Rationale: Pathological angiogenesis is a critical component of diseases, such as ocular disorders, cancers, and atherosclerosis. It is usually caused by the abnormal activity of biological processes, such as cell proliferation, cell motility, immune, or inflammation response. Long noncoding RNAs (lncRNAs) have emerged as critical regulators of these biological processes. However, the role of lncRNA in diabetes mellitus–induced microvascular dysfunction is largely unknown. Objective: To elucidate whether lncRNA-myocardial infarction–associated transcript (MIAT) is involved in diabetes mellitus–induced microvascular dysfunction. Methods and Results: Using quantitative polymerase chain reaction, we demonstrated increased expression of lncRNA-MIAT in diabetic retinas and endothelial cells cultured in high glucose medium. Visual electrophysiology examination, TUNEL staining, retinal trypsin digestion, vascular permeability assay, and in vitro studies revealed that MIAT knockdown obviously ameliorated diabetes mellitus–induced retinal microvascular dysfunction in vivo, and inhibited endothelial cell proliferation, migration, and tube formation in vitro. Bioinformatics analysis, luciferase assay, RNA immunoprecipitation, and in vitro studies revealed that MIAT functioned as a competing endogenous RNA, and formed a feedback loop with vascular endothelial growth factor and miR-150-5p to regulate endothelial cell function. Conclusions: This study highlights the involvement of lncRNA-MIAT in pathological angiogenesis and facilitates the development of lncRNA-directed diagnostics and therapeutics against neovascular diseases.

Mitochondria are double-membrane organelles with varying shapes influenced by metabolic conditions, developmental stage, and environmental stimuli1–4. Their dynamic morphology is realized through regulated and balanced fusion and fission processes5, 6. Fusion is crucial for the health and physiological functions of mitochondria, including complementation of damaged mitochondrial DNAs and maintenance of membrane potential6–8. Mitofusins (Mfns) are dynamin-related GTPases essential for mitochondrial fusion9, 10. They are embedded in the mitochondrial outer membrane and thought to fuse adjacent mitochondria via concerted oligomerization and GTP hydrolysis11–13. However, the molecular mechanisms behind this process remains elusive. Here we present crystal structures of engineered human Mfn1 containing the GTPase domain and a helical domain in different stages of GTP hydrolysis. The helical domain is composed of elements from widely dispersed sequence regions of Mfn1 and resembles the Neck of the bacterial dynamin-like protein. The structures reveal unique features of its catalytic machinery and explain how GTP binding induces conformational changes to promote G domain dimerization in the transition state. Disruption of G domain dimerization abolishes the fusogenic activity of Mfn1. Moreover, a conserved aspartate trigger was found in Mfn1 to affect mitochondrial elongation, likely through a GTP-loading-dependent domain rearrangement. Based on these results, we propose a mechanistic model for Mfn1-mediated mitochondrial tethering. Our study provides important insights in the molecular basis of mitochondrial fusion and mitofusin-related human neuromuscular disorders14.

Artificial intelligence (AI) is an important technology that supports daily social life and economic activities. It contributes greatly to the sustainable growth of Japan's economy and solves various social problems. In recent years, AI has attracted attention as a key for growth in developed countries such as Europe and the United States and developing countries such as China and India. The attention has been focused mainly on developing new artificial intelligence information communication technology (ICT) and robot technology (RT). Although recently developed AI technology certainly excels in extracting certain patterns, there are many limitations. Most ICT models are overly dependent on big data, lack a self-idea function, and are complicated. In this paper, rather than merely developing nextgeneration artificial intelligence technology, we aim to develop a new concept of general-purpose intelligence cognition technology called "Beyond AI". Specifically, we plan to develop an intelligent learning model called "Brain Intelligence (BI)" that generates new ideas about events without having experienced them by using artificial life with an imagine function. We will also conduct demonstrations of the developed BI intelligence learning model on automatic driving, precision medical care, and industrial robots.

We report the discovery of a series of new drug leads that have potent activity against Mycobacterium tuberculosis as well as against other bacteria, fungi, and a malaria parasite. The compounds are analogues of the new tuberculosis (TB) drug SQ109 (1), which has been reported to act by inhibiting a transporter called MmpL3, involved in cell wall biosynthesis. We show that 1 and the new compounds also target enzymes involved in menaquinone biosynthesis and electron transport, inhibiting respiration and ATP biosynthesis, and are uncouplers, collapsing the pH gradient and membrane potential used to power transporters. The result of such multitarget inhibition is potent inhibition of TB cell growth, as well as very low rates of spontaneous drug resistance. Several targets are absent in humans but are present in other bacteria, as well as in malaria parasites, whose growth is also inhibited.