1.Risk prediction of Reduning Injection batches by near-infrared spectroscopy combined with multiple machine learning algorithms.
Wen-Yu JIA ; Feng TONG ; Heng-Xu LIU ; Shu-Qin JIN ; Yong-Chao ZHANG ; Chen-Feng ZHANG ; Zhen-Zhong WANG ; Xin ZHANG ; Wei XIAO
China Journal of Chinese Materia Medica 2025;50(2):430-438
In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods*
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Drugs, Chinese Herbal/administration & dosage*
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Machine Learning
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Algorithms
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Humans
;
Quality Control
2.Bone loss in patients with spinal cord injury: Incidence and influencing factors.
Min JIANG ; Jun-Wei ZHANG ; He-Hu TANG ; Yu-Fei MENG ; Zhen-Rong ZHANG ; Fang-Yong WANG ; Jin-Zhu BAI ; Shu-Jia LIU ; Zhen LYU ; Shi-Zheng CHEN ; Jie-Sheng LIU ; Jia-Xin FU
Chinese Journal of Traumatology 2025;28(6):477-484
PURPOSE:
To investigate the incidence and influencing factors of bone loss in patients with spinal cord injury (SCI).
METHODS:
A retrospective case-control study was conducted. Patients with SCI in our hospital from January 2019 to March 2023 were collected. According to the correlation between bone mineral density (BMD) at different sites, the patients were divided into the lumbar spine group and the hip joint group. According to the BMD value, the patients were divided into the normal bone mass group (t > -1.0 standard deviation) and the osteopenia group (t ≤ -1.0 standard deviation). The influencing factors accumulated as follows: gender, age, height, weight, cause of injury, injury segment, injury degree, time after injury, start time of rehabilitation, motor score, sensory score, spasticity, serum value of alkaline phosphatase, calcium, and phosphorus. The trend chart was drawn and the influencing factors were analyzed. SPSS 26.0 was used for statistical analysis. Correlation analysis was used to test the correlation between the BMD values of the lumbar spine and bilateral hips. Binary logistic regression analysis was used to explore the influencing factors of osteoporosis after SCI. p < 0.05 was considered statistically significant.
RESULTS:
The incidence of bone loss in patients with SCI was 66.3%. There was a low concordance between bone loss in the lumbar spine and the hip, and the hip was particularly susceptible to bone loss after SCI, with an upward trend in incidence (36% - 82%). In this study, patients with SCI were divided into the lumbar spine group (n = 100) and the hip group (n = 185) according to the BMD values of different sites. Then, the lumbar spine group was divided into the normal bone mass group (n = 53) and the osteopenia group (n = 47); the hip joint group was divided into the normal bone mass group (n = 83) and the osteopenia group (n = 102). Of these, lumbar bone loss after SCI is correlated with gender and weight (p = 0.032 and < 0.001, respectively), and hip bone loss is correlated with gender, height, weight, and time since injury (p < 0.001, p = 0.015, 0.009, and 0.012, respectively).
CONCLUSIONS
The incidence of bone loss after SCI was high, especially in the hip. The incidence and influencing factors of bone loss in the lumbar spine and hip were different. Patients with SCI who are male, low height, lightweight, and long time after injury were more likely to have bone loss.
