The role of ongoing dendritic oscillations in single-neuron dynamics

The dendritic tree contributes significantly to the elementary computations a neuron performs while converting its synaptic inputs into action potential output. Traditionally, these computations have been characterized as temporally local, near-instantaneous mappings from the current input of the cell to its current output, brought about by somatic summation of dendritic contributions that are generated in spatially localized functional compartments. However, recent evidence about the presence of oscillations in dendrites suggests a qualitatively different mode of operation: the instantaneous phase of such oscillations can depend on a long history of inputs, and under appropriate conditions, even dendritic oscillators that are remote may interact through synchronization. Here, we develop a mathematical framework to analyze the interactions of local dendritic oscillations, and the way these interactions influence single cell computations. Combining weakly coupled oscillator methods with cable theoretic arguments, we derive phase-locking states for multiple oscillating dendritic compartments. We characterize how the phase-locking properties depend on key parameters of the oscillating dendrite: the electrotonic properties of the (active) dendritic segment, and the intrinsic properties of the dendritic oscillators. As a direct consequence, we show how input to the dendrites can modulate phase-locking behavior and hence global dendritic coherence. In turn, dendritic coherence is able to gate the integration and propagation of synaptic signals to the soma, ultimately leading to an effective control of somatic spike generation. Our results suggest that dendritic oscillations enable the dendritic tree to operate on more global temporal and spatial scales than previously thought

On How Network Architecture Determines the Dominant Patterns of Spontaneous Neural Activity

In the absence of sensory stimulation, neocortical circuits display complex patterns of neural activity. These patterns are thought to reflect relevant properties of the network, including anatomical features like its modularity. It is also assumed that the synaptic connections of the network constrain the repertoire of emergent, spontaneous patterns. Although the link between network architecture and network activity has been extensively investigated in the last few years from different perspectives, our understanding of the relationship between the network connectivity and the structure of its spontaneous activity is still incomplete. Using a general mathematical model of neural dynamics we have studied the link between spontaneous activity and the underlying network architecture. In particular, here we show mathematically how the synaptic connections between neurons determine the repertoire of spatial patterns displayed in the spontaneous activity. To test our theoretical result, we have also used the model to simulate spontaneous activity of a neural network, whose architecture is inspired by the patchy organization of horizontal connections between cortical columns in the neocortex of primates and other mammals. The dominant spatial patterns of the spontaneous activity, calculated as its principal components, coincide remarkably well with those patterns predicted from the network connectivity using our theory. The equivalence between the concept of dominant pattern and the concept of attractor of the network dynamics is also demonstrated. This in turn suggests new ways of investigating encoding and storage capabilities of neural networks

Evaluation of the Oscillatory Interference Model of Grid Cell Firing through Analysis and Measured Period Variance of Some Biological Oscillators

Models of the hexagonally arrayed spatial activity pattern of grid cell firing in the literature generally fall into two main categories: continuous attractor models or oscillatory interference models. Burak and Fiete (2009, PLoS Comput Biol) recently examined noise in two continuous attractor models, but did not consider oscillatory interference models in detail. Here we analyze an oscillatory interference model to examine the effects of noise on its stability and spatial firing properties. We show analytically that the square of the drift in encoded position due to noise is proportional to time and inversely proportional to the number of oscillators. We also show there is a relatively fixed breakdown point, independent of many parameters of the model, past which noise overwhelms the spatial signal. Based on this result, we show that a pair of oscillators are expected to maintain a stable grid for approximately t = 5µ3/(4πσ)2 seconds where µ is the mean period of an oscillator in seconds and σ2 its variance in seconds2. We apply this criterion to recordings of individual persistent spiking neurons in postsubiculum (dorsal presubiculum) and layers III and V of entorhinal cortex, to subthreshold membrane potential oscillation recordings in layer II stellate cells of medial entorhinal cortex and to values from the literature regarding medial septum theta bursting cells. All oscillators examined have expected stability times far below those seen in experimental recordings of grid cells, suggesting the examined biological oscillators are unfit as a substrate for current implementations of oscillatory interference models. However, oscillatory interference models can tolerate small amounts of noise, suggesting the utility of circuit level effects which might reduce oscillator variability. Further implications for grid cell models are discussed

