Water quality in dental chair units. A random sample in the canton of St. Gallen

This study aimed to identify the microbial contamination of water from dental chair units (DCUs) using the prevalence of Pseudomonas aeruginosa, Legionella species and heterotrophic bacteria as a marker of pollution in water in the area of St. Gallen, Switzerland. Water (250 ml) from 76 DCUs was collected twice (early on a morning before using all the instruments and after using the DCUs for at least two hours) either from the high-speed handpiece tube, the 3 in 1 syringe or the micromotor for water quality testing. An increased bacterial count (>300 CFU/ml) was found in 46 (61%) samples taken before use of the DCU, but only in 29 (38%) samples taken two hours after use. Pseudomonas aeruginosa was found in both water samples in 6/76 (8%) of the DCUs. Legionella were found in both samples in 15 (20%) of the DCUs tested. Legionella anisa was identified in seven samples and Legionella pneumophila was found in eight. DCUs which were less than five years old were contaminated less often than older units (25% und 77%, p<0.001). This difference remained significant (0=0.0004) when adjusted for manufacturer and sampling location in a multivariable logistic regression. A large proportion of the DCUs tested did not comply with the Swiss drinking water standards nor with the recommendations of the American Centers for Disease Control and Prevention (CDC).

The impact of the stone age diet on gingival conditions in the absence of oral hygiene

BACKGROUND: The objective of this study was to assess the oral microbiota and clinical data in subjects without access to traditional oral hygiene methods and who ate a diet available in the Stone Age. METHODS: Ten subjects living in an environment replicating the Stone Age for 4 weeks were enrolled in this study. Bleeding on probing (BOP), gingival and plaque indices, and probing depth (PD) were assessed at baseline and at 4 weeks. Microbiologic samples were collected at the mesio-buccal subgingival aspects of all teeth and from the dorsum of the tongue and were processed by checkerboard DNA-DNA hybridization methods. RESULTS: No subject had periodontitis. Mean BOP decreased from 34.8% to 12.6% (P <0.001). Mean gingival index scores changed from 0.38 to 0.43 (not statistically significant) and mean plaque scores increased from 0.68 to 1.47 (P <0.001). PD at sites of subgingival sampling decreased (mean difference: 0.2 mm; P <0.001). At week 4, the total bacterial count was higher (P <0.001) for 24 of 74 species, including Bacteroides ureolyticus, Eikenella corrodens, Lactobacillus acidophilus, Capnocytophaga ochracea, Escherichia coli, Fusobacterium nucleatum naviforme, Haemophilus influenzae, Helicobacter pylori, Porphyromonas endodontalis, Staphylococcus aureus (two strains), Streptococcus agalactiae, Streptococcus anginosis, and Streptococcus mitis. Bacterial counts from tongue samples were higher at baseline (P <0.001) for 20 species, including Tannerella forsythia (previously T. forsythensis), Aggregatibacter actinomycetemcomitans (previously Actinobacillus actinomycetemcomitans; serotype a), and Streptococcus spp. CONCLUSIONS: The experimental gingivitis protocol is not applicable if the diet (e.g., Stone Age) does not include refined sugars. Although plaque levels increased, BOP and PD decreased. Subgingival bacterial counts increased for several species not linked to periodontitis, whereas tongue bacterial samples decreased during the study period.

[Spontaneous bacterial peritonitis]

Spontaneous bacterial peritonitis (SBP) is the most frequent infection in patients with cirrhosis during hospitalization and is associated with high acute and long-term mortality. Diagnosis is made by paracentesis with determination of neutrophil count in ascitic fluid. Empirical antibiotic therapy must be initiated immediately. The choice of drug is dependent on prior therapies. Liver transplantation has to be considered in the absence of contra-indications. Prophylaxis of SBP is indicated in patients with ascites and gastrointestinal hemorrhage, and in patients after SBP. Primary prophylaxis should be considered in high-risk patients with cirrhosis and ascites. The development of resistance to antibiotic drugs is a relevant side-effect.

Matrix metalloproteinase (MMP)-8 and MMP-9 in cerebrospinal fluid during bacterial meningitis: association with blood-brain barrier damage and neurological sequelae.

To evaluate the spectrum and regulation of matrix metalloproteinases (MMPs) in bacterial meningitis (BM), concentrations of MMP-2, MMP-3, MMP-8, and MMP-9 and endogenous inhibitors of metalloproteinases (TIMP-1 and TIMP-2) were measured in the cerebrospinal fluid (CSF) of 27 children with BM. MMP-8 and MMP-9 were detected in 91% and 97%, respectively, of CSF specimens from patients but were not detected in control patients. CSF levels of MMP-9 were higher (P<.05) in 5 patients who developed hearing impairment or secondary epilepsy than in those who recovered without neurological deficits. Levels of MMP-9 correlated with concentrations of TIMP-1 (P<.001) and tumor necrosis factor-alpha (P=.03). Repeated lumbar punctures showed that levels of MMP-8 and MMP-9 were regulated independently and did not correlate with the CSF cell count. Therefore, MMPs may derive not only from granulocytes infiltrating the CSF space but also from parenchymal cells of the meninges and brain. High concentrations of MMP-9 are a risk factor for the development of postmeningitidal neurological sequelae.

Automated counting of bacterial colony forming units on agar plates.

Manual counting of bacterial colony forming units (CFUs) on agar plates is laborious and error-prone. We therefore implemented a colony counting system with a novel segmentation algorithm to discriminate bacterial colonies from blood and other agar plates.A colony counter hardware was designed and a novel segmentation algorithm was written in MATLAB. In brief, pre-processing with Top-Hat-filtering to obtain a uniform background was followed by the segmentation step, during which the colony images were extracted from the blood agar and individual colonies were separated. A Bayes classifier was then applied to count the final number of bacterial colonies as some of the colonies could still be concatenated to form larger groups. To assess accuracy and performance of the colony counter, we tested automated colony counting of different agar plates with known CFU numbers of S. pneumoniae, P. aeruginosa and M. catarrhalis and showed excellent performance.