Cellular Mechanisms Underlying State-Dependent Neural Inhibition with Magnetic Stimulation

Novel stimulation protocols for neuromodulation with magnetic fields are explored in clinical and laboratory settings. Recent evidence suggests that the activation state of the nervous system plays a significant role in the outcome of magnetic stimulation, but the underlying cellular and molecular mechanisms of state-dependency have not been completely investigated. We recently reported that high frequency magnetic stimulation could inhibit neural activity when the neuron was in a low active state. In this paper, we investigate state-dependent neural modulation by applying a magnetic field to single neurons, using the novel micro-coil technology. High frequency magnetic stimulation suppressed single neuron activity in a state-dependent manner. It inhibited neurons in slow-firing states, but spared neurons from fast-firing states, when the same magnetic stimuli were applied. Using a multi-compartment NEURON model, we found that dynamics of voltage-dependent sodium and potassium channels were significantly altered by the magnetic stimulation in the slow-firing neurons, but not in the fast-firing neurons. Variability in neural activity should be monitored and explored to optimize the outcome of magnetic stimulation in basic laboratory research and clinical practice. If selective stimulation can be programmed to match the appropriate neural state, prosthetic implants and brain-machine interfaces can be designed based on these concepts to achieve optimal results

A High-resolution Large-eddy Simulation Framework for Wildfire Predictions using TensorFlow

As the impact of wildfires has become increasingly more severe over the last decades, there is continued pressure for improvements in our ability to predict wildland fire behavior over a wide range of conditions. One approach towards this goal is through coupled fire/atmosphere modeling tools. While significant progress has been made on advancing their physical fidelity, existing modeling tools have not taken full advantage of emerging programming paradigms and computing architectures to enable high-resolution wildfire simulations. By addressing this gap, this work presents a new wildfire simulation framework that enables landscape-scale wildfire simulations with physical representation of the combustion at affordable computational cost. This is achieved by developing a coupled fire/atmosphere model in the TensorFlow programming paradigm, which enables highly efficient and scalable computations on Tensor Processing Unit (TPU) hardware architecture. To validate this simulation framework and demonstrate its efficiency, simulations of the prescribed fire experiment FireFlux II (Clements et al., 2019) are performed. By considering a parametric study on the mesh resolution, we show that the global quantities such as volumetric heat release and fire-spread rate are insensitive to the horizontal mesh resolution within a range between 0.5 m and 2 m, which is sufficient for predicting fire intermittency and dynamic fire properties associated with fine-scale turbulent structures in the atmospheric boundary layer.Comment: 10 figures, 2 tables, 4559 word

Development of a tomato xylem-mimicking microfluidic system to study Ralstonia pseudosolanacearum biofilm formation

The bacterial wilt pathogen Ralstonia pseudosolanacearum (Rps) colonizes plant xylem vessels and blocks the flow of xylem sap by its biofilm (comprising of bacterial cells and extracellular material), resulting in devastating wilt disease across many economically important host plants including tomatoes. The technical challenges of imaging the xylem environment, along with the use of artificial cell culture plates and media in existing in vitro systems, limit the understanding of Rps biofilm formation and its infection dynamics. In this study, we designed and built a microfluidic system that mimicked the physical and chemical conditions of the tomato xylem vessels, and allowed us to dissect Rps responses to different xylem-like conditions. The system, incorporating functional surface coatings of carboxymethyl cellulose-dopamine, provided a bioactive environment that significantly enhanced Rps attachment and biofilm formation in the presence of tomato xylem sap. Using computational approaches, we confirmed that Rps experienced linear increasing drag forces in xylem-mimicking channels at higher flow rates. Consistently, attachment and biofilm assays conducted in our microfluidic system revealed that both seeding time and flow rates were critical for bacterial adhesion to surface and biofilm formation inside the channels. These findings provided insights into the Rps attachment and biofilm formation processes, contributing to a better understanding of plant-pathogen interactions during wilt disease development

