Exploring the Advantages of Quantum Generative Adversarial Networks in Generative Chemistry.

De novo drug design with desired biological activities is crucial for developing novel therapeutics for patients. The drug development process is time- and resource-consuming, and it has a low probability of success. Recent advances in machine learning and deep learning technology have reduced the time and cost of the discovery process and therefore, improved pharmaceutical research and development. In this paper, we explore the combination of two rapidly developing fields with lead candidate discovery in the drug development process. First, artificial intelligence has already been demonstrated to successfully accelerate conventional drug design approaches. Second, quantum computing has demonstrated promising potential in different applications, such as quantum chemistry, combinatorial optimizations, and machine learning. This article explores hybrid quantum-classical generative adversarial networks (GAN) for small molecule discovery. We substituted each element of GAN with a variational quantum circuit (VQC) and demonstrated the quantum advantages in the small drug discovery. Utilizing a VQC in the noise generator of a GAN to generate small molecules achieves better physicochemical properties and performance in the goal-directed benchmark than the classical counterpart. Moreover, we demonstrate the potential of a VQC with only tens of learnable parameters in the generator of GAN to generate small molecules. We also demonstrate the quantum advantage of a VQC in the discriminator of GAN. In this hybrid model, the number of learnable parameters is significantly less than the classical ones, and it can still generate valid molecules. The hybrid model with only tens of training parameters in the quantum discriminator outperforms the MLP-based one in terms of both generated molecule properties and the achieved KL divergence. However, the hybrid quantum-classical GANs still face challenges in generating unique and valid molecules compared to their classical counterparts.

Dynamics of beating cardiac tissue under slow periodic drives.

Effects of mechanical coupling on cardiac dynamics are studied by monitoring the beating dynamics of a cardiac tissue which is being pulled periodically at a pace slower than its intrinsic beating rate. The tissue is taken from the heart of a bullfrog that includes pacemaker cells. The cardiac tissue beats spontaneously with an almost constant interbeat interval (IBI) when there is no external forcing. On the other hand, the IBI is observed to vary significantly under an external periodic drive. Interestingly, when the period of the external drive is about two times the intrinsic IBI of the tissue without pulling, the IBI as a function of time exhibits a wave packet structure. Our experimental results can be understood theoretically by a phase-coupled model under external driving. In particular, the theoretical prediction of the wave-packet period as a function of the normalized driving period agrees excellently with the observations. Furthermore, the cardiac mechanical coupling constant can be extracted from the experimental data from our model and is found to be insensitive to the external driving period. Implications of our results on cardiac physiology are also discussed.

Fractal Regulation in Temporal Activity Fluctuations: A Biomarker for Circadian Control and Beyond.

Motor activity in humans and other animals possesses fractal temporal fluctuations that co-exists with circadian or daily activity rhythms. The perturbations in fractal activity patterns are often accompanied by altered circadian/daily rhythms. The goal of this study is to test whether fractal regulation in motor activity provides physiological information independent from 24-h/circadian rhythmicity. To achieve the goal, we studied locomotor activity recordings of rats with the lesion of the suprachiasmatic nucleus (SCN) that are known to have diminished circadian/daily activity rhythms and perturbed fractal regulation. By restricting feeding time (i.e., food was only availability in the dark period of the 12h: 12h light-dark cycles), we found that mean activity levels in these animals displayed significant 24-h rhythms. In contrast, the restricted feeding had no influences on the perturbed fractal regulation in these SCN-lesioned animals, i.e., activity fluctuations in these animals remained random over a wide range of time scales from 2-20h. Our results indicate that 24-h rhythm of food availability can restore/improve circadian/daily rhythms in the SCN-lesioned animals but not necessarily improve the disrupted fractal activity regulation in these animals. This study provides clear and direct evidence that fractal activity patterns offer complementary information about motor activity regulation at multiple time scales that is beyond 24-h rhythm control.

Mechanisms of fast and stringent search in homologous pairing of double-stranded DNA.

Self-organization in the cell relies on the rapid and specific binding of molecules to their cognate targets. Correct bindings must be stable enough to promote the desired function even in the crowded and fluctuating cellular environment. In systems with many nearly matched targets, rapid and stringent formation of stable products is challenging. Mechanisms that overcome this challenge have been previously proposed, including separating the process into multiple stages; however, how particular in vivo systems overcome the challenge remains unclear. Here we consider a kinetic system, inspired by homology dependent pairing between double stranded DNA in bacteria. By considering a simplified tractable model, we identify different homology testing stages that naturally occur in the system. In particular, we first model dsDNA molecules as short rigid rods containing periodically spaced binding sites. The interaction begins when the centers of two rods collide at a random angle. For most collision angles, the interaction energy is weak because only a few binding sites near the collision point contribute significantly to the binding energy. We show that most incorrect pairings are rapidly rejected at this stage. In rare cases, the two rods enter a second stage by rotating into parallel alignment. While rotation increases the stability of matched and nearly matched pairings, subsequent rotational fluctuations reduce kinetic trapping. Finally, in vivo chromosome are much longer than the persistence length of dsDNA, so we extended the model to include multiple parallel collisions between long dsDNA molecules, and find that those additional interactions can greatly accelerate the searching.

Interactive Effects of Dorsomedial Hypothalamic Nucleus and Time-Restricted Feeding on Fractal Motor Activity Regulation.

