Objective To prepare a redox-responsive doxorubicin-loaded nanoparticle,and to study its in vitro realease behavior and targeting effect on heptoma cells.Methods Cystamine was grafted on the side chains of hyaluronic acid with 1-(3-dimethylaminopropyl)-3-ethylcarbodiimide hydrochloride/N-hydroxysuccinimide catalyst,and then β-cyclodextrin (β-CD) was conjugated on the amine groups of the cystamine by Schiff's base reaction to prepare β-CD modified hyaluronic acid (HACD).The HACD/DOX nanoparticles were prepared by encapsulating DOX into HACD using dialysis method.The drug loading,encapsulation efficiency,particle size and distribution,zeta potential and other physical and chemical properties,as well as in vitro drug release behavior of the HACD/DOX nanoparticles were characterized.The cytotoxicity of HACD/DOX nanoparticles to HepG2 cells was studied by cell counting kit-8 (CCK-8) method.The targeting effect of HACD/DOX nanoparticles on HepG2 cells was studied using flow cytometry and confocal laser scanning microscopy (CLSM).Results HACD were successfully synthesized,which could carry DOX to form uniform homogeneous nanoparticles.The drug loading of DOX in the nanoparticles was (16.1±0.2)％ and the encapsulation efficiency was (64.2±0.9)％.The transmission electron microscope images indicated that the shape of the HACD/DOX nanoparticles was homogeneous sphere.The results of granularity analysis showed that the average size of the HACD/DOX nanoparticles was (203.1 ±2.5) nm with a narrow size distribution (PDI =0.202).The zeta potential of the HACD/DOX nanoparticles was (-29.1±0.8) mV.The in vitro release behavior of the nanoparticles exhibited obvious redox-sensitivity.The results of in vitro cytotoxicity showed that the blank carrier material HACD had no obvious toxicity to hepatoma cells,and the HACD/DOX nanoparticles could effectively kill hepatoma cells with the 0.38 μg/ml half maximal inhibitory concentration (IC50) value at 48 h.Flow cytometry and CLSM results demonstrated that the HACD/DOX nanoparticles could target hepatoma cells through the mediating effect of hyaluronic acid.Conclusions The prepared HACD/DOX nanoparticles have suitable particle size,high drug loading and encapsulation efficiency,and can release DOX under the stimulation of reducing agent.These nanoparticles have obvious targeting effect on hepatoma cells,which is expected to be applied as the drug delivery system of hepatocellular carcinoma (HCC) therapy.

Objective To identify the role of RNA-editing enzyme ADAR1 (adenosine deaminase acting on RNA) in EV71 infection and virus mutation.Methods RNAi technology was applied to establish ADAR1 knock-down stable cell lines.Then the cells were served to evaluate the role of ADAR1 in EV71 infection by MTT assay for detecting virus-induced cell viability,virus plaque assay for quantification of the virus titer and the cellular susceptibility to the virus,and Western blot for virus protein expressions.ADAR1-mediated RNA editing can result in the genetic A-G and T-C mutations.To further determine whether the effects of ADAR1 on EV71 infection were correlated with ADAR1-mediated EV71 RNA editing and therefore increased the viral mutations during the infection,the characteristics of EV71 mutation were analyzed based on the different full-length viral genomes from epidemic regions.The viral genome was also sequenced from the infected ADAR1 knock-down cells.Results After ADAR1 knock-down,the cell viability decreased quickly after the virus infection,and formed much more and larger sizes of plaques than the control cells.The virus capsid protein VP1 expressions and virus titer in the cells culture media were both increased in ADAR1 knockdown cells.Statistic analysis showed that A-G and T-C mutations were the major mutations of EV71,which were believed to be the hot sites for RNA-editing.However,the results of viral RNA genomic sequencing data indicated that ADAR1 did not edit EV71 genome directly.Conclusions ADAR1 was a restriction factor for controlling EV71.However,ADAR1 does not directly edit EV71 genome.

