Deficits in temporal order memory induced by interferon-alpha (IFN-α) treatment are rescued by aerobic exercise

Patients receiving cytokine immunotherapy with IFN-α frequently present with neuropsychiatric consequences and cognitive impairments, including a profound depressive-like symptomatology. While the neurobiological substrates of the dysfunction that leads to adverse events in IFN-α-treated patients remains ill-defined, dysfunctions of the hippocampus and prefrontal cortex (PFC) are strong possibilities. To date, hippocampal deficits have been well-characterised; there does however remain a lack of insight into the nature of prefrontal participation. Here, we used a PFC-supported temporal order memory paradigm to examine if IFN-α treatment induced deficits in performance; additionally, we used an object recognition task to assess the integrity of the perirhinal cortex (PRH). Finally, the utility of exercise as an ameliorative strategy to recover temporal order deficits in rats was also explored. We found that IFN-α-treatment impaired temporal order memory discriminations, whereas recognition memory remained intact, reflecting a possible dissociation between recognition and temporal order memory processing. Further characterisation of temporal order memory impairments using a longitudinal design revealed that deficits persisted for 10 weeks following cessation of IFN-α-treatment. Finally, a 6 week forced exercise regime reversed IFN-α-induced deficits in temporal order memory. These data provide further insight into the circuitry involved in cognitive impairments arising from IFN-α-treatment. Here we suggest that PFC (or the hippocampo-prefrontal pathway) may be compromised whilst the function of the PRH is preserved. Deficits may persist after cessation of IFN-α-treatment which suggests that extended patient monitoring is required. Aerobic exercise may be restorative and could prove beneficial for patients treated with IFN-α

Space and time-related firing in a model of hippocampo-cortical interactions

International audienceIn a previous model [3], a spectral timing neural network [4] was used to account for the role of the Hs in the acquisition of classical conditioning. The ability to estimate the timing between separate events was then used to learn and predict transitions between places in the environment. We propose a neural architecture based on this work and explaining the out-of-field activities in the Hs along with their temporal prediction capabilities. The model uses the hippocampo-cortical pathway as a means to spread reward signals to entorhinal neurons. Secondary predictions of the reward signal are then learned, based on transition learning, by pyramidal neurons of the CA region

Regulation of Yersina pestis Virulence by AI-2 Mediated Quorum Sensing

The proposed research was motivated by an interest in understanding Y. pestis virulence mechanisms and bacteria cell-cell communication. It is expected that a greater understanding of virulence mechanisms will ultimately lead to biothreat countermeasures and novel therapeutics. Y. pestis is the etiological agent of plague, the most devastating disease in human history. Y. pestis infection has a high mortality rate and a short incubation before mortality. There is no widely available and effective vaccine for Y. pestis and multi-drug resistant strains are emerging. Y. pestis is a recognized biothreat agent based on the wide distribution of the bacteria in research laboratories around the world and on the knowledge that methods exist to produce and aerosolize large amounts of bacteria. We hypothesized that cell-cell communication via signaling molecules, or quorum sensing, by Y. pestis is important for the regulation of virulence factor gene expression during host invasion, though a causative link had never been established. Quorum sensing is a mode of intercellular communication which enables orchestration of gene expression for many bacteria as a function of population density and available evidence suggests there may be a link between quorum sensing and regulation of Y. pesits virulence. Several pathogenic bacteria have been shown to regulate expression of virulence factor genes, including genes encoding type III secretion, via quorum sensing. The Y. pestis genome encodes several cell-cell signaling pathways and the interaction of at least three of these are thought to be involved in one or more modes of host invasion. Furthermore, Y. pestis gene expression array studies carried out at LLNL have established a correlation between expression of known virulence factors and genes involved in processing of the AI-2 quorum sensing signal. This was a basic research project that was intended to provide new insights into bacterial intercellular communication and how it is used to regulate virulence in Y. pestis. It is known that many bacteria use intercellular signaling molecules to orchestrate gene expression and cellular function. A fair amount is known about production and uptake of signaling molecules, but very little is known about how intercellular signaling regulates other pathways. Although several studies demonstrate that intercellular signaling plays a role in regulating virulence in other pathogens, the link between signaling and regulation of virulence has not been established. Very little work had been done directly with Y. pestis intercellular signaling apart from the work carried out at LLNL. The research we proposed was intended to both establish a causative link between AI-2 intercellular signaling and regulation of virulence in Y. pestis and elucidate the fate of the AI-2 signaling molecule after it is taken up and processed by Y. pestis. Elucidating the fate of AI-2 was expected to lead directly to the understanding of how AI-2 signal processing regulates other pathways as well as provide new insights in this direction

Model of the Hippocampal Learning of Spatio-temporal Sequences

International audienceWe propose a model of the hippocampus aimed at learning the timed association between subsequent sensory events. The properties of the neural network allow it to learn and predict the evolution of con- tinuous rate-coded signals as well as the occurrence of transitory events, using both spatial and non-spatial information. The system is able to provide predictions based on the time trace of past sensory events. Per- formance of the neural network in the precise temporal learning of spatial and non-spatial signals is tested in a simulated experiment. The ability of the hippocampus proper to predict the occurrence of upcoming spatio- temporal events could play a crucial role in the carrying out of tasks requiring accurate time estimation and spatial localization

Insensitivity of place cells to the value of spatial goals in a two-choice flexible navigation task

