Distinct Activity States Research Articles

A Multiwavelength Study to Decipher the 2017 Flare of the Blazar OJ 287

In 2017 February, the blazar OJ 287 underwent a period of intense multiwavelength activity. It reached a new historic peak in the soft X-ray (0.3–10 keV) band, as measured by the Swift X-ray Telescope. This event coincides with a very-high-energy (VHE) γ-ray outburst that led VERITAS to detect emission above 100 GeV, with a detection significance of 10σ (from 2016 December 9 to 2017 March 31). The time-averaged VHE γ-ray spectrum was consistent with a soft power law (Γ = −3.81 ± 0.26) and an integral flux corresponding to ∼2.4% that of the Crab Nebula above the same energy. Contemporaneous data from multiple instruments across the electromagnetic spectrum reveal a complex flaring behavior, primarily in the soft X-ray and VHE bands. To investigate the possible origin of such an event, our study focuses on three distinct activity states: before, during, and after the 2017 February peak. The spectral energy distributions during these periods suggest the presence of at least two nonthermal emission zones, with the more compact one responsible for the observed flare. Broadband modeling results and observations of a new radio knot in the jet of OJ 287 in 2017 are consistent with a flare originating from a strong recollimation shock outside the radio core.

Player Activity and Load Profiling with Hidden Markov Models: A Novel Application in Rugby League

ABSTRACT Player movement in rugby league is complex, being spatiotemporal and multifaceted. Modeling this complexity to provide robust measures of player activity and load has proved difficult, with important aspects of player movement yet to be considered. These include the influence of time-varying covariates on player activity and the combination of different dimensions of player movement. Few studies have simultaneously categorized player activity into different activity states and investigated factors influencing the transition between states, or compared player activity and load profiles between matches and training. This study applied hidden Markov models (HMMs)—a data-driven, multivariate approach—to rugby league training and match GPS data to i) demonstrate how HMMs can combine multiple variables in a data-driven way to effectively categorize player movement states, ii) investigate the influence of two time-varying covariates, score difference and elapsed match time on player activity states, and iii) compare player activity and load profiles within and between training and match modalities. HMMs were fitted to player GPS, accelerometer and heart rate data of one English Super League team across 60 training sessions and 35 matches. Distinct activity states were detected for both matches and training, with transitions between states in matches influenced by score difference and elapsed time and clear differences in activity and load profiles between training and matches. HMMs can model the complexity of player movement to effectively profile player activity and load in rugby league and have the potential to facilitate new research across several sports.

Illuminating Protein Allostery by Chemically Accurate Contact Response Analysis (ChACRA).

Decoding allostery at the atomic level is essential for understanding the relationship between a protein's sequence, structure, and dynamics. Recently, we have shown that decomposing temperature responses of inter-residue contacts can reveal allosteric couplings and provide useful insight into the functional dynamics of proteins. The details of this Chemically Accurate Contact Response Analysis (ChACRA) are presented here along with its application to two well-known allosteric proteins. The first protein, IGPS, is a model of ensemble allostery that lacks clear structural differences between the active and inactive states. We show that the application of ChACRA reveals the experimentally identified allosteric coupling between effector and active sites of IGPS. The second protein, ATCase, is a classic example of allostery with distinct active and inactive structural states. Using ChACRA, we directly identify the most significant residue level interactions underlying the enzyme's cooperative behavior. Both test cases demonstrate the utility of ChACRA's unsupervised machine learning approach for dissecting allostery at the residue level.

