A dynamic mode of mitotic bookmarking by transcription factors.

During mitosis, transcription is shut off, chromatin condenses, and most transcription factors (TFs) are reported to be excluded from chromosomes. How do daughter cells re-establish the original transcription program? Recent discoveries that a select set of TFs remain bound on mitotic chromosomes suggest a potential mechanism for maintaining transcriptional programs through the cell cycle termed mitotic bookmarking. Here we report instead that many TFs remain associated with chromosomes in mouse embryonic stem cells, and that the exclusion previously described is largely a fixation artifact. In particular, most TFs we tested are significantly enriched on mitotic chromosomes. Studies with Sox2 reveal that this mitotic interaction is more dynamic than in interphase and is facilitated by both DNA binding and nuclear import. Furthermore, this dynamic mode results from lack of transcriptional activation rather than decreased accessibility of underlying DNA sequences in mitosis. The nature of the cross-linking artifact prompts careful re-examination of the role of TFs in mitotic bookmarking

EEG source imaging assists decoding in a face recognition task

EEG based brain state decoding has numerous applications. State of the art decoding is based on processing of the multivariate sensor space signal, however evidence is mounting that EEG source reconstruction can assist decoding. EEG source imaging leads to high-dimensional representations and rather strong a priori information must be invoked. Recent work by Edelman et al. (2016) has demonstrated that introduction of a spatially focal source space representation can improve decoding of motor imagery. In this work we explore the generality of Edelman et al. hypothesis by considering decoding of face recognition. This task concerns the differentiation of brain responses to images of faces and scrambled faces and poses a rather difficult decoding problem at the single trial level. We implement the pipeline using spatially focused features and show that this approach is challenged and source imaging does not lead to an improved decoding. We design a distributed pipeline in which the classifier has access to brain wide features which in turn does lead to a 15% reduction in the error rate using source space features. Hence, our work presents supporting evidence for the hypothesis that source imaging improves decoding

Robust model-based analysis of single-particle tracking experiments with Spot-On.

Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce 'Spot-On', an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants

Restmaterialer fra bio-energiproduktion - kan de tilbageføres til marken?

Efluents from biogas production may be recycled to soil as plant nutrition. However, the proportion of plant-available nitrogen is high and may cause loss due to leaching or gaseous emissions. Hence, such waste stream materials must be applied with care to ensure maximum plant uptake to minimize loss. Spread of weed seeds via application of biogas effluents is only a problem when the digestion is performed at mesophilic conditions and when the seeds are staying less than a week in the plant. At thermophilic conditions, seeds from a range of weed plant were unable to germinate efter just a few days

Molecular orbital investigation of chemisorption. I. Hydrogen on tungsten (100) surface

The relative bonding energies of hydrogen chemisorbed at three symmetric sites on a W(100) surface were obtained by means of the extended Hückel molecular orbital theory (EHMO). The preferred site for hydrogen chemisorption was found to be the single coordination number (1 CN) site or the site above a surface tungsten atom. The W(100) surface was represented by finite arrays of tungsten atoms which were shown to be adequate for obtaining semiquantitative results. The basis set for the calculations contained the valence orbitals of tungsten and, initially, the 5p orbitals which were nonbonding but provided the necessary repulsion at small internuclear separation. The repulsive energy provided by these orbitals was replaced by an analytical exponential repulsive energy term. This allowed the 5p orbitals to be omitted from the basis set to simplify computation. Functionally, the energy change for the reaction Wn + H → Wn H was calculated for various assumed configurations of the Wn H ``molecule.'' The bonding between tungsten atoms was found to be changed as a result of Wn H formation, and the change varied with hydrogen position. Energy barriers to surface diffusion were also calculated and found to agree reasonably with experimental values.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71349/2/JCPSA6-59-10-5277-1.pd

Implicit regularization in AI meets generalized hardness of approximation in optimization -- Sharp results for diagonal linear networks

