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.

A tripartite microbial reporter gene system for real-time assays of soil nutrient status

Plant-derived carbon is the substrate which drives the rate of microbial assimilation and turnover of nutrients, in particular N and P, within the rhizosphere. To develop a better understanding of rhizosphere dynamics, a tripartite reporter gene system has been developed. We used three lux-marked Pseudomonas fluorescens strains to report on soil (1) assimilable carbon, (2) N-status, and (3) P-status. In vivo studies using soil water, spiked with C, N and P to simulate rhizosphere conditions, showed that the tripartite reporter system can provide real-time assessment of carbon and nutrient status. Good quantitative agreement for bioluminescence output between reference material and soil water samples was found for the C and P reporters. With regard to soil nitrate, the minimum bioavailable concentration was found to be greater than that analytically detectable in soil water. This is the first time that bioavailable soil C, N and P have been quantified using a tripartite reporter gene system.

Packet classification by multi-level cutting of the classification space: An algorithmic-architectural solution for IP packet classification in next generation networks

Traditionally, the Internet provides only a “best-effort” service, treating all packets going to the same destination equally. However, providing differentiated services for different users based on their quality requirements is increasingly becoming a demanding issue. For this, routers need to have the capability to distinguish and isolate traffic belonging to different flows. This ability to determine the flow each packet belongs to is called packet classification. Technology vendors are reluctant to support algorithmic solutions for classification due to their non-deterministic performance. Although CAMs are favoured by technology vendors due to their deterministic high lookup rates, they suffer from the problems of high power dissipation and high silicon cost. This paper provides a new algorithmic-architectural solution for packet classification that mixes CAMs with algorithms based on multi-level cutting the classification space into smaller spaces. The provided solution utilizes the geometrical distribution of rules in the classification space. It provides the deterministic performance of CAMs, support for dynamic updates, and added flexibility for system designers.

Packet classification by multi-level cutting of the classification space

Traditionally, the Internet provides only a “best-effort” service, treating all packets going to the same destination equally. However, providing differentiated services for different users based on their quality requirements is increasingly becoming a demanding issue. For this, routers need to have the capability to distinguish and isolate traffic belonging to different flows. This ability to determine the flow each packet belongs to is called packet classification. Technology vendors are reluctant to support algorithmic solutions for classification due to their nondeterministic performance. Although content addressable memories (CAMs) are favoured by technology vendors due to their deterministic high-lookup rates, they suffer from the problems of high-power consumption and high-silicon cost. This paper provides a new algorithmic-architectural solution for packet classification that mixes CAMs with algorithms based on multilevel cutting of the classification space into smaller spaces. The provided solution utilizes the geometrical distribution of rules in the classification space. It provides the deterministic performance of CAMs, support for dynamic updates, and added flexibility for system designers.

Physicochemical and mineralogical characteristics of soil/saprolite cores from a field research site, Tennessee

Site characterization is an essential initial step in determining the feasibility of remedial alternatives at hazardous waste sites. Physicochemical and mineralogical characterization of U-contaminated soils in deeply weathered saprolite at Area 2 of the DOE Field Research Center (FRC) site, Oak Ridge, TN, was accomplished to examine the feasibility of bioremediation. Concentrations of U in soil–saprolite (up to 291 mg kg–1 in oxalate-extractable Uo) were closely related to low pH (ca. 4–5), high effective cation exchange capacity without Ca (64.7–83.2 cmolc kg–1), amorphous Mn content (up to 9910 mg kg–1), and the decreased presence of relative clay mineral contents in the bulk samples (i.e., illite 2.5–12 wt. %, average 32 wt. %). The pH of the fill material ranged from 7.0 to 10.5, whereas the pH of the saprolite ranged from 4.5 to 8. Uranium concentration was highest (about 300 mg kg–1) at around 6 m below land surface near the saprolite–fill interface. The pH of ground water at Area 2 tended to be between 6 and 7 with U concentrations of about 0.9 to 1.7 mg L–1. These site specific characteristics of Area 2, which has lower U and nitrate contamination levels and more neutral ground water pH compared with FRC Areas 1 and 3 (ca. 5.5 and

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.