A 16-Gene Signature Distinguishes Anaplastic Astrocytoma from Glioblastoma

Anaplastic astrocytoma (AA; Grade III) and glioblastoma (GBM; Grade IV) are diffusely infiltrating tumors and are called malignant astrocytomas. The treatment regimen and prognosis are distinctly different between anaplastic astrocytoma and glioblastoma patients. Although histopathology based current grading system is well accepted and largely reproducible, intratumoral histologic variations often lead to difficulties in classification of malignant astrocytoma samples. In order to obtain a more robust molecular classifier, we analysed RT-qPCR expression data of 175 differentially regulated genes across astrocytoma using Prediction Analysis of Microarrays (PAM) and found the most discriminatory 16-gene expression signature for the classification of anaplastic astrocytoma and glioblastoma. The 16-gene signature obtained in the training set was validated in the test set with diagnostic accuracy of 89%. Additionally, validation of the 16-gene signature in multiple independent cohorts revealed that the signature predicted anaplastic astrocytoma and glioblastoma samples with accuracy rates of 99%, 88%, and 92% in TCGA, GSE1993 and GSE4422 datasets, respectively. The protein-protein interaction network and pathway analysis suggested that the 16-genes of the signature identified epithelial-mesenchymal transition (EMT) pathway as the most differentially regulated pathway in glioblastoma compared to anaplastic astrocytoma. In addition to identifying 16 gene classification signature, we also demonstrated that genes involved in epithelial-mesenchymal transition may play an important role in distinguishing glioblastoma from anaplastic astrocytoma.

Balanced Excitatory and Inhibitory Synaptic Currents Promote Efficient Coding and Metabolic Efficiency

A balance between excitatory and inhibitory synaptic currents is thought to be important for several aspects of information processing in cortical neurons in vivo, including gain control, bandwidth and receptive field structure. These factors will affect the firing rate of cortical neurons and their reliability, with consequences for their information coding and energy consumption. Yet how balanced synaptic currents contribute to the coding efficiency and energy efficiency of cortical neurons remains unclear. We used single compartment computational models with stochastic voltage-gated ion channels to determine whether synaptic regimes that produce balanced excitatory and inhibitory currents have specific advantages over other input regimes. Specifically, we compared models with only excitatory synaptic inputs to those with equal excitatory and inhibitory conductances, and stronger inhibitory than excitatory conductances (i.e. approximately balanced synaptic currents). Using these models, we show that balanced synaptic currents evoke fewer spikes per second than excitatory inputs alone or equal excitatory and inhibitory conductances. However, spikes evoked by balanced synaptic inputs are more informative (bits/spike), so that spike trains evoked by all three regimes have similar information rates (bits/s). Consequently, because spikes dominate the energy consumption of our computational models, approximately balanced synaptic currents are also more energy efficient than other synaptic regimes. Thus, by producing fewer, more informative spikes approximately balanced synaptic currents in cortical neurons can promote both coding efficiency and energy efficiency.

Multivariate Granger causality: an estimation framework based on factorization of the spectral density matrix

Granger causality is increasingly being applied to multi-electrode neurophysiological and functional imaging data to characterize directional interactions between neurons and brain regions. For a multivariate dataset, one might be interested in different subsets of the recorded neurons or brain regions. According to the current estimation framework, for each subset, one conducts a separate autoregressive model fitting process, introducing the potential for unwanted variability and uncertainty. In this paper, we propose a multivariate framework for estimating Granger causality. It is based on spectral density matrix factorization and offers the advantage that the estimation of such a matrix needs to be done only once for the entire multivariate dataset. For any subset of recorded data, Granger causality can be calculated through factorizing the appropriate submatrix of the overall spectral density matrix.

