1.Studies on the relationship between sinomenine distribution and its organic toxicology
Murong YE ; Liang LIU ; Yuaner ZENG ; Liqun ZHANG ; Yongheng TAN ; Sujian DENG ; Guiying HUANG ;
Chinese Pharmacological Bulletin 1987;0(01):-
AIM To investigate the relationship between sinomenine distribution and its organic toxicology in rats so as to give some pharmacological data for clinical application of sinomenine. METHODS Three kinds of administration plans were designed in the experiment, ie sinomenine was ip administered at the dosage of l50 mg?kg -1 per day, repreat dosed for 6 wk and suspended the drug for 1 wk after 6wk repeat doses.At the end of the each administration plan,the animals were sacrificed and their blood and their main internal organs were collected for the purpose of measurement of sinomenine concentration in each sample by HPLC. Meanwhile,the histopathological and serological examinations were also done in the experiments. RESULTS The sinomenine concentration in rats internal organs were in order of liver, heart, lung and brain either in single dosed treated animals or in repeat dosed treated animals for 6 wk. However,the concentration of sinomenine could not be detected by HPLC after l wk drug suspension,the histopathological examination showed that sinomenine at the dosage of l50 mg?kg -l per day for 6wk treatment could slightly damage liver ce11s, dominant1y caused the cell edema,but no any influence on the sero1ogy of liver and kidney. Sinomenine ip could also cause a mild hyperaemia of the rats heart tissues but no any histopathological changes had been observed. In testis tissues no sinomenine had beed detected although the animals were treated by repeat treatment for 6 wk and no any histopathological changes had been found yet. However, Sinomenine could partialy inhibit the sperm vitalities and amount of the dead sperms were a1so augmented. It was similar to in vitro eperiments. These influences of sinomenine on testis could be quickly recovered by drug suspension. CONCLUSION Sinomenine concentration were in order of liver, heart, kidney, lung and brain either in treatment by single dose or by repeat dose administration. The histopathological changes were only abserved in liver cells of the animals which indicates that it should be in consideration of the liver functions during treatment course of the drug.
2.Studies on the relationship between sinomenine distribution and its organic toxicology
Murong YE ; Liang LIU ; Yuaner ZENG ; Liqun ZHANG ; Yongheng TAN ; Sujian DENG ; Guiying HUANG
Chinese Pharmacological Bulletin 2001;17(1):65-69
AIM To investigate the relationship between sinomenine distribution and its organic toxicology in rats so as to give some pharmacological data for clinical application of sinomenine. METHODS Three kinds of administration plans were designed in the experiment, ie sinomenine was ip administered at the dosage of l50 mg*kg-1 per day, repreat-dosed for 6 wk and suspended the drug for 1 wk after 6wk repeat-doses.At the end of the each administration plan,the animals were sacrificed and their blood and their main internal organs were collected for the purpose of measurement of sinomenine concentration in each sample by HPLC. Meanwhile,the histopathological and serological examinations were also done in the experiments. RESULTS The sinomenine concentration in rats internal organs were in order of liver, heart, lung and brain either in single-dosed treated animals or in repeat-dosed treated animals for 6 wk. However,the concentration of sinomenine could not be detected by HPLC after l wk drug-suspension,the histopathological examination showed that sinomenine at the dosage of l50 mg*kg-l per day for 6wk treatment could slightly damage liver ce11s, dominant1y caused the cell edema,but no any influence on the sero1ogy of liver and kidney. Sinomenine ip could also cause a mild hyperaemia of the rats heart tissues but no any histopathological changes had been observed. In testis tissues no sinomenine had beed detected although the animals were treated by repeat treatment for 6 wk and no any histopathological changes had been found yet. However, Sinomenine could partialy inhibit the sperm vitalities and amount of the dead sperms were a1so augmented. It was similar to in vitro eperiments. These influences of sinomenine on testis could be quickly recovered by drug suspension. CONCLUSION Sinomenine concentration were in order of liver, heart, kidney, lung and brain either in treatment by single dose or by repeat-dose administration. The histopathological changes were only abserved in liver cells of the animals which indicates that it should be in consideration of the liver functions during treatment course of the drug.