Everolimus for patients with mantle cell lymphoma refractory to or intolerant of bortezomib: multicentre, single‐arm, phase 2 study

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106815/1/bjh12780.pd

Limits to Rest-Frame Ultraviolet Emission From Far-Infrared-Luminous z~6 Quasar Hosts

We report on a Hubble Space Telescope search for rest-frame ultraviolet emission from the host galaxies of five far-infrared-luminous $z\simeq{}6$ quasars and the $z=5.85$ hot-dust free quasar SDSS J0005-0006. We perform 2D surface brightness modeling for each quasar using a Markov-Chain Monte-Carlo estimator, to simultaneously fit and subtract the quasar point source in order to constrain the underlying host galaxy emission. We measure upper limits for the quasar host galaxies of $m_J>22.7$ mag and $m_H>22.4$ mag, corresponding to stellar masses of $M_\ast<2\times10^{11}M_\odot$. These stellar mass limits are consistent with the local $M_{\textrm{BH}}$-$M_\ast$ relation. Our flux limits are consistent with those predicted for the UV stellar populations of $z\simeq6$ host galaxies, but likely in the presence of significant dust ($\langle A_{\mathrm{UV}}\rangle\simeq 2.6$ mag). We also detect a total of up to 9 potential $z\simeq6$ quasar companion galaxies surrounding five of the six quasars, separated from the quasars by 1.4''-3.2'', or 8.4-19.4 kpc, which may be interacting with the quasar hosts. These nearby companion galaxies have UV absolute magnitudes of -22.1 to -19.9 mag, and UV spectral slopes $\beta$ of -2.0 to -0.2, consistent with luminous star-forming galaxies at $z\simeq6$. These results suggest that the quasars are in dense environments typical of luminous $z\simeq6$ galaxies. However, we cannot rule out the possibility that some of these companions are foreground interlopers. Infrared observations with the James Webb Space Telescope will be needed to detect the $z\simeq6$ quasar host galaxies and better constrain their stellar mass and dust content.Comment: 22 pages, 13 figures. Accepted for publication in Ap

Vocal learning-associated convergent evolution in mammalian proteins and regulatory elements.

Vocal production learning (vocal learning) is a convergently evolved trait in vertebrates. To identify brain genomic elements associated with mammalian vocal learning, we integrated genomic, anatomical, and neurophysiological data from the Egyptian fruit bat (Rousettus aegyptiacus) with analyses of the genomes of 215 placental mammals. First, we identified a set of proteins evolving more slowly in vocal learners. Then, we discovered a vocal motor cortical region in the Egyptian fruit bat, an emergent vocal learner, and leveraged that knowledge to identify active cis-regulatory elements in the motor cortex of vocal learners. Machine learning methods applied to motor cortex open chromatin revealed 50 enhancers robustly associated with vocal learning whose activity tended to be lower in vocal learners. Our research implicates convergent losses of motor cortex regulatory elements in mammalian vocal learning evolution

A frontal attention mechanism in the visual mismatch negativity

Automatic detection of environmental change is a core component of attention. The mismatch negativity (MMN), an electrophysiological marker of this mechanism, has been studied prominently in the auditory domain, with cortical generators identified in temporal and frontal regions. Here, we combined electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to assess whether the underlying frontal regions associated with auditory change detection also play a role in visual change detection. Twenty healthy young adults completed a visual MMN task in separate EEG and fMRI sessions. Region of interest analyses were conducted on left and right middle frontal (MFG) and inferior frontal (IFG) gyri, i.e., the frontal areas identified as potential auditory MMN generators. A significant increase in activation was observed in the left IFG and MFG in response to blocks containing deviant stimuli. These findings suggest that a frontal mechanism is involved in the detection of change in the visual MMN. Our results support the notion that frontal mechanisms underlie attention switching, as measured via MMN, across multiple modalities

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Correction to: Cluster identification, selection, and description in Cluster randomized crossover trials: the PREP-IT trials

An amendment to this paper has been published and can be accessed via the original article