Biology subjects

Zuckerman, D.

Publications and source records attributed to Zuckerman, D..

3 recordsLinked to original sources

bioRxiv2021

#COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy of Delta SARS-CoV-2 in a Respiratory Aerosol

We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus ob-scure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized. ACM Reference FormatAbigail Dommer1{dagger}, Lorenzo Casalino1{dagger}, Fiona Kearns1{dagger}, Mia Rosenfeld1, Nicholas Wauer1, Surl-Hee Ahn1, John Russo,2 Sofia Oliveira3, Clare Morris1, AnthonyBogetti4, AndaTrifan5,6, Alexander Brace5,7, TerraSztain1,8, Austin Clyde5,7, Heng Ma5, Chakra Chennubhotla4, Hyungro Lee9, Matteo Turilli9, Syma Khalid10, Teresa Tamayo-Mendoza11, Matthew Welborn11, Anders Christensen11, Daniel G. A. Smith11, Zhuoran Qiao12, Sai Krishna Sirumalla11, Michael OConnor11, Frederick Manby11, Anima Anandkumar12,13, David Hardy6, James Phillips6, Abraham Stern13, Josh Romero13, David Clark13, Mitchell Dorrell14, Tom Maiden14, Lei Huang15, John McCalpin15, Christo- pherWoods3, Alan Gray13, MattWilliams3, Bryan Barker16, HarindaRajapaksha16, Richard Pitts16, Tom Gibbs13, John Stone6, Daniel Zuckerman2*, Adrian Mulholland3*, Thomas MillerIII11,12*, ShantenuJha9*, Arvind Ramanathan5*, Lillian Chong4*, Rommie Amaro1*. 2021. #COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy ofDeltaSARS-CoV-2 in a Respiratory Aerosol. In Supercomputing 21: International Conference for High Perfor-mance Computing, Networking, Storage, and Analysis. ACM, New York, NY, USA, 14 pages. https://doi.org/finalDOI

biophysics↗

bioRxiv2021

More than a feeling: scalp EEG and eye correlates of conscious tactile perception

Understanding the neural basis of consciousness is a fundamental goal of neuroscience. Many of the studies tackling this question have focused on conscious perception, but these studies have been largely vision-centric, with very few involving tactile perception. Therefore, we developed a novel tactile threshold perception task, which we used in conjunction with high-density scalp electroencephalography and eye-metric recordings. Participants were delivered threshold-level vibrations to one of the four non-thumb fingers, and were asked to report their perception using a response box. With false discovery rate (FDR) mass univariate analysis procedures, we found significant event-related potentials (ERP) including bilateral N140 and P300 for perceived vibrations; significant bilateral P100 and P300 were found following vibrations that were not perceived. Significant differences between perceived and not perceived trials were found bilaterally in the N140 and P300. Additionally, we found that pupil diameter and blink rate increased and that microsaccade rate decreased following vibrations that were perceived relative to those that were not perceived. While many of the signals are consistent with similar ERP-findings across sensory modalities, our results indicating a significant P300 in not perceived trials raise more questions regarding P300s perceptual meaning. Additionally, our findings support the use of eye metrics as a measure of physiological arousal as pertains to conscious perception, and may represent a novel path toward the creation of tactile no-report tasks in the future. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/466706v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@e4e7fforg.highwire.dtl.DTLVardef@3b3ed0org.highwire.dtl.DTLVardef@198d517org.highwire.dtl.DTLVardef@cddef3_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIA novel tactile perceptual threshold task yields robust behavioral results C_LIO_LIEvent-related potentials differ according to perception status C_LIO_LIP300 is observed in both perceived and not perceived trials C_LIO_LIBlink rate, pupil diameter, and microsaccades differ across trial conditions C_LI

neuroscience↗

bioRxiv2019

Extensive Evaluation of Weighted Ensemble Strategies for Calculating Rate Constants and Binding Affinities of Molecular Association/Dissociation Processes

The weighted ensemble (WE) path sampling strategy is highly efficient in generating pathways and rate constants for rare events using atomistic molecular dynamics simulations. Here we extensively evaluated the impact of several advances to the WE strategy on the efficiency of computing association and dissociation rate constants (kon, koff) as well as binding affinities (KD) for a set of benchmark systems, listed in order of increasing timescales of molecular association/dissociation processes: methane/methane, Na+/Cl-, and K+/18-crown-6 ether. In particular, we assessed the advantages of carrying out (i) a large set of \"light-weight\" WE simulations that each consist of a small number of trajectories vs. a single \"heavy-weight\" WE simulation that consists of a relatively large number of trajectories, (ii) equilibrium vs. steady-state WE simulations, (iii) history augmented Markov State Model (haMSM) post-simulation analysis of equilibrium sets of trajectories, and (iv) tracking of trajectory history (the state last visited) during the dynamics propagation of equilibrium WE simulations. Provided that state definitions are known in advance, our results reveal that heavy-weight, steady-state WE simulations are the most efficient protocol for calculating kon, koff, and KD values. If states are not strictly defined in advance, heavy-weight, equilibrium WE simulations are the most efficient protocol. This efficiency can be further improved with the inclusion of trajectory history during dynamics propagation. In addition, applying the haMSM post-simulation analysis enhances the efficiency of both steady-state and equilibrium WE simulations. Recommendations of appropriate WE protocols are made according to the goals of the simulations (e.g. to efficiently calculate rate constants and/or generate a diverse set of pathways).

biophysics↗