A new family of diprotodontian marsupials from the latest Oligocene of Australia and the evolution of wombats, koalas, and their relatives (Vombatiformes)

We describe the partial cranium and skeleton of a new diprotodontian marsupial from the late Oligocene (~26–25 Ma) Namba Formation of South Australia. This is one of the oldest Australian marsupial fossils known from an associated skeleton and it reveals previously unsuspected morphological diversity within Vombatiformes, the clade that includes wombats (Vombatidae), koalas (Phascolarctidae) and several extinct families. Several aspects of the skull and teeth of the new taxon, which we refer to a new family, are intermediate between members of the fossil family Wynyardiidae and wombats. Its postcranial skeleton exhibits features associated with scratch-digging, but it is unlikely to have been a true burrower. Body mass estimates based on postcranial dimensions range between 143 and 171 kg, suggesting that it was ~5 times larger than living wombats. Phylogenetic analysis based on 79 craniodental and 20 postcranial characters places the new taxon as sister to vombatids, with which it forms the superfamily Vombatoidea as defined here. It suggests that the highly derived vombatids evolved from wynyardiid-like ancestors, and that scratch-digging adaptations evolved in vombatoids prior to the appearance of the ever-growing (hypselodont) molars that are a characteristic feature of all post-Miocene vombatids. Ancestral state reconstructions on our preferred phylogeny suggest that bunolophodont molars are plesiomorphic for vombatiforms, with full lophodonty (characteristic of diprotodontoids) evolving from a selenodont morphology that was retained by phascolarctids and ilariids, and wynyardiids and vombatoids retaining an intermediate selenolophodont condition. There appear to have been at least six independent acquisitions of very large (>100 kg) body size within Vombatiformes, several having already occurred by the late Oligocene

Kinetic modelling of competition and depletion of shared miRNAs by competing endogenous RNAs

Non-conding RNAs play a key role in the post-transcriptional regulation of mRNA translation and turnover in eukaryotes. miRNAs, in particular, interact with their target RNAs through protein-mediated, sequence-specific binding, giving rise to extended and highly heterogeneous miRNA-RNA interaction networks. Within such networks, competition to bind miRNAs can generate an effective positive coupling between their targets. Competing endogenous RNAs (ceRNAs) can in turn regulate each other through miRNA-mediated crosstalk. Albeit potentially weak, ceRNA interactions can occur both dynamically, affecting e.g. the regulatory clock, and at stationarity, in which case ceRNA networks as a whole can be implicated in the composition of the cell's proteome. Many features of ceRNA interactions, including the conditions under which they become significant, can be unraveled by mathematical and in silico models. We review the understanding of the ceRNA effect obtained within such frameworks, focusing on the methods employed to quantify it, its role in the processing of gene expression noise, and how network topology can determine its reach.Comment: review article, 29 pages, 7 figure

Fall Classification by Machine Learning Using Mobile Phones

Fall prevention is a critical component of health care; falls are a common source of injury in the elderly and are associated with significant levels of mortality and morbidity. Automatically detecting falls can allow rapid response to potential emergencies; in addition, knowing the cause or manner of a fall can be beneficial for prevention studies or a more tailored emergency response. The purpose of this study is to demonstrate techniques to not only reliably detect a fall but also to automatically classify the type. We asked 15 subjects to simulate four different types of falls–left and right lateral, forward trips, and backward slips–while wearing mobile phones and previously validated, dedicated accelerometers. Nine subjects also wore the devices for ten days, to provide data for comparison with the simulated falls. We applied five machine learning classifiers to a large time-series feature set to detect falls. Support vector machines and regularized logistic regression were able to identify a fall with 98% accuracy and classify the type of fall with 99% accuracy. This work demonstrates how current machine learning approaches can simplify data collection for prevention in fall-related research as well as improve rapid response to potential injuries due to falls

Analysis of Stochastic Strategies in Bacterial Competence: A Master Equation Approach