Engineering Anti‐CRISPR Proteins to Create CRISPR‐Cas Protein Switches for Activatable Genome Editing and Viral Protease Detection

AbstractProteins capable of switching between distinct active states in response to biochemical cues are ideal for sensing and controlling biological processes. Activatable CRISPR‐Cas systems are significant in precise genetic manipulation and sensitive molecular diagnostics, yet directly controlling Cas protein function remains challenging. Herein, we explore anti‐CRISPR (Acr) proteins as modules to create synthetic Cas protein switches (CasPSs) based on computational chemistry‐directed rational protein interface engineering. Guided by molecular fingerprint analysis, electrostatic potential mapping, and binding free energy calculations, we rationally engineer the molecular interaction interface between Cas12a and its cognate Acr proteins (AcrVA4 and AcrVA5) to generate a series of orthogonal protease‐responsive CasPSs. These CasPSs enable the conversion of specific proteolytic events into activation of Cas12a function with high switching ratios (up to 34.3‐fold). These advancements enable specific proteolysis‐inducible genome editing in mammalian cells and sensitive detection of viral protease activities during virus infection. This work provides a promising strategy for developing CRISPR‐Cas tools for controllable gene manipulation and regulation and clinical diagnostics.

Engineering Anti-CRISPR Proteins to Create CRISPR-Cas Protein Switches for Activatable Genome Editing and Viral Protease Detection.

Proteins capable of switching between distinct active states in response to biochemical cues are ideal for sensing and controlling biological processes. Activatable CRISPR-Cas systems are significant in precise genetic manipulation and sensitive molecular diagnostics, yet directly controlling Cas protein function remains challenging. Herein, we explore anti-CRISPR (Acr) proteins as modules to create synthetic Cas protein switches (CasPSs) based on computational chemistry-directed rational protein interface engineering. Guided by molecular fingerprint analysis, electrostatic potential mapping, and binding free energy calculations, we rationally engineer the molecular interaction interface between Cas12a and its cognate Acr proteins (AcrVA4 and AcrVA5) to generate a series of orthogonal protease-responsive CasPSs. These CasPSs enable the conversion of specific proteolytic events into activation of Cas12a function with high switching ratios (up to 34.3-fold). These advancements enable specific proteolysis-inducible genome editing in mammalian cells and sensitive detection of viral protease activities during virus infection. This work provides a promising strategy for developing CRISPR-Cas tools for controllable gene manipulation and regulation and clinical diagnostics.

A survey of neurophysiological differentiation across mouse visual brain areas and timescales.

Neurophysiological differentiation (ND), a measure of the number of distinct activity states that a neural population visits over a time interval, has been used as a correlate of meaningfulness or subjective perception of visual stimuli. ND has largely been studied in non-invasive human whole-brain recordings where spatial resolution is limited. However, it is likely that perception is supported by discrete neuronal populations rather than the whole brain. Therefore, here we use Neuropixels recordings from the mouse brain to characterize the ND metric across a wide range of temporal scales, within neural populations recorded at single-cell resolution in localized regions. Using the spiking activity of thousands of simultaneously recorded neurons spanning 6 visual cortical areas and the visual thalamus, we show that the ND of stimulus-evoked activity of the entire visual cortex is higher for naturalistic stimuli relative to artificial ones. This finding holds in most individual areas throughout the visual hierarchy. Moreover, for animals performing an image change detection task, ND of the entire visual cortex (though not individual areas) is higher for successful detection compared to failed trials, consistent with the assumed perception of the stimulus. Together, these results suggest that ND computed on cellular-level neural recordings is a useful tool highlighting cell populations that may be involved in subjective perception.