Hippocampal place cells show position-specific activity, thought to reflect a self-localization signal. Several reports also point to some form of goal encoding by place cells. We investigated this by asking whether they also encode the value of spatial goals, which is a crucial information for optimizing goal-directed navigation. We used a continuous place navigation task in which male rats navigate to one of two (freely chosen) unmarked locations and wait, triggering the release of reward which is then located and consumed elsewhere. This allows sampling of place fields, and dissociates spatial goal from reward consumption. The two goals varied in the amount of reward provided, allowing assessment of whether the rats factored goal value into their navigational choice, and of possible neural correlates of this value. Rats successfully learned the task, indicating goal localization, and they preferred higher-value goals, indicating processing of goal value. Replicating previous findings, there was goal-related activity in the out-of-field firing of CA1 place cells, with a ramping-up of firing rate during the waiting period, but no general over-representation of goals by place fields, an observation that we extended to CA3 place cells. Importantly, place cells were not modulated by goal value. This suggests that dorsal hippocampal place cells encode space independently of its associated value, despite the effect of that value on spatial behavior. Our findings are consistent with a model of place cells in which they provide a spontaneously constructed value-free spatial representation, rather than encoding other navigationally relevant, but non-spatial, information

An adaptive first-order polarization-mode dispersion compensation system aided by polarization scrambling: Theory and demonstration

©2000 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.An adaptive polarization-mode dispersion (PMD) compensation system has been developed to cancel the effects of first-order PMD by producing a complementary PMD vector in the receiver. Control parameters for the PMD compensation system comprised of a polarization controller and a PMD emulator are derived from the nonreturn-to-zero (NRZ) signal in the channel to be compensated. Estimates of the link's differential group delay (DGD) and principal states of polarization (PSP's) based on this signal are reliable when the signal power is equally split between the link's two PSP's; however this condition cannot be assumed, To meet this requirement, we scramble the state of polarization (SOP) of the input signal at a rate much greater than the response time of the PMD monitor signal so that each sample represents many different SOP alignments. This approach allows the effective cancellation of the first-order PMD effects within an optical fiber channel

Electrophysiological correlates of high-level perception during spatial navigation

We studied the electrophysiological basis of object recognition by recording scalp\ud electroencephalograms while participants played a virtual-reality taxi driver game.\ud Participants searched for passengers and stores during virtual navigation in simulated\ud towns. We compared oscillatory brain activity in response to store views that were targets or\ud nontargets (during store search) or neutral (during passenger search). Even though store\ud category was solely defined by task context (rather than by sensory cues), frontal ...\ud \u

Neutrino oscillations from relativistic flavor currents

By resorting to recent results on the relativistic currents for mixed (flavor) fields, we calculate a space-time dependent neutrino oscillation formula in Quantum Field Theory. Our formulation provides an alternative to existing approaches for the derivation of space dependent oscillation formulas and it also accounts for the corrections due to the non-trivial nature of the flavor vacuum. By exploring different limits of our formula, we recover already known results. We study in detail the case of one-dimensional propagation with gaussian wavepackets both in the relativistic and in the non-relativistic regions: in the last case, numerical evaluations of our result show significant deviations from the standard formula.Comment: 16 pages, 4 figures, RevTe

Crop-livestock integration provides opportunities to mitigate environmental trade-offs in transitioning smallholder agricultural systems of the Greater Mekong Subregion

CONTEXT: The Greater Mekong Subregion has been undergoing rapid agricultural transformation over the last decades, as traditional diverse subsistence-oriented agriculture is evolving towards intensified commercial production systems. Negative environmental impacts often include deforestation, nutrient pollution, and greenhouse gas (GHG) emissions. OBJECTIVE: This study aims to explore the potential of crop-livestock integration to mitigate trade-offs between economic and environmental impacts of smallholder farming systems at different stages of agricultural transition and degrees of agricultural diversity across the Greater Mekong Subregion. METHODS: We chose a ‘middle ground’ between detailed modeling of few, representative farming systems and modeling of large household populations. 24 low and high diversity farms were selected in Laos (Xieng Khouang province), Cambodia (Ratanakiri province) and Vietnam (Central Highlands) from a survey dataset of 1300 households. These farming systems were simulated with the whole-farm bio-economic and multi-objective optimization model FarmDESIGN, calculating operating profit, GHG emissions and nitrogen (N) balance. Two optimizations (‘business as usual’ vs. ‘crop-livestock integration’) were performed, generating ‘solution spaces’ or alternative configurations aiming to maximize profitability, keep farm N balanced and minimize GHG emissions. RESULTS AND CONCLUSIONS: Agricultural systems across the sites differed in their production orientation and management practices, representing various stages of agricultural transition. Nitrogen balances varied between sites, being negative in Ratanakiri (average 20.5 kg N ha 1 y 1) and Xieng Khouang ( 36.5 kg N ha 1 y 1) and positive in the Central Highlands (73 kg N ha 1 y 1). Negative balances point to unsustainable mining of nutrients due to sale of cash crops without sufficient inputs, and positive balances to the risk of environmental contamination. Total GHG emissions ranged from 0.52–8.12 t CO2e ha 1 and were not significantly impacted by stage of agricultural transformation or agricultural diversity. GHG sources in Ratanakiri and Xieng Khouang were determined by crop residue burning while in Central Highlands fertilizer and livestock were main emitters. High diversity farms obtained higher operating profits (10,379 USD y 1) than low diversity farms (4584 USD y 1). Crop-livestock integration, a combination of measures including introduction of improved forages grasses, manure recycling and residue feeding, and reduction of residue burning, resulted in larger ‘solution spaces’, thus providing farmers with more options to mitigate agro-environmental trade-offs. SIGNIFICANCE: These findings underline the potential of crop-livestock integration to support sustainable intensification pathways in the Greater Mekong region. Public and private investment in further research and extension is needed to develop and scale context-specific crop-livestock integration practices