1.In vitro expansion of hematopoietic stem/progenitor cells from human umbilical cord blood.
Ying GAO ; Hongnv CHU ; Chunjue GUO ; Meijue SHEN ; Xiaoling LV ; Yuning HOU ; Jinfu WANG
Journal of Chinese Physician 2008;10(10):1303-1306
Objective To separate and cultivate homo umbilical cord blood (UCB) hematopoietic stem cell (HSC) in vitro, and u-tilize bone marrow desmohemoblast stem cell as trophoblastic layer combined with cytokine to amplify umbilical cord blood hematopoietic stem/progenitor cell. Methods Ficoll lymph-cell separating medium density gradient centrifugalization was used to segregate UCBHSC.Bone marrow desmohemoblast stem ceil and cytokine were added, and the sum of NC cells and CD34 + cells was counted. Results The sum of NC cells amplified 75.2±15.0 times, and the sum of CD 34 + cells amplified 18.7±12.3 times. Conclusions It has significant effect on amplification of hematopoietic stem cell with bone marrow desmohemoblast stem cell and eytokine when HSC are cultured in vitro.
2.Analysis of renal glucose threshold and related factors in patients with type 2 diabetes mellitus
Jinfu SHEN ; Zhuoqun WANG ; Shuangshuang FENG ; Mao LI ; Juan LI ; Tingting GAO ; Jingjing KANG ; Xingpo MA ; Min NIU
Chinese Journal of Endocrinology and Metabolism 2021;37(1):34-38
Objective:To investigate the value of renal glucose threshold and related factors in patients with type 2 diabetes mellitus.Methods:According to the cut-off point of normal renal glucose threshold(RT G 8.9-10 mmol/L), 107 patients with type 2 diabetes mellitus hospitalized in the Endocrinology Department of our hospital were divided into three groups: high RT G group(RT G>10 mmol/L), medium RT G group(8.9 mmol/L≤RT G≤10 mmol/L), and low RT G group(RT G<8.9 mmol/L). The clinical data and biochemical characteristics of each group were collected and analyzed. Results:The proportions of patients with high, medium, and low RT G of type 2 diabetes mellitus were 56%, 29%, and 15%, respectively. There were significant differences in RT G value, age, course of disease, body mass index(BMI), fasting plasma glucose(FPG), HbA 1C, total cholesterol(TC), serum creatinine, mean blood glucose(MBG), and 24-hour urine glucose between high and medium RT G groups. RT G, gender, BMI, FPG, HbA 1C, TC, and MBG in patients with high RT G group were different from those in low RT G group. Only RT G revealed a difference between medium and low RT G groups. Correlation analysis showed that RT G was positively correlated with gender, age, BMI, HbA 1C, TC, and low density lipoprotein-cholesterol(LDL-C). Regression analysis showed that BMI, HbA 1C, and LDL-C were the related factors affecting the RT G of patients with type 2 diabetes. Conclusion:There is a larger proportion of patients with high RT G in type 2 diabetes mellitus. Their BMI, HbA 1C, and LDL-C are associated with RT G in the patients with type 2 diabetes mellitus.
3.A new triple-branched aortic arch covered stent graft in DeBakey Type I aortic dissection.
Tao TANG ; Kangjun SHEN ; Hao TANG ; Xinmin ZHOU ; Jinfu YANG
Journal of Central South University(Medical Sciences) 2012;37(7):706-710
OBJECTIVE:
To explore the effect of a new triple-branched aortic arch covered stent graft on DeBakey Type I aortic dissection, and to assess its efficacy in comparison with traditional surgery.
METHODS:
From January 2010 to November 2010, 38 patients of DeBakey Type I aortic dissection were treated surgically in the Second Xiangya Hospital of Central South University, in which 16 operations used triple-branched aortic arch covered stent grafts (stent graft group, SG group), 22 operations used traditional 4 sides branches aortic arch grafts (arch graft group, AG group).
