Abstract:The pulse-based charging method for battery cells has been recognized as a fast and efficient way to overcome the shortcoming of a slow charging time in distributed battery cells, which is regarded as a connection of cells such as the Internet of Things (IoT). The pulse frequency for controlling the battery charge duration is dynamically controlled within a certain range in order to inject the maximum charge current into the battery cells. The optimal frequency is determined in order to minimize battery impedance. The adaptation of the proposed pulse duty and frequency decreases the concentration of the polarization by sensing the runtime characteristics of battery cells so that it guarantees a certain level of safety in charging the distributed battery cells within the operating temperature range of 5-45 • C. The sensed terminal voltage and temperature of battery cells are dynamically monitored while the battery is charging so as to adjust the frequency and duty of the proposed charging pulse method, thereby preventing battery degradation. The evaluation results show that a newly designed charging algorithm for the implemented charger system is about 18.6% faster than the conventional constant-current (CC) charging method with the temperature rise within a reasonable range. The implemented charger system, which is based on the proposed dynamic frequency and duty control by considering the cell polarization, charges to about 80% of its maximum capacity in less than 56 min and involves a 13 • C maximum temperature rise without damaging the battery.
Noncovalent interactions between cells and environmental cues have been recognized as fundamental physiological interactions that regulate cell behavior. However, the effects of the covalent interactions between cells and biomaterials on cell behavior have not been examined. Here, we demonstrate a combined strategy based on covalent conjugation between biomaterials (collagen fibers/lipid nanoparticles) and various cells (exogenous neural progenitor cells/astrocytes/endogenous tissue-resident cells) to promote neural regeneration after spinal cord injury (SCI). We found that metabolic azido-labeled human neural progenitor cells conjugated on dibenzocyclooctyne-modified collagen fibers significantly promoted cell adhesion, spreading, and differentiation compared with noncovalent adhesion. In addition, dibenzocyclooctyne-modified lipid nanoparticles containing edaravone, a well-known ROS scavenger, could target azide-labeled spinal cord tissues or transplanted azide-modified astrocytes to improve the SCI microenvironment. The combined application of these covalent conjugation strategies in a rat SCI model boosted neural regeneration, suggesting that the covalent interactions between cells and biomaterials have great potential for tissue regeneration.
The growth rate of bacteria increases under simulated microgravity (SMG) with lowshear force. The next-generation microbial chassis Vibrio natriegens (V. natriegens) is a fast-growing Gram-negative, non-pathogenic bacterium with a generation time of less than 10 min. Screening of a V. natriegens strain with faster growth rate was attempted by 2-week continuous long-term culturing under SMG. However, the rapid growth rate of this strain made it difficult to obtain the desired mutant strain with even more rapid growth. Thus, a mutant with slower growth rate emerged. Multi-omics integration analysis was conducted to explore why this mutant grew more slowly, which might inform us about the molecular mechanisms of rapid growth of V. natriegens instead. The transcriptome data revealed that whereas genes related to mechanical signal transduction and flagellin biogenesis were up-regulated, those involved in adaptive responses, anaerobic and nitrogen metabolism, chromosome segregation and cell vitality were down-regulated. Moreover, genome-wide chromosome conformation capture (Hi-C) results of the slower growth mutant and wide type indicated that SMG-induced great changes of genome 3D organization were highly correlated with differentially expressed genes (DEGs). Meanwhile, whole genome re-sequencing found a significant number of structure variations (SVs) were enriched in regions with lower interaction frequency and down-regulated genes in the slower growth mutant compared with wild type (WT), which might represent a prophage region. Additionally, there was also a decreased interaction frequency in regions associated with well-orchestrated chromosomes replication. These results suggested that SMG might regulate local gene expression by sensing stress changes through conformation changes in the genome region of genes involved in flagellin, adaptability and chromosome segregation, thus followed by alteration of some physiological characteristics and affecting the growth rate and metabolic capacity.
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