SRF Phosphorylation by Glycogen Synthase Kinase-3 Promotes Axon Growth in Hippocampal Neurons

The growth of axons is an intricately regulated process involving intracellular signaling cascades and gene transcription. We had previously shown that the stimulus-dependent transcription factor, serum response factor (SRF), plays a critical role in regulating axon growth in the mammalian brain. However, the molecular mechanisms underlying SRF-dependent axon growth remains unknown. Here we report that SRF is phosphorylated and activated by GSK-3 to promote axon outgrowth in mouse hippocampal neurons. GSK-3 binds to and directly phosphorylates SRF on a highly conserved serine residue. This serine phosphorylation is necessary for SRF activity and for its interaction with MKL-family cofactors, MKL1 and MKL2, but not with TCF-family cofactor, ELK-1. Axonal growth deficits caused by GSK-3 inhibition could be rescued by expression of a constitutively active SRF. The SRF target gene and actin-binding protein, vinculin, is sufficient to overcome the axonal growth deficits of SRF-deficient and GSK-3-inhibited neurons. Furthermore, short hairpin RNA-mediated knockdown of vinculin also attenuated axonal growth. Thus, our findings reveal a novel phosphorylation and activation of SRF by GSK-3 that is critical for SRF-dependent axon growth in mammalian central neurons.

Features in visual search combine linearly

Single features such as line orientation and length are known to guide visual search, but relatively little is known about how multiple features combine in search. To address this question, we investigated how search for targets differing in multiple features ( intensity, length, orientation) from the distracters is related to searches for targets differing in each of the individual features. We tested race models (based on reaction times) and coactivation models ( based on reciprocal of reaction times) for their ability to predict multiple feature searches. Multiple feature searches were best accounted for by a co-activation model in which feature information combined linearly (r = 0.95). This result agrees with the classic finding that these features are separable i.e., subjective dissimilarity ratings sum linearly. We then replicated the classical finding that the length and width of a rectangle are integral features-in other words, they combine nonlinearly in visual search. However, to our surprise, upon including aspect ratio as an additional feature, length and width combined linearly and this model outperformed all other models. Thus, length and width of a rectangle became separable when considered together with aspect ratio. This finding predicts that searches involving shapes with identical aspect ratio should be more difficult than searches where shapes differ in aspect ratio. We confirmed this prediction on a variety of shapes. We conclude that features in visual search co-activate linearly and demonstrate for the first time that aspect ratio is a novel feature that guides visual search.

Consequences of Converting Graded to Action Potentials upon Neural Information Coding and Energy Efficiency

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a `footprint' in the generator potential that obscures incoming signals. These three processes reduce information rates by similar to 50% in generator potentials, to similar to 3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation.

Effect of amplitude correlations on coherence in the local field potential

Neural activity across the brain shows both spatial and temporal correlations at multiple scales, and understanding these correlations is a key step toward understanding cortical processing. Correlation in the local field potential (LFP) recorded from two brain areas is often characterized by computing the coherence, which is generally taken to reflect the degree of phase consistency across trials between two sites. Coherence, however, depends on two factors-phase consistency as well as amplitude covariation across trials-but the spatial structure of amplitude correlations across sites and its contribution to coherence are not well characterized. We recorded LFP from an array of microelectrodes chronically implanted in the primary visual cortex of monkeys and studied correlations in amplitude across electrodes as a function of interelectrode distance. We found that amplitude correlations showed a similar trend as coherence as a function of frequency and interelectrode distance. Importantly, even when phases were completely randomized between two electrodes, amplitude correlations introduced significant coherence. To quantify the contributions of phase consistency and amplitude correlations to coherence, we simulated pairs of sinusoids with varying phase consistency and amplitude correlations. These simulations confirmed that amplitude correlations can significantly bias coherence measurements, resulting in either over-or underestimation of true phase coherence. Our results highlight the importance of accounting for the correlations in amplitude while using coherence to study phase relationships across sites and frequencies.

