A comparison of the strength of biodiversity effects across multiple functions

In order to predict which ecosystem functions are most at risk from biodiversity loss, meta-analyses have generalised results from biodiversity experiments over different sites and ecosystem types. In contrast, comparing the strength of biodiversity effects across a large number of ecosystem processes measured in a single experiment permits more direct comparisons. Here, we present an analysis of 418 separate measures of 38 ecosystem processes. Overall, 45 % of processes were significantly affected by plant species richness, suggesting that, while diversity affects a large number of processes not all respond to biodiversity. We therefore compared the strength of plant diversity effects between different categories of ecosystem processes, grouping processes according to the year of measurement, their biogeochemical cycle, trophic level and compartment (above- or belowground) and according to whether they were measures of biodiversity or other ecosystem processes, biotic or abiotic and static or dynamic. Overall, and for several individual processes, we found that biodiversity effects became stronger over time. Measures of the carbon cycle were also affected more strongly by plant species richness than were the measures associated with the nitrogen cycle. Further, we found greater plant species richness effects on measures of biodiversity than on other processes. The differential effects of plant diversity on the various types of ecosystem processes indicate that future research and political effort should shift from a general debate about whether biodiversity loss impairs ecosystem functions to focussing on the specific functions of interest and ways to preserve them individually or in combination.     

Extremotolerance and Resistance of Lichens: Comparative Studies on Five Species Used in Astrobiological Research II. Secondary Lichen Compounds

Lichens, which are symbioses of a fungus and one or two photoautotrophs, frequently tolerate extreme environmental conditions. This makes them valuable model systems in astrobiological research to fathom the limits and limitations of eukaryotic symbioses. Various studies demonstrated the high resistance of selected extremotolerant lichens towards extreme, non-terrestrial abiotic factors including space exposure, hypervelocity impact simulations as well as space and Martian parameter simulations. This study focusses on the diverse set of secondary lichen compounds (SLCs) that act as photo- and UVR-protective substances. Five lichen species used in present-day astrobiological research were compared: Buellia frigida, Circinaria gyrosa, Rhizocarpon geographicum, Xanthoria elegans, and Pleopsidium chlorophanum. Detailed investigation of secondary substances including photosynthetic pigments was performed for whole lichen thalli but also for axenically cultivated mycobionts and photobionts by methods of UV/VIS-spectrophotometry and two types of high performance liquid chromatography (HPLC). Additionally, a set of chemical tests is presented to confirm the formation of melanic compounds in lichen and mycobiont samples. All investigated lichens reveal various sets of SLCs, except C. gyrosa where only melanin was putatively identified. Such studies will help to assess the contribution of SLCs on lichen extremotolerance, to understand the adaptation of lichens to prevalent abiotic stressors of the respective habitat, and to form a basis for interpreting recent and future astrobiological experiments. As most of the identified SLCs demonstrated a high capacity in absorbing UVR, they may also explain the high resistance of lichens towards non-terrestrial UVR.     

Visualization of cyclooxygenase-2 using a 2,3-diarylsubstituted indole-based inhibitor and confocal laser induced cryofluorescence microscopy at 20 K in melanoma cells in vitro

This study aimed at visualization of cyclooxygenase-2 (COX-2) protein expression in melanoma cells by confocal laser induced cryofluorescence microscopy using 4-(3-(4-methoxyphenyl)-1H-indol-2-yl)benzene-sulfonamide (C1) representative for a novel class of autofluorescent 2,3-diarylsubstituted indole-based selective COX-2 inhibitors.COX-2 expression was measured in human melanoma cell lines A2058 and MelJuso by immunocytochemistry and immunoblotting. Cellular uptake experiments using varying C1 concentrations down to 0.1 nM (with/without molar excess of celecoxib as control) were performed at 37 °C. Cryofluorescence microscopy was conducted at 20 K.COX-2 protein expression was successfully visualized by C1 in A2058 cells. COX-2-negative MelJuso cells showed no specific accumulation of C1. Control experiments using celecoxib and, additionally, implemented fluorescence spectroscopy confirmed specificity of both cellular uptake and intracellular association of C1.Cryofluorescence microscopy in combination with spectroscopy allowed for visualization of COX-2 protein expression in melanoma cells in vitro using a selective COX-2 inhibitor at very low concentrations.     

