Classifying diseases by using biological features to identify potential nosological models.

Established nosological models have provided physicians an adequate enough classification of diseases so far. Such systems are important to correctly identify diseases and treat them successfully. However, these taxonomies tend to be based on phenotypical observations, lacking a molecular or biological foundation. Therefore, there is an urgent need to modernize them in order to include the heterogeneous information that is produced in the present, as could be genomic, proteomic, transcriptomic and metabolic data, leading this way to more comprehensive and robust structures. For that purpose, we have developed an extensive methodology to analyse the possibilities when it comes to generate new nosological models from biological features. Different datasets of diseases have been considered, and distinct features related to diseases, namely genes, proteins, metabolic pathways and genetical variants, have been represented as binary and numerical vectors. From those vectors, diseases distances have been computed on the basis of several metrics. Clustering algorithms have been implemented to group diseases, generating different models, each of them corresponding to the distinct combinations of the previous parameters. They have been evaluated by means of intrinsic metrics, proving that some of them are highly suitable to cover new nosologies. One of the clustering configurations has been deeply analysed, demonstrating its quality and validity in the research context, and further biological interpretations have been made. Such model was particularly generated by OPTICS clustering algorithm, by studying the distance between diseases based on gene sharedness and following cosine index metric. 729 clusters were formed in this model, which obtained a Silhouette coefficient of 0.43.

Leveraging network analysis to evaluate biomedical named entity recognition tools.

The ever-growing availability of biomedical text sources has resulted in a boost in clinical studies based on their exploitation. Biomedical named-entity recognition (bio-NER) techniques have evolved remarkably in recent years and their application in research is increasingly successful. Still, the disparity of tools and the limited available validation resources are barriers preventing a wider diffusion, especially within clinical practice. We here propose the use of omics data and network analysis as an alternative for the assessment of bio-NER tools. Specifically, our method introduces quality criteria based on edge overlap and community detection. The application of these criteria to four bio-NER solutions yielded comparable results to strategies based on annotated corpora, without suffering from their limitations. Our approach can constitute a guide both for the selection of the best bio-NER tool given a specific task, and for the creation and validation of novel approaches.

DisMaNET: A network-based tool to cross map disease vocabularies.

BACKGROUND AND OBJECTIVES: The growing integration of healthcare sources is improving our understanding of diseases. Cross-mapping resources such as UMLS play a very important role in this area, but their coverage is still incomplete. With the aim to facilitate the integration and interoperability of biological, clinical and literary sources in studies of diseases, we built DisMaNET, a system to cross-map terms from disease vocabularies by leveraging the power and interpretability of network analysis. METHODS: First, we collected and normalized data from 8 disease vocabularies and mapping sources to generate our datasets. Next, we built DisMaNET by integrating the generated datasets into a Neo4j graph database. Then we exploited the query mechanisms of Neo4j to cross-map disease terms of different vocabularies with a relevance score metric and contrasted the results with some state-of-the-art solutions. Finally, we made our system publicly available for its exploitation and evaluation both through a graphical user interface and REST APIs. RESULTS: DisMaNET contains almost half a million nodes and near nine hundred thousand edges, including hierarchical and mapping relationships. Its query capabilities enabled the detection of connections between disease vocabularies that are not present in major mapping sources such as UMLS and the Disease Ontology, even for rare diseases. Furthermore, DisMaNET was capable of obtaining more than 80% of the mappings with UMLS reported in MonDO and DisGeNET, and it was successfully exploited to resolve the missing mappings in the DISNET project. CONCLUSIONS: DisMaNET is a powerful, intuitive and publicly available system to cross-map terms from different disease vocabularies. Our study proves that it is a competitive alternative to existing mapping systems, incorporating the potential of network analysis and the interpretability of the results through a visual interface as its main advantages. Expansion with new sources, versioning and the improvement of the search and scoring algorithms are envisioned as future lines of work.

DISNET: a framework for extracting phenotypic disease information from public sources.

BACKGROUND: Within the global endeavour of improving population health, one major challenge is the identification and integration of medical knowledge spread through several information sources. The creation of a comprehensive dataset of diseases and their clinical manifestations based on information from public sources is an interesting approach that allows one not only to complement and merge medical knowledge but also to increase it and thereby to interconnect existing data and analyse and relate diseases to each other. In this paper, we present DISNET (http://disnet.ctb.upm.es/), a web-based system designed to periodically extract the knowledge from signs and symptoms retrieved from medical databases, and to enable the creation of customisable disease networks. METHODS: We here present the main features of the DISNET system. We describe how information on diseases and their phenotypic manifestations is extracted from Wikipedia and PubMed websites; specifically, texts from these sources are processed through a combination of text mining and natural language processing techniques. RESULTS: We further present the validation of our system on Wikipedia and PubMed texts, obtaining the relevant accuracy. The final output includes the creation of a comprehensive symptoms-disease dataset, shared (free access) through the system's API. We finally describe, with some simple use cases, how a user can interact with it and extract information that could be used for subsequent analyses. DISCUSSION: DISNET allows retrieving knowledge about the signs, symptoms and diagnostic tests associated with a disease. It is not limited to a specific category (all the categories that the selected sources of information offer us) and clinical diagnosis terms. It further allows to track the evolution of those terms through time, being thus an opportunity to analyse and observe the progress of human knowledge on diseases. We further discussed the validation of the system, suggesting that it is good enough to be used to extract diseases and diagnostically-relevant terms. At the same time, the evaluation also revealed that improvements could be introduced to enhance the system's reliability.