Understanding the implicit regularization imposed by neural network architectures and gradient based optimization methods is a key challenge in deep learning and AI. In this work we provide sharp results for the implicit regularization imposed by the gradient flow of Diagonal Linear Networks (DLNs) in the over-parameterized regression setting and, potentially surprisingly, link this to the phenomenon of phase transitions in generalized hardness of approximation (GHA). GHA generalizes the phenomenon of hardness of approximation from computer science to, among others, continuous and robust optimization. It is well-known that the $\ell^1$-norm of the gradient flow of DLNs with tiny initialization converges to the objective function of basis pursuit. We improve upon these results by showing that the gradient flow of DLNs with tiny initialization approximates minimizers of the basis pursuit optimization problem (as opposed to just the objective function), and we obtain new and sharp convergence bounds w.r.t.\ the initialization size. Non-sharpness of our results would imply that the GHA phenomenon would not occur for the basis pursuit optimization problem -- which is a contradiction -- thus implying sharpness. Moreover, we characterize $\textit{which}$ $\ell_1$ minimizer of the basis pursuit problem is chosen by the gradient flow whenever the minimizer is not unique. Interestingly, this depends on the depth of the DLN

Nature-Inspired and Energy Efficient Route Planning

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Guided nuclear exploration increases CTCF target search efficiency.

The enormous size of mammalian genomes means that for a DNA-binding protein the number of nonspecific, off-target sites vastly exceeds the number of specific, cognate sites. How mammalian DNA-binding proteins overcome this challenge to efficiently locate their target sites is not known. Here, through live-cell single-molecule tracking, we show that CCCTC-binding factor, CTCF, is repeatedly trapped in small zones that likely correspond to CTCF clusters, in a manner that is largely dependent on an internal RNA-binding region (RBRi). We develop a new theoretical model called anisotropic diffusion through transient trapping in zones to explain CTCF dynamics. Functionally, transient RBRi-mediated trapping increases the efficiency of CTCF target search by ~2.5-fold. Overall, our results suggest a 'guided' mechanism where CTCF clusters concentrate diffusing CTCF proteins near cognate binding sites, thus increasing the local ON-rate. We suggest that local guiding may allow DNA-binding proteins to more efficiently locate their target sites

Redefining effect size interpretations for psychotherapy RCTs in depression

Introduction: Effect sizes are often used to interpret the magnitude of a result and in power calculations when planning research studies. However, as effect size interpretations are context-dependent, Jacob Cohen’s suggested guidelines for what represents a small, medium, and large effect are unlikely to be suitable for a diverse range of research populations and interventions. Our objective here is to determine empirically-derived effect size thresholds associated with psychotherapy randomized controlled trials (RCTs) in depression by calculating the effect size distribution. Methods: We extracted effect sizes from 366 RCTs provided by the systematic review of Cuijpers and colleagues (2020) on psychotherapy for depressive disorders across all age groups. The 50th percentile effect size, as this represents a medium effect size, and the 25th (small) and 75th (large) percentile effect sizes were calculated to determine empirically-derived effect size thresholds. Results: After adjusting for publication bias, 0.27, 0.53, and 0.86 represent small, medium, and large effect sizes, respectively, for psychotherapy treatment for depressive disorders. Discussion: The effect size distribution for psychotherapy treatment of depression indicates that observed effect size thresholds are larger than Cohen’s suggested effect size thresholds (0.2, 0.5, and 0.8). These results have implications for the interpretation of study effects and the planning of future studies via power analyses, which often use effect size thresholds.publishedVersio

Evidence for DNA-mediated nuclear compartmentalization distinct from phase separation.

RNA Polymerase II (Pol II) and transcription factors form concentrated hubs in cells via multivalent protein-protein interactions, often mediated by proteins with intrinsically disordered regions. During Herpes Simplex Virus infection, viral replication compartments (RCs) efficiently enrich host Pol II into membraneless domains, reminiscent of liquid-liquid phase separation. Despite sharing several properties with phase-separated condensates, we show that RCs operate via a distinct mechanism wherein unrestricted nonspecific protein-DNA interactions efficiently outcompete host chromatin, profoundly influencing the way DNA-binding proteins explore RCs. We find that the viral genome remains largely nucleosome-free, and this increase in accessibility allows Pol II and other DNA-binding proteins to repeatedly visit nearby DNA binding sites. This anisotropic behavior creates local accumulations of protein factors despite their unrestricted diffusion across RC boundaries. Our results reveal underappreciated consequences of nonspecific DNA binding in shaping gene activity, and suggest additional roles for chromatin in modulating nuclear function and organization