Reference Cluster Normalization Improves Detection of Frontotemporal Lobar Degeneration by Means of FDG-PET.

Positron emission tomography with [18F] fluorodeoxyglucose (FDG-PET) plays a well-established role in assisting early detection of frontotemporal lobar degeneration (FTLD). Here, we examined the impact of intensity normalization to different reference areas on accuracy of FDG-PET to discriminate between patients with mild FTLD and healthy elderly subjects. FDG-PET was conducted at two centers using different acquisition protocols: 41 FTLD patients and 42 controls were studied at center 1, 11 FTLD patients and 13 controls were studied at center 2. All PET images were intensity normalized to the cerebellum, primary sensorimotor cortex (SMC), cerebral global mean (CGM), and a reference cluster with most preserved FDG uptake in the aforementioned patients group of center 1. Metabolic deficits in the patient group at center 1 appeared 1.5, 3.6, and 4.6 times greater in spatial extent, when tracer uptake was normalized to the reference cluster rather than to the cerebellum, SMC, and CGM, respectively. Logistic regression analyses based on normalized values from FTLD-typical regions showed that at center 1, cerebellar, SMC, CGM, and cluster normalizations differentiated patients from controls with accuracies of 86%, 76%, 75% and 90%, respectively. A similar order of effects was found at center 2. Cluster normalization leads to a significant increase of statistical power in detecting early FTLD-associated metabolic deficits. The established FTLD-specific cluster can be used to improve detection of FTLD on a single case basis at independent centers - a decisive step towards early diagnosis and prediction of FTLD syndromes enabling specific therapies in the future.

Prototip d'instal·lació d'un cluster de càlcul emprant programari lliure i de codi obert

Metodologia d'instal·lació d'un sistema operatiu i aplicacions orientada al seu ús en clusters de càlcul i enfocada principalment a la senzillesa de manteniment i a la compartició d'un màxim de programari entre equips.

MSISpIC: A Probabilistic Scan Matching Algorithm Using a Mechanical Scanned Imaging Sonar

This paper compares two well known scan matching algorithms: the MbICP and the pIC. As a result of the study, it is proposed the MSISpIC, a probabilistic scan matching algorithm for the localization of an Autonomous Underwater Vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), and the robot displacement estimated through dead-reckoning with the help of a Doppler Velocity Log (DVL) and a Motion Reference Unit (MRU). The proposed method is an extension of the pIC algorithm. Its major contribution consists in: 1) using an EKF to estimate the local path traveled by the robot while grabbing the scan as well as its uncertainty and 2) proposing a method to group into a unique scan, with a convenient uncertainty model, all the data grabbed along the path described by the robot. The algorithm has been tested on an AUV guided along a 600m path within a marina environment with satisfactory results

An Efficient Nominal Unification Algorithm

Nominal Unification is an extension of first-order unification where terms can contain binders and unification is performed modulo α equivalence. Here we prove that the existence of nominal unifiers can be decided in quadratic time. First, we linearly-reduce nominal unification problems to a sequence of freshness and equalities between atoms, modulo a permutation, using ideas as Paterson and Wegman for first-order unification. Second, we prove that solvability of these reduced problems may be checked in quadràtic time. Finally, we point out how using ideas of Brown and Tarjan for unbalanced merging, we could solve these reduced problems more efficiently

Validation of a clinical algorithm to identify low-risk patients with pulmonary embolism.

Summary Background: We previously derived a clinical prognostic algorithm to identify patients with pulmonary embolism (PE) who are at low-risk of short-term mortality who could be safely discharged early or treated entirely in an outpatient setting. Objectives: To externally validate the clinical prognostic algorithm in an independent patient sample. Methods: We validated the algorithm in 983 consecutive patients prospectively diagnosed with PE at an emergency department of a university hospital. Patients with none of the algorithm's 10 prognostic variables (age >/= 70 years, cancer, heart failure, chronic lung disease, chronic renal disease, cerebrovascular disease, pulse >/= 110/min., systolic blood pressure < 100 mm Hg, oxygen saturation < 90%, and altered mental status) at baseline were defined as low-risk. We compared 30-day overall mortality among low-risk patients based on the algorithm between the validation and the original derivation sample. We also assessed the rate of PE-related and bleeding-related mortality among low-risk patients. Results: Overall, the algorithm classified 16.3% of patients with PE as low-risk. Mortality at 30 days was 1.9% among low-risk patients and did not differ between the validation and the original derivation sample. Among low-risk patients, only 0.6% died from definite or possible PE, and 0% died from bleeding. Conclusions: This study validates an easy-to-use, clinical prognostic algorithm for PE that accurately identifies patients with PE who are at low-risk of short-term mortality. Low-risk patients based on our algorithm are potential candidates for less costly outpatient treatment.

