Effects of anti-ganglioside GD2 14G2a monoclonal antibody (mAb) alone or in combination with ET A receptor (ETAR) antagonist on osteosarcoma (OS) cell viability.

<p>Methlythiazoletetrazolium (MTT) cell viability assays were performed in Saos-2 (<i>A</i>), MG-63 (<i>B</i>) and SJSA-1 (<i>C</i>) OS cells treated with control IgG (PK136 mAb, 50 µg/mL), 14G2a mAb (50 µg/mL), selective ETAR antagonist BQ123 (5 µM), and 14G2a (50 µg/mL)+BQ123 (5 µM) for 24 or 48 hours. Cells with knockdown of ETAR (ETAR-shRNA) with or without 14G2a mAb treatment were also tested. Cells treated with selective phosphatidylinositide 3-kinase (PI3K) inhibitor BKM120 (50 µM) was used as a positive control. Viability of the control cells was designated as 100%. The inhibition rate of cell viability was calculated and shown as a percentage of the control cell viability. Each experiment was repeated for three times in triplicates. Data values were expressed as Mean+SD.</p

Effects of anti-ganglioside GD2 14G2a monoclonal antibody (mAb) alone or in combination with ET A receptor (ETAR) antagonist on matrix metalloproteinase-2 (MMP-2) mRNA levels in osteosarcoma (OS) cells.

<p>MMP-2 mRNA levels were determined by real-time RT-PCR in Saos-2 (<i>A</i>), MG-63 (<i>B</i>) and SJSA-1 (<i>C</i>) OS cells treated with control IgG (PK136 mAb, 50 µg/mL), 14G2a mAb (50 µg/mL), selective ETAR antagonist BQ123 (5 µM), and 14G2a (50 µg/mL)+BQ123 (5 µM) for 48 hours. Cells with knockdown of ETAR (ETAR-shRNA) with or without 14G2a mAb treatment were also tested. Cells treated with selective phosphatidylinositide 3-kinase (PI3K) inhibitor BKM120 (50 µM) was used as a positive control. The MMP-2 mRNA level was shown as fold changes to that of the untreated control cells (designated as 1). Each experiment was repeated for three times in duplicates. Data values were expressed as Mean+SD. ^a<i>p</i><0.05 vs. control or control IgG; ^b<i>p</i><0.05 vs. BQ123; ^c<i>p</i><0.05 vs. ETAR-shRNA; ^d<i>p</i><0.05 vs. 14G2a; ^e<i>p</i><0.05 vs. 14G2a+BQ123; ^f<i>p</i><0.05 vs. 14G2a+ETAR-shRNA.</p

Endothelin-1 (ET-1) and ET A receptor (ETAR) expression levels and scatchard plot for anti-ganglioside GD2 14G2a monoclonal antibody (mAb) binding sites in human osteosarcoma (OS) cells.

<p>(<i>A</i>) ETAR levels were determined by Western blot analysis in Saos-2, MG-63 and SJSA-1 human OS cell lines. <i>Lane 1</i>, SJSA-1 cells; <i>lane 2</i>, SJSA-1 cells stably transduced with ETAR-shRNA; <i>lane 3</i>, MG-63 cells; <i>lane 4</i>, MG-63 cells stably transduced with ETAR-shRNA; <i>lane 5</i>, Saos-2 cells; <i>lane 6</i>, Saos-2 cells stably transduced with ETAR-shRNA. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) blotting was used as a loading control. Density of the ETAR blot was normalized against that of GAPDH to obtain a relative blot density, which was expressed as fold changes to the relative ETAR blot density of SJSA-1 control cells (designated as 1). Three independent experiments were performed for each Western blot analysis. Data values were expressed as Mean+SD. *<i>p</i><0.05 vs. control. (<i>B</i>) Secreted ET-1 levels in cell culture supernatants were quantified using ELISA and normalized against cell number (per 10⁶ cells). Each ELISA experiment was repeated for three times in duplicates. Data values were expressed as Mean+SD. (<i>C</i>) Scatchard plot for binding of I-125-labeled anti-ganglioside GD2 14G2a mAb to OS cells.</p

Effects of anti-ganglioside GD2 14G2a monoclonal antibody (mAb) alone or in combination with ET A receptor (ETAR) antagonist on phosphatidylinositide 3-kinase (PI3K) activity in osteosarcoma (OS) cells.

<p>PI3K activities were determined with a PI3K Activity ELISA kit (Echelon Biosciences) in Saos-2 (<i>A</i>), MG-63 (<i>B</i>) and SJSA-1 (<i>C</i>) OS cells treated with control IgG (PK136 mAb, 50 µg/mL), 14G2a mAb (50 µg/mL), selective ETAR antagonist BQ123 (5 µM), and 14G2a (50 µg/mL)+BQ123 (5 µM) for 48 hours. Cells with knockdown of ETAR (ETAR-shRNA) with or without 14G2a mAb treatment were also tested. Cells treated with selective phosphatidylinositide 3-kinase (PI3K) inhibitor BKM120 (50 µM) was used as a positive control. The PI3K activity was shown as fold changes to that of the untreated control cells (designated as 1). Each experiment was repeated for three times in duplicates. Data values were expressed as Mean+SD. ^a<i>p</i><0.05 vs. control or control IgG; ^b<i>p</i><0.05 vs. BQ123; ^c<i>p</i><0.05 vs. ETAR-shRNA; ^d<i>p</i><0.05 vs. 14G2a; ^e<i>p</i><0.05 vs. 14G2a+BQ123; ^f<i>p</i><0.05 vs. 14G2a+ETAR-shRNA.</p

