• ALGAE
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• v.19 no.2
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• pp.79-90
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• 2004

Nuclear DNA contents of spermatia from eight ceramiacean and four dasyacean algae (Ceramiales, Rhodophyta) and microspores from two land plants were estimated by fluorescence microscopic image processing and their nuclear SSU rDNA sequence data were analyzed. In frequency distribution patterns, the DAPI-stained nuclear volume (NV) of spermatia showed two peaks corresponding to 1C and 2C. Nuclear 2C DNA contents estimated from NV were 0.45-2.31 pg in ceramiacean and 0.40-0.57 pg in dasyacean algae and 8.42-9.51 pg in two land plants, Capsicum annuum and Nicotiana tabacum. By nuclear patterning of vegetative cells derived from an apical cell, 2C DNA contents of spermatia were 2.31 pg in an alga having uninucleate and non-polyploid nucleus (Aglaothamnion callophyllidicola), 0.45-1.94 pg in algae having uninucleate and polyploid nucleus (Antithamnion spp. and Pterothamnion yezoense), and 0.40-0.62 pg in algae having multinucleate and non-polyploid nuclei (Griffithsia japonica and dasyacean algae). Each mature spermatium and microspore (pollen grain) seemed to have a 2C nucleus, which may provide a genetic buffering system to protect the genetic content of a spermatium and microspore from potentially lethal mutations. Nuclear DNA content and SSU rDNA sequence of Antithamnion sparsum from Korea were reasonably different from those of Antithamnion densum from France. The data did not support the previous taxonomic studies that these two taxa could be conspecific.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.76-81
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• 2023

To distinguish cancer cells from normal cells, H&E (Hematoxylin & Eosin) staining is required. Pathological staining requires a lot of money and time. Recently, a digital dyeing method has been introduced to reduce such cost and time. In this paper, we propose a novel digital pathology algorithms. The first algorithm is the Pair method. This method learns the dyed phase image and unstained amplitude image taken by FPM (Fourier Ptychographic Microscopy) and converts it into a dyed amplitude image. The second algorithm is the unpair method. This method use the stained and unstained fluorescence microscopic images for modeling. In this study, digital staining was performed using a generative adversarial network (GAN). From the experimental results, we noticed that both the pair and unpair algorithms shows the excellent performance.