The Application of Paewinsky et al.'s Age Estimation Method to Periapical Radiographs

Roh, Byung-Yoon; Seo, Jeong Uk; Kim, Chang Gyum; Choi, Chang Un; Lee, Won Joon; Lee, Sang-Seob

doi:10.7580/kjlm.2018.42.4.141

Cited by 1 publication

(1 citation statement)

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“…Furthermore, in response to APAP administration, there was significant variability in the immune response across individuals, with certain samples exhibiting elevated levels of neutrophils and monocytes. These results were consistent with existing findings [22][23][24][25]. To our knowledge, this is the first report of an increase in eosinophils after GAL administration, and the responses of various immune cells after MDA administration were captured using flow cytometry.…”

Section: Flow Cytometry Analysis On the Evaluation Datasetsupporting

confidence: 92%

Investigation of the usefulness of liver-specific deconvolution method toward legacy data utilization

Azuma

Mizuno

Morita³

et al. 2023

Preprint

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Background: Deconvolution is a methodology for estimating the immune cell proportions from the transcriptome. It is mainly applied to blood-derived samples and tumor tissues. However, the influence of tissue-specific modeling on the estimation results has rarely been investigated. In this study, we constructed a system to evaluate the performance of the deconvolution method on liver transcriptome data. Results: We prepared various mouse liver injury models and established dataset with corresponding bulk RNA-Seq and immune cell proportions. Here, we found that the combination of reference cell sets affects the estimation results of reference-based deconvolution methods. We established a liver tissue-specific deconvolution by optimizing the reference cell set for each cell to be estimated. We applied this model to independent data sets and showed that the liver-specific modeling focusing on reference cell sets is highly extrapolatable. Conclusions: We provide an approach of liver-specific modeling when applying reference-based deconvolution to bulk RNA-Seq data and show its importance. It is expected to enable sophisticated estimation from rich tissue data accumulated in public databases and to obtain information on aggregated immune cell trafficking.

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Section: Flow Cytometry Analysis On the Evaluation Datasetsupporting

confidence: 92%