Competence is a transiently differentiated state that certain bacterial cells reach when faced with a stressful environment. Entrance into competence can be attributed to the excitability of the dynamics governing the genetic circuit that regulates this cellular behavior. Like many biological behaviors, entrance into competence is a stochastic event. In this case cellular noise is responsible for driving the cell from a vegetative state into competence and back. In this work we present a novel numerical method for the analysis of stochastic biochemical events and use it to study the excitable dynamics responsible for competence in Bacillus subtilis. Starting with a Finite State Projection (FSP) solution of the chemical master equation (CME), we develop efficient numerical tools for accurately computing competence probability. Additionally, we propose a new approach for the sensitivity analysis of stochastic events and utilize it to elucidate the robustness properties of the competence regulatory genetic circuit. We also propose and implement a numerical method to calculate the expected time it takes a cell to return from competence. Although this study is focused on an example of cell-differentiation in Bacillus subtilis, our approach can be applied to a wide range of stochastic phenomena in biological systems

Amplification of asynchronous inhibition-mediated synchronization by feedback in recurrent networks

Synchronization of 30-80 Hz oscillatory activity of the principle neurons in the olfactory bulb (mitral cells) is believed to be important for odor discrimination. Previous theoretical studies of these fast rhythms in other brain areas have proposed that principle neuron synchrony can be mediated by short-latency, rapidly decaying inhibition. This phasic inhibition provides a narrow time window for the principle neurons to fire, thus promoting synchrony. However, in the olfactory bulb, the inhibitory granule cells produce long lasting, small amplitude, asynchronous and aperiodic inhibitory input and thus the narrow time window that is required to synchronize spiking does not exist. Instead, it has been suggested that correlated output of the granule cells could serve to synchronize uncoupled mitral cells through a mechanism called "stochastic synchronization", wherein the synchronization arises through correlation of inputs to two neural oscillators. Almost all work on synchrony due to correlations presumes that the correlation is imposed and fixed. Building on theory and experiments that we and others have developed, we show that increased synchrony in the mitral cells could produce an increase in granule cell activity for those granule cells that share a synchronous group of mitral cells. Common granule cell input increases the input correlation to the mitral cells and hence their synchrony by providing a positive feedback loop in correlation. Thus we demonstrate the emergence and temporal evolution of input correlation in recurrent networks with feedback. We explore several theoretical models of this idea, ranging from spiking models to an analytically tractable model. © 2010 Marella, Ermentrout

The Ninth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-III Baryon Oscillation Spectroscopic Survey

The Sloan Digital Sky Survey III (SDSS-III) presents the first spectroscopic data from the Baryon Oscillation Spectroscopic Survey (BOSS). This ninth data release (DR9) of the SDSS project includes 535,995 new galaxy spectra (median z=0.52), 102,100 new quasar spectra (median z=2.32), and 90,897 new stellar spectra, along with the data presented in previous data releases. These spectra were obtained with the new BOSS spectrograph and were taken between 2009 December and 2011 July. In addition, the stellar parameters pipeline, which determines radial velocities, surface temperatures, surface gravities, and metallicities of stars, has been updated and refined with improvements in temperature estimates for stars with T_eff<5000 K and in metallicity estimates for stars with [Fe/H]>-0.5. DR9 includes new stellar parameters for all stars presented in DR8, including stars from SDSS-I and II, as well as those observed as part of the SDSS-III Sloan Extension for Galactic Understanding and Exploration-2 (SEGUE-2). The astrometry error introduced in the DR8 imaging catalogs has been corrected in the DR9 data products. The next data release for SDSS-III will be in Summer 2013, which will present the first data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) along with another year of data from BOSS, followed by the final SDSS-III data release in December 2014.Comment: 9 figures; 2 tables. Submitted to ApJS. DR9 is available at http://www.sdss3.org/dr

Acquisition of Chemoresistance in Gliomas Is Associated with Increased Mitochondrial Coupling and Decreased ROS Production

