Optimization of CRISPR-Cas9 system in Eustoma grandiflorum

Li, Xueqi; Bu, Fanqi; Wang, Lishan; Kim, Cholmin; Xue, Wanjie; Zhang, Man; Kawabata, Saneyuki; Zhang, Qingzhu; Li, Yuhua; Zhang, Yang

doi:10.1016/j.isci.2024.109053

iScience

2024

DOI: 10.1016/j.isci.2024.109053

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Optimization of CRISPR-Cas9 system in Eustoma grandiflorum

Xueqi Li,

Fanqi Bu,

Lishan Wang

et al.

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2024

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Cited by 2 publications

References 49 publications

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Classification of Vase Life Day Based on Petal Colorimetric Data in Cut Lisianthus Using AutoML

Kwon,

Heo

2024

Horticulturae

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This study investigated the potential of petal colorimetric data to classify vase life stages in cut lisianthus flowers (Eustoma grandiflorum). We analyzed the changes in the petal color space over time, focusing on the b* value as an indicator of senescence due to increasing yellowing caused by copigmentation. A comparative analysis was conducted between two cultivation methods: soil (S) and hydroponic (H) cultivation. The objective was to evaluate the performance of machine learning models trained to classify vase life stages based on petal color data. Automated machine learning models exhibited better performance in H-cultivated cut flowers, effectively distinguishing days within the vase life stages from Days 1 to 14 for H cultivation. Cut flowers cultivated under S conditions showed less variation in the color space from Days 1 to 9, maintaining a relatively uniform color range. This made it more difficult to distinguish the vase life stages compared to H cultivation. These findings demonstrate that petal color metrics can serve as reliable indicators of cut flower senescence and potentially facilitate nondestructive methods for classifying vase life stages. This technology holds promise for wider applications in the floriculture industry, improving quality control, and extending the vase life of various cut-flower crops.

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Classification of Vase Life Day Based on Petal Colorimetric Data in Cut Lisianthus Using AutoML

Kwon,

Heo

2024

Horticulturae

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Targeted Gene Therapy: Promises and Challenges in Disease Management

Vickram,

Manikandan,

Richard

et al. 2024

J Bio-X Res

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Targeted gene therapy may revolutionize disease treatment by precisely treating genetic defects. This method targets particular cells or tissues with therapeutic genes to treat a variety of genetic problems, including cancer, hereditary diseases, and viral infections. Viral, nonviral, and genome editing techniques such as CRISPR-Cas9 are used for targeted gene therapy to fix or modify disease-causing genes with minimal off-target effects. The issues of vector immunogenicity, off-target mutations, and gene delivery to target cells persist despite tremendous progress. The successful implementation of targeted gene therapy is further hindered by hereditary illness complexity and genetic background diversity. These difficulties require multidisciplinary cooperation, novel vector design, and thorough preclinical and clinical assessments. The long-term and unforeseen effects of gene editing must also be considered from an ethical viewpoint. Targeted gene therapy has considerable therapeutic promise, but more research and technological advances are needed to overcome limitations and develop safe and successful clinical treatments.

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Optimization of CRISPR-Cas9 system in Eustoma grandiflorum

Cited by 2 publications

References 49 publications

Classification of Vase Life Day Based on Petal Colorimetric Data in Cut Lisianthus Using AutoML

Classification of Vase Life Day Based on Petal Colorimetric Data in Cut Lisianthus Using AutoML

Targeted Gene Therapy: Promises and Challenges in Disease Management

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