Triamterene-β-cyclodextrin systems: Preparation,characterization and in vivo evaluation

The purpose of this research was to improve the solubility and therefore dissolution and bioavailability of triamterene, a poorly water soluble diuretic, by complexation with β-cyclodextrin. Triamterene has been reported to show low bioavailability after oral administration, with wide intersubject variation. This study presents the formulation of solid dispersions of triamterene with β-cyclodextrin—by cogrinding, kneading, and coevaporation, using low pH conditions—and their characterizations, evaluation of improvement in dissolution profiles, and in vivo advantage. Phase solubility studies indicated complex with possible stoichiometry of 1∶1 and a stability constant of 167.67M⁻¹. The solid dispersions were characterized by Fourier transform infrared spectroscopy, nuclear magnetic resonance, x-ray diffraction, and differential scanning calorimetry studies. The characterization studies confirmed inclusion of the phenyl ring of triamterene within the nonpolar cavity of β-cyclodextrin in the coevaporate. Remarkable improvement in in vitro drug release profiles in 0.1 N HCl and pH 6.8 phosphate buffer was observed with all dispersions, especially the coevaporate. The coevaporate, when administered orally in rats, also exhibited improved in vivo activity, as measured by net sodium ion excretion, as compared with triamterene powder. Thus, coevaporation of the drug and β-cyclodextrin from acidified alcohol provide the optimum condition for inclusion complexation to give a binary system with remarkable improvement in in vitro drug release profile and in vivo performance.     

Evaluating markers for selecting a patient's treatment

Selecting the best treatment for a patient's disease may be facilitated by evaluating clinical characteristics or biomarker measurements at diagnosis. We consider how to evaluate the potential impact of such measurements on treatment selection algorithms. For example, magnetic resonance neurographic imaging is potentially useful for deciding whether a patient should be treated surgically for Carpal Tunnel Syndrome or should receive less-invasive conservative therapy. We propose a graphical display, the selection impact (SI) curve that shows the population response rate as a function of treatment selection criteria based on the marker. The curve can be useful for choosing a treatment policy that incorporates information on the patient's marker value exceeding a threshold. The SI curve can be estimated using data from a comparative randomized trial conducted in the population as long as treatment assignment in the trial is independent of the predictive marker. Estimating the SI curve is therefore part of a post hoc analysis to determine whether the marker identifies patients that are more likely to benefit from one treatment over another. Nonparametric and parametric estimates of the SI curve are proposed in this article. Asymptotic distribution theory is used to evaluate the relative efficiencies of the estimators. Simulation studies show that inference is straightforward with realistic sample sizes. We illustrate the SI curve and statistical inference for it with data motivated by an ongoing trial of surgery versus conservative therapy for Carpal Tunnel Syndrome.     

Partially supervised learning using an EM-boosting algorithm

Training data in a supervised learning problem consist of the class label and its potential predictors for a set of observations. Constructing effective classifiers from training data is the goal of supervised learning. In biomedical sciences and other scientific applications, class labels may be subject to errors. We consider a setting where there are two classes but observations with labels corresponding to one of the classes may in fact be mislabeled. The application concerns the use of protein mass-spectrometry data to discriminate between serum samples from cancer and noncancer patients. The patients in the training set are classified on the basis of tissue biopsy. Although biopsy is 100% specific in the sense that a tissue that shows itself to have malignant cells is certainly cancer, it is less than 100% sensitive. Reference gold standards that are subject to this special type of misclassification due to imperfect diagnosis certainty arise in many fields. We consider the development of a supervised learning algorithm under these conditions and refer to it as partially supervised learning. Boosting is a supervised learning algorithm geared toward high-dimensional predictor data, such as those generated in protein mass-spectrometry. We propose a modification of the boosting algorithm for partially supervised learning. The proposal is to view the true class membership of the samples that are labeled with the error-prone class label as missing data, and apply an algorithm related to the EM algorithm for minimization of a loss function. To assess the usefulness of the proposed method, we artificially mislabeled a subset of samples and applied the original and EM-modified boosting (EM-Boost) algorithms for comparison. Notable improvements in misclassification rates are observed with EM-Boost.     

Biochemical mechanisms for a possible involvement of the transglutaminase activity in the pathogenesis of the polyglutamine diseases: Minireview article

Summary. Transglutaminases are a family of enzymes which show the common capacity to catalyse the cross-linking of protein substrates. Some members of this family of enzymes are also capable to catalyse other chemical reactions for the cell life. The distribution and the role of these enzymes have been studied in numerous cell types and tissues, but only recently their expression and functions started to be investigated in the Nervous System. One of the main biochemical properties of the Transglutaminase enzymes is to form large protein aggregates that are insoluble in all known protein detergents. Recently, the Transglutaminase activity has been hypothesised to be involved in the pathogenetic mechanisms responsible for the formation of cellular inclusions present in the Corea Major and in other polyglutamine diseases. In this review we describe the biochemical mechanisms by which the Transglutaminases could play a critical role in the physiopathology of the polyglutamine diseases.     