Long-term multi-wavelength study of 1ES 0647+250

Context. The BL Lac object 1ES 0647+250 is one of the few distant γ-ray emitting blazars detected at very high energies (VHEs; ≳100 GeV) during a non-flaring state. It was detected with the MAGIC telescopes during a period of low activity in the years 2009−2011 as well as during three flaring activities in the years 2014, 2019, and 2020, with the highest VHE flux in the last epoch. An extensive multi-instrument data set was collected as part of several coordinated observing campaigns over these years. Aims. We aim to characterise the long-term multi-band flux variability of 1ES 0647+250, as well as its broadband spectral energy distribution (SED) during four distinct activity states selected in four different epochs, in order to constrain the physical parameters of the blazar emission region under certain assumptions. Methods. We evaluated the variability and correlation of the emission in the different energy bands with the fractional variability and the Z-transformed discrete correlation function, as well as its spectral evolution in X-rays and γ rays. Owing to the controversy in the redshift measurements of 1ES 0647+250 reported in the literature, we also estimated its distance in an indirect manner through a comparison of the GeV and TeV spectra from simultaneous observations with Fermi-LAT and MAGIC during the strongest flaring activity detected to date. Moreover, we interpret the SEDs from the four distinct activity states within the framework of one-component and two-component leptonic models, proposing specific scenarios that are able to reproduce the available multi-instrument data. Results. We find significant long-term variability, especially in X-rays and VHE γ rays. Furthermore, significant (3−4σ) correlations were found between the radio, optical, and high-energy (HE) γ-ray fluxes, with the radio emission delayed by about ∼400 days with respect to the optical and γ-ray bands. The spectral analysis reveals a harder-when-brighter trend during the non-flaring state in the X-ray domain. However, no clear patterns were observed for either the enhanced states or the HE (30 MeV < E < 100 GeV) and VHE γ-ray emission of the source. The indirect estimation of the redshift yielded a value of z = 0.45 ± 0.05, which is compatible with some of the values reported in the literature. The SEDs related to the low-activity state and the three flaring states of 1ES 0647+250 can be described reasonably well with the both one-component and two-component leptonic scenarios. However, the long-term correlations indicate the need for an additional radio-producing region located about 3.6 pc downstream from the gamma-ray producing region.

Probing GPCR allosteric activation and biased signaling with rigidity propagation and geometric Monte-Carlo simulations.

GPCR diverse signaling pathways are driven by complex pharmacology arising from a functional conformational ensemble and allosteric modifications rarely captured by structural methods. Our allostery algorithms, which are based on mathematical rigidity theory, provide a mechanical interpretation of allosteric signaling and are designed to predict if perturbation of rigidity at one site of the protein can propagate across a network and in turn cause a change in rigidity at a second distant site, resulting in allosteric transmission. We model the GPCR as a constraint network (graph) consisting of nodes (atoms) and edges (i.e., constraints such as covalent bonds, electrostatic interactions, hydrogen bonds, and hydrophobic contacts). Starting with a set of known GPCR structures we can detect how ligands at either orthosteric site or other regions trigger rigidity changes which propagate to functionally important regions (such as G-protein interface or GDP pocket) in turn cause a rearrangement and alteration of the shape of the cytoplasmic binding region. In collaborations with NMR experimentalists, 19FNMR and computational allostery predictions was used to delineate allostery and distinct key functional activation and precoupled intermediate states in A2AR complexed with heterotrimeric G-protein. NMR showed that binding of G-protein stabilizes a precoupled activation intermediate state and two distinct active states which facilitate nucleotide exchange by full or partial agonists. Rigidity theory allostery algorithms showed Gbg is critical in facilitating allostery within the ternary complex. Recent work investigates the selectivity and efficacy in A2AR in the presence of different G protein subtypes using simulations, allostery predictions and NMR.

State-dependent activity dynamics of hypothalamic stress effector neurons.

The stress response necessitates an immediate boost in vital physiological functions from their homeostatic operation to an elevated emergency response. However, the neural mechanisms underlying this state-dependent change remain largely unknown. Using a combination of in vivo and ex vivo electrophysiology with computational modeling, we report that corticotropin releasing hormone (CRH) neurons in the paraventricular nucleus of the hypothalamus (PVN), the effector neurons of hormonal stress response, rapidly transition between distinct activity states through recurrent inhibition. Specifically, in vivo optrode recording shows that under non-stress conditions, CRHPVN neurons often fire with rhythmic brief bursts (RB), which, somewhat counterintuitively, constrains firing rate due to long (~2 s) interburst intervals. Stressful stimuli rapidly switch RB to continuous single spiking (SS), permitting a large increase in firing rate. A spiking network model shows that recurrent inhibition can control this activity-state switch, and more broadly the gain of spiking responses to excitatory inputs. In biological CRHPVN neurons ex vivo, the injection of whole-cell currents derived from our computational model recreates the in vivo-like switch between RB and SS, providing direct evidence that physiologically relevant network inputs enable state-dependent computation in single neurons. Together, we present a novel mechanism for state-dependent activity dynamics in CRHPVN neurons.

