and large mammals in the Loka Abaya National Park,southern Ethiopia

We evaluated the richness, diversity, and composition of the medium and large mammal community in the Loka Abaya National Park (LANP), southern Ethiopia, and how these parameters differ among four habitat types: wooded grassland, riverine forest, hilly scrubland and wetland, and between seasons. We recorded a total of 2,573 individual animals of 28 medium and large mammal species in the park. This included three globally threatened species: the endangered African wild dog (Lycaon pictus), the vulnerable Leopard (Panthera pardus), and Hippopotamus (Hippopothamus amphibius). Season had little effect on species richness, diversity, and composition both across and within habitat types. However, species richness across seasons was significantly different among the four habitat types, in the declining order of the following: wooded grassland > riverine forest > hilly scrubland > wetland. The strongest similarity in species composition, both across and within seasons, was found between wooded grassland and riverine forest. In terms of relative abundance, mammal assemblage of the wooded grassland and wetland habitats had more evenly distributed number of species with different relative abundance categories. Overall, Anubis Baboon (Papio anubis), Grivet Monkey (Chlorocebus aethiops), and Greater Kudu (Tragelephus strepsiceros) were the three most abundant species across habitat types. In conclusion, findings of our study reveal that LANP plays an important role in Ethiopia's mammal conservation. Our findings will serve as baseline information for managers of the park to make effective conservation decisions and as a baseline for researchers wishing to conduct related ecological studies.