Dysfunctional 3D model based on structural and neuropsychological information

Acquired brain injury (ABI) 1-2 refers to any brain damage occurring after birth. It usually causes certain damage to portions of the brain. ABI may result in a significant impairment of an individuals physical, cognitive and/or psychosocial functioning. The main causes are traumatic brain injury (TBI), cerebrovascular accident (CVA) and brain tumors. The main consequence of ABI is a dramatic change in the individuals daily life. This change involves a disruption of the family, a loss of future income capacity and an increase of lifetime cost. One of the main challenges in neurorehabilitation is to obtain a dysfunctional profile of each patient in order to personalize the treatment. This paper proposes a system to generate a patient s dysfunctional profile by integrating theoretical, structural and neuropsychological information on a 3D brain imaging-based model. The main goal of this dysfunctional profile is to help therapists design the most suitable treatment for each patient. At the same time, the results obtained are a source of clinical evidence to improve the accuracy and quality of our rehabilitation system. Figure 1 shows the diagram of the system. This system is composed of four main modules: image-based extraction of parameters, theoretical modeling, classification and co-registration and visualization module.

A machine learning approach to identify clinical trials involving nanodrugs and nanodevices from ClinicalTrials.gov

BACKGROUND: Clinical Trials (CTs) are essential for bridging the gap between experimental research on new drugs and their clinical application. Just like CTs for traditional drugs and biologics have helped accelerate the translation of biomedical findings into medical practice, CTs for nanodrugs and nanodevices could advance novel nanomaterials as agents for diagnosis and therapy. Although there is publicly available information about nanomedicine-related CTs, the online archiving of this information is carried out without adhering to criteria that discriminate between studies involving nanomaterials or nanotechnology-based processes (nano), and CTs that do not involve nanotechnology (non-nano). Finding out whether nanodrugs and nanodevices were involved in a study from CT summaries alone is a challenging task. At the time of writing, CTs archived in the well-known online registry ClinicalTrials.gov are not easily told apart as to whether they are nano or non-nano CTs-even when performed by domain experts, due to the lack of both a common definition for nanotechnology and of standards for reporting nanomedical experiments and results. METHODS: We propose a supervised learning approach for classifying CT summaries from ClinicalTrials.gov according to whether they fall into the nano or the non-nano categories. Our method involves several stages: i) extraction and manual annotation of CTs as nano vs. non-nano, ii) pre-processing and automatic classification, and iii) performance evaluation using several state-of-the-art classifiers under different transformations of the original dataset. RESULTS AND CONCLUSIONS: The performance of the best automated classifier closely matches that of experts (AUC over 0.95), suggesting that it is feasible to automatically detect the presence of nanotechnology products in CT summaries with a high degree of accuracy. This can significantly speed up the process of finding whether reports on ClinicalTrials.gov might be relevant to a particular nanoparticle or nanodevice, which is essential to discover any precedents for nanotoxicity events or advantages for targeted drug therapy.

Nanoinformatics approaches for information extraction and text mining in nanomedical research texts