Decoding the temporal and regional specification of microglia in the developing human brain

Region-related heterogeneity and state transitions of microglia are important for brain development and neurological pathogenesis. However, regional specialization and state transition in microglia during early human CNS development remain unclear. Here, we profile single-cell transcriptomes of microglia from distinct regions of the developing human brain, and combined with experimental verification, we define and characterize early microglial fate determinations related to regional specification and state transition. We identified several subclasses of neuronal gene-enriched microglia with regional specification that dynamically and transiently appeared as early brain regions formed. In contrast, immune-related microglia were regionally specialized at later stages of CNS development. Surprisingly, we discovered that region-specialized immune-related microglia exit from a relative resting state and transition into distinct active states. In addition, we experimentally verified the microglial state transition. Finally, we showed that the state transition is conserved but that there are molecular differences in developing microglia in humans and mice.

An Interpretable Convolutional Neural Network Framework for Analyzing Molecular Dynamics Trajectories: a Case Study on Functional States for G-Protein-Coupled Receptors.

Molecular dynamics (MD) simulations have made great contribution to revealing structural and functional mechanisms for many biomolecular systems. However, how to identify functional states and important residues from vast conformation space generated by MD remains challenging; thus an intelligent navigation is highly desired. Despite intelligent advantages of deep learning exhibited in analyzing MD trajectory, its black-box nature limits its application. To address this problem, we explore an interpretable convolutional neural network (CNN)-based deep learning framework to automatically identify diverse active states from the MD trajectory for G-protein-coupled receptors (GPCRs), named the ICNNMD model. To avoid the information loss in representing the conformation structure, the pixel representation is introduced, and then the CNN module is constructed to efficiently extract features followed by a fully connected neural network to realize the classification task. More importantly, we design a local interpretable model-agnostic explanation interpreter for the classification result by local approximation with a linear model, through which important residues underlying distinct active states can be quickly identified. Our model showcases higher than 99% classification accuracy for three important GPCR systems with diverse active states. Notably, some important residues in regulating different biased activities are successfully identified, which are beneficial to elucidating diverse activation mechanisms for GPCRs. Our model can also serve as a general tool to analyze MD trajectory for other biomolecular systems. All source codes are freely available at https://github.com/Jane-Liu97/ICNNMD for aiding MD studies.

ALG-2 and peflin regulate COPII targeting and secretion in response to calcium signaling

ER-to-Golgi transport is the first step in the constitutive secretory pathway, which, unlike regulated secretion, is believed to proceed nonstop independent of Ca2+ flux. However, here we demonstrate that penta-EF hand (PEF) proteins ALG-2 and peflin constitute a hetero-bifunctional COPII regulator that responds to Ca2+ signaling by adopting one of several distinct activity states. Functionally, these states can adjust the rate of ER export of COPII-sorted cargos up or down by ∼50%. We found that at steady-state Ca2+, ALG-2/peflin hetero-complexes bind to ER exit sites (ERES) through the ALG-2 subunit to confer a low, buffered secretion rate, while peflin-lacking ALG-2 complexes markedly stimulate secretion. Upon Ca2+ signaling, ALG-2 complexes lacking peflin can either increase or decrease the secretion rate depending on signaling intensity and duration—phenomena that could contribute to cellular growth and intercellular communication following secretory increases or protection from excitotoxicity and infection following decreases. In epithelial normal rat kidney (NRK) cells, the Ca2+-mobilizing agonist ATP causes ALG-2 to depress ER export, while in neuroendocrine PC12 cells, Ca2+ mobilization by ATP results in ALG-2-dependent enhancement of secretion. Furthermore, distinct Ca2+ signaling patterns in NRK cells produce opposing ALG-2-dependent effects on secretion. Mechanistically, ALG-2-dependent depression of secretion involves decreased levels of the COPII outer shell and increased peflin targeting to ERES, while ALG-2-dependent enhancement of secretion involves increased COPII outer shell and decreased peflin at ERES. These data provide insights into how PEF protein dynamics affect secretion of important physiological cargoes such as collagen I and significantly impact ER stress.