Disease networks and their contribution to disease understanding: A review of their evolution, techniques and data sources.

Over a decade ago, a new discipline called network medicine emerged as an approach to understand human diseases from a network theory point-of-view. Disease networks proved to be an intuitive and powerful way to reveal hidden connections among apparently unconnected biomedical entities such as diseases, physiological processes, signaling pathways, and genes. One of the fields that has benefited most from this improvement is the identification of new opportunities for the use of old drugs, known as drug repurposing. The importance of drug repurposing lies in the high costs and the prolonged time from target selection to regulatory approval of traditional drug development. In this document we analyze the evolution of disease network concept during the last decade and apply a data science pipeline approach to evaluate their functional units. As a result of this analysis, we obtain a list of the most commonly used functional units and the challenges that remain to be solved. This information can be very valuable for the generation of new prediction models based on disease networks.

Encuesta sobre prácticas de prevención de infecciones asociadas a la broncoscopía en la República Argentina 2014 / Survey about Practices to Prevent Bronchoscopy-Associated Infections in the Republic of Argentina in 2014

Introducción y objetivo: Encuestas nacionales sobre la práctica broncoscópica se han repetido desde hace tres décadas en el mundo. En Argentina la broncoscopía tiene una larga historia, sin embargo, hay poca información disponible sobre esta práctica. El objetivo del estudio es obtener información sobre las características específicas de las prácticas de prevención de infecciones en los procedimientos broncoscópicos. Métodos: En 2014, distribuimos una encuesta para broncoscopistas y asistentes en la reunión anual de neumólogos. Resultados: Se completaron un total de 41 cuestionarios. No recibió capacitación específica en prevención de infecciones el 68%. Es neumonólogo el 85%. Infecciones, pseudoinfeciones o pseudoepidemias asociadas a broncoscopía fueron registradas por el 7%. No refiere haber sufrido un accidente laboral relacionado con la broncoscopía el 87%. Conoce la conducta a adoptar ante un accidente el 80%. Utiliza detergente enzimático para el proceso de limpieza 97%. Reutiliza este detergente 40%. Ortofitalaldehído, glutaraldehído o ambos es empleado como agente de desinfección de alto nivel (DAN) por el 95%. Realiza DAN sobre el broncoscopio siempre el 75%, lo hace a veces 9% y no lo hace el 14%. Realiza DAN o esterilización sobre material reutilizable el 87%. Los accesorios reutilizables (pinzas o cepillos) son esterilizados, reprocesados con DAN o ambas cosas por el 77%; y sometidos sólo a limpieza de nivel medio por el 12%. Emplea “Single Use Device” 78%, de ellos reprocesa este material 84%. Posee procesador automático el 5%. Conclusiones: Se identificaron características específicas locales de prácticas de prevención de infecciones en los procedimientos broncoscópicos.

Background and objective: Nationwide surveys about bronchoscopic practice have been carried out for three decades over the world. In Argentina, bronchoscopy has a long history; however, little information is available about this practice. The aim of this study is to obtain information regarding specific characteristics of practices to prevent in the bronchoscopy-associated infections. Methods: In 2014, we carried out a survey addressed to bronchoscopists and bronchoscopy assistants at the annual meeting of lung specialists. Results: 41 persons were surveyed. 68% did not receive any specific training in infection prevention practices. 85% were pulmonologists. 7% recorded infections, pseudoepidemics or pseudoinfections. 80% knew how to manage bronchoscopy-related accidents. 97% used enzymatic detergents in the cleaning process. 40% knew when to reuse the detergent. 95% used orthophthaldehyde, glutaraldehyde, or both of them as a high level disinfection agent (HLD). 75% used always HLD to clean the bronchoscope while 9% did it sometimes, and 14% never did it. 87% used HLD or sterilization for reusable materials. 77% sterilized reusable accessories (biopsy forceps or brushes), 77% reprocessed them with HLD, and 12% exposed them to mid level cleaning. 78% used a single device. 84% reprocessed the materials. 5% had an automatic processor. Conclusions: Local specific characteristics on the practice to prevent infections in the bronchoscopic procedures were identified.

[Rituximab-induced interstitial lung disease]. / Enfermedad pulmonar intersticial asociada a rituximab.

The introduction of the anti-CD20 antibody rituximab into clinical practice has improved substantially the prognosis of a variety of haematological and autoimmune diseases. The interstitial lung disease is one of most serious and potentially fatal complications of rituximab therapy. This diagnosis should be considered in patients who have received the drug and present with dyspnea, fever and cough without clear evidence of infection. We report a case of rituximab-induced interstitial lung disease.