Spatial and Temporal Variations in the Annual Pollen Index Recorded by Sites Belonging to the Portuguese Aerobiology Network

This study presents the findings of a 10-year survey carried out by the Portuguese Aerobiology Network (RPA) at seven pollen-monitoring stations: five mainland stations (Oporto, Coimbra, Lisbon, Évora and Portimão) and two insular stations [Funchal (Madeira archipelago) and Ponta Delgada (Azores archipelago)]. The main aim of the study was to examine spatial and temporal variations in the Annual Pollen Index (API) with particular focus on the most frequently recorded pollen types. Pollen monitoring (2003–2012) was carried out using Hirst-type volumetric spore traps, following the minimum recommendations proposed by the European Aerobiology Society Working Group on Quality Control. Daily pollen data were examined for similarities using the Kruskal–Wallis nonparametric test and multivariate regression trees. Simple linear regression analysis was used to describe trends in API. The airborne pollen spectrum at RPA stations is dominated by important allergenic pollen types such as Poaceae, Olea and Urticaceae. Statistically significant differences were witnessed in the API recorded at the seven stations. Mean API is higher in the southern mainland cities, e.g. Évora, Lisbon and Portimão, and lower in insular and littoral cities. There were also a number of significant trends in API during the 10-year study. This report identifies spatial and temporal variations in the amount of airborne pollen recorded annually in the Portuguese territory. There were also a number of significant changes in API, but no general increases in the amount of airborne pollen

Quantitative Proteomics of Intracellular Campylobacter jejuni Reveals Metabolic Reprogramming

Campylobacter jejuni is the major cause of bacterial food-borne illness in the USA and Europe. An important virulence attribute of this bacterial pathogen is its ability to enter and survive within host cells. Here we show through a quantitative proteomic analysis that upon entry into host cells, C. jejuni undergoes a significant metabolic downshift. Furthermore, our results indicate that intracellular C. jejuni reprograms its respiration, favoring the respiration of fumarate. These results explain the poor ability of C. jejuni obtained from infected cells to grow under standard laboratory conditions and provide the bases for the development of novel anti microbial strategies that would target relevant metabolic pathways

NOXA as critical mediator for drug combinations in polychemotherapy

During polychemotherapy, cytotoxic drugs are given in combinations to enhance their anti-tumor effectiveness. For most drug combinations, underlying signaling mechanisms responsible for positive drug–drug interactions remain elusive. Here, we prove a decisive role for the Bcl-2 family member NOXA to mediate cell death by certain drug combinations, even if drugs were combined which acted independently from NOXA, when given alone. In proof-of-principle studies, betulinic acid, doxorubicin and vincristine induced cell death in a p53- and NOXA-independent pathway involving mitochondrial pore formation, release of cytochrome c and caspase activation. In contrast, when betulinic acid was combined with either doxorubicine or vincristine, cell death signaling changed considerably; the drug combinations clearly depended on both p53 and NOXA. Similarly and of high clinical relevance, in patient-derived childhood acute leukemia samples the drug combinations, but not the single drugs depended on p53 and NOXA, as shown by RNA interference studies in patient-derived cells. Our data emphasize that NOXA represents an important target molecule for combinations of drugs that alone do not target NOXA. NOXA might have a special role in regulating apoptosis sensitivity in the complex interplay of polychemotherapy. Deciphering the differences in signaling of single drugs and drug combinations might enable designing highly effective novel polychemotherapy regimens

Hypoxia increases the metastatic ability of breast cancer cells via upregulation of CXCR4

