A combined molecular clinical predictor of survival validated with the rtog-0525 cohort

For glioblastoma (GBM), survival classification has primarily relied on clinical criteria, exemplified by the Radiation Therapy Oncology Group (RTOG) recursive partitioning analysis (RPA). We sought to improve tumor classification by combining tumor biomarkers with the clinical RPA data. To accomplish this, we first developed 4 molecular biomarkers derived from gene expression profiling, a glioma CpG island methylator phenotype, a novel MGMT promoter methylation assay, and IDH1 mutations. A molecular predictor (MP) model was created with these 4 biomarkers on a training set of 220 retrospectively collected archival GBMtumors. ThisMPwas further combined with RPA classification to develop a molecular-clinical predictor (MCP). The median survivals for the combined, 4-class MCP were 65 months, 31 months, 13 months, and 9 months, which was significantly improved when compared with the RPA alone. The MCP was then applied to 725 samples from the RTOG-0525 cohort, showing median survival for each risk group of NR, 26 months, 16 months, and 11 months. The MCP was significantly improved over the RPA at outcome prediction in the RTOG 0525 cohort with a 33%increase in explained variation with respect to survival, validating the result obtained in the training set. To illustrate the benefit of the MCP for patient stratification, we examined progression-free survival (PFS) for patients receiving standard-dose temozolomide (SD-TMZ) vs. dose-dense TMZ (DD-TMZ) in RPA and MCP risk groups. A significant difference between DD-TMZ and SD-TMZ was observed in the poorest surviving MCP risk group with a median PFS of 6 months vs. 3 months (p ¼ 0.048, log-rank test). This difference was not seen using the RPA classification alone. In summary, we have developed a combined molecular-clinical predictor that appears to improve outcome prediction when compared with clinical variables alone. This MCP may serve to better identify patients requiring intensive treatments beyond the standard of care.

Consensus document on allergic conjunctivitis (DECA).

Allergic conjunctivitis (AC) is an inflammatory disease of the conjunctiva caused mainly by an IgE-mediated mechanism. It is the most common type of ocular allergy. Despite being the most benign form of conjunctivitis, AC has a considerable effect on patient quality of life, reduces work productivity, and increases health care costs. No consensus has been reached on its classification, diagnosis, or treatment. Consequently, the literature provides little information on its natural history, epidemiological data are scarce, and it is often difficult to ascertain its true morbidity. The main objective of the Consensus Document on Allergic Conjunctivitis (Documento dE Consenso sobre Conjuntivitis Alérgica [DECA]), which was drafted by an expert panel from the Spanish Society of Allergology and Spanish Society of Ophthalmology, was to reach agreement on basic criteria that could prove useful for both specialists and primary care physicians and facilitate the diagnosis, classification, and treatment of AC. This document is the first of its kind to describe and analyze aspects of AC that could make it possible to control symptoms.

Small vascular and Alzheimer disease-related pathologic determinants of dementia in the oldest-old.

The relative contributions of Alzheimer disease (AD) and vascular lesion burden to the occurrence of cognitive decline are more difficult to define in the oldest-old than they are in younger cohorts. To address this issue, we examined 93 prospectively documented autopsy cases from 90 to 103 years with various degrees of AD lesions, lacunes, and microvascular pathology. Cognitive assessment was performed prospectively using the Clinical Dementia Rating scale. Neuropathologic evaluation included the Braak neurofibrillary tangle (NFT) and β-amyloid (Aβ) protein deposition staging and bilateral semiquantitative assessment of vascular lesions. Statistics included regression models and receiver operating characteristic analyses. Braak NFTs, Aβ deposition, and cortical microinfarcts (CMIs) predicted 30% of Clinical Dementia Rating variability and 49% of the presence of dementia. Braak NFT and CMI thresholds yielded 0.82 sensitivity, 0.91 specificity, and 0.84 correct classification rates for dementia. Using these threshold values, we could distinguish 3 groups of demented cases and propose criteria for neuropathologic definition of mixed dementia, pure vascular dementia, and AD in very old age. Braak NFT staging and severity of CMI allow for defining most of demented cases in the oldest-old. Most importantly, single cutoff scores for these variables that could be used in the future to formulate neuropathologic criteria for mixed dementia in this age group were identified.

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment

A novel method for automated classification of epileptiform activity in the human electroencephalogram-based on independent component analysis.

Diagnosis of several neurological disorders is based on the detection of typical pathological patterns in the electroencephalogram (EEG). This is a time-consuming task requiring significant training and experience. Automatic detection of these EEG patterns would greatly assist in quantitative analysis and interpretation. We present a method, which allows automatic detection of epileptiform events and discrimination of them from eye blinks, and is based on features derived using a novel application of independent component analysis. The algorithm was trained and cross validated using seven EEGs with epileptiform activity. For epileptiform events with compensation for eyeblinks, the sensitivity was 65 +/- 22% at a specificity of 86 +/- 7% (mean +/- SD). With feature extraction by PCA or classification of raw data, specificity reduced to 76 and 74%, respectively, for the same sensitivity. On exactly the same data, the commercially available software Reveal had a maximum sensitivity of 30% and concurrent specificity of 77%. Our algorithm performed well at detecting epileptiform events in this preliminary test and offers a flexible tool that is intended to be generalized to the simultaneous classification of many waveforms in the EEG.