An evidence-based consensus for the classification of arbuscular mycorrhizal fungi (Glomeromycota)

The publication of a large number of taxon names at all levels within the arbuscular mycorrhizal fungi (Glomeromycota) has resulted in conflicting systematic schemes and generated considerable confusion among biologists working with these important plant symbionts. A group of biologists with more than a century of collective experience in the systematics of Glomeromycota examined all available molecular–phylogenetic evidence within the framework of phylogenetic hypotheses, incorporating morphological characters when they were congruent. This study is the outcome, wherein the classification of Glomeromycota is revised by rejecting some new names on the grounds that they are founded in error and by synonymizing others that, while validly published, are not evidence-based. The proposed “consensus” will provide a framework for additional original research aimed at clarifying the evolutionary history of this important group of symbiotic fungi.     

Gastrointestinal absorption and metabolism of apple polyphenols ex vivo by the pig intestinal mucosa in the Ussing chamber

Polyphenols contained in food have various positive effects on human health. The absorption and metabolism of polyphenols in the intestinal tract needs to be studied to estimate these effects. The Ussing chamber technique was used to investigate the transport behavior of apple polyphenols through pig small intestinal mucosa, which served as a model for human gastrointestinal mucosa. The identities and concentrations of polyphenols and their metabolites in the half-chambers (luminal and basolateral) within an incubation period of 4 h were determined by HPLC–MS/MS and HPLC–DAD (DAD = diode-array detection). Flux values were also measured. It was found that 5-caffeoylquinic acid and caffeic acid were absorbed and translocated to the basolateral side (1.9 and 3.7%, respectively), but other compounds, including glycosides of phloretin and quercetin, were observed without translocation. A Ussing chamber utilizing pig small intestinal mucosa is a suitable model for assessing the effect of apple polyphenols on mucosal integrity and nutrition absorption across porcine mucosa.     

Nicotinamide nucleotide transhydrogenase mRNA expression is related to human obesity

Objective:

A spontaneous deletion in the nicotinamide nucleotide transhydrogenase (Nnt) gene eliminating exons 7‐11 in C57BL/6J (B6J) mice is associated with reduced glucose‐stimulated insulin secretion in vitro, impaired glucose tolerance, higher epigonadal fat mass, and altered susceptibility to diet induced obesity of male B6J mice was proposed. A potential implication for NNT in human adipose tissue distribution has not been investigated so far.

Design and Methods:

Therefore, NNT mRNA expression in paired human samples of visceral (vis) and subcutaneous (sc) adipose tissue from 221 subjects with a wide range of body mass index (BMI), insulin sensitivity, and glucose tolerance was analyzed.

Results:

NNT mRNA expression is significantly higher in visceral fat of obese patients and correlates with body weight, BMI, % body fat, visceral and sc fat area, waist and hip circumference, and fasting plasma insulin (FPI). Multivariate linear regression analysis revealed visceral NNT expression as age and gender independent predictor of BMI, waist circumference, visceral fat area, and % body fat, but not FPI and 2 h OGTT glucose.

Conclusion:

In conclusion, a functional relevance of NNT in the development of human obesity and visceral fat distribution was suggested here.     

An infrared sensor analysing label‐free the secondary structure of the Abeta peptide in presence of complex fluids

The secondary structure change of the Abeta peptide to beta‐sheet was proposed as an early event in Alzheimer's disease. The transition may be used for diagnostics of this disease in an early state. We present an Attenuated Total Reflection (ATR) sensor modified with a specific antibody to extract minute amounts of Abeta peptide out of a complex fluid. Thereby, the Abeta peptide secondary structure was determined in its physiological aqueous environment by FTIR‐difference‐spectroscopy. The presented results open the door for label‐free Alzheimer diagnostics in cerebrospinal fluid or blood. It can be extended to further neurodegenerative diseases.

An immunologic ATR‐FTIR sensor for Abeta peptide secondary structure analysis in complex fluids is presented.     

