Y chromosome represents masculinization. The extra Y chromosome of XYY patients usually leads to over-masculinization phenotypes. The occurrence of several DSD cases with XYY in blood is controversial. Is XYY associated with disorder of sex development (DSD)? What is the mechanism behind DSD in males with XYY in blood? To this end, this study retrospectively analyzed blood-karyotype data of 4,437 DSD male children and karyotypes data of 6,259 newborn males as the control. Exome sequencing (ES) was performed to test whether the patients with DSD and with XYY in blood had other variants on known DSD-genes. Testicular biopsy was performed. Fluorescence in situ hybridization (FISH) was used to test whether a sex chromosome mosaicism was present in the oral epithelial cells or gonad tissue of patients with DSD and with XYY in blood. learn more Among 4,437 DSD males who received cytogenetic evaluation, 14 patients with 47,XYY were identified. By contrast, five individuals among the 6,259 controls had 47,XYY. XYY in blood is more frequent among males with DSD than in other males (p = 0.004). The XYY karyotypes were confirmed again by GTG-banding in blood samples and by FISH performed on oral epithelial cells. ES on seven XYY DSD patients was successfully performed, but results did not identify any pathogenic variant on 55 known DSD genes. Gonad biopsy (n = 3) revealed testicular dysplasia and true hermaphroditism. FISH of gonad tissues (n = 3) showed that all of the samples had mosaic for X/XY/XYY. This study is the first to investigate the relationship between XYY in blood and DSD. The knowledge that XYY is in the blood and in oral cells have X/XY/XYY mosaicism in gonadal tissue is new for both researchers and clinicians who seek to understand the genetic basis of DSD males.With the progress of medical technology, biomedical field ushered in the era of big data, based on which and driven by artificial intelligence technology, computational medicine has emerged. People need to extract the effective information contained in these big biomedical data to promote the development of precision medicine. Traditionally, the machine learning methods are used to dig out biomedical data to find the features from data, which generally rely on feature engineering and domain knowledge of experts, requiring tremendous time and human resources. Different from traditional approaches, deep learning, as a cutting-edge machine learning branch, can automatically learn complex and robust feature from raw data without the need for feature engineering. The applications of deep learning in medical image, electronic health record, genomics, and drug development are studied, where the suggestion is that deep learning has obvious advantage in making full use of biomedical data and improving medical health level. Deep learning plays an increasingly important role in the field of medical health and has a broad prospect of application. However, the problems and challenges of deep learning in computational medical health still exist, including insufficient data, interpretability, data privacy, and heterogeneity. Analysis and discussion on these problems provide a reference to improve the application of deep learning in medical health.Leaf senescence is an integrated response of the cells to develop age information and various environmental signals. Thus, some of the genes involved in the response to environmental changes are expected to regulate leaf senescence. Light acts not only as the primary source of energy for photosynthesis but also as an essential environmental cue that directly control plant growth and development including leaf senescence. The molecular mechanisms linking light signaling to leaf senescence have recently emerged, exploring the role of Phytochrome-Interacting Factors (PIFs) as a central player leading to diverse senescence responses, senescence-promoting gene regulatory networks (GRNs) involving PIFs, and structural features of transcription modules in GRNs. The circadian clock is an endogenous time-keeping system for the adaptation of organisms to changing environmental signals and coordinates developmental events throughout the life of the plant. Circadian rhythms can be reset by environmental signals, such as light-dark or temperature cycles, to match the environmental cycle. Research advances have led to the discovery of the role of core clock components as senescence regulators and their underlying signaling pathways, as well as the age-dependent shortening of the circadian clock period. These discoveries highlight the close relationship between the circadian system and leaf senescence. Key issues remain to be elucidated, including the effect of light on leaf senescence in relation to the circadian clock, and the identification of key molecules linking aging, light, and the circadian clock, and integration mechanisms of various senescence-affecting signals at the multi-regulation levels in dynamics point of view.Modern agriculture has become heavily dependent on chemical fertilizers, which have caused environmental pollution and the loss of soil fertility and sustainability. Microalgae and plant growth-promoting bacteria (PGPB) have been identified as alternatives to chemical fertilizers for improving soil fertility. This is because of their biofertilizing properties, through the production of bioactive compounds (e.g., phytohormones, amino acids, and carotenoids) and their ability to inhibit plant pathogens. Although treatment based on a single species of microalgae or bacteria is commonly used in agriculture, there is growing experimental evidence suggesting that a symbiotic relationship between microalgae and bacteria synergistically affects each other's physiological and metabolomic processes. Moreover, the co-culture/combination treatment of microalgae and bacteria is considered a promising approach in biotechnology for wastewater treatment and efficient biomass production, based on the advantage of the resulting synergistic effects. However, much remains unexplored regarding the microalgal-bacterial interactions for agricultural applications. In this review, we summarize the effects of microalgae and PGPB as biofertilizing agents on vegetable cultivation. Furthermore, we present the potential of the microalgae-PGPB co-culture/combination system for the environmentally compatible production of vegetables with improved quality.