Neuronal avalanches recorded in the awake and sleeping monkey do not show a power law but can be reproduced by a self-organized critical model

Poster presentation: Self-organized critical (SOC) systems are complex dynamical systems that may express cascades of events, called avalanches [1]. The SOC state was proposed to govern brain function, because of its activity fluctuations over many orders of magnitude, its sensitivity to small input and its long term stability [2,3]. In addition, the critical state is optimal for information storage and processing [4]. Both hallmark features of SOC systems, a power law distribution f(s) for the avalanche size s and a branching parameter (bp) of unity, were found for neuronal avalanches recorded in vitro [5]. However, recordings in vivo yielded contradictory results [6]. Electrophysiological recordings in vivo only cover a small fraction of the brain, while criticality analysis assumes that the complete system is sampled. We hypothesized that spatial subsampling might influence the observed avalanche statistics. In addition, SOC models can have different connectivity, but always show a power law for f(s) and bp = 1 when fully sampled. This may not be the case under subsampling, however. Here, we wanted to know whether a state change from awake to asleep could be modeled by changing the connectivity of a SOC model without leaving the critical state. We simulated a SOC model [1] and calculated f(s) and bp obtained from sampling only the activity of a set of 4 × 4 sites, representing the electrode positions in the cortex. We compared these results with results obtained from multielectrode recordings of local field potentials (LFP) in the cortex of behaving monkeys. We calculated f(s) and bp for the LFP activity recorded while the monkey was either awake or asleep and compared these results to results obtained from two subsampled SOC model with different connectivity. f(s) and bp were very similar for both the experiments and the subsampled SOC model, but in contrast to the fully sampled model, f(s) did not show a power law and bp was smaller than unity. With increasing the distance between the sampling sites, f(s) changed from "apparently supercritical" to "apparently subcritical" distributions in both the model and the LFP data. f(s) and bp calculated from LFP recorded during awake and asleep differed. These changes could be explained by altering the connectivity in the SOC model. Our results show that subsampling can prevent the observation of the characteristic power law and bp in SOC systems, and misclassifications of critical systems as sub- or supercritical are possible. In addition, a change in f(s) and bp for different states (awake/asleep) does not necessarily imply a change from criticality to sub- or supercriticality, but can also be explained by a change in the effective connectivity of the network without leaving the critical state

Rhesus TRIM5α disrupts the HIV-1 capsid at the inter-hexamer interfaces

TRIM proteins play important roles in the innate immune defense against retroviral infection, including human immunodeficiency virus type-1 (HIV-1). Rhesus macaque TRIM5α (TRIM5αrh) targets the HIV-1 capsid and blocks infection at an early post-entry stage, prior to reverse transcription. Studies have shown that binding of TRIM5α to the assembled capsid is essential for restriction and requires the coiled-coil and B30.2/SPRY domains, but the molecular mechanism of restriction is not fully understood. In this study, we investigated, by cryoEM combined with mutagenesis and chemical cross-linking, the direct interactions between HIV-1 capsid protein (CA) assemblies and purified TRIM5αrh containing coiled-coil and SPRY domains (CC-SPRYrh). Concentration-dependent binding of CC-SPRYrh to CA assemblies was observed, while under equivalent conditions the human protein did not bind. Importantly, CC-SPRYrh, but not its human counterpart, disrupted CA tubes in a non-random fashion, releasing fragments of protofilaments consisting of CA hexamers without dissociation into monomers. Furthermore, such structural destruction was prevented by inter-hexamer crosslinking using P207C/T216C mutant CA with disulfide bonds at the CTD-CTD trimer interface of capsid assemblies, but not by intra-hexamer crosslinking via A14C/E45C at the NTD-NTD interface. The same disruption effect by TRIM5αrh on the inter-hexamer interfaces also occurred with purified intact HIV-1 cores. These results provide insights concerning how TRIM5α disrupts the virion core and demonstrate that structural damage of the viral capsid by TRIM5α is likely one of the important components of the mechanism of TRIM5α-mediated HIV-1 restriction. © 2011 Zhao et al

Pleosporales

One hundred and five generic types of Pleosporales are described and illustrated. A brief introduction and detailed history with short notes on morphology, molecular phylogeny as well as a general conclusion of each genus are provided. For those genera where the type or a representative specimen is unavailable, a brief note is given. Altogether 174 genera of Pleosporales are treated. Phaeotrichaceae as well as Kriegeriella, Zeuctomorpha and Muroia are excluded from Pleosporales. Based on the multigene phylogenetic analysis, the suborder Massarineae is emended to accommodate five families, viz. Lentitheciaceae, Massarinaceae, Montagnulaceae, Morosphaeriaceae and Trematosphaeriaceae

The S phase checkpoint promotes the Smc5/6 complex dependent SUMOylation of Pol2, the catalytic subunit of DNA polymerase ε

Replication fork stalling and accumulation of single-stranded DNA trigger the S phase checkpoint, a signalling cascade that, in budding yeast, leads to the activation of the Rad53 kinase. Rad53 is essential in maintaining cell viability, but its targets of regulation are still partially unknown. Here we show that Rad53 drives the hyper-SUMOylation of Pol2, the catalytic subunit of DNA polymerase ε, principally following replication forks stalling induced by nucleotide depletion. Pol2 is the main target of SUMOylation within the replisome and its modification requires the SUMO-ligase Mms21, a subunit of the Smc5/6 complex. Moreover, the Smc5/6 complex co-purifies with Pol ε, independently of other replisome components. Finally, we map Pol2 SUMOylation to a single site within the N-terminal catalytic domain and identify a SUMO-interacting motif at the C-terminus of Pol2. These data suggest that the S phase checkpoint regulate Pol ε during replication stress through Pol2 SUMOylation and SUMO-binding abilit