Critical cysteines in Akt1 regulate its activity and proteasomal degradation: implications for neurodegenerative diseases

Impaired Akt1 signaling is observed in neurodegenerative diseases, including Parkinson's disease (PD). In PD models oxidative modification of Akt1 leads to its dephosphorylation and consequent loss of its kinase activity. To explore the underlying mechanism we exposed Neuro2A cells to cadmium, a pan inhibitor of protein thiol disulfide oxidoreductases, including glutaredoxin 1 (Grx1), or downregulated Grx1, which led to dephosphorylation of Akt1, loss of its kinase activity, and also decreased Akt1 protein levels. Mutation of cysteines to serines at 296 and 310 in Akt1 did not affect its basal kinase activity but abolished cadmium- and Grx1 downregulation-induced reduction in Akt1 kinase activity, indicating their critical role in redox modulation of Akt1 function and turnover. Cadmium-induced decrease in phosphorylated Akt1 correlated with increased association of wild-type (WT) Akt1 with PP2A, which was absent in the C296-310S Akt1 mutant and was also abolished by N-acetylcysteine treatment. Further, increased proteasomal degradation of Akt1 by cadmium was not seen in the C296-310S Akt1 mutant, indicating that oxidation of cysteine residues facilitates degradation of WT Akt1. Moreover, preventing oxidative modification of Akt1 cysteines 296 and 310 by mutating them to serines increased the cell survival effects of Akt1. Thus, in neurodegenerative states such as PD, maintaining the thiol status of cysteines 296 and 310 in Akt1 would be critical for Akt1 kinase activity and for preventing its degradation by proteasomes. Preventing downregulation of Akt signaling not only has long-range consequences for cell survival but could also affect the multiple roles that Ala plays, including in the Akt-mTOR signaling cascade. (C) 2014 Elsevier Inc. All rights reserved.

Online Estimation of Evolving Human Visual Interest

Regions in video streams attracting human interest contribute significantly to human understanding of the video. Being able to predict salient and informative Regions of Interest (ROIs) through a sequence of eye movements is a challenging problem. Applications such as content-aware retargeting of videos to different aspect ratios while preserving informative regions and smart insertion of dialog (closed-caption text) into the video stream can significantly be improved using the predicted ROIs. We propose an interactive human-in-the-loop framework to model eye movements and predict visual saliency into yet-unseen frames. Eye tracking and video content are used to model visual attention in a manner that accounts for important eye-gaze characteristics such as temporal discontinuities due to sudden eye movements, noise, and behavioral artifacts. A novel statistical-and algorithm-based method gaze buffering is proposed for eye-gaze analysis and its fusion with content-based features. Our robust saliency prediction is instantiated for two challenging and exciting applications. The first application alters video aspect ratios on-the-fly using content-aware video retargeting, thus making them suitable for a variety of display sizes. The second application dynamically localizes active speakers and places dialog captions on-the-fly in the video stream. Our method ensures that dialogs are faithful to active speaker locations and do not interfere with salient content in the video stream. Our framework naturally accommodates personalisation of the application to suit biases and preferences of individual users.

Use of Exocentric and Egocentric Representations in the Concurrent Planning of Sequential Saccades

The concurrent planning of sequential saccades offers a simple model to study the nature of visuomotor transformations since the second saccade vector needs to be remapped to foveate the second target following the first saccade. Remapping is thought to occur through egocentric mechanisms involving an efference copy of the first saccade that is available around the time of its onset. In contrast, an exocentric representation of the second target relative to the first target, if available, can be used to directly code the second saccade vector. While human volunteers performed a modified double-step task, we examined the role of exocentric encoding in concurrent saccade planning by shifting the first target location well before the efference copy could be used by the oculomotor system. The impact of the first target shift on concurrent processing was tested by examining the end-points of second saccades following a shift of the second target during the first saccade. The frequency of second saccades to the old versus new location of the second target, as well as the propagation of first saccade localization errors, both indices of concurrent processing, were found to be significantly reduced in trials with the first target shift compared to those without it. A similar decrease in concurrent processing was obtained when we shifted the first target but kept constant the second saccade vector. Overall, these results suggest that the brain can use relatively stable visual landmarks, independent of efference copy-based egocentric mechanisms, for concurrent planning of sequential saccades.

