Ultrasonic Doppler measurement of renal artery blood flow

An extensive evaluation of the practical and theoretical limitations encountered in the use of totally implantable CW Doppler flowmeters is provided. Theoretical analyses, computer models, in-vitro and in-vivo calibration studies describe the sources and magnitudes of potential errors in the measurement of blood flow through the renal artery, as well as larger vessels in the circulatory system. The evaluation of new flowmeter/transducer systems and their use in physiological investigations is reported

Ultrasonic Doppler measurement of renal artery blood flow

Studies were made of (1) blood flow redistribution during lower body negative pressure (LBNP), (2) the profile of blood flow across the mitral annulus of the heart (both perpendicular and parallel to the commissures), (3) testing and evaluation of a number of pulsed Doppler systems, (4) acute calibration of perivascular Doppler transducers, (5) redesign of the mitral flow transducers to improve reliability and ease of construction, and (6) a frequency offset generator designed for use in distinguishing forward and reverse components of blood flow by producing frequencies above and below the offset frequency. Finally methodology was developed and initial results were obtained from a computer analysis of time-varying Doppler spectra

Optical Scattering Lengths in Large Liquid-Scintillator Neutrino Detectors

For liquid-scintillator neutrino detectors of kiloton scale, the transparency of the organic solvent is of central importance. The present paper reports on laboratory measurements of the optical scattering lengths of the organic solvents PXE, LAB, and Dodecane which are under discussion for next-generation experiments like SNO+, Hanohano, or LENA. Results comprise the wavelength range from 415 to 440nm. The contributions from Rayleigh and Mie scattering as well as from absorption/re-emission processes are discussed. Based on the present results, LAB seems to be the preferred solvent for a large-volume detector.Comment: 9 pages, 3 figures, accepted for publication by Rev. Scient. Instr

Analyses and localization of pectin-like carbohydrates in cell wall and mucilage of the green alga Netrium digitus

The unicellular, simply shaped desmid Netrium digitus inhabiting acid bog ponds grows in two phases. Prior to division, the cell elongates at its central zone, whereas in a second phase, polar tip growth occurs. Electron microscopy demonstrates that Netrium is surrounded by a morphologically homogeneous cell wall, which lacks pores. Immunocytochemical and biochemical analyses give insight into physical wall properties and, thus, into adaptation to the extreme environment. The monoclonal antibodies JIM5 and JIM7 directed against pectic epitopes with different degrees of esterification label preferentially growing wall zones in Netrium. In contrast, 2F4 marks the cell wall only after experimental de-esterification. Electron energy loss spectroscopy reveals Ca-binding capacities of pectins and gives indirect evidence for the degree of their esterification. An antibody raised against Netrium mucilage is not only specific to mucilage but also recognizes wall components in transmission electron microscopy and dot blots. These results indicate a smooth transition between mucilage and the cell wall in Netrium

Forecasting the Pharmacokinetics With Limited Early Frames in Dynamic Brain PET Imaging Using Neural Ordinary Differential Equation

In dynamic brain positron emission tomography (PET) studies, acquiring a time series of images, typically lasting more than an hour, is necessary to derive pharmacokinetic parameters. Analytically, these parameters are estimated by establishing kinetic models such as compartment models that consist of sets of ordinary differential equations (ODE), and by fitting the sparse time-activity curve (TAC) of the tracer. Yet, these models are simplified approximations of highly complex underlying processes, and sufficient samples of TAC are required throughout the entire acquisition, which is not only impractical but also hindered by patient involuntary motion and intrinsic noise. Therefore, recovering samples in missing timeframes is often required, which, in practice, is achieved by interpolation or extrapolation. Here, we introduce a novel deep-learning-based method that utilizes neural ODE (N-ODE) to predict TAC in the extended timeframes by mimicking analytical method in a data-driven manner. By training N-ODE to solve and fit sets of ODE such that the solution replicates the observed TAC, the N-ODE converges to the functional shapes that best describe the underlying pharmacokinetic processes. We customized N-ODE to predict the full-dynamic images (12 frames, 60min), hence pharmacokinetic parameters, given limited early-frame images (7 to 9 frames, 20 to 30min). For proof of concept, the proposed N-ODE was applied to simulated and clinical 18F-PI-2620 brain PET. We demonstrated that the proposed N-ODE delivered promising performance, indicated by bias, variance, and mean absolute error as well as pharmacokinetic parameters such as rate constants, standardized uptake value ratio (SUVr), and binding potential (BPND)

MRI Findings in People with Epilepsy and Nodding Syndrome in an Area Endemic for Onchocerciasis: An Observational Study.

