Highly Sensitive Detection Of Malaria Parasites
News Apr 02, 2015
An international team led by Ingrid Felger, from Swiss TPH, Basel, Switzerland, took advantage of genes in the parasite genome that exist in multiple copies to reveal parasites present at concentrations that are 10 times lower than the detection limit of current standard assays.
The researchers compared three methods to detect malaria parasites to look for Plasmodium falciparum in 498 samples randomly selected from a malaria survey in Tanzania: light microscopy, the current standard molecular assay, and the new assays. Parasites were detected in 25% of samples by light microscopy, in 50% by the standard assay, and in 58% by the new assays. Compared to the new assays, the current molecular standard assay failed to identify 16% of infections, and at least 40% of those contained parasite gametocytes, the parasite stage that is transmitted when mosquitoes bite an infected person.
The new assays detect only the most common malaria parasite, P. falciparum, and while they can use very small blood samples collected “in the field”, the analysis itself needs to be done in a biomedical laboratory. Nonetheless, because low-density infections without disease symptoms are expected to become increasingly common as countries improve malaria control, ultra-sensitive tools such as these will likely be critical for malaria surveillance and for monitoring the progress of malaria control and elimination programs.
Hofmann N, Mwingira F, Shekalaghe S, Robinson LJ, Mueller I, Felger I (2015) Ultra-Sensitive Detection of Plasmodium falciparum by Amplification of Multi-Copy Subtelomeric Targets. PLoS Med 12(2) 2014.
Scientists at McGill have found the answer to a question that perplexed Charles Darwin; if natural selection works at the level of the individual, fighting for survival and reproduction, how can a single colony produce worker ants that are so dramatically different in size – from “minor” workers to large-headed soldiers with huge mandibles – especially if they are sterile?
Scientists have developed a successful method to make truly personalized predictions of future disease outcomes for patients with certain types of chronic blood cancers. The study combined extensive genetic and clinical information to predict the prognosis for patients with myeloproliferative neoplasms.
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