Rice (Oryza sativa L.) is an important food crop. The appearance of lesion mimics in rice leads to phytohormone disorders, which affects rice adaptation to environmental stresses and ultimately reduces the yield and quality. To explore whether the changes in the adaptability of rice lesion-mimic mutants to stressful environments are caused by the disorder of phytohormone metabolism in plants. In this study, we screened an ethyl methane sulfonate-treated population of the japonica cultivar 'Taipei 309' for a mutant with rust-like spots on leaves at the early tillering stage and brown-red spots at maturity and named it rsl1 (rust spotted leaf 1). Compared with the wild type, rsl1 showed decreases in plant height, panicle length, primary branch number, secondary branch number, filled grains per panicle, seed-setting rate, and 1 000-grain weight, and an increase in number of effective panicles. Genetic analysis indicated that rsl1 was controlled by a single recessive nuclear gene. RSL1 was localized between two molecular markers, B7-7 and B7-9, on rice chromosome 7 by map-based cloning. PCR sequencing of the annotated genes in this interval revealed a mutation of C1683A on the eighth exon of SPL5 (LOC_Os07g10390) in rsl1, which resulted in premature termination of protein translation. Exogenous phytohormone treatments showed that rsl1 was less sensitive to salicylic acid (SA), abscisic acid (ABA), and indo-3-acetic acid (IAA) and more sensitive to methyl jasmonate (MeJA) and gibberellin acid (GA) than the wild type. In addition, the survival rate of rsl1 was lower than that of the wild type under salt, alkali, drought, and high temperature stresses, and it was higher than that of the wild type under cold stress. Quantitative real-time polymerase chain reaction (qRT-PCR) results showed that RSL1 was involved in the regulation of ABA, SA, MeJA, IAA, and GA-related genes under abiotic stresses. The present study showed that the RSL1 mutation led to the appearance of lesion mimics and affected the growth, development, and stress resistance of rsl1 under abiotic stresses. The study of the functional mechanism of this gene can provide theoretical guidance for the research on rice stress resistance.
Oryza/microbiology* ; Stress, Physiological/genetics* ; Plant Diseases/genetics* ; Cloning, Molecular ; Chromosome Mapping ; Plant Growth Regulators/metabolism* ; Plant Proteins/genetics* ; Mutation ; Cyclopentanes ; Genes, Plant ; Plant Leaves/genetics* ; Oxylipins

Artificial intelligence (AI), a branch of computer science, is an emerging science used to develop theories, methods, technologies and application systems that can simulate human intelligence. The goal is to enable machines to solve some complex tasks that require human intelligence. With the era of big data coming, AI has been widely used in multitudinous professional fields, including machine vision, speech recognition, image understanding, genetic programming, intelligent factory and expert systems. As the most common three-dimensional deformity of the spine, scoliosis not only changes patients' appearance and body shape but also affects their mental health. Some challenges have to be solved in diagnosis and treatment of scoliosis, such as the complexity of the anatomical structure of the spine, the importance of maintaining the posture, and the long learning-curve of spine specialty. Additionally, some aspects, such as heavy workload, fatigue, high misdiagnosis rate and missed diagnosis rate, are prone to occur in large-scale scoliosis screening and diagnosis. Researchers have discovered that AI can learn inherent laws and representation of sample data in recent years. AI technology has been used in clinical practice, such as screening, diagnosis, surgical decision-making, intraoperative operation, prognosis prediction and conservative interventions. However, AI technology has serious limitations currently. There are many disadvantages in diagnosis and treatment of scoliosis, including irregular data collection, technical difficulty, inherent defects of AI, overdependency on AI, legal and ethics issues. Thus, summarizing the relevant trends and application of AI in the diagnosis and treatment of scoliosis is still required by using the literature database and data-sharing network. The aim of the present review is to provide a glimpse into the future applications of AI.