Turing learning: a metric-free approach to inferring behavior and its application to swarms

We propose Turing Learning, a novel system identification method for inferring the behavior of natural or artificial systems. Turing Learning simultaneously optimizes two populations of computer programs, one representing models of the behavior of the system under investigation, and the other representing classifiers. By observing the behavior of the system as well as the behaviors produced by the models, two sets of data samples are obtained. The classifiers are rewarded for discriminating between these two sets, that is, for correctly categorizing data samples as either genuine or counterfeit. Conversely, the models are rewarded for ‘tricking’ the classifiers into categorizing their data samples as genuine. Unlike other methods for system identification, Turing Learning does not require predefined metrics to quantify the difference between the system and its models. We present two case studies with swarms of simulated robots and prove that the underlying behaviors cannot be inferred by a metric-based system identification method. By contrast, Turing Learning infers the behaviors with high accuracy. It also produces a useful by-product—the classifiers—that can be used to detect abnormal behavior in the swarm. Moreover, we show that Turing Learning also successfully infers the behavior of physical robot swarms. The results show that collective behaviors can be directly inferred from motion trajectories of individuals in the swarm, which may have significant implications for the study of animal collectives. Furthermore, Turing Learning could prove useful whenever a behavior is not easily characterizable using metrics, making it suitable for a wide range of applications.     

150 Jahre “Biogenetisches Grundgesetz”

150 years “Biogenetic Law” The zoologist Ernst Haeckel is one of the most well‐known, but also one of the most controversial scientists of the late 19th and early 20th centuries. He was one of the earliest Darwinists and a forceful advocate of evolutionary theory. Together with “Darwin's Bulldog” Thomas Henry Huxley, Haeckel was a central figure in the early history and popularization of Darwinism. But his name is not only a symbol for the disputes about the theory of evolution and its popularization, but also for a campaign for monism, a world‐view or philosophy created by Haeckel himself. Together with Fritz Müller, Ernst Haeckel was one of the first to formulate a “Biogenetic Law”. He also created several concepts and terms still in use in biology today, such as “ontogeny”, “phylogeny”, “ecology”, “cholorogy” and “phylum” in his first, and maybe most important book “General Morphology of Organism”, which was published in 1866, 150 years ago.     

Metabolite targeting: development of a comprehensive targeted metabolomics platform for the assessment of diabetes and its complications

Biomarker studies for metabolic disorders like diabetes mellitus (DM) are an important approach towards a better understanding of the underlying pathophysiological mechanisms of diseases (Roberts and Gerszten in Cell Metab 18:43–50, 2013; Wilson et al. in Proteome Res 4:591–598, 2005). Furthermore, screening of potential metabolic biomarkers opens the opportunity of early diagnosis as well as therapy and drug monitoring of metabolic disorders (Rhee et al. in J Clin Invest 10:1–10, 2011; Wang et al. in Nat Med 17:448–458, 2011; Wenk in Nat Rev Drug Discov 4:594–610, 2005). The aim of the present study was to develop methods for the quantitative determination of 74 potential metabolite biomarkers for DM and diabetic nephropathy (DN) in serum. Several studies have shown that the concentrations of many polar metabolites like amino or organic acids are changed in subjects suffering from diabetes (Wang et al. in Nat Med 17:448–458, 2011; Yuan et al. in J Chromatogr B 813:53–58, 2007). Analyzing polar analytes presents a challenge in liquid chromatography (LC) coupled with ESI–MS/MS (Gika et al. in J Sep Sci 31:1598–1608, 2008; Spagou et al. in J Sep Sci 33:716–727, 2010). Considering those reasons we decided to develop a specific HILIC–ESI–QqQ–MS/MS-method for quantitative determination of these polar metabolites. A subsequent method validation was carried out for both HILIC and RP chromatography with respect to the guidelines of the Food and Drug Administration (FDA in Food and Drug Administration: Guidance for industry, bioanalytical method validation, 2001). The HILIC and RP LC–MS methods were successfully validated. Furthermore, the HILIC method presented here was applied to serum samples of GIPR^dn transgenic mice, a diabetic strain developing DN, and non transgenic littermate controls. Significant, diabetes-associated changes were observed for the concentrations of 21 out of 62 metabolites. The new methods described here accurately quantify 74 metabolites known to be regulated in diabetes, allowing for direct comparison between studies and laboratories. Thus, these methods may be highly adoptable in clinical research, providing a starting point for early diagnosis and metabolic screening.