Carbon materials and their allotropes have been involved significantly in our daily lives. Zero‐dimensional (0D) fullerenes, one‐dimensional (1D) carbon materials, and two‐dimensional (2D) graphene materials have distinctive properties and thus received immense attention from the early 2000s. To meet the growing demand for these materials in applications like energy storage, electrochemical catalysis, and environmental remediation, the special category, i.e., three‐dimensional (3D) structures assembled from graphene sheets, has been developed. Graphene oxide is a chemically altered graphene, the desired building block for 3D graphene matter (i.e., 3D graphene macrostructures). A simple synthesis route and pore morphologies make 3D reduced‐graphene oxide (rGO) a major candidate for the 3D graphene group. To obtain target‐specific 3D rGO, its synthesis mechanism plays an important role. Hence, in this article, we will discuss the general mechanism for 3D rGO synthesis, vital procedures for fabricating advanced 3D rGO, and important aspects controlling the growth of 3D rGO.

Molecular analyses of soil and water commonly reveal large proportions of fungal taxa that cannot be assigned to any taxonomic or functional groups. Some of these so-called dark taxa have been encoded alphanumerically, while others have remained completely overlooked. Using long-read sequencing that covers much of the ribosomal RNA operon, we shed light on the phylogenetic and ecological distribution of fungal dark taxa and formally describe 30 of the most prominent phylum- to order-level lineages based on their characteristic DNA features. This increases the known large-scale fungal phylogenetic diversity by roughly one-third. Formal names will enhance taxonomic reproducibility, facilitate communication among researchers, and enable the estimation of conservation and quarantine needs for uncultivable species and higher-ranking taxa. The new species in the respective highest-level novel taxonomic groups include Pantelleria saittana (Pantelleriomycetes), Paraspizellomyces parrentiae (Paraspizellomycetales), Aquieurochytrium lacustre (Aquieurochytriomycetes), Edaphochytrium valuojaense (Edaphochytriomycetes), Tibetochytrium taylorii (Tibetochytriomycetes), Tropicochytrium toronegroense (Tropicochytriomycetes), Algovorax scenedesmi (comb. nov.) and Solivorax pantropicus (Algovoracomycetes), Aquamastix sanduskyensis (Aquamastigomycetes), Cantoromastix holarctica (Cantoromastigomycetes), Dobrisimastix vlkii (Dobrisimastigomycetes), Palomastix lacustris (Palomastigomycetes), Sedimentomastix tueriensis (Sedimentomastigomycetes), Terrincola waldropii (Terrincolales), Curlevskia holarctica (Curlevskiomycota), Mycosocceria estonica (Mycosocceriales), Maerjamyces jumpponenii (Maerjamycetes), Ruderalia cosmopolita (Ruderaliomycetes), Bryolpidium mundanum (Bryolpidiomycetes), Chthonolpidium enigmatum (Chthonolpidiomycetes), Savannolpidium raadiense (Savannolpidiomycetes), Gelotisporidium boreale (Gelotisporidiomycetes), Sumavosporidium sylvestre (Sumavosporidiomycetes), Parakickxella borikenica (Parakickxellomycetes), Aldinomyces tarquinii (Aldinomycota), Borikenia urbinae (Borikeniomycota), Mirabilomyces abrukanus (Mirabilomycota), Nematovomyces vermicola (comb. nov.) and N. soinasteënsis (Nematovomycota), Viljandia globalis (Viljandiomycota), Waitukubulimyces cliftonii (Waitukubulimycota), and Tartumyces setoi (Tartumyceta).

Mojde Moradi-Pour, Roohallah Saberi-Riseh, Keyvan Esmaeilzadeh-Salestani, Reza Mohammadinejad, and Evelin Loit. J. Microbiol. Biotechnol. 2021;31:1373-82. https://doi.org/10.4014/jmb.2105.05001

Combining chemotherapeutic (CT) and chemopreventive (CP) agents for cancer treatment is controversial, and the issue has not yet been conclusively resolved. In this study, by integrating text mining and protein-protein interaction (PPI), the combined effects of these two kinds of agents in cancer treatment were investigated. First, text mining was performed by the Pathway Studio database to study the effects of various agents (CP and CT) on cancer-related processes. Then, each group’s most important hub genes were obtained by calculating different centralities. Finally, the results of in silico analysis were validated by examining the combined effects of hesperetin (Hst) and vincristine (VCR) on MCF-7 cells. In general, the results of the in silico analysis revealed that the combination of these two kinds of agents could be useful for treating cancer. However, the PPI analysis revealed that there were a few important proteins that could be targeted for intelligent therapy while giving treatment with these agents. In vitro experiments confirmed the results of the in silico analysis. Also, Hst and VCR had good harmony in modulating the hub genes obtained from the in silico analysis and inducing apoptosis in the MCF-7 cell line.