Low Number Of Counts Research Articles

HYPR4D kernel method on TOF PET data with validations including image-derived input function

BackgroundPositron emission tomography (PET) images are typically noisy especially in dynamic imaging where the PET data are divided into a number of short temporal frames often with a low number of counts. As a result, image features such as contrast and time–activity curves are highly variable. Noise reduction in PET is thus essential. Typical noise reduction methods tend to not preserve image features/patterns (e.g. contrast and size dependent) accurately. In this work, we report the first application of our HYPR4D kernel method on time-of-flight (TOF) PET data (i.e. PSF-HYPR4D-K-TOFOSEM). The proposed HYPR4D kernel method makes use of the mean 4D high frequency features and inconsistent noise patterns over OSEM subsets as well as the low noise property of the early reconstruction updates to achieve prior-free de-noising. The method was implemented and tested on the GE SIGNA PET/MR and was compared to the TOF reconstructions with PSF resolution modeling available on the system, namely PSF-TOFOSEM with and without standard post filter and PSF-TOFBSREM (TOF Q.Clear) with various beta values (regularization strengths).ResultsResults from experimental contrast phantom and human subject data with various PET tracers showed that the proposed method provides more robust and accurate image features compared to other regularization methods. The preservation of contrast for the PSF-HYPR4D-K-TOFOSEM was observed to be better and less dependent on the contrast and size of the target structures as compared to TOF Q.Clear and PSF-TOFOSEM with filter. At the same contrast level, PSF-HYPR4D-K-TOFOSEM achieved better 4D noise suppression than other methods (e.g. >2 times lower noise than TOF Q.Clear at the highest contrast). We also present a novel voxel search method to obtain an image-derived input function (IDIF) and demonstrate that the obtained IDIF is the most quantitative w.r.t. the measured blood samples when the acquired data are reconstructed with PSF-HYPR4D-K-TOFOSEM.ConclusionsThe overall results support superior performance of the PSF-HYPR4D-K-TOFOSEM for TOF PET data and demonstrate that the proposed method is likely suitable for all imaging tasks including the generation of IDIF without requiring any prior information as well as further improving the effective sensitivity of the imaging system.

X-ray properties of high-redshift Radio Loud and Radio Quiet Quasars observed by Chandra

We performed a study of high redshift (z>2) quasars, looking for the main differences between Radio Loud Quasars (RLQ) and Radio Quiet Quasars (RQQ) in the X-ray band. Our sample of 472 RQQ and 81 RLQ was selected by cross-matching the SDSS DR7 quasars catalog with the Chandra Source Catalog. We computed the X-ray luminosity for the two samples and confirmed the X-ray luminosity excess of RLQ over RQQ. We fit the X-ray spectra assuming the absorbed power law model and obtained the photon index (Γ) values for all the sources in the sample. We excluded quasars with a low number of counts (<10) and large uncertainty on the best-fit photon index (Γerr>1), and obtained the mean values of ΓRLQ=1.70−0.33+0.36 and ΓRQQ=2.19−0.44+0.46 for the RLQ and RQQ samples, respectively, showing that the RLQ have flatter (harder) X-ray spectra than RQQ. The Kuiper-two test confirms this result with the significant difference between the RLQ and RQQ photon index distributions (Dk=0.37 and P-value =10−6). We also evaluated the hardness ratio distributions and confirmed that the spectra of RLQ are flatter than the spectra of the RQQ. The RLQ's hard-to-soft ratio distribution is skewed towards the hard X-ray band, while the RQQ is towards the soft X-ray band. The hard-to-medium and medium-to-soft ratios show no difference.

