[Objective] The aim was to discuss the effects of probiotics on the growth of Cyprinus carpiod and water quality. [Method] Taking C. carpiod as the research object, probiotics were supplemented in the fodder and water...[Objective] The aim was to discuss the effects of probiotics on the growth of Cyprinus carpiod and water quality. [Method] Taking C. carpiod as the research object, probiotics were supplemented in the fodder and water to study their effects on the growth of C. carpiod and water quality. [Result] Probiotics had promoting effects on the growth of C. carpiod and its optimum dosage was 6%. pH, ammonia nitrogen content and nitrite content in water body in experimental groups were all lower than those in control group. [Conclusion] Compound probiotics had a broad application foreground in the aquatic breeding industry.展开更多
Due to the increasing demand for microbially manufactured products in various industries,it has become important to find optimal designs for microbial cell factories by changing the direction of metabolic flow and its...Due to the increasing demand for microbially manufactured products in various industries,it has become important to find optimal designs for microbial cell factories by changing the direction of metabolic flow and its flux size by means of metabolic engineering such as knocking out competing pathways and introducing exogenous pathways to increase the yield of desired products.Recently,with the gradual cross-fertilization between computer science and bioinformatics fields,machine learning and intelligent optimization-based approaches have received much attention in Genome-scale metabolic network models(GSMMs)based on constrained optimization methods,and many high-quality related works have been published.Therefore,this paper focuses on the advances and applications of machine learning and intelligent optimization algorithms in metabolic engineering,with special emphasis on GSMMs.Specifically,the development history of GSMMs is first reviewed.Then,the analysis methods of GSMMs based on constraint optimization are presented.Next,this paper mainly reviews the development and application of machine learning and intelligent optimization algorithms in genome-scale metabolic models.In addition,the research gaps and future research potential in machine learning and intelligent optimization methods applied in GSMMs are discussed.展开更多
Background:Effective therapeutic options are limited for patients with advanced esophageal squamous cell carcinoma(ESCC).The incorporation of an immune checkpoint inhibitor and a molecular anti-angiogenic agent into t...Background:Effective therapeutic options are limited for patients with advanced esophageal squamous cell carcinoma(ESCC).The incorporation of an immune checkpoint inhibitor and a molecular anti-angiogenic agent into the commonly adopted chemotherapy may produce synergistic effects.Therefore,we aimed to investigate the efficacy and safety of camrelizumab plus apatinib combined with chemotherapy as the first-line treatment of advanced ESCC.Methods:In this single-arm prospective phase II trial,patients with unresectable locally advanced or recurrent/metastatic ESCC received camrelizumab 200 mg,liposomal paclitaxel 150 mg/m2,and nedaplatin 50 mg/m2 on day 1,and apatinib 250 mg on days 1-14.The treatments were repeated every 14 days for up to 9 cycles,followed by maintenance therapy with camrelizumab and apatinib.The primary endpoint was objective response rate(ORR)according to the Response Evaluation Criteria in Solid Tumors(version 1.1).Secondary endpoints included disease control rate(DCR),progression-free survival(PFS),overall survival(OS),and safety.Results:We enrolled 30 patients between August 7,2018 and February 23,2019.The median follow-up was 24.98 months(95%confidence interval[CI]:23.05-26.16 months).The centrally assessed ORR was 80.0%(95%CI:61.4%-92.3%),with a median duration of response of 9.77 months(range:1.54 to 24.82+months).The DCR reached 96.7%(95%CI:82.8%-99.9%).The median PFS was 6.85 months(95%CI:4.46-14.20 months),and the median OS was 19.43 months(95%CI:9.93 months–not reached).The most common grade 3-4 treatmentrelated adverse events(AEs)were leukopenia(83.3%),neutropenia(60.0%),and increased aspartate aminotransferase level(26.7%).Treatment-related serious AEs included febrile neutropenia,leukopenia,and anorexia in one patient(3.3%),and single cases of increased blood bilirubin level(3.3%)and toxic epidermal necrolysis(3.3%).No treatment-related deaths occurred.Conclusions:Camrelizumab plus apatinib combined with liposomal paclitaxel and nedaplatin as first-line treatment demonstrated feasible anti-tumor activity and manageable safety in patients with advanced ESCC.Randomized trials to evaluate this new combination strategy are warranted.Trial registration:This trial was registered on July 27,2018,at ClinicalTrials.gov(identifier:NCT03603756).展开更多
基金Supported by the Project of Quality Safety of Agricultural Products Loaned from World Bank of Jilin Province
文摘[Objective] The aim was to discuss the effects of probiotics on the growth of Cyprinus carpiod and water quality. [Method] Taking C. carpiod as the research object, probiotics were supplemented in the fodder and water to study their effects on the growth of C. carpiod and water quality. [Result] Probiotics had promoting effects on the growth of C. carpiod and its optimum dosage was 6%. pH, ammonia nitrogen content and nitrite content in water body in experimental groups were all lower than those in control group. [Conclusion] Compound probiotics had a broad application foreground in the aquatic breeding industry.
