Mass spectrometry (MS) has many advantages as a quantitative detection technology for applications within drug discovery. However, current methods of liquid sample introduction to a detector are slow ...and limit the use of mass spectrometry for kinetic and high-throughput applications. We present the development of an acoustic mist ionization (AMI) interface capable of contactless nanoliter-scale “infusion” of up to three individual samples per second into the mass detector. Installing simple plate handling automation allowed us to reach a throughput of 100 000 samples per day on a single mass spectrometer. We applied AMI-MS to identify inhibitors of a human histone deacetylase from AstraZeneca’s collection of 2 million small molecules and measured their half-maximal inhibitory concentration. The speed, sensitivity, simplicity, robustness, and consumption of nanoliter volumes of sample suggest that this technology will have a major impact across many areas of basic and applied research.
The ongoing COVID-19 pandemic underscores the importance of developing reliable forecasts that would allow decision makers to devise appropriate response strategies. Despite much recent research on ...the topic, epidemic forecasting remains poorly understood. Researchers have attributed the difficulty of forecasting contagion dynamics to a multitude of factors, including complex behavioral responses, uncertainty in data, the stochastic nature of the underlying process, and the high sensitivity of the disease parameters to changes in the environment. We offer a rigorous explanation of the difficulty of short-term forecasting on networked populations using ideas from computational complexity. Specifically, we show that several forecasting problems (e.g., the probability that at least a given number of people will get infected at a given time and the probability that the number of infections will reach a peak at a given time) are computationally intractable. For instance, efficient solvability of such problems would imply that the number of satisfying assignments of an arbitrary Boolean formula in conjunctive normal form can be computed efficiently, violating a widely believed hypothesis in computational complexity. This intractability result holds even under the ideal situation, where all the disease parameters are known and are assumed to be insensitive to changes in the environment. From a computational complexity viewpoint, our results, which show that contagion dynamics become unpredictable for both macroscopic and individual properties, bring out some fundamental difficulties of predicting disease parameters. On the positive side, we develop efficient algorithms or approximation algorithms for restricted versions of forecasting problems.
To take full advantage of advanced data collection techniques and high beam flux at next‐generation macromolecular crystallography beamlines, rapid and reliable methods will be needed to mount and ...align many samples per second. One approach is to use an acoustic ejector to eject crystal‐containing droplets onto a solid X‐ray transparent surface, which can then be positioned and rotated for data collection. Proof‐of‐concept experiments were conducted at the National Synchrotron Light Source on thermolysin crystals acoustically ejected onto a polyimide `conveyor belt'. Small wedges of data were collected on each crystal, and a complete dataset was assembled from a well diffracting subset of these crystals. Future developments and implementation will focus on achieving ejection and translation of single droplets at a rate of over one hundred per second.
Nested canalyzing functions (NCFs) are a class of Boolean functions which are used to model certain biological phenomena. We derive a complete characterization of NCFs with the largest average ...sensitivity, expressed in terms of a simple structural property of the NCF. This characterization provides an alternate, but elementary, proof of the tight upper bound on the average sensitivity of any NCF established by Klotz et al. (2013). We also utilize the characterization to derive a closed form expression for the number of NCFs that have the largest average sensitivity.
X-ray free-electron lasers (XFELs) provide very intense X-ray pulses suitable for macromolecular crystallography. Each X-ray pulse typically lasts for tens of femtoseconds and the interval between ...pulses is many orders of magnitude longer. Here we describe two novel acoustic injection systems that use focused sound waves to eject picoliter to nanoliter crystal-containing droplets out of microplates and into the X-ray pulse from which diffraction data are collected. The on-demand droplet delivery is synchronized to the XFEL pulse scheme, resulting in X-ray pulses intersecting up to 88% of the droplets. We tested several types of samples in a range of crystallization conditions, wherein the overall crystal hit ratio (e.g., fraction of images with observable diffraction patterns) is a function of the microcrystal slurry concentration. We report crystal structures from lysozyme, thermolysin, and stachydrine demethylase (Stc2). Additional samples were screened to demonstrate that these methods can be applied to rare samples.