Fusion Proteins as Tools to Discriminate the Biased Signaling Profile of β 2 Adrenergic Receptor Ligands

Introduction The β2 Adrenoceptor (β2AR) is a seven-transmembrane domain receptor that induces a cellular response by activating a unique signaling pathway dependent on the conformational state of the receptor. At least two signaling pathways have been characterized for the β2AR: the canonical Gs pathway and the β-arrestin2 (βarr2) pathway. So far, the determination of the signaling preference of multiple β2AR ligands (biased signaling) is compared to the reference β2AR endogenous ligand, epinephrine (EPI), which by convention is defined as unbiased. However, the absolute biased signaling of β2AR ligands on the basis for the distinct active conformational states of the β2AR is unknown. Thus, we used novel fusion proteins (fp) made of the β2AR receptor fused to Gαs (β2AR-Gs) or to βarr2 (β2AR-βarr2) to stabilize the β2AR conformation and characterize the pharmacological properties (affinity, efficacy, and potency) of the β2AR ligands. Our central hypothesis is that by restricting signaling to a single conformational state of the receptor, we will be able to characterize the biased signaling of β2AR ligands (independent of epinephrine). Methods For pharmacological characterization, we used HEK293 cells, a common cell line widely used to study the β2AR biased signaling. We stably transfected each fp (β2AR-Gs or β2AR-βarr2) independently into HEK293 cells. Stably transfected HEK293 cells with wild-type (WT) β2AR and untransfected HEK293 cells served as experimental controls. Using homologous time-resolving fluorescence, we measured cAMP production and ERK phosphorylation as the surrogates for β2AR signaling via Gs and βarr2, respectively. Results For the Gs protein signaling pathway, our data suggest ICI has a higher affinity for the inhibition of cAMP production by isoproterenol (ISO) in both the β2AR-βarr2 and β2AR-Gs fp (apparent pA2=10.38 and 10.16, respectively), compared to both control groups (WT β2AR pA2=9.42; untransfected HEK293 pA2=9.21). Furthermore, the ligands ISO and EPI showed a higher potency for the β2AR-Gs fp compared to the β2AR-βarr2 fp (Table-1). Regarding the βarr2 signaling pathway, EPI showed higher potency at ERK phosphorylation in cells transfected with β2AR-βarr2 vs β2AR-Gs fp (pEC50=7.0 vs 6.365). Conclusion Our preliminary results suggest that the affinity of ICI as well as the potency of EPI might change based on the conformational state of the β2AR. Ongoing binding affinity studies will further develop the absolute biased signaling profile of each β2AR ligand and reveal if the reason for the differences in potency are due to their differing affinities for the conformational states.

Multiwavelength monitoring of NGC 1275 over a decade: evidence of a shift in synchrotron peak frequency and long-term multiband flux increase

ABSTRACT We carried out a detailed study of the temporal and broad-band spectral behaviour of one of the brightest misaligned active galaxies in γ-rays, NGC 1275, utilizing 11 years of Fermi data and the available Swift and AstroSat observations. Based on the cumulative flux distribution of the γ-ray light curve, we identified four distinct activity states and noticed an increase in the baseline flux during the first three states. A similar nature of increase in the average flux was also noticed in the X-ray and UV bands. Strong flaring activity in γ-rays was noticed in the fourth state. The source was observed twice by AstroSat for shorter intervals (∼days) during longer observing (∼years) states 3 and 4. During the AstroSat observing periods, the source γ-ray flux was higher than the average flux observed during longer duration states. The increase in average baseline flux from state 1 to state 3 can be explained by considering a corresponding increase of jet particle normalization. The inverse Comptonization of synchrotron photons explained the average X-ray and γ-ray emission by jet electrons during the first three longer duration states. However, during the shorter duration AstroSat observing periods, a shift of synchrotron peak frequency was noticed, and the synchrotron emission of jet electrons explained the observed X-ray flux well.

