Bayesian Model Selection Applied to the Analysis of Fluorescence Correlation Spectroscopy Data of Fluorescent Proteins in Vitro and in Vivo

Fluorescence correlation spectroscopy (FCS) is a powerful technique to investigate molecular dynamics with single molecule sensitivity. In particular, in the life sciences it has found widespread application using fluorescent proteins as molecularly specific labels. However, FCS data analysis and interpretation using fluorescent proteins remains challenging due to typically low signal-to-noise ratio of FCS data and correlated noise in autocorrelated data sets. As a result, naive fitting procedures that ignore these important issues typically provide similarly good fits for multiple competing models without clear distinction of which model is preferred given the signal-to-noise ratio present in the data. Recently, we introduced a Bayesian model selection procedure to overcome this issue with FCS data analysis. The method accounts for the highly correlated noise that is present in FCS data sets and additionally penalizes model complexity to prevent over interpretation of FCS data. Here, we apply this procedure to evaluate FCS data from fluorescent proteins assayed in vitro and in vivo. Consistent with previous work, we demonstrate that model selection is strongly dependent on the signal-to-noise ratio of the measurement, namely, excitation intensity and measurement time, and is sensitive to saturation artifacts. Under fixed, low intensity excitation conditions, physical transport models can unambiguously be identified. However, at excitation intensities that are considered moderate in many studies, unwanted artifacts are introduced that result in nonphysical models to be preferred. We also determined the appropriate fitting models of a GFP tagged secreted signaling protein, Wnt3, in live zebrafish embryos, which is necessary for the investigation of Wnt3 expression and secretion in development. Bayes model selection therefore provides a robust procedure to determine appropriate transport and photophysical models for fluorescent proteins when appropriate models are provided, to help detect and eliminate experimental artifacts in solution, cells, and in living organisms.National Science Foundation (U.S.). Physics of Living Systems ProgramNational Institute of Mental Health (U.S.) (Award U01MH106011

Interspecies interactions and potential Influenza A virus risk in small swine farms in Peru

<p>Abstract</p> <p>Background</p> <p>The recent avian influenza epidemic in Asia and the H1N1 pandemic demonstrated that influenza A viruses pose a threat to global public health. The animal origins of the viruses confirmed the potential for interspecies transmission. Swine are hypothesized to be prime "mixing vessels" due to the dual receptivity of their trachea to human and avian strains. Additionally, avian and human influenza viruses have previously been isolated in swine. Therefore, understanding interspecies contact on smallholder swine farms and its potential role in the transmission of pathogens such as influenza virus is very important.</p> <p>Methods</p> <p>This qualitative study aimed to determine swine-associated interspecies contacts in two coastal areas of Peru. Direct observations were conducted at both small-scale confined and low-investment swine farms (n = 36) and in open areas where swine freely range during the day (n = 4). Interviews were also conducted with key stakeholders in swine farming.</p> <p>Results</p> <p>In both locations, the intermingling of swine and domestic birds was common. An unexpected contact with avian species was that swine were fed poultry mortality in 6/20 of the farms in Chancay. Human-swine contacts were common, with a higher frequency on the confined farms. Mixed farming of swine with chickens or ducks was observed in 36% of all farms. Human-avian interactions were less frequent overall. Use of adequate biosecurity and hygiene practices by farmers was suboptimal at both locations.</p> <p>Conclusions</p> <p>Close human-animal interaction, frequent interspecies contacts and suboptimal biosecurity and hygiene practices pose significant risks of interspecies influenza virus transmission. Farmers in small-scale swine production systems constitute a high-risk population and need to be recognized as key in preventing interspecies pathogen transfer. A two-pronged prevention approach, which offers educational activities for swine farmers about sound hygiene and biosecurity practices and guidelines and education for poultry farmers about alternative approaches for processing poultry mortality, is recommended. Virological and serological surveillance for influenza viruses will also be critical for these human and animal populations.</p

Resolving fluorescent species by their brightness and diffusion using correlated photon-counting histograms

Fluorescence fluctuation spectroscopy (FFS) refers to techniques that analyze fluctuations in the fluorescence emitted by fluorophores diffusing in a small volume and can be used to distinguish between populations of molecules that exhibit differences in brightness or diffusion. For example, fluorescence correlation spectroscopy (FCS) resolves species through their diffusion by analyzing correlations in the fluorescence over time; photon counting histograms (PCH) and related methods based on moment analysis resolve species through their brightness by analyzing fluctuations in the photon counts. Here we introduce correlated photon counting histograms (cPCH), which uses both types of information to simultaneously resolve fluorescent species by their brightness and diffusion. We define the cPCH distribution by the probability to detect both a particular number of photons at the current time and another number at a later time. FCS and moment analysis are special cases of the moments of the cPCH distribution, and PCH is obtained by summing over the photon counts in either channel. cPCH is inherently a dual channel technique, and the expressions we develop apply to the dual colour case. Using simulations, we demonstrate that two species differing in both their diffusion and brightness can be better resolved with cPCH than with either FCS or PCH. Further, we show that cPCH can be extended both to longer dwell times to improve the signal-to-noise and to the analysis of images. By better exploiting the information available in fluorescence fluctuation spectroscopy, cPCH will be an enabling methodology for quantitative biology

