Prompt-based Grouping Transformer for Nucleus Detection and Classification

Automatic nuclei detection and classification can produce effective information for disease diagnosis. Most existing methods classify nuclei independently or do not make full use of the semantic similarity between nuclei and their grouping features. In this paper, we propose a novel end-to-end nuclei detection and classification framework based on a grouping transformer-based classifier. The nuclei classifier learns and updates the representations of nuclei groups and categories via hierarchically grouping the nucleus embeddings. Then the cell types are predicted with the pairwise correlations between categorical embeddings and nucleus features. For the efficiency of the fully transformer-based framework, we take the nucleus group embeddings as the input prompts of backbone, which helps harvest grouping guided features by tuning only the prompts instead of the whole backbone. Experimental results show that the proposed method significantly outperforms the existing models on three datasets.Comment: MICCAI 2023, released code: https://github.com/lhaof/PG

A Deep Learning-Based System (Microscan) for the Identification of Pollen Development Stages and Its Application to Obtaining Doubled Haploid Lines in Eggplant

[EN] The development of double haploids (DHs) is a straightforward path for obtaining pure lines but has multiple bottlenecks. Among them is the determination of the optimal stage of pollen induction for androgenesis. In this work, we developed Microscan, a deep learning-based system for the detection and recognition of the stages of pollen development. In a first experiment, the algorithm was developed adapting the RetinaNet predictive model using microspores of different eggplant accessions as samples. A mean average precision of 86.30% was obtained. In a second experiment, the anther range to be cultivated in vitro was determined in three eggplant genotypes by applying the Microscan system. Subsequently, they were cultivated following two different androgenesis protocols (Cb and E6). The response was only observed in the anther size range predicted by Microscan, obtaining the best results with the E6 protocol. The plants obtained were characterized by flow cytometry and with the Single Primer Enrichment Technology high-throughput genotyping platform, obtaining a high rate of confirmed haploid and double haploid plants. Microscan has been revealed as a tool for the high-throughput efficient analysis of microspore samples, as it has been exemplified in eggplant by providing an increase in the yield of DHs production.This research was funded by the Spanish Ministerio de Ciencia, Innovacion y Universidades, Agencia Estatal de Investigacion and Fondo Europeo de Desarrollo Regional (grant RTI-2018-094592-B-I00 from MCIU/AEI/FEDER, UE). This work was also undertaken as part of the initiative "Adapting Agriculture to Climate Change: Collecting, Protecting and Preparing Crop Wild Relatives", which is supported by the Government of Norway. The project is managed by the Global Crop Diversity Trust with the Millennium Seed Bank of the Royal Botanic Gardens, Kew, and implemented in partnership with national and international gene banks and plant breeding institutes around the world. For further information, see the project website: http://www.cwrdiversity.org/.The Spanish Ministerio de Educacion, Cultura y Deporte funded a predoctoral fellowship granted to Edgar Garcia-Fortea (FPU17/02389).García-Fortea, E.; García-Pérez, A.; Gimeno -Páez, E.; Sánchez-Gimeno, A.; Vilanova Navarro, S.; Prohens Tomás, J.; Pastor-Calle, D. (2020). A Deep Learning-Based System (Microscan) for the Identification of Pollen Development Stages and Its Application to Obtaining Doubled Haploid Lines in Eggplant. Biology. 9(9):1-19. https://doi.org/10.3390/biology9090272S11999Prohens, J., Gramazio, P., Plazas, M., Dempewolf, H., Kilian, B., Díez, M. J., … Vilanova, S. (2017). 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Methods in Molecular Biology, 1-11. doi:10.1007/978-1-0716-0672-8_1Bologna-Molina, R., Damián-Matsumura, P., & Molina-Frechero, N. (2011). An easy cell counting method for immunohistochemistry that does not use an image analysis program. Histopathology, 59(4), 801-803. doi:10.1111/j.1365-2559.2011.03954.xChoudhry, P. (2016). High-Throughput Method for Automated Colony and Cell Counting by Digital Image Analysis Based on Edge Detection. PLOS ONE, 11(2), e0148469. doi:10.1371/journal.pone.0148469Du, Li, X., & Li, Q. (2019). Detection and Classification of Cervical Exfoliated Cells Based on Faster R-CNN*. 2019 IEEE 11th International Conference on Advanced Infocomm Technology (ICAIT). doi:10.1109/icait.2019.8935931Chowdhury, A. B., Roberson, J., Hukkoo, A., Bodapati, S., & Cappelleri, D. J. (2020). Automated Complete Blood Cell Count and Malaria Pathogen Detection Using Convolution Neural Network. 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H., & Houben, A. (2019). Analysis of Pollen Grains by Immunostaining and FISH in Triticeae Species. Plant Meiosis, 347-358. doi:10.1007/978-1-4939-9818-0_24James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning. Springer Texts in Statistics. doi:10.1007/978-1-4614-7138-7García-Fortea, E., Lluch-Ruiz, A., Pineda-Chaza, B. J., García-Pérez, A., Bracho-Gil, J. P., Plazas, M., … Prohens, J. (2020). A highly efficient organogenesis protocol based on zeatin riboside for in vitro regeneration of eggplant. BMC Plant Biology, 20(1). doi:10.1186/s12870-019-2215-yDUMAS DE VAULX, R., CHAMBONNET, D., & POCHARD, E. (1981). Culture in vitro d’anthères de piment (Capsicum annuum L.) : amélioration des taux d’obtention de plantes chez différents génotypes par des traitements à + 35 °C. Agronomie, 1(10), 859-864. doi:10.1051/agro:19811006Dpooležel, J., Binarová, P., & Lcretti, S. (1989). Analysis of Nuclear DNA content in plant cells by Flow cytometry. 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An Investigation of the Cellular Stress Response in Cells Infected With Herpes Simplex Virus

