Requirements for mammalian promoters to decode transcription factor dynamics

In response to different stimuli many transcription factors (TFs) display different activation dynamics that trigger the expression of specific sets of target genes, suggesting that promoters have a way to decode them. Combining optogenetics, deep learning-based image analysis and mathematical modeling, we find that decoding of TF dynamics occurs only when the coupling between TF binding and transcription pre-initiation complex formation is inefficient and that the ability of a promoter to decode TF dynamics gets amplified by inefficient translation initiation. Furthermore, we propose a theoretical mechanism based on phase separation that would allow a promoter to be activated better by pulsatile than sustained TF signals. These results provide an understanding on how TF dynamics are decoded in mammalian cells, which is important to develop optimal strategies to counteract disease conditions, and suggest ways to achieve multiplexing in synthetic pathways.

Oculo-retinal dynamics can explain the perception of minimal recognizable configurations

Natural vision is a dynamic and continuous process. Under natural conditions, visual object recognition typically involves continuous interactions between ocular motion and visual contrasts, resulting in dynamic retinal activations. In order to identify the dynamic variables that participate in this process and are relevant for image recognition, we used a set of images that are just above and below the human recognition threshold and whose recognition typically requires >2 s of viewing. We recorded eye movements of participants while attempting to recognize these images within trials lasting 3 s. We then assessed the activation dynamics of retinal ganglion cells resulting from ocular dynamics using a computational model. We found that while the saccadic rate was similar between recognized and unrecognized trials, the fixational ocular speed was significantly larger for unrecognized trials. Interestingly, however, retinal activation level was significantly lower during these unrecognized trials. We used retinal activation patterns and oculomotor parameters of each fixation to train a binary classifier, classifying recognized from unrecognized trials. Only retinal activation patterns could predict recognition, reaching 80% correct classifications on the fourth fixation (on average, ∼2.5 s from trial onset). We thus conclude that the information that is relevant for visual perception is embedded in the dynamic interactions between the oculomotor sequence and the image. Hence, our results suggest that ocular dynamics play an important role in recognition and that understanding the dynamics of retinal activation is crucial for understanding natural vision.

A New Muscle Activation Dynamics Model, That Simulates the Calcium Kinetics and Incorporates the Role of Store-Operated Calcium Entry Channels, to Enhance the EMG-Driven Hill-type Models

Hill-type models are frequently used in biomechanical simulations. They are attractive for their low computational cost and close relation to commonly measured musculotendon parameters. Still, more attention is needed to improve the activation dynamics of the model specifically because of the nonlinearity observed in the EMG-Force relation. Moreover, one of the important and practical questions regarding the assessment of the model's performance is how adequately can the model simulate any fundamental type of human movement without modifying model parameters for different tasks? This paper tries to answer this question by proposing a simple physiologically based activation dynamics model. The model describes the ?kinetics of the calcium dynamics while activating and deactivating the muscle contraction process. Hence, it allowed simulating the recently discovered role of store-operated calcium entry (SOCE) channels as immediate counter-flux to calcium loss across the tubular system during excitation-contraction coupling. By comparing the ability to fit experimental data without readjusting the parameters, the proposed model has proven to have more steady performance than phenomenologically based models through different submaximal isometric contraction levels. This model indicates that more physiological insights is key for improving Hill-type model performance.

Characterization of Potency of the P2Y13 Receptor Agonists: A Meta-Analysis

P2Y13 is an ADP-stimulated G-protein coupled receptor implicated in many physiological processes, including neurotransmission, metabolism, pain, and bone homeostasis. Quantitative understanding of P2Y13 activation dynamics is important for translational studies. We systematically identified PubMed annotated studies that characterized concentration-dependence of P2Y13 responses to natural and synthetic agonists. Since the comparison of the efficacy (maximum response) is difficult for studies performed in different systems, we normalized the data and conducted a meta-analysis of EC50 (concentration at half-maximum response) and Hill coefficient (slope) of P2Y13-mediated responses to different agonists. For signaling events induced by heterologously expressed P2Y13, EC50 of ADP-like agonists was 17.2 nM (95% CI: 7.7–38.5), with Hills coefficient of 4.4 (95% CI: 3.3–5.4), while ATP-like agonists had EC50 of 0.45 μM (95% CI: 0.06–3.15). For functional responses of endogenously expressed P2Y13, EC50 of ADP-like agonists was 1.76 μM (95% CI: 0.3–10.06). The EC50 of ADP-like agonists was lower for the brain P2Y13 than the blood P2Y13. ADP-like agonists were also more potent for human P2Y13 compared to rodent P2Y13. Thus, P2Y13 appears to be the most ADP-sensitive receptor characterized to date. The detailed understanding of tissue- and species-related differences in the P2Y13 response to ADP will improve the selectivity and specificity of future pharmacological compounds.