3.Thalassemia screening and genotyping in Southwest Guizhou Autonomous Prefecture of Guizhou Province
Hongmei MURONG ; Xiuxiu ZHANG ; Hua CHANG ; Panpan LI ; Hong ZHAO ; Qiong LI ; Yuting XIANG ; Dachun TANG ; Chan HUANG
Chinese Journal of Endemiology 2022;41(6):444-449
Objective:To analyze the thalassemia screening and genotyping in Southwest Guizhou Autonomous Prefecture (referred it as Qianxinan Prefecture), this essay provides the theoretical reference for clinical diagnosis of thalassemia and suspicious cases.Methods:The pregnant women, spouses and neonates who were screened for thalassemia gene in Qian Xi Nan People's Hospital from January 2016 to December 2020 were selected as the research subjects, and peripheral blood or umbilical cord blood samples were collected to extract DNA. The gap-polymerase chain reaction (Gap-PCR) and next-generation sequencing (NGS) technology were used to screen thalassemia, and ArcMap 10.8 software was adopted to map the local spatial distribution of thalassemia based on the screening data.Results:A total of 67 185 cases of people from various regions in Qianxinan Prefecture were screened, and 8 202 cases of thalassemia gene carriers were detected, with a total detection rate of 12.21%. Among them, 5 660 cases of α-thalassemia, with a detection rate of 8.42%; 2 132 cases of β-thalassemia, with a detection rate of 3.17%; 410 cases of αβ complex thalassemia, with a detection rate of 0.61%. In the detection of thalassemia genes, 27 genotypes of α-thalassemia were detected, mainly αα/-α 3.7, accounting for 41.13% (2 328/5 660); 33 genotypes of β-thalassemia were detected, mainly β CD17(A>T)/β A, accounting for 44.09% (940/2 132); 55 genotypes of αβ complex thalassemia were detected, and αα/-α 3.7 complexed β CD17(A>T)/β A dominated, accounting for 21.22% (87/410). There were high incidence areas in the spatial distribution of thalassemia, which were Wangmo County and Ceheng County, and the detection rate was 26.76% (1 438/5 374), 24.39% (1 314/5 387), respectively. Conclusions:The detection rate of thalassemia gene in Qianxinan Prefecture is relatively high, mainly αα/-α 3.7 genotype of α-thalassemia. Wangmo County and Ceheng County are high-incidence areas of thalassemia, and screening efforts should be continued.
4.Establishment of prognostic model for severe primary graft dysfunction in patients with idiopathic pulmonary fibrosis after lung transplantation
Zhiyun SONG ; Taoyin DAI ; Sijia GU ; Xiaoshan LI ; Murong HUANG ; Shixiao TANG ; Chunxiao HU ; Jingyu CHEN
Organ Transplantation 2024;15(4):591-598
Objective To explore the establishment of a prognostic model based on machine learning algorithm to predict primary graft dysfunction (PGD) in patients with idiopathic pulmonary fibrosis (IPF) after lung transplantation. Methods Clinical data of 226 IPF patients who underwent lung transplantation were retrospectively analyzed. All patients were randomly divided into the training and test sets at a ratio of 7:3. Using regularized logistic regression, random forest, support vector machine and artificial neural network, the prognostic model was established through variable screening, model establishment and model optimization. The performance of this prognostic model was assessed by the area under the receiver operating characteristic curve (AUC), positive predictive value, negative predictive value and accuracy. Results Sixteen key features were selected for model establishment. The AUC of the four prognostic models all exceeded 0.7. DeLong and McNemar tests found no significant difference in the performance among different models (both P>0.05). Conclusions Based on four machine learning algorithms, the prognostic model for grade 3 PGD after lung transplantation is preliminarily established. The overall prediction performance of each model is similar, which may predict the risk of grade 3 PGD in IPF patients after lung transplantation.