Humans
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Spinal Cord Injuries/complications*
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Male
;
Female
;
Retrospective Studies
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Incidence
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Adult
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Bone Density
;
Middle Aged
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Case-Control Studies
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Osteoporosis/etiology*
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Lumbar Vertebrae
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Bone Diseases, Metabolic/etiology*
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Aged
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Risk Factors
3.Association between Gene Polymorphisms and SNP-SNP Interactions of the Matrix Metalloproteinase 2 Signaling Pathway and the Risk of Vascular Senescence
Yu Zhen LIAO ; Shuo YANG ; Song HU ; Jia LIU ; Jun Yong MAO ; Qin Shu SUN
Biomedical and Environmental Sciences 2024;37(2):146-156
Objective This study aimed to explore the association of single nucleotide polymorphisms(SNP)in the matrix metalloproteinase 2(MMP-2)signaling pathway and the risk of vascular senescence(VS). Methods In this cross-sectional study,between May and November 2022,peripheral venous blood of 151 VS patients(case group)and 233 volunteers(control group)were collected.Fourteen SNPs were identified in five genes encoding the components of the MMP-2 signaling pathway,assessed through carotid-femoral pulse wave velocity(cfPWV),and analyzed using multivariate logistic regression.The multigene influence on the risk of VS was assessed using multifactor dimensionality reduction(MDR)and generalized multifactor dimensionality regression(GMDR)modeling. Results Within the multivariate logistic regression models,four SNPs were screened to have significant associations with VS:chemokine(C-C motif)ligand 2(CCL2)rs4586,MMP2 rs14070,MMP2 rs7201,and MMP2 rs1053605.Carriers of the T/C genotype of MMP2 rs14070 had a 2.17-fold increased risk of developing VS compared with those of the C/C genotype,and those of the T/T genotype had a 19.375-fold increased risk.CCL2 rs4586 and MMP-2 rs14070 exhibited the most significant interactions. Conclusion CCL2 rs4586,MMP-2 rs14070,MMP-2 rs7201,and MMP-2 rs1053605 polymorphisms were significantly associated with the risk of VS.
4. Research progress of Parkin protein regulating mitochondrial homeostasis through ubiquitination in cardiovascular diseases
Ke-Juan LI ; Jian-Shu CHEN ; Yi-Xin XIE ; Jia-Le BU ; Xiao-Wei ZHANG ; Yong-Nan LI
Chinese Pharmacological Bulletin 2024;40(2):224-228
In addition to providing energy for cells, mitochondria also participate in calcium homeostasis, cell information transfer, cell apoptosis, cell growth and differentiation. Therefore, maintaining mitochondrial homeostasis is very crucial for the body to carry out normal life activities. Ubiquitination, a post-translational modification of proteins, is involved in various physiological and pathological processes of cells by regulating mitochondrial homeostasis. However, the mechanism by which ubiquitination regulates mitochondrial homeostasis has not been summarized, especially the effect of Parkin protein on cardiovascular diseases. In this paper, the specific mechanism of mitochondrial homeostasis regulated by ubiquitination of Parkin protein is discussed, and the influence of mitochondrial homeostasis imbalance on cardiovascular diseases is reviewed, with a view to providing potential therapeutic strategies for the clinical treatment of cardiovascular diseases.
5. A new strategy for evaluating antitumor activity in vitro with time-dimensional characteristics of RTCA technology
Fang-Tong LIU ; Shu-Yan XING ; Jia YANG ; Guo-Ying ZHANG ; Rong RONG ; Xiao-Yun LIU ; Dong-Xue YE ; Yong YANG ; Xiao-Yun LIU ; Dong-Xue YE ; Rong RONG ; Yong YANG ; Xiao-Yun LIU ; Dong-Xue YE ; Yong YANG ; Xiao-Yun LIU ; Dong-Xue YE ; Yong YANG
Chinese Pharmacological Bulletin 2024;40(3):592-598
Aim To analyze the anti-A549 and HI299 lung ade-nocarcinoma activities via using examples of baicalin, astragalo-side, hesperidin and cisplatin based on real time cellular analysis (RTCA) technology, and to build a new strategy for EC50 e-valuation reflecting the time-dimensional characteristic. Methods Using RTCA Software Pro for data analysis and GraphPad Prism and Origin Pro plotting, the in vitro anti-A549 and H1299 lung adenocarcinoma activities of baicalin, astragaloside, hesperidin, and cisplatin were characterized using the endpoint method and time dimension, respectively. Results (X) There were significant differences in EC50 values of A549 and H1299 cells at 24 h and 48 h endpoint methods. (2) The correlation coefficient of the curve fitted with the four-parameter equation was > 0. 9, and the dynamic change of EC50 remained relatively stable (the linear fitting of EC50 at adjacent 4 points I slope 1^1) used to calculate the EC50 value within this time dimension. The EC50 of baicalin, astragaloside, hesperidin and cisplatin on A549 cells was 52. 97 ±1.75 плпо! • L~1(16~48 h) , 62.88 ± 2.91 ijunol • L"1 (32.25 -48 h) , 78.84 ±0.33 плпо1 • L"1 (21.5 -29.75 h), 13.57 ±1.54 плпо1 • L_1(27.5 -48 h), respectively; the EC50 of baicalin, astragaloside, hesperidin and cisplatin on H1299 cells was 43. 71 ± 1. 26 |лто1 • L_1 ( 19. 5 -48 h), 47.23 ±1. 19 |лто1 • L_1(14 -48 h) , 39.45 ±0.24 плпо1 • L"1 (12.75 -46.25 h), 25.97 ±4.76 плпо1 • L"1 (10. 25 -48 h) , respectively. The results showed that the time window for the anti-tumor effect of the test solution/drug was different. Conclusions Based on RTCA technology, it is more accurate and reasonable to select EC50 data that exhibit better fitting, stable changes, and time-dimensional characteristics for the evaluation of anti-tumor activity. In addition, this method of distinguishing different effective time of antitumor drugs can provide a reference for the timing of clinical combination drugs, and this approach will also provide a reference for further related studies.
