Insights into Functionality-Specific Adsorption Dynamics and Stable Reaction Intermediates Using Fast Field Cycling NMR

Fast field cycling, FFC, NMR relaxometry experiments are reported in the frequency range of 10 kHz to 40 MHz to characterize the molecular dynamics of a series of protic (methanol and water) and aprotic (dimethyl sulfoxide, acetone, cyclohexane, and n-heptane) adsorbates on a γ-alumina surface of catalytic interest. By analyzing the data in the T1 domain, two distinct peaks were observed for both methanol and acetone. In the case of methanol, the two peaks have been shown to originate from the two chemical environments of methanol, which at low field strengths differentiate the O1H and alkyl 1H interactions with the surface. In contrast, the second environment of adsorbed acetone is assigned to a stable reaction intermediate formed during an aldol reaction, which strongly influences other molecular adsorption processes at the surface. Inversion of the FFC-NMR data into the T1-domain enables the combination of the ability of low field NMR to characterize relaxation modes directly associated with adsorption with T1 measurements specific to functional groups and reaction intermediates, thereby avoiding misinterpretation of molecular adsorption characteristics and giving greater insight into adsorption and catalytic behavior than is possible from the overall relaxation dispersion profiles alone

A Long Slit-Like Entrance Promotes Ventilation in the Mud Nesting Social Wasp, Polybia spinifex: Visualization of Nest Microclimates using Computational Fluid Dynamics

Polybia spinifex Richards (Hymenoptera: Vespidae) constructs mud nests characterized by a long slit-like entrance. The ventilation and thermal characteristics of the P. spinifex nest were investigated to determine whether the nest microclimate is automatically maintained due to the size of the entrance. In order to examine this hypothesis, a numerical simulation was employed to predict the effects of the entrance length. The calculations were performed with 3D-virtual models that simulated the P. spinifex nest conditions, and the reliability of the simulations was experimentally examined by using gypsum-model nests and a P. spinifex nest. The ventilation effect was determined by blowing air through the nest at 1–3 m/s (airflow conditions); the airspeed was found to be higher in models with a longer entrance. The ventilation rate was also higher in models with longer entrances, suggesting that the P. spinifex nest is automatically ventilated by natural winds. Next, the thermal effect was calculated under condition of direct sunlight. Under a calm condition (airflow, 0 m/s), thermal convection and a small temperature drop were observed in the case of models with a long entrance, whereas the ventilation and thermoregulation effects seemed small. Under airflow conditions, the temperature at the mid combs steeply dropped due to the convective airflow through the entrance at 1–2 m/s, and at 3 m/s, most of the heat was eliminated due to high thermal conductivity of the mud envelope, rather than convection

Joint multi-field T1 quantification for fast field-cycling MRI

Acknowledgment This article is based upon work from COST Action CA15209, supported by COST (European Cooperation in Science and Technology). Oliver Maier is a Recipient of a DOC Fellowship (24966) of the Austrian Academy of Sciences at the Institute of Medical Engineering at TU Graz. The authors would like to acknowledge the NVIDIA Corporation Hardware grant support.Peer reviewedPublisher PD

A theoretical foundation for multi-scale regular vegetation patterns

Self-organized regular vegetation patterns are widespread and thought to mediate ecosystem functions such as productivity and robustness, but the mechanisms underlying their origin and maintenance remain disputed. Particularly controversial are landscapes of overdispersed (evenly spaced) elements, such as North American Mima mounds, Brazilian murundus, South African heuweltjies, and, famously, Namibian fairy circles. Two competing hypotheses are currently debated. On the one hand, models of scale-dependent feedbacks, whereby plants facilitate neighbours while competing with distant individuals, can reproduce various regular patterns identified in satellite imagery. Owing to deep theoretical roots and apparent generality, scale-dependent feedbacks are widely viewed as a unifying and near-universal principle of regular-pattern formation despite scant empirical evidence. On the other hand, many overdispersed vegetation patterns worldwide have been attributed to subterranean ecosystem engineers such as termites, ants, and rodents. Although potentially consistent with territorial competition, this interpretation has been challenged theoretically and empirically and (unlike scale-dependent feedbacks) lacks a unifying dynamical theory, fuelling scepticism about its plausibility and generality. Here we provide a general theoretical foundation for self-organization of social-insect colonies, validated using data from four continents, which demonstrates that intraspecific competition between territorial animals can generate the large-scale hexagonal regularity of these patterns. However, this mechanism is not mutually exclusive with scale-dependent feedbacks. Using Namib Desert fairy circles as a case study, we present field data showing that these landscapes exhibit multi-scale patterning-previously undocumented in this system-that cannot be explained by either mechanism in isolation. These multi-scale patterns and other emergent properties, such as enhanced resistance to and recovery from drought, instead arise from dynamic interactions in our theoretical framework, which couples both mechanisms. The potentially global extent of animal-induced regularity in vegetation-which can modulate other patterning processes in functionally important ways-emphasizes the need to integrate multiple mechanisms of ecological self-organization