La nanotecnología es un área de investigación de reciente creación que trata con la manipulación y el control de la materia con dimensiones comprendidas entre 1 y 100 nanómetros. A escala nanométrica, los materiales exhiben fenómenos físicos, químicos y biológicos singulares, muy distintos a los que manifiestan a escala convencional. En medicina, los compuestos miniaturizados a nanoescala y los materiales nanoestructurados ofrecen una mayor eficacia con respecto a las formulaciones químicas tradicionales, así como una mejora en la focalización del medicamento hacia la diana terapéutica, revelando así nuevas propiedades diagnósticas y terapéuticas. A su vez, la complejidad de la información a nivel nano es mucho mayor que en los niveles biológicos convencionales (desde el nivel de población hasta el nivel de célula) y, por tanto, cualquier flujo de trabajo en nanomedicina requiere, de forma inherente, estrategias de gestión de información avanzadas. Desafortunadamente, la informática biomédica todavía no ha proporcionado el marco de trabajo que permita lidiar con estos retos de la información a nivel nano, ni ha adaptado sus métodos y herramientas a este nuevo campo de investigación. En este contexto, la nueva área de la nanoinformática pretende detectar y establecer los vínculos existentes entre la medicina, la nanotecnología y la informática, fomentando así la aplicación de métodos computacionales para resolver las cuestiones y problemas que surgen con la información en la amplia intersección entre la biomedicina y la nanotecnología. Las observaciones expuestas previamente determinan el contexto de esta tesis doctoral, la cual se centra en analizar el dominio de la nanomedicina en profundidad, así como en el desarrollo de estrategias y herramientas para establecer correspondencias entre las distintas disciplinas, fuentes de datos, recursos computacionales y técnicas orientadas a la extracción de información y la minería de textos, con el objetivo final de hacer uso de los datos nanomédicos disponibles. El autor analiza, a través de casos reales, alguna de las tareas de investigación en nanomedicina que requieren o que pueden beneficiarse del uso de métodos y herramientas nanoinformáticas, ilustrando de esta forma los inconvenientes y limitaciones actuales de los enfoques de informática biomédica a la hora de tratar con datos pertenecientes al dominio nanomédico. Se discuten tres escenarios diferentes como ejemplos de actividades que los investigadores realizan mientras llevan a cabo su investigación, comparando los contextos biomédico y nanomédico: i) búsqueda en la Web de fuentes de datos y recursos computacionales que den soporte a su investigación; ii) búsqueda en la literatura científica de resultados experimentales y publicaciones relacionadas con su investigación; iii) búsqueda en registros de ensayos clínicos de resultados clínicos relacionados con su investigación. El desarrollo de estas actividades requiere el uso de herramientas y servicios informáticos, como exploradores Web, bases de datos de referencias bibliográficas indexando la literatura biomédica y registros online de ensayos clínicos, respectivamente. Para cada escenario, este documento proporciona un análisis detallado de los posibles obstáculos que pueden dificultar el desarrollo y el resultado de las diferentes tareas de investigación en cada uno de los dos campos citados (biomedicina y nanomedicina), poniendo especial énfasis en los retos existentes en la investigación nanomédica, campo en el que se han detectado las mayores dificultades. El autor ilustra cómo la aplicación de metodologías provenientes de la informática biomédica a estos escenarios resulta efectiva en el dominio biomédico, mientras que dichas metodologías presentan serias limitaciones cuando son aplicadas al contexto nanomédico. Para abordar dichas limitaciones, el autor propone un enfoque nanoinformático, original, diseñado específicamente para tratar con las características especiales que la información presenta a nivel nano. El enfoque consiste en un análisis en profundidad de la literatura científica y de los registros de ensayos clínicos disponibles para extraer información relevante sobre experimentos y resultados en nanomedicina —patrones textuales, vocabulario en común, descriptores de experimentos, parámetros de caracterización, etc.—, seguido del desarrollo de mecanismos para estructurar y analizar dicha información automáticamente. Este análisis concluye con la generación de un modelo de datos de referencia (gold standard) —un conjunto de datos de entrenamiento y de test anotados manualmente—, el cual ha sido aplicado a la clasificación de registros de ensayos clínicos, permitiendo distinguir automáticamente los estudios centrados en nanodrogas y nanodispositivos de aquellos enfocados a testear productos farmacéuticos tradicionales. El presente trabajo pretende proporcionar los métodos necesarios para organizar, depurar, filtrar y validar parte de los datos nanomédicos existentes en la actualidad a una escala adecuada para la toma de decisiones. Análisis similares para otras tareas de investigación en nanomedicina ayudarían a detectar qué recursos nanoinformáticos se requieren para cumplir los objetivos actuales en el área, así como a generar conjunto de datos de referencia, estructurados y densos en información, a partir de literatura y otros fuentes no estructuradas para poder aplicar nuevos algoritmos e inferir nueva información de valor para la investigación en nanomedicina. ABSTRACT Nanotechnology is a research area of recent development that deals with the manipulation and control of matter with dimensions ranging from 1 to 100 nanometers. At the nanoscale, materials exhibit singular physical, chemical and biological phenomena, very different from those manifested at the conventional scale. In medicine, nanosized compounds and nanostructured materials offer improved drug targeting and efficacy with respect to traditional formulations, and reveal novel diagnostic and therapeutic properties. Nevertheless, the complexity of information at the nano level is much higher than the complexity at the conventional biological levels (from populations to the cell). Thus, any nanomedical research workflow inherently demands advanced information management. Unfortunately, Biomedical Informatics (BMI) has not yet provided the necessary framework to deal with such information challenges, nor adapted its methods and tools to the new research field. In this context, the novel area of nanoinformatics aims to build new bridges between medicine, nanotechnology and informatics, allowing the application of computational methods to solve informational issues at the wide intersection between biomedicine and nanotechnology. The above observations determine the context of this doctoral dissertation, which is focused on analyzing the nanomedical domain in-depth, and developing nanoinformatics strategies and tools to map across disciplines, data sources, computational resources, and information extraction and text mining techniques, for leveraging available nanomedical data. The author analyzes, through real-life case studies, some research tasks in nanomedicine that would require or could benefit from the use of nanoinformatics methods and tools, illustrating present drawbacks and limitations of BMI approaches to deal with data belonging to the nanomedical domain. Three different scenarios, comparing both the biomedical and nanomedical contexts, are discussed as examples of activities that researchers would perform while conducting their research: i) searching over the Web for data sources and computational resources supporting their research; ii) searching the literature for experimental results and publications related to their research, and iii) searching clinical trial registries for clinical results related to their research. The development of these activities will depend on the use of informatics tools and services, such as web browsers, databases of citations and abstracts indexing the biomedical literature, and web-based clinical trial registries, respectively. For each scenario, this document provides a detailed analysis of the potential information barriers that could hamper the successful development of the different research tasks in both fields (biomedicine and nanomedicine), emphasizing the existing challenges for nanomedical research —where the major barriers have been found. The author illustrates how the application of BMI methodologies to these scenarios can be proven successful in the biomedical domain, whilst these methodologies present severe limitations when applied to the nanomedical context. To address such limitations, the author proposes an original nanoinformatics approach specifically designed to deal with the special characteristics of information at the nano level. This approach consists of an in-depth analysis of the scientific literature and available clinical trial registries to extract relevant information about experiments and results in nanomedicine —textual patterns, common vocabulary, experiment descriptors, characterization parameters, etc.—, followed by the development of mechanisms to automatically structure and analyze this information. This analysis resulted in the generation of a gold standard —a manually annotated training or reference set—, which was applied to the automatic classification of clinical trial summaries, distinguishing studies focused on nanodrugs and nanodevices from those aimed at testing traditional pharmaceuticals. The present work aims to provide the necessary methods for organizing, curating and validating existing nanomedical data on a scale suitable for decision-making. Similar analysis for different nanomedical research tasks would help to detect which nanoinformatics resources are required to meet current goals in the field, as well as to generate densely populated and machine-interpretable reference datasets from the literature and other unstructured sources for further testing novel algorithms and inferring new valuable information for nanomedicine.

