Objective To detect the induction of inducible nitric oxide synthase (iNOS) and nitric oxide (NO) production in immunostimulated retinal pigment epithelial (RPE) cells to seek for the supplying of the arginine, a substrate for NOS; as well as the effects of produced NO on the tight junction of RPE-J cells. Methods Rat′s RPE-J cells were treated with interferon-?(INF-?), tumor necrosis factor-?(TNF-?) and lipopolysaccharide (LPS), and Northern and Western blotting were applied to analyze the expression of the citrulline-NO cycle enzymes and related enzymes and the effect of dexamethasone and cyclic adenosine monophosphate (camp) on the expression of iNOS. Immunocytochemistry reaction and Western blotting were used to evaluate the effect of produced NO on the tight junctions of RPE-J cells. Results iNOS and argininosuccinate synthetase (AS) were highly induced at both mRNA and protection levels in immunostimulated RPE cells while arginiosuccinate lyase (AL) was not induced. NO was produced by cells after stimulation with TNF?, IFN? and LPS. The induction of iNOS mRNA and the production of NO by these immunostimulated cells was further enhanced by cAMP. NO was produced from citrulline as well as from arginine. And the produced NO impaired the tight junction of RPE-J cells, decreased the production of tight junction related protein ZO-1. Conclusion In activated RPE-J cells, citrulline-arginine recycling is important for NO production, and the produced NO weakened the function of tight junction of RPE-J cells.

OBJECTIVE:To explore the trend of cooper enrichment in hirudinidae influenced by culture environment. MET-HODS:The soil containing low-content,medium-content and high-content of cooper groups(30.00,60.00,90.00 μg/g)and water culture control group were set up. Hirudinidae leech were culture for 60 d,and sampled every 15 days. ICP-MS techniques was used to determined and compared the contents of cooper in W. pigra and soil. RESULTS:In first 15 days,the contents of cooper in leech from 4 groups increased greatly,compared with before;in the following 15 days,the content of cooper kept stable in high-content group while decreased in other 3 groups;in the 30-45 day,the contents of cooper increased rapidly in 4 groups,and those of low-content group and high-content group reached the peak in this experiment;in the last 15 days,the contents of cooper in control group and high-content group increased continuously,while those of low-content and medium-content groups decreased to some extent. Compared with before,the contents of cooper in leech from control group,low-content,medium-content and high-content groups increased by 292%,186%,293%,464% respectively;those of soil from latter 3 groups increased by 81.12%,35.98% and 21.28% respectively. CONCLUSIONS:The content of cooper in leech increase with time,and is positively correlated with the content of cooper in soil. It is suggested to control the content of cooper in hirudinidae through controlling cul-ture environment when hirudinidae are cultured as medicinal material,in order to meet the quality standard of heavy metal in medic-inal material.

This study was aimed to detect the heavy metal residues of medicinal leeches, in order to understand the current market circulation situation of medicinal leeches, and to analyze possible factors which may cause heavy metal pollution, and to provide references for the standardized safe cultivation of medicinal leeches. Inductively coupled plasma mass spectrometry (ICP-MS) technique was applied to detect heavy metal residues in medicinal leeches. The results showed that medicinal leech samples tested for heavy metal content severely exceeded the standard, which caused a great threat to the safety of medication. It was conclude that more attentions should be paid on factors for causing heavy metal accumulation within medicinal leeches during the breeding process. The related department should also list safety limits explicitly and separately for animal drugs such as medicinal leech during the development of quality standards of Chinese materia medica.

Objective To establish a machine learning radiomics model that can accurately predict MRI enhancement patterns of glioma based on T2 fluid attenuated inversion recovery(T2-FLAIR)images for optimizing the workflow of magnetic resonance imaging(MRI)examinations of glioma patients.Methods We retrospectively collected preoperative MR T2-FLAIR images from 385 patients with pathologically confirmed glioma,who were divided into enhancing and non-enhancing groups according to the enhancement pattern.Predictive radiomics models were established using Gaussian Process,Linear Regression,Linear Regression-Least absolute shrinkage and selection operator,Support Vector Machine,Linear Discriminant Analysis or Naive Bayes as the classifiers in the training cohort(n=201)and tested both in the internal(n=85)and external validation cohorts(n=99).The receiver-operating characteristic curve was used to assess the predictive performance of the models.Results The predictive model constructed based on 15 radiomics features using Gaussian Process as the classifier had the best predictive performance in both the training cohort and the internal validation cohort,with areas under the curve(AUC)of 0.88(95%CI:0.81-0.94)and 0.80(95%CI:0.71-0.88),respectively.In the external validation cohort,the model showed an AUC of 0.81(95%CI:0.71-0.90)with sensitivity,specificity,positive predictive value and negative predictive value of 0.98,0.61,0.76 and 0.96,respectively.Conclusion The T2-FLAIR-based machine learning radiomics model can accurately predict the enhancement pattern of gliomas on MRI.

