5 research outputs found

    Role of the human beta-herpesviruses in organ allograft rejection following transplantation.

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    In previous prospective studies conducted in our department, PCR was used to detect the three ({dollar}-herpesviruses, human cytomegalovirus (HCMV), and human herpesviruses 6 and 7 (HHV-6 and HHV-7) in the blood of solid organ transplant patients. The viruses were commonly detected post-transplantation, and HCMV and HHV-6 were independently associated with graft rejection in liver recipients. HHV-7 was also associated with increased episodes of rejection in renal transplant patients. To better understand the role of these viruses in graft rejection, in situ techniques including in situ hybridisation (ISH) and immunohistochemistry (IHC) were developed to detect these viruses in renal and liver allograft biopsies from patients in the original prospective studies. HCMV DNA was detected in a significant proportion of liver and renal biopsies (approximately 50%) by ISH, with detection being widespread especially in renal allografts. The presence of HCMV DNA in the biopsies is likely to represent low level HCMV replication not detectable by IHC. HCMV was not statistically associated with either renal or liver allograft rejection by ISH. It remains possible that HCMV infection in the graft leads to dysfunction and is clinically interpreted as allograft rejection. HHV-6 and HHV-7 were not detected in any allografts by ISH or IHC. In addition, an uncommon form of HHV-6 persistence is characterized by high viral loads in blood and integration of viral sequences into host cell chromosomes. Fluorescence in situ hybridisation (FISH) was developed to examine integration events in a healthy individual with a consistently high HHV-6 load and also in a case of genetic transmission of integrated virus through stem cell transplantation. In the former individual, integrated HHV-6 was identified on chromosome lip 15.5 and in the latter shown in the donor and the recipient (post-transplantation only) on chromosome 17pl3.3. The confounding effect of HHV-6 integration must be considered when investigating novel disease associations of HHV-6