Selective Review of Proton Magnetic Resonance Spectroscopy in Schizophrenia

Magnetic Resonance Spectroscopy (MRS) offers a unique opportunity to measure brain metabolites in-vivo, and in doing so enables one to understand the brain function and cellular processes implicated in the pathophysiology of psychiatric disorders. MRS, in addition to being non-invasive, is devoid of radioactive tracers and ionizing radiation, a distinct advantage over other imaging modalities like positron emission tomography and single photon emission computed tomography. With advances in MRS technique it is now possible to quantify concentrations of relevant compounds like neurotransmitters, neuronal viability markers and pharmacological compounds. Majority of the MRS studies have examined the neurometabolites in schizophrenia, a common and debilitating psychiatric disorder. Abnormalities in N Acetyl aspartate and Glutamate are consistently reported while the reports regarding the myoinsoitol and choline are inconsistent. These abnormalities are not changed across the illness stages and despite treatment. However, multiple technical challenges have limited the widespread use of MRS in psychiatric disorders. Guidelines for uniform acquisition and preprocessing are need of the hour, which. would increase the replicability and validity of MRS measures in psychiatry. Finally long term, prospective, longitudinal studies are required in different psychiatric disorders for potential clinical applications.

Texture discriminability in monkey inferotemporal cortex predicts human texture perception

Shape and texture are both important properties of visual objects, but texture is relatively less understood. Here, we characterized neuronal responses to discrete textures in monkey inferotemporal (IT) cortex and asked whether they can explain classic findings in human texture perception. We focused on three classic findings on texture discrimination: 1) it can be easy or hard depending on the constituent elements; 2) it can have asymmetries, and 3) it is reduced for textures with randomly oriented elements. We recorded neuronal activity from monkey inferotemporal (IT) cortex and measured texture perception in humans for a variety of textures. Our main findings are as follows: 1) IT neurons show congruent selectivity for textures across array size; 2) textures that were easy for humans to discriminate also elicited distinct patterns of neuronal activity in monkey IT; 3) texture pairs with asymmetries in humans also exhibited asymmetric variation in firing rate across monkey IT; and 4) neuronal responses to randomly oriented textures were explained by an average of responses to homogeneous textures, which rendered them less discriminable. The reduction in discriminability of monkey IT neurons predicted the reduced discriminability in humans during texture discrimination. Taken together, our results suggest that texture perception in humans is likely based on neuronal representations similar to those in monkey IT.

Chaperone protein HYPK interacts with the first 17 amino acid region of Huntingtin and modulates mutant HTT-mediated aggregation and cytotoxicity

Huntington's disease is a polyglutamine expansion disorder, characterized by mutant HTT-mediated aggregate formation and cytotoxicity. Many reports suggests roles of N-terminal 17 amino acid domain of HTT (HTT-N17) towards subcellular localization, aggregate formation and subsequent pathogenicity induced by N-terminal HTT harboring polyQ stretch in pathogenic range. HYPK is a HTT-interacting chaperone which can reduce N-terminal mutant HTT-mediated aggregate formation and cytotoxicity in neuronal cell lines. However, how HYPK interacts with N-terminal fragment of HTT remained unknown. Here we report that specific interaction of HYPK with HTT-N17 is crucial for the chaperone activity of HYPK. Deletion of HTT-N17 leads to formation of tinier, SDS-soluble nuclear aggregates formed by N-terminal mutant HTT. The increased cytotoxicity imparted by these tiny aggregates might be contributed due to loss of interaction with HYPK. (C) 2014 Elsevier Inc. All rights reserved.