<p>Abstract</p> <p>Background</p> <p>Chemokine SDF1α and its unique receptor CXCR4 have been implicated in organ-specific metastases of many cancers including breast cancer. Hypoxia is a common feature of solid tumors and is associated with their malignant phenotype. We hypothesized that hypoxia would upregulate CXCR4 expression and lead to increased chemotactic responsiveness to its specific ligand SDF1α.</p> <p>Methods</p> <p>Three breast cancer cell lines MDA-MB-231, MCF7 and 4T1 were subjected to 48 hrs of hypoxia or normoxia. Cell surface receptor expression was evaluated using flow cytometry. An extracellular matrix invasion assay and microporous migration assay was used to assess chemotactic response and metastatic ability.</p> <p>Results</p> <p>CXCR4 surface expression was significantly increased in the two human breast cancer cell lines, MDA-MB-231 and MCF7, following exposure to hypoxia. This upregulation of CXCR4 cell surface expression corresponded to a significant increase in migration and invasion in response to SDF1-α <it>in vitro</it>. The increase in metastatic potential of both the normoxic and the hypoxic treated breast cancer cell lines was attenuated by neutralization of CXCR4 with a CXCR4 neutralizing mAb, MAB172 or a CXCR4 antagonist, AMD3100, showing the relationship between CXCR4 overexpression and increased chemotactic responsiveness.</p> <p>Conclusions</p> <p>CXCR4 expression can be modulated by the tissue microenvironment such as hypoxia. Upregulation of CXCR4 is associated with increased migratory and invasive potential and this effect can be abrogated by CXCR4 inhibition. Chemokine receptor CXCR4 is a potential therapeutic target in the adjuvant treatment of breast cancer.</p

Functional and Computational Analysis of Amino Acid Patterns Predictive of Type III Secretion System Substrates in Pseudomonas syringae

Bacterial type III secretion systems (T3SSs) deliver proteins called effectors into eukaryotic cells. Although N-terminal amino acid sequences are required for translocation, the mechanism of substrate recognition by the T3SS is unknown. Almost all actively deployed T3SS substrates in the plant pathogen Pseudomonas syringae pathovar tomato strain DC3000 possess characteristic patterns, including (i) greater than 10% serine within the first 50 amino acids, (ii) an aliphatic residue or proline at position 3 or 4, and (iii) a lack of acidic amino acids within the first 12 residues. Here, the functional significance of the P. syringae T3SS substrate compositional patterns was tested. A mutant AvrPto effector protein lacking all three patterns was secreted into culture and translocated into plant cells, suggesting that the compositional characteristics are not absolutely required for T3SS targeting and that other recognition mechanisms exist. To further analyze the unique properties of T3SS targeting signals, we developed a computational algorithm called TEREE (Type III Effector Relative Entropy Evaluation) that distinguishes DC3000 T3SS substrates from other proteins with a high sensitivity and specificity. Although TEREE did not efficiently identify T3SS substrates in Salmonella enterica, it was effective in another P. syringae strain and Ralstonia solanacearum. Thus, the TEREE algorithm may be a useful tool for identifying new effector genes in plant pathogens. The nature of T3SS targeting signals was additionally investigated by analyzing the N-terminus of FtsX, a putative membrane protein that was classified as a T3SS substrate by TEREE. Although the first 50 amino acids of FtsX were unable to target a reporter protein to the T3SS, an AvrPto protein substituted with the first 12 amino acids of FtsX was translocated into plant cells. These results show that the T3SS targeting signals are highly mutable and that secretion may be directed by multiple features of substrates

Threat of allergenic airborne grass pollen in Szczecin, NW Poland: the dynamics of pollen seasons, effect of meteorological variables and air pollution

The dynamics of Poaceae pollen season, in particularly that of the Secale genus, in Szczecin (western Poland) 2004–2008 was analysed to establish a relationship between the meteorological variables, air pollution and the pollen count of the taxa studied. Consecutive phases during the pollen season were defined for each taxon (1, 2.5, 5, 25, 50, 75, 95, 97.5, 99% of annual total), and duration of the season was determined using the 98% method. On the basis of this analysis, the temporary differences in the dynamics of the seasons were most evident for Secale in 2005 and 2006 with the longest main pollen season (90% total pollen). The pollen season of Poaceae started the earliest in 2007, when thermal conditions were the most favourable. Correlation analysis with meteorological factors demonstrated that the relative humidity, mean and maximum air temperature, and rainfall were the factors influencing the average daily pollen concentrations in the atmosphere; also, the presence of air pollutants such as ozone, PM10 and SO2 was statistically related to the pollen count in the air. However, multiple regression models explained little part of the total variance. Atmospheric pollution induces aggravation of symptoms of grass pollen allergy