Long-Duration Spaceflight Increases Depth Ambiguity of Reversible Perspective Figures.

The objective of this study was to investigate depth perception in astronauts during and after spaceflight by studying their sensitivity to reversible perspective figures in which two-dimensional images could elicit two possible depth representations. Other ambiguous figures that did not give rise to a perception of illusory depth were used as controls. Six astronauts and 14 subjects were tested in the laboratory during three sessions for evaluating the variability of their responses in normal gravity. The six astronauts were then tested during four sessions while on board the International Space Station for 5-6 months. They were finally tested immediately after return to Earth and up to one week later. The reaction time decreased throughout the sessions, thus indicating a learning effect. However, the time to first percept reversal and the number of reversals were not different in orbit and after the flight compared to before the flight. On Earth, when watching depth-ambiguous perspective figures, all subjects reported seeing one three-dimensional interpretation more often than the other, i.e. a ratio of about 70-30%. In weightlessness this asymmetry gradually disappeared and after 3 months in orbit both interpretations were seen for the same duration. These results indicate that the perception of "illusory" depth is altered in astronauts during spaceflight. This increased depth ambiguity is attributed to the lack of the gravitational reference and the eye-ground elevation for interpreting perspective depth cues.

Perceptual reversal of bi-stable figures in microgravity and hypergravity during parabolic flight.

This experiment investigated whether the perception of depth-reversible figures is altered when the observer is in microgravity or hypergravity. A set of five bi-stable ambiguous figures was presented to ten participants in 1g, 0 g, and 1.8 g during parabolic flight. The figures included static images such as the Necker cube; kinetic depth displays such as a moving plaid and a sphere cluster of moving dots appearing to rotate in one of two directions; and a silhouette photograph. For each stimulus figure, subjects reported which of the two possible perceptual configurations they saw first and then continuously indicated when perceptual reversals occurred for durations ranging from 20 to 30s. The same first percept was reported in 1g, 0 g, and 1.8 g. The time delay for the first reversal between the two possible image interpretations was longer and the number of reversals was fewer in 0 g as compared to 1g for four of the five figures. The opposite effects were seen when going from 0 g to 1.8 g. These findings confirm that, consistent with a multisensory approach to three-dimensional form perception, gravity has a clear effect on the interpretation of depth-based stimuli and this gravity-based component interferes with visual perception stability.

Ensemble Rule-Based Classification of Substrates of the Human ABC-Transporter ABCB1 Using Simple Physicochemical Descriptors.

Within the last decades, the detailed knowledge on the impact of membrane bound drug efflux transporters of the ATP binding cassette (ABC) protein family on the pharmacological profile of drugs has enormously increased. Especially, ABCB1 (P-glycoprotein, P-gp, MDR1) has attracted particular interest in medicinal chemistry, since it determines the clinical efficacy, side effects and toxicity risks of drug candidates. Based on this, the development of in silico models that provide rapid and cost-effective screening tools for the classification of substrates and nonsubstrates of ABCB1 is an urgent need in contemporary ADMET profiling. A characteristic hallmark feature of this transporter is its polyspecific ligand recognition pattern. In this study we describe a method for classifying ABCB1 ligands in terms of simple, conjunctive rules (RuleFit) based on interpretable ADMET features. The retrieved results showed that models based on large, very diverse data sets gave better classification performance than models based on smaller, more homogenous training sets. The best model achieved gave a correct classification rate of 0.90 for an external validation set. Furthermore, from the interpretation of the best performing model it could be concluded that in comparison to nonsubstrates ABCB1 substrates generally show a higher number of hydrogen-bond acceptors, are more flexible and exhibit higher logP values.

Predicting ligand interactions with ABC transporters in ADME.

ABC-type drug efflux pumps, e.g., ABCB1 (=P-glycoprotein, =MDR1), ABCC1 (=MRP1), and ABCG2 (=MXR, =BCRP), confer a multi-drug resistance (MDR) phenotype to cancer cells. Furthermore, the important contribution of ABC transporters for bioavailability, distribution, elimination, and blood-brain barrier permeation of drug candidates is increasingly recognized. This review presents an overview on the different computational methods and models pursued to predict ABC transporter substrate properties of drug-like compounds. They encompass ligand-based approaches ranging from 'simple rule'-based efforts to sophisticated machine learning methods. Many of these models show excellent performance for the data sets used. However, due to the complex nature of the applied methods, useful interpretation of the models that can be directly translated into chemical structures by the medicinal chemist is rather difficult. Additionally, very recent and promising attempts in the field of structure-based modeling of ABC transporters, which embody homology modeling as well as recently published X-ray structures of murine ABCB1, will be discussed.

In silico prediction of substrate properties for ABC-multidrug transporters.

Overexpression of ABC (ATP-binding cassette)-type drug efflux pumps, such as ABCB1, ABCC1 and ABCG2 in cancer cells confers multi-drug resistance (MDR) and represents a major cause of treatment failures in cancer therapy. Furthermore, there is increasing evidence for the important contribution of ABC-transporters to bioavailability, distribution, elimination and blood-brain barrier permeation of drug candidates. This review presents an overview on the different computational methods and models pursued to predict ABC-transporter substrate properties of drug-like compounds. They range from linear discriminant analysis to pharmacophore modelling and machine learning algorithms. Many of these models show a satisfying performance within the study-specific, defined chemical space but general applicability for the whole drug-like chemical space still needs to be proven. First attempts aiming towards selectivity profiling for ligands of the two polyspecific transporters ABCB1 and ABCG2 is also discussed. This might pave the way for a pharmacological profiling of compound series with special focus on their ADMET (absorption, distribution, metabolism, excretion and toxicity) properties.

DGGE and real-time PCR analysis of lactic acid bacteria in bacterial communities of the phyllosphere of lettuce.

Food associated indigenous microbial communities exert antagonistic effects on pathogens and may routinely deliver health relevant microorganisms to the GI tract. By using molecular, culture independent methods including PCR-DGGE of 16S rDNA-coding regions and real-time PCR (RT-PCR) as well as BIOLOG metabolic fingerprinting, microbial communities on lettuce were analyzed in samples from fields, from supermarkets and soil. Amplified 16S rRNA gene sequences (57.7%) could be assigned to species previously reported as typical for the phyllosphere including Pantoea agglomerans, Pseudomonas flavescens, Moraxella spp., and Mycobacterium spp. 71.8% of the sequences obtained represented so far undescribed taxa. Principal component analysis of BIOLOG metabolic profiles indicated a seasonal variation in the lettuce phyllosphere microbial community structure. Various lactic acid bacteria were detected including several Lactobacillus and Leuconostoc species in particular on lettuce from organic farming. By RT-PCR lactobacilli were found with a range of abundances from 1x10(4 )to 1x10(5 )copies/g lettuce. Considering the importance of salad in many diets lettuce may contribute to a constant supply with LAB.