BackgroundHuman adenoviruses (HAdV) play a significant role in pediatric respiratory tract infections. To date, over 60 types of HAdV have been identified. Here, HAdV types are characterized in children in the Beijing area with acute lower respiratory tract infections (ALRTIs) and the clinical features and laboratory findings of hospitalized HAdV-infected cases are described.MethodsRespiratory specimens were collected from pediatric patients with ALRTIs in the emergency department or from those admitted to Beijing Children’s Hospital between March 2007 and December 2012. Infections with common respiratory viruses were determined by PCR or RT-PCR. HAdV positive samples were further typed by PCR and sequencing.ResultsAmong 3356 patients with ALRTIs, 194 (5.8 %) were found to have HAdV infection. HAdV infection was primarily confined to children (88.35 %) less than 5 years of age. A total of 11 different types of HAdV were detected throughout the study period, with HAdV-B7 (49.0 %) and HAdV-B3 (26.3 %) as the most prevalent types, followed by HAdV-C2 (7.7 %) and HAdVC1 (4.6 %). Newly emerging and re-emergent types or variants, HAdV-B55 (n = 5), HAdV-C57 (n = 3), and HAdV-B14p1 (n = 1), were identified. Results also included the reported first case of co-infection with HAdV-C2 and HAdV-C57. Clinical entities of patients with single HAdV infection (n = 49) were similar to those with mixed HAdV/respiratory syncytial virus (RSV) infections (n = 41). Patients with HAdV-B7 infection had longer duration of fever and higher serum levels of muscle enzymes than HAdV-B3-infected patients.ConclusionsDuring the study period, HAdV-B7 and HAdV-B3 were the predominant types identified in pediatric ALRTIs. HAdV-B7 infection tends to have more severe clinical consequences. The presence of newly emerging types or variants and co-infection with different types of HAdV highlights the need for constant and close surveillance of HAdV infection.

BackgroundAdenomyomectomy has recently been considered the priority option for the treatment of adenomyosis, however, the surgical efficacy and modes are still debated. We aimed to evaluate the efficacy of laparoscopic adenomyomectomy using a double-flap method for the treatment of uterine diffuse adenomyosis when compared with conventional laparoscopic adenomyomectomy.MethodsLaparoscopic adenomyomectomy using the conventional method (group A, n = 48) and the double-flap method (group B, n = 46) to treat diffuse uterine adenomyosis, respectively. Visual analog scale (VAS), menstrual amount, serum CA125 levels, and uterine volume were comparatively analyzed in both groups.ResultsThe VAS scores, menstrual amount, serum CA125 levels, and uterine volume at 12 or 24 months after surgery significantly reduced in group B than in group A (P < 0.05); these parameters were statistically decreased in both groups after surgery compared with those obtained before surgery (P < 0.001). Moreover, serum CA125 levels and uterine volume at six months of follow up were significantly lower in group B than in group A (P < 0.01). In addition, blood loss during surgery was similar in groups A and B (P > 0.05), although the operative time was significantly longer in group B than that in group A (P < 0.05).ConclusionsLaparoscopic adenomyomectomy using the double-flap method may be an effective technique to treat uterine diffuse adenomyosis.

BackgroundTea plants (Camellia sinensis) are used to produce one of the most important beverages worldwide. The nutritional value and healthful properties of tea are closely related to the large amounts of three major characteristic constituents including polyphenols (mainly catechins), theanine and caffeine. Although oil tea (Camellia oleifera) belongs to the genus Camellia, this plant lacks these three characteristic constituents. Comparative analysis of tea and oil tea via RNA-Seq would help uncover the genetic components underlying the biosynthesis of characteristic metabolites in tea.ResultsWe found that 3,787 and 3,359 bud genes, as well as 4,042 and 3,302 leaf genes, were up-regulated in tea and oil tea, respectively. High-performance liquid chromatography (HPLC) analysis revealed high levels of all types of catechins, theanine and caffeine in tea compared to those in oil tea. Activation of the genes involved in the biosynthesis of these characteristic compounds was detected by RNA-Seq analysis. In particular, genes encoding enzymes involved in flavonoid, theanine and caffeine pathways exhibited considerably different expression levels in tea compared to oil tea, which were also confirmed by quantitative RT-PCR (qRT-PCR).ConclusionWe assembled 81,826 and 78,863 unigenes for tea and oil tea, respectively, based on their differences at the transcriptomic level. A potential connection was observed between gene expression and content variation for catechins, theanine and caffeine in tea and oil tea. The results demonstrated that the metabolism was activated during the accumulation of characteristic metabolites in tea, which were present at low levels in oil tea. From the molecular biological perspective, our comparison of the transcriptomes and related metabolites revealed differential regulatory mechanisms underlying secondary metabolic pathways in tea versus oil tea.

BackgroundA central question for disease studies and crop improvements is how genetics variants drive phenotypes. Genome Wide Association Study (GWAS) provides a powerful tool for characterizing the genotype-phenotype relationships in complex traits and diseases. Epistasis (gene-gene interaction), including high-order interaction among more than two genes, often plays important roles in complex traits and diseases, but current GWAS analysis usually just focuses on additive effects of single nucleotide polymorphisms (SNPs). The lack of effective computational modelling of high-order functional interactions often leads to significant under-utilization of GWAS data.ResultsWe have developed a novel Bayesian computational method with a Markov Chain Monte Carlo (MCMC) search, and implemented the method as a Bayesian High-order Interaction Toolkit (BHIT) for detecting epistatic interactions among SNPs. BHIT first builds a Bayesian model on both continuous data and discrete data, which is capable of detecting high-order interactions in SNPs related to case—control or quantitative phenotypes. We also developed a pipeline that enables users to apply BHIT on different species in different use cases.ConclusionsUsing both simulation data and soybean nutritional seed composition studies on oil content and protein content, BHIT effectively detected some high-order interactions associated with phenotypes, and it outperformed a number of other available tools. BHIT is freely available for academic users at http://digbio.missouri.edu/BHIT/.