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Molecular hydrogen (hydrogen gas; H2) is gaining prominence in the scientific literature as well as the popular media. Early studies suggest the use of H2 treatment for a wide range of human diseases, from COVID-19 to various neurodegenerative diseases. Moreover, its biological activity also appears to have therapeutic and regulatory effects in plants. Accordingly, it has been suggested to be useful in agricultural settings. H2 has effects on a range of physiological events in plants. It has been shown to have effects on seed germination, plant growth, and development. It has also been found to be involved in plant stress responses and to be protective against abiotic stress. It also has beneficial effects during the post-harvest storage of crops. Therefore, its use in the agricultural setting has great potential as it appears to be safe, with no toxicity or harm to the environment. One of the conundrums of the use of H2 is how it induces these effects in plants and plant cells. It is difficult to envisage how it works based on a classical receptor mechanism. There is evidence that it may act as a direct antioxidant, by scavenging hydroxyl radicals, or via enhancing the plant’s innate antioxidant system as a signaling molecule. It has also been reported to exert effects through action on heme oxygenase, cross-talk with other signaling molecules, and regulating the expression of various genes. However, how H2 fits into, and integrates with, other signaling pathways is not clearly understood. Future work is needed to elucidate the mechanism and significance of the interaction of H2 with these and other cellular systems.

antioxidants --- heme oxygenase --- hydrogen gas --- hydrogenase --- hydroxyl radicals --- molecular hydrogen --- nitric oxide --- reactive oxygen species --- Chinese chive --- storage quality --- antioxidant capacity --- hydrogen nanobubble water --- vase life --- senescence-associated enzymes --- cut carnation flowers --- glucosamine --- sucrose --- starch --- gene expression --- sugar metabolism --- amylose --- cadmium --- field quality --- hydrogen-based agriculture --- rice --- Wuzhimaotao (Ficus hirta Vahl) --- hydrogen --- transcription factors --- secondary metabolism --- phytohormones signaling pathways --- phenylpropanoid biosynthesis and metabolism --- Chinese herbal medicine --- carbendazim degradation --- glutathione metabolism --- detoxification system --- redox balance --- cut flower --- flower industry --- postharvest quality --- postharvest technique --- the fourth industrial revolution --- n/a

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As the amount of biological and its diversity accumulates massively there is a critical need to facilitate the integration of this data to allow new and unexpected conclusions to be drawn from it. The Semantic Web is a new wave of web-based technologies that allows the linking of data between diverse data sets via standardised data formats ("big data"). Semantic Biology is the application of semantic web technology in the biological domain (including medical and health informatics). The Special Topic welcomes papers in this very broad area, including not only ontologies (development and applications), but also text mining, data integration and data analysis making use of the technologies of the Semantic Web. Ontologies are a critical requirement for such integration as they allow conclusions drawn about biological experiments, or descriptions of biological entities, to be understandable and integratable despite being contained in different databases and analysed by different software systems. Ontologies are the standard structures used in biology, and more broadly in computer science, to hold standardized terminologies for particular domains of knowledge. Ontologies consist of sets of standard terms, which are defined and may have synonyms for ease of searching and to accommodate different usages by different communities. These terms are linked by standard relationships, such as “is a” (an eye “is a” sense organ) or “part of” (an eye is “part of” a head). By linking terms in this way, more detailed, or granular, terms can be linked to broader terms, allowing computation to be carried out that takes these relationships into account.

Telecommunications --- Electrical & Computer Engineering --- Engineering & Applied Sciences --- Semantic Web --- data representation --- data analysis --- ontologies --- semantic biology