Objective To study the prognosis of gastroesophageal reflux disease ( GERD) in children, and explore the factors which impacts on the prognosis of GERD. Methods One hundred and thirteen children with GERD were enrolled on the basis of positive result of 24-hour pH-monitoring between January 2007 and November 2011. The number of patients who were followed up was 87,and the parents of children were contacted with the telephone. The prognosis was evaluated by comparing the degree of patients′symptom relief,and the cumulative symptom relief rate was calculated by Kaplan-meier product limit method. The univariate Log-rank test and the COX proportional hazardmodel multivariate analysis were applied to detect the factors impacting on the prognosis,including age,gender,the regularity of treatment,reflux index,and Boix-Ochoa standard score,with esophageal hiatal hernia or without,receiving surgical treatment or not,the diet and lifestyle improved or not,receiving anti-acid treatment or not,as well as with allergies his-tory or without. Results At last,76 out of 87 children had symptom relieved. Survival curve showed the cumulative symptom relief rate at different time points,the median cumulative symptom relief rate reached 6 months,the final relief rate was close to 90. 0%,and the continuous treatment time was 44 months. The study showed that 14. 9% (13/87 ca-ses) of children′s growth and development were affected and the life and learning in 16. 1% (14/87 cases) of children were impacted. Age (P=0. 012,Wald=6. 376) and the regularity of treatment (P=0. 000,Wald=13. 059) were the risk factors in the prognosis of GERD. Conclusions Age and the treatment regularity were the factors in the prognosis. The children aged more than 1-year old have poor prognosis compared with those less than 1-year old,and the irregular treatment is the risk factor in the prognosis.

Industrial bioprocess is a complex systematic process and bio-manufacturing can be realized on the basis of understanding the metabolism process of living cells. In this article, the multi-scale optimization principle and practice of industrial fermentation process are reviewed, including multi-scale optimizing theory and equipment, on-line sensing technology for cellular macroscopic metabolism, and correlated analysis of physiological parameters. Furthermore, intelligent control of industrial bioprocess is further addressed, in terms of new sensing technology for intracellular physiological metabolism, big database establishment and data depth calculation, intelligent decision.
Bioreactors ; Biotechnology ; Fermentation ; Industrial Microbiology

Currently, biomanufacturing technology and industry are receiving worldwide attention. However, there are still great challenges on bioprocess optimization and scale-up, including: lacing the process detection methods, which makes it difficult to meet the requirement of monitoring of key indicators and parameters; poor understanding of cell metabolism, which arouses problems to rationally achieve process optimization and regulation; the reactor environment is very different across the scales, resulting in low efficiency of stepwise scale-up. Considering the above key issues that need to be resolved, here we summarize the key technological innovations of the whole chain of fermentation process, i.e., real-time detection-dynamic regulation-rational scale-up, through case analysis. In the future, bioprocess design will be guided by a full lifecycle in-silico model integrating cellular physiology (spatiotemporal multiscale metabolic models) and fluid dynamics (CFD models). This will promote computer-aided design and development, accelerate the realization of large-scale intelligent production and serve to open a new era of green biomanufacturing.
Bioreactors ; Computer Simulation ; Fermentation ; Hydrodynamics