The effects of sulfated polysaccharides from brown seaweeds GS201 on neuronal survival of cultured brain neurons were investigated in this paper.Results indicated that GS201 at concentrations of 0.01 0.1 1 10 mg?L -1 significantly enhanced the neuronal survival of both hippocampus and neurocortex.The mechanisms underlying the neurotrophic effect exerted by GS201 need to be further elucidated.

Objective The anti-UV-B radiation mechanism of UV-B tolerance strain KFS-9 was studied from the profile of metabolites.Methods The compounds were separated by column chromatography and their structures were elucidated based on GC-MS,LC-TOF-MS,EI-MS and NMR analyses.Results Three unsaturated fatty acids(identified as 9-hexadecenoic acid,9,12-octadecadienoic acid and 11-octadecenoic acid) and 1,2-benzenedicarboxylic acid able to absorb ultraviolet were isolated from the petroleum ether extract of the fermentation liquid of Pantoea agglomerans KFS-9.Fraction(Ⅱ) was isolated from the ethyl acetate extract and was composed of 2,3-butanediol and a series of high unsaturated aroma compounds.Fraction(Ⅱ) had a wide absorption peak,and it could protect E.coli from UV-B damage in some sense.Conclusion Strain KFS-9 produced metabolites that were able to absorb UV to build a natural barrier and so improved the tolerance to UV radiation.The UV-B radiation protection test to the E.coli also showed fraction(Ⅱ) was not the only protector,and there definitely existedother materials and mechanism to protect the strain.

Objective:To construct an optimal planning model based on backpropagation(BP)neural network algorithm,and to explore its application value in the quality control of magnetic resonance imaging(MRI)equipment.Methods:Taking image quality,quality control cost and troubleshooting time as control objectives,and 13 indicators such as environmental factors,human factors,equipment factors,and use frequency as decision factors,an optimal planning model based on BP neural network algorithm is constructed.The operation data of a 1.5T magnetic resonance device in clinical use in Zhongshan People's Hospital from 31 May 2021 to 4 June 2023 were selected.The equipment operation data for 52 weeks from 31 May 2021 to 29 May 2022 was used for model training,which was used as the data of the conventional quality control scheme,and the optimal scheme evolution and dynamic optimization were carried out by reverse calculation.The dynamic optimization scheme was used to apply the practice from 6 June 2022 to 4 June 2023,and its operation data was used as the data of the optimization quality control scheme.The equipment image quality score,quality control cost and troubleshooting time of the two schemes were compared.Results:The image quality score of MRI equipment optimized using the optimal planning model for quality control scheme was(4.15±0.35)points,which was higher than that of conventional quality control scheme,the quality control cost and troubleshooting time were CNY(5247.44±1711.39)and(4.34±2.31)h,respectively,which were lower than those of conventional quality control scheme,the differences were statistically significant(t=4.084,6.442,10.776,P＜0.05).Conclusion:The optimal planning model was constructed based on the BP neural network algorithm and the quality control scheme of MRI equipment was optimized,which can effectively improve the quality management level of MRI equipment,ensure image quality,improve equipment stability,reduce failure rates and quality control costs.