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.     

Nestboxes and immigration drive the growth of an urban Peregrine Falcon Falco peregrinus population

Drivers of wildlife population dynamics are generally numerous and interacting. Some of these drivers may impact demographic processes that are difficult to estimate, such as immigration into the focal population. Populations may furthermore be small and subject to demographic stochasticity. All of these factors contribute to blur the causal relationship between past management action and current population trends. The urban Peregrine Falcon Falco peregrinus population in Cape Town, South Africa, increased from three pairs in 1997 to 18 pairs in 2010. Nestboxes were installed over this period to manage the interface between new urban pairs of Falcons and the human users of colonized buildings, and incidentally to improve breeding success. We used integrated population models (IPMs) formally to combine information from a capture–mark–recapture study, monitoring of reproductive success and counts of population size. As all local demographic processes were directly observed, the IPM approach also allowed us to estimate immigration by difference. The provision of nestboxes, as a possible stimulant of population growth, improved breeding success and accounted for an estimated 3–26% of the population increase. The most important driver of growth, however, was immigration. Despite low sample sizes, the IPM approach allowed us to obtain relatively precise estimates of the population‐level impact of nestbox deployment. The goal of conservation interventions is often to increase population size, so the effectiveness of such interventions should ideally be assessed at the population level. IPMs are powerful tools in this context for combining demographic information that may be limited due to small population size or practical constraints on monitoring. Our study quantitatively documented both the immigration process that led to growth of a small population and the effect of a management action that helped the process.     

Deletion of the mammalian INDY homolog mimics aspects of dietary restriction and protects against adiposity and insulin resistance in mice

Reduced expression of the Indy (I'm Not Dead, Yet) gene in D.?melanogaster and its homolog in C.?elegans prolongs life span and in D.?melanogaster augments mitochondrial biogenesis in a manner akin to caloric restriction. However, the cellular mechanism by which Indy does this is unknown. Here, we report on the knockout mouse model of the mammalian Indy (mIndy) homolog, SLC13A5. Deletion of mIndy in mice (mINDY(-/-) mice) reduces hepatocellular ATP/ADP ratio, activates hepatic AMPK, induces PGC-1α, inhibits ACC-2, and reduces SREBP-1c levels. This signaling network promotes hepatic mitochondrial biogenesis, lipid oxidation, and energy expenditure and attenuates hepatic de novo lipogenesis. Together, these traits protect mINDY(-/-) mice from the adiposity and insulin resistance that evolve with high-fat feeding and aging. Our studies demonstrate a profound effect of mIndy on mammalian energy metabolism and suggest that mINDY might be a therapeutic target for the treatment of obesity and type 2 diabetes.     

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.     

The microenvironment of naked mole‐rat burrows in East Africa

Naked mole‐rats (Heterocephalus glaber) can be extremely long‐lived and are resistant to cancer. Hence, they have been proposed as a model organism for delayed ageing. Adaptation to a constant hypoxic and hypercapnic environment has been suggested as reason for their apparent ability to tolerate oxidative stress. Nevertheless, little is known about the natural habitat to which the species evolved. Naked mole‐rat burrow environments were assessed in Ethiopia and Kenya. Despite reported thermolability of naked mole‐rats, skin temperature upon capture varied (23.7–35.4°C), mostly within the species’ thermoneutral zone, demonstrating their ability to maintain homoiothermy even under wide fluctuations of burrow temperature (24.6–48.8°C) and humidity (31.2%–92.8%), which are far greater than previously reported. Burrow temperature regularly alternates during the daytime and night‐time, driving convective currents that circulate air in the tunnels. Consequently, concentrations of CO₂ and O₂ in burrows only slightly deviated from surface atmosphere. This contradicts the assumption of constant hypoxia/hypercapnia in subterranean burrows. In addition to diffusion, animal movement and occasional wind‐driven ventilation, our data support the temperature‐driven convective model of circulation. The naked mole‐rat burrow is a relatively normoxic subterranean microenvironment with considerable fluctuations in temperature and humidity.     

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.     

Integrated population modeling reveals the impact of climate on the survival of juvenile emperor penguins

Early‐life demographic traits are poorly known, impeding our understanding of population processes and sensitivity to climate change. Survival of immature individuals is a critical component of population dynamics and recruitment in particular. However, obtaining reliable estimates of juvenile survival (i.e., from independence to first year) remains challenging, as immatures are often difficult to observe and to monitor individually in the field. This is particularly acute for seabirds, in which juveniles stay at sea and remain undetectable for several years. In this work, we developed a Bayesian integrated population model to estimate the juvenile survival of emperor penguins (Aptenodytes forsteri), and other demographic parameters including adult survival and fecundity of the species. Using this statistical method, we simultaneously analyzed capture–recapture data of adults, the annual number of breeding females, and the number of fledglings of emperor penguins collected at Dumont d'Urville, Antarctica, for the period 1971–1998. We also assessed how climate covariates known to affect the species foraging habitats and prey [southern annular mode (SAM), sea ice concentration (SIC)] affect juvenile survival. Our analyses revealed that there was a strong evidence for the positive effect of SAM during the rearing period (SAMR) on juvenile survival. Our findings suggest that this large‐scale climate index affects juvenile emperor penguins body condition and survival through its influence on wind patterns, fast ice extent, and distance to open water. Estimating the influence of environmental covariates on juvenile survival is of major importance to understand the impacts of climate variability and change on the population dynamics of emperor penguins and seabirds in general and to make robust predictions on the impact of climate change on marine predators.     

Molecular engineering of <Emphasis Type="SmallCaps">l</Emphasis>-aspartate-α-decarboxylase for improved activity and catalytic stability

β-Alanine is an important precursor for the production of food additives, pharmaceuticals, and nitrogen-containing chemicals. Compared with the conventional chemical routes for β-alanine production, the biocatalytic routes using l-aspartate-α-decarboxylase (ADC) are more attractive when energy and environment are concerned. However, ADC’s poorly understood properties and its inherent mechanism-based inactivation significantly limited the application of this enzyme. In this study, three genes encoding the ADC enzymes from Escherichia coli, Corynebacterium glutamicum, and Bacillus subtilis were overexpressed in E. coli. Their properties including specific activity, thermostability, and mechanism-based inactivation were characterized. The ADC enzyme from B. subtilis, which had higher specific activity and thermostability than the others, was selected for further study. In order to improve its activity and relieve its mechanism-based inactivation by molecular engineering so as to improve its catalytic stability, a high-throughput fluorometric assay of β-alanine was developed. From a library of 4000 mutated enzymes, two variants with 18–22% higher specific activity and 29–64% higher catalytic stability were obtained. The best variant showed 50% higher β-alanine production than the wild type after 8 h of conversion of l-aspartate, showing great potential for industrial biocatalytic production of β-alanine.