Burst search method based on likelihood ratio in Poisson statistics

ABSTRACTSearching for X-ray and gamma-ray bursts, including Gamma-ray bursts (GRBs), Soft Gamma-ray Repeaters (SGRs), and high energy transients associated with Gravitational wave (GW) events or Fast radio bursts (FRBs), is of great importance in the multimessenger and multiwavelength era. Although a coherent search based on the likelihood ratio and Gaussian statistics has been established and utilized in many studies, this Gaussian-based method could be problematic for weak and short bursts which usually have very few counts. To deal with all bursts including weak ones, here we propose the coherent search in Poisson statistics. We studied the difference between Poisson-based and Gaussian-based search methods by Monte Carlo simulations, and find that the Poisson-based search method has advantages compared to the Gaussian case, especially for weak bursts. Our results show that, for very weak bursts with very low number of counts, the Poisson-based search can provide higher significance than the Gaussian-based search, and its likelihood ratio (for background fluctuation) still generally follows the χ2 distribution, making the significance estimation of searched bursts very convenient. Thus, we suggest that the coherent search based on Poisson-likelihood ratio is more appropriate in the search for generic transients including very weak ones.

Smart Data Analytic-Based Transform of Low-Count Gamma-Ray Spectra for Enhancing Isotope Detection by Using a Self-Learning Window of Relevance Vector Regression

Identification of isotope signatures in low-count gamma-ray spectra measured with a portable NaI detector is of great importance with concern to nuclear security and non-proliferation. Specifically, in hidden radioactive source search scenarios, where a mobile detector acquires consecutive measurements in a very small interval of time (for instance every second), the measured spectra may exhibit a low number of counts and high fluctuation. These two factors challenge the radioisotope identifier algorithm both in detection accuracy and processing time by providing a high number of spectral peaks that need to be checked against known signatures. In this article, a new smart data analytics-driven transform for enhancing isotope detection is presented. In particular, a machine learning (ML) tool, i.e., the relevance vector regression (RVR), is utilized to transform the obtained signal into a form where the isotopic peaks are resolved with higher efficiency while several spectral peaks resulting from fluctuation are removed. Initially, the transform uses the data within a step-size window as its training set—self-learning (i.e., no external datasets are used) window of RVR—and subsequently replaces the window values with the RVR outputs. The presented data analytics-based transform is tested on a set of real-world gamma-ray spectra measured with a low-resolution NaI detector. Results exhibit that the presented transform improves detection certainty as obtained by two radioisotope identifier algorithms, and concurrently reduces the number of random peaks by providing a smoothed signal with fewer spectral peaks to be checked.

A Monte Carlo method for calculation of the characteristic limits decision threshold and detection limit in low-level radioactivity measurements

In this study, calculation of decision threshold and detection limit expressed in counts for low-level radioactivity measurements were evaluated and compared to a Monte Carlo method for the case of paired Poisson-distributed observations, i.e. for discrete variables. The calculated characteristic limits obtained from Monte Carlo calculations were compared with analytical expressions given in literature. The results in this study show that the equations given by Currie are in good agreement with the results from the Monte Carlo calculations simulating nuclear counting applications with a low number of observed counts. An exception is observed for a background corresponding to zero counts. This study also shows that at a low number of counts, the specific boundary conditions of the interval that represents counts corresponding to the presence of the analyte (>or ≥), have an impact on the false positives and negatives rates as defined by the parameters α and β.

First spectroscopic study of 51Ar by the (p,2p) reaction

The nuclear structure of 51Ar, an uncharted territory so far, was studied by the (p,2p) reaction using γ-ray spectroscopy for the bound states and the invariant mass method for the unbound states. Two peaks were detected in the γ-ray spectrum and six peaks were observed in the 50Ar+n relative energy spectrum. Comparing the results to our shell-model calculations, two bound and six unbound states were established. Three of the unbound states could only be placed tentatively due to the low number of counts in the relative energy spectrum of events associated with the decay through the first excited state of 50Ar. The low cross sections populating the two bound states of 51Ar could be interpreted as a clear signature for the presence of significant subshell closures at neutron numbers 32 and 34 in argon isotopes. It was also revealed that due to the two valence holes, unbound collective states coexist with individual-particle states in 51Ar.

