[Development and application of the plant phenomics analysis platform].

With the completion of the whole genome sequencing of major important crops, researchers have an increasing demand for high-throughput, accurate and nondestructive phenotyping technologies. The Plant Phenomics Analysis Platform (PPAP) was established in 2017 at the Institute of Genetics and Developmental Biology, Chinese Academy of Sciences. The platform has the most up-to-date comprehensive phenotyping analysis facility in China with a full spectrum of imaging systems consisting of eight units including visible light, infrared, near-infrared, root near-infrared, fluorescence, chlorophyll fluorescence, high spectral and lidar imaging. The platform has also specifically established phenotyping technologies for complex traits, such as root phenotype collection and analysis, spike and spikelet feature collection and analysis and responses under stress conditions. PPAP is dedicated to providing all-possible services for domestic and international academic communities and industrial partners engaged in plant sciences.

Transcriptome profiling of developmental leaf senescence in sorghum (Sorghum bicolor).

KEY MESSAGE: This piece of the submission is being sent via mail. Leaf senescence is essential for the nutrient economy of crops and is executed by so-called senescence-associated genes (SAGs). Here we explored the monocot C4 model crop Sorghum bicolor for a holistic picture of SAG profiles by RNA-seq. Leaf samples were collected at four stages during developmental senescence, and in total, 3396 SAGs were identified, predominantly enriched in GO categories of metabolic processes and catalytic activities. These genes were enriched in 13 KEGG pathways, wherein flavonoid and phenylpropanoid biosynthesis and phenylalanine metabolism were overrepresented. Seven regions on Chromosomes 1, 4, 5 and 7 contained SAG 'hotspots' of duplicated genes or members of cupin superfamily involved in manganese ion binding and nutrient reservoir activity. Forty-eight expression clusters were identified, and the candidate orthologues of the known important senescence transcription factors such as ORE1, EIN3 and WRKY53 showed "SAG" expression patterns, implicating their possible roles in regulating sorghum leaf senescence. Comparison of developmental senescence with salt- and dark- induced senescence allowed for the identification of 507 common SAGs, 1996 developmental specific SAGs as well as 176 potential markers for monitoring senescence in sorghum. Taken together, these data provide valuable resources for comparative genomics analyses of leaf senescence and potential targets for the manipulation of genetic improvement of Sorghum bicolor.

Simplified liver imaging reporting and data system for the diagnosis of hepatocellular carcinoma on gadoxetic acid-enhanced magnetic resonance imaging.

BACKGROUND: The liver imaging reporting and data system (LI-RADS) diagnostic table has 15 cells and is too complex. The diagnostic performance of LI-RADS for hepatocellular carcinoma (HCC) is not satisfactory on gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI). AIM: To evaluate the ability of the simplified LI-RADS (sLI-RADS) to diagnose HCC on EOB-MRI. METHODS: A total of 331 patients with 356 hepatic observations were retrospectively analysed. The diagnostic performance of sLI-RADS A-D using a single threshold was evaluated and compared with LI-RADS v2018 to determine the optimal sLI-RADS. The algorithms of sLI-RADS A-D are as follows: The single threshold for sLI-RADS A and B was 10 mm, that is, classified observations ≥ 10mm using an algorithm of 10-19 mm observations (sLI-RADS A) and ≥ 20 mm observations (sLI-RADS B) in the diagnosis table of LI-RADS v2018, respectively, while the classification algorithm remained unchanged for observations < 10 mm; the single threshold for sLI-RADS C and D was 20 mm, that is, for < 20 mm observations, the algorithms for < 10 mm observations (sLI-RADS C)and 10-19 mm observations (sLI-RADS D) were used, respectively, while the algorithm remained unchanged for observations ≥ 20 mm. With hepatobiliary phase (HBP) hypointensity as a major feature (MF), the final sLI-RADS (F-sLI-RADS) was formed according to the optimal sLI-RADS, and its diagnostic performance was evaluated. The times needed to classify the observations according to F-sLI-RADS and LI-RADS v2018 were compared. RESULTS: The optimal sLI-RADS was sLI-RADS D (with a single threshold of 20 mm), because its sensitivity was greater than that of LI-RADS v2018 (89.8% vs 87.0%, P = 0.031), and its specificity was not lower (89.4% vs 90.1%, P > 0.999). With HBP hypointensity as an MF, the sensitivity of F-sLI-RADS was greater than that of LI-RADS v2018 (93.0% vs 87.0%, P < 0.001) and sLI-RADS D (93.0% vs 89.8%, P = 0.016), without a lower specificity (86.5% vs 90.1%, P = 0.062; 86.5% vs 89.4%, P = 0.125). Compared with that of LI-RADS v2018, the time to classify lesions according to F-sLI-RADS was shorter (51 ± 21 s vs 73 ± 24 s, P < 0.001). CONCLUSION: The use of sLI-RADS with HBP hypointensity as an MF may improve the sensitivity of HCC diagnosis and reduce lesion classification time.