基金supported by the National key research and development program of China(Grant no.2020YFA0908303).
文摘Due to the increasing demand for microbially manufactured products in various industries,it has become important to find optimal designs for microbial cell factories by changing the direction of metabolic flow and its flux size by means of metabolic engineering such as knocking out competing pathways and introducing exogenous pathways to increase the yield of desired products.Recently,with the gradual cross-fertilization between computer science and bioinformatics fields,machine learning and intelligent optimization-based approaches have received much attention in Genome-scale metabolic network models(GSMMs)based on constrained optimization methods,and many high-quality related works have been published.Therefore,this paper focuses on the advances and applications of machine learning and intelligent optimization algorithms in metabolic engineering,with special emphasis on GSMMs.Specifically,the development history of GSMMs is first reviewed.Then,the analysis methods of GSMMs based on constraint optimization are presented.Next,this paper mainly reviews the development and application of machine learning and intelligent optimization algorithms in genome-scale metabolic models.In addition,the research gaps and future research potential in machine learning and intelligent optimization methods applied in GSMMs are discussed.
基金This study was supported by the Chinese Society of Clinical Oncology(CSCO)-Hengrui Oncology Research Fund(No.Y-HR2018-364)。
文摘Background:Effective therapeutic options are limited for patients with advanced esophageal squamous cell carcinoma(ESCC).The incorporation of an immune checkpoint inhibitor and a molecular anti-angiogenic agent into the commonly adopted chemotherapy may produce synergistic effects.Therefore,we aimed to investigate the efficacy and safety of camrelizumab plus apatinib combined with chemotherapy as the first-line treatment of advanced ESCC.Methods:In this single-arm prospective phase II trial,patients with unresectable locally advanced or recurrent/metastatic ESCC received camrelizumab 200 mg,liposomal paclitaxel 150 mg/m2,and nedaplatin 50 mg/m2 on day 1,and apatinib 250 mg on days 1-14.The treatments were repeated every 14 days for up to 9 cycles,followed by maintenance therapy with camrelizumab and apatinib.The primary endpoint was objective response rate(ORR)according to the Response Evaluation Criteria in Solid Tumors(version 1.1).Secondary endpoints included disease control rate(DCR),progression-free survival(PFS),overall survival(OS),and safety.Results:We enrolled 30 patients between August 7,2018 and February 23,2019.The median follow-up was 24.98 months(95%confidence interval[CI]:23.05-26.16 months).The centrally assessed ORR was 80.0%(95%CI:61.4%-92.3%),with a median duration of response of 9.77 months(range:1.54 to 24.82+months).The DCR reached 96.7%(95%CI:82.8%-99.9%).The median PFS was 6.85 months(95%CI:4.46-14.20 months),and the median OS was 19.43 months(95%CI:9.93 months–not reached).The most common grade 3-4 treatmentrelated adverse events(AEs)were leukopenia(83.3%),neutropenia(60.0%),and increased aspartate aminotransferase level(26.7%).Treatment-related serious AEs included febrile neutropenia,leukopenia,and anorexia in one patient(3.3%),and single cases of increased blood bilirubin level(3.3%)and toxic epidermal necrolysis(3.3%).No treatment-related deaths occurred.Conclusions:Camrelizumab plus apatinib combined with liposomal paclitaxel and nedaplatin as first-line treatment demonstrated feasible anti-tumor activity and manageable safety in patients with advanced ESCC.Randomized trials to evaluate this new combination strategy are warranted.Trial registration:This trial was registered on July 27,2018,at ClinicalTrials.gov(identifier:NCT03603756).