36,662 research outputs found
Revisiting protein aggregation as pathogenic in sporadic Parkinson and Alzheimer diseases.
The gold standard for a definitive diagnosis of Parkinson disease (PD) is the pathologic finding of aggregated α-synuclein into Lewy bodies and for Alzheimer disease (AD) aggregated amyloid into plaques and hyperphosphorylated tau into tangles. Implicit in this clinicopathologic-based nosology is the assumption that pathologic protein aggregation at autopsy reflects pathogenesis at disease onset. While these aggregates may in exceptional cases be on a causal pathway in humans (e.g., aggregated α-synuclein in SNCA gene multiplication or aggregated β-amyloid in APP mutations), their near universality at postmortem in sporadic PD and AD suggests they may alternatively represent common outcomes from upstream mechanisms or compensatory responses to cellular stress in order to delay cell death. These 3 conceptual frameworks of protein aggregation (pathogenic, epiphenomenon, protective) are difficult to resolve because of the inability to probe brain tissue in real time. Whereas animal models, in which neither PD nor AD occur in natural states, consistently support a pathogenic role of protein aggregation, indirect evidence from human studies does not. We hypothesize that (1) current biomarkers of protein aggregates may be relevant to common pathology but not to subgroup pathogenesis and (2) disease-modifying treatments targeting oligomers or fibrils might be futile or deleterious because these proteins are epiphenomena or protective in the human brain under molecular stress. Future precision medicine efforts for molecular targeting of neurodegenerative diseases may require analyses not anchored on current clinicopathologic criteria but instead on biological signals generated from large deeply phenotyped aging populations or from smaller but well-defined genetic-molecular cohorts
Bibliometric Perspectives on Medical Innovation using the Medical Subject Headings (MeSH) of PubMed
Multiple perspectives on the nonlinear processes of medical innovations can
be distinguished and combined using the Medical Subject Headings (MeSH) of the
Medline database. Focusing on three main branches-"diseases," "drugs and
chemicals," and "techniques and equipment"-we use base maps and overlay
techniques to investigate the translations and interactions and thus to gain a
bibliometric perspective on the dynamics of medical innovations. To this end,
we first analyze the Medline database, the MeSH index tree, and the various
options for a static mapping from different perspectives and at different
levels of aggregation. Following a specific innovation (RNA interference) over
time, the notion of a trajectory which leaves a signature in the database is
elaborated. Can the detailed index terms describing the dynamics of research be
used to predict the diffusion dynamics of research results? Possibilities are
specified for further integration between the Medline database, on the one
hand, and the Science Citation Index and Scopus (containing citation
information), on the other.Comment: forthcoming in the Journal of the American Society for Information
Science and Technolog
Summarisation and visualisation of e-Health data repositories
At the centre of the Clinical e-Science Framework (CLEF) project is a repository of well organised,
detailed clinical histories, encoded as data that will be available for use in clinical care and in-silico
medical experiments. We describe a system that we have developed as part of the CLEF project, to perform the task of generating a diverse range of textual and graphical summaries of a patient’s clinical history from a data-encoded model, a chronicle, representing the record of the patient’s medical history. Although the focus of our current work is on cancer patients, the approach we
describe is generalisable to a wide range of medical areas
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Visualization of back pain data-A 3-D solution
Traditional approaches to gathering and visualizing pain data rely on two-dimensional (2-D) human body models, where different types of sensation are recorded with various monochrome symbols. We proposean alternative that uses a three-dimensional (3-D) representation of the human body, which can be marked in color to visualize and record pain data
Exploring the relationship between the Engineering and Physical Sciences and the Health and Life Sciences by advanced bibliometric methods
We investigate the extent to which advances in the health and life sciences
(HLS) are dependent on research in the engineering and physical sciences (EPS),
particularly physics, chemistry, mathematics, and engineering. The analysis
combines two different bibliometric approaches. The first approach to analyze
the 'EPS-HLS interface' is based on term map visualizations of HLS research
fields. We consider 16 clinical fields and five life science fields. On the
basis of expert judgment, EPS research in these fields is studied by
identifying EPS-related terms in the term maps. In the second approach, a
large-scale citation-based network analysis is applied to publications from all
fields of science. We work with about 22,000 clusters of publications, each
representing a topic in the scientific literature. Citation relations are used
to identify topics at the EPS-HLS interface. The two approaches complement each
other. The advantages of working with textual data compensate for the
limitations of working with citation relations and the other way around. An
important advantage of working with textual data is in the in-depth qualitative
insights it provides. Working with citation relations, on the other hand,
yields many relevant quantitative statistics. We find that EPS research
contributes to HLS developments mainly in the following five ways: new
materials and their properties; chemical methods for analysis and molecular
synthesis; imaging of parts of the body as well as of biomaterial surfaces;
medical engineering mainly related to imaging, radiation therapy, signal
processing technology, and other medical instrumentation; mathematical and
statistical methods for data analysis. In our analysis, about 10% of all EPS
and HLS publications are classified as being at the EPS-HLS interface. This
percentage has remained more or less constant during the past decade
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