Anaerobic Carbon Monoxide Dehydrogenase Diversity in the Homoacetogenic Hindgut Microbial Communities of Lower Termites and the Wood Roach

Anaerobic carbon monoxide dehydrogenase (CODH) is a key enzyme in the Wood-Ljungdahl (acetyl-CoA) pathway for acetogenesis performed by homoacetogenic bacteria. Acetate generated by gut bacteria via the acetyl-CoA pathway provides considerable nutrition to wood-feeding dictyopteran insects making CODH important to the obligate mutualism occurring between termites and their hindgut microbiota. To investigate CODH diversity in insect gut communities, we developed the first degenerate primers designed to amplify cooS genes, which encode the catalytic (β) subunit of anaerobic CODH enzyme complexes. These primers target over 68 million combinations of potential forward and reverse cooS primer-binding sequences. We used the primers to identify cooS genes in bacterial isolates from the hindgut of a phylogenetically lower termite and to sample cooS diversity present in a variety of insect hindgut microbial communities including those of three phylogenetically-lower termites, Zootermopsis nevadensis, Reticulitermes hesperus, and Incisitermes minor, a wood-feeding cockroach, Cryptocercus punctulatus, and an omnivorous cockroach, Periplaneta americana. In total, we sequenced and analyzed 151 different cooS genes. These genes encode proteins that group within one of three highly divergent CODH phylogenetic clades. Each insect gut community contained CODH variants from all three of these clades. The patterns of CODH diversity in these communities likely reflect differences in enzyme or physiological function, and suggest that a diversity of microbial species participate in homoacetogenesis in these communities

XeNA: an automated ‘open-source’ 129Xe hyperpolarizer for clinical use

Here we provide a full report on the construction, components, and capabilities of our consortium’s “open-source” large-scale (~ 1 L/h) 129Xe hyperpolarizer for clinical, pre-clinical, and materials NMR/MRI (Nikolaou et al., Proc. Natl. Acad. Sci. USA, 110, 14150 (2013)). The ‘hyperpolarizer’ is automated and built mostly of off-the-shelf components; moreover, it is designed to be cost-effective and installed in both research laboratories and clinical settings with materials costing less than $125,000. The device runs in the xenon-rich regime (up to 1800 Torr Xe in 0.5 L) in either stopped-flow or single-batch mode—making cryo-collection of the hyperpolarized gas unnecessary for many applications. In-cell 129Xe nuclear spin polarization values of ~ 30%–90% have been measured for Xe loadings of ~ 300–1600 Torr. Typical 129Xe polarization build-up and T1 relaxation time constants were ~ 8.5 min and ~ 1.9 h respectively under our spin-exchange optical pumping conditions; such ratios, combined with near-unity Rb electron spin polarizations enabled by the high resonant laser power (up to ~ 200 W), permit such high PXe values to be achieved despite the high in-cell Xe densities. Importantly, most of the polarization is maintained during efficient HP gas transfer to other containers, and ultra-long 129Xe relaxation times (up to nearly 6 h) were observed in Tedlar bags following transport to a clinical 3 T scanner for MR spectroscopy and imaging as a prelude to in vivo experiments. The device has received FDA IND approval for a clinical study of chronic obstructive pulmonary disease subjects. The primary focus of this paper is on the technical/engineering development of the polarizer, with the explicit goals of facilitating the adaptation of design features and operative modes into other laboratories, and of spurring the further advancement of HP-gas MR applications in biomedicine

Temperature-ramped 129Xe spin-exchange optical pumping

We describe temperature-ramped spin-exchange optical pumping (TR-SEOP) in an automated high-throughput batch-mode 129Xe hyperpolarizer utilizing three key temperature regimes: (i) “hot”where the 129Xe hyperpolarization rate is maximal, (ii) “warm”-where the 129Xe hyperpolarization approaches unity, and (iii) “cool” where hyperpolarized 129Xe gas is transferred into a Tedlar bag with low Rb content (<5 ng per ∼1 L dose) suitable for human imaging applications. Unlike with the conventional approach of batch-mode SEOP, here all three temperature regimes may be operated under continuous high-power (170 W) laser irradiation, and hyperpolarized 129Xe gas is delivered without the need for a cryocollection step. The variable-temperature approach increased the SEOP rate by more than 2-fold compared to the constant-temperature polarization rate (e.g., giving effective values for the exponential buildup constant γSEOP of 62.5 ± 3.7 × 10−3 min−1 vs 29.9 ± 1.2 × 10−3 min−1) while achieving nearly the same maximum %PXe value (88.0 ± 0.8% vs 90.1% ± 0.8%, for a 500 Torr (67 kPa) Xe cell loadingcorresponding to nuclear magnetic resonance/magnetic resonance imaging (NMR/MRI) enhancements of ∼3.1 × 105 and ∼2.32 × 108 at the relevant fields for clinical imaging and HP 129Xe production of 3 T and 4 mT, respectively); moreover, the intercycle “dead” time was also significantly decreased. The higher-throughput TR-SEOP approach can be implemented without sacrificing the level of 129Xe hyperpolarization or the experimental stability for automation-making this approach beneficial for improving the overall 129Xe production rate in clinical settings

The separable effects of feature precision and item load in visual short-term memory