Enfermedad pulmonar intersticial asociada a rituximab / Rituximab-induced interstitial lung disease

La introducción en la práctica clínica del anticuerpo anti-CD20 rituximab ha mejorado sustancialmente el pronóstico de diversas enfermedades autoinmunes y hematológicas. Con el incremento de su uso ha aumentado el registro de efectos adversos, entre ellos la toxicidad pulmonar. Una de sus complicaciones más serias es la enfermedad pulmonar intersticial, entidad potencialmente fatal que debe ser considerada en pacientes que han recibido rituximab y presentan disnea, fiebre y tos sin clara evidencia de infección. Presentamos un caso de enfermedad pulmonar intersticial asociada a rituximab.(AU)

The introduction of the anti-CD20 antibody rituximab into clinical practice has improved substantially the prognosis of a variety of haematological and autoimmune diseases. The interstitial lung disease is one of most serious and potentially fatal complications of rituximab therapy. This diagnosis should be considered in patients who have received the drug and present with dyspnea, fever and cough without clear evidence of infection. We report a case of rituximab-induced interstitial lung disease.(AU)

Enfermedad pulmonar intersticial asociada a rituximab / Rituximab-induced interstitial lung disease

La introducción en la práctica clínica del anticuerpo anti-CD20 rituximab ha mejorado sustancialmente el pronóstico de diversas enfermedades autoinmunes y hematológicas. Con el incremento de su uso ha aumentado el registro de efectos adversos, entre ellos la toxicidad pulmonar. Una de sus complicaciones más serias es la enfermedad pulmonar intersticial, entidad potencialmente fatal que debe ser considerada en pacientes que han recibido rituximab y presentan disnea, fiebre y tos sin clara evidencia de infección. Presentamos un caso de enfermedad pulmonar intersticial asociada a rituximab.

The introduction of the anti-CD20 antibody rituximab into clinical practice has improved substantially the prognosis of a variety of haematological and autoimmune diseases. The interstitial lung disease is one of most serious and potentially fatal complications of rituximab therapy. This diagnosis should be considered in patients who have received the drug and present with dyspnea, fever and cough without clear evidence of infection. We report a case of rituximab-induced interstitial lung disease.

Enfermedad pulmonar intersticial asociada a rituximab. / [Rituximab-induced interstitial lung disease].

The introduction of the anti-CD20 antibody rituximab into clinical practice has improved substantially the prognosis of a variety of haematological and autoimmune diseases. The interstitial lung disease is one of most serious and potentially fatal complications of rituximab therapy. This diagnosis should be considered in patients who have received the drug and present with dyspnea, fever and cough without clear evidence of infection. We report a case of rituximab-induced interstitial lung disease.

Diferencias entre la tuberculosis pulmonar con baciloscopia positiva y negativa / Differences between smear positive and smear negative pulmonary tuberculosis

En el análisis de 318 pacientes con tuberculosis (TB) pulmonar activa, tratados entre enero de 1980 y diciembre de 1990, en un Hospital General del Gran Buenos Aires, el grupo (n = 48) con baciloscopía negativa (D-) tuvo diferencias clínicas y radiológicas significativas con respecto al grupo (n = 270) con baciioscopía positivia (D+). Estas diferencias fueron la mayor edad, la mayor frecuencia de otras enfermedades pulmonares y de Rx "secuela", con menos antecedentes clínicos y cavidades pulmonares radiológicas. Dos subgrupos se distinguem en el grupo D-, de acuerdo a la iniciación empírica del tratamiento. Por un lado un subgrupo con características similares al grupo D+, lo que facilitó la decisión de comenzarlo aún con la baciloscopía negativa (D-TI). El otro subgrupo tuvo características totalmente diferentes al grupo D+, lo que hizo pensar en otros diagnósticos, difiriendo así la decisión del tratamiento hasta la obtención del cultivo (D-TD). (AU)

Diferencias entre la tuberculosis pulmonar con baciloscopia positiva y negativa / Differences between smear positive and smear negative pulmonary tuberculosis

En el análisis de 318 pacientes con tuberculosis (TB) pulmonar activa, tratados entre enero de 1980 y diciembre de 1990, en un Hospital General del Gran Buenos Aires, el grupo (n = 48) con baciloscopía negativa (D-) tuvo diferencias clínicas y radiológicas significativas con respecto al grupo (n = 270) con baciioscopía positivia (D+). Estas diferencias fueron la mayor edad, la mayor frecuencia de otras enfermedades pulmonares y de Rx "secuela", con menos antecedentes clínicos y cavidades pulmonares radiológicas. Dos subgrupos se distinguem en el grupo D-, de acuerdo a la iniciación empírica del tratamiento. Por un lado un subgrupo con características similares al grupo D+, lo que facilitó la decisión de comenzarlo aún con la baciloscopía negativa (D-TI). El otro subgrupo tuvo características totalmente diferentes al grupo D+, lo que hizo pensar en otros diagnósticos, difiriendo así la decisión del tratamiento hasta la obtención del cultivo (D-TD).