Consequences of the multipatient use of a single-patient capillary blood sampling device (CBSD)

Introduction/objectives: Multipatient use of a single-patient CBSD occurred inan outpatient clinic during 4 to 16 months before itsnotification. We looked for transmission of blood-bornepathogens among exposed patients.Methods: Exposed patients underwent serology testing for HBV,HCV and HIV. Patients with isolated anti-HBc receivedone dose of hepatitis B vaccine to look for a memoryimmune response. Possible transmissions were investigatedby mapping visits and sequencing of the viral genomeif needed.Results: Of 280 exposed patients, 9 had died without suspicionof blood-borne infection, 3 could not be tested, and 5declined investigations. Among the 263 (93%) testedpatients, 218 (83%) had negative results. We confirmeda known history of HCV infection in 6 patients (1 coinfectedby HIV), and also identified resolved HBVinfection in 37 patients, of whom 18 were alreadyknown. 2 patients were found to have a previouslyunknown HCV infection. According to the time elapsedfrom the closest previous visit of a HCV-infected potentialsource patient, we could rule out nosocomial transmissionin one case (14 weeks) but not in the other (1day). In the latter, however, transmission was deemedvery unlikely by 2 reference centers based on thesequences of the E1 and HVR1 regions of the virus.Conclusion: We did not identify any transmission of blood-bornepathogens in 263 patients exposed to a single-patientCBSD, despite the presence of potential source cases.Change of needle and disinfection of the device betweenpatients may have contributed to this outcome.Although we cannot exclude transmission of HBV, previousacquisition in endemic countries is a more likelyexplanation in this multi-national population.

Evaluating sampling strategies and logistic regression methods for modelling complex land cover changes

The role of land cover change as a significant component of global change has become increasingly recognized in recent decades. Large databases measuring land cover change, and the data which can potentially be used to explain the observed changes, are also becoming more commonly available. When developing statistical models to investigate observed changes, it is important to be aware that the chosen sampling strategy and modelling techniques can influence results. We present a comparison of three sampling strategies and two forms of grouped logistic regression models (multinomial and ordinal) in the investigation of patterns of successional change after agricultural land abandonment in Switzerland. Results indicated that both ordinal and nominal transitional change occurs in the landscape and that the use of different sampling regimes and modelling techniques as investigative tools yield different results. Synthesis and applications. Our multimodel inference identified successfully a set of consistently selected indicators of land cover change, which can be used to predict further change, including annual average temperature, the number of already overgrown neighbouring areas of land and distance to historically destructive avalanche sites. This allows for more reliable decision making and planning with respect to landscape management. Although both model approaches gave similar results, ordinal regression yielded more parsimonious models that identified the important predictors of land cover change more efficiently. Thus, this approach is favourable where land cover change pattern can be interpreted as an ordinal process. Otherwise, multinomial logistic regression is a viable alternative.

Problèmes d'échantillonnage lors d'une enquête sur la plombémie d'enfants citadin [Sampling problems in a survey of blood lead levels in city children].

A study on lead pollution was carried out on a sample of ca. 300 city children. This paper presents the errors producing bias in the sample. It is emphasized that, in Switzerland, the difference between the Swiss and the migrant population (the latter being mainly Italian and Spanish) must be taken into account.

Decision-theoretic analysis of forensic sampling criteria using Bayesian decision networks

Sampling issues represent a topic of ongoing interest to the forensic science community essentially because of their crucial role in laboratory planning and working protocols. For this purpose, forensic literature described thorough (Bayesian) probabilistic sampling approaches. These are now widely implemented in practice. They allow, for instance, to obtain probability statements that parameters of interest (e.g., the proportion of a seizure of items that present particular features, such as an illegal substance) satisfy particular criteria (e.g., a threshold or an otherwise limiting value). Currently, there are many approaches that allow one to derive probability statements relating to a population proportion, but questions on how a forensic decision maker - typically a client of a forensic examination or a scientist acting on behalf of a client - ought actually to decide about a proportion or a sample size, remained largely unexplored to date. The research presented here intends to address methodology from decision theory that may help to cope usefully with the wide range of sampling issues typically encountered in forensic science applications. The procedures explored in this paper enable scientists to address a variety of concepts such as the (net) value of sample information, the (expected) value of sample information or the (expected) decision loss. All of these aspects directly relate to questions that are regularly encountered in casework. Besides probability theory and Bayesian inference, the proposed approach requires some additional elements from decision theory that may increase the efforts needed for practical implementation. In view of this challenge, the present paper will emphasise the merits of graphical modelling concepts, such as decision trees and Bayesian decision networks. These can support forensic scientists in applying the methodology in practice. How this may be achieved is illustrated with several examples. The graphical devices invoked here also serve the purpose of supporting the discussion of the similarities, differences and complementary aspects of existing Bayesian probabilistic sampling criteria and the decision-theoretic approach proposed throughout this paper.