GRADE Evidence to Decision (EtD) frameworks : a systematic and transparent approach to making well informed healthcare choices. 2: Clinical practice guidelines

Funding: Work on this article has been partially funded by the European Commission FP7 Program (grant agreement 258583) as part of the DECIDE project. Sole responsibility lies with the authors; the European Commission is not responsible for any use that may be made of the information contained therein.

Using epidemiological data to guide clinical practice: review of studies on cardiovascular disease and use of combined oral contraceptives

Objective: To explore the usefulness of epidemiological data to guide clinical practice by seeking an answer to the question “What is the risk of cardiovascular disease among users of currently available, low dose, combined oral contraceptives who are aged less than 35 years, do not smoke, and do not have a medical condition known to increase the risk of vascular disease?”

Structuring the pre-search reference interview: a useful technique for handling clinical questions*

Objectives: To explore whether structuring a literature search request form according to an evidence-based medicine (EBM) anatomy elicits more information, improves precision of search results, and is acceptable to participating librarians.

Information needs of rural health professionals: a review of the literature

This review analyzes the existing research on the information needs of rural health professionals and relates it to the broader information-needs literature to establish whether the information needs of rural health professionals differ from those of other health professionals. The analysis of these studies indicates that rural health practitioners appear to have the same basic needs for patient-care information as their urban counterparts, and that both groups rely on colleagues and personal libraries as their main sources of information. Rural practitioners, however, tend to make less use of journals and online databases and ask fewer clinical questions; a difference that correlates with geographic and demographic factors. Rural practitioners experience pronounced barriers to information access including lack of time, isolation, inadequate library access, lack of equipment, lack of skills, costs, and inadequate Internet infrastructure. Outreach efforts to this group of underserved health professionals must be sustained to achieve equity in information access and to change information-seeking behaviors.