Onchocerciasis has been implicated in the pathogenesis of epilepsy. The debate on a potential causal relationship between Onchocerca volvulus and epilepsy has taken a new direction in the light of the most recent epidemic of nodding syndrome. To document MRI changes in people with different types of epilepsy and investigate whether there is an association with O. volvulus infection. In a prospective study in southern Tanzania, an area endemic for O. volvulus with a high prevalence of epilepsy and nodding syndrome, we performed MRI on 32 people with epilepsy, 12 of which suffered from nodding syndrome. Polymerase chain reaction (PCR) of O. volvulus was performed in skin and CSF. The most frequent abnormalities seen on MRI was atrophy (twelve patients (37.5%)) followed by intraparenchymal pathologies such as changes in the hippocampus (nine patients (28.1%)), gliotic lesions (six patients (18.8%)) and subcortical signal abnormalities (three patients (9.4%)). There was an overall trend towards an association of intraparenchymal cerebral pathologies and infection with O. volvulus based on skin PCR (Fisher's Exact Test p=0.067) which was most pronounced in children and adolescents with nodding syndrome compared to those with other types of epilepsy (Fisher's Exact Test, p=0.083). Contrary to skin PCR results, PCR of CSF was negative in all patients. The observed trend towards an association of intraparenchymal cerebral pathological results on MRI and a positive skin PCR for O. volvulus despite negative PCR of CSF is intriguing and deserves further attention

The LAGUNA design study- towards giant liquid based underground detectors for neutrino physics and astrophysics and proton decay searches

The feasibility of a next generation neutrino observatory in Europe is being considered within the LAGUNA design study. To accommodate giant neutrino detectors and shield them from cosmic rays, a new very large underground infrastructure is required. Seven potential candidate sites in different parts of Europe and at several distances from CERN are being studied: Boulby (UK), Canfranc (Spain), Fr\'ejus (France/Italy), Pyh\"asalmi (Finland), Polkowice-Sieroszowice (Poland), Slanic (Romania) and Umbria (Italy). The design study aims at the comprehensive and coordinated technical assessment of each site, at a coherent cost estimation, and at a prioritization of the sites within the summer 2010.Comment: 5 pages, contribution to the Workshop "European Strategy for Future Neutrino Physics", CERN, Oct. 200

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

Spectral observations at the CILBO observatory: calibration and data sets

Stars and planetary system

Search for Solar Axions Produced in p(d,3He)Ap(d,\rm{^3He})A Reaction with Borexino Detector

A search for 5.5-MeV solar axions produced in the $p+d\rightarrow\rm{^3He}+A (5.5 \rm{MeV})$ reaction was performed using the Borexino detector. The Compton conversion of axions to photons, ${\rm A}+e\rightarrow e+\gamma$; the axio-electric effect, ${\rm A}+e+Z\rightarrow e+Z$; the decay of axions into two photons, ${\rm A}\rightarrow2\gamma$; and inverse Primakoff conversion on nuclei, ${\rm A}+Z\rightarrow\gamma+Z$, are considered. Model independent limits on axion-electron ($g_{Ae}$), axion-photon ($g_{A\gamma}$), and isovector axion-nucleon ($g_{3AN}$) couplings are obtained: $|g_{Ae}\times g_{3AN}| \leq 5.5\times 10^{-13}$ and $|g_{A\gamma}\times g_{3AN}| \leq 4.6\times 10^{-11} \rm{GeV}^{-1}$ at $m_A <$ 1 MeV (90% c.l.). These limits are 2-4 orders of magnitude stronger than those obtained in previous laboratory-based experiments using nuclear reactors and accelerators.Comment: 11 pages, 7 figures, submitted to Phys.Rev.