Large multi-gene phylogenetic trees of the grasses (Poaceae): progress towards complete tribal and generic level sampling.

In this paper we included a very broad representation of grass family diversity (84% of tribes and 42% of genera). Phylogenetic inference was based on three plastid DNA regions rbcL, matK and trnL-F, using maximum parsimony and Bayesian methods. Our results resolved most of the subfamily relationships within the major clades (BEP and PACCMAD), which had previously been unclear, such as, among others the: (i) BEP and PACCMAD sister relationship, (ii) composition of clades and the sister-relationship of Ehrhartoideae and Bambusoideae + Pooideae, (iii) paraphyly of tribe Bambuseae, (iv) position of Gynerium as sister to Panicoideae, (v) phylogenetic position of Micrairoideae. With the presence of a relatively large amount of missing data, we were able to increase taxon sampling substantially in our analyses from 107 to 295 taxa. However, bootstrap support and to a lesser extent Bayesian inference posterior probabilities were generally lower in analyses involving missing data than those not including them. We produced a fully resolved phylogenetic summary tree for the grass family at subfamily level and indicated the most likely relationships of all included tribes in our analysis.

Interpolation and sampling in small Bergman spaces

"Vegeu el resum a l'inici del document del fitxer adjunt."

Orthogonal higher order structure and confirmatory factor analysis of the French Wechsler Adult Intelligence Scale (WAIS-III).

According to the most widely accepted Cattell-Horn-Carroll (CHC) model of intelligence measurement, each subtest score of the Wechsler Intelligence Scale for Adults (3rd ed.; WAIS-III) should reflect both 1st- and 2nd-order factors (i.e., 4 or 5 broad abilities and 1 general factor). To disentangle the contribution of each factor, we applied a Schmid-Leiman orthogonalization transformation (SLT) to the standardization data published in the French technical manual for the WAIS-III. Results showed that the general factor accounted for 63% of the common variance and that the specific contributions of the 1st-order factors were weak (4.7%-15.9%). We also addressed this issue by using confirmatory factor analysis. Results indicated that the bifactor model (with 1st-order group and general factors) better fit the data than did the traditional higher order structure. Models based on the CHC framework were also tested. Results indicated that a higher order CHC model showed a better fit than did the classical 4-factor model; however, the WAIS bifactor structure was the most adequate. We recommend that users do not discount the Full Scale IQ when interpreting the index scores of the WAIS-III because the general factor accounts for the bulk of the common variance in the French WAIS-III. The 4 index scores cannot be considered to reflect only broad ability because they include a strong contribution of the general factor.

Spin-labeling coronary MR angiography with steady-state free precession and radial k-space sampling: initial results in healthy volunteers.

The purpose of this study was to prospectively compare free-breathing navigator-gated cardiac-triggered three-dimensional steady-state free precession (SSFP) spin-labeling coronary magnetic resonance (MR) angiography performed by using Cartesian k-space sampling with that performed by using radial k-space sampling. A new dedicated placement of the two-dimensional selective labeling pulse and an individually adjusted labeling delay time approved by the institutional review board were used. In 14 volunteers (eight men, six women; mean age, 28.8 years) who gave informed consent, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), vessel sharpness, vessel length, and subjective image quality were investigated. Differences between groups were analyzed with nonparametric tests (Wilcoxon, Pearson chi2). Radial imaging, as compared with Cartesian imaging, resulted in a significant reduction in the severity of motion artifacts, as well as an increase in SNR (26.9 vs 12.0, P < .05) in the coronary arteries and CNR (23.1 vs 8.8, P < .05) between the coronary arteries and the myocardium. A tendency toward improved vessel sharpness and vessel length was also found with radial imaging. Radial SSFP imaging is a promising technique for spin-labeling coronary MR angiography.

