1.Epidemiological survey of glenoid fractures in the Third Affiliated Hospital to Hebei Medical University from 2003 through 2012
Lei LIU ; Zongyou YANG ; Jiayuan SUN ; Yunwei CUI ; Xiaodong CHENG ; Yanjiang YANG ; Pan HU ; Wei CHEN ; Bing YIN ; Song LIU ; Yingze ZHANG
Chinese Journal of Orthopaedic Trauma 2017;19(4):329-332
Objective To analyze the epidemiological features and trends of glenoid fractures from 2003 through 2012 in the Third Affiliated Hospital to Hebei Medical University.Methods The clinical data were collected of the patients with glenoid fracture who had been treated between January 2003 and December 2012 in our hospital.The patients' gender,age and fracture type of Ideberg classification were documented.The data from January 2003 to December 2007 were assigned into group A and those from January 2008 to December 2012 into group B.The 2 groups were compared to find out the general epidemiological characteristics and trends in the recent 10 years.Results A total of 225 patients with glenoid fracture were collected,including 176 males and 49 females.The total male/female ratio was 3.59∶ 1.The glenoid fractures predominated in an age range of 31 to 40 years (23.56%).According to Ideberg classification,there were 35 cases (15.56%) of type Ⅰ,58 ones (25.78%) of type Ⅱ,64 ones (28.44%) of type Ⅲ,21 ones (9.33%) of type Ⅳ,30 ones(13.33%) of type Ⅴ and 17 ones(7.56%) of type Ⅵ.The male/female ratio was 5.29∶1 in group A of 107 patients and 2.69∶1 in group B of 118 patients.The mean age of group A was 40.2 ± 16.0 years and that of group B 47.5 ± 14.8 years.The differences in male/female ratio,mean age and distribution of age were statistically significant between the 2 groups (P < O.05).The fractures predominated in an age range of 31 to 40 years (28.97%) in group A and in the age group of 51 to 60 years (27.12%) in group B.The most frequent fracture type was type Ⅲ in both groups,accounting for 29.91% and 27.12% respectively.There was no significant difference between the 2 groups in distribution of Ideberg classification (P > 0.05).Conclusions The peak age of glenoid fractures was from 31 to 40 years.There was an increasing trend in the mean age.There were more male patients than female ones.The high-frequency type was Ideberg type Ⅲ.
2.Biocompatibility of alpha-calcium sulfate hemihydrate (CSH)/multi-walled carbon nanotube (MWCNT) composites for bone reconstruction application.
Yi LOU ; Zongyou PAN ; Ruikai WU ; Enxing XUE ; Libo JIANG ; Guangyong YANG ; Yang ZHOU ; Jianli LIU ; Qing HUANG ; Huazi XU
Chinese Journal of Biotechnology 2012;28(3):340-348
We examined the biocompatibility and the safety of a-calcium sulfate hemihydrate (CSH)/multi-walled carbon nanotube (MWCNT) composites for bone reconstruction application. The biocompatibility of the CSH/MWCNT composites was evaluated by the measures which taking L929 fibroblast cells cultured in the extracted liquid of the composite soaking solution and putting bone marrow stromal cells planted on the composite pellets in vitro, respectively. The cell proliferation was evaluated by MTT test and further observed using an inverted optical microscope and a scanning electric microscope. The toxicity of the composites was evaluated by acute and subacute systemic toxicity test. Long-term muscle and bone implantation in vivo tests were also conducted. L929 fibroblast cells grew well in the extracted liquid, as well as bone marrow stromal cells that could adhere on the surface of sample pellets and proliferated rapidly. MTT test showed that there were no significant differences between the experimental and control groups (P > 0.05). In vivo test manifested that the composites were no toxicity, no irritation to skin and good for bone defect reconstruction. It was proved that a-calcium sulfate hemihydrate (CSH)/multi-walled carbon nanotube (MWCNT) composites exhibited excellent biocompatibility for the potential application in bone tissue engineering.
Animals
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Biocompatible Materials
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chemistry
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Bone Marrow Cells
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cytology
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Bone Substitutes
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chemical synthesis
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chemistry
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Calcium Sulfate
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chemistry
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Cell Line
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Cell Proliferation
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Fibroblasts
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cytology
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Materials Testing
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Nanotubes, Carbon
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chemistry
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Rabbits
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Stromal Cells
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cytology
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Tissue Engineering
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methods
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Toxicity Tests
3.Study research on multi-level representation of syndrome elements in TCM intelligent auxiliary diagnosis system
Yingjie SHI ; Wen HUANG ; Pan ZHAO ; Chengyuan LIU ; Zongyou LI
International Journal of Traditional Chinese Medicine 2020;42(10):1001-1007
Objective:This paper studied the classification of syndrome and the multi-level expression method of syndrome elements, to realize the processing of syndrome name wiht computer, which could be applied to the research on traditional Chinese medicine (TCM) intelligent auxiliary diagnosis system.Methods:With the guidance of TCM theory combining the syndrome differentiation and syndrome elements theory, the syndrome elements are divided into a more fine-grained way, and the hierarchical division method and multi-level expression method of syndrome elements are put forward. Than to conduct artificial analysis on the syndrome of gynecological diseases to verify the rationality of multi-level expression of syndrome elements. Based on the multi-level expression method of syndrome elements and pattern extraction method of pattern matching,form the extraction method of syndrome elements and through the batch processing of the Clinical Diagnosis and Treatment Term of TCM& Syndrome Part to verify the accuracy of the batch processing methodexpression. Results:Guided by TCM theory, this study divided the constituent elements of syndrome names into two levels and five types containing disease location elements, disease nature elements which includes basic material, etiology, pathological state and conjunctions, based on which the syndrome splitting process is constructed. Based on this, the process of syndrome name elements separation is constructed. Artificial analysis of TCM syndrome names of menstrual diseases and infertility shows that all syndrome names can be divided into one or more disease location elements, disease nature elements, and conjunctions based on that splitting process. The accuracy rate of computer batch processing is as high as 71.4% based on that splitting process.Conclusions:The multi-level representation method of syndrome elements provides a theoretical framework for mass data processing by computer, improves the efficiency and accuracy of data processing, provides a theoretical basis for the construction of training data set of syndrome differentiation model, provides support for TCM syndrome differentiation reasoning model, and can be applied to the research of TCM intelligent auxiliary diagnosis system.