diana1983941@mail.hzau.edu.cn or yaowen@henau.edu.cn.

To determine incidence and clinically relevant risk factors for diabetic amputation in a large cohort study of diabetic foot ulceration patients in China, we investigated a total of 669 diabetic foot ulceration patients, who were assessed at baseline for demographic information, medical and social history, peripheral neuropathy screening, periphery artery disease screening, assessment of nutritional status and diabetic control, physical examination including foot deformity in 15 Grade III-A hospitals. Of the 669 patients, 435 were male and 201 were female, with the mean age being 64.0 years. Of all patients, 110 had neuropathic ulcers, 122 had ischemic ulcers, 276 had neuroischemic ulcers, and 12 cases were unclassified. Wagner classification showed 61 cases were grade I, 216 cases grade II, 159 cases grade III, 137 cases grade IV, and 7 cases grade V. The overall amputation rate among diabetic foot patients was 19.03%, and major and minor amputation rates were 2.14% and 16.88%, respectively. By univariate analysis, statistically significant differences were found in smoking, rest pain, ulcer history, revascularization history, amputation history, gangrene, infection, Wagner grades, duration of diabetes, and postprandial blood glucose, aldehyde, total protein, globulin, albumin, white blood cell (WBC), hemoglobin, HbA1c, ulcer property, body mass index, as well as creatinine. Binary logistic regression model showed that increased WBC (odds ratio 1.25) and ulcer history (odds ratio 6.8) were associated with increased risks from diabetic foot ulcer to major amputation; increased duration of diabetes (odds ratio 1.004), WBC (odds ratio 1.102), infection (odds ratio 2.323), foot deformity (odds ratio 1.973), revascularization history (odds ratio 2.662), and decreased postprandial blood sugar (odds ratio 0.94) were associated with increased risks from diabetic foot ulcer to minor amputation. It is of great importance to give better management to diabetic patients at early stages. Following a diagnosis of DFU more intensive surveillance and aggressive care may improve outcome.

BackgroundAs a main staple food, rice is also a model plant for functional genomic studies of monocots. Decoding of every DNA element of the rice genome is essential for genetic improvement to address increasing food demands. The past 15 years have witnessed extraordinary advances in rice functional genomics. Systematic characterization and proper deposition of every rice gene are vital for both functional studies and crop genetic improvement.FindingsWe built a comprehensive and accurate dataset of ∼2800 functionally characterized rice genes and ∼5000 members of different gene families by integrating data from available databases and reviewing every publication on rice functional genomic studies. The dataset accounts for 19.2% of the 39 045 annotated protein-coding rice genes, which provides the most exhaustive archive for investigating the functions of rice genes. We also constructed 214 gene interaction networks based on 1841 connections between 1310 genes. The largest network with 762 genes indicated that pleiotropic genes linked different biological pathways. Increasing degree of conservation of the flowering pathway was observed among more closely related plants, implying substantial value of rice genes for future dissection of flowering regulation in other crops. All data are deposited in the funRiceGenes database (https://funricegenes.github.io/). Functionality for advanced search and continuous updating of the database are provided by a Shiny application (http://funricegenes.ncpgr.cn/).ConclusionsThe funRiceGenes dataset would enable further exploring of the crosslink between gene functions and natural variations in rice, which can also facilitate breeding design to improve target agronomic traits of rice.

Application of Next Generating Sequencing (NGS) technology in transcriptome profiling has 10 greatly improved our understanding of transcriptional regulation at genome-wide scale in the last decade, and tens of thousands of RNA-sequencing (RNA-seq) libraries have been produced by the research community. However, accessing such huge amount of RNA-seq data poses a big challenge for groups that lack dedicated bioinformatic personnel or expensive computational resources. Here, we introduce the Arabidopsis RNA-seq database (ARS), a free, web-accessible, and user-friendly to quickly explore expression level of any gene in 20,000+ publicly available Arabidopsis RNA-seq libraries.In the last decade, RNA-sequencing (RNA-seq) has surpassed microarray to become the gold standard for gene expression profiling due to the continuous drop in sequencing cost and the development of easy-to-use library construction kits. To date, the Arabidopsis community has .

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