Orthogonal organic and aqueous-based washes of tissue sections to enhance protein sensitivity by MALDI imaging mass spectrometry.

Imaging mass spectrometry (IMS) is an emergent and innovative approach for measuring the composition, abundance and regioselectivity of molecules within an investigated area of fixed dimension. Although providing unprecedented molecular information compared with conventional MS techniques, enhancement of protein signature by IMS is still necessary and challenging. This paper demonstrates the combination of conventional organic washes with an optimized aqueous-based buffer for tissue section preparation before matrix-assisted laser desorption/ionization (MALDI) IMS of proteins. Based on a 500 mM ammonium formate in water-acetonitrile (9:1; v/v, 0.1% trifluororacetic acid, 0.1% Triton) solution, this buffer wash has shown to significantly enhance protein signature by profiling and IMS (~fourfold) when used after organic washes (70% EtOH followed by 90% EtOH), improving the quality and number of ion images obtained from mouse kidney and a 14-day mouse fetus whole-body tissue sections, while maintaining a similar reproducibility with conventional tissue rinsing. Even if some protein losses were observed, the data mining has demonstrated that it was primarily low abundant signals and that the number of new peaks found is greater with the described procedure. The proposed buffer has thus demonstrated to be of high efficiency for tissue section preparation providing novel and complementary information for direct on-tissue MALDI analysis compared with solely conventional organic rinsing.

Solid phase microextraction as a short-term sampling technique for BTEX occupational exposure

Solid phase microextraction (SPME) has been widely used for many years in various applications, such as environmental and water samples, food and fragrance analysis, or biological fluids. The aim of this study was to suggest the SPME method as an alternative to conventional techniques used in the evaluation of worker exposure to benzene, toluene, ethylbenzene, and xylene (BTEX). Polymethylsiloxane-carboxen (PDMS/CAR) showed as the most effective stationary phase material for sorbing BTEX among other materials (polyacrylate, PDMS, PDMS/divinylbenzene, Carbowax/divinylbenzene). Various experimental conditions were studied to apply SPME to BTEX quantitation in field situations. The uptake rate of the selected fiber (75 microm PDMS/CAR) was determined for each analyte at various concentrations, relative humidities, and airflow velocities from static (calm air) to dynamic (> 200 cm/s) conditions. The SPME method also was compared with the National Institute of Occupational Safety and Health method 1501. Unlike the latter, the SPME approach fulfills the new requirement for the threshold limit value-short term exposure limit (TLV-STEL) of 2.5 ppm for benzene (8 mg/m(3))

Active Learning of Very-High Resolution Optical Imagery with SVM: Entropy vs Margin Sampling

An active learning method is proposed for the semi-automatic selection of training sets in remote sensing image classification. The method adds iteratively to the current training set the unlabeled pixels for which the prediction of an ensemble of classifiers based on bagged training sets show maximum entropy. This way, the algorithm selects the pixels that are the most uncertain and that will improve the model if added in the training set. The user is asked to label such pixels at each iteration. Experiments using support vector machines (SVM) on an 8 classes QuickBird image show the excellent performances of the methods, that equals accuracies of both a model trained with ten times more pixels and a model whose training set has been built using a state-of-the-art SVM specific active learning method

Comparison between splenic and lymph node aspirations as sampling methods for the parasitological detection of Leishmania chagasi infection in dogs

The sensitivities of spleen and lymph node cultures for the diagnosis of canine visceral leishmaniasis were compared in 64 anti-Leishmania antibody positive dogs from an endemic area in Brazil. The sensitivity of spleen cultures for Leishmania detection was 97.9%; in lymph node cultures it was 25%. Positive spleen culture was more frequent (p = 0.048, Fisher's exact probability test) in symptomatic (28 out of 33 animals) than in asymptomatic animals (19 out of 31 animals). These results support the use of spleen instead of lymph node aspiration as the choice method for the parasitological diagnosis of the infection.