Unified theoretical framework for mixing state of black carbon

Black carbon (BC) plays an important role in the climate system due to its strongwarming effect, yet the magnitude of this effect is highly uncertain due to the complex mixingstate of aerosols. Here we build a unified theoretical framework to describe BC’s mixing states,linking dynamic processes to BC coating thickness distribution, and show its self-similarity for sites in diverse environments. The size distribution of BC-containing particles is found to followan exponential pattern and is independent of BC core size. A mixing state module is establishedbased on this finding and successfully applied in global and regional models, which increases theaccuracy of aerosol climate effect estimations. Our theoretical framework can bridge the gap be-tween observation and model simulation in both mixing state description and light absorption quantification<br

An almond-enriched diet increases plasma α-tocopherol and improves vascular function but does not affect oxidative stress markers or lipid levels

Vascular dysfunction is one of the major causes of cardiovascular (CV) mortality and increases with age. Epidemiological studies suggest that Mediterranean diets and high nut consumption reduce CV disease risk and mortality while increasing plasma α-tocopherol. Therefore, we have investigated whether almond supplementation can improve oxidative stress markers and CV risk factors over 4 weeks in young and middle-aged men. Healthy middle-aged men (56 ± 5.8 years), healthy young men (22.1 ± 2.9 years) and young men with two or more CV risk factors (27.3 ± 5 years) consumed 50 g almond/day for 4 weeks. A control group maintained habitual diets over the same period. Plasma α-tocopherol/cholesterol ratios were not different between groups at baseline and were significantly elevated by almond intervention with 50 g almond/day for 4 weeks (p < 0.05). Plasma protein oxidation and nitrite levels were not different between groups whereas, total-, HDL- and LDL-cholesterols and triglycerides were significantly higher in healthy middle-aged and young men with CV risk factors but were not affected by intake. In the almond-consuming groups, flow-mediated dilatation (FMD) improved and systolic blood pressure reduced significantly after 50 g almonds/day for 4 weeks, but diastolic blood pressure reduced only in healthy men. In conclusion, a short-term almond-enriched diet can increase plasma α-tocopherol and improve vascular function in asymptomatic healthy men aged between 20 and 70 years without any effect on plasma lipids or markers of oxidative stress. © 2014 Informa UK, Ltd

Genetic Deletion of the Nociceptin/Orphanin FQ Receptor in the Rat Confers Resilience to the Development of Drug Addiction

The nociceptin (NOP) receptor is a G-protein-coupled receptor whose natural ligand is the nociceptin/orphanin FQ (N/OFQ) peptide. Evidence from pharmacological studies suggests that the N/OFQ system is implicated in the regulation of several addiction-related phenomena, such as drug intake, withdrawal and relapse. Here, to further explore the role of NOP system in addiction, we used NOP (-/-) rats to study the motivation for cocaine, heroin and alcohol self-administration in the absence of N/OFQ function. Conditioned place preference (CPP) and saccharin (0.2% w/v) self-administration were also investigated. Results showed that NOP (-/-) rats self-administer less cocaine (0.25, 0.125 or 0.5 mg/infusion) both under a Fixed Ratio 1 and a Progressive Ratio schedule of reinforcement compared to wild type (Wt) controls. Consistently, cocaine (10 mg/kg, i.p.) was able to induce CPP in Wt but not in NOP (-/-). When NOP (-/-) rats were tested for heroin (20 μg/infusion) and ethanol (10% v/v) self-administration, they showeda significantly lower drug intake compared to Wt. Conversely, saccharin self-administration was not affected by NOP deletion, excluding the possibility of nonspecific learning deficits or generalized disruption of reward mechanisms in NOP (-/-) rats. These findings were confirmed with pharmacological experiments using two selective NOP antagonists, SB-612111 and LY2817412. Both drugs attenuated alcohol self-administration in Wt rats but not in NOP (-/-) rats. In conclusion, our results demonstrate that genetic deletion of NOP receptors confers resilience to drug abuse and support a role for NOP receptor antagonism as a potential treatment option for drug addiction.Neuropsychopharmacology accepted article preview online, 26 August 2016. doi:10.1038/npp.2016.171

Seizure prediction : ready for a new era

Acknowledgements: The authors acknowledge colleagues in the international seizure prediction group for valuable discussions. L.K. acknowledges funding support from the National Health and Medical Research Council (APP1130468) and the James S. McDonnell Foundation (220020419) and acknowledges the contribution of Dean R. Freestone at the University of Melbourne, Australia, to the creation of Fig. 3.Peer reviewedPostprin

Phytochemical-loaded mesoporous silica nanoparticles for nose-to-brain olfactory drug delivery