6.Optimization of the extraction process of peptide from Poecilobdella manillensis by response surface methodology and investigation of its whitening and anti-aging activities
Jia-hui WANG ; Shu-qi LI ; Hao LIU ; Hai-tao GUO ; Guo-hua YANG ; Yu-sheng YANG ; Yong-gang LIU ; Tao MA
Acta Pharmaceutica Sinica 2024;59(12):3394-3401
The objective of this study was to optimise the extraction process of peptide of
7.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
8.Purification process for coumarins in Fraxini Cortex by macroporous resin
Dong-Xu ZHANG ; Yong ZHANG ; Si-Han XU-CHEN ; Jia-Yi ZHOU ; Le-Yang YU ; Shen-Shu WANG ; Tong ZHANG ; Yue DING
Chinese Traditional Patent Medicine 2024;46(9):2885-2891
AIM To investigate the purification process for esculin,fraxin,esculetin and fraxetin in Fraxini Cortex by macroporous resin.METHODS Static adsorption experiment was applied to screening resin model,single factor test was adopted in the optimization of purification process,UPLC-QTOF-MS/MS was used for identifying main components,after which heatmap was drawn.RESULTS The optimal resin model was ADS-5.The optimal purification process was determined to be 1.1 BV for loading amount,0.75 g/mL for loading concentration,2 BV pure water for washing impurity,and 4 BV 25%ethanol for eluting effective constituents,coumarins demonstrated the total transfer rate,purity and yield of 84.42%,53.28%and 4.79%,respectively.Total 37 constituents were identified,among which coumarins and phenylethanol glycosides were mainly concentrated in 25%ethanol eluent,organic acids,iridoids and flavonoids were mainly concentrated in 95%ethanol eluent.CONCLUSION This stable,feasible and accurate method can characterize the distribution patterns of coumarins in Fraxini Cortex in different eluents of macroporous resin,which provides guidance for further related pharmaceutical research.
9.Altered microRNA expression profiles of human spermatozoa in normal fertile men of different ages.
Ming-Jia ZHAO ; Yao-Nan ZHANG ; Yong-Ping ZHAO ; Xian-Bing CHEN ; Bao-Sheng HAN ; Ning DING ; Yi-Qun GU ; Shu-Song WANG ; Jing MA ; Mei-Ling LIU
Asian Journal of Andrology 2023;25(6):737-744
MicroRNAs (miRNAs) are mediators of the aging process. The purpose of this work was to analyze the miRNA expression profiles of spermatozoa from men of different ages with normal fertility. Twenty-seven donors were divided into three groups by age (Group A, n = 8, age: 20-30 years; Group B, n = 10, age: 31-40 years; and Group C, n = 9, age: 41-55 years) for high-throughput sequencing analysis. Samples from 65 individuals (22, 22, and 21 in Groups A, B, and C, respectively) were used for validation by quantitative real-time polymerase chain reaction (qRT-PCR). A total of 2160 miRNAs were detected: 1223 were known, 937 were newly discovered and unnamed, of which 191 were expressed in all donors. A total of 7, 5, and 17 differentially expressed microRNAs (DEMs) were found in Group A vs B, Group B vs C, and Group A vs C comparisons, respectively. Twenty-two miRNAs were statistically correlated with age. Twelve miRNAs were identified as age-associated miRNAs, including hsa-miR-127-3p, mmu-miR-5100_L+2R-1, efu-miR-9226_L-2_1ss22GA, cgr-miR-1260_L+1, hsa-miR-652-3p_R+1, pal-miR-9993a-3p_L+2R-1, hsa-miR-7977_1ss6AG, hsa-miR-106b-3p_R-1, hsa-miR-186-5p, PC-3p-59611_111, hsa-miR-93-3p_R+1, and aeca-mir-8986a-p5_1ss1GA. There were 9165 target genes of age-associated miRNAs. Gene Ontology (GO) analysis of the target genes identified revealed enrichment of protein binding, membrane, cell cycle, and so on. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of age-related miRNAs for target genes revealed 139 enriched pathways, such as signaling pathways regulating stem cell pluripotency, metabolic pathways, and the Hippo signaling pathway. This suggests that miRNAs play a key role in male fertility changes with increasing age and provides new evidence for the study of the mechanism of age-related male fertility decline.
