4.8 Article

Fluorescence lifetime imaging microscopy for early diagnosis and severity prediction of preeclampsia with Nile Blue probe

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BIOSENSORS & BIOELECTRONICS
卷 244, 期 -, 页码 -

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ELSEVIER ADVANCED TECHNOLOGY
DOI: 10.1016/j.bios.2023.115809

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Fluorescence lifetime imaging; Early diagnosis; Microenvironment monitoring; Nile Blue probe

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Preeclampsia is a common pregnancy complication and the leading cause of maternal and perinatal mortality. However, early diagnostic methods for preeclampsia are still rare. This study explores the possibility of using fluorescence lifetime imaging and the Nile Blue probe for the early diagnosis and severity prediction of preeclampsia.
Preeclampsia (PE) is a common pregnancy complication and the leading cause of maternal and perinatal mortality. Unfortunately, the early diagnostic methods for PE are still rare. Fluorescence lifetime imaging (FLIM) technology has proven to be applicable for diagnosis of various diseases. Here, we explore the possibility of the FLIM technique for PE early diagnosis and severity prediction with Nile Blue probe as biosensor. 23 placental slices and 162 third-trimester-collected maternal peripheral blood serum samples were stained with Nile blue and imaged by FLIM system. Fluorescence lifetimes of the probe increased significantly as the disease worsened (p < 0.0001). Characterization of the probe showed an increasing tendency in lifetimes under lower polarity conditions and revealed that the reason for the lifetime differences in serum sample was polarity changes caused by abnormal lipid metabolism in serum. For early diagnosis, we investigated 42 12th-week-collected chronic hypertension (CH) serum samples and successfully distinguished PE patients from pregnant women. With the functions of measuring fluorescence lifetime and detecting polarity changes caused by an abnormal lipid microenvironment in maternal peripheral blood, FLIM technology, together with Nile Blue probe, presents a feasible and advantageous approach for PE early noninvasive diagnosis and severity prediction.

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