The EXOD search for faint transients in XMM-Newton observations: Method and discovery of four extragalactic Type I X-ray bursters

Context. The observations carried out with XMM-Newton have produced a very extensive X-ray source catalogue in which the standard pipeline determines the variability of sufficiently bright sources through χ2 and fractional variability tests. Faint sources, however, are not automatically checked for variability, and this means that faint, short timescale transients are overlooked. From dedicated X-ray searches, as well as optical and radio archive searches, we know that some such dim sources can still be identified with high confidence. Aims. Our goal is to find new faint, fast transients in XMM-Newton EPIC-pn observations. To that end we created the EPIC-pn XMM-Newton outburst detector (EXOD) algorithm, which we run on the EPIC-pn full-frame data available in the 3XMM-DR8 catalogue. Methods. In EXOD, we computed the variability of the whole field of view by first binning in time the counts detected in each pixel of the detector. We next computed the difference between the median and maximal number of counts in each time bin and pixel to detect variability. We applied EXOD to 5751 observations in the full frame mode and compared the variability of the detected sources to the standard χ2 and Kolmogorov–Smirnov (KS) variability tests. Results. The algorithm is able to detect periodic and aperiodic variability, with both short and long flares. Of the sources detected by EXOD, 60−95% are also shown to be variable by the standard χ2 and KS tests. EXOD computes the variability over the entire field of view faster than the light curve generation takes for all the individual sources. We detect a total of 2961 X-ray variable sources. After removing the spurious detections, we obtain a net number of 2536 variable sources. Of these we investigate the nature of 35 sources with no previously confirmed classification. Amongst the new sources, we find stellar flares and AGNs, in addition to four extragalactic type I X-ray bursters that double the known neutron-star population in M 31. Conclusions. This algorithm is a powerful tool for the prompt detection of interesting variable sources in XMM-Newton observations. EXOD also detects fast transients that other variability tests would classify as non-variable due to their short duration and low number of counts. This is of increasing importance for the multi-messenger detection of transient sources. Finally, EXOD allows us to identify the nature of compact objects through their variability and to detect rare compact objects. We demonstrate this through the discovery of four extragalactic neutron-star low-mass X-ray binaries, doubling the number of known neutron stars in M 31.

Investigation on the health status of workers exposed to benzene in one province

Objective: To explore the health status of occupational benzene exposure workers, and to provide a scientific basis for the development of reasonable health monitoring and effective protective measures. Methods: In March 2019, the occupational health surveillance data were collected including blood pressure, electrocardiogram, blood routine, urine routine, liver function, etc of 7810 benzene contact workers in 150 enterprises in Jiangxi Province in 2017, to analyze and assess their health status. Results: Among the 7810 benzene workers, there were 5451 males and 2359 females; the average age was (40.5±9.9) years; and the median benzene working age was 3.5 years. The detection rate of hypertension was 17.0% (734/4317) , the abnormal rate of urine routine was 15.7% (1227/7810) , the abnormal rate of liver function was 8.6% (356/4147) , and the abnormal rate of electrocardiogram was 12.3%(963/7810). The detection rates of low count number of leukocytes, platelets, neutrophils and occupational contraindications were 4.6%(360/7810) , 1.4%(108/7810) , 4.2%(330/7810) and 1.4%(110/7810) , respectively. The detection rates of low count number of leukocytes, platelets and neutrophils in female were all higher than those in male (P<0.05). The detection rates of low count number of platelets, neutropenia and occupational contraindications increased with age and working age (P<0.05 ). There were significant differences in the detection rates of low count number of leukocytes, platelets, neutrophils and occupational contraindications among benzene workers in different economic types (P<0.05) , and the highest among foreign companies, followed by private enterprise. There were statistically significant differences in the detection rates of low count number of platelets, neutrophils and occupational contraindications in benzene workers of different enterprise sizes (P<0.05) , and the highest was found in micro enterprises, followed by small enterprises. Conclusion: In 2017, the occupational health status of workers exposed to benzene in Jiangxi province is not optimistic. It is necessary to strengthen the occupational health supervision of small and micro-sized enterprises, foreign enterprises and private enterprises, take the initiative to improve health surveillance, and effectively protect the physical and mental health of workers.