Central nervous system (CNS) drug delivery is often hampered due to the insidious nature of the blood-brain barrier (BBB). Nose-to-brain delivery via olfactory pathways have become a target of attention for drug delivery due to bypassing of the BBB. The antioxidant properties of phytochemicals make them promising as CNS active agents but possess poor water solubility and limited BBB penetration. The primary aim of this study was the development of mesoporous silica nanoparticles (MSNs) loaded with the poorly water-soluble phytochemicals curcumin and chrysin which could be utilised for nose-to-brain delivery. We formulated spherical MSNP using a templating approach resulting in ∼220nm particles with a high surface porosity. Curcumin and chrysin were successfully loaded into MSNP and confirmed through Fourier transformation infrared spectroscopy (FT-IR), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA) and HPLC approaches with a loading of 11-14% for curcumin and chrysin. Release was pH dependant with curcumin demonstrating increased chemical stability at a lower pH (5.5) with a release of 53.2%±2.2% over 24h and 9.4±0.6% for chrysin. MSNP were demonstrated to be non-toxic to olfactory neuroblastoma cells OBGF400, with chrysin (100μM) demonstrating a decrease in cell viability to 58.2±8.5% and curcumin an IC50 of 33±0.18μM. Furthermore confocal microscopy demonstrated nanoparticles of <500nm were able to accumulate within cells with FITC-loaded MSNP showing membrane localised and cytoplasmic accumulation following a 2h incubation. MSNP are useful carriers for poorly soluble phytochemicals and provide a novel vehicle to target and deliver drugs into the CNS and bypass the BBB through olfactory drug delivery

The AeroCom evaluation and intercomparison of organic aerosol in global models

This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a−1 (range 34–144 Tg a−1) and the median SOA source strength (natural and anthropogenic) is 19 Tg a−1 (range 13–121 Tg a−1). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a−1 (range 16–121 Tg a−1), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a−1; range 13–20 Tg a−1, with one model at 37 Tg a−1). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a−1 (range 28–209 Tg a−1), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at the surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately

PMHT based multiple point targets tracking using multiple models in infrared image sequence

Data association and model selection are important factors for tracking multiple targets in a dense clutter environment. We propose a sequential probabilistic multiple hypotheses tracking (PMHT) based algorithm using interacting multiple modelling (IMM), namely the IMM-PMHT algorithm. Inclusion of IMM enables any arbitrary trajectory to be tracked without any a priori information about the target dynamics. IMM allows us to incorporate different dynamic models for the targets and PMHT helps to avoid the uncertainty about the measurement origin. It operates in an iterative mode using an expectation-maximization (EM) algorithm. The proposed algorithm uses only measurement association as missing data, which simplifies E-step and M-step. It is computationally more efficient, and an important characteristic of our proposed algorithm is that it operates in a single batch model, i.e. sequential, and hence can be used for real time tracking.© IEE

Data association for multiple target tracking : an optimization approach

In multiple target tracking the data association, observation to track fusion, is crucial and plays an important role for success of any tracking algorithm. The observation may be due to true target or may be clutter. In this paper, data association problem is viewed as an optimization problem and two methods, (i) using neural network and (ii) using the evolutionary algorithm, have been proposed and compared

Interacting multiple model based tracking of multiple point targets using expectation maximization algorithm in infrared image sequence

Data association and model selection are important factors for tracking multiple targets in a dense clutter environment without using apriori information about the target dynamic. We propose Interacting Multiple Model-Expectation Maximization (IMM-EM) algorithm, by incorporating different dynamic models for the target and Markov Random Field (MRF) for data association, and hence it is possible to track maneuvering and non-maneuvering targets simultaneously in a single batch mode (sequential). Moreover it can be used for real time application. The proposed method overcomes the problem of data association by incooperating all validated measurements together using EM algorithm and exploiting MRF. It treats the data association problem as incomplete data problem. In the proposed method, all validated measurements are used to update the target state. It uses only measurement association as missing data, which simplifies E-step and M-step of the algorithm. In the proposed approach probability density function (pdf) of an observed data given target state and measurement association, is treated as a mixture pdf. This allows to combine likelihood of a measurement due to each model, and the association process is defined to incorporate IMM and consequently, it is possible to track any arbitrary trajectory. We also consider two different cases for association of measurement to target: Case I:-association of each measurement to target is independent of each other, Case II:- association of a measurement influences an association of its neighbor measurement

Genetic IMM_NN based tracking of multiple point targets in infrared image sequence

Tracking of maneuvering and non-maneuvering targets simultaneously is a challenging task for multiple target tracking (MTT) system. Interacting multiple model (IMM) filtering has been used for tracking multiple targets successfully. IMM needs to evaluate model probability using an observation assigned to the track. We propose a tracking algorithm based on IMM which exploits the genetic algorithm for data association. Genetic algorithm performs nearest neighbor (NN) based data assignment. A mixture probability density function (pdf) for the likelihood of the observation is used for data assignment