Distribution-free ROC analysis using binary regression techniques

Receiver operating characteristic (ROC) regression methodology is used to identify factors that affect the accuracy of medical diagnostic tests. In this paper, we consider a ROC model for which the ROC curve is a parametric function of covariates but distributions of the diagnostic test results are not specified. Covariates can be either common to all subjects or specific to those with disease. We propose a new estimation procedure based on binary indicators defined by the test result for a diseased subject exceeding various specified quantiles of the distribution of test results from non-diseased subjects with the same covariate values. This procedure is conceptually and computationally simplified relative to existing procedures. Simulation study results indicate that the approach has fairly high statistical efficiency. The new ROC regression methodology is used to evaluate childhood measurements of body mass index as a predictive marker of adult obesity.     

Characterization of Langmuir-Blodgett films of rhodopsin: thermal stability studies.

Two-dimensional close packing of purified bovine rhodopsin, made by the Langmuir-Blodgett technique, was characterized by small angle x-ray scattering and nanogravimetric measurements. The area occupied by a molecule of rhodopsin in the film was approximately 1100 Angstrum2 and the periodicity of the layers resulted in 59 Angstrum. The circular dichroism measurements showed that bleached rhodopsin in Langmuir-Blodgett film had high thermal stability, in fact, reaching a temperature of 150 degrees C without a loss of the secondary structure. Moreover, when the film was made up in the dark, rhodopsin maintained its stability up to at least 200 degrees C and its characteristic absorbance peak at 500 nm up to about 90 degrees C.     

Cloning of an Aeromonas hydrophila type IV pilus biogenesis gene cluster: complementation of pilus assembly functions and characterization of a type IV leader peptidase/N-methyltransferase required for extracellular protein secretion

Aeromonas hydrophila secretes several extracellular proteins that are associated with virulence including an enterotoxin, a protease, and the hole-forming toxin, aerolysin. These degradative enzymes and toxins are exported by a conserved pathway found in many Gram-negative bacteria. In Pseudomonas aeruginosa this export pathway and type IV pilus biogenesis are dependent on the product of the pilD gene. PilD is a bifunctional enzyme that processes components of the extracellular secretory pathway as well as a type IV prepilin. An A. hydrophila genomic library was transferred into a P. aeruginosa pilD mutant that is defective for type IV pilus biogenesis. The A. hydrophila pilD homologue, tapD , was identified by its ability to complement the pilD mutation in P. aeruginosa . Transconjugants containing tapD were sensitive to the type IV pilus-specific phage, PO4. Sequence data revealed that tapD is part of a cluster of genes ( tapABCD ) that are homologous to P. aeruginosa type IV pilus biogenesis genes ( pilABCD ). We showed that TapB and TapC are functionally homologous to P. aeruginosa PilB and PilC, the first such functional complementation of pilus assembly demonstrated between bacteria that express type IV pili. In vitro studies revealed that TapD has both endopeptidase and N -methyltransferase activities using P. aeruginosa prepilin as substrate. Furthermore, we show that tapD is required for extracellular secretion of aerolysin and protease, indicating that tapD may play an important role in the virulence of A. hydrophila     

Behaviour of Listeria monocytogenes during the traditional manufacture of water-buffalo Mozzarella cheese

F. VILLANI, O. PEPE, G. MAURIELLO, G. MOSCHETTI, L. SANNINO AND S. COPPOLA. 1996. The behaviour of a four-strains mixture of Listeria monocytogenes (strains Scott A, V7, OH and Cal) during the traditional manufacture of water-buffalo Mozzarella cheese was investigated at two levels of inoculation: ca 10⁵and 10³cfu ml^-1of vat milk. No significant change in Listeria counts was observed during the curd ripening (4.0–4.5 h), at the end of which the pH ranged between 4.83 and 4.91. A decrease of about 2 log was observed after stretching of the curd in hot water (95°C), followed by complete elimination of Listeria after 48 and 24 h of storage of the final cheese in the conditioning liquid (skim water resulting from the stretching, pH ca 4.0) with initial high and low contamination of the cheese milk respectively. Results also indicated that a 1.7 log reduction of L. monocytogenes could be achieved during the preparation of the natural whey culture utilized as starter in cheesemaking.