Microstates and power envelope hidden Markov modeling probe bursting brain activity at different timescales

State modeling of whole-brain electroencephalography (EEG) or magnetoencephalography (MEG) allows to investigate transient, recurring neurodynamical events. Two widely-used techniques are the microstate analysis of EEG signals and hidden Markov modeling (HMM) of MEG power envelopes. Both reportedly lead to similar state lifetimes on the 100 ms timescale, suggesting a common neural basis. We addressed this issue by using simultaneous MEG/EEG recordings at rest and comparing the spatial signature and temporal activation dynamics of microstates and power envelope HMM states obtained separately from EEG and MEG. Results showed that microstates and power envelope HMM states differed both spatially and temporally. Microstates tend to exhibit spatio-temporal locality, whereas power envelope HMM states disclose network-level activity with 100–200 ms lifetimes. Further, MEG microstates do not correspond to the canonical EEG microstates but are better interpreted as split HMM states. On the other hand, both MEG and EEG HMM states involve the (de)activation of similar functional networks. Microstate analysis and power envelope HMM thus appear sensitive to neural events occurring over different spatial and temporal scales. As such, they represent complementary approaches to explore the fast, sub-second scale bursting electrophysiological dynamics in spontaneous human brain activity.

A fair and EMG-validated comparison of recruitment criteria, musculotendon models and muscle coordination strategies, for the inverse-dynamics based optimization of muscle forces during gait

Experimental studies and EMG collections suggest that a specific strategy of muscle coordination is chosen by the central nervous system to perform a given motor task. A popular mathematical approach for solving the muscle recruitment problem is optimization. Optimization-based methods minimize or maximize some criterion (objective function or cost function) which reflects the mechanism used by the central nervous system to recruit muscles for the movement considered. The proper cost function is not known a priori, so the adequacy of the chosen function must be validated according to the obtained results. In addition of the many criteria proposed, several physiological representations of the musculotendon actuator dynamics (that prescribe constraints for the forces) along with different musculoskeletal models can be found in the literature, which hinders the selection of the best neuromusculotendon model for each application. Seeking to provide a fair base for comparison, this study measures the efficiency and accuracy of: (i) four different criteria within the static optimization approach (where the physiological character of the muscle, which affects the constraints of the forces, is not considered); (ii) three physiological representations of the musculotendon actuator dynamics: activation dynamics with elastic tendon, simplified activation dynamics with rigid tendon and rigid tendon without activation dynamics; (iii) a synergy-based method; all of them within the framework of inverse-dynamics based optimization. Motion/force/EMG gait analyses were performed on ten healthy subjects. A musculoskeletal model of the right leg actuated by 43 Hill-type muscles was scaled to each subject and used to calculate joint moments, musculotendon kinematics and moment arms. Muscle activations were then estimated using the different approaches, and these estimates were compared with EMG measurements. Although no significant differences were obtained with all the methods at statistical level, it must be pointed out that a higher complexity of the method does not guarantee better results, as the best correlations with experimental values were obtained with two simplified approaches: the static optimization and the physiological approach with simplified activation dynamics and rigid tendon, both using the sum of the squares of muscle forces as objective function.

Cracking Prosody in Articulatory Phonology

Articulatory Phonology advances an account of phonological structure in which dynamically defined vocal tract tasks—gestures—are simultaneously and isomorphically units of cognitive representation and units of physical action. This paradigm has fundamentally altered our understanding of the linguistic representation of words. This article reviews the relatively recent incorporation of prosody into Articulatory Phonology. A capsule review of the Articulatory Phonology theoretical framework is presented, and the notions of phrasal and prominence organization are introduced as the key aspects of linguistic prosodic structure under consideration. Parameter dynamics, activation dynamics, and prosodic modulation gestures, such as the π-gesture, are outlined. The review is extended to touch on rhythm, intonation, and pauses and to consider innovations for integrating multiple aspects of prosodic structure under this dynamical approach. Finally, a range of questions emerges, crystallizing outstanding issues ranging from the abstract and theoretical to the interactive and functional.

Axonal blockage with microscopic magnetic stimulation

Numerous neurological dysfunctions are characterized by undesirable nerve activity. By providing reversible nerve blockage, electric stimulation with an implanted electrode holds promise in the treatment of these conditions. However, there are several limitations to its application, including poor bio-compatibility and decreased efficacy during chronic implantation. A magnetic coil of miniature size can mitigate some of these problems, by coating it with biocompatible material for chronic implantation. However, it is unknown if miniature coils could be effective in axonal blockage and, if so, what the underlying mechanisms are. Here we demonstrate that a submillimeter magnetic coil can reversibly block action potentials in the unmyelinated axons from the marine mollusk Aplysia californica. Using a multi-compartment model of the Aplysia axon, we demonstrate that the miniature coil causes a significant local depolarization in the axon, alters activation dynamics of the sodium channels, and prevents the traveling of the invading action potentials. With improved biocompatibility and capability of emitting high-frequency stimuli, micro coils provide an interesting alternative for electric blockage of axonal conductance in clinical settings.