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Sharing successful practices with other stakeholders is important for achieving SDGs. In this study, with a deep-learning natural language processing model, bidirectional encoder representations from transformers (BERT), the authors aimed to build (1) a classifier that enables semantic mapping of practices and issues in the SDGs context, (2) a visualizing method of SDGs nexus based on co-occurrence of goals (3) a matchmaking process between local issues and initiatives that may embody solutions. A data frame was built using documents published by official organizations and multi-labels corresponding to SDGs. A pretrained Japanese BERT model was fine-tuned on a multi-label text classification task, while nested cross-validation was conducted to optimize the hyperparameters and estimate cross-validation accuracy. A system was then developed to visualize the co-occurrence of SDGs and to couple the stakeholders by evaluating embedded vectors of local challenges and solutions. The paper concludes with a discussion of four future perspectives to improve the natural language processing system. This intelligent information system is expected to help stakeholders take action to achieve the sustainable development goals.

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Genetic cardiomyopathy is a group of intractable cardiovascular disorders involving heterogeneous genetic contribution. This heterogeneity has hindered the development of life-saving therapies for this serious disease. Genetic mutations in dystrophin and its associated glycoproteins cause cardiomuscular dysfunction. Large animal models incorporating these genetic defects are crucial for developing effective medical treatments, such as tissue regeneration and gene therapy. In the present study, we knocked out the δ-sarcoglycan (δ-SG) gene (SGCD) in domestic pig by using a combination of efficient de novo gene editing and somatic cell nuclear transfer. Loss of δ-SG expression in the SGCD knockout pigs caused a concomitant reduction in the levels of α-, β-, and γ-SG in the cardiac and skeletal sarcolemma, resulting in systolic dysfunction, myocardial tissue degeneration, and sudden death. These animals exhibited symptoms resembling human genetic cardiomyopathy and are thus promising for use in preclinical studies of next-generation therapies.