Objective To investigate the effects of hypoxia-inducible factor-1α (HIF-1α)expression on pathogenesis of retinopathy of prematurity (ROP) and to find new target for gene therapy.Methods After liposome-mediated small interference RNA (siRNA) transfection into rat retinal endothelial cells,the cells were cultured in medium with CoCl2-induced hypoxic condition.Expression of HIF-1α mRNA was determined by fluorenscence quantitative reverse transcription-polymerase chain reaction(RT-PCR),HIF-1α protein expression was detected by Western Blot after cocultured for 8 hours.Cell proliferation was measured with 3-(4,5)-dimethylthiazol (-2-yl)-2,5-diphenyltetrazolium bromide(MTT) assay after cocultured for 24 hours.Difference between groups was compared with independent samples t test.Results Rat retinal vascular endothelial cells were successfully transfected with siRNA.Fluorescence quantitative RT-PCR results showed that at 48 hours of transfection,the expression of HIF-1α mRNA in the interference group of siRNA1,siRNA2 and siRNA4 were 0.1620 ± 0.0147,0.2034 ± 0.0251 and 0.3049 ± 0.0165,which were 16.20％,20.34 ％ and 30.49％ of blank control group (1.0000±0.0344),and were lower than that of negative control group (0.8334±0.0242) (t=16.786,8.953 and 4.087,P＜0.05 respectively).Western Blot results showed that HIF-1α protein expression was significantly inhibited by siRNA1(0.4956 ± 0.0421 ) and siRNA2 (0.6544 ± 1.0032) comparing with blank control group (3.5105 ±0.4084) and negative control group (3.4019 ± 1.0677) (t =6.861,2.893,4.567 and 5.072,P＜0.05 respectively).As for cellular proliferation activity,(49.5±2.9) ％ and (67.4±1.2) ％ of cells growth inhibition were observed after transfection with siRNA1 and siRNA2,which were higher than those of negative control group [(15.7±1.5) ％ ] (t=2.786 and 6.904,P＜0.05).Conclusions The synthetic HIF-1α siRNA could effectively inhibit the expression of HIF-1α gene and reduce cell proliferation in rat retinal endothelial cells under hypoxic condition.RNA interference technology targeting HIF-1α might become a new strategy for gene therapy of ROP.

Objective:To investigate the risk factors for recurrence after liver transplantation in patients with hepatitis B virus (HBV) infection-related hepatocellular carcinoma (HCC), and to further construct a predictive model.Methods:The clinical data of 106 patients with HCC undergoing liver transplantation in the First Affiliated Hospital of Hebei North University from January 2015 to May 2020 were retrospec-tively analyzed. The χ2 test was used to analyze the factors influencing HCC recurrence, and multivariate logistic regression was used to analyze the influencing factors of HCC recurrence. According to the selected risk factors, the predictive model of HCC recurrence was constructed, and the receiver operating characteristic (ROC) curve was used to evaluate the predictive model. Results:Of the 106 HCC patients, 23 had recurrence, with a recurrence rate of 21.70%, and 20 died. Tumor differentiation ( χ2=6.066, P=0.014), maximum tumor diameter ( χ2=4.916, P=0.027), with or without envelope invasion ( χ2=5.543, P=0.019), preoperative alpha fetoprotein (AFP) ( χ2=5.458, P=0.019), HBV-DNA ( χ2=5.446, P=0.020), neutrophil lymphocyte ratio (NLR) ( χ2=12.161, P<0.001), the expressions of miR-424 ( χ2=4.400, P=0.036), chromodomain helicase DNA-binding protein 8 (CHD8) ( χ2=10.561, P=0.001), T-cadherin (T-cad) ( χ2=48.723, P<0.001), laminin (LN) ( χ2=18.506, P<0.001) and hepatocyte growth factor (HGF) ( χ2=11.178, P=0.001) were related to the recurrence of HCC. Multivariate logistic regression analysis showed that the maximum tumor diameter≥6.5 cm ( OR=1.69, 95% CI: 1.25-3.17, P=0.002), preoperative AFP>400 ng/ml ( OR=1.38, 95% CI: 1.09-1.92, P=0.038), positive CHD8 ( OR=0.77, 95% CI: 0.52-0.89, P=0.021), positive T-cad ( OR=0.84, 95% CI: 0.68-0.92, P=0.006), positive LN ( OR=1.22, 95% CI: 1.03-1.50, P=0.013) were the risk factors of HCC recurrence. According to the results of logistic analysis, the regression equation logit( P)=0.262+ 0.523 X1+ 0.326 X2-0.259 X3-0.286 X4+ 0.203 X5 was constructed, where X1, X2, X3, X4, X5 were the maximum tumor diameter, AFP, CHD8, T-cad and LN. ROC curve analysis showed that the area under the curve for predicting HCC recurrence was 0.849 (95% CI: 0.763-0.894, P<0.001), the accuracy rate was 83.02%, the sensitivity was 86.96%, the specificity was 81.93%, and the cut-off value was 0.736. According to the logit( P) function model, P=1/(1+ e - Y), where Y=0.262+ 0.523 X1+ 0.326 X2-0.259 X3-0.286 X4+ 0.203 X5. One patient was randomly selected. According to his clinical data, P=0.564, which was less than the cut-off value (0.736). It could be considered that this patient would not have HCC recurrence with an accuracy rate of 83.02%. Conclusion:Tumor maximum diameter, preoperative AFP, CHD8, T-cad, LN expression are related to the recurrence of HCC after liver transplantation. The prediction model constructed based on this can effectively predict the risk of HCC recurrence.

