Comparative Study of a Real-Time PCR Assay Targeting senX3-regX3 versus Other Molecular Strategies Commonly Used in the Diagnosis of Tuberculosis.

BACKGROUND Nucleic acid amplification tests are increasingly used for the rapid diagnosis of tuberculosis. We undertook a comparative study of the efficiency and diagnostic yield of a real-time PCR senX3-regX3 based assay versus the classical IS6110 target and the new commercial methods. METHODS This single-blind prospective comparative study included 145 consecutive samples: 76 from patients with culture-confirmed tuberculosis (86.8% pulmonary and 13.2% extrapulmonary tuberculosis: 48.7% smear-positive and 51.3% smear-negative) and 69 control samples (24 from patients diagnosed with non-tuberculous mycobacteria infections and 45 from patients with suspected tuberculosis which was eventually ruled out). All samples were tested by two CE-marked assays (Xpert®MTB/RIF and AnyplexTM plus MTB/NTM) and two in-house assays targeting senX3-regX3 and the IS6110 gene. RESULTS The detection limit ranged from 1.00E+01 fg for Anyplex, senX3-regX3 and IS6110 to 1.00E+04 fg for Xpert. All three Xpert, senX3-regX3 and IS6110 assays detected all 37 smear-positive cases. Conversely, Anyplex was positive in 34 (91.9%) smear-positive cases. In patients with smear-negative tuberculosis, differences were observed between the assays; Xpert detected 22 (56.41%) of the 39 smear-negative samples, Anyplex 24 (61.53%), senX3-regX3 28 (71.79%) and IS6110 35 (89.74%). Xpert and senX3-regX3 were negative in all control samples; however, the false positive rate was 8.7% and 13% for Anyplex and IS6110, respectively. The overall sensitivity was 77.6%, 85.7%, 77.3% and 94.7% and the specificity was 100%, 100%, 90.8% and 87.0% for the Xpert, senX3-regX3, Anyplex and IS6110 assays, respectively. CONCLUSION Real-time PCR assays targeting IS6110 lack the desired specificity. The Xpert MTB/RIF and in-house senX3-regX3 assays are both sensitive and specific for the detection of MTBC in both pulmonary and extrapulmonary samples. Therefore, the real time PCR senX3-regX3 based assay could be a useful and complementary tool in the diagnosis of tuberculosis.

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).

Analysis of factors influencing telephone call response rate in an epidemiological study.

Descriptive epidemiology research involves collecting data from large numbers of subjects. Obtaining these data requires approaches designed to achieve maximum participation or response rates among respondents possessing the desired information. We analyze participation and response rates in a population-based epidemiological study though a telephone survey and identify factors implicated in consenting to participate. Rates found exceeded those reported in the literature and they were higher for afternoon calls than for morning calls. Women and subjects older than 40 years were the most likely to answer the telephone. The study identified geographical differences, with higher RRs in districts in southern Spain that are not considered urbanized. This information may be helpful for designing more efficient community epidemiology projects.