1.Comparative study of volatile chemical constituents from shell and kernel of Caesalpinia minax Hance
Xin HUO ; Naijia YANG ; Wenwei LIU ; Lina DING ; Yueling YUAN
China Journal of Traditional Chinese Medicine and Pharmacy 2005;0(06):-
Objective:To compare the volatile chemical constituents from the shell and kernel of Caesalpinia minax Hance.Methods:The volatile chemical compositions of Caesalpinia minax Hance were obtained by organic solvent-wet distillation and were analyzed by GC-MS equipped with a elastic quartz capillary column HP-5MS 5%Phenyl Methyl Siloxane(30m?0.25mm?0.25?m).The constituents were identified by their mass spectra.The relative percentage of the volatile constituents was calculated from the GC peak areas.Results:One hundred and fifteen kinds of chemical constituents in the shell of Caesalpinia minax Hance were separated and sixty-three of them,which accounts for 54.7%of total volatile constituents, were characterized.There are five kinds whose relative contents were more than 2.0%.One hundred and two kinds of chemical constituents in the kernel of Caesalpinia minax Hance were separated and fifty-one of them,which accounts for 50.0%,were characterized.There are seven kinds whose relative contents were more than 2.0%.Form the shell and kernel of Caesalpinia minax Hance there were forty kinds of chemical constituents the same.The most relative contents were Limonene(5.31%,shell)and 1-Hexanol(12.94%,kernel).Conclusion:This paper reports,for the first time,the comparison of volatile constituents from shell and kernel of Caesalpinia minax Hance.It is helpful for controlling the quality and further researching of Caesalpinia minax Hance.
2.Determination of chemical constituents of essential oil from flower of Dendrobium candidum Wall.ex Lind1.
Xin HUO ; Jianhua ZHOU ; Naijia YANG ; Wenwei LIU ; Jiancheng HUANG
China Journal of Traditional Chinese Medicine and Pharmacy 2005;0(08):-
Objective: To study the chemical constituents of volatile oil from flower of Dendrobium candidum Wall. ex Lind1. Methods: The chemical compositions of volatile oil of the plant which were obtained by steam distillation with hexane were analyzed by GC-MS equipped with a elastic quartz capillary column-HP-5MS5% Phenyl Methyl Siloxane (30 m? 0.25 mm ?0.25 ?m). The constituents were identifi ed by their mass spectra. The relative percentage of the oil constituents was calculated from the GC peak areas. Results: Eighty-nine kinds of chemical constituents in Dendrobium candidum Wall.ex Lind1.flower were separated; of which fifty-nine compounds representing 76.51% of the oil were characterized. Relative contents that were more than 2.0% were determined as Nonanal 9.21%, Eudesma-5,11-dien-8,12-olide 5.55%, (E)-2-Decenal 4.63%, 2,3-Dehydro- 1,8-cineole 4.39%, Pentacosane 4.03%,?-Cedrol 3.69%, Isoalantolactone 3.65%, (E)-2-Heptenal 3.60%, E,E-2,4-Decadienal 2.14%,?-Phorone 2.03%.Conclusion: This paper reports, for the first time, the composition of volatile oils of Dendrobium candidum Wall.ex Lind1.flower by GC/MS.
3.Progress in computer-assisted Alberta stroke program early computer tomography score of acute ischemic stroke based on different modal images.
Naijia LIU ; Ying HU ; Yifeng YANG ; Yuehua LI ; Shengdong NIE
Journal of Biomedical Engineering 2021;38(4):790-796
Clinically, non-contrastive computed tomography (NCCT) is used to quickly diagnose the type and area of stroke, and the Alberta stroke program early computer tomography score (ASPECTS) is used to guide the next treatment. However, in the early stage of acute ischemic stroke (AIS), it's difficult to distinguish the mild cerebral infarction on NCCT with the naked eye, and there is no obvious boundary between brain regions, which makes clinical ASPECTS difficult to conduct. The method based on machine learning and deep learning can help physicians quickly and accurately identify cerebral infarction areas, segment brain areas, and operate ASPECTS quantitative scoring, which is of great significance for improving the inconsistency in clinical ASPECTS. This article describes current challenges in the field of AIS ASPECTS, and then summarizes the application of computer-aided technology in ASPECTS from two aspects including machine learning and deep learning. Finally, this article summarizes and prospects the research direction of AIS-assisted assessment, and proposes that the computer-aided system based on multi-modal images is of great value to improve the comprehensiveness and accuracy of AIS assessment, which has the potential to open up a new research field for AIS-assisted assessment.
Alberta
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Brain Ischemia/diagnostic imaging*
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Humans
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Ischemic Stroke
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Stroke/diagnostic imaging*
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Tomography, X-Ray Computed