Bio-based P-N flame retardant with ZIF-67 in-situ growth on flexible polyurethane foam with excellent fire safety performance.

The wide application of flexible polyurethane foam (FPUF) poses a giant challenge to human society in terms of fire prevention and environmental pollution. To solve this problem, the lignocellulose-based P-N flame retardant (LFPN) has been developed using mechanochemical methods. It was found that FPUF treated using LFPN exhibited good flame retardancy, but suffered from high smoke generation and toxicity. The hollow dodecahedral ZIF-67 has been used for smoke suppression catalysis, but the agglomeration phenomenon makes it inefficient. Hence, in this study, the adhesive properties of polydopamine (PDA) were utilized to assist the in-situ growth of ZIF-67. The results showed that the total smoke release rate of the treated FPUF was reduced by 40.5%. The toxic gases, such as carbon monoxide (CO), hydrogen cyanide, etc., also showed the same decreasing trend. What's more, the catalytic effect of ZIF-67 itself and the synergistic effect with LFPN gave FPUF great flame retardant and smoke inhibition properties. This novel FPUF provides a new reference for achieving smoke suppression and toxicity reduction.

Enabling AI in synthetic biology through Construction File specification.

The Construction File (CF) specification establishes a standardized interface for molecular biology operations, laying a foundation for automation and enhanced efficiency in experiment design. It is implemented across three distinct software projects: PyDNA_CF_Simulator, a Python project featuring a ChatGPT plugin for interactive parsing and simulating experiments; ConstructionFileSimulator, a field-tested Java project that showcases 'Experiment' objects expressed as flat files; and C6-Tools, a JavaScript project integrated with Google Sheets via Apps Script, providing a user-friendly interface for authoring and simulation of CF. The CF specification not only standardizes and modularizes molecular biology operations but also promotes collaboration, automation, and reuse, significantly reducing potential errors. The potential integration of CF with artificial intelligence, particularly GPT-4, suggests innovative automation strategies for synthetic biology. While challenges such as token limits, data storage, and biosecurity remain, proposed solutions promise a way forward in harnessing AI for experiment design. This shift from human-driven design to AI-assisted workflows, steered by high-level objectives, charts a potential future path in synthetic biology, envisioning an environment where complexities are managed more effectively.

Female Users' TikTok Use and Body Image: Active Versus Passive Use and Social Comparison Processes.

This study examined two ways of using the TikTok application (active vs. passive use), and their association with female users' self-esteem pertaining to appearance and weight. By adopting a cross-sectional online survey design, this study recruited 7,750 adult female TikTok users from China (Douyin), and acquired self-reported data on 2 ways of using TikTok, state-level social comparison, appearance-esteem, weight-esteem, body mass index, and age. The results indicated that passive and active TikTok uses were negatively and positively associated with participants' appearance- and weight-esteem, respectively. A mediation analysis revealed that the participants' state-level social comparison while using TikTok mediated the association between two ways of TikTok use, and their effects on appearance- and weight-esteem. These results help us understand the complicated impact of TikTok use on body image, and design campaigns for promoting body acceptance.