Evaluation of a Bayesian penalized likelihood reconstruction algorithm for low-count clinical 18F-FDG PET/CT

BackgroundRecently, a Bayesian penalized likelihood (BPL) reconstruction algorithm was introduced for a commercial PET/CT with the potential to improve image quality. We compared the performance of this BPL algorithm with conventional reconstruction algorithms under realistic clinical conditions such as daily practiced at many European sites, i.e. low 18F-FDG dose and short acquisition times.ResultsTo study the performance of the BPL algorithm, regular clinical 18F-FDG whole body PET scans were made. In addition, two types of phantoms were scanned with 4-37 mm sized spheres filled with 18F-FDG at sphere-to-background ratios of 10-to-1, 4-to-1, and 2-to-1. Images were reconstructed using standard ordered-subset expectation maximization (OSEM), OSEM with point spread function (PSF), and the BPL algorithm using β-values of 450, 550 and 700. To quantify the image quality, the lesion detectability, activity recovery, and the coefficient of variation (COV) within a single bed position (BP) were determined. We found that when applying the BPL algorithm both smaller lesions in clinical studies as well as spheres in phantom studies can be detected more easily due to a higher SUV recovery, especially for higher contrast ratios. Under standard clinical scanning conditions, i.e. low number of counts, the COV is higher for the BPL (β=450) than the OSEM+PSF algorithm. Increase of the β-value to 550 or 700 results in a COV comparable to OSEM+PSF, however, at the cost of contrast, though still better than OSEM+PSF. At the edges of the axial field of view (FOV) where BPs overlap, COV can increase to levels at which bands become visible in clinical images, related to the lower local axial sensitivity of the PET/CT, which is due to the limited bed overlap of 23% such as advised by the manufacturer.ConclusionsThe BPL algorithm performs better than the standard OSEM+PSF algorithm on small lesion detectability, SUV recovery, and noise suppression. Increase of the percentage of bed overlap, time per BP, administered activity, or the β-value, all have a direct positive impact on image quality, though the latter with some loss of small lesion detectability. Thus, BPL algorithms are very interesting for improving image quality, especially in small lesion detectability.

NEMA NU 2\u20132007 performance characteristics of GE Signa integrated PET/MR for different PET isotopes

BackgroundFully integrated PET/MR systems are being used frequently in clinical research and routine. National Electrical Manufacturers Association (NEMA) characterization of these systems is generally done with 18F which is clinically the most relevant PET isotope. However, other PET isotopes, such as 68Ga and 90Y, are gaining clinical importance as they are of specific interest for oncological applications and for follow-up of 90Y-based radionuclide therapy. These isotopes have a complex decay scheme with a variety of prompt gammas in coincidence. 68Ga and 90Y have higher positron energy and, because of the larger positron range, there may be interference with the magnetic field of the MR compared to 18F. Therefore, it is relevant to determine the performance of PET/MR for these clinically relevant and commercially available isotopes.MethodsNEMA NU 2–2007 performance measurements were performed for characterizing the spatial resolution, sensitivity, image quality, and the accuracy of attenuation and scatter corrections for 18F, 68Ga, and 90Y. Scatter fraction and noise equivalent count rate (NECR) tests were performed using 18F and 68Ga. All phantom data were acquired on the GE Signa integrated PET/MR system, installed in UZ Leuven, Belgium.Results18F, 68Ga, and 90Y NEMA performance tests resulted in substantially different system characteristics. In comparison with 18F, the spatial resolution is about 1 mm larger in the axial direction for 68Ga and no significative effect was found for 90Y. The impact of this lower resolution is also visible in the recovery coefficients of the smallest spheres of 68Ga in image quality measurements, where clearly lower values are obtained. For 90Y, the low number of counts leads to a large variability in the image quality measurements. The primary factor for the sensitivity change is the scale factor related to the positron emission fraction. There is also an impact on the peak NECR, which is lower for 68Ga than for 18F and appears at higher activities.ConclusionsThe system performance of GE Signa integrated PET/MR was substantially different, in terms of NEMA spatial resolution, image quality, and NECR for 68Ga and 90Y compared to 18F. But these differences are compensated by the PET/MR scanner technologies and reconstructions methods.

