深卷积神经网络可以检测到具有铁下垂形态的DLBCL细胞。

Pyry Kotkaranta, Mikko Chan, Tero Vuolio, Ilkka Miinalainen, Hanne Kuitunen, Taina Turpeenniemi-Hujanen, Hanna-Riikka Teppo, Outi Kuittinen, Milla E L Kuusisto
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摘要

已经证实弥漫性大b细胞淋巴瘤(DLBCL)对铁下垂特别敏感。目前,确认铁下垂的存在需要流式细胞术,这是一项耗时且劳动密集型的任务。细胞膜起泡已被证明是一种铁中毒特有的形态学变化。在这项研究中,我们开发了一种深度卷积神经网络来检测细胞膜的起泡。与DMSO对照组相比,丁硫氨酸亚砜处理使IKE的起泡细胞百分比从2 %增加到38 % (p 氧化平均值)(345 vs 462, p
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DLBCL cells with ferroptosis morphology can be detected with a deep convolutional neural network.

It has been demonstrated that diffuse large B-cell lymphoma (DLBCL) is especially sensitive to ferroptosis. Currently, confirming the presence of ferroptosis requires flow cytometry, which is a time consuming and labor-intensive task. Blistering of the cell membrane has been shown to be a ferroptosis-specific morphological change. In this study we developed a deep convolutional neural network to detect the blistering of cell membrane. Buthionine sulfoximine treatment increased the percentage of blistering cells from 2 % to 38 % (p < 0.001) when glutathione was deprived from the culture media. Ferrostatin-1 treatment completely reversed the effect. Imidazole ketone erastin (IKE) and auranofin treatment increased blistering cells gradually in dose response manner from 5.4 % to 18.1 % (p < 0.05) and 6.1-50.1 % (p < 0.0001) respectively. We also tested malignant melanoma and breast cancer cell lines to confirm that the blistering phenomena can also be observed in adherent cell lines. We used fluorescence-activated cell sorting to measure the lipid peroxidation associated with ferroptosis and found a significant increase of bodiby-C11oxidized mean compared to DMSO controls for IKE (345 vs 462, p < 0.01) and auranofin (345 vs 686.5, p < 0.05).

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