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Next-generation sequencing has allowed identification of millions of somatic mutations in human cancer cells. A key challenge in interpreting cancer genomes is to distinguish drivers of cancer development among available genetic mutations. To address this issue, we present the first web-based application, consensus cancer driver gene caller (C3), to identify the consensus driver genes using six different complementary strategies, i.e., frequency-based, machine learning-based, functional bias-based, clustering-based, statistics model-based, and network-based strategies. This application allows users to specify customized operations when calling driver genes, and provides solid statistical evaluations and interpretable visualizations on the integration results. C3 is implemented in Python and is freely available for public use at http://drivergene.rwebox.com/c3. Keywords: Somatic mutation, Cancer driver genes, Consensus, Data integration, Web server

Next-generation sequencing has allowed identification of millions of somatic mutations in human cancer cells. A key challenge in interpreting cancer genomes is to distinguish drivers of cancer development among available genetic mutations. To address this issue, we present the first web-based application, consensus cancer driver gene caller (C3), to identify the consensus driver genes using six different complementary strategies, i.e., frequency-based, machine learning-based, functional bias-based, clustering-based, statistics model-based, and network-based strategies. This application allows users to specify customized operations when calling driver genes, and provides solid statistical evaluations and interpretable visualizations on the integration results. C3 is implemented in Python and is freely available for public use at http://drivergene.rwebox.com/c3.

Aryl hydrocarbon receptor (Ahr) is thought to be a crucial factor that regulates immune responses, which may be involved in the pathogenesis of autoimmune inflammation including rheumatoid arthritis (RA). The results of our group in recent years have shown that Paeoniflorin-6'-O-benzene sulfonate (code: CP-25), a novel ester derivative of paeoniflorin, has a good effect on improving RA animal models. However, whether the anti-arthritis effect of CP-25 is related to Ahr remains unclear. Here, we showed that CP-25 treatment ameliorated adjuvant-induced arthritis (AA), a rat model of RA, by inhibiting Ahr-related activities in fibroblasts like synoviocytes (FLS). AA rats were treated with CP-25 or paroxetine from days 17 to 33 after immunization. We showed that CP-25 alleviated arthritis symptoms and the pathological changes. Treatment with CP-25 decreased the expression of Ahr in the synovium of AA rats. CP-25 inhibited the expression of Ahr and the G protein-coupled receptor kinase 2 (GRK2) as well as the co-expression of GRK2 with Ahr in FLS of AA rats. Furthermore, CP-25 down-regulated the production of Kyn in FLS of AA rats. These results suggested that CP-25 may inhibit the expression and activation of Ahr. Besides, treatment with CP-25 reduced the proliferation and migration of MH7A caused by Ahr activation. In addition, we also demonstrated that CP-25 down-regulated the total and nuclear expression of Ahr and the expression of GRK2 in Kyn-treated MH7A. Moreover, the co-expression and co-localization of Ahr and GRK2in Kyn-treated MH7A were also repressed by CP-25. The data presented here demonstrated that CP-25 suppressed FLS dysfunction in rats with AA, which were associated with reduced Ahr activation and the interaction between Ahr and GRK2.

OBJECTIVE: To investigate the incidence rate of infectious diseases during hospitalization in late preterm infants in Beijing, China, as well as the risk factors for infectious diseases and the effect of breastfeeding on the development of infectious diseases. METHODS: Related data were collected from the late preterm infants who were hospitalized in the neonatal wards of 25 hospitals in Beijing, China, from October 23, 2015 to October 30, 2017. According to the feeding pattern, they were divided into a breastfeeding group and a formula feeding group. The two groups were compared in terms of general status and incidence rate of infectious diseases. A multivariate logistic regression analysis was used to investigate the risk factors for infectious diseases. RESULTS: A total of 1 576 late preterm infants were enrolled, with 153 infants in the breastfeeding group and 1 423 in the formula feeding group. Of all infants, 484 (30.71%) experienced infectious diseases. The breastfeeding group had a significantly lower incidence rate of infectious diseases than the formula feeding group (22.88% vs 31.55%, P=0.033). The multivariate logistic regression analysis showed that breastfeeding was an independent protective factor against infectious diseases (OR=0.534, P=0.004), while male sex, premature rupture of membranes, gestational diabetes mellitus, and asphyxia were risk factors for infectious diseases (OR=1.328, 5.386, 1.535, and 2.353 respectively, P < 0.05). CONCLUSIONS: Breastfeeding can significantly reduce the incidence of infectious diseases and is a protective factor against infectious diseases in late preterm infants. Breastfeeding should therefore be actively promoted for late preterm infants during hospitalization.

