130,668 research outputs found
Epidemics with two levels of mixing
No full textWe consider epidemics with removal (SIR epidemics) in populations that mix at two levels: global and local. We develop a general modelling framework for such processes, which allows us to analyze the conditions under which a large outbreak is possible, the size of such outbreaks when they can occur and the implications for vaccination strategies, in each case comparing our results with the simpler homogeneous mixing case. More precisely, we consider models in which each infectious individual i has a global probability pG for infecting each other individual in the population and a local probability pL, typically much larger, of infecting each other individual among a set of neighbors script N (i). Our main concern is the case where the population is partitioned into local groups or households, but our approach also applies to cases where neighborhoods do not form a partition, for instance, to spatial models with a mixture of local (e.g., nearest-neighbor) and global contacts. We use a variety of theoretical approaches: a random graph framework for the initial exposition of the simple case where an individual's contacts are independent; branching process approximations for the general threshold result; and an embedding representation for rigorous results on the final size of outbreaks. From the applied viewpoint the key result is that, compared with the homogeneous mixing model in which individuals make contacts simply with probability pG, the local infectious contacts have an "amplification" effect. The basic reproductive ratio of the epidemic is increased from its individual-to-individual value RG in the absence of local infections to a group-to-group value R* = µRG, where µ is the mean size of an outbreak, started by a randomly chosen individual, in which only local infections count. Where the groups are large and the within-group epidemics are above threshold, this amplification can permit an outbreak in the whole population at very low levels of pG, for instance, for pG = O(1/Nn) in a population of N divided into groups of size n. The implication of these results for control strategies is that vaccination should be directed preferentially toward reducing µ; we discuss the conditions under which the equalizing strategy, aimed at leaving unvaccinated sets of neighbors of equal sizes, is optimal. We also discuss the estimation of our threshold parameter R* from data on epidemics among households.</p
The rhesus factor and disease prevention
No full textThe prevention of rhesus disease of the newborn is a stunning medical success story. This disease afflicted thousands of newborns each year, causing serious health problems, even death. Yet from the early 1940s to the 1970s – British and American researchers uncovered the basis of the disease and developed the medical intervention that could prevent its occurrence. Many of the key steps leading to this remarkable achievement took place at the University of Liverpool School of Medicine. Chaired by Professor Sir David Weatherall, this Witness Seminar examines the factors that triggered these studies and the challenges that confronted scientists and clinicians; the intellectual, institutional, and social factors that guided the work; the crucial insights; and the vistas that the prevention of rhesus disease has opened in fetal medicine. Participants include Professor Robin Coombs, the late Professor Ronald Finn, Dr Nevin Hughes-Jones, Professor Patrick Mollison, Dr Archie Norman, Dr Derrick Tovey, Professor Charles Whitfield, Professor John Woodrow and Professor Doris Zallen
Relationship between cognition and white matter abnormalities in Multiple Sclerosis as detected by magnetic resonance imaging
No full textBackground
Multiple sclerosis (MS) is a highly variable disease of the central nervous system
with inflammatory and neurodegenerative components, associated with both
physical and cognitive disability. Abnormalities are visible on routine magnetic
resonance imaging (MRI) of the brain, with 'white matter hyperintensities'
(WMHs) representing sites of previous inflammation. Techniques for measuring
WMHs have not been standardised, although manual outlining is conventionally
taken to be the reference standard, despite its subjective element.
WMHs have been found to only partly explain the degree of cognitive impairment,
forming part of the 'clinico-radiological paradox'. Research interest has largely
moved to advanced imaging techniques, one such technique being diffusion tensor
imaging (DTI). Through sensitivity to water molecule movement, DTI reflects the
integrity of white matter tracts and thus its measures may be relevant to both
the inflammatory and degenerative disease components.
Aims
The work described in this thesis aims to improve our understanding of the true
relationship between measures of white matter damage and cognitive impairment
in people with MS, to determine the optimum measurement technique(s) for
quantifying WMHs, including developing and testing a novel visual rating scale,
and to assess whether information provided by DTI can strengthen the association
of imaging and clinical findings.