Les champignons : essai de classification / par le Dr Paul Vuillemin,...

Collection : Bibliothèque de botanique cryptogamique

Object and Scene Classification: what does a Supervised Approach Provide us?

Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurrences to perform a scene classification (e.g. beach scene, mountain scene). We achieve this by using a supervised learning algorithm able to learn with few images to facilitate the user task. We use a probabilistic model to recognise the objects and further we classify the scene based on their object occurrences. Experimental results are shown and evaluated to prove the validity of our proposal. Object recognition performance is compared to the approaches of He et al. (2004) and Marti et al. (2001) using their own datasets. Furthermore an unsupervised method is implemented in order to evaluate the advantages and disadvantages of our supervised classification approach versus an unsupervised one

Performance of classic electrocardiographic criteria for left ventricular hypertrophy in an African population.

ECG criteria for left ventricular hypertrophy (LVH) have been almost exclusively elaborated and calibrated in white populations. Because several interethnic differences in ECG characteristics have been found, the applicability of these criteria to African individuals remains to be demonstrated. We therefore investigated the performance of classic ECG criteria for LVH detection in an African population. Digitized 12-lead ECG tracings were obtained from 334 African individuals randomly selected from the general population of the Republic of Seychelles (Indian Ocean). Left ventricular mass was calculated with M-mode echocardiography and indexed to body height. LVH was defined by taking the 95th percentile of body height-indexed LVM values in a reference subgroup. In the entire study sample, 16 men and 15 women (prevalence 9.3%) were finally declared to have LVH, of whom 9 were of the reference subgroup. Sensitivity, specificity, accuracy, and positive and negative predictive values for LVH were calculated for 9 classic ECG criteria, and receiver operating characteristic curves were computed. We also generated a new composite time-voltage criterion with stepwise multiple linear regression: weighted time-voltage criterion=(0.2366R(aVL)+0.0551R(V5)+0.0785S(V3)+ 0.2993T(V1))xQRS duration. The Sokolow-Lyon criterion reached the highest sensitivity (61%) and the R(aVL) voltage criterion reached the highest specificity (97%) when evaluated at their traditional partition value. However, at a fixed specificity of 95%, the sensitivity of these 10 criteria ranged from 16% to 32%. Best accuracy was obtained with the R(aVL) voltage criterion and the new composite time-voltage criterion (89% for both). Positive and negative predictive values varied considerably depending on the concomitant presence of 3 clinical risk factors for LVH (hypertension, age >/=50 years, overweight). Median positive and negative predictive values of the 10 ECG criteria were 15% and 95%, respectively, for subjects with none or 1 of these risk factors compared with 63% and 76% for subjects with all of them. In conclusion, the performance of classic ECG criteria for LVH detection was largely disparate and appeared to be lower in this population of East African origin than in white subjects. A newly generated composite time-voltage criterion might provide improved performance. The predictive value of ECG criteria for LVH was considerably enhanced with the integration of information on concomitant clinical risk factors for LVH.

Defining responses to therapy and study outcomes in clinical trials of invasive fungal diseases: Mycoses Study Group and European Organization for Research and Treatment of Cancer consensus criteria.

Invasive fungal diseases (IFDs) have become major causes of morbidity and mortality among highly immunocompromised patients. Authoritative consensus criteria to diagnose IFD have been useful in establishing eligibility criteria for antifungal trials. There is an important need for generation of consensus definitions of outcomes of IFD that will form a standard for evaluating treatment success and failure in clinical trials. Therefore, an expert international panel consisting of the Mycoses Study Group and the European Organization for Research and Treatment of Cancer was convened to propose guidelines for assessing treatment responses in clinical trials of IFDs and for defining study outcomes. Major fungal diseases that are discussed include invasive disease due to Candida species, Aspergillus species and other molds, Cryptococcus neoformans, Histoplasma capsulatum, and Coccidioides immitis. We also discuss potential pitfalls in assessing outcome, such as conflicting clinical, radiological, and/or mycological data and gaps in knowledge.

