Ulcerative colitis impairs the acylethanolamide-based anti-inflammatory system reversal by 5-aminosalicylic acid and glucocorticoids

Studies in animal models and humans suggest anti-inflammatory roles on the N acylethanolamide (NAE)-peroxisome proliferators activated receptor alpha (PPARα) system in inflammatory bowel diseases. However, the presence and function of NAE-PPARα signaling system in the ulcerative colitis (UC) of humans remain unknown as well as its response to active anti-inflammatory therapies such as 5-aminosalicylic acid (5-ASA) and glucocorticoids. Expression of PPARα receptor and PPARα ligands-biosynthetic (NAPE-PLD) and -degrading (FAAH and NAAA) enzymes were analyzed in untreated active and 5-ASA/glucocorticoids/immunomodulators-treated quiescent UC patients compared to healthy human colonic tissue by RT-PCR and immunohistochemical analyses. PPARα, NAAA, NAPE-PLD and FAAH showed differential distributions in the colonic epithelium, lamina propria, smooth muscle and enteric plexus. Gene expression analysis indicated a decrease of PPARα, PPARγ and NAAA, and an increase of FAAH and iNOS in the active colitis mucosa. Immunohistochemical expression in active colitis epithelium confirmed a PPARα decrease, but showed a sharp NAAA increase and a NAPE-PLD decrease, which were partially restored to control levels after treatment. We also characterized the immune cells of the UC mucosa infiltrate. We detected a decreased number of NAAA-positive and an increased number of FAAH-positive immune cells in active UC, which were partially restored to control levels after treatment. NAE-PPARα signaling system is impaired during active UC and 5-ASA/glucocorticoids treatment restored its normal expression. Since 5-ASA actions may work through PPARα and glucocorticoids through NAE-producing/degrading enzymes, the use of PPARα agonists or FAAH/NAAA blockers that increases endogenous PPARα ligands may yield similar therapeutics advantages.

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).

Meta-analysis of studies analyzing the role of human papillomavirus in the development of bladder carcinoma

PURPOSE We aimed to ascertain the degree of association between bladder cancer and human papillomavirus (HPV) infection. MATERIALS AND METHODS We performed a meta-analysis of observational studies with cases and controls with publication dates up to January 2011. The PubMed electronic database was searched by using the key words "bladder cancer and virus." Twenty-one articles were selected that met the required methodological criteria. We implemented an internal quality control system to verify the selected search method. We analyzed the pooled effect of all the studies and also analyzed the techniques used as follows: 1) studies with DNA-based techniques, among which we found studies with polymerase chain reaction (PCR)-based techniques and 2) studies with non-PCR-based techniques, and studies with non-DNA-based techniques. RESULTS Taking into account the 21 studies that were included in the meta-analysis, we obtained a heterogeneity chi-squared value of Q(exp)=26.45 (p=0.383). The pooled odds ratio (OR) was 2.13 (95% confidence interval [CI], 1.54 to 2.95), which points to a significant effect between HPV and bladder cancer. Twenty studies assessed the presence of DNA. The overall effect showed a significant relationship between virus presence and bladder cancer, with a pooled OR of 2.19 (95% CI, 1.40 to 3.43). Of the other six studies, four examined the virus's capsid antigen and two detected antibodies in serum by Western blot. The estimated pooled OR in this group was 2.11 (95% CI, 1.27 to 3.51), which confirmed the relationship between the presence of virus and cancer. CONCLUSIONS The pooled OR value showed a moderate relationship between viral infection and bladder tumors.