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•Acoustic methods inject crystal-containing droplets directly from microplate wells•On-demand acoustic injection uses crystals efficiently without orifices or clogging•Diffraction patterns from crystals measuring several tens of μm are of high quality•Complete datasets can be obtained from fewer than 50,000 crystals
Acoustic droplet ejection provides an automated tool for efficient use of protein crystals in SFX experiments. Roessler et al. used this method to deliver crystal-containing droplets into the XFEL beam to coincide with each X-ray pulse.
Acoustic liquid handling uses high-frequency acoustic signals that are focused on the surface of a fluid to eject droplets with high accuracy and precision for various life science applications. Here ...we present a multiwell source plate, the Echo Qualified Reservoir (ER), which can acoustically transfer over 2.5 mL of fluid per well in 25-nL increments using an Echo 525 liquid handler. We demonstrate two Labcyte technologies-Dynamic Fluid Analysis (DFA) methods and a high-voltage (HV) grid-that are required to maintain accurate and precise fluid transfers from the ER at this volume scale. DFA methods were employed to dynamically assess the energy requirements of the fluid and adjust the acoustic ejection parameters to maintain a constant velocity droplet. Furthermore, we demonstrate that the HV grid enhances droplet velocity and coalescence at the destination plate. These technologies enabled 5-µL per destination well transfers to a 384-well plate, with accuracy and precision values better than 4%. Last, we used the ER and Echo 525 liquid handler to perform a quantitative polymerase chain reaction (qPCR) assay to demonstrate an application that benefits from the flexibility and larger volume capabilities of the ER.
Symmetry Properties of Nested Canalyzing Functions Rosenkrantz, Daniel J; Marathe, Madhav V; Ravi, S.S ...
Discrete Mathematics and Theoretical Computer Science,
08/2019, Letnik:
21, Številka:
4
Journal Article
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Many researchers have studied symmetry properties of various Boolean functions. A class of Boolean functions, called nested canalyzing functions (NCFs), has been used to model certain biological ...phenomena. We identify some interesting relationships between NCFs, symmetric Boolean functions and a generalization of symmetric Boolean functions, which we call r-symmetric functions (where r is the symmetry level). Using a normalized representation for NCFs, we develop a characterization of when two variables of an NCF are symmetric. Using this characterization, we show that the symmetry level of an NCF f can be easily computed given a standard representation of f. We also present an algorithm for testing whether a given r-symmetric function is an NCF. Further, we show that for any NCF f with n variables, the notion of strong asymmetry considered in the literature is equivalent to the property that f is n-symmetric. We use this result to derive a closed form expression for the number of n-variable Boolean functions that are NCFs and strongly asymmetric. We also identify all the Boolean functions that are NCFs and symmetric.
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Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
During the height of the Cold War, between 1965 and 1968, Robert Aumann, Michael Maschler, and Richard Stearns collaborated on research on the dynamics of arms control negotiations that has since ...become foundational to work on repeated games. These five seminal papers are collected here for the first time, with the addition of "postscripts" describing many of the developments since the papers were written. The basic model studied throughout the book is one in which players ignorant about the game being played must learn what they can from the actions of the others. The original work, done under contract to the United States Arms Control and Disarmament Agency, was intended to tackle the gradual disarmament problem, in which neither player knew what his own payoff would be for any given agreement, because of uncertainty about the other side's arsenal and weapons production technology. But the research soon became much more generalized, covering information concealment and revelation, signaling and learning, and related ideas in any repeated competitive situation. The first four chapters of the book treat the competitive zero-sum side of the theory of repeated games. Chapter five takes up cooperative phenomena where one player may want to signal information to another. An extensive bibliography covers all items mentioned in the main text, in the postscripts, and in the introduction. The bibliography also includes a compilation of published papers and books that refer to the original reports.
Motivated by applications such as the spread of epidemics and the propagation of influence in social networks, we propose a formal model for analyzing the dynamics of such networks. Our model is a ...stochastic version of discrete graphical dynamical systems. Using this model, we formulate and study the computational complexity of two fundamental problems (called reachability and predecessor existence problems) which arise in the context of social networks. We also address other problems that deal with the time evolution of such stochastic dynamical systems. Further, we point out the implications of our results to problems for other computational models such as Hopfield networks, communicating finite state machines and systolic arrays. In particular, our polynomial time algorithms for the predecessor existence problem for stochastic dynamical systems imply similar results for one-dimensional finite cellular automata.
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