Els apareguts i el culte de les ànimes del Purgatori (segles XIV-XVII). Estudi i edició de textos catalans

Report for the scientific sojourn carried out at the Institut National d'Histoire de l'Art (INHA), France, from 2010 to 2012. It has focused on the analysis and editing of tales of human apparitions from the other world belonging to the Catalan culture or referring to it. We have studied and edited different versions of the process of Esperança Alegre (Lleida, 1500) and the Peregrinació del Venturós Pelegrí. These medieval works have been preserved in sources of the late sixteenth century or later. We have located a manuscript of the Esperança Alegre's tale, unknown to us at the beginning of this research (Biblioteca Nacional de España, ms. 1701), which differs from the version of ms. Baluze 238 of the Bibliothèque Nationale de France. The scribe of the ms. 1701 adds several paragraphs where considers the case as a diabolical phantasmagoria. About the Venturós Pelegrí, we have tried to establish firm criteria for the classification of many editions from the seventeenth to nineteenth centuries. We have been looking for printed books in the libràries of the world and we have made several requests for photographic reproductions, in order to classify undated editions by comparing woodcuts and other decorative elements. In the legend of Prince Charles of Viana (1421-1461), the appearances of his ghost are accompanied by rumors of his poisoning and of his sanctity. In addition, we have studied the cycles of masses for the souls in Purgatory linked to the hagiographies of St. Amadour and St. Vincent Ferrer, as well as the appearances described in L'Ànima d’Oliver of Francesc Moner, in the Carmelite chronicles of Father John of St. Joseph (1642-1718) and in some folktales collected from the eighteenth to the twentieth century. All this have allowed us to verify the evolution of certain cultural paradigms since the Middle Ages to the present.

Age above 60 years is not a negative predictive factor for combined antiviral therapy with pegylated interferon alpha and ribavirin in hepatitis C patients

Background: Age is frequently discussed as negative host factor to achieve a sustained virological response (SVR) to antiviral hepatitis C therapy. However, elderly patients often show relevant fibrosis or cirrhosis which is a known negative predictive factor, making it difficult to interpret age as an independent predictive factor. Methods: From the framework of the Swiss hepatitis C cohort (SCCS), we collected data from 545 antiviral hepatitis C therapies, including data from 67 hepatitis C patients ≥ 60 y who had been treated with PEG-interferon and ribavirin. We analyzed host factors (age, gender, fibrosis, haemoglobin, depression, earlier hepatitis C treatment), viral factors (genotype, viral load) and treatment course (early virological response, end of treatment response, SVR). Generalised estimating equations (GEE) regression modelling was used for the primary end point (SVR), with age ≥ 60 y and < 60 y as independent variable and gender, presence of cirrhosis, genotype, earlier treatment and viral load as confounders. SVR was analysed in young and elderly patients after matching for these confounders. Additionally, classification tree analysis was done in elderly patients using these confounders. Results: SVR analyzed in 545 patients was 55%. In genotype 1/4, SVR was 42.9% in 259 patients < 60 y and 26.1% in 46 patients ≥ 60 y. In genotype 2/3, SVR was 74.4% in 215 patients < 60 y and 84% in 25 patients ≥ 60 y. However, GEE model showed that age had no influence on achieving SVR (Odds ratio 0.91). Confounders influenced SVR as known from previous studies (cirrhosis, genotype 1/4, previous treatment and viral load >600'000 IE/ml as negative predictive factors). When young and elderly patients were matched (analysis in 59 elderly patients), SVR was not different in these patient groups (54.2% and 55.9%, resp.; p=0.795 in binomial test). The classification tree-derived best criterion for SVR in elderly patients was genotype, with no further criteria relevant for predicting SVR in genotype 2/3. In patients with genotype 1/4, further criteria were presence of cirrhosis and low viral load <600'000 IE/ml in non-cirrhotic patients. Conclusions: Age is not a relevant predictive factor for achieving SVR, when confounders were taken into account. In terms of effectiveness of antiviral therapy, age does not play a major role and should not be regarded as relevant negative predictive factor. Since life expectancy in Switzerland at age 60 is more than 22 y, hepatitis C therapy is reasonable in elderly patients with known relevant fibrosis or cirrhosis, because interferon-based hepatitis C therapy improves survival and reduces carcinogenesis.

HAMAP in 2015: updates to the protein family classification and annotation system.

HAMAP (High-quality Automated and Manual Annotation of Proteins-available at http://hamap.expasy.org/) is a system for the automatic classification and annotation of protein sequences. HAMAP provides annotation of the same quality and detail as UniProtKB/Swiss-Prot, using manually curated profiles for protein sequence family classification and expert curated rules for functional annotation of family members. HAMAP data and tools are made available through our website and as part of the UniRule pipeline of UniProt, providing annotation for millions of unreviewed sequences of UniProtKB/TrEMBL. Here we report on the growth of HAMAP and updates to the HAMAP system since our last report in the NAR Database Issue of 2013. We continue to augment HAMAP with new family profiles and annotation rules as new protein families are characterized and annotated in UniProtKB/Swiss-Prot; the latest version of HAMAP (as of 3 September 2014) contains 1983 family classification profiles and 1998 annotation rules (up from 1780 and 1720). We demonstrate how the complex logic of HAMAP rules allows for precise annotation of individual functional variants within large homologous protein families. We also describe improvements to our web-based tool HAMAP-Scan which simplify the classification and annotation of sequences, and the incorporation of an improved sequence-profile search algorithm.