Brain states govern the spatio-temporal dynamics of resting-state functional connectivity

Previously, using simultaneous resting-state functional magnetic resonance imaging (fMRI) and photometry-based neuronal calcium recordings in the anesthetized rat, we identified blood oxygenation level-dependent (BOLD) responses directly related to slow calcium waves, revealing a cortex-wide and spatially organized correlate of locally recorded neuronal activity (Schwalm et al., 2017). Here, using the same techniques, we investigate two distinct cortical activity states: persistent activity, in which compartmentalized network dynamics were observed; and slow wave activity, dominated by a cortex-wide BOLD component, suggesting a strong functional coupling of inter-cortical activity. During slow wave activity, we find a correlation between the occurring slow wave events and the strength of functional connectivity between different cortical areas. These findings suggest that down-up transitions of neuronal excitability can drive cortex-wide functional connectivity. This study provides further evidence that changes in functional connectivity are dependent on the brain's current state, directly linked to the generation of slow waves.

Ex vivo Quantitative Proteomic Analysis of Serotonin Transporter Interactome: Network Impact of the SERT Ala56 Coding Variant.

Altered serotonin (5-HT) signaling is associated with multiple brain disorders, including major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and autism spectrum disorder (ASD). The presynaptic, high-affinity 5-HT transporter (SERT) tightly regulates 5-HT clearance after release from serotonergic neurons in the brain and enteric nervous systems, among other sites. Accumulating evidence suggests that SERT is dynamically regulated in distinct activity states as a result of environmental and intracellular stimuli, with regulation perturbed by disease-associated coding variants. Our lab identified a rare, hypermorphic SERT coding substitution, Gly56Ala, in subjects with ASD, finding that the Ala56 variant stabilizes a high-affinity outward-facing conformation (SERT∗) that leads to elevated 5-HT uptake in vitro and in vivo. Hyperactive SERT Ala56 appears to preclude further activity enhancements by p38α mitogen-activated protein kinase (MAPK) and can be normalized by pharmacological p38α MAPK inhibition, consistent with SERT Ala56 mimicking, constitutively, a high-activity conformation entered into transiently by p38α MAPK activation. We hypothesize that changes in SERT-interacting proteins (SIPs) support the shift of SERT into the SERT∗ state which may be captured by comparing the composition of SERT Ala56 protein complexes with those of wildtype (WT) SERT, defining specific interactions through comparisons of protein complexes recovered using preparations from SERT–/– (knockout; KO) mice. Using quantitative proteomic-based approaches, we identify a total of 459 SIPs, that demonstrate both SERT specificity and sensitivity to the Gly56Ala substitution, with a striking bias being a loss of SIP interactions with SERT Ala56 compared to WT SERT. Among this group are previously validated SIPs, such as flotillin-1 (FLOT1) and protein phosphatase 2A (PP2A), whose functions are believed to contribute to SERT microdomain localization and regulation. Interestingly, our studies nominate a number of novel SIPs implicated in ASD, including fragile X mental retardation 1 protein (FMR1) and SH3 and multiple ankyrin repeat domains protein 3 (SHANK3), of potential relevance to long-standing evidence of serotonergic contributions to ASD. Further investigation of these SIPs, and the broader networks they engage, may afford a greater understanding of ASD as well as other brain and peripheral disorders associated with perturbed 5-HT signaling.