RESULTS:
Compared with AG group, the cardiopulmonary bypass time[(138.1± 56.42) vs (179.21± 67.64) min], the clamp time [(98.56±28.08) vs (134.36±46.46) min] and the selective cerebral perfusion time[(27.3±14.76) vs (48.74±18.22) min] in SG group were obviously shortened(P<0.05). The volume of drainage 24 hours after operation in SG group also reduced[(608.93±308.15) vs (899.04±437.79) mL](P<0.05). The SG group had a lower rate of recurrent laryngeal nerve injury (6.25% vs 27.3%) and duration of hospitalization[(16.15±6.68) vs (21.18±12.69) d](P<0.05). During a following-up period of 14 to 24 months,reexamination of aortic CT angiography showed that the triple-branched aortic arch covered stent graft expanded well, and attached to the wall satisfactorily, while the corresponding false lumen of the aortic artery disappeared and the distal false lumen was filled with thrombus. The life quality of patients were good.
CONCLUSION
The new triple-branched aortic arch covered stent graft is appropriated for most patients with DeBakey Type I aortic dissection. Its use can simplify the aortic arch procedure,decrease the operation risk and has satisfactory results in early and middle stage after operation.
Adult
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Aneurysm, Dissecting
;
surgery
;
Aorta, Thoracic
;
surgery
;
Aortic Aneurysm
;
surgery
;
Blood Vessel Prosthesis Implantation
;
instrumentation
;
methods
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Cardiopulmonary Bypass
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Female
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Humans
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Male
;
Middle Aged
;
Stents
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Treatment Outcome
4.Association of bone resorption marker β-CTX with hypercalcemia in patients with Graves′ disease
Ruimei JIANG ; Zhuoqun WANG ; Min NIU ; Jinfu SHEN ; Yao QIN ; Juan LI
Journal of Chinese Physician 2023;25(4):528-531,536
Objective:To explore the association of bone resorption marker β carboxyterminal peptide of collagen Ⅰ (β-CTX) with hypercalcemia in patients with Graves′ disease (GD).Methods:287 patients with GD who were hospitalized in the endocrinology department of Fuyang People′s Hospital from January 2021 to December 2021 were divided into control group ( n=251) and hypercalcemia group ( n=36) according to the corrected blood calcium level. The clinical data and serum β-CTX level of the two groups were compared. Logistic regression model was used to analyze the risk factors of hypercalcemia in GD patients. Pearson correlation was used to analyze the correlation between serum β-CTX level and other indexes. Results:Of the 287 GD patients, 36 were diagnosed as hypercalcemia, and the incidence of hypercalcemia was 12.54%. The levels of free triiodothyronine (FT3), free thyroxine (FT4), blood phosphorus (P) and β-CTX in hypercalcemia group were higher than those in control group, and the total parathyroid hormone (iPTH) in hypercalcemia group were lower than those in control group (all P<0.05). Multivariate Logistic regression analysis showed that FT3 ( OR=1.283, 95% CI: 1.049-1.570, P<0.05), iPTH ( OR=0.924, 95% CI: 0.863-0.989, P<0.05), β-CTX ( OR=2.488, 95% CI: 1.193-5.189, P<0.05) were the influencing factors for hypercalcemia in GD patients. Pearson correlation analysis showed that β-CTX was positively correlated with FT3, FT4, blood calcium, P, alkaline phosphatase (ALP), total procollagen type I amino end terminal peptide (PINP), N-bone-gamma-carboxyglutamic-acid-containing proteins (N-MID) and 25(OH)D, and negatively correlated with iPTH (all P<0.05). Conclusions:β-CTX is highly expressed in the serum of GD patients with hypercalcemia, which is a risk factor for the occurrence of hypercalcemia in GD patients.
5.Recognition of S1 and S2 heart sounds with two-stream convolutional neural networks.
Yujing SHEN ; Xun WANG ; Min TANG ; Jinfu LIANG
Journal of Biomedical Engineering 2021;38(1):138-144
Auscultation of heart sounds is an important method for the diagnosis of heart conditions. For most people, the audible component of heart sound are the first heart sound (S1) and the second heart sound (S2). Different diseases usually generate murmurs at different stages in a cardiac cycle. Segmenting the heart sounds precisely is the prerequisite for diagnosis. S1 and S2 emerges at the beginning of systole and diastole, respectively. Locating S1 and S2 accurately is beneficial for the segmentation of heart sounds. This paper proposed a method to classify the S1 and S2 based on their properties, and did not take use of the duration of systole and diastole. S1 and S2 in the training dataset were transformed to spectra by short-time Fourier transform and be feed to the two-stream convolutional neural network. The classification accuracy of the test dataset was as high as 91.135%. The highest sensitivity and specificity were 91.156% and 92.074%, respectively. Extracting the features of the input signals artificially can be avoid with the method proposed in this article. The calculation is not complicated, which makes this method effective for distinguishing S1 and S2 in real time.
