Sepsis is a serious condition with high mortality rates due to the highly variable and complex immune response. Early detection and immediate intervention are essential, which is why the scientific community is actively searching for new biomarkers that can provide rapid and reliable monitoring of patients affected by sepsis.
Current biomarkers, such as CRP and PCT, have certain limitations, including delays in detection. To overcome this delay, approaches including analysis of RNA levels and sequencing of single cells have been attempted, but these methods require considerable time.
The morphological appearance of immune cells appears to offer promising prospects as a rapid biomarker. Morphological changes occur rapidly during inflammation and can provide immediate insight into the immune system response.
However, most studies focus on cell lines or healthy cells, leaving behind the complexity of human immune responses. To overcome these limitations and accurately capture immune cell dynamics in sepsis, extensive investigations are needed.
Recently, in research published in the journal Light Science & Application, a team of scientists led by researchers from Yonsei University College of Medicine in South Korea created an artificial intelligence (AI) model using 3D imaging label-free to analyze changes in immune cell structure in health, sepsis and subsequent recovery.
By comparing data between healthy groups and sepsis patients at different stages of recovery, the team identified significant changes in morphological characteristics such as the volume and dry mass of CD8+ T cells.
This finding suggests that analysis of label-free 3D structures of CD8+ T cells can complement traditional diagnostic tools and provide critical information for clinical decisions in sepsis cases.
Being suitable for repeated and periodic tests requiring only a small blood sample, these label-free 3D structures represent a promising option for regular monitoring of patients with sepsis.
The authors of the study state that the developed technology can be used in the prediction of the health status of patients with low immunity and can be applied in various conditions, thus opening new perspectives in precise measurement and diagnosis of diseases.
Source: 360medical.ro
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2023-11-23 20:15:20
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