X-ray observations of dust obscured galaxies in theChandradeep field south

We present the properties of X-ray detected dust obscured galaxies (DOGs) in the Chandra Deep Field South. In recent years, it has been proposed that a significant percentage of the elusive Compton-thick (CT) active galactic nuclei (AGN) could be hidden among DOGs. In a previous work, we presented the properties of X-ray detected DOGs by making use of the deepest X-ray observations available at that time, the 2Ms observations of the Chandra deep fields. In that work, we only found a moderate percentage ($<$ 50%) of CT AGN among the DOGs sample, but we were limited by poor photon statistics. In this paper, we use not only a deeper 6 Ms Chandra survey of the Chandra Deep Field South (CDF-S), but combine these data with the 3 Ms XMM-Newton survey of the CDF-S. We also take advantage of the great coverage of the CDF-S region from the UV to the far-IR to fit the spectral energy distributions (SEDs) of our sources. Out of the 14 AGN composing our sample, 9 are highly absorbed (but only 3 could be CT AGN), whereas 2 look unabsorbed, and the other 3 are only moderately absorbed. In only one of the CT AGN, we detect a strong Fe K$\alpha$ emission line; the source is already classified as a CT AGN with Chandra data in a previous work. For the other two CT candidates, the non-detection of the line could be because of the low number of counts in their X-ray spectra, but their location in the L$_{\rm 2-10\,keV}$/L$_{12\mu m}$ plot supports their CT classification. Although a higher number of CT sources could be hidden among the X-ray undetected DOGs, our results indicate that DOGs could be as well composed of only a fraction of CT AGN plus a number of moderate to highly absorbed AGN, as previously suggested. From our study of the X-ray undetected DOGs in the CDF-S, we estimate a percentage between 13 and 44% of CT AGN among the whole population of DOGs.

Age-driven modulation of tRNA-derived fragments in Drosophila and their potential targets.

BackgroundDevelopment of sequencing technologies and supporting computation enable discovery of small RNA molecules that previously escaped detection or were ignored due to low count numbers. While the focus in the analysis of small RNA libraries has been primarily on microRNAs (miRNAs), recent studies have reported findings of fragments of transfer RNAs (tRFs) across a range of organisms.ResultsHere we describe Drosophila melanogaster tRFs, which appear to have a number of structural and functional features similar to those of miRNAs but are less abundant. As is the case with miRNAs, (i) tRFs seem to have distinct isoforms preferentially originating from 5’ or 3’ end of a precursor molecule (in this case, tRNA), (ii) ends of tRFs appear to contain short “seed” sequences matching conserved regions across 12 Drosophila genomes, preferentially in 3’ UTRs but also in introns and exons; (iii) tRFs display specific isoform loading into Ago1 and Ago2 and thus likely function in RISC complexes; (iii) levels of loading in Ago1 and Ago2 differ considerably; and (iv) both tRF expression and loading appear to be age-dependent, indicating potential regulatory changes from young to adult organisms.ConclusionsWe found that Drosophila tRF reads mapped to both nuclear and mitochondrial tRNA genes for all 20 amino acids, while previous studies have usually reported fragments from only a few tRNAs. These tRFs show a number of similarities with miRNAs, including seed sequences. Based on complementarity with conserved Drosophila regions we identified such seed sequences and their possible targets with matches in the 3’UTR regions. Strikingly, the potential target genes of the most abundant tRFs show significant Gene Ontology enrichment in development and neuronal function. The latter suggests that involvement of tRFs in the RNA interfering pathway may play a role in brain activity or brain changes with age.ReviewersThis article was reviewed by Eugene Koonin, Neil Smalheiser and Alexander Kel.Electronic supplementary materialThe online version of this article (doi:10.1186/s13062-015-0081-6) contains supplementary material, which is available to authorized users.

