Open partial nephrectomy in renal cancer: a feasible gold standard technique in all hospitals

Introduction. Partial nephrectomy (PN) is playing an increasingly important role in localized renal cell carcinoma (RCC) as a true alternative to radical nephrectomy. With the greater experience and expertise of surgical teams, it has become an alternative to radical nephrectomy in young patients when the tumor diameter is 4 cm or less in almost all hospitals since cancer-specific survival outcomes are similar to those obtained with radical nephrectomy. Materials and Methods. The authors comment on their own experience and review the literature, reporting current indications and outcomes including complications. The surgical technique of open partial nephrectomy is outlined. Conclusions. Nowadays, open PN is the gold standard technique to treat small renal masses, and all nonablative techniques must pass the test of time to be compared to PN. It is not ethical for patients to undergo radical surgery just because the urologists involved do not have adequate experience with PN. Patients should be involved in the final treatment decision and, when appropriate, referred to specialized centers with experience in open or laparoscopic partial nephrectomies

Use of unmodified starches and partial removal of serum to improve Granada medium stability

The use of 1% unmodified rice starch and 1% horse serum instead of 2% soluble starch and 5% serum in Granada medium is described. These components result in a medium of increased stability, preventing spoilage after a few days of storage at room temperature

A novel study of copy number variations in Hirschsprung disease using the multiple ligation-dependent probe amplification (MLPA) technique.

BACKGROUND Hirschsprung disease (HSCR) is a congenital malformation of the hindgut produced by a disruption in neural crest cell migration during embryonic development. HSCR has a complex genetic etiology and mutations in several genes, mainly the RET proto-oncogene, have been related to the disease. There is a clear predominance of missense/nonsense mutations in these genes whereas copy number variations (CNVs) have been seldom described, probably due to the limitations of conventional techniques usually employed for mutational analysis. METHODS In this study we have aimed to analyze the presence of CNVs in some HSCR genes (RET, EDN3, GDNF and ZFHX1B) using the Multiple Ligation-dependent Probe Amplification (MLPA) approach. RESULTS Two alterations in the MLPA profiles of RET and EDN3 were detected, but a detailed inspection showed that the decrease in the corresponding dosages were due to point mutations affecting the hybridization probes regions. CONCLUSION Our results indicate that CNVs of the gene coding regions analyzed here are not a common molecular cause of Hirschsprung disease. However, further studies are required to determine the presence of CNVs affecting non-coding regulatory regions, as well as other candidate genes.

Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

Scimitar Syndrome in an Asymptomatic Adult: Fortuitous Diagnosis by Imaging Technique

Congenital cardiopathies in adults are a rare clinical entity in the cardiology consultations. Advances in imaging techniques allow the fortuitous diagnosis of mild forms of these congenital abnormalities. We describe a case of an asymptomatic 41-year-old man, with a medical history of recurrent pneumonia during childhood and an established diagnosis of scimitar syndrome by computed tomography.