One evolutionary adaptation in motor activity control of animals is the anticipation of food that drives foraging under natural conditions and is mimicked in laboratory with daily scheduled food availability. Food anticipation is characterized by increased activity a few hours before the feeding period. Here we report that 2-h food availability during the normal inactive phase of rats not only increases activity levels before the feeding period but also alters the temporal organization of motor activity fluctuations over a wide range of time scales from minutes up to 24 h. We demonstrate this multiscale alteration by assessing fractal patterns in motor activity fluctuations-similar fluctuation structure at different time scales-that are robust in intact animals with ad libitum food access but are disrupted under food restriction. In addition, we show that fractal activity patterns in rats with ad libitum food access are also perturbed by lesion of the dorsomedial hypothalamic (DMH)-a neural node that is involved in food anticipatory behavior. Instead of further disrupting fractal regulation, food restriction restores the disrupted fractal patterns in these animals after the DMH lesion despite the persistence of the 24-h rhythms. This compensatory effect of food restriction is more clearly pronounced in the same animals after the additional lesion of the suprachiasmatic nucleus (SCN)-the central master clock in the circadian system that generates and orchestrates circadian rhythms in behavior and physiological functions in synchrony with day-night cycles. Moreover, all observed influences of food restriction persist even when data during the food anticipatory and feeding period are excluded. These results indicate that food restriction impacts dynamics of motor activity at different time scales across the entire circadian/daily cycle, which is likely caused by the competition between the food-induced time cue and the light-entrained circadian rhythm of the SCN. The differential impacts of food restriction on fractal activity control in intact and DMH-lesioned animals suggest that the DMH plays a crucial role in integrating these different time cues to the circadian network for multiscale regulation of motor activity.

Anterior Insula Regulates Multiscale Temporal Organization of Sleep and Wake Activity.

The role of specific cortical regions in sleep-regulating circuits is unclear. The anterior insula (AI) has strong reciprocal connectivity with wake and sleep-promoting hypothalamic and brainstem regions, and we hypothesized that the AI regulates patterns of sleep and wakefulness. To test this hypothesis, we lesioned the AI in rats (n = 8) and compared sleep, wake, and activity regulation in these animals with nonlesioned controls (n = 8) with 24-h sleep recordings and chronic infrared activity monitoring. Compared to controls, animals with AI lesions had decreased wakefulness and increased rapid eye movement (REM) sleep and non-REM (NREM) sleep. AI-lesioned animals had shorter wake bouts, especially during the active dark phase. AI-lesioned animals also had more transitions from NREM to REM sleep, especially during the inactive light phase. Chronic infrared monitoring revealed that AI-lesioned animals also had a disturbed temporal organization of locomotor activity at multiple time scales with more random activity fluctuations from 4 to 12 h despite intact circadian rhythms. These results suggest that the AI regulates sleep and activity and contributes to the regulation of sleep and motor behavior rhythmicity across multiple time scales. Dysfunction of the AI may underlie changes in sleep-wake patterns in neurological diseases.

Suprachiasmatic neuron numbers and rest-activity circadian rhythms in older humans.

The suprachiasmatic nucleus (SCN) of the hypothalamus, the master mammalian circadian pacemaker, synchronizes endogenous rhythms with the external day-night cycle. Older humans, particularly those with Alzheimer disease (AD), often have difficulty maintaining normal circadian rhythms compared to younger adults, but the basis of this change is unknown. We report that the circadian rhythm amplitude of motor activity in both AD subjects and age-matched controls is correlated with the number of vasoactive intestinal peptide-expressing SCN neurons. AD was additionally associated with delayed circadian phase compared to cognitively healthy subjects, suggesting distinct pathologies and strategies for treating aging- and AD-related circadian disturbances.

Simple models for quorum sensing: nonlinear dynamical analysis.

Quorum sensing refers to the change in the cooperative behavior of a collection of elements in response to the change in their population size or density. This behavior can be observed in chemical and biological systems. These elements or cells are coupled via chemicals in the surrounding environment. Here we focus on the change of dynamical behavior, in particular from quiescent to oscillatory, as the cell population changes. For instance, the silent behavior of the elements can become oscillatory as the system concentration or population increases. In this work, two simple models are constructed that can produce the essential representative properties in quorum sensing. The first is an excitable or oscillatory phase model, which is probably the simplest model one can construct to describe quorum sensing. Using the mean-field approximation, the parameter regime for quorum sensing behavior can be identified, and analytical results for the detailed dynamical properties, including the phase diagrams, are obtained and verified numerically. The second model consists of FitzHugh-Nagumo elements coupled to the signaling chemicals in the environment. Nonlinear dynamical analysis of this mean-field model exhibits rich dynamical behaviors, such as infinite period bifurcation, supercritical Hopf, fold bifurcation, and subcritical Hopf bifurcations as the population parameter changes for different coupling strengths. Analytical result is obtained for the Hopf bifurcation phase boundary. Furthermore, two elements coupled via the environment and their synchronization behavior for these two models are also investigated. For both models, it is found that the onset of oscillations is accompanied by the synchronized dynamics of the two elements. Possible applications and extension of these models are also discussed.

Frequency enhancement in coupled noisy excitable elements.

Oscillatory dynamics of coupled excitable FitzHugh-Nagumo elements in the presence of noise is investigated as a function of the coupling strength g. For two such coupled elements, their frequencies are enhanced and will synchronize at a frequency higher than the uncoupled frequencies of each element. As g increases, there is an unexpected peak in the frequency enhancement before reaching synchronization. The results can be understood with an analytic model based on the excitation across a potential barrier whose height is controlled by g. Simulation results of a coupled square lattice can quantitatively reproduce the unexpected peak in the variation of the beating rates observed in cultured cardiac cells experiments.