Profiling of counterfeit medicines by vibrational spectroscopy

Counterfeit pharmaceutical products have become a widespread problem in the last decade. Various analytical techniques have been applied to discriminate between genuine and counterfeit products. Among these, Near-infrared (NIR) and Raman spectroscopy provided promising results.The present study offers a methodology allowing to provide more valuable information fororganisations engaged in the fight against counterfeiting of medicines.A database was established by analyzing counterfeits of a particular pharmaceutical product using Near-infrared (NIR) and Raman spectroscopy. Unsupervised chemometric techniques (i.e. principal component analysis - PCA and hierarchical cluster analysis - HCA) were implemented to identify the classes within the datasets. Gas Chromatography coupled to Mass Spectrometry (GC-MS) and Fourier Transform Infrared Spectroscopy (FT-IR) were used to determine the number of different chemical profiles within the counterfeits. A comparison with the classes established by NIR and Raman spectroscopy allowed to evaluate the discriminating power provided by these techniques. Supervised classifiers (i.e. k-Nearest Neighbors, Partial Least Squares Discriminant Analysis, Probabilistic Neural Networks and Counterpropagation Artificial Neural Networks) were applied on the acquired NIR and Raman spectra and the results were compared to the ones provided by the unsupervised classifiers.The retained strategy for routine applications, founded on the classes identified by NIR and Raman spectroscopy, uses a classification algorithm based on distance measures and Receiver Operating Characteristics (ROC) curves. The model is able to compare the spectrum of a new counterfeit with that of previously analyzed products and to determine if a new specimen belongs to one of the existing classes, consequently allowing to establish a link with other counterfeits of the database.

Bone marrow dosimetry in rats using direct tissue counting after injection of radio-iodinated intact monoclonal antibodies or F(ab')2 fragments.

Normal rats were injected intravenously with 131I- and 125I-labeled intact murine and chimeric mouse-human monoclonal antibodies directed against carcinoembryonic antigen or with the corresponding F(ab')2 fragments. At different times after injection, individual animals were killed and radioactivity of blood and major organs, including bones and bone marrow, was determined. Ratios comparing radioactivity concentration in different tissues with that of bone marrow were calculated and found to remain stable during several effective half-lives of the antibodies. Mean bone marrow radioactivity was 35% (range, 29%-40%) of that of blood and 126% (range, 108%-147%) of that of liver after injection of intact Mabs or F(ab')2 fragments. In nude rats bearing human colon carcinoma xenografts producing carcinoembryonic antigen, relative bone marrow radioactivity was slightly lower than that in normal rats.

A fast Bayesian reconstruction algorithm for emission tomography with entropy prior converging to feasible images

The development and tests of an iterative reconstruction algorithm for emission tomography based on Bayesian statistical concepts are described. The algorithm uses the entropy of the generated image as a prior distribution, can be accelerated by the choice of an exponent, and converges uniformly to feasible images by the choice of one adjustable parameter. A feasible image has been defined as one that is consistent with the initial data (i.e. it is an image that, if truly a source of radiation in a patient, could have generated the initial data by the Poisson process that governs radioactive disintegration). The fundamental ideas of Bayesian reconstruction are discussed, along with the use of an entropy prior with an adjustable contrast parameter, the use of likelihood with data increment parameters as conditional probability, and the development of the new fast maximum a posteriori with entropy (FMAPE) Algorithm by the successive substitution method. It is shown that in the maximum likelihood estimator (MLE) and FMAPE algorithms, the only correct choice of initial image for the iterative procedure in the absence of a priori knowledge about the image configuration is a uniform field.

An analysis of the currently available calibrations inStromgren photometry by using open clusters

In recent years, several authors have revised the calibrations used to compute physical parameters (tex2html_wrap_inline498, tex2html_wrap_inline500, log g, [Fe/H]) from intrinsic colours in the tex2html_wrap_inline504 photometric system. For reddened stars, these intrinsic colours can be computed through the standard relations among colour indices for each of the regions defined by Strömgren (1966) on the HR diagram. We present a discussion of the coherence of these calibrations for main-sequence stars. Stars from open clusters are used to carry out this analysis. Assuming that individual reddening values and distances should be similar for all the members of a given open cluster, systematic differences among the calibrations used in each of the photometric regions might arise when comparing mean reddening values and distances for the members of each region. To classify the stars into Strömgren's regions we extended the algorithm presented by Figueras et al. (1991) to a wider range of spectral types and luminosity classes. The observational ZAMS are compared with the theoretical ZAMS from stellar evolutionary models, in the range tex2html_wrap_inline506 K. The discrepancies are also discussed.