Temozolomide (TMZ) is an alkylating agent used for treating gliomas. Chemoresistance is a severe limitation to TMZ therapy; there is a critical need to understand the underlying mechanisms that determine tumor response to TMZ. We recently reported that chemoresistance to TMZ is related to a remodeling of the entire electron transport chain, with significant increases in the activity of complexes II/III and cytochrome c oxidase (CcO). Moreover, pharmacologic and genetic manipulation of CcO reverses chemoresistance. Therefore, to test the hypothesis that TMZ-resistance arises from tighter mitochondrial coupling and decreased production of reactive oxygen species (ROS), we have assessed mitochondrial function in TMZ-sensitive and -resistant glioma cells, and in TMZ-resistant glioblastoma multiform (GBM) xenograft lines (xenolines). Maximum ADP-stimulated (state 3) rates of mitochondrial oxygen consumption were greater in TMZ-resistant cells and xenolines, and basal respiration (state 2), proton leak (state 4), and mitochondrial ROS production were significantly lower in TMZ-resistant cells. Furthermore, TMZ-resistant cells consumed less glucose and produced less lactic acid. Chemoresistant cells were insensitive to the oxidative stress induced by TMZ and hydrogen peroxide challenges, but treatment with the oxidant L-buthionine-S,R-sulfoximine increased TMZ-dependent ROS generation and reversed chemoresistance. Importantly, treatment with the antioxidant N-acetyl-cysteine inhibited TMZ-dependent ROS generation in chemosensitive cells, preventing TMZ toxicity. Finally, we found that mitochondrial DNA-depleted cells (ρ°) were resistant to TMZ and had lower intracellular ROS levels after TMZ exposure compared with parental cells. Repopulation of ρ° cells with mitochondria restored ROS production and sensitivity to TMZ. Taken together, our results indicate that chemoresistance to TMZ is linked to tighter mitochondrial coupling and low ROS production, and suggest a novel mitochondrial ROS-dependent mechanism underlying TMZ-chemoresistance in glioma. Thus, perturbation of mitochondrial functions and changes in redox status might constitute a novel strategy for sensitizing glioma cells to therapeutic approaches

Positive feedback and noise activate the stringent response regulator Rel in mycobacteria

Phenotypic heterogeneity in an isogenic, microbial population enables a subset of the population to persist under stress. In mycobacteria, stresses like nutrient and oxygen deprivation activate the stress response pathway involving the two-component system MprAB and the sigma factor, SigE. SigE in turn activates the expression of the stringent response regulator, rel. The enzyme polyphosphate kinase 1 (PPK1) regulates this pathway by synthesizing polyphosphate required for the activation of MprB. The precise manner in which only a subpopulation of bacterial cells develops persistence, remains unknown. Rel is required for mycobacterial persistence. Here we show that the distribution of rel expression levels in a growing population of mycobacteria is bimodal with two distinct peaks corresponding to low (L) and high (H) expression states, and further establish that a positive feedback loop involving the mprAB operon along with stochastic gene expression are responsible for the phenotypic heterogeneity. Combining single cell analysis by flow cytometry with theoretical modeling, we observe that during growth, noise-driven transitions take a subpopulation of cells from the L to the H state within a "window of opportunity" in time preceding the stationary phase. We find evidence of hysteresis in the expression of rel in response to changing concentrations of PPK1. Our results provide, for the first time, evidence that bistability and stochastic gene expression could be important for the development of "heterogeneity with an advantage" in mycobacteria.Comment: Accepted for publication in PLoS On

A New Isoform of the Histone Demethylase JMJD2A/KDM4A Is Required for Skeletal Muscle Differentiation

In proliferating myoblasts, muscle specific genes are silenced by epigenetic modifications at their promoters, including histone H3K9 methylation. Derepression of the promoter of the gene encoding the myogenic factor myogenin (Myog) is key for initiation of muscle differentiation. The mechanism of H3K9 demethylation at the Myog promoter is unclear, however. Here, we identify an isoform of the histone demethylase JMJD2A/KDM4A that lacks the N-terminal demethylase domain (ΔN-JMJD2A). The amount of ΔN-JMJD2A increases during differentiation of C2C12 myoblasts into myotubes. Genome-wide expression profiling and exon-specific siRNA knockdown indicate that, in contrast to the full-length protein, ΔN-JMJD2A is necessary for myotube formation and muscle-specific gene expression. Moreover, ΔN-JMJD2A promotes MyoD-induced conversion of NIH3T3 cells into muscle cells. ChIP-on-chip analysis indicates that ΔN-JMJD2A binds to genes mainly involved in transcriptional control and that this binding is linked to gene activation. ΔN-JMJD2A is recruited to the Myog promoter at the onset of differentiation. This binding is essential to promote the demethylation of H3K9me2 and H3K9me3. We conclude that induction of the ΔN-JMJD2A isoform is crucial for muscle differentiation: by directing the removal of repressive chromatin marks at the Myog promoter, it promotes transcriptional activation of the Myog gene and thus contributes to initiation of muscle-specific gene expression