University of Massachusetts Boston

About: University of Massachusetts Boston is a education organization based out in Boston, Massachusetts, United States. It is known for research contribution in the topics: Population & Health care. The organization has 6541 authors who have published 12918 publications receiving 411731 citations. The organization is also known as: UMass Boston.

Fluorous linker-facilitated chemical synthesis.

Abstract: 2.2.6. Tetrahydropyran (THP)-Type Linkers 763 2.2.7. Carbonyl Linkers 764 2.2.8. Phenol Linkers 765 2.2.9. Benzaldehyde Linkers for Diol Protections 766 2.3. Carboxyl Group Protections 768 2.3.1. Trimetylsilylethyl (TMSE)-Type Linkers 768 2.3.2. Benzhydryl (Rink)-Type Linkers 768 2.3.3. PMB-OH-Type Linkers 768 2.3.4. t-Butyl-Type Linkers 770 2.4. Diol Linkers for Carbonyl Group Protections 770 3. Synthetic Applications of Fluorous Displaceable Linkers 772

The teaching of cultural issues in U.S. and Canadian medical schools.

Abstract: Purpose. Despite the importance of culture in health care and the rapid growth of ethnic diversity in the United States and Canada, little is known about the teaching of cultural issues in medical schools. The study goals, therefore, were to determine the number of U.S. and Canadian medical schools that have courses on cultural issues, and to examine the format, content, and timing of those courses. Method. The authors contacted the deans of students and/ or directors of courses on cultural issues at all 126 U.S. and all 16 Canadian medical schools. Using a cross-sectional telephone survey, they asked whether each school had a course on cultural sensitivity or multicultural issues and, if so, whether it was separate or contained within a larger course, when in the curriculum the course was taught, and which ethnic groups the course addressed. Results. The response rates were 94% for both U.S. (118) and Canadian (15) schools. Very few schools (U.S. = 8%; and Canada = 0%) had separate courses specifically addressing cultural issues. Schools in both countries usually addressed cultural issues in one to three lectures as part of larger, mostly preclinical courses. Significantly more Canadian than U.S. schools provided no instruction on cultural issues (27% versus 8%; p = .04). Few schools taught about the specific cultural issues of the largest minority groups in their geographic areas: only 28% and 26% of U.S. schools taught about African American and Latino issues, respectively, and only two thirds of Canadian schools taught about either Asian or Native Canadian issues. Only 35% of U.S. schools addressed the cultural issues of the largest minority groups in their particular states. Conclusions. Most U.S. and Canadian medical schools provide inadequate instruction about cultural issues, especially the specific cultural aspects of large minority groups. Acad. Med. 2000;75:451‐455.

A roadmap for urban evolutionary ecology

Abstract: Urban ecosystems are rapidly expanding throughout the world, but how urban growth affects the evolutionary ecology of species living in urban areas remains largely unknown. Urban ecology has advanced our understanding of how the development of cities and towns change environmental conditions and alter ecological processes and patterns. However, despite decades of research in urban ecology, the extent to which urbanization influences evolutionary and eco-evolutionary change has received little attention. The nascent field of urban evolutionary ecology seeks to understand how urbanization affects the evolution of populations, and how those evolutionary changes in turn influence the ecological dynamics of populations, communities, and ecosystems. Following a brief history of this emerging field, this Perspective article provides a research agenda and roadmap for future research aimed at advancing our understanding of the interplay between ecology and evolution of urban-dwelling organisms. We identify six key questions that, if addressed, would significantly increase our understanding of how urbanization influences evolutionary processes. These questions consider how urbanization affects nonadaptive evolution, natural selection, and convergent evolution, in addition to the role of urban environmental heterogeneity on species evolution, and the roles of phenotypic plasticity versus adaptation on species' abundance in cities. Our final question examines the impact of urbanization on evolutionary diversification. For each of these six questions, we suggest avenues for future research that will help advance the field of urban evolutionary ecology. Lastly, we highlight the importance of integrating urban evolutionary ecology into urban planning, conservation practice, pest management, and public engagement.

Method of chemically depositing material onto a substrate

Abstract: Methods are described for depositing a film of material on the surface of a substrate by i) dissolving a precursor of the material into a supercritical or near-supercritical solvent to form a supercritical or near-supercritical solution; ii) exposing the substrate to the solution, under conditions at which the precursor is stable in the solution; and iii) mixing a reaction reagent into the solution under conditions that initiate a chemical reaction involving the precursor, thereby depositing the material onto the solid substrate, while maintaining supercritical or near-supercritical conditions. The invention also includes similar methods for depositing material particles into porous solids, and films of materials on substrates or porous solids having material particles deposited in them.

Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives.

Abstract: In secondary analysis of electronic health records, a crucial task consists in correctly identifying the patient cohort under investigation. In many cases, the most valuable and relevant information for an accurate classification of medical conditions exist only in clinical narratives. Therefore, it is necessary to use natural language processing (NLP) techniques to extract and evaluate these narratives. The most commonly used approach to this problem relies on extracting a number of clinician-defined medical concepts from text and using machine learning techniques to identify whether a particular patient has a certain condition. However, recent advances in deep learning and NLP enable models to learn a rich representation of (medical) language. Convolutional neural networks (CNN) for text classification can augment the existing techniques by leveraging the representation of language to learn which phrases in a text are relevant for a given medical condition. In this work, we compare concept extraction based methods with CNNs and other commonly used models in NLP in ten phenotyping tasks using 1,610 discharge summaries from the MIMIC-III database. We show that CNNs outperform concept extraction based methods in almost all of the tasks, with an improvement in F1-score of up to 26 and up to 7 percentage points in area under the ROC curve (AUC). We additionally assess the interpretability of both approaches by presenting and evaluating methods that calculate and extract the most salient phrases for a prediction. The results indicate that CNNs are a valid alternative to existing approaches in patient phenotyping and cohort identification, and should be further investigated. Moreover, the deep learning approach presented in this paper can be used to assist clinicians during chart review or support the extraction of billing codes from text by identifying and highlighting relevant phrases for various medical conditions.