Diastole
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Heart
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Heart Sounds
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Neural Networks, Computer
;
Rivers
6.Clinical characteristics of the 2019 novel coronavirus Omicron variant infected cases
Ying LYU ; Wei YUAN ; Dongling SHI ; Yixin LIAO ; Yingchuan LI ; Ming ZHONG ; Feng LI ; Enqiang MAO ; Yinzhong SHEN ; Jinfu XU ; Yuanlin SONG ; Bijie HU ; Wenhong ZHANG ; Yun LING
Chinese Journal of Infectious Diseases 2022;40(5):257-263
Objective:To investigate the clinical characteristics and prognostic factors of 2019 novel coronavirus (2019-nCoV) Omicron variant infected cases.Methods:A total of 987 coronavirus disease 2019 (COVID-19) adult imported cases admitted to Shanghai Public Health Clinical Center, Fudan University from July 1, 2021 to January 6, 2022 were recruited. The cases were divided into Omicron group (193 cases) and non-Omicron group (794 cases) according to the genotype of the virus. The clinical data, imaging examination and laboratory results of two groups were collected and compared. Chi-square test and Mann-Whitney U test were used as statistical methods. Multiple linear regression analysis was used for multiple linear regression analysis. Results:The majority of patients in Omicron group were 18 to 30 years old, accounting for 51.3%(99/193), which was higher than 31.4%(249/794) in non-Omicron group. The difference was statistically significant ( χ2=52.75, P<0.001). The proportion of mild cases in Omicron group was 88.6%(171/193), which was higher than 81.6%(648/794) in non-Omicron group. The difference was statistically significant ( χ2=5.37, P=0.021). Cases with symptoms were more common in Omicron group than those in non-Omicron group (60.1%(116/193) vs 29.1%(231/794)), and the difference was statistically significant ( χ2=65.49, P<0.001), with the main clinical manifestations of sore/itchy throat, fever and cough/expectoration. The proportion of cases with pulmonary computed tomography (CT) imaging manifestations at admission in Omicron group was 13.0%(25/193), which was lower than that in non-Omicron group (215/794, 27.1%). The difference was statistically significant ( χ2=16.83, P<0.001). The proportion of cases with 2019-nCoV IgG positive at admission was 47.7%(92/193) in Omicron group, which was lower than 61.1%(485/794) in non-Omicron group, and the difference was statistically significant ( χ2=11.51, P<0.001). The hospitalization time of Omicron group was 20.0 (16.0, 23.0) d, which was longer than that of non-Omicron group (14.0 (10.0, 22.0) d), and the difference was statistically significant ( Z=-7.42, P<0.001). Multiple linear regression analysis showed that the time of hospitalization of cases with 2019-nCoV IgG positive at admission was shorter, while that of the cases with fever in Omicron group was longer (both P<0.050). Conclusions:The main clinical characteristics of cases with Omicron variant are fever and upper respiratory symptoms. Their pulmonary CT imaging manifestations are less, and the time of hospitalization is slightly longer. The time of hospitalization and the virus clearance time in Omicron variant infected cases with 2019-nCoV IgG positive at admission and not presented with fever are both shorter.
7.Eligibility of C-BIOPRED severe asthma cohort for type-2 biologic therapies.
Zhenan DENG ; Meiling JIN ; Changxing OU ; Wei JIANG ; Jianping ZHAO ; Xiaoxia LIU ; Shenghua SUN ; Huaping TANG ; Bei HE ; Shaoxi CAI ; Ping CHEN ; Penghui WU ; Yujing LIU ; Jian KANG ; Yunhui ZHANG ; Mao HUANG ; Jinfu XU ; Kewu HUANG ; Qiang LI ; Xiangyan ZHANG ; Xiuhua FU ; Changzheng WANG ; Huahao SHEN ; Lei ZHU ; Guochao SHI ; Zhongmin QIU ; Zhongguang WEN ; Xiaoyang WEI ; Wei GU ; Chunhua WEI ; Guangfa WANG ; Ping CHEN ; Lixin XIE ; Jiangtao LIN ; Yuling TANG ; Zhihai HAN ; Kian Fan CHUNG ; Qingling ZHANG ; Nanshan ZHONG
Chinese Medical Journal 2023;136(2):230-232