体育実技から健康・スポーツ科学実習へ : 自己評価による新カリキュラムの創造

Background: Endocytosis is regarded as a mechanism of attenuating the epidermal growth factor receptor (EGFR) signaling and of receptor degradation. There is increasing evidence becoming available showing that breast cancer progression is associated with a defect in EGFR endocytosis. In order to find related Ribonucleic acid (RNA) regulators in this process, high-throughput imaging with fluorescent markers is used to visualize the complex EGFR endocytosis process. Subsequently a dedicated automatic image and data analysis system is developed and applied to extract the phenotype measurement and distinguish different developmental episodes from a huge amount of images acquired through high-throughput imaging. For the image analysis, a phenotype measurement quantifies the important image information into distinct features or measurements. Therefore, the manner in which prominent measurements are chosen to represent the dynamics of the EGFR process becomes a crucial step for the identification of the phenotype. In the subsequent data analysis, classification is used to categorize each observation by making use of all prominent measurements obtained from image analysis. Therefore, a better construction for a classification strategy will support to raise the performance level in our image and data analysis system.Results: In this paper, we illustrate an integrated analysis method for EGFR signalling through image analysis of microscopy images. Sophisticated wavelet-based texture measurements are used to obtain a good description of the characteristic stages in the EGFR signalling. A hierarchical classification strategy is designed to improve the recognition of phenotypic episodes of EGFR during endocytosis. Different strategies for normalization, feature selection and classification are evaluated.Conclusions: The results of performance assessment clearly demonstrate that our hierarchical classification scheme combined with a selected set of features provides a notable improvement in the temporal analysis of EGFR endocytosis. Moreover, it is shown that the addition of the wavelet-based texture features contributes to this improvement. Our workflow can be applied to drug discovery to analyze defected EGFR endocytosis processes

Folate Receptor–Targeted Single-Photon Emission Computed Tomography/Computed Tomography to Detect Activated Macrophages in Atherosclerosis: Can It Distinguish Vulnerable from Stable Atherosclerotic Plaques?

The need for noninvasive imaging to distinguish stable from vulnerable atherosclerotic plaques is evident. Activated macrophages play a role in atherosclerosis and express folate receptor folate receptor β (FR-β). The feasibility of folate targeting to detect atherosclerosis was demonstrated in human and mouse plaques, and it was suggested that molecular imaging of FR-β through folate conjugates might be a specific marker for plaque vulnerability. However, these studies did not allow differentiation between stable and vulnerable atherosclerotic plaques. We investigated the feasibility of a folate-based radiopharmaceutical (111In-EC0800) with high-resolution animal single-photon emission computed tomography/computed tomography (SPECT/CT) to differentiate between stable and vulnerable atherosclerotic plaques in apolipoprotein E 7 mice in which we can induce plaques with the characteristics of stable and vulnerable plaques by placing a flow-modifying cast around the common carotid artery. Both plaques showed 111In-EC0800 uptake, with higher uptake in the vulnerable plaque. However, the vulnerable plaque was larger than the stable plaque. Therefore, we determined tracer uptake per plaque volume and demonstrated higher accumulation of 111In-EC0800 in the stable plaque normalized to plaque volume. Our data show that 111In-EC0800 is not a clear-cut marker for the detection of vulnerable plaques but detects both stable and vulnerable atherosclerotic plaques in a mouse model of atherosclerosis.ISSN:1535-3508ISSN:1536-012

Folate Receptor–Targeted Single-Photon Emission Computed Tomography/Computed Tomography to Detect Activated Macrophages in Atherosclerosis: Can It Distinguish Vulnerable from Stable Atherosclerotic Plaques?

The need for noninvasive imaging to distinguish stable from vulnerable atherosclerotic plaques is evident. Activated macrophages play a role in atherosclerosis and express folate receptor folate receptor β (FR-β). The feasibility of folate targeting to detect atherosclerosis was demonstrated in human and mouse plaques, and it was suggested that molecular imaging of FR-β through folate conjugates might be a specific marker for plaque vulnerability. However, these studies did not allow differentiation between stable and vulnerable atherosclerotic plaques. We investigated the feasibility of a folate-based radiopharmaceutical ( 111 In-EC0800) with high-resolution animal single-photon emission computed tomography/computed tomography (SPECT/CT) to differentiate between stable and vulnerable atherosclerotic plaques in apolipoprotein E 7 mice in which we can induce plaques with the characteristics of stable and vulnerable plaques by placing a flow-modifying cast around the common carotid artery. Both plaques showed 111 In-EC0800 uptake, with higher uptake in the vulnerable plaque. However, the vulnerable plaque was larger than the stable plaque. Therefore, we determined tracer uptake per plaque volume and demonstrated higher accumulation of 111 In-EC0800 in the stable plaque normalized to plaque volume. Our data show that 111 In-EC0800 is not a clear-cut marker for the detection of vulnerable plaques but detects both stable and vulnerable atherosclerotic plaques in a mouse model of atherosclerosis