Search

Laura Khurana,1 Ellen M Durand,1 Sarah Tressel Gary,1 Antonio V Otero,1 Kelly M Dumais,1 Jamie Beck,1 David Zurakowski,2 Christine Teel Hall,1 Susan M Dallabrida11eResearch Technology (ERT), Boston, MA, USA; 2Harvard Medical School, Boston Children’s Hospital, Boston, MA, USAPurpose: Effective health care and patient adherence to their prescribed regimens relies on successful communication between patients and their providers. This study examined mechanisms for optimizing patient–physician communication in subjects with type 2 diabetes, with a focus on optimizing the incorporation of e-clinical technology to improve engagement and communication.Methods: A total of 105 subjects with type 2 diabetes participating in a large US mode equivalency study were surveyed independently of this trial. In addition to demographic information, each subject was queried on their familiarity with and preference for e-clinical technologies. Survey questions focused on mobile technology use, perceptions, and preferences for improving communication and interactions with health care providers.Results: Subjects were diverse in age, sex, education, and ethnicity. Forty nine percent owned a smartphone, and 64% had a computer at home. Most subjects (81%) were interested in using electronic methods (eg, app on a smartphone, email, or text messages) to interact more with physicians between visits. The majority of subjects were interested in using technology to help manage their type 2 diabetes, including 62% favoring communicating with their health-care providers via email and a considerable fraction interested in using smartphones to be provided medication reminders (56%), clinical visit scheduling (55%), and text messaging (49%).Conclusion: Subjects are interested in using electronic methods to increase communication with their physicians and manage their type 2 diabetes. Health-care providers should consider engaging patients with e-clinical technology to increase patient–physician communication and for the ultimate goal of improved health care.Keywords: technology, eCOA, preferences, electronic, smartphone

We present evidence that quantitative definitions of extreme events in wind, so called gusts, may be flawed and unable to grasp true extreme situations of wind velocity in short time intervals. In particular, we show that the same statistics of particular pattern shapes in wind data are found in surrogate data generated from the original series of measurements. We apply a pattern recognition algorithm to a two-parameter “Mexican-hat” (duration and amplitude) and find the same probability of occurrence for both original measurements and surrogate data. The distribution of the corresponding values of the duration and amplitude present deviations that can be explained by the filtering of n-point correlations in the original series.

