Michael P. Barrett

Bio: Michael P. Barrett is an academic researcher from University of Glasgow. The author has contributed to research in topics: Trypanosoma brucei & Metabolomics. The author has an hindex of 65, co-authored 318 publications receiving 13859 citations. Previous affiliations of Michael P. Barrett include University of Bordeaux & Wellcome Trust.

Drug resistance and treatment failure in leishmaniasis: A 21st century challenge

Abstract: Reevaluation of treatment guidelines for Old and New World leishmaniasis is urgently needed on a global basis because treatment failure is an increasing problem. Drug resistance is a fundamental determinant of treatment failure, although other factors also contribute to this phenomenon, including the global HIV/AIDS epidemic with its accompanying impact on the immune system. Pentavalent antimonials have been used successfully worldwide for the treatment of leishmaniasis since the first half of the 20th century, but the last 10 to 20 years have witnessed an increase in clinical resistance, e.g., in North Bihar in India. In this review, we discuss the meaning of “resistance” related to leishmaniasis and discuss its molecular epidemiology, particularly for Leishmania donovani that causes visceral leishmaniasis. We also discuss how resistance can affect drug combination therapies. Molecular mechanisms known to contribute to resistance to antimonials, amphotericin B, and miltefosine are also outlined.

Human African trypanosomiasis: pharmacological re-engagement with a neglected disease

Abstract: This review discusses the challenges of chemotherapy for human African trypanosomiasis (HAT). The few drugs registered for use against the disease are unsatisfactory for a number of reasons. HAT has two stages. In stage 1 the parasites proliferate in the haemolymphatic system. In stage 2 they invade the central nervous system and brain provoking progressive neurological dysfunction leading to symptoms that include the disrupted sleep wake patterns that give HAT its more common name of sleeping sickness. Targeting drugs to the central nervous system offers many challenges. However, it is the cost of drug development for diseases like HAT, that afflict exclusively people of the world's poorest populations, that has been the principal barrier to new drug development and has led to them becoming neglected. Here we review drugs currently registered for HAT, and also discuss the few compounds progressing through clinical trials. Finally we report on new initiatives that might allow progress to be made in developing new and satisfactory drugs for this terrible disease.

Toward global metabolomics analysis with hydrophilic interaction liquid chromatography-mass spectrometry: improved metabolite identification by retention time prediction.

Abstract: Metabolomics is an emerging field of postgenomic biology concerned with comprehensive analysis of small molecules in biological systems. However, difficulties associated with the identification of detected metabolites currently limit its application. Here we demonstrate that a retention time prediction model can improve metabolite identification on a hydrophilic interaction chromatography (HILIC)–high-resolution mass spectrometry metabolomics platform. A quantitative structure retention relationship (QSRR) model, incorporating six physicochemical variables in a multiple-linear regression based on 120 authentic standard metabolites, shows good predictive ability for retention times of a range of metabolites (cross-validated R2 = 0.82 and mean squared error = 0.14). The predicted retention times improved metabolite identification by removing 40% of the false identifications that occurred with identification by accurate mass alone. The importance of this procedure was demonstrated by putative identification ...

IDEOM : an Excel interface for analysis of LC-MS-based metabolomics data

Abstract: The application of emerging metabolomics technologies to the comprehensive investigation of cellular biochemistry has been limited by bottlenecks in data processing, particularly noise filtering and metabolite identification. IDEOM provides a user-friendly data processing application that automates filtering and identification of metabolite peaks, paying particular attention to common sources of noise and false identifications generated by liquid chromatography-mass spectrometry (LC-MS) platforms. Building on advanced processing tools such as mzMatch and XCMS, it allows users to run a comprehensive pipeline for data analysis and visualization from a graphical user interface within Microsoft Excel, a familiar program for most biological scientists.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

“Bioinformatics” 특집을 내면서

Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

Risk factors for human disease emergence.

Abstract: A comprehensive literature review identifies 1415 species of infectious organism known to be pathogenic to humans, including 217 viruses and prions, 538 bacteria and rickettsia, 307 fungi, 66 protozoa and 287 helminths. Out of these, 868 (61%) are zoonotic, that is, they can be transmitted between humans and animals, and 175 pathogenic species are associated with diseases considered to be 'emerging'. We test the hypothesis that zoonotic pathogens are more likely to be associated with emerging diseases than non-emerging ones. Out of the emerging pathogens, 132 (75%) are zoonotic, and overall, zoonotic pathogens are twice as likely to be associated with emerging diseases than non-zoonotic pathogens. However, the result varies among taxa, with protozoa and viruses particularly likely to emerge, and helminths particularly unlikely to do so, irrespective of their zoonotic status. No association between transmission route and emergence was found. This study represents the first quantitative analysis identifying risk factors for human disease emergence.