Surgical outcome of safe surgery system trabeculectomy combined with cataract extraction.

PURPOSE: To determine the efficacy of safe surgery system trabeculectomy combined with manual small incision cataract surgery/phacoemulsification in primary glaucoma coexistent with cataract. METHODS: This is a retrospective analysis of 105 cases who underwent single-site combined surgery between January 2008 and December 2009. Safe surgery system trabeculectomy with diffuse and posterior application of mitomycin C was performed in all cases. Cataract extraction was done either by Manual Small Incision Cataract Surgery (MSICS) or phacoemulsification. Main outcome measures were success rate of trabeculectomy, as determined by four different IOP goals and incidence of postoperative complications. Analysis was performed using R-2.15, and the significance was tested at 5% level. RESULTS: The minimum follow-up period was 12 months. The overall success rates (with or without medication) when safe surgery system trabeculectomy was combined with MSICS were 91, 70, and 51% for IOP ≤18, ≤15, and ≤12 mm Hg, respectively, and target IOP was achieved in 72% cases. The mean IOP reduction was 43.8% with MSICS and 42.08% with phacoemulsification. The surgical outcome was not significantly different for both techniques. Postoperative complications were infrequent and comparable. CONCLUSION: The Safe Surgery System Trabeculectomy combined with cataract surgery offers excellent IOP control with minimal postoperative complications. It offers an effective and improved solution for primary glaucoma coexistent with cataract found in developing countries.

Identification of signature and primers specific to genus Pseudomonas using mismatched patterns of 16S rDNA sequences.

BACKGROUND: Pseudomonas, a soil bacterium, has been observed as a dominant genus that survives in different habitats with wide hostile conditions. We had a basic assumption that the species level variation in 16S rDNA sequences of a bacterial genus is mainly due to substitutions rather than insertion or deletion of bases. Keeping this in view, the aim was to identify a region of 16S rDNA sequence and within that focus on substitution prone stretches indicating species level variation and to derive patterns from these stretches that are specific to the genus. RESULTS: Repeating elements that are highly conserved across different species of Pseudomonas were considered as guiding markers to locate a region within the 16S gene. Four repeating patterns showing more than 80% consistency across fifty different species of Pseudomonas were identified. The sub-sequences between the repeating patterns yielded a continuous region of 495 bases. The sub-sequences after alignment and using Shanon's entropy measure yielded a consensus pattern. A stretch of 24 base positions in this region, showing maximum variations across the sampled sequences was focused for possible genus specific patterns. Nine patterns in this stretch showed nearly 70% specificity to the target genus. These patterns were further used to obtain a signature that is highly specific to Pseudomonas. The signature region was used to design PCR primers, which yielded a PCR product of 150 bp whose specificity was validated through a sample experiment. CONCLUSIONS: The developed approach was successfully applied to genus Pseudomonas. It could be tried in other bacterial genera to obtain respective signature patterns and thereby PCR primers, for their rapid tracking in the environmental samples.

Distinguishing features of 16S rDNA gene for five dominating bacterial genus observed in bioremediation.

Defining a microbial community and identifying bacteria, at least at the genus level, is a first step in predicting the behavior of a microbial community in bioremediation. In biological treatment systems, the most dominating groups observed are Pseudomonas, Moraxella, Acinetobactor, Burkholderia, and Alcaligenes. Our interest lies in identifying the distinguishing features of these bacterial groups based on their 16S rDNA sequence data, which could be used further for generating genus-specific probes. Accordingly, 20 sequences representing different species from each genus above were retrieved, which constituted a training set. A 16-dimensional feature vector comprised of transition probabilities of nucleotides was considered and each sampled sequence was expressed in terms of these features. A stepwise feature selection method was used to identify features that are distinct across the species of these five groups. Wilk's lambda selection criterion was used and resulted in a subset with six distinguishing features. The discriminating efficacy of this subset was tested through multiple group discriminant analysis. Two linear composites, as a function of these features, could discriminate the test set of forty-five sequences from these groups with 95% accuracy, thereby ascertaining the relevance of the identified features. The geometric representation of feature correlation in the reduced discriminant space demonstrated the dominance of identified features in specific groups. These features independently or in combination could be used to generate genus-specific patterns to design probes, so as to develop a tracking tool for the selected group of bacteria.

Nosocomial surgical infections: incidence and cost in a developing country.

Eight hundred twenty-nine patients were monitored for nosocomial surgical infections from January to December 1980 at the University Hospital of the West Indies. Two hundred twenty-five patients (27%) had 189 postoperative wound infections (POWI) and 295 other nosocomial infections, with an average of 2.1 infections per infected patient. The incidence of POWI was 22.8%, varying from 7.3% in clean to 82.2% in infected wounds. The most common organisms isolated were gram-negative bacilli and Staphylococcus aureus. The most frequent nosocomial infection other than POWI was urinary tract infection (27.8%). A statistically significant number of urinary tract infections and septicemias were associated with the use of medical devices such as indwelling urethral catheters and central venous pressure lines (p less than 0.001). Septicemia was frequently associated with operations on the lower gastrointestinal and hepatobiliary tracts (p less than 0.001). The postoperative stay of an infected patient was prolonged by an average of 18 days. The total excess cost of hospitalization for the infected patients was U.S. $170,000.

Quantitative structure-activity relationships based on functional and structural characteristics of organic compounds.

In the present quantitative structure-activity relationship (QSAR) modeling, organic compounds, including priority pollutants, have been considered and classified based on their functional and structural characteristics. Five physico-chemical characteristics have been used to develop a QSAR model for Pimephales promelas, by means of multiple regression analysis. Collinearity diagnostics was carried out using two different approaches based on condition index and K correlation index. The outlier analysis was carried out using the variable subsets obtained through both the approaches. An attempt has been made to justify the deletion of outliers in each group referring to their physico-chemical characteristics. The expressions obtained by using both approaches provide almost the same prediction accuracy, however, the latter approach resulted in expressions with reduced number of molecular descriptors. The QSARs obtained through this exercise would certainly assist in designing environment-friendly molecules with lower toxicity.

Self-organizing maps: a tool to ascertain taxonomic relatedness based on features derived from 16S rDNA sequence.

Exploitation of microbial wealth, of which almost 95% or more is still unexplored, is a growing need. The taxonomic placements of a new isolate based on phenotypic characteristics are now being supported by information preserved in the 16S rRNA gene. However, the analysis of 16S rDNA sequences retrieved from metagenome, by the available bioinformatics tools, is subject to limitations. In this study, the occurrences of nucleotide features in 16S rDNA sequences have been used to ascertain the taxonomic placement of organisms. The tetra- and penta-nucleotide features were extracted from the training data set of the 16S rDNA sequence, and was subjected to an artificial neural network (ANN) based tool known as self-organizing map (SOM), which helped in visualization of unsupervised classification. For selection of significant features, principal component analysis (PCA) or curvilinear component analysis (CCA) was applied. The SOM along with these techniques could discriminate the sample sequences with more than 90% accuracy, highlighting the relevance of features. To ascertain the confidence level in the developed classification approach, the test data set was specifically evaluated for Thiobacillus, with Acidiphilium, Paracocus and Starkeya, which are taxonomically reassigned. The evaluation proved the excellent generalization capability of the developed tool. The topology of genera in SOM supported the conventional chemo-biochemical classification reported in the Bergey manual.