Rosiglitazone Suppresses the Growth and Invasiveness of SGC-7901 Gastric Cancer Cells and Angiogenesis In Vitro via PPARγ Dependent and Independent Mechanisms

Although thiazolidinediones (TZDs) were found to be ligands for peroxisome proliferators-activated receptorγ (PPARγ), the mechanism by which TZDs exert their anticancer effect remains unclear. Furthermore, the effect of TZDs on metastatic and angiogenesis potential of cancer cells is unknown. Our results in this paper show that rosiglitazone inhibited SGC-7901 gastric cancer cells growth, caused G1 cell cycle arrest and induced apoptosis in a dose-dependent manner. The effects of rosiglitazone on SGC-7901 cancer cells were completely reversed by treatment with PPARγ antagonist GW9662. Rosiglitazone inhibited SGC-7901 cell migration, invasiveness, and the expression of MMP-2 in dose-dependent manner via PPARγ-independent manner. Rosiglitazone reduced the VEGF induced angiogenesis of HUVEC in dose-dependent manner through PPARγ-dependent pathway. Moreover, rosiglitazone did not affect the expression of VEGF by SGC-7901 cells. Our results demonstrated that by PPARγ ligand, rosiglitazone inhibited growth and invasiveness of SGC-7901 gastric cancer cells and angiogenesis in vitro via PPARγ-dependent or -independent pathway

Multiwater Index Synergistic Monitoring of Typical Wetland Water Bodies in the Arid Regions of West-Central Ningxia over 30 Years

The Shapotou National Nature Reserve in the Ningxia Hui Autonomous Region is a typical arid region in China. There is an exceptionally serious problem of surface water resource conservation, and dynamic monitoring of surface water with the help of water indices can help to elucidate its change patterns and impact mechanisms. Here, we analysed the characteristics of interannual variation in surface water area in the study area from 1992–2021. The correlation coefficients of the surface water area in the previous year and the contemporaneous water bodies of the Yellow River with the total surface water area (TSWA) were calculated. The results show the following: ① In terms of the classification accuracy of the two methods, water indices and support vector machine classification, water indices are more suitable for water body extraction in the study area. In particular, the three water indices, NDWI, MNDWI and AWEIsh, were more effective, with average overall accuracies of 90.38%, 90.33% and 90.36% over the 30-year period, respectively. ② From the TSWA extraction results from the last 30 years, the TSWA showed an increasing trend with an increase of 368.28 hm2. Among the areas, Tenggeli Lake contributed the most to the increase in TSWA. ③ The highest correlation between the TSWA and the previous year’s TSWA was 0.89, indicating that the better way to protect the water body is to maintain water surface stability year-round. The surface water area of the Yellow River and TSWA also showed a strong correlation, indicating that the rational use of Yellow River water is also an important direction for the future conservation of water resources in the study area

Establishment and application of suspension static method in blood group screening of automated blood group analyzer

Abstract The accuracy of blood group identification is the basis of blood transfusion safety. In order to increase the detection rate of weak agglutination, unexpected antibodies (UAb) and blood subtypes for pre-transfusion testing, the blood group screening process of automated blood group analyzer (ABGA) is ameliorated by introducing one static step and establishing a suspension static method (SSM). One static step was introduced in the blood group screening process of ABGA and three static time conditions were designed: 300 s, 400 s and 500 s, from which the optimal static time was selected and SSM was established; By comparing the detection of weak agglutination and UAb before and after the application of SSM, the feasibility and effect of suspension static method were verified and evaluated. The last two steps of the automatic blood group screening process were replaced with static, light centrifugation and imaging. The optimal static time parameter was selected as 400 s and SSM was established; After the application of SSM, it was verified that: (1) The detection level of weak antibodies (anti-A and anti-B) and weak antigens (weak D phenotype) could be improved by SSM, including antibodies in plasma of known type O samples with 0, 2, 4, 8, 16 and 32 times serial dilutions(simulating weak anti-A and weak anti-B), weak antibodies (anti-B) in plasma of one normal A-type sample and weak antigens on red blood cells (RBC) of 5 weak D phenotype samples (weak D antigen); (2) Three blood donor samples (type A, O and B) with known UAb were detected by SSM. The results showed that SSM could detect both weak antibodies (anti-A and anti-B) and UAb; (3) SSM was applied to detect the samples of 3 A2B and 3 subtype B blood donors and the blood subtypes could be clearly detected; (4) The number of screening samples was 95,314 and 106,814 before SSM (2018) and after (2020) the application of SSM and the positive rate of UAb (63/95,314 and 187/106,814) increased after SSM, discrepancy of which was statistically significant (χ 2 = 48.42, P < 0.01). The above results demonstrate that SSM of ABGA is conducive to the detection of weak agglutination, UAb and blood subtypes in blood samples, which can improve the sensitivity of blood group detection and ensure the safety of clinical blood transfusion to a certain extent

Proteomic analysis of prolactinoma cells by immuno-laser capture microdissection combined with online two-dimensional nano-scale liquid chromatography/mass spectrometry

Abstract Background Pituitary adenomas, the third most common intracranial tumor, comprise nearly 16.7% of intracranial neoplasm and 25%-44% of pituitary adenomas are prolactinomas. Prolactinoma represents a complex heterogeneous mixture of cells including prolactin (PRL), endothelial cells, fibroblasts, and other stromal cells, making it difficult to dissect the molecular and cellular mechanisms of prolactin cells in pituitary tumorigenesis through high-throughout-omics analysis. Our newly developed immuno-laser capture microdissection (LCM) method would permit rapid and reliable procurement of prolactin cells from this heterogeneous tissue. Thus, prolactin cell specific molecular events involved in pituitary tumorigenesis and cell signaling can be approached by proteomic analysis. Results Proteins from immuno-LCM captured prolactin cells were digested; resulting peptides were separated by two dimensional-nanoscale liquid chromatography (2D-nanoLC/MS) and characterized by tandem mass spectrometry. All MS/MS spectrums were analyzed by SEQUEST against the human International Protein Index database and a specific prolactinoma proteome consisting of 2243 proteins was identified. This collection of identified proteins by far represents the largest and the most comprehensive database of proteome for prolactinoma. Category analysis of the proteome revealed a widely unbiased access to various proteins with diverse functional characteristics. Conclusions This manuscript described a more comprehensive proteomic profile of prolactinomas compared to other previous published reports. Thanks to the application of immuno-LCM combined with online two-dimensional nano-scale liquid chromatography here permitted identification of more proteins and, to our best knowledge, generated the largest prolactinoma proteome. This enlarged proteome would contribute significantly to further understanding of prolactinoma tumorigenesis which is crucial to the management of prolactinomas.</p