Sensitivity and specificity of the electrocardiogram to detect chronic myocardial infarction of the anteroseptal wall.

L`electrocardiograma és la primera eina diagnòstica fàcilment disponible per la detecció de l´infart a la práctica clínica. El seu valor va ser donat principalment amb estudis antics anatomopatològics. La ressonància magnètica cardíaca actualment és la tècnica d`elecció per la detecció de l`infart. Aquest estudi investiga el valor de l`electrocardiograma ( sensibilitat i especificitat) per detectar infarts de la zona anteroseptal. Conclusiò: la sensibilitat y la especificitat de quatre patents electrocardiogràfiques de la zona anteroseptal va ser valorada. Així mateix, encara que s`observin extenses ones Q en les derivacions anteriors la necrosis és usualment limitada si VL no está afectat. 3

The hardness profile as a tool to detect spurious stationary points in the potential energy surface

The energy and hardness profile for a series of inter and intramolecular conformational changes at several levels of calculation were computed. The hardness profiles were found to be calculated as the difference between the vertical ionization potential and electron affinity. The hardness profile shows the correct number of stationary points independently of the basis set and methodology used. It was found that the hardness profiles can be used to check the reliability of the energy profiles for those chemical system

Probe-specific mixed-model approach to detect copy number differences using multiplex ligation-dependent probe amplification (MLPA)

Background: MLPA method is a potentially useful semi-quantitative method to detect copy number alterations in targeted regions. In this paper, we propose a method for the normalization procedure based on a non-linear mixed-model, as well as a new approach for determining the statistical significance of altered probes based on linear mixed-model. This method establishes a threshold by using different tolerance intervals that accommodates the specific random error variability observed in each test sample.Results: Through simulation studies we have shown that our proposed method outperforms two existing methods that are based on simple threshold rules or iterative regression. We have illustrated the method using a controlled MLPA assay in which targeted regions are variable in copy number in individuals suffering from different disorders such as Prader-Willi, DiGeorge or Autism showing the best performace.Conclusion: Using the proposed mixed-model, we are able to determine thresholds to decide whether a region is altered. These threholds are specific for each individual, incorporating experimental variability, resulting in improved sensitivity and specificity as the examples with real data have revealed.

Analcime crystallization and compositional profiles - Comparing approaches to detect post-depositional alterations in archaeological pottery

The approaches of comparative studies and profile measurements, often used in order to detect post-depositional alterations of ceramics, have been applied simultaneously to two sets of Roman pottery, both of which include altered individuals. As analytical techniques, Neutron Activation Analysis and X-Ray Diffraction have been used. Both approaches lead to substantially different results. This shows that they detect different levels of alteration and should complement each other rather than being used exclusively. For the special process of a glassy phase decomposition followed by a crystallization of the Na-zeolite analcime, the results suggest that it changes high-fired calcareous pottery rapidly, and so fundamentally that the results of various archaeometric techniques can be severely disturbed.

Generation of biological association networks: A novel strategy to detect new targets in cancer therapy

The aim of this work was to design a novel strategy to detect new targets for anticancer treatments. The rationale was to build Biological Association Networks from differentially expressed genes in drug-resistant cells to identify important nodes within the Networks. These nodes may represent putative targets to attack in cancer therapy, as a way to destabilize the gene network developed by the resistant cells to escape from the drug pressure. As a model we used cells resistant to methotrexate (MTX), an inhibitor of DHFR. Selected node-genes were analyzed at the transcriptional level and from a genotypic point of view. In colon cancer cells, DHFR, the AKR1 family, PKC¿, S100A4, DKK1, and CAV1 were overexpressed while E-cadherin was lost. In breast cancer cells, the UGT1A family was overexpressed, whereas EEF1A1 was overexpressed in pancreatic cells. Interference RNAs directed against these targets sensitized cells towards MTX.

FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals

We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR) with Model-Based MDR (MB-MDR). We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits. When comparing FAM-MDR with Pedigree-based Generalized MDR (PGMDR), which is a generalization of Multifactor Dimensionality Reduction (MDR) to continuous traits and related individuals, FAM-MDR was found to outperform PGMDR in terms of power, in most of the considered simulated scenarios. Additional simulations revealed that PGMDR does not appropriately deal with multiple testing and consequently gives rise to overly optimistic results. FAM-MDR adequately deals with multiple testing in epistasis screens and is in contrast rather conservative, by construction. Furthermore, simulations show that correcting for lower order (main) effects is of utmost importance when claiming epistasis. As Type 2 Diabetes Mellitus (T2DM) is a complex phenotype likely influenced by gene-gene interactions, we applied FAM-MDR to examine data on glucose area-under-the-curve (GAUC), an endophenotype of T2DM for which multiple independent genetic associations have been observed, in the Amish Family Diabetes Study (AFDS). This application reveals that FAM-MDR makes more efficient use of the available data than PGMDR and can deal with multi-generational pedigrees more easily. In conclusion, we have validated FAM-MDR and compared it to PGMDR, the current state-of-the-art MDR method for family data, using both simulations and a practical dataset. FAM-MDR is found to outperform PGMDR in that it handles the multiple testing issue more correctly, has increased power, and efficiently uses all available information.