Objective To investigate the dosimetric effect of accelerator gantry rotation angle errors, collimator and multileaf collimator ( MLC) leaf position errors on volumetric-modulated arc therapy ( VMAT) for cervical cancer. Methods A total of 10 patients with cervical cancer were selected. The plan. Trail file of each clinical plan was extracted from the Pinnacle3 V9. 2 planning system of USA Philips, then the operating parameters of tach control point were read and modified by Matlab programs, and thus the operating error of the accelerator was simulated. Results In this paper, it was discovered that systematic accelerator gantry rotation angle errors, systematic collimator position errors and systematic MLC shift errors which led to the maximum changes of the PTV dose limit were 0. 16％, 0. 46％ and 0. 57％, respectively, and the maximum changes of the dose limit of organs at risk ( OAR) were 0. 38％, -1. 32％ and -0. 44％, respectively. When the systematic MLC gap width errors were ± 0. 5, ± 1 and ± 2 mm, respectively, the maximum changes of PTV dose were 2. 11％, 3. 04％ and 6. 03％, respectively, while the maximum changes of the OAR average dose were 2. 17％, 3. 92％ and 7. 97％, respectively. Furthermore, the dose limits of PTV and OAR showed a strong linear correlation with MLC open or close errors(t=21. 201～90. 562,P<0. 05). If actual errors of each parameter of accelerator were introduced, the maximum changes of PTV and OAR dose limits were 0. 16％ and 1. 30％, respectively, and conformity index (CI) and homogeneity index (HI) were barely changed. Conclusions No significant effect was found for systematic accelerator gantry rotation angle errors, systematic collimator position errors and systematic MLC shift errors for cervical cancer VMAT patients. However, there is a high sensitivity to dose distribution for MLC open or close errors. Therefore, it is necessary to pay more attention on the quality control of the accelerator running in particular MLC position errors to ensure the therapeutic accuracy.

OBJECTIVE: To assess the association of apolipoprotein (apo) C1 (APOC1) gene rs4420638A/G and -317H1/H2 polymorphisms with the risk of pre-eclampsia (PE) and the influence of their genotypes on the clinical and metabolic indexes among Chinese women. METHODS: In total 289 PE patients and 824 women with uncomplicated pregnancies were included. The rs4420638A/G genotype was determined by a Taqman real-time PCR allelic discrimination assay. The -317H1/H2 genotype was measured through PCR and restriction fragment length polymorphism analysis. Serum lipid and apo levels were measured by an enzymatic kit and a PEG-enhanced immunoturbidimetric assay. RESULTS: Allelic and genotypic frequencies of the APOC1 gene rs4420638A/G and -317H1/H2 were not significantly different between the two groups (all P> 0.05). However, patients carrying the G allele of the rs4420638A/G locus had higher serum levels of triglyceride, non-HDL-C and apoB, and a higher apoB/apoA1 ratio compared with those with an AA genotype (all P< 0.05). Patients carrying the H2 allele of the -317H1/H2 polymorphism had smaller delivery gestational weeks compared with those with the H1H1 genotype (P< 0.05). CONCLUSION Polymorphisms of the APOC1 gene rs4420638 and -317H1/H2 sites may be associated with abnormal lipoprotein metabolism among Chinese patients with PE, though no association was found between variants of the APOC1 gene and the risk of PE among them.

