2020/04/17 14:34
阅读:235
分享:方案摘要:
产品配置单:
布鲁克 timsTOF fleX 组学和成像质谱系统
型号: timsTOF fleX™
产地: 德国
品牌: 布鲁克
面议
参考报价
联系电话
方案详情:
While phospholipids play key roles in lung physiology and pathology, the complex
composition and function of the lipidome in the lungs is poorly understood.
We applied MALDI mass spectrometry imaging to characterize the spatial distribution
of phospholipid molecules in mouse lungs.
下载本篇解决方案:
更多
4D-脂质组学高通量工作流程
Lipid profiling from complex lipid extracts can be a challenging and time consuming task. The high complexity of samples and co-elution of isobaric or isomeric compounds complicate the confident annotation of lipids. The presented 4D-Lipidomics workflow simplifies and streamlines the annotation and validation process using mobility-enhanced MS data.
医疗/卫生
2021/03/05
PASEF应用于COVID-19的高通量定量大规模血浆蛋白质组学研究
However, the dynamic range of protein concentration in these samples poses a challenge for in-depth proteome quantification. PASEF® is a powerful technology for rapid in-depth and sensitive proteome quantification that is also applicable to biofluids like plasma and serum. We combined PASEF with high-throughput gradient settings for the analysis of hundreds of plasma and serum samples and quantified several hundred protein groups routinely in 21- and 47-minute runtimes. The timsTOF Pro coupled with the Evosep One nanoflow UPLC delivers quantitation with median CV less than 20% and quantified more than 70 known biomarkers in a study investigating over 700 COVID-19 serum samples
医疗/卫生
2021/03/05
Proteomic Interrogation of Primary Insulin-secreting Pancreatic β-cells
The combination of integrated ion mobility with warp-speed MS/MS acquisition on the timsTOF Pro paves the way for deep, molecular level understanding of β-cell physiology and potential new targetable pathways for diabetes.
生物产业
2020/09/21
空间定位组学对肿瘤亚细胞群的深度蛋白组分析
MALDI Guided SpatialOMx,即基于质谱成像定位的空间多组学分析,完美的将MALDI成像技术和传统LC-MS/MS组学流程结合在了一起,它的特点是利用了MALDI成像技术能在分子原位对生物分子进行定位的特点,在生物组织的内部锁定目标微区(ROI,Region of Interests),在对该目标微区实施激光微切割(LCM,laser capture microdissection)后,进行LC-MS/MS组学分析,从而实现了深度的蛋白组信息挖掘。
医疗/卫生
2020/09/18