Photodynamic inactivation of Candida albicans by BAM-SiPc.

Photodynamic therapy is a treatment that combines the use of three non-toxic components, viz. photosensitiser, light and oxygen to cause localised oxidative photodamage. In the present study, the antifungal effect of the photosensitiser, BAM-SiPc, an unsymmetrical bisamino phthalocyanine, was investigated. BAM-SiPc was effective in photo-inactivating Candida albicans in a dose-dependent manner. The cell viability as determined by the clonogenic assay was reduced to c. 10% at 0.02 micromol l(-1) BAM-SiPc with a total fluence of 12 J cm(-2) at a cell density of 10(7) cells ml(-1). A short incubation time of 5-15 min was sufficient to allow the photosensitiser to exert its optimal antifungal activity. Microscopical analysis showed that BAM-SiPc was effectively internalised by the fungal cells. Photodynamic treatment led to an increase in the intracellular reactive oxygen species level and disturbed the membrane integrity of the fungal cells.

J1 acylase, a glutaryl-7-aminocephalosporanic acid acylase from Bacillus laterosporus J1, is a member of the alpha/beta-hydrolase fold superfamily.

J1 acylase, a glutaryl-7-aminocephalosporanic acid acylase (GCA) isolated from Bacillus laterosporus J1, has been conventionally grouped as the only member of class V GCA, although its amino acid sequence shares less than 10% identity with members of other classes of GCA. Instead, it shows higher sequence similarities with Rhodococcus sp. strain MB1 cocaine esterase (RhCocE) and Acetobacter turbidans alpha-amino acid ester hydrolase (AtAEH), members of the alpha/beta-hydrolase fold superfamily. Homology modeling and secondary structure prediction indicate that the N-terminal region of J1 acylase has an alpha/beta-hydrolase folding pattern. The catalytic triads in RhCocE and AtAEH were identified in J1 acylase as S125, D264 and H309. Mutations to alanine at these positions were found to completely inactivate the enzyme. These results suggest that J1 acylase is a member of the alpha/beta-hydrolase fold superfamily with a serine-histidine-aspartate catalytic triad.

Characterization of Actinobacillus actinomycetemcomitans isolated from young Chinese aggressive periodontitis patients.

OBJECTIVE: This study characterized Actinobacillus actinomycetemcomitans isolates from young Chinese aggressive periodontitis patients. METHODS: Subgingival plaque samples (two/subject) were collected from diseased subjects < 25 years old (n = 9, mean age 21.1 +/- 1.6 years) and age-matched periodontitis-free controls (n = 47, mean age 22.0 +/- 1.1 years). Selective and anaerobic culture were used. The serotype, leukotoxin gene (ltx) operon promoter and the cytolethal distending toxin (cdt) genes complex of the A. actinomycetemcomitans isolates were investigated. Effects of the isolates on non-keratinizing periodontal ligament epithelial cells monolayer were studied. RESULTS: Diseased subjects had significantly higher full-mouth bleeding score (p = 0.002) and total viable counts from plaque samples (7.2 x 10(6) vs. 2.1 x 10(5) CFU/paperpoint, p < 0.005). A. actinomycetemcomitans was isolated from 67%/56% or 6%/4% of diseased or controls subject/sites, respectively (p < 0.001). The proportion of A. actinomycetemcomitans isolatable from aggressive periodontitis or periodontitis-free associated subgingival plaque was low (0.7% vs. 0.1%, p < 0.02). The serotype of the isolates was characterized. All isolates possessed 652-like ltx gene promoter and all but one serotype c isolate from a diseased patient had intact cdtABC genes. That particular strain appeared to confer the least cellular damages on periodontal ligament epithelial monolayer compared to others. CONCLUSION: This preliminary study confirmed the notion of increased prevalence and quantity of A. actinomycetemcomitans associated with aggressive periodontitis in young patients. The overall ltx promoter and cdt characteristics of the A. actinomycetemcomitans isolates, however, were similar among the diseased and control groups. A strain lacking the cdtABC gene appeared to be less damaging to a periodontal ligament epithelial cell model. Further studies therefore are warranted to clarify the pathogenic role and potentials of A. actinomycetemcomitans in aggressive periodontitis.

Charting epilepsy by searching for intelligence in network space with the help of evolving autonomous agents.

The problem of demarcating neural network space is formidable. A simple fully connected recurrent network of five units (binary activations, synaptic weight resolution of 10) has 3.2 *10(26) possible initial states. The problem increases drastically with scaling. Here we consider three complementary approaches to help direct the exploration to distinguish epileptic from healthy networks. [1] First, we perform a gross mapping of the space of five-unit continuous recurrent networks using randomized weights and initial activations. The majority of weight patterns (>70%) were found to result in neural assemblies exhibiting periodic limit-cycle oscillatory behavior. [2] Next we examine the activation space of non-periodic networks demonstrating that the emergence of paroxysmal activity does not require changes in connectivity. [3] The next challenge is to focus the search of network space to identify networks with more complex dynamics. Here we rely on a major available indicator critical to clinical assessment but largely ignored by epilepsy modelers, namely: behavioral states. To this end, we connected the above network layout to an external robot in which interactive states were evolved. The first random generation showed a distribution in line with approach [1]. That is, the predominate phenotypes were fixed-point or oscillatory with seizure-like motor output. As evolution progressed the profile changed markedly. Within 20 generations the entire population was able to navigate a simple environment with all individuals exhibiting multiply-stable behaviors with no cases of default locked limit-cycle oscillatory motor behavior. The resultant population may thus afford us a view of the architectural principles demarcating healthy biological networks from the pathological. The approach has an advantage over other epilepsy modeling techniques in providing a way to clarify whether observed dynamics or suggested therapies are pointing to computational viability or dead space.