CD56抗原を指標としたNK様培養細胞の活性評価

NK cells play an important role in the elimination of viral infection and tumors. In recent years, immune cell therapy using activated NK cells has attracted attention, and the search for activators and evaluation of NK cell activity have become important. We previously reported a positive correlation between CD５６antigen expression, which is the major cell membrane antigen of human NK cells, and NK cell activity or cytotoxicity, and demonstrated that it is possible to evaluate NK cell function using the CD５６ antigen as an index. This simple evaluation method is useful for functional evaluation of NK cells and the search for activators. However, it requires blood sampling and preparation of NK cells because it uses human NK cells. Therefore, in this study, we examined whether the CD５６ antigen functions as an activation index using KHYG‐１ human NK-like cultured cells as a substitute for NK cells. As a result, the CD５６antigen on the KHYG‐１cell membrane was increased in a concentration-dependent manner by IL‐２ stimulation, as was the cytotoxicity. This suggests that the CD５６ antigen on the KHYG‐１ cell membrane can be used as an evaluation index of NK activity as in human NK cells

KHYG‐１における細胞傷害性と細胞傷害性顆粒の変化

Three major therapies, “surgery”, “chemotherapy”, and “radiotherapy”, have been used to treat cancer. Recently, “immunotherapy” has attracted attention as the fourth treatment. We previously performed fundamental studies using NK cells, one cell type that has attracted attention in immunotherapy, and revealed that the surface CD５６ antigen on the KHYG‐１ human NK cell-like cultured cells as a substitute for human NK cells can be used as an evaluation index of NK cell activity as in human NK cells. We also reported that the cytotoxicity of KHYG‐１increases by IL‐２ stimulation. In this study, we improved the conventional cytotoxicity measurement method to evaluate the effects of a small amount of activator on NK cells. As a result, the cytotoxicity rate and measurement sensitivity at low-concentration IL‐２ stimulation were increased, and it became possible to evaluate the effects of a smaller amount of the activator. In the dynamic observation of KHYG‐１ intracellular granules, it was possible to observe in real time how the target cells were damaged after the influx of granules. Furthermore, the relationship between the activation of KHYG‐１and the change in the intracellular expression level of granzyme B by IL‐２stimulation was clarified, and future research tasks were shown

Case-based similar image retrieval for weakly annotated large histopathological images of malignant lymphoma using deep metric learning

In the present study, we propose a novel case-based similar image retrieval (SIR) method for hematoxylin and eosin (H&E)-stained histopathological images of malignant lymphoma. When a whole slide image (WSI) is used as an input query, it is desirable to be able to retrieve similar cases by focusing on image patches in pathologically important regions such as tumor cells. To address this problem, we employ attention-based multiple instance learning, which enables us to focus on tumor-specific regions when the similarity between cases is computed. Moreover, we employ contrastive distance metric learning to incorporate immunohistochemical (IHC) staining patterns as useful supervised information for defining appropriate similarity between heterogeneous malignant lymphoma cases. In the experiment with 249 malignant lymphoma patients, we confirmed that the proposed method exhibited higher evaluation measures than the baseline case-based SIR methods. Furthermore, the subjective evaluation by pathologists revealed that our similarity measure using IHC staining patterns is appropriate for representing the similarity of H&E-stained tissue images for malignant lymphoma

Editorial for the MEDIA special issue on MICCAI 2013

International audienc

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013 - Part 2

International audienceThe three-volume set LNCS 8149, 8150, and 8151 constitutes the refereed proceedings of the 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013, held in Nagoya, Japan, in September 2013. Based on rigorous peer reviews, the program committee carefully selected 262 revised papers from 789 submissions for presentation in three volumes. The 95 papers included in the first volume have been organized in the following topical sections: physiological modeling and computer-assisted intervention; imaging, reconstruction, and enhancement; registration; machine learning, statistical modeling, and atlases; computer-aided diagnosis and imaging biomarkers; intraoperative guidance and robotics; microscope, optical imaging, and histology; cardiology, vasculatures and tubular structures; brain imaging and basic techniques; diffusion MRI; and brain segmentation and atlases

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013 - Part 1

International audienceThe three-volume set LNCS 8149, 8150, and 8151 constitutes the refereed proceedings of the 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013, held in Nagoya, Japan, in September 2013. Based on rigorous peer reviews, the program committee carefully selected 262 revised papers from 789 submissions for presentation in three volumes. The 95 papers included in the first volume have been organized in the following topical sections: physiological modeling and computer-assisted intervention; imaging, reconstruction, and enhancement; registration; machine learning, statistical modeling, and atlases; computer-aided diagnosis and imaging biomarkers; intraoperative guidance and robotics; microscope, optical imaging, and histology; cardiology, vasculatures and tubular structures; brain imaging and basic techniques; diffusion MRI; and brain segmentation and atlases

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013 Part III

International audienceThe three-volume set LNCS 8149, 8150, and 8151 constitutes the refereed proceedings of the 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013, held in Nagoya, Japan, in September 2013. Based on rigorous peer reviews, the program committee carefully selected 262 revised papers from 789 submissions for presentation in three volumes. The 81 papers included in the third volume have been organized in the following topical sections: image reconstruction and motion modeling; machine learning in medical image computing; imaging, reconstruction, and enhancement; segmentation; physiological modeling, simulation, and planning; intraoperative guidance and robotics; microscope, optical imaging, and histology; diffusion MRI; brain segmentation and atlases; and functional MRI and neuroscience applications