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Xanthomonas sacchari, was first identified as a pathogenic bacterium isolated from diseased sugarcane in Guadeloupe. In this study, R1 was first isolated from rice seed samples from Philippines in 2002. The antagonistic ability against several rice pathogens raises our attention. The genomic feature of this strain was described in this paper. The total genome size of X. sacchari R1 is 5,000,479 bp with 4315 coding sequences (CDS), 59 tRNAs, 2rRNAs and one plasmid.

Background: Bone age can reflect the true growth and development status of a child; thus, it plays a critical role in evaluating growth and endocrine disorders. This study established and validated an optimized Tanner-Whitehouse 3 artificial intelligence (TW3-AI) bone age assessment (BAA) system based on a convolutional neural network (CNN).Methods: A data set of 9,059 clinical radiographs of the left hand was obtained from the picture archives and communication systems (PACS) between January 2012 and December 2016. Among these, 8,005/9,059 (88%) samples were treated as the training set for model implementation, 804/9,059 (9%) samples as the validation set for parameters optimization, and the remaining 250/9,059 (3%) samples were used to verify the accuracy and reliability of the model compared to that of 4 experienced endocrinologists and 2 experienced radiologists. The overall variation of TW3-metacarpophalangeal, radius, ulna and short bones (RUS) and TW3-Carpal bone score, as well as each bone (13 RUS + 7 Carpal) between reviewers and the AI, were compared by Bland-Altman (BA) chart and Kappa test, respectively. Furthermore, the time consumption between the model and reviewers was also compared. Results:The performance of TW3-AI model was highly consistent with the reviewers' overall estimation, and the root mean square (RMS) was 0.50 years. The accuracy of the BAA of the TW3-AI model was better than the estimate of the reviewers. Further analysis revealed that human interpretations of the male capitate, hamate, the first distal and fifth middle phalanx and female capitate, the trapezoid, and the third and fifth middle phalanx, were most inconsistent. The average image processing time was 1.5±0.2 s in the TW3-AI model, which was significantly shorter than manual interpretation. Conclusions:The diagnostic performance of CNN-based TW3 BAA was accurate and timesaving, and possesses better stability compared to diagnostics made by experienced experts.

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AIM:To create a rabbit model of pediatric nonalcoholic steatohepatitis (NASH) and to evaluate the role of adiponectin in the process. METHODS:Thirty-two specific pathogen-free male New Zealand rabbits were divided randomly into three groups: (1) the normal control group (n = 10) was fed with standard diet for 12 wk; (2) the model group A (n = 11); and (3) model group B (n = 11) were fed with a highfat diet (standard diet + 10% lard + 2% cholesterol) for 8 and 12 wk, respectively. Hepatic histological changes were observed and biochemical parameters as well as serum levels of adiponectin, interleukin (IL)-6, IL-10 and tumor necrosis factor (TNF)-α were measured. RESULTS:Typical histological hepatic lesions of NASH were observed in both model groups described as liver steatosis, liver inflammatory infiltration, cytologic ballooning, perisinusoidal fibrosis and overall fibrosis. Compared with the normal control group, there were significant increases in model groups A and B in weight gain (1097.2 ± 72.3, 1360.5 ± 107.6 vs 928.0 ± 58.1, P < 0.05, P < 0.01), liver weight (93.81 ± 6.64, 104.6 ± 4.42 vs 54.4 ± 1.71, P < 0.01), Lg (ALT) (1.9 ± 0.29, 1.84 ± 0.28 vs 1.60 ± 0.17, P < 0.01), and Lg (TG) (1.03 ± 0.24, 1.16 ± 0.33 vs 0.00 ± 0.16, P < 0.01). Weight gain was much more in model group B than in model group A (1360.5 ± 107.6 vs 1097.2 ± 72.3, P < 0.05). But, there was no significant difference between the two groups concerning the other indexes. Pro-inflammatory cytokines (IL-6 and TNF-α) increased in model group B compared with that of control and model group A (IL-6: 1.86 ± 0.21 vs 1.41 ± 0.33, 1.38 ± 0.42, P < 0.01; TNF-α: 1.18 ± 0.07 vs 0.66 ± 0.08, 0.86 ± 0.43, P < 0.01, P < 0.05), whereas serum adiponectin and IL-10 decreased in model groups compared with that in the control (adiponectin:A: 21.87 ± 4.84 and B: 21.48 ± 4.60 vs 27.36 ± 7.29, P < 0.05. IL-10: A: 1.72 ± 0.38 and B: 1.83 ± 0.39 vs 2.26 ± 0.24, P < 0.01). Lg (TC) and the degree of liver fatty infiltration was an independent determinant of serum adiponectin level analyzed by stepwise multiple regressions, resulting in 29.4% of variances. CONCLUSION:This rabbit model produces the key features of pediatric NASH and may provide a realistic model for future studies. Adiponectin level partially reflects the severity of liver steatosis, but not the degree of liver inflammation.