Microbial analysis of soil and groundwater from a gasworks site and comparison to a sequenced biological reactive barrier remediation process (SEREBAR)

Aims: To investigate the distribution of a polymicrobial community of biodegradative bacteria in (i) soil and groundwater at a former manufactured gas plant (FMGP) site and (ii) in a novel SEquential REactive BARrier (SEREBAR) bioremediation process designed to bioremediate the contaminated groundwater. Methods and Results: Culture-dependent and culture-independent analyses using denaturing gradient gel electrophoresis (DGGE) and polymerase chain reaction (PCR) for the detection of 16S ribosomal RNA gene and naphthalene dioxygenase (NDO) genes of free-living (planktonic groundwater) and attached (soil biofilm) samples from across the site and from the SEREBAR process was applied. Naphthalene arising from groundwater was effectively degraded early in the process and the microbiological analysis indicated a dominant role for Pseudomonas and Comamonas in its degradation. The microbial communities appeared highly complex and diverse across both the sites and in the SEREBAR process. An increased population of naphthalene degraders was associated with naphthalene removal. Conclusion: The distribution of micro-organisms in general and naphthalene degraders across the site was highly heterogeneous. Comparisons made between areas contaminated with polycyclic aromatic hydrocarbons (PAH) and those not contaminated, revealed differences in the microbial community profile. The likelihood of noncultured bacteria being dominant in mediating naphthalene removal was evident. Significance and Impact of the Study: This work further emphasizes the importance of both traditional and molecular-based tools in determining the microbial ecology of contaminated sites and highlights the role of noncultured bacteria in the process.

Ca II K observations of QSOs in the line-of-sight to the Magellanic Bridge

We describe medium-resolution spectroscopic observations taken with the ESO Multi-Mode Instrument (EMMI) in the CaII K line (lambda air = 3933.661 angstrom) towards 7 QSOs located in the line-of-sight to the Magellanic Bridge. At a spectral resolution R =lambda/Delta lambda = 6000, five of the sightlines have a signal-to-noise ( S/N) ratio of similar to 20 or higher. Definite Ca absorption due to Bridge material is detected towards 3 objects, with probable detection towards two other sightlines. Gas-phase CaII K Bridge and Milky Way abundances or lower limits for the all sightlines are estimated by the use of Parkes 21-cm H. emission line data. These data only have a spatial resolution of 14 arcmin compared with the optical observations which have milli-arcsecond resolution. With this caveat, for the three objects with sound CaII K detections, we find that the ionic abundance of CaII K relative to HI, A = log( N( CaK)/ N( HI)) for low- velocity Galactic gas ranges from - 8.3 to - 8.8 dex, with HI column densities varying from 3- 6 x 10(20) cm(-2). For Magellanic Bridge gas, the values of A are similar to 0.5 dex higher, ranging from similar to- 7.8 to - 8.2 dex, with N( HI) = 1- 5 x 1020 cm(-2). Higher values of A correspond to lower values of N( HI), although numbers are small. For the sightline towards B 0251 - 675, the Bridge gas has two different velocities, and in only one of these is CaII tentatively detected, perhaps indicating gas of a different origin or present-day characteristics ( such as dust content), although this conclusion is uncertain and there is the possibility that one of the components could be related to the Magellanic Stream. Higher signal-to-noise CaII K data and higher resolution H. data are required to determine whether A changes with N( HI) over the Bridge and if the implied difference in the metalicity of the two Bridge components towards B 0251-675 is real.

A non-LTE abundance analysis of the post-AGB star ROA 5701

An analysis of high-resolution Anglo-Australian Telescope (AAT)/University College London Echelle Spectrograph (UCLES) optical spectra for the ultraviolet (UV)-bright star ROA 5701 in the globular cluster omega Cen (NGC 5139) is performed, using non-local thermodynamic equilibrium (non-LTE) model atmospheres to estimate stellar atmospheric parameters and chemical composition. Abundances are derived for C, N, O, Mg, Si and S, and compared with those found previously by Moehler et al. We find a general metal underabundance relative to young B-type stars, consistent with the average metallicity of the cluster. Our results indicate that ROA 5701 has not undergone a gas-dust separation scenario as previously suggested. However, its abundance pattern does imply that ROA 5701 has evolved off the asymptotic giant branch (AGB) prior to the onset of the third dredge-up.

Computerised Diagnostic Decision Support System for the Classification of Pre-Invasive Cervical Squamous Lesions.

Previous studies have revealed considerable interobserver and intraobserver variation in the histological classification of preinvasive cervical squamous lesions. The aim of the present study was to develop a decision support system (DSS) for the histological interpretation of these lesions. Knowledge and uncertainty were represented in the form of a Bayesian belief network that permitted the storage of diagnostic knowledge and, for a given case, the collection of evidence in a cumulative manner that provided a final probability for the possible diagnostic outcomes. The network comprised 8 diagnostic histological features (evidence nodes) that were each independently linked to the diagnosis (decision node) by a conditional probability matrix. Diagnostic outcomes comprised normal; koilocytosis; and cervical intraepithelial neoplasia (CIN) 1, CIN II, and CIN M. For each evidence feature, a set of images was recorded that represented the full spectrum of change for that feature. The system was designed to be interactive in that the histopathologist was prompted to enter evidence into the network via a specifically designed graphical user interface (i-Path Diagnostics, Belfast, Northern Ireland). Membership functions were used to derive the relative likelihoods for the alternative feature outcomes, the likelihood vector was entered into the network, and the updated diagnostic belief was computed for the diagnostic outcomes and displayed. A cumulative probability graph was generated throughout the diagnostic process and presented on screen. The network was tested on 50 cervical colposcopic biopsy specimens, comprising 10 cases each of normal, koilocytosis, CIN 1, CIN H, and CIN III. These had been preselected by a consultant gynecological pathologist. Using conventional morphological assessment, the cases were classified on 2 separate occasions by 2 consultant and 2 junior pathologists. The cases were also then classified using the DSS on 2 occasions by the 4 pathologists and by 2 medical students with no experience in cervical histology. Interobserver and intraobserver agreement using morphology and using the DSS was calculated with K statistics. Intraobserver reproducibility using conventional unaided diagnosis was reasonably good (kappa range, 0.688 to 0.861), but interobserver agreement was poor (kappa range, 0.347 to 0.747). Using the DSS improved overall reproducibility between individuals. Using the DSS, however, did not enhance the diagnostic performance of junior pathologists when comparing their DSS-based diagnosis against an experienced consultant. However, the generation of a cumulative probability graph also allowed a comparison of individual performance, how individual features were assessed in the same case, and how this contributed to diagnostic disagreement between individuals. Diagnostic features such as nuclear pleomorphism were shown to be particularly problematic and poorly reproducible. DSSs such as this therefore not only have a role to play in enhancing decision making but also in the study of diagnostic protocol, education, self-assessment, and quality control. (C) 2003 Elsevier Inc. All rights reserved.