Data_Sheet_1_Measuring equality in access to urban parks: A big data analysis from Chengdu.docx

Spatial equality of parks is a significant issue in environmental justice studies. In cities with high-density development and limited land resources, this study uses a supply-demand adjusted two-step floating catchment area model (2SFCA), paying attention to residents' subjective preferences and psychological accessibility. It assesses equality of access to urban parks from two dimensions: spatial equality and quantitative equality at a fine scale of 100 × 100 m grid resolution. The spatial equality of urban parks in Chengdu is measured under different transportation modes (walking, cycling, and driving) based on multi-source geospatial big data and machine learning approaches. The results show: (1) There were significant differences in the spatial distribution of park accessibility under different modes of transportation. The spatial distribution under walking was significantly influenced by the park itself, while the distribution of rivers significantly influenced the spatial distribution under cycling and driving; (2) Accessibility to urban parks was almost universally equal in terms of driving, relatively equal in terms of cycling, and seriously unequal in terms of walking; (3) Spatial local autocorrelation analysis shows that park accessibility tended to be significantly clustered, with little spatial variation; and (4) The supply and demand of urban parks were relatively equal. The results can help urban planners to formulate effective strategies to alleviate spatial inequality more reasonably and precisely. The applied research methods can further improve the system of scientific evaluation from a new perspective.</p

Table_1_Measuring equality in access to urban parks: A big data analysis from Chengdu.XLSX

Spatial equality of parks is a significant issue in environmental justice studies. In cities with high-density development and limited land resources, this study uses a supply-demand adjusted two-step floating catchment area model (2SFCA), paying attention to residents' subjective preferences and psychological accessibility. It assesses equality of access to urban parks from two dimensions: spatial equality and quantitative equality at a fine scale of 100 × 100 m grid resolution. The spatial equality of urban parks in Chengdu is measured under different transportation modes (walking, cycling, and driving) based on multi-source geospatial big data and machine learning approaches. The results show: (1) There were significant differences in the spatial distribution of park accessibility under different modes of transportation. The spatial distribution under walking was significantly influenced by the park itself, while the distribution of rivers significantly influenced the spatial distribution under cycling and driving; (2) Accessibility to urban parks was almost universally equal in terms of driving, relatively equal in terms of cycling, and seriously unequal in terms of walking; (3) Spatial local autocorrelation analysis shows that park accessibility tended to be significantly clustered, with little spatial variation; and (4) The supply and demand of urban parks were relatively equal. The results can help urban planners to formulate effective strategies to alleviate spatial inequality more reasonably and precisely. The applied research methods can further improve the system of scientific evaluation from a new perspective.</p

The changes of Th subsets were assayed by flow cytometry and real-time PCR.

<p>A, B: Influence of NS1 on changes of Th subsets was assayed by flow cytometry (**P<0.01 versus 16 HBE group; ##P<0.01 versus GFP group; P<0.01 GFP-NS1 group). C. Influence of NS2 on changes of Th subsets was assayed by flow cytometry (**P<0.01 versus 16 HBE group; ##P<0.01 versus RFP group; P<0.01 RFP-NS2 group). D: Influence of NS1 on changes of Th subsets was assayed by real-time PCR (**P<0.01 versus GFP group; ##P<0.01 GFP-NS1 group). E. influence of NS2 on changes of Th subsets was assayed by real-time PCR (**P<0.01 versus RFP group; ##P<0.01 RFP-NS2 group). Data represent Means ± SE of 6 experiments.</p

Titers of pLenO-GFP-NS1 and pLenO-RFP-NS2 were assayed by flow cytometry.

<p>A, B: Infection of HEK293T cells with different dilutions of pLenO-GFP-NS1 under light microcopy and fluorescence microscopy respectively (×100); C, D: Infection of HEK293T cells with different dilutions of pLenO-RFP-NS2 under light microcopy and fluorescence microscopy respectively. From above to below represent the concentration of 1.0 ul, 0.1 ul, 0.01 ul and representative images of flow cytometry (0.01 ul).</p

The contents of IFN-, IL-4 and IL-17 from cocultured 16 HBE and lymphocytes were assayed by ELISA (n = 6).

<p>A: Influence of NS1 on the secretion of IFN-, IL-4 and IL-17 from cocultured 16 HBE in the presence of OVA and lymphocytes (**P<0.01 versus GFP group; ## P<0.01 versus GFP-NS1 group) B: Influence of NS1 on the secretion of IFN-, IL-4 and IL-17 from cocultured 16 HBE in the presence of OVA and lymphocytes. (*P<0.05, **P<0.01 versus RFP group; # p<0.05, ## P<0.01 versus RFP-NS2 group).</p

Efficiencies of lentiviral infections to 16 HBE were assayed by fluorescence microscopy and indirect immunofluorescent technology.

<p>A: Infection of 16 HBE by pLenO-GFP-NS1 (MOI = 10); B: Infection of 16 HBE by pLenO-RFP-NS2 (MOI = 10). From above to below represent images under light microcopy, fluorescence microscopy and indirect immunofluorescent assay (×200).</p