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The carbon emissions of modern information and communication technologies (ICT) present a significant environmental challenge, accounting for approximately 4% of global greenhouse gases, and are on par with the aviation industry. Modern internet services levy high carbon emissions due to the significant infrastructure resources required to operate them, owing to strict service requirements expected by users. One opportunity to reduce emissions is relaxing strict service requirements by leveraging eco-feedback. In this study, we explore the effect of the carbon reduction impact of allowing longer internet service response time based on user preferences and feedback. Across four services (i.e., Amazon, Google, ChatGPT, Social Media) our study reveals opportunities to relax latency requirements of services based on user feedback; this feedback is application-specific, with ChatGPT having the most favorable eco-feedback tradeoff. Further system studies suggest leveraging the reduced latency can bring down the carbon footprint of an average service request by 93.1%. 

The blood-brain barrier (BBB) is a dynamic interface that regulates the molecular exchanges between the brain and peripheral blood. The permeability of the BBB is primarily regulated by the junction proteins on the brain endothelial cells. In vitro BBB models have shown great potential for the investigation of the mechanisms of physiological function, pathologies, and drug delivery in the brain. However, few studies have demonstrated the ability to monitor and evaluate the barrier integrity by quantitatively analyzing the junction presentation in 3D microvessels. This study aimed to fabricate a simple vessel-on-chip, which allows for a rigorous quantitative investigation of junction presentation in 3D microvessels. To this end, we developed a rapid protocol that creates 3D microvessels with polydimethylsiloxane and microneedles. We established a simple vessel-on-chip model lined with human iPSC-derived brain microvascular endothelial-like cells (iBMEC-like cells). The 3D image of the vessel structure can then be “unwrapped” and converted to 2D images for quantitative analysis of cell–cell junction phenotypes. Our findings revealed that 3D cylindrical structures altered the phenotype of tight junction proteins, along with the morphology of cells. Additionally, the cell–cell junction integrity in our 3D models was disrupted by the tumor necrosis factor α. This work presents a “quick and easy” 3D vessel-on-chip model and analysis pipeline, together allowing for the capability of screening and evaluating the cell–cell junction integrity of endothelial cells under various microenvironment conditions and treatments.