Methods
A systematic review of the literature and meta-analysis relating WMHs to
cognition was conducted, focussing on image analysis technique. Three separate
methods for quantifying WMHs were then investigated. The reproducibility
of manual outlining was assessed using scans available from 43 people with
secondary progressive MS (SPMS). An automated software method was optimised
for the same cohort, based on the results of the manual outlining. A novel
semi-quantitative visual rating scale was developed, with validation using the
same scans within a larger, more varied cohort. All available information
regarding the participants studied was then used to construct a linear regression
model predicting cognitive outcomes and determining the utility of the various
imaging markers derived from conventional imaging techniques. A non-linear
relationship for WMHs was also considered. White matter DTI metrics in the
same smaller cohort of 43 people were then investigated, primarily considering
tissue outwith WMHs, as well as that within major tracts and the novel diffusion
marker `peak width of skeletonised mean diffusivity'. The additional explanatory
power of DTI metrics within the linear models developed previously was then
determined.
Results
High variability was found in the literature regarding imaging marker
measurement and reporting of technique reproducibility. Manual outlining was
found to be associated with considerable measurement error, dependent on
observer and cohort factors. It was possible to optimise the automated software
for a particular cohort, either for volumetric or spatial outputs. Visual rating of
MS imaging features was found to be feasible and measures of WMH burden were
closely related to fully quantitative measures. The overall association of WMHs
to cognitive function was similar to that found in the published literature, with
no additional association following addition of DTI metrics. A trend towards
a greater effect of WMH volume at higher levels was found, consistent with a
non-linear relationship between imaging metrics and cognitive phenotype.
Conclusions
Substantial heterogeneity in the reporting of the reproducibility of WMH
measurement supports a move towards benchmarking against reference datasets.
Poor reliability of the current reference standard, manual segmentation, should
be recognised as a key limitation for the field. Rich information can be captured
quickly using visual rating of imaging features. The close correlation of visual
ratings of WMHs with quantitative measures may represent a practical alternative
in the appropriate circumstances. Combining visual rating features provided
additional explanatory power, supporting a multidimensional substrate for the
cognitive phenotype. Finally, both automated and visual rating analyses support
a non-linear relationship between disease burden and cognitive performance in
MS
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Patrick Mollison - Bibliography from Patrick Mollison CBE. 17 March 1914—26 November 2011
No full textPatrick Mollison was a pioneer in blood transfusion, playing a major role in changing it from a risky procedure to one which is now extremely safe. The urgent need for blood during World War II provided a stimulus for the development of this important lifesaving measure. His first major contribution was to devise a mechanism whereby blood could be stored for more than just short periods. Mixing donated blood with acid–citrate–dextrose (ACD) became a standard procedure for almost 30 years and was used worldwide. He later took a special interest in haemolytic disease of the newborn (HDN), which was largely due to Rhesus incompatibility between mother and baby. He was also involved with work which eventually led to HDN becoming preventable with the use of anti-D treatment of mothers. He wrote the first standard textbook on blood transfusion; almost 70 years later it is in its eleventh edition and still bears his name in the title. He spent his working life in blood transfusion and the study of the scientific aspects of this subject, developing a university department at Hammersmith Hospital and publishing almost 200 scientific papers as well as the textbook. He was very much a clinical scientist rather than a front-line clinician, although he was physician to Her Majesty Queen Elizabeth and was present at the birth of all four of her children
The Drosophila Melanogaster Protein Suppressor of Sable Negatively Regulates Transposon-Containing Transcripts By A Mechanism That Involves Directly Binding To Its RNA Target
No full textLonna Finnic Mollison: The Drosophila melanogaster Protein Suppressor of sable [Su(s)] Negatively Regulates Transposon-Containing Transcripts by a Mechanism that Involves Directly Binding to its RNA Target (Under the direction of Lillie Searles) RNA quality control systems operate at various stages of gene expression to prevent aberrant RNAs from accumulating. The nuclear pathways that lead to the identification and elimination of defective pre-mRNAs are incompletely understood, especially in multicellular organisms. The Suppressor of sable (Su(s)) protein of D. melanogaster plays a role in this process. Su(s) is a nuclear RNA-binding protein that negatively regulates the accumulation of RNA from genes that contain transposon insertions in the 5’ transcribed region. Previous studies have shown that the Su(s)-regulatory pathway induces premature transcription termination and degradation of the resulting RNAs. Here, I present in vitro and in vivo evidence that Su(s) recognizes specific sequences in one of its biological targets. I found that a U-rich element is efficiently bound by Su(s) and a G-rich element appears to be a weaker binding site. The results of reporter gene analysis confirmed that the U-rich and G-rich elements are relevant regulatory sequences. However, a GUA-rich element that contributes significantly to this regulation is not a Su(s) binding site. These results indicate that this regulation depends on the direct binding of Su(s) and, possibly, one or more other proteins to the RNA.Doctor of Philosoph
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
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