Background: This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Methods: The study identified DKD risk factors through literature review and physician focus group, and collected 7 years of data from 6,040 type 2 diabetes mellitus patients based on the risk factors. Pytorch was used to build the LSTM neural network, with 70% of the data used for training and the other 30% for testing. Three models were established to examine the impact of glycosylated hemoglobin (HbA1c), systolic blood pressure (SBP), and pulse pressure (PP) variabilities on the model’s performance. Results: The developed model achieved an accuracy of 83% and an AUC of 0.83. When the risk factor of HbA1c variability, SBP variability, or PP variability was removed one by one, the accuracy of each model was significantly lower than that of the optimal model, with an accuracy of 78% (P<0.001), 79% (P<0.001), and 81% (P<0.001), respectively. The AUC of ROC was also significantly lower for each model, with values of 0.72 (P<0.001), 0.75 (P<0.001), and 0.77 (P<0.05). Conclusion The developed DKD risk predictive model using LSTM neural networks demonstrated high accuracy and AUC value. When HbA1c, SBP, and PP variabilities were added to the model as featured characteristics, the model’s performance was greatly improved.

Background: This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Methods: The study identified DKD risk factors through literature review and physician focus group, and collected 7 years of data from 6,040 type 2 diabetes mellitus patients based on the risk factors. Pytorch was used to build the LSTM neural network, with 70% of the data used for training and the other 30% for testing. Three models were established to examine the impact of glycosylated hemoglobin (HbA1c), systolic blood pressure (SBP), and pulse pressure (PP) variabilities on the model’s performance. Results: The developed model achieved an accuracy of 83% and an AUC of 0.83. When the risk factor of HbA1c variability, SBP variability, or PP variability was removed one by one, the accuracy of each model was significantly lower than that of the optimal model, with an accuracy of 78% (P<0.001), 79% (P<0.001), and 81% (P<0.001), respectively. The AUC of ROC was also significantly lower for each model, with values of 0.72 (P<0.001), 0.75 (P<0.001), and 0.77 (P<0.05). Conclusion The developed DKD risk predictive model using LSTM neural networks demonstrated high accuracy and AUC value. When HbA1c, SBP, and PP variabilities were added to the model as featured characteristics, the model’s performance was greatly improved.

Background: This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve. Methods: The study identified DKD risk factors through literature review and physician focus group, and collected 7 years of data from 6,040 type 2 diabetes mellitus patients based on the risk factors. Pytorch was used to build the LSTM neural network, with 70% of the data used for training and the other 30% for testing. Three models were established to examine the impact of glycosylated hemoglobin (HbA1c), systolic blood pressure (SBP), and pulse pressure (PP) variabilities on the model’s performance. Results: The developed model achieved an accuracy of 83% and an AUC of 0.83. When the risk factor of HbA1c variability, SBP variability, or PP variability was removed one by one, the accuracy of each model was significantly lower than that of the optimal model, with an accuracy of 78% (P<0.001), 79% (P<0.001), and 81% (P<0.001), respectively. The AUC of ROC was also significantly lower for each model, with values of 0.72 (P<0.001), 0.75 (P<0.001), and 0.77 (P<0.05). Conclusion The developed DKD risk predictive model using LSTM neural networks demonstrated high accuracy and AUC value. When HbA1c, SBP, and PP variabilities were added to the model as featured characteristics, the model’s performance was greatly improved.

Objective To discuss the pathological and clinical characteristics,treatments and prognosis of schwannoma of the kidney.Methods Two cases of schwannoma of the kidney in our hospital were reviewed with clinicopathological data and their follow-up.The related literatures were reviewed.The first case was a male patient,28 years old,complained about paroxysmal abdominal pain with nausea over 2 weeks.The physical exam found a 10 cm,qualitative hard,poor activity,tenderness mass in kidney region.MRI preoperative diagnosis was right renal cell carcinoma with renal vein and inferior vena cava tumor thrombus formation.The second patient,female,53 years old,the mass on upper right kidney was found occasionally.It was diagnosed as adrenal pheochromocytoma before operation,laparoscopic resection of right renal hilum mass and right partial adrenectomy plus right nephrectomy were performed.There was no tumor recurrence in the follow-up.Results The abdominal aortography and double renal arteriography were done and right renal artery embolization and inferior vena cava filter were allocated.Then right radical nephrectomy and inferior vena cava tumor thrombus removal were carried out on the first patient.The first malignant and the second benign renal schwannoma patient showed significant difference in pathological presentations.Their immunohistochemistry also showed great diversity.Malignant renal schwannoma was significantly stained by Ki-67 ＞ 40％,S-100 was negative.Ki-67 in benign neurilemmomas was about 2％,and S-100 in benign renal schwannoma was positive.Conclusions Schwannoma of the kidney is rare with a favorable prognosis.The golden standard of diagnosis is pathology.Surgical resection has become the first choice for treatment.Recurrence and malignant transformation would happen after the surgery so that all the patients should be followed up.