Objective To explore the biological function and downstream mechanism of ETS1 in glioma.Methods Bioinformatics and immunohistochemistry were used to analyze the differential expression characteristics of ETS1 in gliomas;qRT-PCR was employed to detect the expression level of ETS1 mRNA and lncRNA X-inactive specific transcript(XIST).CCK-8 and 5-ethyl-2′-deoxyuridine experiments were conducted to detect cell growth.Western blot was used to detect the expression of apoptosis-related proteins(Bax,Bak,Bcl-2).PROMO database was utilized to predict the binding sites between ETS1 and XIST promoter.Dual-luciferase reporter gene assay and chromatin immunoprecipitation-quantitative polymerase chain reaction assays were performed to verify the binding relationship between ETS1 and the XIST promoter region.cBioPortal database was used to analyze the correlation between the expression of ETS1 mRNA and XIST in glioma tissues.Results The expression levels of ETS1 mRNA and protein were significantly upregulated in glioma(P<0.05).The depletion of ETS1 significantly inhibited the proliferation of glioma cells and promoted cell apoptosis(P<0.05).ETS1 could target and bind with the XIST promoter and promote the expression of XIST(P<0.05).The overexpression of XIST reversed the effects of ETS1 on the proliferation of glioma cells and the promotion of cell apoptosis(P<0.05).Conclusion ETS1 is highly expressed in glioma tissues.It could promote the expression of lncRNA XIST,boost the proliferation of glioma cells,and inhibit cell apoptosis.

Objective To establish a machine learning radiomics model that can accurately predict MRI enhancement patterns of glioma based on T2 fluid attenuated inversion recovery(T2-FLAIR)images for optimizing the workflow of magnetic resonance imaging(MRI)examinations of glioma patients.Methods We retrospectively collected preoperative MR T2-FLAIR images from 385 patients with pathologically confirmed glioma,who were divided into enhancing and non-enhancing groups according to the enhancement pattern.Predictive radiomics models were established using Gaussian Process,Linear Regression,Linear Regression-Least absolute shrinkage and selection operator,Support Vector Machine,Linear Discriminant Analysis or Naive Bayes as the classifiers in the training cohort(n=201)and tested both in the internal(n=85)and external validation cohorts(n=99).The receiver-operating characteristic curve was used to assess the predictive performance of the models.Results The predictive model constructed based on 15 radiomics features using Gaussian Process as the classifier had the best predictive performance in both the training cohort and the internal validation cohort,with areas under the curve(AUC)of 0.88(95%CI:0.81-0.94)and 0.80(95%CI:0.71-0.88),respectively.In the external validation cohort,the model showed an AUC of 0.81(95%CI:0.71-0.90)with sensitivity,specificity,positive predictive value and negative predictive value of 0.98,0.61,0.76 and 0.96,respectively.Conclusion The T2-FLAIR-based machine learning radiomics model can accurately predict the enhancement pattern of gliomas on MRI.

OBJECTIVETo explore effects of iron overload on hematopoiesis in mice with bone marrow injury and its possible mechanism (s).

METHODSC57BL/6 mice were divided into control, iron, irradiation, irradiation+iron groups. The iron-overloaded model of bone marrow injury was set up after mice were exposed to the dose of 4 Gy total body irradiation and (or) were injected iron dextran intraperitoneally. Iron overload was confirmed by observing iron deposits in mice and bone marrow labile iron pool. Additionally, the number of peripheral blood and bone marrow mononuclear cells and the frequency of erythroid cells and myeloid cells were counted and hematopoietic function was assessed.

RESULTS(1)Iron overload occurred by bone marrow biopsy and flow cytometry analysis. (2)Compared with control group, the number of platelets [(801.9±81.2)×10⁹/L vs (926.0±28.2)×10⁹/L] and BMMNC and the frequency of erythroid cells and myeloid cells decreased. Moreover, hematopoietic colony forming units and single-cell cloning counts decreased significantly in irradiation group (P<0.05). (3)Compared with irradiation group, the number of platelets [(619.0±60.9)×10⁹/L vs (801.9±81.2)×10⁹/L] and the frequency of erythroid cells and myeloid cells decreased; moreover, hematopoietic colony forming units and single-cell cloning counts decreased significantly in irradiation+iron group (P<0.05). (4)Compared with irradiation group, ROS level increased by 1.94 fold in BMMNC, 1.93 fold in erythroid cells and 2.70 fold in myeloid cells, respectively (P<0.05).

CONCLUSIONThe dose of 4 Gy total body irradiation caused bone marrow damage and iron overload based on this injury model, which could damage bone marrow hematopoietic function aggravatingly. And further study found that iron overload was closely related to increased ROS level in BMMNC. The findings would be helpful to further study the injury mechanism of iron overload on the hematopoiesis of bone marrow.

Animals ; Bone Marrow ; injuries ; Bone Marrow Cells ; cytology ; Hematopoiesis ; Iron Overload ; Mice ; Mice, Inbred C57BL