Tumor volume in subcutaneous mouse xenografts measured by microCT is more accurate and reproducible than determined by 18F-FDG-microPET or external caliper

<p>Abstract</p> <p>Background</p> <p>In animal studies tumor size is used to assess responses to anticancer therapy. Current standard for volumetric measurement of xenografted tumors is by external caliper, a method often affected by error. The aim of the present study was to evaluate if microCT gives more accurate and reproducible measures of tumor size in mice compared with caliper measurements. Furthermore, we evaluated the accuracy of tumor volume determined from ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) PET.</p> <p>Methods</p> <p>Subcutaneously implanted human breast adenocarcinoma cells in NMRI nude mice served as tumor model. Tumor volume (n = 20) was determined <it>in vivo </it>by external caliper, microCT and ¹⁸F-FDG-PET and subsequently reference volume was determined <it>ex vivo</it>. Intra-observer reproducibility of the microCT and caliper methods were determined by acquiring 10 repeated volume measurements. Volumes of a group of tumors (n = 10) were determined independently by two observers to assess inter-observer variation.</p> <p>Results</p> <p>Tumor volume measured by microCT, PET and caliper all correlated with reference volume. No significant bias of microCT measurements compared with the reference was found, whereas both PET and caliper had systematic bias compared to reference volume. Coefficients of variation for intra-observer variation were 7% and 14% for microCT and caliper measurements, respectively. Regression coefficients between observers were 0.97 for microCT and 0.91 for caliper measurements.</p> <p>Conclusion</p> <p>MicroCT was more accurate than both caliper and ¹⁸F-FDG-PET for <it>in vivo </it>volumetric measurements of subcutaneous tumors in mice.¹⁸F-FDG-PET was considered unsuitable for determination of tumor size. External caliper were inaccurate and encumbered with a significant and size dependent bias. MicroCT was also the most reproducible of the methods.</p

Diagnostic stability among chronic patients with functional psychoses: an epidemiological and clinical study

<p>Abstract</p> <p>Background</p> <p>Diagnostic stability and illness course of chronic non-organic psychoses are complex phenomena and only few risk factors or predictors are known that can be used reliably. This study investigates the diagnostic stability during the entire course of illness in patients with non-organic psychoses and attempts to identify non-psychopathological risk factors or predictors.</p> <p>Method</p> <p>100 patients with functional psychosis were initially characterised using the Operational Criteria Checklist for Psychotic Illness and Affective Illness (OPCRIT), medical records and health registers. To study the stability of diagnoses (i.e. shifts per time), we used registry data to define four measures of diagnostic variation that were subsequently examined in relation to four possible measures of time (i.e. observation periods or hospitalisation events). Afterwards, we identified putative co-variables and predictors of the best measures of diagnostic stability.</p> <p>Results</p> <p>All four measures of diagnostic variation are very strongly associated with numbers-of-hospitalisations and less so with duration-of-illness, duration-of-hospitalisation and with year-of-first-admission. The four measures of diagnostic variation corrected for numbers-of-hospitalisations were therefore used to study the diagnostic stability. Conventional predictors of illness course – e.g. age-of-onset and premorbid-functioning – are not significantly associated with stability. Only somatic-comorbidity is significantly associated with two measures of stability, while family-history-of-psychiatric-illness and global-assessment-of-functioning (GAF) scale score show a trend. However, the traditional variables age-of-first-admission, civil-status, first-diagnosis-being-schizophrenia and somatic-comorbidity are able to explain two-fifth of the variation in numbers-of-hospitalisations.</p> <p>Conclusion</p> <p>Diagnostic stability is closely linked with the contact between patient and the healthcare system. This could very likely be due to fluctuation of disease manifestation over time or presence of co-morbid psychiatric illness in combination with rigid diagnostic criteria that are unable to capture the multiple psychopathologies of the functional psychoses that results in differential diagnoses and therefore diagnostic instability. Not surprisingly, somatic-comorbidity was found to be a predictor of diagnostic variation thereby being a non-psychiatric confounder.</p

Subsampling effects in neuronal avalanche distributions recorded in vivo

Background Many systems in nature are characterized by complex behaviour where large cascades of events, or avalanches, unpredictably alternate with periods of little activity. Snow avalanches are an example. Often the size distribution f(s) of a system's avalanches follows a power law, and the branching parameter sigma, the average number of events triggered by a single preceding event, is unity. A power law for f(s), and sigma=1, are hallmark features of self-organized critical (SOC) systems, and both have been found for neuronal activity in vitro. Therefore, and since SOC systems and neuronal activity both show large variability, long-term stability and memory capabilities, SOC has been proposed to govern neuronal dynamics in vivo. Testing this hypothesis is difficult because neuronal activity is spatially or temporally subsampled, while theories of SOC systems assume full sampling. To close this gap, we investigated how subsampling affects f(s) and sigma by imposing subsampling on three different SOC models. We then compared f(s) and sigma of the subsampled models with those of multielectrode local field potential (LFP) activity recorded in three macaque monkeys performing a short term memory task. Results Neither the LFP nor the subsampled SOC models showed a power law for f(s). Both, f(s) and sigma, depended sensitively on the subsampling geometry and the dynamics of the model. Only one of the SOC models, the Abelian Sandpile Model, exhibited f(s) and sigma similar to those calculated from LFP activity. Conclusions Since subsampling can prevent the observation of the characteristic power law and sigma in SOC systems, misclassifications of critical systems as sub- or supercritical are possible. Nevertheless, the system specific scaling of f(s) and sigma under subsampling conditions may prove useful to select physiologically motivated models of brain function. Models that better reproduce f(s) and sigma calculated from the physiological recordings may be selected over alternatives