Leukemia is a type of cancer that starts in blood-forming tissue, such as the bone marrow. It causes the production of large numbers of abnormal blood cells that end up entering into the bloodstream. Within the different types of leukemia, Mantle Cell Lymphoma (MCL) is the one with the worst prognosis due to the short survival average of a patient, which is close to three years. This tumor is characterized by the over-expression of Cyclin D1, a protein that helps control cell division. MCL is also characterized by the binding of this protein to certain regions of DNA involved in the regulation of DNA-damage response (DDR). The presented study aims to identify similarities between the gene expression regulated by Cyclin D1 in lymphomas and the gene expression in DNA damage. That knowledge will allow the exploration of essential mechanisms of carcinogenesis and help in the identification of genes that could be an interesting therapeutic target in the process of tumor progression. Additionally, new biomarkers that could be used in early diagnosis can be found. With the addition of machine learning algorithms to the biology analysis pipeline, this project explores new ways to improve the traditional methodologies and boost the identification of significantly enriched genes that will serve the purposes mentioned above. The result of such a pipeline is the accurate selection of genes correlated with Cyclin D1, involved in MCL and DDR, and its posterior analysis and identification of significantly enriched gene sets. As a conclusion, the results obtained in this study suggested that targeting of Notch pathway and studying potential common mechanisms of hypoxia and apoptosis resistance would be of great interest for possible future studies on treatments of MCL. La leucemia es un tipo de cáncer que empieza en los tejidos generadores de sangre, tales como la médula ósea. Esta enfermedad causa la producción de un gran número de células sanguíneas anormales que van a parar al flujo sanguíneo. Dentro de la leucemia encontramos diferentes tipos, siendo el Linfoma de las células del manto (en adelante, Mantle Cell Lymphoma o MCL) el que peor pronóstico tiene, debido a la corta media de supervivencia del paciente, cercana a los tres años. Este tumor se caracteriza por la sobre-expresión de la ciclina D1, proteína que ayuda a controlar la división celular, y también por la unión de ésta proteína a ciertas regiones de ADN involucradas en la regulación del proceso de reparación del daño al ADN (en adelante, DNA-Damage Response o DDR). El presente estudio tiene como objetivo identificar las similitudes entre la expresión génica derivada de la regulación por la ciclina D1 en Linfoma con la que se da en el caso del daño en el ADN. Este conocimiento permitirá la exploración de los mecanismos esenciales de carcinogénesis y ayudará en la identificación de genes que pueden ser un objetivo terapéutico interesante en el proceso de progresión tumoral. Adicionalmente, se podrían hallar nuevos biomarcadores para el diagnóstico precoz de la enfermedad. Con la adición de machine learning al proceso de análisis biológico, este proyecto explora nuevas formas de mejorar las metodologías tradicionales e impulsar la identificación de genes significativamente enriquecidos que servirán a los propósitos mencionados anteriormente. El resultado de dicho proceso analítico es la precisa selección de genes correlacionados con la ciclina D1, involucrados en MCL y DDR, y su posterior análisis. Como conclusión, los resultados obtenidos en este estudio sugirieron que el tratamiento del Notch pathway y el potencial estudio de los mecanismos comunes de resistencia a la hipoxia y apoptosis serían de gran interés para posibles estudios futuros sobre tratamientos de MCL. La leucèmia és un tipus de càncer que comença en els teixits generadors de sang, com ara la medul·la òssia. Aquesta malaltia causa la producció d'un gran nombre de cèl·lules sanguínies anormals que van a parar al flux sanguini. Dins de la leucèmia trobem diferents tipus, sent el Limfoma de les cèl·lules del mantell (en endavant, Mantle Cell Lymphoma o MCL) el que pitjor pronòstic té, a causa de la curta mitjana de supervivència del pacient, propera als tres anys. Aquest tumor es caracteritza per la sobre-expressió de la ciclina D1, proteïna que ajuda a controlar la divisió cel·lular, i també per la unió d'aquesta proteïna a certes regions d'ADN involucrades en la regulació del procés de reparació del dany a l'ADN (en endavant, DNA-Damage Response o DDR). El present estudi té com a objectiu identificar les similituds entre l'expressió gènica derivada de la regulació per la ciclina D1 en Limfoma amb la que es dóna en el cas del dany en l'ADN. Aquest coneixement permetrà l'exploració dels mecanismes essencials de carcinogènesi i ajudarà en la identificació de gens que poden ser un objectiu terapèutic interessant en el procés de progressió tumoral. Addicionalment, es podrien trobar nous biomarcadors per al diagnòstic precoç de la malaltia. Amb l'addició de machine learning al procés d'anàlisi biològica, aquest projecte explora noves formes de millorar les metodologies tradicionals i impulsar la identificació de gens significativament enriquits que serviran als propòsits esmentats anteriorment. El resultat d'aquest procés analític és la precisa selecció de gens correlacionats amb la ciclina D1, involucrats en MCL i DDR, i la seva posterior anàlisi. Com a conclusió, els resultats obtinguts en aquest estudi van suggerir que el tractament del Notch pathway i el potencial estudi dels mecanismes comuns de resistència a la hipòxia i apoptosi serien de gran interès per a possibles estudis futurs sobre tractaments de MCL.

Journal of synchrotron radiation 26(2), 393 - 405 (2019). doi:10.1107/S1600577519001267, MXCuBE2 is the second-generation evolution of the MXCuBE beamline control software, initially developed and used at ESRF – the European Synchrotron. MXCuBE2 extends, in an intuitive graphical user interface (GUI), the functionalities and data collection methods available to users while keeping all previously available features and allowing for the straightforward incorporation of ongoing and future developments. MXCuBE2 introduces an extended abstraction layer that allows easy interfacing of any kind of macromolecular crystallography (MX) hardware component, whether this is a diffractometer, sample changer, detector or optical element. MXCuBE2 also works in strong synergy with the ISPyB Laboratory Information Management System, accessing the list of samples available for a particular experimental session and associating, either from instructions contained in ISPyB or from user input via the MXCuBE2 GUI, different data collection types to them. The development of MXCuBE2 forms the core of a fruitful collaboration which brings together several European synchrotrons and a software development factory and, as such, defines a new paradigm for the development of beamline control platforms for the European MX user community., Published by Wiley-Blackwell, [S.l.]