Photometric and Spectroscopic Observations of the Cluster of Galaxies Abell 2390

Spectroscopic and photometric observations in a 6 arcmin x 6 arcmin field centered on the rich cluster of galaxies Abell 2390 are presented. The photometry concerns 700 objects and the spectroscopy 72 objects. The redshift survey shows that the mean redshift of the cluster is 0.232. An original method for automatic determination of the spectral type of galaxies is presented.

Photometric and spectroscopic survey of the cluster of galaxies Abell A2218

We present new photometric and spectroscopic observations of objects in the field of the cluster of galaxies Abell 2218. The photometric survey, centered on the cluster core, extends to a field of about 4 x 4 arcmin. It was performed in 5 bands (B,g,r,i and z filters). This sample, which includes 729 objects, is about three times larger than the survey made by Butcher and collaborators (Butcher et al., 1983, Butcher and Oemler, 1984) in the same central region of the field. Only 228 objects appear in both catalogues since our survey covers a smaller region. The spectral range covered by our filters is wider and the photometry is much deeper, up to magnitude 27 in r. The spectroscopic survey concerns 66 objects, on a field comparable to that of Butcher and collaborators. From our observations we calculate the mean redshift of the cluster, 0.1756, and its velocity dispersion, 1370 km/s. The spectral types are determined for many galaxies in the sample by comparing their spectra with synthetic ones from Rocca-Volmerange and Guiderdoni (1988).

Efforts to standardise Ki-67 counting in breast cancer. A pilot study of the Swiss Working Group of Gyneco- and Breast Pathologists

Goals: Adjuvant chemotherapy decisions in breast cancer are increasing based on the pathologist's assessment of the proliferation fraction in the tumor. Yet, how good and how reproducible are we pathologists at providing reliable Ki-67 readings on breast carcinomas. Exactly how to count and in which areas to count within a tumor remains inadequately standardized. The Swiss Working Group of Gyneco- and Breast Pathologists has tried to appreciate this dilemma and to propose ways to obtain more reproducible results.Methods: In a first phase, 5 pathologists evaluated Ki67 counts in 10 breast cancers by exact counting (500 cells) and by eyeballing. Pathologists were free to select the region in which Ki67 was evaluated. In a second phase 16 pathologists evaluated Ki-67 counts in 3 breast cancers also by exact counting and eyeballing, but in predefined fields of interest. In both phases, Ki67 was assessed in centrally immunostained slides (ZH) and on slides immunostained in the 11 participating laboratories. In a third phase, these same 16 pathologists were once again asked to read the 3 cases from phase 2, plus three new cases, and this time exact guidelines were provided as to what exactly is considered a Ki-67 positive nucleus.Results: Discordance of Ki67 assessment was due to each of the following 4 factors: (i) pathologists' divergent definitions of what counts as a positive nucleus (ii) the mode of assessment (counting vs. eyeballing), (iii) immunostaining technique/protocol/antibody, and (iv) the selection of the area in which to count.Conclusion: Providing guidelines as to where to count (representative field in the tumor periphery and omitting hot spots) and what nuclei to count (even faintly immunostained nuclei count as positive) reduces the discordance rates of Ki67 readings between pathologists. Laboratory technique is only of minor importance (even over a large antibody dilution range), and counting nuclei does not improve accuracy, but rather aggravates deviations from the group mean values.Disclosure of Interest: None Declared

Accurate calculations of intermolecular interaction energies using explicitly correlated coupled cluster wave functions and a dispersion-weighted MP2 method.

Explicitly correlated coupled-cluster calculations of intermolecular interaction energies for the S22 benchmark set of Jurecka, Sponer, Cerny, and Hobza (Chem. Phys. Phys. Chem. 2006, 8, 1985) are presented. Results obtained with the recently proposed CCSD(T)-F12a method and augmented double-zeta basis sets are found to be in very close agreement with basis set extrapolated conventional CCSD(T) results. Furthermore, we propose a dispersion-weighted MP2 (DW-MP2) approximation that combines the good accuracy of MP2 for complexes with predominately electrostatic bonding and SCS-MP2 for dispersion-dominated ones. The MP2-F12 and SCS-MP2-F12 correlation energies are weighted by a switching function that depends on the relative HF and correlation contributions to the interaction energy. For the S22 set, this yields a mean absolute deviation of 0.2 kcal/mol from the CCSD(T)-F12a results. The method, which allows obtaining accurate results at low cost, is also tested for a number of dimers that are not in the training set.