Trauma Treatment in Forensic Settings: Clinicians' Perspectives, Barriers to Effective Treatment, and Suggestions for Clinical Practice

Between 30% and 90% of the prison population is estimated to have survived traumatic experiences such as sexual, emotional, and physical abuse prior to incarceration (Anonymous, 1999; Fondacaro, Holt, & Powell, 1999; Messina & Grella, 2006; Pollard & Baker, 2000; Veysey, De Cou, & Prescott, 1998). Similarly, information from the Bureau of Justice Statistics (as reported in Warren, 2001) estimated that more than half of the women in state prisons have experienced past physical and sexual abuse. Thus, given the astonishing number of inmates who appear to be victims of some kind of trauma, it seems likely that those who work with these inmates (e.g., prison staff, guards, and treatment providers) will in some way encounter challenges related to the inmates' trauma history. These difficulties may appear in any number of forms including inmates' behavioral outbursts, increased emotionality, sensitivity to triggering situations, and chronic physical or mental health needs (Veysey, et al., 1998). It is also likely that these individuals with trauma histories would benefit greatly from treatment while incarcerated. This treatment could be utilized to minimize symptoms of posttraumatic stress, decrease behavioral problems, and help the inmate function more effectively in society when released from incarceration (Kokorowski & Freng, 2001; Tucker, Cosio, Meshreki, 2003). Few studies have explored the types of trauma treatment that are effective with inmate populations or made specific suggestions for clinicians working in forensic settings (Kokorowski & Freng, 2001). Essentially, there appears to be a large gap in terms of the need for trauma treatment for inmates and the lack of literature addressing what to do about it. However, clinicians across the country seem to be quietly attempting to fulfill this need for trauma treatment with incarcerated populations. They are providing this greatly needed treatment every day. in the face of enormous challenges and often without recognition or the opportunity to share their valuable work with the larger community.

Gender analysis of moxifloxacin clinical trials

Purpose: To determine the inclusion of women and the sex-stratification of results in moxifloxacin Clinical Trials (CTs), and to establish whether these CTs considered issues that specifically affect women, such as pregnancy and use of hormonal therapies. Previous publications about women’s inclusion in CTs have not specifically studied therapeutic drugs. Although this type of drug is taken by men and women at a similar rate, adverse effects occur more frequently in the latter. Methods: We reviewed 158 published moxifloxacin trials on humans, retrieved from MedLine and the Cochrane Library (1998–2010), to determine whether they complied with the gender recommendations published by U.S. Food and Drug Administration Guideline. Results: Of a total of 80,417 subjects included in the moxifloxacin CTs, only 33.7% were women in phase I, in contrast to phase II, where women accounted for 45%, phase III, where they represented 38.3% and phase IV, where 51.3% were women. About 40.9% (n = 52) of trials were stratified by sex and 15.3% (n = 13) and 9% (n = 7) provided data by sex on efficacy and adverse effects, respectively. We found little information about the influence of issues that specifically affect women. Only 3 of the 59 journals that published the moxifloxacin CTs stated that authors should stratify their results by sex. Conclusions: Women are under-represented in the published moxifloxacin trials, and this trend is more marked in phase I, as they comprise a higher proportion in the other phases. Data by sex on efficacy and adverse effects are scarce in moxifloxacin trials. These facts, together with the lack of data on women-specific issues, suggest that the therapeutic drug moxifloxacin is only a partially evidence-based medicine.

Level of involvement of clinical nurses in the evaluation of competence of nursing students

Objective. To determine the level of involvement of clinical nurses accredited by the Universitat Jaume I (Spain) as mentors of practice (Reference Nurses) in the evaluation of competence of nursing students. Methodolgy. Cross-sectional study, in which the “Clinical Practice Assessment Manual” (CPAM) reported by reference 41 nurses (n=55) were analyzed. Four quality criteria for completion were established: with information at least 80% of the required data, the presence of the signature and final grade in the right place. Verification of learning activities was also conducted. Data collection was performed concurrently reference for nurses and teachers of the subjects in the formative evaluations of clinical clerkship period in the matter “Nursing Care in Healthcare Processes “, from March to June 2013. Results. 63% of CPAM were completed correctly, without reaching the quality threshold established (80%). The absence of the signature is the main criteria of incorrect completion (21%). Nine learning activities do not meet the quality threshold set (80%) (p < 0.05). There are significant differences according to clinical units p < 0.05. From the 30 learning activities evaluated in the CPAM, it can be stated that nine of them do not reach the verification threshold established (80%), therefore it cannot be assumed that these activities had been completed by students and evaluated by the RefN throughout the clinical clerkship period. Conclusion. The level of involvement of Reference Nurse cannot be considered adequate, although strategies to encourage involvement through collaboration and training must be developed.