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Objective.--The routine clinical laboratory detection of Bordetella pertussis is through culture, which can require 5 to 7 days for the bacteria to grow. Using a polymerase chain reaction (PCR) assay can shorten this detection time while increasing the sensitivity of detection with similar specificity. This study compared culture with TaqMan PCR for detection of B pertussis in clinical specimens and the turnaround time for each assay during the pertussis season. Materials and Methods.--Nasopharyngeal swabs in Regan-Lowe transport media were collected from 1556 persons who had symptoms of whooping cough or who had had contact with infected persons; the swabs were submitted for B pertussis detection during the pertussis season. A single nasopharyngeal swab from each patient was submitted for both culture and TaqMan PCR detection. Upon receipt of the specimens, the swabs were inoculated onto Regan-Lowe agar for culture and incubated for up to 7 days. The same swab was processed for PCR detection using TaqMan PCR assay. A second nested PCR was used on positive specimens for resolution purposes. The TaqMan PCR assay was performed 3 to 5 days a week, whereas the culture was performed 6 days a week. All specimens were processed on the same day or earliest possible working day for TaqMan or culture, and specimens queued for resolution by nested PCR were batched. Results.--There were a total of 275 PCR positives and 28 culture positives. After resolution with the second nested PCR, the sensitivity, specificity, positive predictive value, and negative predictive value were 100%, 97.4%, 87.6%, and 100% for TaqMan PCR and 11.6%, 100%, 100%, and 85.7% for culture. The average turnaround time for positive culture was 5.1 days, and the average turnaround time for PCR was 2.3 days. Conclusion.--The TaqMan PCR assay has superior sensitivity and shorter turnaround time over culture because it can be finished within one working day. Furthermore, the same swab can be used for culture of the bacteria for antibiotic susceptibility testing. The early detection of pertussis using TaqMan PCR assay allows early intervention on the spread of the disease and the ability to culture the bacteria from the same swab, thereby eliminating the need for a second swab and allowing for detection of antibiotic resistance., Pertussis is an acute disease of the respiratory tract characterized by progressive, repetitive paroxysmal coughing; mild systemic complaints; and lymphocytosis. Bordetella pertussis does not survive well in the environment and [...]

Abstract Background Document gene normalization is the problem of creating a list of unique identifiers for genes that are mentioned within a document. Automating this process has many potential applications in both information extraction and database curation systems. Here we present two separate solutions to this problem. The first is primarily based on standard pattern matching and information extraction techniques. The second and more novel solution uses a statistical classifier to recognize valid gene matches from a list of known gene synonyms. Results We compare the results of the two systems, analyze their merits and argue that the classification based system is preferable for many reasons including performance, simplicity and robustness. Our best systems attain a balanced precision and recall in the range of 74%–92%, depending on the organism.

The number of missing children in Canada is increasing. An estimated 64% of missing children are runaways. Other causes of the problem are parental abduction, kidnappings and children getting lost. Of the runaways, one third were repeat offenders, while the greatest amount of missing children was found in the age group of 12 to 17 years. Child Fund Canada Inc and the Missing Children's Network are two of the non-profit organizations that help recover missing children. By region, the western provinces have a greater incidence of missing children.

Consuming wood as a primary food source poses many challenges for animals. Rich in non-assimilable carbohydrates, wood digestion requires a high degree of anatomical and physiological specialization by both the host and its microbiome. However, wood comsumption (xylivory) as a dietary strategy to obtain energy has been recorded in a small number of animals including beaver, porcupine, and moose and wood typically accounts for a small fraction of the overall diet in these organisms, or, is limited to the nutrient-rich tissues of the bark and vascular cambium. The paucity of wood-feeding organisms is due to the recalcitrant and nutrient-poor nature of the substrate. Our current understanding of wood feeding is limited to a small number of marine and terrestrial invertebrate systems. In this chapter we focus on the Neotropical catfish, Panaque nigrolineatus, which ingests large quantities of wood as part of its diet. The microbiome of P. nigrolineatus has been shown to include bacterial and fungal communities participating in both lignocellulose degradation and nitrogen fixation that are taxonomically distinct from all other wood-feeding organisms, although the functional capacity of these communities is consistent with those observed in other wood-feeders. This environmentally recruited microbiome allows the gastrointestinal tract microbiome a high degree of flexibility and resilience ideally suited to rapid changes in dietary strategy. [ABSTRACT FROM AUTHOR]

Abstract Background Surveillance examining the incidence of community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) was conducted over 8 years beginning in 2001 in three health regions covering the northern half of Saskatchewan. The annual rate of individuals reported with CA-MRSA infection in these regions dramatically increased from 8.2 per 10,000 population in 2001 (range to 4.4-10.1 per 10,000) to 168.1 per 10,000 in 2006 (range 43.4-230.9 per 10,000). To address this issue, a team of community members, healthcare professionals, educators and research scientists formed a team called "the Northern Antibiotic Resistance Partnership" (NARP) to develop physician, patient, community, and school based educational materials in an attempt to limit the spread of CA-MRSA. Methods Posters, radio broadcasts, community slide presentations, physician treatment algorithms, patient pamphlets, and school educational programs Do Bugs Need Drugs http://www.dobugsneeddrugs.org and Germs Away http://www.germsaway.ca were provided to targeted northern communities experiencing high rates of infections. Results Following implementation of this program, the rates of MRSA infections in the targeted communities have decreased nearly two-fold (242.8 to 129.3 infections/10,000 population) from 2006 to 2008. Through pre-and post-educational intervention surveys, this decrease in MRSA infections coincided with an increase in knowledge related to appropriate antimicrobial usage and hand washing in these communities. Conclusion These educational materials are all freely available http://www.narp.ca and will hopefully aid in increasing awareness of the importance of proper antimicrobial usage and hygiene in diminishing the spread of S. aureus and other infectious diseases in other communities.

Abstract Background The rapid proliferation of biomedical text makes it increasingly difficult for researchers to identify, synthesize, and utilize developed knowledge in their fields of interest. Automated information extraction procedures can assist in the acquisition and management of this knowledge. Previous efforts in biomedical text mining have focused primarily upon named entity recognition of well-defined molecular objects such as genes, but less work has been performed to identify disease-related objects and concepts. Furthermore, promise has been tempered by an inability to efficiently scale approaches in ways that minimize manual efforts and still perform with high accuracy. Here, we have applied a machine-learning approach previously successful for identifying molecular entities to a disease concept to determine if the underlying probabilistic model effectively generalizes to unrelated concepts with minimal manual intervention for model retraining. Results We developed a named entity recognizer (MTag), an entity tagger for recognizing clinical descriptions of malignancy presented in text. The application uses the machine-learning technique Conditional Random Fields with additional domain-specific features. MTag was tested with 1,010 training and 432 evaluation documents pertaining to cancer genomics. Overall, our experiments resulted in 0.85 precision, 0.83 recall, and 0.84 F-measure on the evaluation set. Compared with a baseline system using string matching of text with a neoplasm term list, MTag performed with a much higher recall rate (92.1% vs. 42.1% recall) and demonstrated the ability to learn new patterns. Application of MTag to all MEDLINE abstracts yielded the identification of 580,002 unique and 9,153,340 overall mentions of malignancy. Significantly, addition of an extensive lexicon of malignancy mentions as a feature set for extraction had minimal impact in performance. Conclusion Together, these results suggest that the identification of disparate biomedical entity classes in free text may be achievable with high accuracy and only moderate additional effort for each new application domain.