A new method for the rapid and sensitive detection of Legionella pneumophila in hot water systems has been developed. The method is based on an IF assay combined with detection by solid-phase cytometry. This method allowed the enumeration of L. pneumophila serogroup 1 and L. pneumophila serogroups 2 to 6, 8 to 10, and 12 to 15 in tap water samples within 3 to 4 h. The sensitivity of the method was between 10 and 100 bacteria per liter and was principally limited by the filtration capacity of membranes. The specificity of the antibody was evaluated against 15 non-Legionella strains, and no cross-reactivity was observed. When the method was applied to natural waters, direct counts of L. pneumophila were compared with the number of CFU obtained by the standard culture method. Direct counts were always higher than culturable counts, and the ratio between the two methods ranged from 1.4 to 325. Solid-phase cytometry offers a fast and sensitive alternative to the culture method for L. pneumophila screening in hot water systems.
Free-living Naegleria fowleri amoebae cause primary amoebic meningoencephalitis (PAM). Because of the apparent conflict between their ubiquity and the rarity of cases observed, we sought to develop a model characterizing the risk of PAM after swimming as a function of the concentration of N. fowleri. The probability of death from PAM as a function of the number of amoebae inhaled is modeled according to results obtained from animals infected with amoeba strains. The calculation of the probability of inhaling one or more amoebae while swimming is based on a double hypothesis: that the distribution of amoebae in the water follows a Poisson distribution and that the mean quantity of water inhaled while swimming is 10 ml. The risk of PAM for a given concentration of amoebae is then obtained by summing the following products: the probability of inhaling n amoebae ؋ the probability of PAM associated with inhaling these n amoebae. We chose the lognormal model to assess the risk of PAM because it yielded the best analysis of the studentized residuals. Nonetheless, the levels of risk thereby obtained cannot be applied to humans without correction, because they are substantially greater than those indicated by available epidemiologic data. The curve was thus adjusted by a factor calculated with the least-squares method. This provides the PAM risk in humans as a function of the N. fowleri concentration in the river. For example, the risk is 8.5 ؋ 10 ؊8 at a concentration of 10 N. fowleri amoebae per liter.
Apoptosis or programmed cell death plays a key role in many biological processes particularly in oncology. The detection of apoptotic cells is crucial for the study of the phenomenon itself and its relation with the proliferative cell cycle. A new method to detect apoptosis in situ in Feulgen stained cells was developed, based on multiparametric analysis (Eactorial and decisional analysis), using 15 densitometric and textural parameters measured on a SAMBA 200 cell image processor. Six reference files corresponding to G1, S, and G2 phases and to apoptotic cells derived from these cell cycle phases were constructed. The projection of these files in the factorial principal plane formed distinct clusters.While the concept of physiological and programmed cell death had been introduced in the early 1950s, the term "apoptosis" was only introduced by Kerr et al. (24) in 1972. This phenomenon plays a critical role in many biological processes: developmental biology (4), maintenance of a steady state in continuously renewing tissues (26); or in oncology: cancer development, role of protooncogenes, or cancer chemotherapy (2830,3436). The characteristic of apoptosis is internucleosomal DNA degradation which is mediated by Ca2 +/Mg* +-dependent endonuclease and can be activated by both physiological and pathological stimuli (37). Many studies reveal the close link existing between apoptosis and the proliferative cell cycle (3,7,23,32). To study the impact of programmed cell death on cancer development and therapy and its relation with the proliferative cell cycle, it is very important to be able to detect the apoptotic cells easily.Many assay systems based on internucleosomal DNA fragmentation, like gel electrophoresis of internucleosomal DNA fragments, were used. But these assay systems failed to evaluate apoptosis on a cell-by-cell basis (33) and required many cells. Recently, enzymatic methods based on the detection of degradation products of the DNA fkagmentation were adapted to reveal apoptosis at the cellular level in tissue sections and in cell culture systems In a previous article (6), the use of scanning cytometry for mammary epithelial cell cycle studies on Feulgen-(18).Using the decisional discriminant analysis, it was possible to ascertain the state (apoptosis or proliferative) and the phase for each cell of a population. The correct classification rate of this analysis was 0.9962. Determining the cell cycle phase from which each apoptotic cell comes, we are able to study the relation between apoptosis and the proliferative cell cycle. Moreover, the detection in situ allows us to study cell-cell interactions.0 1996 Wiley-Liss, I~c.Key terms: Apoptosis, cell cycle, multiparametric quantitative microscopy, mammary epithelial cell line Rossenbech stoichiometric DNA stained cells was proposed. In the present work, we extended this methodology taking into account the phenomenon of apoptosis. This technique constitutes a new method to detect the apoptotic cells without specific staining. Moreover, the use of Feulgen...
Based on the data from a French outbreak of legionellosis, a probabilistic approach was developed to analyze and assess the potential role of several suspected sources of contamination. Potential dates of exposure of all cases were determined using back-calculation, using two probability distribution functions to model incubation period. A probabilistic analysis and risk assessment were then used to determine the most probable sources of contamination for each wave of the outbreak. The risk assessment was based on parameters representing emission and dispersion of Legionella: level and duration of emission; aerosol dispersion capacity; and probability of potential exposure for each patient. Four types of facilities containing the Legionella epidemic strain were analyzed: cooling towers, aerated wastewater basins, high pressure water cleaners, and car wash stations. The results highlighted the potential role of an aerated wastewater basin in the outbreak in addition to cooling towers. The role of high-pressure water cleaners and car wash stations appeared to be non-significant. This study also reveals the lack of knowledge on facility parameters that can be useful for microbial risk assessments. This type of probabilistic analysis can be used to quantitatively assess the risk for various facilities in order to manage a legionellosis outbreak.
Our lack of knowledge about the biological mechanisms of 50 Hz magnetic fields makes it hard to improve exposure assessment. To provide better information about these exposure measures, we use multidimensional analysis techniques to examine the relations between different exposure metrics for a group of subjects. We used a combination of a two stage Principal Component Analysis (PCA) followed by an ascending hierarchical classification (AHC) to identify a set of measures that would capture the characteristics of the total exposure. This analysis gives an indication of the aspects of the exposure that are important to capture to get a complete picture of the magnetic field environment. We calculated 44 metrics of exposure measures from 16 exposed EDF employees and 15 control subjects, containing approximately 20,000 recordings of magnetic field measurements, taken every 30 s for 7 days with an EMDEX II dosimeter. These metrics included parameters used routinely or occasionally and some that were new. To eliminate those that expressed the least variability and that were most highly correlated to one another, we began with an initial Principal Component Analysis (PCA). A second PCA of the remaining 12 metrics enabled us to identify from the foreground 82.7% of the variance: the first component (62.0%) was characterized by central tendency metrics, and the second (20.7%) by dispersion characteristics. We were able to use AHC to divide the entire sample (of individuals) into four groups according to the axes that emerged from the PCA. Finally, discriminant analysis tested the discriminant power of the variables in the exposed/control classification as well as those from the AHC classification. The first showed that two subjects had been incorrectly classified, while no classification error was observed in the second. This exploratory study underscores the need to improve exposure measures by using at least two dimensions: intensity and dispersion. It also indicates the usefulness of constructing a typology of magnetic field exposures.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.