Humans
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Male
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Young Adult
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Adult
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Middle Aged
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MicroRNAs/genetics*
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Signal Transduction/genetics*
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Spermatozoa/metabolism*
;
Gene Expression Profiling
10.Protective Mechanism of Cordyceps sinensis Treatment on Acute Kidney Injury-Induced Acute Lung Injury through AMPK/mTOR Signaling Pathway.
Ruo-Lin WANG ; Shu-Hua LIU ; Si-Heng SHEN ; Lu-Yong JIAN ; Qi YUAN ; Hua-Hui GUO ; Jia-Sheng HUANG ; Peng-Hui CHEN ; Ren-Fa HUANG
Chinese journal of integrative medicine 2023;29(10):875-884
OBJECTIVE:
To investigate protective effect of Cordyceps sinensis (CS) through autophagy-associated adenosine monophosphate-activated protein kinase (AMPK)/mammalian target of rapamycin (mTOR) signaling pathway in acute kidney injury (AKI)-induced acute lung injury (ALI).
METHODS:
Forty-eight male Sprague-Dawley rats were divided into 4 groups according to a random number table, including the normal saline (NS)-treated sham group (sham group), NS-treated ischemia reperfusion injury (IRI) group (IRI group), and low- (5 g/kg·d) and high-dose (10 g/kg·d) CS-treated IRI groups (CS1 and CS2 groups), 12 rats in each group. Nephrectomy of the right kidney was performed on the IRI rat model that was subjected to 60 min of left renal pedicle occlusion followed by 12, 24, 48, and 72 h of reperfusion. The wet-to-dry (W/D) ratio of lung, levels of serum creatinine (Scr), blood urea nitrogen (BUN), inflammatory cytokines such as interleukin- β and tumor necrosis factor- α, and biomarkers of oxidative stress such as superoxide dismutase, malonaldehyde (MDA) and myeloperoxidase (MPO), were assayed. Histological examinations were conducted to determine damage of tissues in the kidney and lung. The protein expressions of light chain 3 II/light chain 3 I (LC3-II/LC3-I), uncoordinated-51-like kinase 1 (ULK1), P62, AMPK and mTOR were measured by Western blot and immunohistochemistry, respectively.
RESULTS:
The renal IRI induced pulmonary injury following AKI, resulting in significant increases in W/D ratio of lung, and the levels of Scr, BUN, inflammatory cytokines, MDA and MPO (P<0.01); all of these were reduced in the CS groups (P<0.05 or P<0.01). Compared with the IRI groups, the expression levels of P62 and mTOR were significantly lower (P<0.05 or P<0.01), while those of LC3-II/LC3-I, ULK1, and AMPK were significantly higher in the CS2 group (P<0.05 or P<0.01).
CONCLUSION
CS had a potential in treating lung injury following renal IRI through activation of the autophagy-related AMPK/mTOR signaling pathway in AKI-induced ALI.
Rats
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Male
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Animals
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AMP-Activated Protein Kinases/metabolism*
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Cordyceps/metabolism*
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Rats, Sprague-Dawley
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Kidney/pathology*
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Acute Kidney Injury/metabolism*
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Signal Transduction
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TOR Serine-Threonine Kinases/metabolism*
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Reperfusion Injury/metabolism*
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Cytokines/metabolism*
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Acute Lung Injury/drug therapy*
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Mammals/metabolism*

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