Application of Multi-SNP Approaches Bayesian LASSO and AUC-RF to Detect Main Effects of Inflammatory-Gene Variants Associated with Bladder Cancer Risk

The relationship between inflammation and cancer is well established in several tumor types, including bladder cancer. We performed an association study between 886 inflammatory-gene variants and bladder cancer risk in 1,047 cases and 988 controls from the Spanish Bladder Cancer (SBC)/EPICURO Study. A preliminary exploration with the widely used univariate logistic regression approach did not identify any significant SNP after correcting for multiple testing. We further applied two more comprehensive methods to capture the complexity of bladder cancer genetic susceptibility: Bayesian Threshold LASSO (BTL), a regularized regression method, and AUC-Random Forest, a machine-learning algorithm. Both approaches explore the joint effect of markers. BTL analysis identified a signature of 37 SNPs in 34 genes showing an association with bladder cancer. AUC-RF detected an optimal predictive subset of 56 SNPs. 13 SNPs were identified by both methods in the total population. Using resources from the Texas Bladder Cancer study we were able to replicate 30% of the SNPs assessed. The associations between inflammatory SNPs and bladder cancer were reexamined among non-smokers to eliminate the effect of tobacco, one of the strongest and most prevalent environmental risk factor for this tumor. A 9 SNP-signature was detected by BTL. Here we report, for the first time, a set of SNP in inflammatory genes jointly associated with bladder cancer risk. These results highlight the importance of the complex structure of genetic susceptibility associated with cancer risk.

Definition of linear color models in the RGB vector color space to detect red peaches in orchard images taken under natural illumination

This work proposes the detection of red peaches in orchard images based on the definition of different linear color models in the RGB vector color space. The classification and segmentation of the pixels of the image is then performed by comparing the color distance from each pixel to the different previously defined linear color models. The methodology proposed has been tested with images obtained in a real orchard under natural light. The peach variety in the orchard was the paraguayo (Prunus persica var. platycarpa) peach with red skin. The segmentation results showed that the area of the red peaches in the images was detected with an average error of 11.6%; 19.7% in the case of bright illumination; 8.2% in the case of low illumination; 8.6% for occlusion up to 33%; 12.2% in the case of occlusion between 34 and 66%; and 23% for occlusion above 66%. Finally, a methodology was proposed to estimate the diameter of the fruits based on an ellipsoidal fitting. A first diameter was obtained by using all the contour pixels and a second diameter was obtained by rejecting some pixels of the contour. This approach enables a rough estimate of the fruit occlusion percentage range by comparing the two diameter estimates.

Using transient elastography to detect chronic liver diseases in a primary care nurse consultancy

Background: Chronic liver diseases (CLDs) are significant causes of death in adults in many countries and are usually diagnosed at late stages. Early detection may allow time for treatment to prevent disease progression. Objectives: The aim of this study was to assess the feasibility of screening for unrecognized CLDs in a primary care nurse consultancy and report findings from screening. Methods: Two experienced nurses in a primary care nurse consultancy were trained to perform transient elastography (TE). Subjects aged from 18 to 70 years were identified randomly from the health registry and invited to participate in a feasibility pilot study. Exclusion criteria were past or current history of liver diseases. Nurses collected demographic and clinical data and performed TE tests using Fibroscan tomeasure liver stiffness; a cutoff score of 6.8 kPa or greater was used as an indicator of the presence of CLD with fibrosis. Results: Accurate measurements were obtained in 495 of 502 participants (98.6%). Prevalence of elevated liver stiffness was observed in 28 of 495 subjects (5.7%). Compared to patients with normal liver stiffness, patients with increased liver stiffness were older, were more frequently male, and had higher frequency of metabolic syndrome. Nonalcoholic fatty liver was the most common cause of CLD. Discussion: Following training in procedures for conducting TE, nurses in a primary care clinic were able to detect unrecognized CLDs in presumably healthy subjects. Early detection of CLDs is feasible in primary care clinics and may facilitate identification of undiagnosed CLD in adults.