Discovery of stable and variable differences in the Mycobacterium avium subsp. paratuberculosis type I, II, and III genomes by pan-genome microarray analysis

Mycobacterium avium subsp. paratuberculosis is an important animal pathogen widely disseminated in the environment that has also been associated with Crohn's disease in humans. Three M. avium subsp. paratuberculosis genomotypes are recognized, but genomic differences have not been fully described. To further investigate these potential differences, a 60-mer oligonucleotide microarray (designated the MAPAC array), based on the combined genomes of M. avium subsp. paratuberculosis (strain K-10) and Mycobacterium avium subsp. hominissuis (strain 104), was designed and validated. By use of a test panel of defined M. avium subsp. paratuberculosis strains, the MAPAC array was able to identify a set of large sequence polymorphisms (LSPs) diagnostic for each of the three major M. avium subsp. paratuberculosis types. M. avium subsp. paratuberculosis type II strains contained a smaller genomic complement than M. avium subsp. paratuberculosis type I and M. avium subsp. paratuberculosis type III genomotypes, which included a set of genomic regions also found in M. avium subsp. hominissuis 104. Specific PCRs for genes within LSPs that differentiated M. avium subsp. paratuberculosis types were devised and shown to accurately screen a panel (n = 78) of M. avium subsp. paratuberculosis strains. Analysis of insertion/deletion region INDEL12 showed deletion events causing a reduction in the complement of mycobacterial cell entry genes in M. avium subsp. paratuberculosis type II strains and significantly altering the coding of a major immunologic protein (MPT64) associated with persistence and granuloma formation. Analysis of MAPAC data also identified signal variations in several genomic regions, termed variable genomic islands (vGIs), suggestive of transient duplication/deletion events. vGIs contained significantly low GC% and were immediately flanked by insertion sequences, integrases, or short inverted repeat sequences. Quantitative PCR demonstrated that variation in vGI signals could be associated with colony growth rate and morphology.

Cell Pattern in Adult Human Corneal Endothelium

A review of the current data on the cell density of normal adult human endothelial cells was carried out in order to establish some common parameters appearing in the different considered populations. From the analysis of cell growth patterns, it is inferred that the cell aging rate is similar for each of the different considered populations. Also, the morphology, the cell distribution and the tendency to hexagonallity are studied. The results are consistent with the hypothesis that this phenomenon is analogous with cell behavior in other structures such as dry foams and grains in polycrystalline materials. Therefore, its driving force may be controlled by the surface tension and the mobility of the boundaries.

A Diagnostic Calculator for Detecting Glaucoma on the Basis of Retinal Nerve Fiber Layer, Optic Disc, and Retinal Ganglion Cell Analysis by Optical Coherence Tomography

Purpose: The purpose of this study was to develop and validate a multivariate predictive model to detect glaucoma by using a combination of retinal nerve fiber layer (RNFL), retinal ganglion cell-inner plexiform (GCIPL), and optic disc parameters measured using spectral-domain optical coherence tomography (OCT). Methods: Five hundred eyes from 500 participants and 187 eyes of another 187 participants were included in the study and validation groups, respectively. Patients with glaucoma were classified in five groups based on visual field damage. Sensitivity and specificity of all glaucoma OCT parameters were analyzed. Receiver operating characteristic curves (ROC) and areas under the ROC (AUC) were compared. Three predictive multivariate models (quantitative, qualitative, and combined) that used a combination of the best OCT parameters were constructed. A diagnostic calculator was created using the combined multivariate model. Results: The best AUC parameters were: inferior RNFL, average RNFL, vertical cup/disc ratio, minimal GCIPL, and inferior-temporal GCIPL. Comparisons among the parameters did not show that the GCIPL parameters were better than those of the RNFL in early and advanced glaucoma. The highest AUC was in the combined predictive model (0.937; 95% confidence interval, 0.911–0.957) and was significantly (P = 0.0001) higher than the other isolated parameters considered in early and advanced glaucoma. The validation group displayed similar results to those of the study group. Conclusions: Best GCIPL, RNFL, and optic disc parameters showed a similar ability to detect glaucoma. The combined predictive formula improved the glaucoma detection compared to the best isolated parameters evaluated. The diagnostic calculator obtained good classification from participants in both the study and validation groups.