[Efficacy and safety of Changsulin® compared with Lantus® in type 2 diabetes: a phase â ¢ multicenter, randomized, open-label, parallel, controlled clinical trial].

Objective: To compare the efficacy and safety of Changsulin® with Lantus® in treating patients with type 2 diabetes mellitus (T2DM). Methods: This was a phase Ⅲ, multicenter, randomized, open-label, parallel-group, active-controlled clinical trial. A total of 578 participants with T2DM inadequately controlled on oral hypoglycemic agents were randomized 3∶1 to Changsulin® or Lantus® treatment for 24 weeks. The efficacy measures included changes in glycosylated hemoglobin (HbA1c), fasting plasma glucose (FPG), 2h postprandial plasma glucose (2hPG), 8-point self-monitoring of blood glucose (SMBG) profiles from baseline, and proportions of subjects achieving targets of HbA1c and FPG. The safety outcomes included rates of hypoglycemia, adverse events (AEs) and anti-insulin glargine antibody. Results: After 24 weeks of treatment, mean HbAlc decreased 1.16% and 1.25%, FPG decreased 3.05 mmol/L and 2.90 mmol/L, 2hPG decreased 2.49 mmol/L and 2.38 mmol/L in Changsulin® and in Lantus®, respectively. No significant differences could be viewed in above parameters between the two groups (all P>0.05). There were also no significant differences between Changsulin® and Lantus® in 8-point SMBG profiles from baseline and proportions of subjects achieving the targets of HbA1c and FPG (all P>0.05). The rates of total hypoglycemia (38.00% and 39.01% for Changsulin® and Lantus®, respectively) and nocturnal hypoglycemia (17.25% and 16.31% for Changsulin® and Lantus®, respectively) were similar between the two groups (all P>0.05). Most of the hypoglycemia events were asymptomatic, and no severe hypoglycemia were found in both groups. No differences were observed in rates of AEs (61.77% vs.52.48%) and anti-insulin glargine antibody (after 24 weeks of treatment, 6.91% vs.3.65%) between the two groups (all P>0.05). Conclusions: Changsulin® shows similar efficacy and safety profiles compared with Lantus® and Changsulin® treatment was well tolerated in patients with T2DM.

Reconstructed metagenomes reveal changes of microbial functional profiling during PAHs degradation along a rice (Oryza sativa) rhizosphere gradient.

AIMS: The response of microbial metagenome to polycyclic aromatic hydrocarbons (PAHs) degradation in the rice rhizosphere remains poorly understood. We investigated the spatial and temporal variations of microbial communities and reconstructed metagenomes along the rice rhizosphere gradient during PAHs degradation. METHODS AND RESULTS: The experiment was performed in rhizoboxes, in which the rhizosphere region was divided into five 1-mm thick layers. Based on denaturant gradient gel electrophoresis profiling and sequencing of bacterial and archaeal 16S rRNA genes, predicted metagenomes were reconstructed. The microbial communities in the rice rhizosphere were influenced by the PAHs concentration and distance from the root surface during PAHs degradation. Correlation network analysis showed that archaea played an important role in PAHs degradation. Predicted metagenomes can be clustered into two groups with high and low PAHs degrading potential, respectively. The relative abundance of genes for defense mechanisms, replication, recombination and reparation was significantly higher in samples with high PAHs degrading potentials. The relative abundance of the dioxygenase gene was greater near the root surface of the rice. However, the abundance of aldolase and dehydrogenase was constant in rhizosphere soils at different distances from the root surface. CONCLUSIONS: Distance from root surface and PAH concentrations affected the microbial communities and metagenomes in rice rhizosphere. The abundance of dioxygenase genes relating to PAH degradation in metagenomes mirrored the PAH degradation potential in rice rhizosphere. SIGNIFICANCE AND IMPACT OF THE STUDY: Our findings suggested that the predicted metagenomes reconstructed from 16S rRNA marker gene sequences provide further insights into the spatial variation and dynamics of microbial functioning that occur during bioremediation.