The suite of adaptations associated with the extreme stature of the giraffe has long interested biologists and physiologists. By generating a high-quality chromosome-level giraffe genome and a comprehensive comparison with other ruminant genomes, we identified a robust catalog of giraffe-specific mutations. These are primarily related to cardiovascular, bone growth, vision, hearing, and circadian functions. Among them, the giraffe FGFRL1 gene is an outlier with seven unique amino acid substitutions not found in any other ruminant. Gene-edited mice with the giraffe-type FGFRL1 show exceptional hypertension resistance and higher bone mineral density, both of which are tightly connected with giraffe adaptations to high stature. Our results facilitate a deeper understanding of the molecular mechanism underpinning distinct giraffe traits, and may provide insights into the study of hypertension in humans.

In recent years, methods based on photodissociation in the gas phase have become powerful means in the field of chiral analysis. Among them, infrared multiple photon dissociation (IRMPD) spectroscopy is a very attractive one, since it can provide valuable spectral and structural information of chiral complexes in addition to chiral discrimination. Experimentally, the method can be fulfilled by the isolation of target diastereomeric ions in an ion trap followed by the irradiation of a tunable IR laser. Chiral analysis is performed by comparing the difference existing in the spectra of enantiomers. Combined with theoretical calculations, their structures can be further understood on the molecular scale. By now, lots of chiral molecules, including amino acids and peptides, have been studied with the method combined with theoretical calculations. This review summarizes the relative experimental results obtained, and discusses the limitation and prospects of the method.

In recent years, due to the wide implementation of mobile agents, the Internet-of-Things (IoT) networks have been applied in several real-life scenarios, servicing applications in the areas of public safety, proximity-based services, and fog computing. Meanwhile, when more complex tasks are processed in IoT networks, demands on identity authentication, certifiable traceability, and privacy protection for services in IoT networks increase. Building a blockchain system in IoT networks can greatly satisfy such demands. However, the blockchain building in IoT brings about new challenges compared with that in the traditional full-blown Internet with reliable transmissions, especially in terms of achieving consensus on each block in complex wireless environments, which directly motivates our work.In this study, we fully considered the challenges of achieving a consensus in a blockchain system in IoT networks, including the negative impacts caused by contention and interference in wireless channel, and the lack of reliable transmissions and prior network organizations. By proposing a distributed consensus algorithm for blockchains on multi-hop IoT networks, we showed that it is possible to directly reach a consensus for blockchains in IoT networks, without relying on any additional network layers or protocols to provide reliable and ordered communications. In our theoretical analysis, we showed that our consensus algorithm is asymptotically optimal on time complexity and is energy saving. The extensive simulation results also validate our conclusions in the theoretical analysis.

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