VAL1 as an assembly platform co-ordinating co-transcriptional repression and chromatin regulation at Arabidopsis FLC

Polycomb (PcG) silencing is crucial for development across eukaryotes, but how PcG targets are regulated is still incompletely understood. The slow timescale of cold-induced PcG silencing at Arabidopsis thaliana FLOWERING LOCUS C (FLC) makes it an excellent system to dissect this mechanism. Binding of the DNA binding protein VAL1 to an FLC intronic RY motif within the PcG nucleation region is an early step in the silencing process. VAL1 interacts with APOPTOSIS AND SPLICING ASSOCIATED PROTEIN (ASAP) complex and POLYCOMB REPRESSIVE COMPLEX 1 (PRC1). Here, we show that ASAP and PRC1 function as co-repressors that quantitatively regulate FLC transcription. Upon the shift to cold PRC1-mediated H2Aub accumulates only at the nucleation region, is transiently maintained after transfer back to warm, but unlike the PRC2-delivered H3K27me3 does not spread across the locus. H2K27me3 thus provides long-term epigenetic silencing, whereas H2Aub is a transient repression signal. Overall, our work highlights how a DNA sequence-specific binding protein can act as an assembly platform co-ordinating the co-transcriptional repression and chromatin regulation necessary for Polycomb silencing.

Disentangling how multiple traits drive 2 strain frequencies in SIS dynamics with coinfection

A general theory for competitive dynamics among many strains at the epidemiological level is required to understand polymorphisms in virulence, transmissibility, antibiotic resistance and other biological traits of infectious agents. Mathematical coinfection models have addressed specific systems, focusing on the criteria leading to stable coexistence or competitive exclusion, however, due to their complexity and nonlinearity, analytical solutions in coinfection models remain rare. Here we study a 2-strain SIS compartmental model with co-infection/co-colonization, incorporating multiple fitness dimensions under the same framework: variation in transmissibility, duration of carriage, pairwise susceptibilities to coinfection, coinfection duration, and transmission priority effects from mixed coinfection. Taking advantage of a singular perturbation approach, under the assumption of strain similarity, we expose how strain dynamics on a slow timescale are explicitly governed by a replicator equation which encapsulates all traits and their interplay. This allows us to predict explicitly not only the final epidemiological outcome of a given 2-player competition, but moreover, their entire frequency dynamics as a direct function of their relative variation and of strain-transcending global parameters. Based on mutual invasion fitnesses, we analyze and report rigorous results on transition phenomena in the 2-strain system, strongly mediated via coinfection prevalence. This framework offers a deeper analytical understanding of 2-strain competitive games in coinfection, with applications to virulence, interventions, antibiotic resistance, and social evolution theory.

Two timescales control the creation of large protein aggregates in cells

Protein aggregation is of particular interest due to its connection with many diseases and disorders. Many factors can alter the dynamics and result of this process, one of them being the diffusivity of the monomers and aggregates in the system. Here, we study experimentally and theoretically an aggregation process in cells, and we identify two distinct physical timescales that set the number and size of aggregates. The first timescale involves fast aggregation of small clusters freely diffusing in the cytoplasm, while, in the second one, the aggregates are larger than the pore size of the cytoplasm and thus barely diffuse, and the aggregation process is slowed down. However, the process is not entirely halted, potentially reflecting a myriad of active but random forces forces that stir the aggregates. Such slow timescale is essential to account for the experimental results of the aggregation process. These results could also have implications in other processes of spatial organization in cell biology, such as phase-separated droplets.

A clock for the Sun's magnetic Hale cycle and 27 day recurrences in the aa geomagnetic index

<p>We construct a new solar cycle phase clock which maps each of the last 18 solar cycles onto a single normalized epoch for the approximately 22 year Hale (magnetic polarity) cycle, using the Hilbert transform of daily sunspot numbers (SSN) since 1818. We use the clock to study solar and geomagnetic climatology as seen in datasets available over multiple solar cycles. The occurrence of solar maxima on the clock shows almost no Hale cycle dependence, confirming that the clock is synchronized with polarity reversals.  The odd cycle minima lead the even cycle minima by ~ 1.1 normalized years, whereas the odd cycle terminators (when sunspot bands from opposite hemispheres have moved to the equator and coincide, thus terminating the cycle, McIntosh(2019)) lag the even cycle terminators  by ~ 2.3 normalized years.  The average interval between each minimum and terminator  is thus relatively extended for odd cycles and shortened for even ones. We re-engineer the R27 index that was orignally proposed by Sargent(1985) to parameterize 27 day recurrences in the aa index. We perform an epoch analysis of autocovariance in the aa index using the Hale cycle clock to obtain a high time resolution parameter for 27 day recurrence, <acv(27)>. This reveals that the transition to recurrence, that is, to an ordered solar wind dominated by high speed streams, is fast, occurring within 2-3 solar rotations or less. It resolves an extended late declining phase which is approximately twice as long on even Schwabe cycles as odd ones. We find that Galactic Cosmic Ray flux rises in step with <acv(27)> but then stays high. Our analysis also identifies a slow timescale trend in SSN that simply tracks the Gleissberg cycle. We find that this trend is in phase with the slow timescale trend in the modulus of sunspot latitudes, and in antiphase with that of the R27 index.</p>