Visual short-term memory (VSTM) has been described as being limited by the number of discrete visual objects, the aggregate quantity of information across multiple visual objects, or some combination of the two. Many recent studies examining these capacity limitations have shown that increasing the number of items in VSTM increases the frequency and magnitude of errors in a participant's recall of the stimulus. This increase in response dispersion has been interpreted as a loss of precision in an item's representation as the number of items in memory increases, possibly due to a change in the tuning of the underlying representation. However, increased response dispersion can also be caused by a reduction in the total memory strength available for decision making as a consequence of a reduction in the total amount of a fixed resource representing a stimulus. We investigated the effects of load on the precision of memory representations in a fine orientation discrimination task. Accuracy was well captured by extending a simple sample-size model of VSTM, using a tuning function to account for the effect of orientation precision on performance. The best model of the data was one in which the item strength decreased progressively with memory load at all stimulus exposure durations but in which tuning bandwidth was invariant. Our results imply that memory strength and feature precision are experimentally dissociable attributes of VSTM

Magnetic resonance imaging in children: common problems and possible solutions for lung and airways imaging

Pediatric chest MRI is challenging. High-resolution scans of the lungs and airways are compromised by long imaging times, low lung proton density and motion. Low signal is a problem of normal lung. Lung abnormalities commonly cause increased signal intenstities. Among the most important factors for a successful MRI is patient cooperation, so the long acquisition times make patient preparation crucial. Children usually have problems with long breath-holds and with the concept of quiet breathing. Young children are even more challenging because of higher cardiac and respiratory rates giving motion blurring. For these reasons, CT has often been preferred over MRI for chest pediatric imaging. Despite its drawbacks, MRI also has advantages over CT, which justifies its further development and clinical use. The most important advantage is the absence of ionizing radiation, which allows frequent scanning for short- and long-term follow-up studie

Erratum: Causal Knowledge Promotes Behavioral Self-Regulation: An Example using Climate Change Dynamics (PLoS ONE (2017) 12:9 (E0184480) DOI: 10.1371/Journal.pone.0184480)

In the Task overview: Managing a dynamic human-climate system subsection of the Introduction, there is an error in equation 4. There is a factor of τ that is missing from the denominator of the first term that appears on the right-hand side of the equation. Please view the complete, correct equation here [Formula Presented]

Predicting perceptual decision biases from early brain activity

Perceptual decision making is believed to be driven by the accumulation of sensory evidence following stimulus encoding. More controversially, some studies report that neural activity preceding the stimulus also affects the decision process. We used a multivariate pattern classification approach for the analysis of the human electroencephalogram (EEG) to decode choice outcomes in a perceptual decision task from spatially and temporally distributed patterns of brain signals. When stimuli provided discriminative information, choice outcomes were predicted by neural activity following stimulus encoding; when stimuli provided no discriminative information, choice outcomes were predicted by neural activity preceding the stimulus. Moreover, in the absence of discriminative information, the recent choice history primed the choices on subsequent trials. A diffusion model fitted to the choice probabilities and response time distributions showed that the starting point of the evidence accumulation process was shifted toward the previous choice, consistent with the hypothesis that choice priming biases the accumulation process toward a decision boundary. This bias is reflected in prestimulus brain activity, which, in turn, becomes predictive of future decisions. Our results provide a model of how non-stimulus-driven decision making in humans could be accomplished on a neural level

Three-Dimensional X-ray Observation of Atmospheric Biological Samples by Linear-Array Scanning-Electron Generation X-ray Microscope System

Recently, we developed a soft X-ray microscope called the scanning-electron generation X-ray microscope (SGXM), which consists of a simple X-ray detection system that detects X-rays emitted from the interaction between a scanning electron beam (EB) and the thin film of the sample mount. We present herein a three-dimensional (3D) X-ray detection system that is based on the SGXM technology and designed for studying atmospheric biological samples. This 3D X-ray detection system contains a linear X-ray photodiode (PD) array. The specimens are placed under a CuZn-coated Si3N4 thin film, which is attached to an atmospheric sample holder. Multiple tilt X-ray images of the samples are detected simultaneously by the linear array of X-ray PDs, and the 3D structure is calculated by a new 3D reconstruction method that uses a simulated-annealing algorithm. The resulting 3D models clearly reveal the inner structure of the bacterium. In addition, the proposed method can easily be used for diverse samples in a broad range of scientific fields

Flexibility and size heterogeneity of the LH1 light harvesting complex revealed by atomic force microscopy - Functional significance for bacterial photosynthesis

Previous electron microscopic studies of bacterial RC-LH1 complexes demonstrated both circular and elliptical conformations of the LH1 ring, and this implied flexibility has been suggested to allow passage of quinol from the

An expert guide to planning experimental tasks for evidence-accumulation modeling

Evidence-accumulation models (EAMs) are powerful tools for making sense of human and animal decision-making behavior. EAMs have generated significant theoretical advances in psychology, behavioral economics, and cognitive neuroscience and are increasingly used as a measurement tool in clinical research and other applied settings. Obtaining valid and reliable inferences from EAMs depends on knowing how to establish a close match between model assumptions and features of the task/data to which the model is applied. However, this knowledge is rarely articulated in the EAM literature, leaving beginners to rely on the private advice of mentors and colleagues and inefficient trial-and-error learning. In this article, we provide practical guidance for designing tasks appropriate for EAMs, relating experimental manipulations to EAM parameters, planning appropriate sample sizes, and preparing data and conducting an EAM analysis. Our advice is based on prior methodological studies and the our substantial collective experience with EAMs. By encouraging good task-design practices and warning of potential pitfalls, we hope to improve the quality and trustworthiness of future EAM research and applications