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Improved lipid analysis to inform future therapeutic strategies

Improved lipid analysis to inform future therapeutic strategies
改进脂质分析以指导未来的治疗策略
批准号:
2679337
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --

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中文摘要
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英文摘要
Antimicrobial resistance (AMR) threatens to rival cancer in mortality and financial burden by 2050. Mycobacterial infections are the primary bacterial cause of global morbidity and mortality (2 million deaths annually), costing $12 billion, with lipids implicated in AMR1. Medulloblastoma is the most common malignant child brain tumour, with various phospholipids implicated in tumour metastastasis2. Because lipids are indicative of disease/progression and impact therapeutic strategies/success it is imperative to have sensitive methods of detection and identification directly from biological samples.Surface-sampling MS approaches offer the benefit of direct analysis and imaging; recent advances in instrumentation allow coupling to high resolution (trapping) mass analysers (HRMS), offering high accurate mass analysis3,4, aiding identification. Complementary approaches will be utilised; secondary ion MS (SIMS), ambient pressure (AP) matrix-assisted laser desorption/ionisation (MALDI) and liquid extraction surface analysis (LESA).Lipid analysis is complicated by the formation of (naturally occurring) adducts ([M+H]+, [M+Na]+, [M+K]+), decreasing sensitivity and complicating assignments. Salt additives have been shown to afford improvements in sensitivity, decrease spectral complexity and identification via MALDI and LESA5,6. MALDI matrix enhancement can also improve SIMS (ME-SIMS)7, and hasn't been investigated via OrbiSIMS. This project will deliver sensitive analytical methods for the direct detection and identification of lipids implicated in disease/infection.
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