Supplemental material, sj-pdf-1-tar-10.1177_1753466620977376 for Modified and simplified clinically important deterioration: multidimensional indices of short-term disease trajectory to predict future exacerbations in patients with chronic obstructive pulmonary disease by Yi-yang Zhao, Cong Liu, Yu-qin Zeng, Ai-yuan Zhou, Jia-xi Duan, Wei Cheng, Tian Sun, Xin Li, Li-bing Ma, Qi-mi Liu, Ying-qun Zhu, Ming Chen, Mei-ling Zhou and Ping Chen in Therapeutic Advances in Respiratory Disease

Supplemental material, sj-pdf-2-tar-10.1177_1753466620977376 for Modified and simplified clinically important deterioration: multidimensional indices of short-term disease trajectory to predict future exacerbations in patients with chronic obstructive pulmonary disease by Yi-yang Zhao, Cong Liu, Yu-qin Zeng, Ai-yuan Zhou, Jia-xi Duan, Wei Cheng, Tian Sun, Xin Li, Li-bing Ma, Qi-mi Liu, Ying-qun Zhu, Ming Chen, Mei-ling Zhou and Ping Chen in Therapeutic Advances in Respiratory Disease

Supplemental material, sj-pdf-3-tar-10.1177_1753466620977376 for Modified and simplified clinically important deterioration: multidimensional indices of short-term disease trajectory to predict future exacerbations in patients with chronic obstructive pulmonary disease by Yi-yang Zhao, Cong Liu, Yu-qin Zeng, Ai-yuan Zhou, Jia-xi Duan, Wei Cheng, Tian Sun, Xin Li, Li-bing Ma, Qi-mi Liu, Ying-qun Zhu, Ming Chen, Mei-ling Zhou and Ping Chen in Therapeutic Advances in Respiratory Disease

Next-generation sequencing has allowed identification of millions of somatic mutations in human cancer cells. A key challenge in interpreting cancer genomes is to distinguish drivers of cancer development among available genetic mutations. To address this issue, we present the first web-based application, consensus cancer driver gene caller (C3), to identify the consensus driver genes using six different complementary strategies, i.e., frequency-based, machine learning-based, functional bias-based, clustering-based, statistics model-based, and network-based strategies. This application allows users to specify customized operations when calling driver genes, and provides solid statistical evaluations and interpretable visualizations on the integration results. C3 is implemented in Python and is freely available for public use at http://drivergene.rwebox.com/c3.

An investigation was designed and conducted to detect pharmacokinetic differences between paeoniflorin (Pae) microemulsion and Pae saline. Pae microemulsion (25, 50,100 mg x kg(-1)) was administered to three groups of rats with adjuvant arthritis (AA) while Pae (25, 50,100 mg x kg(-1)) was given to another three groups of rats both for ten days. A HPLC assay was developed to determine the plasma concentrations of Pae. The plasma concentrations of Pae groups (25, 50 mg x kg(-1)) were undetectable. Furthermore, compared with pharmacokinetic parameters of Pae group (100 mg x kg(-1)), maximum concentration (C(max)), the area under the plasma concentration-time curve (AUC(0-t)), and mean retention time MRT(0-infinity))(h) of Pae microemulsion (100 mg x kg(-1)) increased apparently, while volume of distribution (Vd) and clearance rate (CL/F) decreased. These results indicate that a microemulsion significantly improves the absorption of Pae in AA rats.