Comparative analysis of Achilles tendon healing outcomes after open tenotomy versus percutaneous tenotomy: An experimental study in rats.

There is growing interest in conservative treatment of Achilles tendon rupture. However, the majority of experimental studies of Achilles tendon have been performed by open tenotomy. More appropriate model of conservative treatment of Achilles tendon rupture is required. We performed an experimental study to evaluate whether outcomes differ between open tenotomy and percutaneous tenotomy of the Achilles tendon in rats. The Achilles tendons of 48 rats were transected. The animals were divided into two groups according to surgical technique: open tenotomy or microscopy-assisted percutaneous tenotomy. After 1, 2, and 4 weeks, functional, biomechanical, and histological analyses were performed. Western blot was performed for quantitative molecular analysis at 1 week. The Achilles functional index was superior in the percutaneous tenotomy group, compared with the open tenotomy group, at 1 week. The cross-sectional area was significantly larger in the percutaneous tenotomy group than in the open tenotomy group at 4 weeks. Relative to the native tendons, load to failure and stiffness yielded comparable results at 2 weeks in the percutaneous tenotomy group and at 4 weeks in the open tenotomy group. The histological score was significantly better in the percutaneous tenotomy group than in the open tenotomy group at 1 week. At 1 week, interleukin-1ß expression in the open tenotomy group was higher than in the percutaneous tenotomy group. In summary, Achilles tendon healing was substantially affected by the tenotomy method. We presume that our percutaneous tenotomy method might constitute a useful experimental animal model for conservative treatment of Achilles tendon rupture.

Gene expression databases for kidney epithelial cells.

The 21st century has seen an explosion of new high-throughput data from transcriptomic and proteomic studies. These data are highly relevant to the design and interpretation of modern physiological studies but are not always readily accessible to potential users in user-friendly, searchable formats. Data from our own studies involving transcriptomic and proteomic profiling of renal tubule epithelia have been made available on a variety of online databases. Here, we provide a roadmap to these databases and illustrate how they may be useful in the design and interpretation of physiological studies. The databases can be accessed through http://helixweb.nih.gov/ESBL/Database.

Dynamics of the G protein-coupled vasopressin V2 receptor signaling network revealed by quantitative phosphoproteomics.

G protein-coupled receptors (GPCRs) regulate diverse physiological processes, and many human diseases are due to defects in GPCR signaling. To identify the dynamic response of a signaling network downstream from a prototypical G(s)-coupled GPCR, the vasopressin V2 receptor, we have carried out multireplicate, quantitative phosphoproteomics with iTRAQ labeling at four time points following vasopressin exposure at a physiological concentration in cells isolated from rat kidney. A total of 12,167 phosphopeptides were identified from 2,783 proteins, with 273 changing significantly in abundance with vasopressin. Two-dimensional clustering of phosphopeptide time courses and Gene Ontology terms revealed that ligand binding to the V2 receptor affects more than simply the canonical cyclic adenosine monophosphate-protein kinase A and arrestin pathways under physiological conditions. The regulated proteins included key components of actin cytoskeleton remodeling, cell-cell adhesion, mitogen-activated protein kinase signaling, Wnt/ß-catenin signaling, and apoptosis pathways. These data suggest that vasopressin can regulate an array of cellular functions well beyond its classical role in regulating water and solute transport. These results greatly expand the current view of GPCR signaling in a physiological context and shed new light on potential roles for this signaling network in disorders such as polycystic kidney disease. Finally, we provide an online resource of physiologically regulated phosphorylation sites with dynamic quantitative data (http://helixweb.nih.gov/ESBL/Database/TiPD/index.html).

Comparative analysis of logistic regression and artificial neural network for computer-aided diagnosis of breast masses.

RATIONALE AND OBJECTIVE: To compare logistic regression and artificial neural network for computer-aided diagnosis on breast sonograms. MATERIALS AND METHODS: Ultrasound images of 24 malignant and 30 benign masses were analyzed quantitatively for margin sharpness, margin echogenicity, and angular variation in margin. These features and age of patients were used with two pattern classifiers, logistic regression, and an artificial neural network to differentiate between malignant and benign masses. The performance of two methods was compared by receiver operating characteristic (ROC) analysis. RESULTS: The area under the ROC curve Az (+/-SD) of the logistic regression analysis was 0.853 +/- 0.059 with 95% confidence limit (0.760-0.950). The area under the ROC curve of the artificial neural network analysis was 0.856 +/- 0.058 with 95% confidence limit (0.734-0.936). Although both the logistic regression and the artificial neural network had the same area under the ROC curve, the shapes of two curves were different. At 95% sensitivity, the artificial neural network had 76.5% specificity, whereas logistic regression had 64.7% specificity. CONCLUSION: There was no difference in performance between logistic regression and the artificial neural network as measured by the area under the ROC curve. However, at a fixed 95% sensitivity, the artificial neural network had higher (12%) specificity compared with logistic regression value.