Thanks to the precise control over their structural and functional properties, genetically engineered protein-based hydrogels have emerged as a promising candidate for biomedical applications. Given the growing demand for creating stimuli-responsive "smart" hydrogels, here we show the synthesis of entirely protein-based photoresponsive hydrogels by covalently polymerizing the adenosylcobalamin (AdoB 12 )-dependent photoreceptor C-terminal adenosylcobalamin binding domain (CarH C ) proteins using genetically encoded SpyTagSpyCatcher chemistry under mild physiological conditions. The resulting hydrogel composed of physically self-assembled CarH C polymers exhibited a rapid gel-sol transition on light exposure, which enabled the facile release/recovery of 3T3 fibroblasts and human mesenchymal stem cells (hMSCs) from 3D cultures while maintaining their viability. A covalently cross-linked CarH C hydrogel was also designed to encapsulate and release bulky globular proteins, such as mCherry, in a light-dependent manner. The direct assembly of stimuli-responsive proteins into hydrogels represents a versatile strategy for designing dynamically tunable materials.hydrogels | cell encapsulation | drug delivery | photoresponsive materials | protein engineering
Objective To compare the medicines included in national essential medicines lists with the World Health Organization’s (WHO’s) Model list of essential medicines , and assess the extent to which countries’ characteristics, such as WHO region, size and health care expenditure, account for the differences. Methods We searched the WHO’s Essential Medicines and Health Products Information Portal for national essential medicines lists. We compared each national list of essential medicines with both the 2017 WHO model list and other national lists. We used linear regression to determine whether differences were dependent on WHO Region, population size, life expectancy, infant mortality, gross domestic product and health-care expenditure. Findings We identified 137 national lists of essential medicines that collectively included 2068 unique medicines. Each national list contained between 44 and 983 medicines (median 310: interquartile range, IQR: 269 to 422). The number of differences between each country’s essential medicines list and WHO’s model list ranged from 93 to 815 (median: 296; IQR: 265 to 381). Linear regression showed that only WHO region and health-care expenditure were significantly associated with the number of differences (adjusted R 2 : 0.33; P < 0.05). Most medicines (1248; 60%) were listed by no more than 10% (14) of countries. Conclusion The substantial differences between national lists of essential medicines are only partly explained by differences in country characteristics and thus may not be related to different priority needs. This information helps to identify opportunities to improve essential medicines lists.
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