Optimal assignment methods for ligand-based virtual screening

<p>Abstract</p> <p>Background</p> <p>Ligand-based virtual screening experiments are an important task in the early drug discovery stage. An ambitious aim in each experiment is to disclose active structures based on new scaffolds. To perform these "scaffold-hoppings" for individual problems and targets, a plethora of different similarity methods based on diverse techniques were published in the last years. The optimal assignment approach on molecular graphs, a successful method in the field of quantitative structure-activity relationships, has not been tested as a ligand-based virtual screening method so far.</p> <p>Results</p> <p>We evaluated two already published and two new optimal assignment methods on various data sets. To emphasize the "scaffold-hopping" ability, we used the information of chemotype clustering analyses in our evaluation metrics. Comparisons with literature results show an improved early recognition performance and comparable results over the complete data set. A new method based on two different assignment steps shows an increased "scaffold-hopping" behavior together with a good early recognition performance.</p> <p>Conclusion</p> <p>The presented methods show a good combination of chemotype discovery and enrichment of active structures. Additionally, the optimal assignment on molecular graphs has the advantage to investigate and interpret the mappings, allowing precise modifications of internal parameters of the similarity measure for specific targets. All methods have low computation times which make them applicable to screen large data sets.</p

Transcranial Magnetic Stimulation Intensities in Cognitive Paradigms

BACKGROUND: Transcranial magnetic stimulation (TMS) has become an important experimental tool for exploring the brain's functional anatomy. As TMS interferes with neural activity, the hypothetical function of the stimulated area can thus be tested. One unresolved methodological issue in TMS experiments is the question of how to adequately calibrate stimulation intensities. The motor threshold (MT) is often taken as a reference for individually adapted stimulation intensities in TMS experiments, even if they do not involve the motor system. The aim of the present study was to evaluate whether it is reasonable to adjust stimulation intensities in each subject to the individual MT if prefrontal regions are stimulated prior to the performance of a cognitive paradigm. METHODS AND FINDINGS: Repetitive TMS (rTMS) was applied prior to a working memory task, either at the 'fixed' intensity of 40% maximum stimulator output (MSO), or individually adapted at 90% of the subject's MT. Stimulation was applied to a target region in the left posterior middle frontal gyrus (pMFG), as indicated by a functional magnetic resonance imaging (fMRI) localizer acquired beforehand, or to a control site (vertex). Results show that MT predicted the effect size after stimulating subjects with the fixed intensity (i.e., subjects with a low MT showed a greater behavioral effect). Nevertheless, the individual adaptation of intensities did not lead to stable effects. CONCLUSION: Therefore, we suggest assessing MT and account for it as a measure for general cortical TMS susceptibility, even if TMS is applied outside the motor domain

GWAS and drug targets

Genome wide association studies (GWAS) have revealed a large number of links between genome variation and complex disease. Among other benefits, it is expected that these insights will lead to new therapeutic strategies, particularly the identification of new drug targets. In this paper, we evaluate the power of GWAS studies to find drug targets by examining how many existing drug targets have been directly 'rediscovered' by this technique, and the extent to which GWAS results may be leveraged by network information to discover known and new drug targets. We find that only a very small fraction of drug targets are directly detected in the relevant GWAS studies. We investigate two possible explanations for this observation. First, we find evidence of negative selection acting on drug target genes as a consequence of strong coupling with the disease phenotype, so reducing the incidence of SNPs linked to the disease. Second, we find that GWAS genes are substantially longer on average than drug targets and than all genes, suggesting there is a length related bias in GWAS results. In spite of the low direct relationship between drug targets and GWAS reported genes, we found these two sets of genes are closely coupled in the human protein network. As a consequence, machine-learning methods are able to recover known drug targets based on network context and the set of GWAS reported genes for the same disease. We show the approach is potentially useful for identifying drug repurposing opportunities. Although GWA studies do not directly identify most existing drug targets, there are several reasons to expect that new targets will nevertheless be discovered using these data. Initial results on drug repurposing studies using network analysis are encouraging and suggest directions for future development.https://doi.org/10.1186/1471-2164-15-S4-S

Tau pathology does not affect experience-driven single-neuron and network-wide Arc/Arg3.1 responses

Intraneuronal neurofibrillary tangles (NFTs) – a characteristic pathological feature of Alzheimer’s and several other neurodegenerative diseases – are considered a major target for drug development. Tangle load correlates well with the severity of cognitive symptoms and mouse models of tauopathy are behaviorally impaired. However, there is little evidence that NFTs directly impact physiological properties of host neurons. Here we used a transgenic mouse model of tauopathy to study how advanced tau pathology in different brain regions affects activity-driven expression of immediate-early gene Arc required for experience-dependent consolidation of long-term memories. We demonstrate in vivo that visual cortex neurons with tangles are as likely to express comparable amounts of Arc in response to structured visual stimulation as their neighbors without tangles. Probability of experience-dependent Arc response was not affected by tau tangles in both visual cortex and hippocampal pyramidal neurons as determined postmortem. Moreover, whole brain analysis showed that network-wide activity-driven Arc expression was not affected by tau pathology in any of the brain regions, including brain areas with the highest tangle load. Our findings suggest that intraneuronal NFTs do not affect signaling cascades leading to experience-dependent gene expression required for long-term synaptic plasticity