Modeling time-series count data: The unique challenges facing political communication studies

This paper demonstrates the importance of proper model specification when analyzing time-series count data in political communication studies. It is common for scholars of media and politics to investigate counts of coverage of an issue as it evolves over time. Many scholars rightly consider the issues of time dependence and dynamic causality to be the most important when crafting a model. However, to ignore the count features of the outcome variable overlooks an important feature of the data. This is particularly the case when modeling data with a low number of counts. In this paper, we argue that the Poisson autoregressive model (Brandt and Williams, 2001) accurately meets the needs of many media studies. We replicate the analyses of Flemming et al. (1997), Peake and Eshbaugh-Soha (2008), and Ura (2009) and demonstrate that models missing some of the assumptions of the Poisson autoregressive model often yield invalid inferences. We also demonstrate that the effect of any of these models can be illustrated dynamically with estimates of uncertainty through a simulation procedure. The paper concludes with implications of these findings for the practical researcher.

Transport and energy selection of laser generated protons for postacceleration with a compact linac

Laser accelerated proton beams have a considerable potential for various applications including oncological therapy. However, the most consolidated target normal sheath acceleration regime based on irradiation of solid targets provides an exponential energy spectrum with a significant divergence. The low count number at the cutoff energy seriously limits at present its possible use. One realistic scenario for the near future is offered by hybrid schemes. The use of transport lines for collimation and energy selection has been considered. We present here a scheme based on a high field pulsed solenoid and collimators which allows one to select a beam suitable for injection at 30 MeV into a compact linac in order to double its energy while preserving a significant intensity. The results are based on a fully 3D simulation starting from laser acceleration.

Grain Size Measurements Using Circular or Rectangular Test Grids

Abstract Experiments were conducted to determine the influence of the number of grains counted using the Jeffries planimetric procedure of ASTM E 112 with a single test circle compared to the number counted using rectangles as suggested by Saltykov. Both planimetric methods produced similar estimates of the ASTM grain size number when the counts per field placement were high. The Saltykov rectangle method is a viable test method and produced good data down to low count numbers. Bias was not observed at low counts, only data scatter. The intercept count method, using only a single test circle per field, yielded slightly higher estimates of the ASTM grain size number, but the difference was relatively insignificant.

Dead‐time correction for time‐of‐flight secondary‐ion mass spectral images: a critical issue in multivariate image analysis

Dead-time effects result in a non-linear detector response in the common time-of-flight secondary-ion mass spectrometry instruments. This can result in image artifacts that can often be misinterpreted. Although the Poisson correction procedure has been shown to effectively eliminate this non-linearity in spectra, applying the correction to images presents difficulties because the low number of counts per pixel can create large statistical errors. The efficacy of three approaches to dead-time correction in images has been explored. These approaches include: pixel binning, image segmentation and a binomial statistical correction. When few pixels are fully saturated, all three approaches work satisfactorily. When a large number of pixels are fully saturated, the statistical approach fails to remove the dead-time artifacts revealed by multivariate analysis. Pixel binning is accurate at higher levels of saturation so long as the bin size is much smaller than the feature size. The segmentation approach works well independent of feature size or the number of fully saturated pixels but requires an accurate segmentation algorithm. It is recommended that images be collected under conditions that minimize the number of fully saturated pixels. When this is impractical and small features are present in the image, segmentation can provide an accurate way to correct for the detector saturation effect.