    Global warming and malaria: a call for accuracy

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    For more than a decade, malaria has held a prominent place in speculations on the impacts of global climate change. Mathematical models that “predict? increases in the geographic distribution of malaria vectors and the prevalence of the disease have received wide publicity. Efforts to put the issue into perspective1, 2, 3, 4 and 5 are rarely quoted and have had little influence on the political debate. The model proposed by Frank C Tanser and colleagues6 in The Lancet and the accompanying Commentary by Simon Hales and Alistair Woodward7 are typically misleading examples.The relation between climate and malaria transmission is complex and varies according to location,2 yet Tanser et al base their projections on thresholds derived from a mere 15 African locations. Slight adjustments of values assigned to such thresholds and rules can influence spatial predictions strongly.8 The authors invest considerable effort in assessing the sensitivity of their model to climate change scenarios but do not report the internal sensitivities to thresholds and rules. The predictive skill of their model is low (63% sensitivity, 95% CI 61–65%) but they consider projections acceptable if prevalence is projected “to within a month? (presumably +/- 1 month?), thereby biasing their model towards success. A model covering an entire year in a parasite-positive site would always be correct, although in such areas it would be relatively insensitive to climate. By contrast, sites in which transmission is seasonal would provide a more reliable test of accuracy, but estimation is more difficult because climate sensitivity is greater. Furthermore, because parasite clearance in communities is not instantaneous,9 spot samples of parasitaemia on survey dates are not a suitable indicator of the duration of the transmission season. Lastly, “person/months? are unsuitable as a measure of transmission: an extension of season from 1 to 4 months will have more impact than from 10 to 12 months. According to their model, an extension of transmission from 11 to 12 months results in 106 more person/months in a population of 106 people, whereas an extension from 1 to 5 months gives the same increase in a population of 250·000.What Tanser and colleagues have modelled is merely the duration of the transmission season, which they interpret as “heightened transmission? and increased incidence. A greater failing is their reliance on “parasite-ratio studies?. The relations between transmission season and parasite prevalence, and parasite prevalence and clinical disease, are unclear but unlikely to be linear. Moreover, they use 1995 data for human populations, although these are projected to double by 2030. In addition, the proportion living in urban areas—with a specific climate10 and orders of magnitude less malaria transmission11 and 12—is projected to rise from 37% to 53%.13 For all these reasons, we do not accept the model as a “baseline against which interventions can be planned?.It is regrettable that many involved in this debate ignore the rich heritage of literature on the subject. For example, in 1937, in his classic textbook,14 L W Hackett stated: “Everything about malaria is so moulded and altered by local conditions that it becomes a thousand different diseases and epidemiological puzzles. Like chess, it is played with a few pieces, but is capable of an infinite variety of situations?. A pressing question in Hackett's time was the changing distribution of the disease in Europe. On the role of climate, he wrote: “Certainly, climate lays down the broad lines of malaria distribution…Nevertheless, although this is a very simple and plausible explanation…even the early malariologists felt that there was something unsatisfactory about it…malaria has not so much receded as it has contracted, oftentimes toward the north…Thus in Germany it is the northern coast which is still malarious, the south is free…There is, therefore, no climatic reason why (malaria) should have abandoned south Germany or the French Riviera?.We quote Hackett because we feel that the classic components of science—unbiased observation and systematic experimentation—cannot be sidestepped with models that omit many of his chess pieces. Yet Hales and Woodward7 begin by stating: “The present geographical distribution of malaria is explained by a combination of environmental factors (especially climate) and social factors (such as disease-control measures)?. In our opinion, “even the early malariologists? would surely disagree: much of the decline of malaria in Europe took place without control measures during a period when the climate was warming.The text by Hales and Woodward that follows displays a lack of knowledge. Thus, “Most people at risk of malaria live in areas of stable transmission…? is simply wrong. It is true that in many parts of the world malaria is termed “stable? because transmission remains relatively constant from year to year, the disease is endemic, the collective immunity is high, and epidemics are uncommon. However, in many other regions, the disease is endemic but “unstable? because annual transmission varies considerably, and the potential for epidemics is great. Climatic factors, particularly rainfall, are sometimes, but by no means always, relevant.15Again, “On the fringes of endemic zones, where transmission is limited by rainfall…there are strong seasonal patterns, and occasional major epidemics? is also wrong. In many regions, far from any “fringes?, malaria is endemic, stable, but highly seasonal. For example, in semi-arid regions of Mali, transmission is restricted to the rainy season, from July to September. The same 3 months constituted the transmission season for Plasmodium falciparum in Italy before it was eliminated.16 Paradoxically, in parts of the Sudan, rainfall is restricted to a month at most, but malaria is transmitted throughout the year. Female Anopheles gambiae survive drought and heat by resting in dwellings and other sheltered places.17 Blood feeding and transmission continue, but the mosquitoes do not develop eggs until the rains return. This phenomenon, termed gonotrophic dissociation, is remarkably similar to the winter survival strategy of Anopheles atroparvus, the principal vector of malaria in Holland until the mid 20th century.16By contrast, malaria is unstable in many regions that normally have abundant rainfall, and epidemics occur during periods of drought. An illustrative example is the catastrophic 1934–35 epidemic in Ceylon (now Sri Lanka), estimated to have killed 100·000 people.18 Worst hit was the south-western quadrant of the country, where average annual rainfall is greater than 250 cm, and malaria was endemic, but unstable and relatively infrequent. The dominant vector, Anopheles culicifacies, breeds along the banks of rivers and tends to be scarce in normal years. In the years 1928–33 there was abundant rainfall, river flow was high, A culicifacies was rare, and the human population was exceptionally malaria-free. However, after failure of two successive monsoons, the drying rivers produced colossal numbers of A culicifacies, and the resulting epidemic was exacerbated by the low collective immunity. In the drier parts of the island, where A culicifacies was dominant but transmission was more stable, immunity protected the population from the worst ravages of the disease.Hales and Woodward state that “the underlying problem? of the future “extension of seasonality? of malaria is “pollution of the atmosphere?, and call for rich countries to “recognise their obligations to the poorest by substantially reducing fossil-fuel consumption?. We understand public anxiety about climate change, but are concerned that many of these much-publicised predictions are ill informed and misleading. We urge those involved to pay closer attention to the complexities of this challenging subject. <br/

    Guidelines for the use and interpretation of assays for monitoring autophagy

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    In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field
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