A Multi-Timescale Bilinear Model for Optimization and Control of HVAC Systems with Consistency

Reducing the energy consumption of the heating, ventilation, and air conditioning (HVAC) systems while ensuring users’ comfort is of both academic and practical significance. However, the-state-of-the-art of the optimization model of the HVAC system is that either the thermal dynamic model is simplified as a linear model, or the optimization model of the HVAC system is single-timescale, which leads to heavy computation burden. To balance the practicality and the overhead of computation, in this paper, a multi-timescale bilinear model of HVAC systems is proposed. To guarantee the consistency of models in different timescales, the fast timescale model is built first with a bilinear form, and then the slow timescale model is induced from the fast one, specifically, with a bilinear-like form. After a simplified replacement made for the bilinear-like part, this problem can be solved by a convexification method. Extensive numerical experiments have been conducted to validate the effectiveness of this model.

Theta and alpha power across fast and slow timescales in cognitive control

Theta and alpha frequency neural oscillations are important for learning and cognitive control, but their exact role has remained obscure. In particular, it is unknown whether they operate at similar timescales, and whether they support different cognitive processes. We recorded EEG in 30 healthy human participants while they performed a procedural learning task containing both novel (block-unique) and repeating stimuli. We investigated behavior and electrophysiology at both fast (i.e., within blocks) and slow (i.e., between blocks) time scales. Behaviorally, both response time and accuracy improved over both fast and slow timescales. At the same time, on the spectral level, theta power significantly decreased along the slow timescale, whereas alpha power instead significantly increased along the fast timescale. We thus demonstrate that theta and alpha both play a role during learning, but operate at different timescales. This result poses important empirical constraints for theories on learning, cognitive control, and neural oscillations.

Correlating structural changes with the photophysics of terrylenediimide films during spontaneous annealing

Films of consisting of a rigid extended aromatic surface and long alkyl chains to undergo structural rearrangement at room temperature. The slow timescale allows us to monitor the relationship of structure and photophysical behavior.

Predicting N-strain coexistence from co-colonization interactions: epidemiology meets ecology and the replicator equation

Multi-type spreading processes are ubiquitous in ecology, epidemiology and social systems, but remain hard to model mathematically and to understand on a fundamental level. Here, we describe and study a multi-type susceptible-infected-susceptible (SIS) model that allows for up to two co-infections of a host. Fitness differences between N infectious agents are mediated through altered susceptibilities to secondary infections that depend on colonizer- co-colonizer interactions. By assuming small differences between such pairwise traits (and other infection parameters equal), we derive a model reduction framework using separation of timescales. This ‘quasi-neutrality’ in strain space yields a fast timescale where all types behave as neutral, and a slow timescale where non-neutral dynamics take place. On the slow timescale, N equations govern strain frequencies and accurately approximate the dynamics of the full system with O(N2) variables. We show that this model reduction coincides with a special case of the replicator equation, which, in our system, emerges in terms of the pairwise invasion fitnesses among strains. This framework allows to build the multi-type community dynamics bottom-up from only pairwise outcomes between constituent members. We find that mean fitness of the multi-strain system, changing with individual frequencies, acts equally upon each type, and is a key indicator of system resistance to invasion. Besides efficient computation and complexity reduction, these results open new perspectives into high-dimensional community ecology, detection of species interactions, and evolution of biodiversity, with applications to other multi-type biological contests. By uncovering the link between an epidemiological system and the replicator equation, we also show our co-infection model relates to Fisher’s fundamental theorem and to conservative Lotka-Volterra systems.

Associations Between Slow- and Fast-Timescale Indicators of Emotional Functioning

“Core affect”—defined as momentary valence (pleasantness) and arousal (activation) levels—plays an important role in our emotional experiences. We examined the relationship between the “fast-timescale” (moment-to-moment) changes in core affect and “slow-timescale” (trait-level) indicators of emotional functioning. Results from an experience sampling study showed that daily valence and arousal baselines were positively related to emotional well-being. Furthermore, we found meaningful positive associations between fast-timescale core affect regulation and the habitual deployment of reappraisal as emotion regulation strategy.