Exploration of street space architectural color measurement based on street view big data and deep learning-A case study of Jiefang North Road Street in Tianjin.

Urban space architectural color is the first feature to be perceived in a complex vision beyond shape, texture and material, and plays an important role in the expression of urban territory, humanity and style. However, because of the difficulty of color measurement, the study of architectural color in street space has been difficult to achieve large-scale and fine development. The measurement of architectural color in urban space has received attention from many disciplines. With the development and promotion of information technology, the maturity of street view big data and deep learning technology has provided ideas for the research of street architectural color measurement. Based on this background, this study explores a highly efficient and large-scale method for determining architectural colors in urban space based on deep learning technology and street view big data, with street space architectural colors as the research object. We conducted empirical research in Jiefang North Road, Tianjin. We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. Based on K-Means clustering model, we identified the colors of the architectural elements in the street view. The accuracy of the building color measurement results was cross-sectionally verified by means of a questionnaire survey. The validation results show that the method is feasible for the study of architectural colors in street space. Finally, the overall coordination, sequence continuity, and primary and secondary hierarchy of architectural colors of Jiefang North Road in Tianjin were analyzed. The results show that the measurement model can realize the intuitive expression of architectural color information, and also can assist designers in the analysis of architectural color in street space with the guidance of color characteristics. The method helps managers, planners and even the general public to summarize the characteristics of color and dig out problems, and is of great significance in the assessment and transformation of the color quality of the street space environment.

Transcriptomic heterogeneity of cultured ADSCs corresponds to embolic risk in the host.

Stem cell therapy emerges as an effective approach for treating various currently untreatable diseases. However, fatal and unknown risks caused by their systemic use remain to be a major obstacle to clinical application. We developed a functional single-cell RNA sequencing (scRNA-seq) procedure and identified that transcriptomic heterogeneity of adipose-derived stromal cells (ADSCs) in cultures is responsible for a fatal embolic risk of these cells in the host. The pro-embolic subpopulation of ADSCs in cultures was sorted by gene set enrichment analysis (GSEA) and verified by a supervised machine learning analysis. A mathematical model was developed and validated for the prediction of embolic risk of cultured ADSCs in animal models and further confirmed by its application to public data. Importantly, modification of culture conditions prevented the embolic risk. This novel procedure can be applied to other aspects of risk assessment and would help further the development of stem cell clinical applications.

Cardiomyocyte-Specific COMMD1 Deletion Suppresses Ischemia-Induced Myocardial Apoptosis.

Copper metabolism MURR domain 1 (COMMD1) increases in ischemic myocardium along with suppressed contractility. Cardiomyocyte-specific deletion of COMMD1 preserved myocardial contractile function in response to the same ischemic insult. This study was undertaken to test the hypothesis that cardiomyocyte protection in COMMD1 myocardium is responsible for the functional preservation of the heart in response to ischemic insult. After ischemic insult, there were significantly more cardiomyocytes in the cardiomyocyte-specific COMMD1 deletion myocardium than that in WT controls. This preservation of cardiomyocytes was paralleled by a significant suppression of apoptosis in the COMMD1 deletion myocardium compared to controls. In searching for the mechanistic understanding of the anti-apoptotic effect of COMMD1 deletion, we found the anti-apoptotic Bcl-2 mRNA and protein expression were upregulated and the pro-apoptotic Bax mRNA and protein expression were downregulated. The critical transcription factor RelA, maintaining a high ratio between Bcl-2 and Bax for anti-apoptotic action, was suppressed by ischemia, but was rescued in the COMMD1 deletion myocardium. Because COMMD1 is critically involved in RelA ubiquitination and degradation, the data obtained here demonstrate that COMMD1 deletion leads to RelA preservation in ischemic myocardium, promoting the Bcl-2 anti-apoptotic pathway and suppressing the Bax pro-apoptotic pathway, and in combination, leading to protection of cardiomyocytes from ischemia-induced apoptosis.