1,892 research outputs found
Rapid mortality transition of Pacific Islands in the 19th century
The depopulation of Pacific islands during the 16th to 19th centuries is a striking example of historical mass mortality due to infectious disease. Pacific Island populations have not been subject to such cataclysmic infectious disease mortality since. Here we explore the processes which could have given rise to this shift in infectious disease mortality patterns. We show, using mathematical models, that the population dynamics exhibited by Pacific Island populations are unlikely to be the result of Darwinian evolution. We propose that extreme mortality during first-contact epidemics is a function of epidemiological isolation, not a lack of previous selection. If, as pathogens become established in populations, extreme mortality is rapidly suppressed by herd immunity, Pacific Island population mortality patterns can be explained with no need to invoke genetic change. We discuss the mechanisms by which this could occur, including (i) a link between the proportion of the population transmitting infectious agents and case-fatality rates, and (ii) the course of infection with pathogens such as measles and smallpox being more severe in adults than in children. Overall, we consider the present-day risk of mass mortality from newly emerging infectious diseases is unlikely to be greater on Pacific islands than in other geographical areas
The nonchromatin substructures of the nucleus: the ribonucleoprotein (RNP)-containing and RNP-depleted matrices analyzed by sequential fractionation and resinless section electron microscopy.
Using a population-based approach to prevent hepatocellular cancer in New South Wales, Australia: effects on health services utilisation
<p>Abstract</p> <p>Background</p> <p>Australians born in countries where hepatitis B infection is endemic are 6-12 times more likely to develop hepatocellular cancer (HCC) than Australian-born individuals. However, a program of screening, surveillance and treatment of chronic hepatitis B (CHB) in high risk populations could significantly reduce disease progression and death related to end-stage liver disease and HCC. Consequently we are implementing the <it>B Positive </it>pilot project, aiming to optimise the management of CHB in at-risk populations in south-west Sydney. Program participants receive routine care, enhanced disease surveillance or specialist referral, according to their stage of CHB infection, level of viral load and extent of liver injury. In this paper we examine the program's potential impact on health services utilisation in the study area.</p> <p>Methods</p> <p>Estimated numbers of CHB infections were derived from Australian Bureau of Statistics data and applying estimates of HBV prevalence rates from migrants' countries of birth. These figures were entered into a Markov model of disease progression, constructing a hypothetical cohort of Asian-born adults with CHB infection. We calculated the number of participants in different CHB disease states and estimated the numbers of GP and specialist consultations and liver ultrasound examinations the cohort would require annually over the life of the program.</p> <p>Results</p> <p>Assuming a 25% participation rate among the 5,800 local residents estimated to have chronic hepatitis B infection, approximately 750 people would require routine follow up, 260 enhanced disease surveillance and 210 specialist care during the first year after recruitment is completed. This translates into 5 additional appointments per year for each local GP, 25 for each specialist and 420 additional liver ultrasound examinations.</p> <p>Conclusions</p> <p>While the program will not greatly affect the volume of local GP consultations, it will lead to a significant increase in demand for specialist services. New models of CHB care may be required to aid program implementation and up scaling the program will need to factor in additional demands on health care utilisation in areas of high hepatitis B sero-prevalence.</p
Epithelial structure revealed by chemical dissection and unembedded electron microscopy.
Nuclear matrix proteins distinguish normal diploid osteoblasts from osteosarcoma cells
Interrelationships between nuclear architecture and gene expression were examined by comparing the representation of nuclear matrix proteins in ROS 17/2.8 rat and MG-63 human osteosarcoma cells with those in normal diploid osteoblasts. The tumor-derived cells coexpress genes which are expressed in a sequential and mutually exclusive manner during the progressive stages of osteoblast differentiation. In osteosarcoma cells two-dimensional electrophoretic analysis indicates a composite representation of nuclear matrix proteins characteristic of both the proliferative and postproliferative periods of osteoblast phenotype development. In addition, nuclear matrix proteins unique to the tumor cells and the absence of nuclear matrix proteins found only in normal diploid osteoblasts are observed. Tumor-specific nuclear matrix proteins include those expressed in a proliferation-dependent and independent manner. There is a parallel relationship between nuclear matrix proteins and the expression of cell growth and tissue-specific genes during osteoblast differentiation and in osteosarcoma cells where the developmental sequence of gene expression has been abrogated. Nuclear matrix proteins therefore provide markers reflecting defined periods of bone cell differentiation and phenotypic characteristics of an osteosarcoma
Reverse immunodynamics : a new method for identifying targets of protective immunity
Despite a dramatic increase in our ability to catalogue variation among pathogen genomes, we have made far fewer advances in using this information to identify targets of protective immunity. Epidemiological models predict that strong immune selection can cause antigenic variants to structure into genetically discordant sets of antigenic types (e.g. serotypes). A corollary of this theory is that targets of immunity may be identified by searching for non-overlapping associations of amino acids among co-circulating antigenic variants. We propose a novel population genetics methodology that combines such predictions with phylogenetic analyses to identify genetic loci (epitopes) under strong immune selection. We apply this concept to the AMA-1 protein of the malaria parasite Plasmodium falciparum and find evidence of epitopes among certain regions of low variability which could render them ideal vaccine candidates. The proposed method can be applied to a myriad of multi-strain pathogens for which vast amounts of genetic data has been collected in recent years
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