Modelling of the effect of ELMs on fuel retention at the bulk W divertor of JET

Effect of ELMs on fuel retention at the bulk W target of JET ITER-Like Wall was studied with multi-scale calculations. Plasma input parameters were taken from ELMy H-mode plasma experiment. The energetic intra-ELM fuel particles get implanted and create near-surface defects up to depths of few tens of nm, which act as the main fuel trapping sites during ELMs. Clustering of implantation-induced vacancies were found to take place. The incoming flux of inter-ELM plasma particles increases the different filling levels of trapped fuel in defects. The temperature increase of the W target during the pulse increases the fuel detrapping rate. The inter-ELM fuel particle flux refills the partially emptied trapping sites and fills new sites. This leads to a competing effect on the retention and release rates of the implanted particles. At high temperatures the main retention appeared in larger vacancy clusters due to increased clustering rate

Tritium distributions on W-coated divertor tiles used in the third JET ITER-like wall campaign

Tritium (T) distributions on tungsten (W)-coated plasma-facing tiles used in the third ITER-like wall campaign (2015–2016) of the Joint European Torus (JET) were examined by means of an imaging plate technique and β-ray induced x-ray spectrometry, and they were compared with the distributions after the second (2013–2014) campaign. Strong enrichment of T in beryllium (Be) deposition layers was observed after the second campaign. In contrast, T distributions after the third campaign was more uniform though Be deposition layers were visually recognized. The one of the possible explanations is enhanced desorption of T from Be deposition layers due to higher tile temperatures caused by higher energy input in the third campaign

The effect of beryllium oxide on retention in JET ITER-like wall tiles

Preliminary results investigating the microstructure, bonding and effect of beryllium oxide formation on retention in the JET ITER-like wall beryllium tiles, are presented. The tiles have been investigated by several techniques: Scanning Electron Microscopy (SEM) equipped with Energy Dispersive X-ray (EDX), Transmission Electron microscopy (TEM) equipped with EDX and Electron Energy Loss Spectroscopy (EELS), Raman Spectroscopy and Thermal Desorption Spectroscopy (TDS). This paper focuses on results from melted materials of the dump plate tiles in JET. From our results and the literature, it is concluded, beryllium can form micron deep oxide islands contrary to the nanometric oxides predicted under vacuum conditions. The deepest oxides analyzed were up to 2-micron thicknesses. The beryllium Deuteroxide (BeOxDy) bond was found with Raman Spectroscopy. Application of EELS confirmed the oxide presence and stoichiometry. Literature suggests these oxides form at temperatures greater than 700 °C where self-diffusion of beryllium ions through the surface oxide layer can occur. Further oxidation is made possible between oxygen plasma impurities and the beryllium ions now present at the wall surface. Under Ultra High Vacuum (UHV) nanometric Beryllium oxide layers are formed and passivate at room temperature. After continual cyclic heating (to the point of melt formation) in the presence of oxygen impurities from the plasma, oxide growth to the levels seen experimentally (approximately two microns) is proposed. This retention mechanism is not considered to contribute dramatically to overall retention in JET, due to low levels of melt formation. However, this mechanism, thought the result of operation environment and melt formation, could be of wider concern to ITER, dependent on wall temperatures

Modelling of tungsten erosion and deposition in the divertor of JET-ILW in comparison to experimental findings

The erosion, transport and deposition of tungsten in the outer divertor of JET-ILW has been studied for an HMode discharge with low frequency ELMs. For this specific case with an inter-ELM electron temperature at the strike point of about 20 eV, tungsten sputtering between ELMs is almost exclusively due to beryllium impurity and self-sputtering. However, during ELMs tungsten sputtering due to deuterium becomes important and even dominates. The amount of simulated local deposition of tungsten relative to the amount of sputtered tungsten in between ELMs is very high and reaches values of 99% for an electron density of 5E13 cm$^{-3}$ at the strike point and electron temperatures between 10 and 30 eV. Smaller deposition values are simulated with reduced electron density. The direction of the B-field significantly influences the local deposition and leads to a reduction if the E×B drift directs towards the scrape-off-layer. Also, the thermal force can reduce the tungsten deposition, however, an ion temperature gradient of about 0.1 eV/mm or larger is needed for a significant effect. The tungsten deposition simulated during ELMs reaches values of about 98% assuming ELM parameters according to free-streaming model. The measured WI emission profiles in between and within ELMs have been reproduced by the simulation. The contribution to the overall net tungsten erosion during ELMs is about 5 times larger than the one in between ELMs for the studied case. However, this is due to the rather low electron temperature in between ELMs, which leads to deuterium impact energies below the sputtering threshold for tungsten

Impact of fast ions on density peaking in JET : fluid and gyrokinetic modeling

The effect of fast ions on turbulent particle transport, driven by ion temperature gradient (ITG)/trapped electron mode turbulence, is studied. Two neutral beam injection (NBI) heated JET discharges in different regimes are analyzed at the radial position rho(t) = 0.6, one of them an L-mode and the other one an H-mode discharge. Results obtained from the computationally efficient fluid model EDWM and the gyro-fluid model TGLF are compared to linear and nonlinear gyrokinetic GENE simulations as well as the experimentally obtained density peaking. In these models, the fast ions are treated as a dynamic species with a Maxwellian background distribution. The dependence of the zero particle flux density gradient (peaking factor) on fast ion density, temperature and corresponding gradients, is investigated. The simulations show that the inclusion of a fast ion species has a stabilizing influence on the ITG mode and reduces the peaking of the main ion and electron density profiles in the absence of sources. The models mostly reproduce the experimentally obtained density peaking for the L-mode discharge whereas the H-mode density peaking is significantly underpredicted, indicating the importance of the NBI particle source for the H-mode density profile