Electroencephalogram Microstate Abnormalities in Early-Course Psychosis

BackgroundMicrostates are periods of characteristic electroencephalographic signal topography that are related to activity in brain networks. Previous work has identified abnormal microstate parameters in individuals with psychotic disorders. We combined microstate analysis with sample entropy analysis to study the dynamics of resting-state networks in patients with early-course psychosis. MethodsWe used microstate analysis to transform resting-state high-density electroencephalography data from 22 patients with early-course psychosis and 22 healthy control subjects into sequences of characteristic scalp topographies. Sample entropy was used to calculate the complexity of microstate sequences across a range of template lengths. ResultsPatients and control subjects produced similar sets of 4 microstates that agree with a widely reported canonical set (A, B, C, and D). Relative to control subjects, patients had decreased frequency of microstate A. In control subjects, sample entropy decreased as template length increased, suggesting that sequence of microstate transitions is self-similar across multiple transitions. In patients, sample entropy did not decrease, suggesting a lack of self-similarity in transition sequences. This finding was unrelated to data length or microstate topography. Entropy was elevated in unmedicated patients, and it decreased in patients who were administered medication. We identified patterns of transitions between microstates that were overrepresented in control data compared with representation in patient data. ConclusionsOur findings suggest that patients with early-course psychosis have abnormally chaotic transitions between brain networks. This chaos may reflect an underlying abnormality in allocating neural resources and effecting appropriate transitions between distinct activity states in psychosis.

The Rat Medial Prefrontal Cortex Exhibits Flexible Neural Activity States during the Performance of an Odor Span Task.

Medial prefrontal cortex (mPFC) activity is fundamental for working memory (WM), attention, and behavioral inhibition; however, a comprehensive understanding of the neural computations underlying these processes is still forthcoming. Toward this goal, neural recordings were obtained from the mPFC of awake, behaving rats performing an odor span task of WM capacity. Neural populations were observed to encode distinct task epochs and the transitions between epochs were accompanied by abrupt shifts in neural activity patterns. Putative pyramidal neuron activity increased earlier in the delay for sessions where rats achieved higher spans. Furthermore, increased putative interneuron activity was only observed at the termination of the delay thus indicating that local processing in inhibitory networks was a unique feature to initiate foraging. During foraging, changes in neural activity patterns associated with the approach to a novel odor, but not familiar odors, were robust. Collectively, these data suggest that distinct mPFC activity states underlie the delay, foraging, and reward epochs of the odor span task. Transitions between these states likely enables adaptive behavior in dynamic environments that place strong demands on the substrates of working memory.

Glycogen distribution in mouse hippocampus.

The hippocampus is a limbic structure involved in the consolidation of episodic memory. In the recent decade, glycogenolysis in the rodent hippocampus has been shown critical for synaptic plasticity and memory formation. Astrocytes are the primary cells that store glycogen which is subject to degradation in hypoglycemic conditions. Focused microwave application to the brain halts metabolic activities, and therefore preserves brain glycogen. Immunohistochemistry against glycogen on focused microwave-assisted brain samples is suitable for both macroscopic and microscopic investigation of glycogen distribution. Glycogen immunohistochemistry in the hippocampus showed a characteristic punctate signal pattern that depended on hippocampal layers. In particular, the hilus is the most glycogen-rich subregion of the hippocampus. Moreover, large glycogen puncta (>0.5µm in diameter) observed in neuropil areas are organized in a patchy pattern consisting of puncta-rich and -poor astrocytes. These observations are discussed with respect to distinct hippocampal neural activity states observed in live animals.

Structures of human PRC2 with its cofactors AEBP2 and JARID2.

Transcriptionally repressive histone H3 lysine 27 methylation by Polycomb repressive complex 2 (PRC2) is essential for cellular differentiation and development. Here we report cryo-electron microscopy structures of human PRC2 in a basal state and two distinct active states while in complex with its cofactors JARID2 and AEBP2. Both cofactors mimic the binding of histone H3 tails. JARID2, methylated by PRC2, mimics a methylated H3 tail to stimulate PRC2 activity, whereas AEBP2 interacts with the RBAP48 subunit, mimicking an unmodified H3 tail. SUZ12 interacts with all other subunits within the assembly and thus contributes to the stability of the complex. Our analysis defines the complete architecture of a functionally relevant PRC2 and provides a structural framework to understand its regulation by cofactors, histone tails, and RNA.