CHANDRA DETECTION OF SN 2010da FOUR MONTHS AFTER OUTBURST: EVIDENCE FOR A HIGH-MASS X-RAY BINARY IN NGC 300

We present the results of a 63 ks {\it Chandra} observation of the "supernova impostor" SN 2010da four months after it was first observed on 25 May 2010. We detect an X-ray source at $\sim7\sigma$ confidence coincident with the optical location of the SN 2010da outburst. Our imaging analysis has revealed a hard central point source, surrounded by soft diffuse emission extending as far as $\sim$8\asn north of the central source. The diffuse emission has a hardness ratio, 0.35-2 keV luminosity ($\sim6\times10^{35}$ erg s$^{-1}$), and size ($\sim20$ pc) consistent with that of a supernova remnant, although the low number of counts prohibits detailed spectral modeling. Our best-fit spectral model for the hard central source is a black body ($kT = 1.79^{+0.66}_{-0.43}$ keV) with no evidence for intrinsic absorption beyond the Galactic column. We estimate the 0.3-10 keV luminosity to be 1.7$^{+0.2}_{-0.5}\times10^{37}$ erg s$^{-1}$, a factor of $\sim$25 decrease since the initial outburst four months previously. The high X-ray luminosity and slow fading rate is not consistent with this object being a single massive star undergoing an outburst; instead, we favor the scenario where the massive star powering the SN 2010da optical transient is part of a wind-fed supergiant X-ray binary system with a compact companion powering the observed X-ray emission.

Advanced alpha spectrum analysis based on the fitting and covariance analysis of dependent variables

Abstract The correct handling of statistical uncertainties is crucial especially when unfolding alpha spectra that contain a low number of counts or overlapping peaks from different nuclides. For this purpose, we have developed a new spectrum analysis software package called ADAM, which performs a full covariance calculus for alpha-particle emitting radionuclides. By analyzing a large number of simulated and measured spectra, the program was proved to give unbiased peak areas and statistically correct uncertainty limits. This applies regardless of the peak areas and the number of unknown parameters during the fitting. In addition, ADAM performs reliable deconvolution for multiplets, which opens the way for the determination of isotope ratios, such as 239 Pu/ 240 Pu.

Architecture of a nascent viral fusion pore

Enveloped viruses use specialized protein machinery to fuse the viral membrane with that of the host cell during cell invasion. In influenza virus, hundreds of copies of the haemagglutinin (HA) fusion glycoprotein project from the virus surface. Despite intensive study of HA and its fusion activity, the protein's modus operandi in manipulating viral and target membranes to catalyse their fusion is poorly understood. Here, the three-dimensional architecture of influenza virus–liposome complexes at pH 5.5 was investigated by electron cryo-tomography. Tomographic reconstructions show that early stages of membrane remodeling take place in a target membrane-centric manner, progressing from punctate dimples, to the formation of a pinched liposomal funnel that may impinge on the apparently unperturbed viral envelope. The results suggest that the M1 matrix layer serves as an endoskeleton for the virus and a foundation for HA during membrane fusion. Fluorescence spectroscopy monitoring fusion between liposomes and virions shows that leakage of liposome contents takes place more rapidly than lipid mixing at pH 5.5. The relation of ‘leaky' fusion to the observed prefusion structures is discussed.

A Scatter Calibration Technique for Dynamic Brain Imaging in High Resolution PET

We describe a scatter calibration technique which improves the quantitative accuracy of the positron emission tomography data in specific scanning conditions: i.e., scans with high random fraction (RF) and/or low number of counts. Such a situation is often encountered in dynamic imaging on scanners with a large number of lines-of-response (LOR) such as the high resolution research tomograph (HRRT). In this paper, we first describe how high RFs and low number of counts affect the scatter scaling process. We then demonstrate experimentally, with phantom studies, the bias in the scatter estimate introduced by the commonly used tail-fitting technique employed in the single scatter simulation (SSS) method. A significant bias in scatter fraction (SF) was found for frames which contain a RF higher than 50% and/or with a number of counts less than 20 M. Finally, we present a new scatter scaling technique which compensates this bias. The scatter calibration technique is based on using the scatter estimate obtained from a reference frame, in which the bias due to high RFs and low number of counts is minimized, to calibrate the scatter in each dynamic frame. The calibration also separately accounts for the change in SF due to the pulse pile-up effect. A much more consistent and accurate SF value was assigned to each segment of the scatter sinogram thus leading to a more quantitative reconstructed image with a better axial uniformity after the scatter calibration. The new calibration technique was tested with phantom, monkey, and human data and was found to significantly improve the quantitative aspect of the early frames: such improvement is expected to positively affect the feasibility of rather novel image analysis methods, such as determination of image derived input function.