This study entailed an investigation of the cellular stress response in secondary chick embryo fibroblasts (CEF) during infection by HSV. It was established that infections at a+ NPT with temperature-sensitive mutants of HSV-1 which are defective in immediate-early viral polypeptide Vmw IE 175 (i.e. tsD, tsK and tsT) cause the stress response to be induced, as manifest by a marked stimulation of synthesis of stress proteins. Induction by tsK was shown to be dependent upon the synthesis of immediate-early viral polypeptides. Infections with other mutants of HSV-1 (tsl201, tsB, tsE, tsG and MDK/2) at a NPT and, to a lesser extent, the revertant of tSK, ts+K, or with wt HSV-1 or wt HSV-2, all of which are non-defective in Vmw IE 175 or the HSV-2 equivalent, Vmw IE 182, cause synthesis of stress proteins to be increased. To account for these observations a hypothesis was advanced, that cells are subjected to stress during infection with wt or mutant HSV, owing to the expresssion of viral functions, and that induction of the stress response is subsequently inhibited depending upon the characteristics of the infecting virus: inhibition is most effective in cells infected with wt viruses, and least effective in cells infected at a NPT with temperature-sensitive mutants of HSV-1 defective in Vmw IE 175

5.Uluslararası Öğrenciler Fen Bilimleri Kongresi Tam Metin Kitabı

Çevrimiçi (IX, 431 Sayfa; 26 cm.)

Microscopy Conference 2021 (MC 2021) - Proceedings

Das Dokument enthält die Kurzfassungen der Beiträge aller Teilnehmer an der Mikroskopiekonferenz "MC 2021"

Biotechnology to Combat COVID-19

This book provides an inclusive and comprehensive discussion of the transmission, science, biology, genome sequencing, diagnostics, and therapeutics of COVID-19. It also discusses public and government health measures and the roles of media as well as the impact of society on the ongoing efforts to combat the global pandemic. It addresses almost every topic that has been studied so far in the research on SARS-CoV-2 to gain insights into the fundamentals of the disease and mitigation strategies. This volume is a useful resource for virologists, epidemiologists, biologists, medical professionals, public health and government professionals, and all global citizens who have endured and battled against the pandemic